Kind: captions
Language: en
the following is a conversation with
Dimitri korkin he's a professor of
bioinformatics and computational biology
at WPI Worcester Polytechnic Institute
where he specializes in bioinformatics
of complex diseases computational
genomics systems biology and biomedical
data analytics I came across Dimitri's
work one in February his group used the
viral genome of the Cova 19 to
reconstruct the 3d structure of its
major viral proteins and their
interaction with the human proteins in
effect creating a structural genomics
map of the corona virus and making this
data open and available to researchers
everywhere we talked about the biology
of covert 19 SARS and viruses in general
and how computational methods can help
us understand their structure and
function in order to develop antiviral
drugs and vaccines this conversation was
recorded recently in the time of the
corona virus pandemic for everyone
feeling the medical psychological and
financial burden of this crisis
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world and now here's my conversation
with Demetri korkin do you find viruses
terrifying or fascinating when I think
about viruses I think about them I mean
I imagine them as those villains that do
their work so perfectly well that's that
is impossible not to be fascinated with
them so what do you imagine when you
think about a virus do you imagine the
individual so these hundred nanometer
particle things or do you imagine the
whole pandemic like Society level the
when you say the efficiency at which
they do their work do you think of
viruses as the millions that him and
that occupy human body or a living
organism Society level like spreading as
a pandemic or do you think of the
individual little guy yes this is I
think this is a unique a unique concept
that allows you to move from micro scale
to the macro scale all right so the
dividers itself I mean it's it's not a
living organism
it's a machine to me it's a machine but
it is perfected to the way that it
essentially has a limited number of
functions it needs to do necessary some
functions and essentially has enough
information just to do those functions
as well as the ability to modify itself
so you know it's it's a machine it's an
intelligent machine so yeah look maybe
on that point you're in danger of
reducing the power of this thing by
calling it a machine right but you now
mention that it's also possibly
intelligent it seems that there's these
elements of brilliance that a virus has
of intelligence of maximizing so many
things about its behavior in to ensure
its survival and its and its success so
do you see it as intelligent so you know
I think the it's a different
understanding differently than you know
I think about you know intelligence over
human kind or intelligence of of the of
the you know of the artificial
intelligence mechanisms
I think the intelligence of a virus is
in its simplicity
the ability to do so much with so little
material and information but also I
think it's it's interesting it keeps me
thinking you know it gives me wondering
whether or not it's also the an example
of the basic swarm intelligence where
you know essentially the viruses act as
the whole and extremely efficient in
that so what do you attribute the
incredible simplicity and the efficiency
- is it the evolutionary process - maybe
another way to ask that if you look at
the next hundred years
are you more worried about the natural
pandemics or the engineered pandemics so
how hard is it to build a virus yes it's
it's a very very interesting
question because obviously there is a
lot of conversations about the you know
whether we are capable of engineering a
you know anyone worse the virus
I personally expect in a mostly
concerned with the naturally occurring
viruses simply because we keep seeing
that we keep seeing new strains of
influenza emerging some of them becoming
pandemic we keep seeing new strains of
coronaviruses emerging this is a natural
process and I think this is why it's so
powerful you know if you ask me you know
did I've read papers about scientists
trying to study the capacity of the
modern you know by technology to alter
the viruses but I hope that that you
know it in it won't be our main concern
in the near future
do you mean by hope well you know if you
look back and look at the history of the
of the most dangerous viruses right so
that's the first thing that comes into
mind is a smallpox so right now there is
perhaps a handful of places where this
you know the the strains of this virus
are stored right so this is essentially
the effort of the whole society to limit
the access to those viruses I mean in a
lab in a controlled environment in order
to study and then smallpox is one of the
viruses for which
should be stated there's a vaccine is
developed yes yes and that's you know
it's until seventies it wasn't in my
opinion it was perhaps the most
dangerous think that was there is there
a very different virus then then the
influenza and coronaviruses it is it is
different in several aspects
biologically it's a so-called
double-stranded DNA virus but also in
the way that it is much more contagious
so they are not for so this is this is
the what are not are not is essentially
an average number as person infected by
the virus can spread to other people so
then the average number of people that
he or she can spread it to and you know
the there is still some you know
discussion about the estimates of the
current virus you know the estimations
vary between you know one point five and
three in case of smallpox it was five to
seven and we're talking about the
exponential growth right so that's
that's a very big difference it's not
the most contagious one measles for
example it's I think 15 and up so so
it's it's you know but it's definitely
definitely more contagious that that the
seasonal flu then
the current coronavirus were stars for
that matter so what makes a what makes a
virus more contagious or the I'm sure
there's a lot of variables that come
into play but is it is it that whole
discussion of aerosol and like the size
of droplets if if it's airborne or
there's some other stuff that's more
biology centered I mean there are a lot
of components and and there are
biological components that there are
also you know social components the
ability of the virus to you know the the
ways in which the virus is spread is
definitely one the ability to virus to
stay on the surfaces to survive the
ability of the virus to replicate fast
also you know once it's in the cell or
whatever once it's inside the host and
interesting enough something that I
think we didn't pay that much attention
to is the incubation period the were you
know hosts are symptomatic and now it
turns out that another thing that we one
really needs to take into account the
percentage of the asymptomatic
population because those people still
shared this virus and still are you know
they still are contagious as other than
the Iceland study which i think is
probably the most impressive size-wise
shows 50 percent asymptomatic this virus
I also recently learned the swine flu is
like just a number of people who got
infected was in the billions it was some
crazy number it was like it was like
like 20 percent of poverty percent of
population something crazy like that so
the lucky thing there is the fatality
rate is low but the fact that a virus
can just take over an entire population
so quickly
it's terrifying I think I mean this is
you know that's perhaps my favorite
example of a butterfly effect because
it's really I mean it's it's even tinier
they'd then a butterfly and look at you
know and with you know if you think
about it right so it used to be in in
those bad species and perhaps because of
you know a couple of small changes in in
the in the viral genome his first had
you know become capable of jumping from
bats to human and then it became capable
of jumping from human to human
alright so this is this is I mean it's
not even the size of a virus it's the
size of several you know several atoms
or says you know few atoms and our
sudden this change has such a major
impact so is that a mutation like on a
single virus is that like so if we talk
about those the the flap of a butterfly
wing like what's the first flap well I
think this is the the the mutations that
make that made this virus capable of
jumping from bat species to human and of
course there's you know the scientists
are still trying to find I mean they
still even trying to find the the who
was the first in fact it is the patient
zero the first human the first human
infected right I mean the fact that
there are corona viruses different
strains of corona viruses in various bat
species I mean we know that so so we you
know viola gist absurdum they studied
them they look at their and genomic
sequences they're trying of course to
understand what make this virus is to
jump from from bats to human there was
you know similar to that and in you know
in influenza that was I think a few
years ago there was this you know
interesting story where several groups
of scientists studying influenza virus
essentially you know made experiments to
show that this virus can jump from one
species to another you know by changing
I think just a couple of residues and
and and of course it was very
controversial I think there was a
moratorium on this study for a while but
then the study was released it was
published so that was their moratorium
is because it shows through engineering
it through modifying it you can make a
jump yes yeah I I personally think it is
important to study this I mean we should
be inform to should try to understand as
much as possible in order to prevent it
but so then the engineering aspect there
is can't you then just start searching
because there's so many strands of
viruses out there
can't you just search for the ones in
bats that are the deadliest from the
virologist perspective and then just try
to engineer try to see how to but see
that's a there's a nice aspect to it the
really nice thing about engineering
viruses it has the same problems nuclear
weapons is it's hard for it to not only
to mutual self-destruction so you can't
control a virus it can't be used as a
weapon right yeah that's why I you know
in the beginning I said you know I I'm
hopeful because that definitely the
definitely regulations to be needed to
be introduced and I mean as the
scientific society is we are in charge
of
you know making the right actions making
the right decisions but I think we we
will benefit tremendously by
understanding the mechanisms by which
the virus can jump by which the virus
can become more you know more more
dangerous to humans because all this
answers with you know eventually to to
designing better vaccines hopefully
Universal vaccines right and that would
be a triumph of the you know science so
what's the universe of vaccines is that
something that well how universal is
universal well I mean you know so what's
the dream I guess because you kind of
mentioned the dream of this I would be
extremely happy if you know we designed
the vaccine that is able I mean I'll
give you an example right so so every
year we do a seasonal flu shot the
reason we do it is because you know we
are in the arms race you know our
vaccines are in the arms race with with
constantly changing virus right now if
the
neck's pandemic influenza pandemic will
a cure most likely this vaccine would
not save us right although it's it's you
know it's the same virus might be
different strain so if we're able to
essentially design a vaccine against you
know influenza A virus no matter what's
the strain no matter which species did
jump from that would be I think that
would be a huge huge progress and
advancement
you mentioned the smallpox until the
seventies might have been something that
he would be worried the most about what
about these days well we're sitting here
in the middle of a cove in nineteen
pandemic but these days nevertheless
what is your biggest worry virus wise
what are you keeping your eye are on it
looks like and you know based on the
past several years of the of the new
viruses emerging I think we're still
dealing with different types of
influence I mean so so the eight seven
and nine avian flu that was that emerged
I think a couple of years ago in China I
think the the mortality rate was
incredible I mean it was you know I
think above thirty percent
you know so this is this is fuchsia I
mean luckily for us this strain was not
pandemic alright so it was jumping from
birds to human but I don't think it it
it was actually transmittable between
the humans and you know this is actually
a very interesting question
which scientists tried to understand
right so the balance the delicate
balance between the virus being very
contagious right so
efficient in spreading and virus to be
very pathogenic you know causing you
know harms you know and and that's to
their horse so it looks like that the
more pathogenic the viruses the less
contagious it is is that a property
biology or what is it was I I don't have
an answer to that
and III think this is this is still an
open question but you know if you look
at you know you know with the corona
virus for example if you look at you
know the the deadlier relative Merce
Merce was never in a pandemic virus
right but the you know did again the the
mortality rate from nurseries far above
you know I think twenty or thirty
percent so so whatever is making this
all happen doesn't want us dead because
it's balancing yeah nicely I mean how do
you explain that one not dead yet like
because there's so many viruses and
they're so good at what they do why do
they keep us alive I mean we will also
have you know a lot of protection right
so the immune system and so I mean we do
have you know ways to to fight against
those viruses and I think with the I now
weigh much better equipped right so with
the discoveries of vaccines and you know
there are vaccines against the the
viruses that maybe two hundred years ago
would wipe us out completely but because
of this vaccines we are actually we're
capable of eradicating pretty much fully
as is the case with smallpox so if we
could can we go to the basics a little
bit of
the biology of the virus how does the
virus infect the body so I think there
are some key steps that the virus needs
to perform and of course the first one
the viral particle needs to get attached
to the host cell in the case of corona
virus there is a lot of evidence that it
actually interacts in the same way of
the as the SARS coronavirus so it gets
attached to a c2 human receptor and so
there is I mean as we speak there is a
growing number of papers suggesting it
moreover a most recent I think most
recent results suggest that this virus
attaches more efficiently to this human
receptor then SARS just a sore back off
so there is a family viruses the corona
viruses and SARS whatever the heck for
that respite or wherever that stands for
so SARS actually stands for the disease
that you get is the syndrome of acute
respiratory so SARS is the first strand
and there's Merce Merce and there is yes
but people scientists actually know more
than three strains I mean so there is
the mhv
strain which is considered to be a
canonical model disease model in mice
and so there is a lot of work done on on
this virus because it's but he hasn't
jumped to humans yet no no yes it's
fascinating so any mention a c2 so the
when you say attached proteins are
involved yeah on both sides yes so so we
have you know so we have this infamous
spike protein on the surface of the
virion particle and
does look like a spike and I mean that's
essentially because of this protein you
know we called the coronavirus
coronavirus so that what makes Corona on
top of the surface so so this via this
protein it actually it acts so it
doesn't act alone it actually it makes a
three copies and it's it makes so-called
trimer so this trimer is essentially a
functional unit a single functional unit
that in starts interacting with the AC
two receptor so this is again another
protein that now sits on the surface of
a human cell host cell I would say and
that's essentially in that way the virus
anchors itself to the host cell because
then it needs to actually it needs to
get inside you know it fuses its
membrane with the host membrane it
releases the the key components it
releases its you know RNA and then
essentially hijacks the the machinery of
the cell because none of the viruses
that we know of have ribosome the the
machinery that allows us to print out
proteins so in order to print out
proteins that are necessary for
functioning of this virus it actually
needs to hijack the host ribosomes the
virus is an RNA wrapped in a bunch of
proteins one of which is this functional
mechanism with by protein that does the
attachment so yeah so you know so if you
look at this virus that there are you
know several basic components right so
we start with the Spike protein this is
not the only surface protein the the
protein that lives on the surface of the
viral particle there is also perhaps the
the protein with the highest number of
copies is the membrane protein so it's
essentially it forms the capsid sorry
the envelope of the protein of the viral
particle and essentially you know helps
to maintain a certain curvature helps to
make a certain curvature then there is a
another protein called envelope protein
or a protein and it it actually occurs
in in far less quantities and still
there is ongoing research what exactly
does this protein do so these are sort
of the three major surface proteins that
you know make the divider envelope and
when we go inside then we have another
structural protein called nuclear
protein and the the purpose of this
protein is to protect the viral RNA it
actually binds to the viral RNA creates
a capsid and so the rest of the virus
viral information is inside of this you
know RNA and you know if you compare the
amount of the genes or you know proteins
that are made of these genes it's much
you know it's significantly higher than
of influenza virus for example influenza
virus has I think around eight or nine
proteins where this one has at least 29
Wow
that has to do with the length of the
RNA strand I mean so I mean so it's it
it affects the length of the RNA strand
right so so so because you essentially
need to have sort of the minimum amount
of information to encode those genes how
many proteases you say 2909 protease yes
so this is this is you know something
definitely interesting because you know
believe it or not
we've been studying you know
coronaviruses for over two decades we've
yet to uncover all functionalities of
his proteins could we maybe take a small
tangent and can you can you say how one
would try to figure out what a function
of a particular protein is so you've
mentioned people are still trying to
figure out what the function of the
envelope protein might be or what's the
process so this is where the research
that computational scientists do might
be of help because you know in the past
several decades was that we actually
have collected a pretty decent amount of
knowledge about different proteins in
different viruses so what we can
actually try to do and this is sort of
could be sort of the our first lead to a
possible function is to see whether
those you know say we have this genome
of the corona virus other of the novel
coronavirus
and we identify the potential proteins
then in order to infer the function what
we can do can actually see whether those
proteins are similar to those ones that
we already know okay in such a way we
can you know for example clearly
identified you know some critical
components that RNA polymerase or
different types of proteases these are
the proteins that essentially clip the
protein sequences and so this works in
many cases however in some cases you
have truly novel proteins and this is a
much more difficult task now as a small
pause when you say similar like what if
some parts are different and some parts
are similar like how do you disentangle
that
you know it's it's a big question of
course you know what by informatics does
it does predictions right so those
predictions and they have to be
validated by experiments functional or
structural predictions both I mean we we
do structural predictions with the
functional predictions we do
interactions predictions things you just
generate a lot of predictions like
reasonable predictions based on
structure and function interaction like
you said and then here you go
that's the power of bioinformatics is
data grounded good predictions of what
should happen so we you know in the way
I see it we're helping experimental
scientists to streamline the discovery
process yeah and the experimental
scientists is that what a virologist is
solely about virology is one of the
experimental sciences that you know
focus on viruses they often work with
other experimental scientists for
example the molecular imaging scientists
right so the the viruses often can be
viewed and reconstructed through
electron microscopy techniques so but
these are you know specialists that are
not necessarily by biologists they've
worked with small small particles more
by whether it's viruses or is it an
organelle of a you know of a human cell
whether it's a you know complex
molecular machinery so the techniques
that are use are very similar in in
surfing in its in their essence and so
yeah so so typically me and in we see it
now the research on you know that is
emerging and that
is needed often involves the
collaborations between biologists you
know
biochemist you know people from from
pharmaceutical sciences computational
sciences so we have to work together so
from my perspective is to step back
sometimes I look at this stuff it's the
how much we understand about RNA DNA how
much we understand about protein like
your work the amount of proteins that
you're exploring is it surprising to you
that we were able we descendants of apes
were able to figure all of this out like
how so your computer scientists so for
me from computer science perspective I I
know how to write a Python program
things are clear but biology is a giant
mess it feels like to me from an
outsider's perspective is how surprising
is it amazing is it that we were able to
figure this stuff out you know if you
look at the you know how computational
science and computer science was
evolving right I think it was just a
matter of time that we would approach
biology so so we we started from you
know applications to much more
fundamental systems physics you know and
now we are or you know small chemical
compounds right so now we are
approaching the more complex biological
systems and I think it's a natural
evolution of you know of the computer
science of mathematics sure that's the
computer science I just might even in in
higher level so that to me surprising
that computer science can offer help in
this messy world but I just mean it's
incredible that the biologists and the
chemists can figure all this out or is
it you sound ridiculous to you that
that of course they would it just seems
like a very complicated set of problems
like the the variety of the kinds of
things that could be produced in the
body the just just like you said 20 and
I approach I mean just getting a hand of
in a hang of it so quickly it just seems
impossible to me I agree I mean it's and
I have to say we are you know in the
very very beginning of this journey I
mean we we've yet to I mean we've yet to
comprehend not even try to understand
and figure out all the details but we've
yet to comprehend the complexity of the
cell we know that neuroscience is not
even at the beginning of understanding
human mind
so where's biology said in terms of
understanding the function deeply
understanding the function of viruses
and cells so there sometimes it's easy
to say when you talk about function what
you really refer to it's perhaps not a
deep understanding but more of a
understanding sufficient to be able to
mess with it using a antiviral like mess
with it chemically to prevent some of
its function or do you understand the
function well I think equally I think
we're much farther in terms of
understanding of the complex genetic
disorders such as cancer where you have
layers of complexity and we you know as
in my laboratory we're trying to
contribute to that research but we're
also in a way overwhelmed with how many
different layers of complexity different
layers of mechanisms that can be
hijacked by cancer simultaneously and so
you know I think biology in the past 20
years again from the perspective of the
outsider because I'm not a biologist but
I think it has advanced tremendously
and one thing that we're computational
scientists and data scientists are now
becoming very very helpful is in the
fact it's kind of from the fact that we
are now able to generate a lot of
information about the cell whether it's
next-generation sequencing or
transcriptomics whether it's life
imaging information where it is you know
complex interactions between proteins or
between proteins and small molecules
such as drugs we we are becoming very
efficient in generating this information
and now the next step is to become
equally efficient in processing this
information and extracting the the key
knowledge from that they could then be
validated with the experiment yeah yeah
so maybe then going all the way back
we're talking you said the first step is
seeing if we can match the new proteins
you found in the virus against something
we've seen before to figure out its
function and then you also mentioned
that but there could be cases where it's
a totally new protein is there something
biron firm addicts can offer when it's a
totally new protein this is where many
of the methods and you probably are
aware of you know the the case of
machine learning many of these methods
rely on the previous knowledge right so
things that where we try to do from
scratch are incredibly difficult you
know something that we call a Benicia
and this is I mean it's not just the
function I mean you know we've yet to
have a robust method to predict the
structures of these proteins in a
Benicia you know by not using any
templates
of other related proteins so protein is
a chain of amino acids residues as
residues yeah and then however somehow
magically maybe you can tell me they
seem to fold in incredibly weird and
complicated 3d shapes yes so and that's
where actually the idea of protein
folding or just not the idea but the
problem of figuring out how the hell it
wants up the concept how they fold into
those weird shapes comes in so that's
another side of computational work so
what can you describe what protein
folding from the computational side is
and maybe your thoughts on the folding
at home efforts that a lot of people
know they you can use your machine to to
do protein folding
so yeah broad protein folding is you
know one of that those 1 million dollar
price challenges right so the reason for
that is we've yet to understand
precisely how the protein gets folded so
efficiently to the point that in many
cases where you you know where you try
to unfold it due to the high temperature
it actually folds back into its original
state right so we know a lot about the
mechanisms right but put putting those
mechanisms together and making sense
it's a computationally very expensive
task in general the proteins fold can
they fold in arbitrary large number of
ways it is they usually fold in a very
small number no it's it's typically I
mean you we tend to think that you know
there is a one sort of canonical fold
for protein although that there are many
cases where the proteins you know upon
the stabilization it can be folded into
a different conformation
and this is especially true when you
look at sort of proteins that in that
include more than one structural unions
so those structural unions we call them
protein domains essentially protein
domain is a single unit that typically
is evolutionary preserved that typically
carries out the single function and
typically has a very distinct fault
structure 3d structure organization but
turns out that if you look at human an
average protein in a human cell would
have to a bit of two or three such
subunit and how they are trying to fold
into the sort of you know next level
fold right
so within subunit is folding and then
and then they fold into the larger 3d
structure right and and all that there's
some wonder saying the basic mechanisms
but not to put together to be able to
fold it we're still I mean we're still
struggling I mean we're we're getting
pretty good about folding relatively
small proteins up to hundred residues
which I mean but we're still far away
from folding you know larger proteins
and some of them are notoriously
difficult for example transmembrane
proteins proteins that that sit in the
in the membranes of the cell they're
incredibly important but they are
incredibly difficult to solve and so
basically there's a lot of degrees of
freedom how it folds and so it's a
combinatorial problem or just explodes
there's so many dimensions Hey well it
is a combinatorial problem but it
doesn't mean that we cannot approach it
from the non canal not from the boot for
a force approach and so the machine
learning approaches you know have been
emerged that try to tackle it so folding
at home
I don't know how familiar with it but is
that used machine learning or is it more
brute force no so folding at home it was
originally and I remember I was a it was
a long time ago I was a postdoc and we
we learned about this you know this game
because it was originally designed as
the game and we you know I took a look
at it and it's interesting because it's
it's really you know it's very
transparent very intuitive so and from
what I heard a via to introduce it to my
son but you know kids are actually
getting very good at folding the
proteins and it was you know it came to
me as they as the not as a surprise but
actually as the sort of manifest of you
know our capacity to do this kind of to
solve these kind of problems when a
paper was published published in one of
these top journals with the coasters
been the actual players of this game so
and what happened is was that they
managed to get better structures than
the scientists themselves so so that you
know that was very I mean it was kind of
profound you know revelation that
problems that are so challenging for a
computational science maybe not that
challenging for a human brain well
that's a really good that's a hopeful
message always when there's a the proof
of existence the existence proof that
it's possible that's really interesting
but the it seems what are the best ways
to do protein folding now so if you look
at what deep mind does with alpha fall
alpha fold yes so they kind of is that's
a learning approach what's your sense I
mean your backgrounds in machine
learning but is this a learnable problem
is this still a brute-force away in the
garry kasparov deep blue days are we in
the alphago playing the game of go days
of folding well I think we are we are
advancing towards this direction I mean
if you look so there is a sort of
olympic game for protein folders called
CASP and it's essentially it's you know
it's a competition where different teams
are given exactly the same protein
sequences and they try to predict their
structures right and of course there's
different sort of subtasks but in the
recent competition half a fault was
among the top performing teams if not
the top performing team so there is
definitely a benefit from the data that
had been generated you know in the past
several decades the structural data and
certainly you know we are now at the
capacity to summarize this data to
generalize this data and to use those
principles you know in order to predict
protein structures as one of the really
cool things here is there's maybe you
can comment on it there seems to be
these open datasets of protein how did
that with the protein databank
the a protein databank I mean as create
is this a recent thing for just the
corona virus or it's it's been for many
many years I believe the first protein
databank was designed on flash cards so
on the so yes it's so this I mean this
is a great example of the community
efforts
of everyone contributing cause every
time you solve a protein or a protein
complex this is where you submit it and
you know the scientists get access to it
scientists get to test it and we went
from occasions use this information to
you know to make predictions so there's
no there's no culture like hoarding
discoveries here so that's I mean you've
you've you've released a few or a bunch
of proteins they were matching its
whatever we'll talk about details a
little bit but it's kind of amazing that
that's the the it's kind of amazing how
open the culture here is it is and I
think this pandemic actually
demonstrated the ability of scientific
community to you know to solve this
challenge collaboratively and this is I
think it if anything it actually moved
us to a brand new level of
collaborations of the efficiency in
which people establish new
collaborations in in which people offer
their help to each other scientists
offer their help to each other and
publish results to it's very interesting
we're now trying to figure out as a few
journals that are trying to sort of do
the very accelerated review cycle but so
many preprints so just hosting a paper
going out
I think it's fundamentally changing the
the way we think about papers yes I mean
the way we think about knowledge now
let's say no yes because yes I
completely agree I think now it's the
knowledge
is becoming sort of the the core value
not the paper or the journal where this
knowledge is published and I think this
is again this is we are living in the in
the times where it becomes really
crystallized that the idea that the most
important value is in the knowledge so
maybe you can comment like what do you
think the future of that knowledge
sharing looks like so you have this
paper that will I hope you get a chance
to talk about a little bit but it has
like a really nice abstract and the
introduction and related like it has all
the usual I mean probably took a long
time to put together so but is that
going to remain like you could have
communicated a lot of fundamental ideas
here in much shorter amount that's less
traditionally acceptable by the journal
context so so well you know so the first
version that we posted not even on a bi
archive because by archive back then it
was essentially you know overwhelmed
with the number of submissions so so our
submission I think it took five or six
days to just for it to be screened and
and and put online so we you know
essentially we put the first pre pre n't
on our website and you know it was
started getting accessed right away so
and and you know so this original
preprint was in a much rougher shape
than this paper and but we tried I mean
we honestly try to be as compact as
possible with you know
introducing the the information that is
necessary that to explain our you know
our results so maybe you can dive right
in if it's okay sure so it's a paper
called structured
of Tsarskoe how do you even pronounce
our scurvy - Co V - yeah by The Cove it
is such a terrible name but it stuck
and yes Tsarskoe V - indicates
evolutionary conserved functional
regions of viral proteins so this is
looking at all kinds of proteins that
are part of the this novel coronavirus
and how they match up against the
previous other kinds of corona viruses
and there's a lot of beautiful figures I
was wondering if you could I mean
there's so many questions I could ask
her but maybe a tough how do you get
started at doing this paper so how do
you start to figure out the 3d structure
of a novel virus yes so there is
actually a little story behind it and so
the story actually dated back in
September of 2019 and you probably
remember that back then we had another
dangerous virus Triple E virus its
eastern equine encephalitis virus and
can you maybe linger in it I have to
admit I was sadly completely unaware so
so that was actually a virus outbreak
that happened in New England only the
the danger in this virus was that it
actually it targeted your brain so so
the word deaths from this virus it was
it was transferred you know transfer the
main vector was mosquitoes and obviously
full-time is you know the time where you
have a lot of them in New England and
you know on one hand people realize this
is this is this actually very dangerous
thing so it had an impact on the local
economy the schools were closed past six
o'clock no activities outside for the
kids because the kids were suffering
quite tremendously from you know what
infected from this virus and how do I
not know about this was impacted it was
in the news I mean it was not impacted
to to high degree in in Boston
necessarily but in the Metro West area
and actually spread around I think all
the way to New Hampshire Connecticut and
you mentioned affecting the brain that's
one other comment
we should make so you mentioned a AC two
for the corona virus so these viruses
kind of attach to something in the body
so it essentially attaches to the to
these proteins in those cells in the
body where those proteins are expressed
where they actually have them in in
abundance so sometimes that could be in
the lungs that could be a brain that
could be so I think what they right now
from what I read they have the
epithelial cells inside in so did the
cells essentially inside the you know
the it's the cells that are covering the
surface you know so inside the nasal
surfaces the this road the lung cells
and I believe liver as a couple of other
organs where they are actually
expressing in abundance that's for the
AC tuition for 318 two percenters okay
so back back to the story yes in the
fall so now the these you know the
impact of this virus is significant
however it's a pre local problem to the
point that you know this something that
we would call a neglected disease
because it's not big enough to make you
know the the drug design companies to
design a new antiviral or in York seen
it's not big enough to generate a lot of
grants from the nation of finding
agencies so so does it mean we cannot do
anything about it and so what I did is I
taught a by informatics class and is in
Worcester Polytechnic Institute and we
are very much problem learning
institution so I thought that that would
be a perfect you know perfect project in
case study so so I asked it you know so
so I we essentially designed a study
where we tried to use by informatics to
to understand as much as possible about
this virus and a very substantial
portion of the study was to understand
the structures of the proteins to
understand how they interact with with
each other and with the with the host
proteins try to understand the evolution
of this virus
it's obviously you know a very important
question how where it will evolve
further how you know how it happened
here you know so so we did all this you
know
projects and now I'm trying to put them
into a paper where all these
undergraduate students will be coasters
but essentially the projects were
finished right about mid-december and a
couple of weeks later I heard about this
mysterious new virus that was discovered
in you know was reported in in Wuhan
province and immediately I thought that
well we just did that can't we do the
same thing with this virus and so we
started waiting for the genome to be
released because that's essentially the
first piece of information that is
critical once you have the genome
sequence you can
doing a lot using my informatics when
you see genome sequence that's referring
to the sequence of letters that make up
the RNA so the sequence that make up the
entire information encoded in the
protein right so so that includes all 29
genes
what are genes what's the encoding of
information sosigenes is essentially is
a basic functional unit that we can
consider so so each gene in the virus
would correspond to a protein that so
gene by itself doesn't do it function it
needs to be converted or translated into
the protein that will become the actual
functional unit like you said the
printer so so we need the printer for
that we need to print it okay so the the
first step is to figure out that the
genome the sequence of things that to be
then used for printing the protein so
okay so then then the next step so once
we have this and so we use the existing
information about Sarkis the Czar's
genomics has been done in abundance so
we have different strains of SARS and
actually other related coronaviruses
MERS the bat coronavirus and we started
by identifying the potential genes
because right now it's just the sequence
right it's a sequence that is roughly
it's less than 30,000 nucleotide long
and this the raw sequence it's a rose
ignore the information really and we now
need to define the boundaries of the
genes
that would then be used to identify the
proteins and protein structures how hard
is that problem it's not I mean it's
pretty straightforward
so you know so because we use the
existing information about SARS proteins
and SARS genes
so once again we kind of we are relying
on the yes so and then once we get there
this is where sort of the first more
traditional bind phonetic steps step
begins we are trying to use these
protein sequences and get the 3d
information about those proteins so this
is where we are relying heavily on the
structure information specifically from
the protein data bank that we are
talking about and here you're looking
for similar proteins yes so so the the
concept that we are operating when we do
this kind of modeling it's called
homology or template based modeling so
essentially using the concept that if
you have two sequences that are similar
in terms of the letters the structures
of these sequences are expected to be
similar as well and this is at the micro
at a very local scale and at the scale
of the whole protein at the whole
protein I saw actually so you know so of
course the devil is any details and this
is why we need actually pre
sophisticated modeling tools to do so
once we get these structures of the
individual proteins we try to see
whether or not this proteins act alone
or they have to be forming protein
complexes in order to perform this
function and again so this is sort of
the next level of the modeling because
now you need to understand how proteins
interact and it could be the case that
the protein interacts with itself and
makes sort of a multi marek complex the
same protein just repeated multiple
times and we have quite quite a few such
proteins in Tsarskoe v2 specifically
spike protein needs three copies to
function and load protein needs five
copies to function and there are some
other multimeric complexes that we mean
by interacted with itself and you see
multiple copy so how do you how do you
make a good guess whether something's
going to interact well again so there
are two approaches right so one is look
at the previously solved complexes now
we're looking not at the individual
structures but the structures of the
whole complex complex is upon multiple
proteins yes so it's a bunch of proteins
essentially glued together and and when
you say glued that's the interaction
that's the interaction so so the
different forces different sort of
physical forces behind this as I
certainly keep asking dumb questions but
is it is the glue is that the
interaction fundamentally structural or
is it functional like in the way you're
thinking about it that's actually a very
good way to ask this question because
turns out that the interaction is
structural but in the way it forms this
truck
it actually also carries out the
function so interaction is often needed
to carry out very specific function or
protein but in terms of an earth-sized
figuring out you're really starting at
the structure before you figure out the
function so there's a beautiful figure
two in the paper of all the different
proteins that make up the able to figure
out the makeup the the new the novel
current virus what what are we looking
at right so these are like that's this
through the the step to the mentioned
when you try to guess at the possible
proteins that's what you're going to get
is these blue blue cyan blobs yes so
those are the individual proteins for
which we have at least some information
from the previous studies right so there
is advantage and disadvantage of using
previous studies the biggest well the
disadvantage is that you know we may not
necessarily have the coverage of all 29
proteins however the biggest advantage
is that the accuracy in which we can
model these proteins is very high much
higher compared to a Benicia methods
that do not use any template information
so but nevertheless this figure also has
incision beautiful and I love these
pictures so much you've as it has like
the pink parts yes there are the parts
that are different so you're
highlighting so the difference you find
is on the 2d sequence and then you try
to infer what I would look like on the
3d yeah so the difference actually is on
1d sequence one d1 design idea so and
and so this is one of these first
questions that we try to answer is that
well if you take this new virus and you
take
the closest relatives which are SARS and
a couple of bad coronavirus strains they
are already the closest relatives that
we are aware of now what are the
difference between this virus and its
close relatives right and what if you
look DIPA Klee when you take a sequence
those differences could be quite far
away from each other so what make what
3d structure makes those difference to
do they very often they tend to cluster
together interesting and over sudden the
differences that may look completely
unrelated actually relate to each other
and sometimes they are there because
they correspond they attack the
functional side right so they are there
because this is the functional side that
is highly mutated so that's a
computational approach to figuring
something out when when it comes
together like that that's kind of a nice
clean indication that there's something
this could be actually indicative of
what's what's happening yes I mean so we
need this information and you know 3d
the 3d structure gives us just a very
intuitive way to look at this
information and then start to ask you
know start asking questions such as so
this place of this protein that is
highly mutated does it does it is it the
functional part of the protein so does
this part of the protein interact with
some other protein so maybe with some
other ligands small small molecules
right so we would try now to
functionally inform this 3d structure
so so you have a bunch of these mutated
parts is like I don't know how like how
many are there in the new novel
coronavirus being compared it's ours oh
we're talking about hundreds of
thousands like these these pink region
all know did much less than that and
it's very interesting that if you look
at that you know so the first thing that
you you start seeing right you know you
look at patterns right and the first
pattern that becomes obvious is that
some of the proteins in the new
coronavirus are pretty much intact right
so they're pretty much exactly the same
as SARS as the bat coronavirus
where some others are heavily mutated so
so it looks like that the you know the
evolution is not is not a curing you
know uniformly across the entire you
know viral genome but actually target
very specific proteins what do you do
with that like from the Sherlock Holmes
perspective well you know so one of the
of the most interesting findings we had
was the fact that the viral so the the
binding sites on the viral surfaces that
get targeted by the known small
molecules the world pretty much not
affected at all and so that means that
the same small drugs or small small drug
like compounds can be efficient for the
new current a virus
this all actually maps to the drug
compounds - like so so you're actually
mapping out what old stuff is gonna work
on this thing and then possibilities for
new stuff to work by mapping out the
things I've mutated yes so so we
essentially know which parts is in
behave differently and which parts are
likely to behave similar and again you
know of course all our predictions need
to be validated by experiments but
hopefully that sort of helps us to
delineate the regions of this virus that
you know can be promising in terms of
the drug discovery you kind of you kind
of mentioned this already but maybe you
can elaborate so how different from this
structural and functional perspective
does the new corona virus appear to be
relative to SARS we now are trying to
understand the overall structural
characteristics of this virus because I
mean that's that's our next step trying
to model the viral particle of a single
viral particle of this virus so that
means you have the individual proteins
you think you said you have to figure
out what their interaction is as you
have this is that where this graph kind
of interact on so so internet so so the
interactome at the site is essentially a
so our prediction on the potential
interactions some of them that we
already deciphered from the structural
knowledge but some of them that
essentially are deciphered from the
knowledge of the existing interactions
that people previously obtained for SARS
for MERS or other related viruses so is
there kind of interact ohms am i
pronouncing that correctly weather
interaction yeah are those already
converged towards for SARS for so do I
think there is there are a couple of
papers that now investigate the sort of
the large-scale set of sets of
interactions between the new czars and
its hosts and so I think that's that's
an ongoing study I think and the success
of that the result would be an interact
on yes
and so when you say not trying to figure
out the entire the article the entire
wrinkle right so if you look you know so
structure right so what this viral
particle looks like right so as I said
it's it's you know the surface of it is
an envelope which is essentially a
so-called lipid bilayer with proteins
integrated into the surface so how so so
an average particle is around 18
nanometers right so this particle can
have about 5,200 spike proteins so at
least we suspect it and you know based
on the
micrographs images it's very comparable
to m hv virus in mice and SARS virus
micrographs are actual pictures of the
actual virus okay so these are models
this is that at least so they did actual
meat images right what do they sorry for
the tangents but what are these things
so when you look on the internet the
models and the pictures are in pen and
the models you have here just gorgeous
and beautiful when you actually take
pictures of them or the micrograph like
what what do we look well
they typically are not perfect it's also
the most of the images that you see now
is the is the sphere with those spikes
you actually see bikes yes yes you do
see the spikes and now you know the our
collaborators for Texas and I am
Benjamin Moomin he actually in the
recent paper about SARS he proposed and
there is some actually evidence behind
it that the particle is not a sphere but
is actually is elongated ellipsoid like
particles so so that's what we are
trying to incorporate into our model and
the reaiiy mean you know if you look at
the actual micrographs you see that
those particles are you know are not
symmetric so there's some of them and of
course you know it could be due to the
treatment of the of the material it
could be due to the some noise in the
imaging so there's a lot of uncertainty
so it's okay so structurally figuring
out the entire part by the way again
sorry for the tangents but why the term
particle or is it just it's it's a
single you know so we could you know we
call it the virion so very unparticle
it's essentially a single virus single
virus but just feels like this particle
to me from the physics perspective feels
like this the most basic unit because
there seems to be so much going on
inside the virus yeah it doesn't feel
like a particle - yes well yeah it's
probably I think it's the the you know
variant is is a good way to call it so
okay so trying to figure out trying to
figure out the entirety of the system
yes so you know so you know so this is
so severe ian has 5,200 spikes a trimer
spikes it has roughly 200 to 400
membrane protein dimers and those are
arranged in there very nice lattice so
you can actually see sort of the it's
it's like a
it's a carpet of on the surface again
exactly on the surface and occasionally
you also see this envelope protein
inside and some of the one we don't know
what it does actually exactly the one
that that forms the pentamer this very
nice pentameric ring and so you know so
this is what we're trying to you know
we're trying to put now all our
knowledge together and see whether we
can actually generate this overall
variant model with an idea to understand
you know well first of all to understand
how how it looks like how far it is from
those images that were generated but I
mean the implications are you know there
is a potential for the you know
nanoparticle design that will mimic this
variant particle is the process of
nanoparticle design meaning artificially
designing something that looks similar
yes you know so the one that can
potentially compete with the actual
variant particles and therefore reduce
the effect of the infection so is this
the idea of like what is a vaccine so
vaccine vaccine so so that yes so there
are two ways of essentially treating and
in the case of vaccine is preventing the
infection so vaccine is you know a way
to train our immune system so our immune
system becomes aware of this new danger
and therefore is capable of generating
the antibodies then we'll essentially
bind to the spike proteins because
that's the main target for the end of
for the vaccines design and block its
found
if you have the spike with the antibody
on top and can no longer interact with a
co2 receptor so the the process of
designing vaccine and is you have to
understand enough about the structure
the virus itself to be able to create an
artificial our official particle well I
mean so so so the nanoparticle is is a
very exciting and new research so there
are already established ways to you know
to make vaccines and several different
ones right so so there is one where
essentially the the virus gets through
the cell culture multiple times so it
becomes essentially account you know
adjusted to the to the specific
embryonic cell and as a result become
becomes less I you know compatible with
the you know host human cells so
therefore it's sort of the idea of the
life vaccine where the particles are
there but they are not so efficient you
know so they cannot replicate you know
as rapidly as you know before the
vaccine and that they can be introduced
to the immune system the immune system
will learn and the person who gets this
vaccine one won't get you know sick or
you know will have mild you know mild
symptoms so then there is sort of
different types of the way to introduce
the non-functional non-functional part
of this virus or the virus where some of
the information is stripped down for
example device with no genetic material
so so we ignore our age you know exactly
so you cannot replicate it cannot
essentially perform most of its
functions that saying well what is the
big
hurtle to design one of these to arrive
one of these is it the work that you're
doing in the fundamental understanding
of this new virus or is it in the from
our perspective a complicated world of
experimental validation and sort of
showing that this like going through the
whole process of showing this is
actually gonna work with FDA approval
all that kind of stuff I think it's both
I mean you know our understanding of the
molecular mechanisms will allow us to
you know to design to have more
efficient designs of the vaccines
however they once you design the vaccine
it it needs to be tested but when you
look at the 18 months and the different
projections which seems like an
exceptionally from historically speaking
maybe you can correct me but it's even
18 months seems like a very accelerated
timeline it is it is I mean I remember
reading about the you know in a book
about some previous vaccines that it
could take up to 10 years to design and
you know properly test a vaccine before
its mass production so yeah we you know
everything is accelerated these days I
mean for better for worse but but you
know we we definitely need that well
especially the corner virus and in the
scientific community is really stepping
up and working together the
collaborative aspect is really
interesting you mentioned so the vaccine
is one and then there's antivirals
antiviral drugs so antiviral drugs so
we're you know vaccines are typically
needed to prevent the infection right
but once you have an infection one you
know so what we try to do try to stop it
so we try to stop virus from functioning
and so the antiviral drugs are designed
to block some critical function of the
of the proteins from the viral from the
virus so there are a number of
interesting candidates and I think you
know if you
ask me I you know I think remedy severe
is perhaps the most promising it's it
has been shown to be you know an
efficient and effective antiviral for
SARS originally it was the the antiviral
drug developed for completely different
virus I think for a ball and bar Marburg
and high level you know how it works so
it tries to mimic one of the nucleotides
in RNA and essentially that that stops
the replication from so messes I guess
that's what so anywhere all drugs mess
some aspect of this yes process so you
know so essentially we try to stop
certain functions of the virus there are
some other ones you know that are
designed to inhibit the protease the the
thing that clips protein sequences there
is one that was originally designed for
malaria which is a bacterial you know
bacterial disease so this is so cool so
but that's exactly where your work steps
in is you're figuring out the functional
then the structure these different so
like providing candidates for where
drugs can plug in exactly well yes
because you know one thing that we don't
know is whether or not so let's say we
have a perfect drug candidate that is
efficient against SARS and again Smurfs
now is it going to be efficient against
New South Korea too we don't know that
and there are multiple aspects that can
affect this efficiency so for instance
if the the binding site so the the part
of the protein where this ligand gets
attached if this site is mutated then
the ligand may not be attachable to this
part any longer and you know our work
and the work of other by informatics
groups you know essentially are trying
to understand whether or not that will
be the case or and it looks like for for
the ligands that we looked at the ligand
binding sites are pretty much intact
which is very promising so if we can
just like zoom out for a second
what are you optimistic so this - well
there's three possible ends - the corona
virus pandemic so one is there's or
drugs or vaccines get figured out very
quickly probably drugs first the other
is the the the pandemic runs its course
for this wave at least and then the the
third is you know things go much worse
and some in some dark bad very bad
direction do you see let's focus on the
first two do you see the anti-drugs of
the work you're doing being relevant for
us right now in stopping the pandemic or
do you hope that the pandemic will run
its course
so the social distancing things like
wearing masks all those discussions that
we're having will be the the method with
which we fight coronavirus in the short
term or do you think that it'll have to
be antiviral drugs I think I think
antivirals would be I would view that as
the at least the short term solution I
see more and more cases in
news of those new drug candidates been
administered in hospitals and I mean
this is right now the best what we have
but do we need it to reopen the economy
I mean we definitely need it i i cannot
sort of speculate on how that will
affect reopening of the economy because
we are you know we are kind of deep in
into the pandemic and it's not just the
the states it's also you know worldwide
you know of course you know there is
also the possibility of the second wave
as we you know as you mentioned and this
is why you know we need to be super
careful we need to follow all the
precautions that the doctors tell us to
do are you worried about the mutation
the virus so it's of course a real
possibility now how to what extent this
virus can mutate it's an open question I
mean we know that it is able to mutate
to jump from one species to another and
to to become transmissible between
humans right so will it you know so
let's imagine that we have the new
antiviral will this virus become
eventually resistant to this antiviral
we don't know I mean this is what needs
to be studied this is such a beautiful
and terrifying process that a virus some
viruses may be able to mutate to respond
to the mutate around the thing we've put
before it can you explain that process
like how does that happen
just is that just the way of evolution I
would say so yes I mean it's it's the
evolutionary mechanisms there is nothing
imprinted into this virus that makes it
you know it just the way it it walls and
actually it's the way it Cory walls with
its host it's just amazing it's
especially the evolution mechanism is
especially amazing given how simple the
virus is it's incredible that it's I
mean it's beautiful
it's beautiful because it's the one of
the cleanest examples of evolution
working well I think I mean the one of
the sort of the reasons for its
simplicity is because it does not
require all the necessary functions to
be stored right so it actually can
hijack they may the majority of the
necessary function from the host cell
and it's so so so so the ability to do
so in my view reduces the complexity of
this machine drastically although if you
look at the you know most recent
discoveries right so the scientists
discovered viruses that are as large as
bacteria right so this mini viruses and
Mama viruses it actually those
discoveries made scientists to
reconsider the origins of the virus you
know and what are the mechanisms and how
you know what are the mechanisms the
evolution mechanisms that leads to the
appearance of the viruses by the way I
mean you did mention that viruses are I
think you mentioned that they're now
living yes they are not living organisms
so let me ask that questioning and why
do you think they're not living
organisms well because they they are
dependent
the majority of the functions of the
virus are dependent on the on the host
so let me do the devil's advocate let me
be the philosophical that was advocate
here and say while humans which we would
say our living need our host planet to
survive so you can basically take every
living organism that we think of as
definitively living it's always going to
have some aspects of it this host that
it needs of its environment so is that
really the key aspect of why a virus is
that dependence because it seems to be
very good at doing so many things that
we consider to be intelligent it's just
that dependence part well I mean it yeah
it's it's difficult to answer in this
way I mean I the way I think about the
virus is you know in order for it to
function it needs to have the critical
component the critical tools that it
doesn't have so I mean that's that's you
know in my way you know the it's not
autonomous I sense and that that's how I
separate the the idea of the living work
is on a very high level yes between the
living organism and and you have some no
we have I mean this is just terms and
perhaps they don't mean much but we have
some kind of sense of what autonomous
means and that humans are autonomous
you've also done excellent work in the
epidemiological modeling the simulation
of these things so the zooming out
outside of the body
during the aging based simulation so
that's where you actually simulate
individual human beings and then the
spread of viruses from one to the other
how does at a high level agent-based
simulation work all right so it's it's
also one of this I irony of timing
because I mean way we we've worked on
this project for the past five years and
the New Year's Eve I got an email from
my Fiji student that you know the last
experiments were completed and you know
the three weeks after that we get we get
this diamond princess story and emailing
each other with the same you know the
same news saying okay so the damn place
is a cruise ship yes and what was the
project that you working so I project I
mean it's you know the codename it
started with the bunch of undergrad use
the code name was zombies on a cruise
ship so they they wanted to essentially
model the the you know zombie apocalypse
apocalypses on a cruise ship and and you
know after having you know some fun we
then thought about the fact that you
know if you look at the cruise ships I
mean the infectious outbreak is has been
one of the biggest threat you know
threats to the cruise ship economy so
perhaps the most you know frequently
occurring via is the normal choirs and
this is essentially one of this stomach
flus that you have and you know it it
can be quite devastating you know so
there are occasionally there are cruise
ships get you know they get canceled
they get returned to the back to the to
the origin
and so we wanted to study and this is
very different from the traditional
epidemiological studies where this scale
is much larger so we wanted to study
this in a confined environment which is
a cruise ship it could be a school it
could be other you know other places
such as you know these large large
company where people are in interaction
and the benefit of this model is we can
actually track that in the real time so
we can actually see the whole course of
the evolution or the whole course of the
interaction between the infected pass
infected horse and you know the host and
the pathogen etcetera so so agent based
system multi-agent system to be
precisely is a good way to approach this
problem because we can introduce the
behavior of the of the passengers of the
cruise and what we did for the first
time that's where you know we introduced
um knology is we introduced a pathogen
agent explicitly so that allowed us to
essentially model the behavior on the
host site as well on the pathogen site
and over sudden weekends we can have a
flexible model that allows us to
integrate all the key parameters about
the infections so for example the virus
right so the ways of of transmitting the
virus between the the horse
how long does virus survive on the
surface for might what is you know how
much of the viral particles does a host
shed when he or she is asymptomatic
versus symptomatic you can encode all of
that into this pattern just for people
who don't know so agent-based simulation
usually the agent represents a single
human being and then there's some graphs
like contact graphs that represent the
interaction between those human being so
yes so we so essentially is you know
social agents are you know individual
programs that are run in parallel and
we're saying we can provide instructions
for these agents how to interact with
each other how to exchange information
in this case exchange the infection but
in this case in your case you've added a
pathogen as an Asian I mean that's kind
of fascinating it's a it's kind of a
brilliant simple like a brilliant way to
condense the parameters to aggregate to
bring the parameters together that
represent them in the pathogen the virus
yes that's fascinating
actually so yeah it was a you know we
realized that you know by bringing in
the virus we can actually start modeling
I mean we were not no longer bounded by
very specific sort of aspects of the
specific virus so we end up we started
with you know Norwalk virus and of
course zombies but we continued to
modeling Ebola virus outbreak flu SARS
and because I felt that we need to add a
little bit more
of excitement for our undergraduate
students so we actually modeled the
virus from the contagion movie yes
so MeV won and you know unfortunately
that virus and we we try to extract as
much information luckily the this movie
was the scientific consultant was Ian
Lipkin a virologist from Columbia
University who is actually who provided
I think he designed this virus for this
movie based on Nipah virus and I think
with some ideas behind source of flu
like airborne viruses and you know the
it the movie surprisingly contained
enough details for us to extract and to
model it I was hoping you'd like publish
a paper of how this virus works
yeah we're planning to publish I would
love it if you guys will be nice if the
you know of the origin of the virus but
you're now actually being a scientist
and studying the virus from that
perspective but the origin of the virus
you do you know you know the first time
actually so this movie is assignment
number one in my band families class
that they give because it it also tell
it tells you that you know by
informatics can be of use because if if
I don't know you watch the have you
watched it a long time so so there is
you know approximately a week from the
you know virus detection we see a
screenshot of scientists looking at the
structure of the surface protein and
this is where I tell my students that
you know if you ask experimental
biologists they will tell you that it's
impossible because it takes months maybe
years to get the crystal structure of
this you know the structure that is
represented if you ask you buy from a
Titian they tell you
why not just get it modeled and and yes
but it was very interesting to to see
that there is actually you know and if
you do it do screenshots you actually
see they feel a genetic tree is the
evolutionary tree that relate this virus
with other viruses so it was a lot of
scientific thought put into the movie
and one thing that I was actually you
know it was interesting to to learn is
that the origin of this virus was a
there were two animals that led to the
you know the the the you know the
zoonotic original dis virus were fruit
bat and as a peak so you know so so this
is this doesn't feel like well this this
definite views like we're living in a
simulation okay but maybe a big picture
agent-based simulation now larger scale
sort of not focused on a cruise ship a
larger scale are used now to drive some
policy so politicians use them to tell
stories and narratives and try to figure
out how how to move forward and there's
so much so much uncertainty but in your
sons are agent-based simulation useful
for actually predicting the future or
are they useful mostly for comparing
relative comparison of different
intervention methods well I think both
because you know in the case of new
coronavirus we essentially learning that
the current intervention methods may not
be efficient enough one thing that one
important aspect that I find to be so
critical and yet something that
was over looked you know during the past
pandemics is the effect of the
symptomatic period this virus is
different because it has such a long
symptomatic period and over sudden that
creates a completely new game when
trying to contain this virus it enters
the dynamics of the infection exactly I
do also I don't know how close you're
tracking this but do you also think that
there's a different like rate of
infection from when you're asymptomatic
like that that aspect or does a virus
not care so there were a couple of works
so one important parameter that tells us
how contagious the the person with a
symptomatic device versus are
symptomatic is looking at the number of
viral particles this person sheds you
know as a function of time so so far
what I saw is the study that tells us
that the you know the person during the
asymptomatic period is already
contagious and it said the person says
enough viruses to infect yeah and
another horse and I think there's too
many excellent papers coming up but I
think I just saw so maybe a nature paper
that said the first week is when you're
symptomatic or asymptomatic you're the
most contagious so the highest level of
the like there's a plot sort of in the
14-day period they collected a bunch of
subjects and I think the first week is
one is the most yeah I I think I mean
I'm waiting I'm waiting to see sort of
more more populated studies where I just
it was kinda
my one of my favorite styles was again
very recent one where scientists
determined that tears are not contagious
so so there is you know so there is no
viral shedding down through three tears
so they found one wick moist thing
that's not contagious and I mean there's
a lot of I'm personally been I'm gonna
serve a paper somehow that's looking at
masks and there's been so much
interesting debate on the efficacy of
masks and there's a lot of work and
there's a lot of interesting work on
whether this virus is airborne and it's
a totally open question is it's leaning
one way right now but it's a totally
open question whether it can travel and
aerosols long distances I mean do you
have us do you think about the stuff do
you track this stuff are you focused on
them yeah I mean I'm at it I mean did
this is this is a very important aspect
for our epidemiology study I think the I
mean and it's sort of a very simple sort
of idea but I agree with people who say
that they mask the masks work in both
stay in both ways so it not only it
protects you from the you know incoming
viral particles it also protect you know
it it you know makes the potentially
contagious person not to spread the
right of party noise when they're
asymptomatic may not even know that
they're in fact it seems to be there's
evidence that they don't surgical and
certainly homemade masks which is what's
needed now actually because there's a
huge shortage of they don't work as to
protect you that while they work much
better to protect others it's it's a
motivation for us to all wear one
exactly because I mean you know very you
don't know where you know inside you
know about 30% as far as I remember at
least 30% of the asymptomatic cases are
completely asymptomatic here right so
you don't really care you don't I mean
you don't have any symptoms yet you shed
viruses do you think it's possible that
we'll all wear masks so I wore masks at
a grocery store and you just you get
looks I mean it was like we could go
maybe it's already changed because I
think CDC or somebody's I think the CDC
has said that we should be wearing masks
like la they starting to happen but you
it just seems like something that this
country will really struggle doing or no
I hope not I mean you know it it was
interesting I was looking through the
through the old pictures during the
Spanish flu and you could see that the
you know pretty much everyone was
wearing masks with some exceptions and
they were like you know sort of iconic
photograph of the thing it was San
Francisco this tram who was refusing to
let in a you know someone without the
mask so I think well you know it's also
you know it's related to the fact you
know how much we are scared right so how
much do we treat this problem seriously
and you know my take on it is we should
because it is very serious
yeah I i from a psychology perspective
just worried about the entirely the
entire big mess the of a psychology
experiment that this is whether masks
will help it or heard it you know the
masks have a way of distancing us from
others by removing the emotional
and all that kind of stuff but at the
same time masks also signal that I care
about your well-being exactly so it's a
really interesting trade-off that's just
uh yeah it's it's interesting right
about distancing uh aren't we distance
enough right exactly
Hey and when we tried to come closer
together when they do reopen the economy
that's going to be a long road of
rebuilding trust and not not all being
huge germophobes let me ask sort of you
have a bit of a Russian accent Russian
or no
Russian accent uh were you born in
Russia yes and the you you're too kind
I have a pre thick Russian accent what
are your favorite memories of Russia so
I so I moved first to Canada and then to
the United States back in 99 so by that
time I was 22 so you know whatever
Russian accent III got back then you
know it's that use me for the rest of my
life
you know it's yeah so I you know by the
time the Soviet Union collapsed I was
you know I was a kid but through you
know old enough to to realize that there
are changes and did you want to be a
scientist back then oh yes oh yeah I
mean my first the first sort of ten
years of my sort of you know a juvenile
life I wanted to be a pilot of a
passenger jet plane Wow
so yes it was like you know I was
getting ready you know to go to a
college to get the degree but
I've been always fascinated by science
and you know so not just by mass of
course math was one of my favorite
subjects but you know biology chemistry
physics somehow I you know I liked those
four subjects together and guess so so
so essentially after a certain period of
time I wanted to actually back then it
was a very popular sort of area of
science called cybernetics so it's sort
of it's not really computer science but
it's it was like you know computation or
robotics yes in this sense and so I
really wanted to do that and but then
you know I you know I realized that you
know my biggest passion was in
mathematics and later I you know when
you know studying in Moscow State
University I also realized that I really
want to apply the the knowledge so I
really wanted to to mix you know the
mathematical knowledge that I get with
real-life problems and that could be you
mentioned chemistry and now biology and
I sort of does it make you sad maybe I'm
wrong on this but it seems like it's
difficult to be in collaboration to do
open big science in Russia from my
distant perspective in computer science
I don't I'm not like we can go to
conferences in Russia I sadly don't have
many collaborators in Russia I don't
know many people doing great
a I work in Russia does it make does
that make you sad
am I wrong and seeing it this way well I
mean I am
I have to tell you I am privileged to to
have collaborators in biometrics in
Russia and I think this is the divine
thematic school in Russia is very strong
we have in Moscow in Moscow in
Novosibirsk in st. Petersburg have great
collaborators in cousin and so at least
you know in terms of you know my area of
research strongly people there
yes strong people a lot of great ideas
very open to collaborations so I perhaps
you know it's my luck but you know I
haven't experienced you know any
difficulties in establishing
collaborations
that's why informatics it could be bad
from a text to an ink yeah it's it could
be person by person related but I just
don't feel the warmth and love that I
would you know you talk about the
seminal people who are French in
artificial intelligence France welcomes
him with open arms in so many ways I
just don't feel the love from Russia I I
do on the human beings like people in
general like friends and and just cool
interesting people but from the
scientific community
no conferences no big conferences and
it's uh yeah it's actually you know I
I'm trying to think yeah I cannot recall
any any big AI conferences in Russia it
has an effect on for me
I haven't sadly been back to Russia so I
should but my problem is it's very
difficult so I am now I have to renounce
the citizenship I was alright I mean I'm
a citizen in the United States and it
makes it very difficult there's a mess
now right so I want to be able to travel
like you know legitimately yeah and it's
it's not it's not an obvious process
they don't make it super easy I mean
that's
that like you know it should be super
easy for me to travel there well you
know hopefully this unfortunate
circumstances that we are in will
actually promote the remote
collaborations yes and I think we weave
jr' experiencing right now is that you
still can do science you know being
current in in your own homes yeah
especially when it comes I mean you know
I I certainly understand there is a very
challenging time for experimental
scientists and and I have many
collaborators who are you know who are
affected by that but for computational
scientists they are really leading into
the remote communication nevertheless I
had to force you to talk to you in
person because there's something that
you just can't do in terms of
conversation like this I don't know why
but in person it's very much needed so I
really appreciate you doing it you have
a collection of science bobbleheads yes
which look amazing which which
bobblehead is your favorite and which
real-world version which scientist is
your favorite yeah so yeah by the way I
was trying to bring it in but they're
cranking now in my in my office they
sort of demonstrate the social distance
so they're nicely spaced away from each
other but so you know it's interesting
so I've been I've been collecting those
bubble has for the past maybe twelve or
thirteen years and it you know
interesting enough it started with the
two bubble heads of Watson and Crick and
interestingly enough my last bubble had
in this collection for now and my
favorite one cuz I felt so good when I
got it was the rosalind Franklin and so
so you know when I go who's the full
group so I have what some Creek Newton
Einstein
Marie Curie Tesla of course Charles
Darwin Sir Charles Darwin and wasn't
Franklin I am definitely missing quite a
few of my favorite scientists and but so
you know if I were to add to this
collection so I would add of course
Kolmogorov injustice that's that's you
know I've been always fascinated by his
well his dedication to science but also
his dedication to educating young people
the next generation so it's it's it's
very inspiring he's one of the right
okay yeah he's one of the Russia's great
yes only yes so he also you know the
school the high school that I attended
was named after him and he was great you
know so he founded this core school and
he actually taught there is this is a
Moscow yes so but then I mean you know
other people that I would definitely
like to see in my collections was would
be Alan Turing would be John von Neumann
yeah you're a little bit later in the
computer scientists yes well I mean they
don't they don't make them you know III
still I'm amazed they they haven't made
Alan Turing yeah yet yes and and and I
would also add the Linus Pauling line is
falling so with Linus point so this is
this is to me is one of the greatest
chemists and the person who actually
discovered
secondary structure of proteins was very
close to solving the DNA structure and
you know people argue but some of them
were pretty sure that if not for this
you know
photograph 51 by rosalind Franklin that
you know what Sun Cree got access to he
would be he would be the one who so
sense is a funny race
let me ask the biggest the most
ridiculous question so you've kind of
studied the human body and its defenses
and these enemies that are about from a
biological perspective and from a tax
perspective a computer scientist
perspective how is that made you see
your own life sort of the meaning of it
or just even seeing your what it means
to be human
well it certainly makes me realizing how
fragile the human life is if you think
about this little tiny thing can impact
the life of the whole human kind to such
extent so you know it's it's something
to appreciate and to you know to
remember that that you know we are
fragile we have to bond together as a
society
and you know it also gives me sort of
hope that what we do a scientist is
useful I don't think there's a better
way to end it means you take it so much
for talking today it was an honor thank
you very much
thanks for listening to this
conversation with Mitra korkin and thank
you to our presenting sponsor cash app
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friedman and now let me leave you with
some words from edward osborne Wilson
Leo Wilson the variety of genes and the
planet and viruses exceeds or is likely
to exceed that in all of the rest of
life combined thank you for listening
and hope to see you next time
you