Herald: So, willkommen zusammen. Heute
Abend gibt es den Talk von Andrea über den

"Corona Virus Structural Task Force". Ich
bin melzai_a Herald für die Session. Wir

haben einen Signal Angel, Dia, sie wird
die Fragen sammeln, die in den Chat

gestellt werden und am Ende gehen wir im
Vortrag über diese Fragen. So viel zum

Ablauf. Der Vortrag wird aufgezeichnet.
Und ist danach nachträglich verfügbar auf

Media.ccc.de irgendwann in den nächsten
Tagen oder Wochen. Und damit würde ich mich

freuen, Andrea, du als
Nachwuchsruppenleiterin an der Uni

Hamburg, du hast die letzten zwei Jahre
mit den Codona Virus beschäftigt, und

daraus wunderbare Visualisierung gemacht.
Wie lief es denn ab und wie sieht Corona

eigentlich aus?

Andrea: Ja, vielen dank! Erstmal danke für
die Einladung. Und ja, genau darum geht es

in dem Talk jetzt, was wir die "corona
virus structure task force" nennen. I'm

going to give the presentation in English;
so that international listeners can also

listen in. But you can ask your questions
in, well, any language anyone here speaks.

I understand German, English and Japanese.
And I want to start with a quote by Marie

Curie. I know the room Mary is not named
after Marie Curie, but she said something

that is very true in this pandemic, which
is: "nothing in life, is to be feared,

only to be understood. Now is the time to
understand more so that we may fear less."

And indeed, this holds true for the corona
virus more than anything, because as you

all know, you cannot see the virus. You
can only see it indirectly visualized by

science or you can see the measures against
it or you can see ill people. But the

virus itself is invisible. And I'm going
to start this talk with questions. There

will be many questions. And the first one
is, what does the corona virus look like?

Now you may think, you know, but the
reality of it is that even German news has

no idea. And I know that ZDF is now using
a different picture, which looks more

similar to what I'm going to show, but
it's very wrong as well. This picture? Is

what most people think the virus looks
like. And I also brought you like two top

model and models of the virus. One can
even make sounds. Any spiky ball of

this days really passes as a corona virus
because no one seems to know what the

thing really looks like. Only it's like
crowned. And it has spikes. That's the

only thing that all the models have in
common. But some things look like you can

just, you know, like they are little Shrek
ears type things or have tentacles. No

one really knows. So how do we know as
scientists and can viruses, be seen? If we

imagine so, this is an electron
microscopic picture of a human hair. It's

0.1 millimeters. It's the length of this
line, so the hair is a little bit less.

The little red dot, which you may or may
not be able to see inside that circle is

the size of the corona virus. Now if we
zoom into the picture of the hair, you can

see, I hope, a little red dot here. And
that's the corona virus to measure. So it

is 150 nanometers, or 0.0001.5 mm large. That is tiny

even by scientists sentence. However. Even
smaller than the virus with 150

nanometers. It's a single atom,
which is represented here again by a

dot, which is barely visible and is 0.1
nanometers in diameter or one. Angstrom.

Atoms are tiny, even compared to the
virus. A virus is composed being matter of

very, very many atoms. How can we
visualize something this small? Can we see

it with a light microscope? And what color
would the virus be? This is to scale.

Yellow light. It is 600 nanometer
wavelength meaning from this point to

this, it is 600 nanometers. So the
wavelength of visible light, which ranges

from 400 to 780 nano meters, is actually
longer than the virus is white. So there

is no chance whatsoever to ever observe a
single virus with light just physically

not possible. We need something that has a
smaller wavelength, and there are two

things we use X-rays, which have 0.1 nanometer wavelength. So they

are very, very small. They're like light. They're also photons. We call it

also X-ray light (Röntgenstralung,
Röntgenlicht). But they have so high energy

that their wavelengths are tiny. The other
thing are electrons, which have even

smaller wavelengths. If you choose to
regard them not as particles, but as

waves. So we can use electrons and X-rays
to observe the virus, and we do. And for

this, we have several possibilities. One
of them is large particle accelerators

like the one I'm working on in Hamburg,
which produces very intense X-rays.

Another one is an electron microscope. So
here is a model of an electron microscope.

In order to use it, you need a scientist
and then you shoot an electron beam from

an electron cannon. That's the official
scientific term. It's an electron cannon

onto both an electron gun electron cannon
electron gun. You shoot your electrons

through lenses, which are magnetic.
Electrons are negatively charged so the

magnetic field can be used as a lens
system onto a sample. For example, the

virus and then you have a detector. What
do we see on this detector? We should

viruses with electrons and record how many
electrons pass through the sample? What we

see looks like this. So of course, it's
black and white because electrons come.

There's no colors involved. And what you
can see is a dark shadow. And then around

it, a little bit of bright spots, almost
like a corona during a sun eclipse. So

this is why the corona virus is called
corona virus, because it spikes under the

electron microscope look like a corona.
And these pictures have no colors, but

scientists like to colored them in
particular in order to tell people that

this is a dangerous virus and that is the
background. So if we colored, it may look

like this. And this is an official picture
released very early in the pandemic by the

National Institutes as one of the first
pictures of the new corona virus. We can

also do scanning electron microscopy,
which is a similar measure where you coat

the entire surface and then you get a
pretty three dimensional picture. What you

can see here are lung cells, the lung
carpet like the like hairy structure here.

That's lung cells that are single type two
alveolar epithelial cells. So there are

like a little like their job is to
get rid of stuff the lungs don't want

there, like a carpet, they can move and
they get rid of stuff for you. However,

these cells, you have a problem. They're
infected with corona virus. You can see

some slime or mucus here, and you can see
the viruses here. Because of the coating,

they look a little bit like cauliflower.
So that's nice. But it doesn't give us the

full picture, but so much for people who
say we cannot isolate the virus. We can

actually even like, make it visible. So we
can make this invisible enemy visible. It

is just a question of having the right
equipment and a good sample of the virus

and many hours of work. The virus
therefore exists and can be made visible

using electron microscopes or, for
example, as a particle accelerator. But

I'm not going to go into detail here. We
have not enough time tonight. I'm only

going to talk about electron microscopes
here. So what is the virus made of. Those

This is the virus. We're going to talk about
this picture later in the talk when we

talk about model a little bit more. But
here is one Spike, I think you've all

heard in news from spike proteins, which
cover the surface of the virus or the

virion. If we draw this schematically, as
Thomas Splettstösser presented for us, he's an

illustrator, burst in Berlin, it looks
like this. And then we take only the head

of the spike, which is the region of the
spike we know most about, and then comes

an animation that I did. So it's not quite
as pretty. If we zoom in, we see the

surface and below that surface we see
things represented as a ribbon. However,

we can show this differently. We can show
the individual atoms connected to each

other. The problem with this display is
that it's really hard to find anything

here. It is super difficult to get an
overview with this picture, so we prefer

to show these complicated and fake
molecules made up of atoms as surfaces and

ribbons. And this ribbon diagram, by the
way, has also been found by a great female

scientist, Jane Richardson, several
decades ago, which was quite revolutionary

for my field. So the virus is made up of
atoms and molecules, and they are

structures can be found out by NMR, X-ray
crystallography and electron microscopy.

For now, this is all I'm going to tell
you. We're now going to dive very deeply

into the biology of the virus and what the
structures tell us. And then in the end,

I'm going to tell you a little bit more
exactly how we actually get from the

measurement to the model, which holds some
pitfalls and problems for us. And it's an

area in which I do usually my research.
But first, I'm going to talk about the

model, you all know this picture from the
CDC, right? And by the way, this thing for

a scientist, this thing is not a virus,
it's a variant. It's only the transport

form of the virus, the virus. That's a few
more things that are not contained in this

little show. That's just a transport form
for its RNA to get into a whole cell. We

call this a variant. But most people, even
scientists, can also refer to it as the

virus. So this is the CDC model, right?
That's the picture that went all through

the press around the world. That's like
THE picture of this pandemic, and it was

made by the CDC very early on by two
scientific illustrators there. However,

already then it had some problems. They
made it in quite a rash and it has some

errors. So we decided to make a new
picture, which looks like this. And. If

you compare it, two pictures, here are the
differences. The head of the spike in this

illustration sits directly into the
surface, while in reality it is singing

sitting on a long, very bendy like rope
like structure that tethers it. So the

virus, the head of the spike, which binds
to the host cell, is quite flexible. The

surface is not quite as coarse as shown
here. It's smaller. The virus actually

relatively large for a virus, and it's got
other proteins swimming in its surface. If

you look exactly, you'll see the virus is
also not exactly round. Now we thought

this is not enough. It's nice to have a
picture, but wouldn't it be nice if we

could actually touch it? So we made a 3D
printable model for those interested. You

can find also all that information on our
homepage. I'm going to show you the 3D

model. Let's see. So. This is the virus
model. As you can see, the virus is not

exactly round because it's outside, it's
very soft. It's like a soap bubble. It can

change its shape quite drastically. It's
wobbly and the spikes are actually

stochastic highly distributed. They're not
like regularly arranged and they are

swimming in the skin. And there are other
proteins in the surface as well, which you

can perhaps see whether they really formed
as little flower shapes, we don't know.

And the virus is huge. So this on the same
scale, one to one million as a rhinovirus

for the common cold. The corona virus is
huge. 20000 base pairs RNA makes it one of

the largest virus genomes we know. And a
virus, therefore as soft on the outside,

while rhinovirus has a very hard and rigid
shell that is always composed the same.

And we need this model in the hopes that,
like other scientists and perhaps schools

would like to print it at home and
actually like, get something tangible and

it turned out they did. So we got quite a
few requests from people, from child care

facilities and from schools and from other
scientists. And even my administration

like to have them printed. One even
proposed we may have them as Christmas

ornaments, but I found that a little bit
like tasteless. We didn't do it. And like,

just before I left Hamburg, we got a new
model. This model is now already a year

old, and in 2021, signs made quite a lot
of progress. So we now know there are

fewer spikes and a virus. All in all, it's
a little bit smaller, so it's not quite

like this, but perhaps less so. It's not
15 centimeters in diameter. The model is

12, and it is still like potato shaped.
It's not round because now what's

important for me to show, and I would have
like to show you this model like in front

of the camera tonight, but. It went into
the museum, it was the first one we had,

and we brought it to the opening of this
exhibition in Hamburg "Pandemierück in ide

Gegenwart" the gigawatt, so you can now
see it in the museum and we'll be back in

my office when they have assembled theres.
And this also holds true. I'm going to

talk about the task force in the second
half of this talk. But one thing that is

really true and what's true for this
project as well is the task force is

typically more interested in new
communication projects than in all the

pile of stuff we need to finish. You may
notice from home. Right. So this is how

our model. Now, let's dive deeper into the
thing, because so far we have only talked

about the virion and only about it's
outside. So the virion has to spike

proteins on the outside. Two other
proteins M and E protein, it has a double

membrane hull, which is very thin and
nucleocapsid, which is wrapping the RNA.

The RNA of actually containing the genes
for everything that the virus needs in

order to like, take possession of the host
cell. So the RNA is the important bit the

virion is transporting and nucleocapsid
and everything else kind of packs it and

makes sure it gets into the host cell. And
I'm going to show you quickly a video

because I think this is so nice to
understand, and it's the answer to the

question why does soap help against corona
virus? Because very many, like other

viruses, are relatively hard to wash off,
but not corona virus, because it's so

large, it has only a double membrane
shell. And this is a very nice video from

the protein data bank from our colleagues
there. So this is the virus double

membrane. It has lipid molecules. You can
see there are hydrophobic on the inside

and hydrophilic on the outside, so they
lock water on the outside, but not the

inside. Green molecules are soap. Soap
also has a hydrophobic tail and a

hydrophilic head. So unlike the water
which stays outside the soap just gets

into the membrane and kind of like goes in
between the lipids. And then they make

whole sort of water molecules can get
inside the virus. They can even assemble.

In around bits of the membrane and get it
out of the virus hull or around a spike

and remove to spike, which is hydrophobic
to stock out of the virus. This leads to a

total decomposition of the membrane and
therefore it can be completely dissolved

by soap. As soon as the nucleocapsid and
an RNA are exposed, the virus is no longer

infectious. It needs a spike in order to
infect so, you don't need to disinfect

your hands. You can just wash them with
soap, which I find is so lucky in this

pandemic because, you know, it would be
really ugly if we would need to disinfect

everything all the time, but we can
actually just use soapy water. Although,

let's be honest, I like to use
disinfectant every here, and then it gives

me just a feeling of more safety. It's
kind of like a ritual to protect me. I

suspect several of you are the same. So,
so much for the virion, that's like the

outer shell, that's like the transport
form. But there is more much more. This is

the corona virus life cycle, or I should
be more correct. It should be called

infection cycle because technically
speaking, viruses are not life. They need

a host cell to reproduce. So we're going
to come back to this picture. We're going

to take this apart bit by bit. First of
all, there is entry entry into oh yeah.

Let's quickly go back. The thing at the
bottom here, the big thing here. That's

the host cell. And a little one is
the virus, right? We're clear on that

Holbrook's here, right? And is the
outside. So this is like your lung

outside. That's your lung cell inside or
hopefully not your lung cell, right?

There's the virus. And this is the spike,
the spike as a vaccine target, as you

know, it's what's encoded in RNA vaccines
and it's also contained in all the like

vector vaccines we see. And I brought you
another model for that, which saw the

picture here. So this is one to 10 million
scale model of the spike. And this is an

antibody. Now if you are vaccinated either
by RNA or by a vector vaccine, your body

overproduce as far as injected with
spikes, which are usually on something to

carry it a host cell or a cell of your
body if it's an RNA vaccine or a vector.

Your body needs a few days to recognize
this thing, so once it has, it will build

antibodies that perfectly fit onto that
they can recognize the spike very, very

exactly. They have a specific binding
site, which is much more rigid than

anything else the antibody can bind to.
Then this gets decomposed because the

vaccine is not viable. What remains in
your body is information for these

antibodies. So now if you get infected
with corona? The immune system antibody

recognizes the spike it has previously
seen in the vaccine, and that is how the

vaccine actually works. So having this
protects you, one of the biggest problems

with COVID 19 infections is that the
immune system responds too late. And then

too much. So having these makes much more
certain that you will not get severe

COVID, which is, I think, very nice. And
what we also did, together with the

animation lab in Utah is not only make
those life life cycle or infection cycle,

we also made an animation the
scientifically most accurate animation

available on how the virus actually binds
onto the whole cell. There's a lot we

don't know, but everything we do know we
have shown here. So here is the virus. You

know the spike protein already. Yes,
nucleocapsid inside there is RNA, which

encodes for the rest, we're going to go
into the rest after this. And then at the

bottom here is the host cell. So lung
cells actually have ACE2 receptors shown

in purple, and a spike protein recognizes
those specifically meaning that items like

a puzzle piece fit exactly onto the purple
receptors on the lung cells. The spikes

bind there and then something else
happens. Another enzyme also being in the

membrane of the host cell cuts the spike,
so it's not like the name spike suggests

it would like shoot something into. But
that's not the case. It gets cut and then

comes to bed where we are a little bit
unclear how this happens. So what we know

is after it's cut, it somehow ends up
being tethered into the host cell and we

don't know the mechanism of this. So we
decided to illustrated here with like a

refolding process and then it's
energetically unstable. So in order to

become more stable, the whole thing clamps
and folds together, thereby dragging the

virus and the host cell membrane together,
the two membranes to buy a lipid membranes

Fuze. The virus material is inserted into
the cell. The RNA is now inside the host

cell, and this is how infection happens.
So we felt it was particularly important

to show this to people. We have made this
animation Creative Commons, but

unfortunately only American television
caught up on it, so we're really hoping

that one of the German like documentaries
will show this, because we think it's

really nice to see this process like as
accurately as we can depicted. So here is

the spike. That's the role of the spike.
Now the nucleocapsid, an RNA a half

entered into the host cell. What happens
now is that the nucleocapsid dissolves.

How that exactly happens, we don't know,
but it dissolves and RNA gets immediately

translated into protein. So the genome
gets RET inside the cell because the cell

believes it's own either comes from the
host cell and it starts building. The

proteins encoded in proteins are again
molecules. And actually, it makes one

very, very long protein chain really long,
which is called the poly protein, which

then gets cleaved. So D'Souza's in this
case, the thing that cleaves all the long

protein chain into individual molecules
that don't actually can work is called the

main protease because it's cutting protein
that's called the protease. And these are

the little triangle shaped things here.
Only when that happens to these bits

become functional. So if it doesn't
happen, if we can like hindered this like

cutting off the long polypeptide chain, we
have an efficient drug against corona,

which is why main protease is a major drug
target. And what you can see here in red

is the drug actually bound two main
protease. So that's what it looks like. We

are looking specifically for inhibitors,
which will stop this molecule from

function. So you can imagine this like a
screwdriver that we put out of right point

in a machine where it fits and it stops
the entire machinery. That's what we want.

And that's like called structure based
drug design. When you actually know the

structure of the molecule and then you
find a molecule, a small molecule, a drug

molecule that specifically stops whatever
that protein molecule is doing. It's also

how many antibiotics work or, for example,
if you've been up long yesterday aspirin.

Then. From here, where we have the poly
protein thing. Something happens inside

the cell, the cell is making some kind of
foam, which is connected to the

endoplasmic reticulum. That's just warm
and inside it. These like enzymes that

have now been cut in our functional start,
like a copy machine to make more and more

copies of the RNA genome of the virus. The
whole cell kind of like foams up and makes

more RNA. And it does so by a copy
machine, which is called RNA polymerase,

because RNA is a polymer and a polymerase
is an enzyme that's making polymers and an

RNA polymerase is an enzyme that makes
more RNA. So one way to block that process

of making more RNAs, which was similarly,
you know, stop the infection cycle because

if it can't produce more RNA, it's got
nothing to put into new viruses is to use

remdesivir or so we thought for a long
time. So does this remdesivir. Remdesivir

looks to the host cell and to RNA
polymerase in particular, like a

nucleotide, like a building block for RNA.
So basically, things are it's new paper it

can copy on when in reality it's kind of
explosive like blocks the entire

polymerase. So you can imagine this like a
Trojan horse, remdesivir is the Trojan

horse and RNA dependent RNA polymerase is
sure looks like RNA to me and just built

that into the strand. So we'll have a look
at this molecule. This is, by the way, I

should probably go back and explain this
for a moment. This is what we get out of

our measurements and electron microscopy.
So this is the so-called reconstruction

density, and that's what we built a
molecule in. So that's like what the

measurement gave us, everything else we
have to do by hand. So here is the

density, and this is what the researcher
built into it. The template strand, the

old one, which is to be copied, is green,
the new one is orange. Remdesivir is

purple and connected to the end, although
the program doesn't display it as such.

What you can also see is free magnesium
ions. That's their own thing and a de

phosphate. So what are more molecules that
researchers modeled in there? Where are

around it as the protein? So I've just
quickly depicted it without so you can see

what's happening because it's all very
crowded and difficult to see around it as

the protein and a jump of two proteins to
copy the RNA and to attach one after the

other, another building block to the
bottom of the orange chain. It's gotten a

remdesivir and it tried to put it there
and it successfully did. And this

structure was taken as to prove that
remdesivir will stop corona. But if you

look at the density, you can see that the
free magnesium ions and DIPHOSPHATE has no

density and are not covered by this great
cloud, right? So we think they were never

really there. And the remdesivir itself is
also not having so much density. So it

turns out that a structure is not quite
seeing what the researchers did because

the density doesn't match up with the
structure they built. And as we later

found out in clinical trials, is that
remdesivir, in fact, doesn't really do

what people hoped, which, among other
things, has to do with the fact that RNA

polymerase from corona virus is able to
proofread go like, Oh, there's a

remdesivir, then go back free nucleotides
take rip out the remdesivir, throw it away

and get the proper nucleotide to build in.
So. We're hoping that one over pea-rel will

be better, which, by the way, uses a
similar mechanism. It's called a

nucleotide. Yeah, it's similar to a
nucleotide. Here's another arrow we found

in the bottom of the structure, only going
to show you because I think the software

by Tristan Kroll is so cool, it does a
real time molecular dynamics simulation

while you're dragging around your
structure. We found that there is an error

in the way the whole molecule was
arranged. If there's any specialist, there

was a nine amino acid out of reach
associate. OK, I'm going to stop like

geeking out. There was just an error. Let
me show you how he correct that. So first

you marks up the wrong region and then he
releases it and <i>quickly flying-away noise</i> it goes where it's up to

go. I wish my life would always be like
this, you said were free days glasses in

front of your computer. You need hours to
do this by hand, but his software just

does it. Sorry. It's just if you've spent
months doing this, you're totally excited

by this wobbly molecule. I just wanted to
show you because I think it's so cool. All

right. Back to a more general content. We
have an hour RNA and a let's imagine we

didn't get any like good drugs so far, so
the infection cycle is still ongoing. The

RNA now is exported from the endoplasmic
reticulum. By the time we make this, we

didn't know how. But Hamburg researchers
and Dutch researchers have now found out

how this actually works as a pore here and
the pore gets the RNA out. The RNA then

gets packed into new nucleocapsid
were also coded by the genome

of the virus, then gets wrapped into a new
double membrane, which is host membrane.

Just it has no spikes, which also were
produced from the genome. And then, of

course, due the Golgi apparatus is somehow
involved, it gets exported. Of course, for

everyone that infected a cell, there will
be thousands that are produced and that's

the entirety of the SarsCoV 2 viral
life cycle. I know, this was a little bit

much, but I think this is cool and
exciting and just about what, you know. I

hope the public can understand about this.
It hopefully also tells you why molecular

structures are important, so they let us
understand how the virus works, how host

cells are infected. They can help us to
find drug targets and to do structure

based drug design, where we find drugs
that specifically block these big

molecular machines from doing their work.
They also help us to understand the

structures of vaccines and antibodies, and
they also let us understand changes due to

two mutations, I haven't got an example
because of the time. But when we get a

mutation with the structure, I can kind of
tell you, that it is going to change or

that it is going to change only by knowing
the new genome. I can already make a

prediction about what the mutation is
going to change in a functionality. That's

really important. So in my group, we have
some theories what a Micron actually does.

We haven't published and we haven't even
tweeted about them yet because we're still

waiting for research results. But it's
important to understand these molecular

structures, however, is not very easy to
get them. So what are the problems? When we

do our measurement, we get density in this
case, the density is blue. It's from the

spike head that I've shown in the
beginning, right? So the top that you may

recognize, this looks a little bit like
the blue density here. This is the result

from our research. And in this case, I
have built almost all of the molecule

already, so I'm going to show it. This is
like the software. We're actually using a

tenfold to speed I'm usually using, and I
would usually be sitting there with 3D

glasses. So here's the density. I said
that with my 3D glasses and this bit

hasn't been built, so you can now see me
like by hand. And one bit of molecule

after the other trying to get the murder
ought to be, and you can quite well see

that the computer is not able to do it all
automatically. So I have to help it a

little bit. And as I said, it's about 10
times the speed. It's even got like the

warning from the bin program not reacting
all of the software, it's also not

commercial. This has been developed by
other scientists, so the usability is like

so-so cool, just an amazing program. But
if you want some new functionality, you

better program it yourself, because perhaps
no one else is going to do it. And we have

actually contributed with a plug in or two
to cut. Yeah, you can see it's not always

easy, so I try and go, like, now it's
good. Settings should nicely in the

density and here it's fairly easy. My
students love doing this is like for them.

It's like computer gaming. They do it for
three months straight. If you don't like,

get them off the chair, go right up your
physics. They'll do it forever. And

secretly, I'm jealous. Because I also like
doing this. I don't know if you can

follow, but this is like playing a game.
Away, if you're interested in playing this

game, we are also having. Like practical
places and stuff. Right! So building,

building, building, going like, oh,
there's another alanine, I need a pralines

or mutated it. I go like, Yeah, OK, now
it's all nicely sitting. So that was easy.

But what do I do here? So I've built for
something here. But is it correct? The

density does not really tell me what's
going on here, and I'm going to show it

this to you in slower again. So you
understand the problem, right? In this

then part of the density, I can really not
tell only from the density what's going

on. I know approximately what a molecule
must look like due to the sequence. So

I've got some information. I know which
Atom is connected to which, but how it all

three dimensionally fits in here, even if
I know which lines have to go in, there is

super hard. So it would be very easy for
me to make an error here, because the

measurement data don't tell me enough
about what the model actually should look

like and several interpretation., everal
models would all be possible. So this is

kind of difficult. I'm just seeing a
questionnaire that I may want to answer

right away. Within could is it possible to
verify if you have chosen created the

right building blocks, you know, the
building blocks because of the genome? So

Gene tells you the order of amino acids
you want to put after each other. So if

you started at the right point, the rest
will also be like the correct atoms and

the correct connection. But how it like
three dimensionally faults, you don't

know. You have to make that on the
density. So it is possible to do it. You

have to write building blocks at hand.
Usually if there are if there is like, you

know, if a magnesium ion, for example, is
sitting there, the magnesium ion was not

in your genomic information. You just need
to know what you're doing to recognize

this is a magnesium ion ore does this a
diophosphate or something like this?

Right. Going to answer the rest of the
questions later. Molecular models need to

be built by hand. This can lead to errors.
There a few automatic algorithms do work

under favorable circumstances, but most of
the stuff still has to happen by hand. As

of today, and I got my postdoc from like
holidays for 15 minutes today, and he gave

new numbers. So we've got 1909 
molecular structures

today. New structures come out every
Wednesday. There are 1334 from X-ray

crystallography. That's the thing. With
the particle accelerator in Hamburg, I

thought, they have been measured at
synchrotrons all over the world. Not only

Hamburg, where BioNTech structures have
been measured, but also had SARS. There

have been large screens a diamond in Japan
and China at Sesamia, at Solemy, in

America. Synchrotrons all over the world
contributed to this. 35 from nuclear

magnetic resonance, which is a little bit
of a niche method for this type of study.

And 566 from electron microscopy. 
So 1909 molecular structures

of different states of 17
macromolecules, 17 proteins from a total

of 28. So corona virus in total has 28
different genes, 4 proteins. There are 28

proteins. And we only structurally know 17
of them. And then we have like different

versions of them, different ph, different
temperatures, spike, head bit of spike

head, spike head with antibody, things like
that. So a 1900 data sets that's in total.

Errors and structures, as we've
just seen, can happen because fit between

the data and model is bad, because complete
automation is not possible. Models are

built manually expertize in many different
areas needed. You need to be good

software. You need to have done all the
lab work. The measurement needs to be done

right. Processing needs to be made. You
need to know your statistical validation.

You need to know your chemistry. You need
to know your biology. So it's really not

easy and you need to know your 3D goggles
unless you get sick from them, in which

case you can't use them. One of the major
aspects of software, the methods you're

using and this is where we come in. Small
structural errors can lead to big

structural problems downstream. Imagine
the bid was to remdesivir, the diphosphate

there, the fact that there was something
bound into that structure that was not

really there. But the model had dose like
additional free magnesium ions down the

line, as I know from insiders, led to like
waste of hundreds thousands of dollars

and many hours of work time in drug
discovery because they kind of like fed

this model in order to find a drug that
ultimately never bound because of

magnesium ion wasn't actually there. So
if we make small structures, that builds

up hugely for the downstream applications
where they need these molecular

structures. Errors are common. And now we
add to this an ongoing pandemic. Right.

And her scientists are there to rescue
today. Lockdown happened, you're sitting

at home, there are no colleagues to help
you. Your child is home schooling. The dog

wants to be fed, your grandma calls,
because she's worried and you've got to

solve the spike structure on which lives
will depend as fast as possible. Normally,

we take a year to five to solve a
structure, and in the pandemic you only

got three months. Of course, errors are
going to happen. So that's well, just a

matter of fact. We've got to arrange
ourselves with it. It's not the fault of

individuals, it's how the whole thing
works. It's such a complex process. Errors

are going to happen! Now in normal life my
team and I methods developers and

structural biology. We are the people, who
give us the experimental techniques and

software to solve their structures as best
as we and they can. We're not usually in

the in the stage like we're usually, you
know. For every Nobel Prize, there have

been like dozens of Nobel Prizes in
structural biology has been methods

developed in the background to develop the
methods that made it possible to see, you

know, the structure of the DNA double
helix or structure of the ribosome, or the

structure of the influenza virus. It's
just that normally we're just enablers.

However, here was the pandemic and very
many structures that had errors. So we did

what we needed to do. We came together as
a relatively large team under my

leadership, we are today 23 people, we
peaked at 27 last year from nine countries

to check an improve the molecular
structures of SARS-CoV-1 and SARS-CoV-2.

So. We are methods developers, most of are
methods developers, we are specialists in

solving structures. We evaluate all the
published Structures and Protein Data

Databank or PDB from SARS and SARS-
CoV-2. We reprocess all of them and we

remodel them, although not all are looked
at manually, because that would be just

too much. We also do a scientific
dissemination, putting these structures

into context for people who want to start
doing molecular research on corona virus.

And we do public outreach. I'll give you a
quick insight into our pipeline because I

thought the software might be interesting
for you. So every Wednesday come new

entries of molecules in the protein
databank, which is, by the way, the World

Wide Protein Databank is an open, open
resource. Everyone in the world can

download the new structures, and all the
journals require people who make new

structures to put them there, which is
nice. I'm really privileged to be in a

field where the data are public. We
compared the new structures with the NCBI

proteomics, so the genes from corona virus
to find the structures that belong to

corona virus, put everything into an sql
metha database. Then we calculate how

different the structures are from the ones
we already know. We look whether all

measurement data available, so we have a
big problem of not all measurement data

being published. I hope we are going to be
like astronomy one day, where everything

gets published. I am sitting in the some
German cometies to that end STIKO AM which

is a very new hub. And then we run a
number of specialized programs which all

do validation and put the results on
GitHub immediately. On Thursday, at the

latest, researchers can find our elevation,
remodeling and the quality indication for

the structure everything, that can be done
automatically online. We then, for some

structures, manually rebuilt them, so we
actively look weathered our problems, that

was, for example, the case with the
remdesivir structure. We tried to do this

for those structures that we think drug
designers will use the most or that are

really important. And when we find errors,
we contact our original office first and

tell them we found an error here is the
corrected structure. Use our data, you

don't need to cite us, just correct your
structure in the database, please. This

means we won't get credit, but I meant
that at the beginning of the pandemic,

people were adjusting their structures
already when the preprint was out, so

there would not be problems downstream.
And I have often been asked I would like

to like this again. That was really like
why people accepted our corrections,

because they didn't need to give anyone
credit. They could just like change them.

And the database is also online, so
everyone from the Philippines to the U.S.

can just use them, whether it's like a
commercial person or a taxpayer, or a

private person research institution, a
foundation, everyone can use our data.

They're just online there for everyone,
and we only ask them to give us credit in

the form of a reference citation. We
disseminate the data via GitHub via

Twitter. 3D bio notes, which is a three
dimensional database linking directly into

our database, we contact the offers. We
also have entries in Proteopedia. Molprobity,

which is a virtual bioinformatics
institute, links directly into our

database. So they're always like up to
date showing what we are doing. We have a

homepage and we do reviews. There's a lot
of downstream users. The biggest ones are

the EU Jedi Grand Challenge folding at
home, which peaked out in July last year.

I think a 2.4 xTFLOPs computing power for
molecular simulations and used in the

majority our models to start from. And
also very big is IBM open pandemics. But

there are a number of others, plus many
individual apps. So we found a great new

many friends. Here is our homepage, that's
where you can find it. There's also an

English version, you can find blog posts
for the public and for scientists. And in

the end, I would like to talk for like
five minutes about daily life in ritual

mobility. So my team is over 20 people
from nine to ... we cover nine time zones,

right? Where nine hours time shift apart.
And we had several lockdowns. So.

Actually, the majority of people in the
task force, about half of them don't work

for me. They are volunteering their
researchers elsewhere that volunteer to be

a part of this effort. And there are many
people in the task force who have never

like personally met. So how do you make
group coherence if you are working for 20

months or 22 months by now in an
environment like this, right? We founded

ourselves in March 2020 as a chat group
called the Coronavirus Structural Task

Force, which was a job back then. It
didn't remain a joke. But that's how life

plays. We have everyday Zoom meetings at
10 o'clock, one time per week in the

afternoon. So do people from Oregon can
join us. We do a lot of like media

outreach in international and German
media. We've been like on nano and Terra X

and Planet E, we've been in breakfast
television. That was a particularly

interesting experience. My email got link
to Querdenker and I got a few very

interesting email exchanges. I also must
say I never got insulted or frightened by

anyone, so I just discussed with them and
it worked out. And I'm happy because like

I understood, like how, what the theories
are, and that was very interesting. Keep

the media also like to write about my
hair, my eyes, blah blah blah on these

things. I just want to note that Streeck
is about my age, and Drosten is only nine

years older than me. So really? OK,
whatever. Most importantly, they're

talking about our research. We also did a
lot of social media. I got a Twitter

account. Everyone else did as well. You
can watch us work on Twitch if you're

interested. We found that people find it
soothing to see us modeling these

structures. I was requested to make
stickers for the team as soon as we got a

grant and we got funded by the Federal
Ministry for Research and Education in

2020. We have a YouTube channel where you
can, for example, see the entry animation

and the students brought a cactus, which
is called Corina the Corona Cactus. I

know. It looked like we had fun, and we
did. I can tell you being caught, you

know, being at home, having to care for
your children. Having people dying. Having

an ongoing pandemic, knowing that I 'd be
more open pandemics is going to spend

another million based on your research.
And also that ZDF wants to talk to you and

the Berliner Abendblatt. This is so
stressful! Think about all the

responsibility we had, and it was really
terrible for us, so we needed to cheer up

every here and then, the whole group kind
of like grew together and we all became

friends. This was unheard. For us, it was
very uncommon as researchers. Typically,

our behavior with each other is much more
formal than their behavior and this group

was. But these were like exceptional
times, and we wanted to fight the pandemic

and inform the public. That's what we were
there for and was not so much about

personal gain. And that was nice. We have
a group chat. You know, I mean, I'm

talking to right audience, right? We have
a group chat. Do you know what that looks

like? Let me tell you. Typically,
professors don't communicate with this.

We have a virtual, Oh, we have a
virtual space. We hope to change to work

adventure soon. We all want to play games
in the evening occasionally with the

group, so we do some team building
efforts. When people can meet in person,

they usually do and sometimes they go and
travel and like, meet each other. But this

has been very limited. And we did grow
together as a network, that will be there

after the pandemic, so we are 25 people
all over the planet that did this

together. And even if we wouldn't have
made any difference against the virus, I

would still be happy to have done it for
the friendships I made. However, we did

make a dent. We don't quite know how big
it is because our science was open science

and the results could be gotten by
everyone without reference. But we know a

few things wouldn't have happened without
us. And I'm. Deeply grateful for having

had a purpose during this pandemic. In the
end, I have a little bit of a more serious

topic. My contract is going to run out in
May. I think it's going to be prolonged.

When it will, I'll be signing my 14 work
contract since 2008. 14, like I had 13

year contracts already out of all my task
force members, there is only one holding a

permanent position and two which are
retired. Everyone else, including six

people whose contract is going to run out
next year, are on temporary contracts and

not students. Students are extra. That the
students are on time limited contracts is

OK, but Germany's got a problem. 84
percent of academics in German

universities are on time limited
contracts. So are we. Only one task force

member has was a permanent position
signed, and that's not me. And this is not

so much on my behalf, because I'm going to
find my way through life. Look at all the

exposure I had, but there are people out
there who are single moms and dads, who

come from less privileged backgrounds or
had a harder life and who can just not

afford to be on one year contracts all the
time while holding a Ph.D.. We're losing

all these bright people and I'm seeing
them right. They leave my institute and

they go to industry. And then the
universities complain that they're not

competitive. We need to change the system.
We need to have more permanent positions

in science. I promise we won't perform
worse, if you give us permanent contracts.

We love what we are doing. So back to the
corona topic. In order to understand the

virus and its life cycle, we need to
understand its molecular biology. This

will help with the design of therapeutics.
We evaluated these molecular structures

with a bespoke pipeline, an expert
knowledge provided context and reached out

to the taxpayer and the general public to
inform them. We also wrote a paper

together with long off a list making the
invisible enemy visible, which is our

motto. And as we started this all with
questions, I'm going to end with

questions. Structural biology remains
difficult. What can we learn from our

findings? Should we, as a scientists
community, change our attitudes towards

errors? Should this serve as a model for
other projects, cannot serve as a model

for other projects? I hadn't thought about
this, but a nature editor asked me when I

was writing a comment whether we believe
that science should always be like this?

My God, that would be awesome. I would
totally be up for it if science would

always be like this! Come together with a
bunch of friends, but without funding!

Start doing something to, you know, fight
a global pandemic, then get some funding.

Still, having like no senior people on a
project. Can open science compete? I don't

know. We get pretty little credit. It
would, definitely. OK, science compete. I

don't know, it doesn't quite look like it
still getting measured only by the

citations my paper gets. And well, at
least a paper is not behind a paywall, but

if we would have published all our stuff
in like papers would possibly get more

credit. I really don't know, but we need
to work on this. If we want science, we

need to change how people are rewarded.
How senior they really need to be. I'm 39.

It seems I'm called a junior group leader.
All of us are young. The youngest is 24.

He's writing our first Alpha article about
a corona virus protein. I feel that the

German academic system and all over the
world, actually you need to be older and

older to become a professor and be
permanent and be like a grant holder. I

don't think it's necessary, I think that
professors could be 30 and the world

wouldn't, you know, like, go down. Well,
what will change in science after a

pandemic? We had like large exposure. It
certainly will also have to do with like

questions like did the virus now come from
an app or didn't it? That, you know, would

change how people view science, I'm sure.
How will scientists be viewed by the

public? Right. Right now, of course, you
know, mom and dad are very proud, but.

What's going to change? Are we going to
still be the bad guys because we often

are. But I'm like general, exclusively
taxpayer funded. I never took any money

from the pharmaceutical industry. I have
like, you know, no stakes in this game.

I'm just like earning tax money, so I
feel that, there is a whole complex of

difficult things there, how people regard
science, but definitely the pandemic is

going to change, how science is going to
be viewed. What's that going to be?

<i>Exspiration</i> In the end. I'd like to
thank all the task force members and all

our collaboration partners and our
scientific fairy godmother, Alvin Pearson,

who had little role in this research but
much role in our mentorship and bringing

us forward. My home, the University of
Hamburg, the Coronavirus Structural

Taskforce, our we are funded by the
Deutsches Officials Command Trust and the

Federal Ministry for Research and
Education. I would like to point out that

we are looking for student assistance, not
only for scientific work, but also for

social media video and programing work and
3D printing. So if you know anyone who's

interested, please point him in my
direction. My email is there. We are also

offering Bachelor, Master and Ph.D. thesis
in areas that cover both Lab work and

computer work, which is a rare thing these
days. You can find us on YouTube and the

internet and on Twitter and. I'm looking
forward to the discussion. And thanks for

listening.
melzai_a: You write it, so.<i>laughing</i>

Andrea: I just brought it up, must have
bmbF because I'm now sitting on the screen

on dislike committees more and more, I'm
reaching an age where I'm sitting on

committees and I told them legacy software
is a problem.

melzai_a: It's a real.big problem.
Andrea: You know, it's very troubling that

the software is written in Fortran. Not
every second Linus go to, so it's written

like assembler. No one knows what's in
there anymore. And if a person dies, we're

not going to be able to do anything about
the algorithms. They're just going to be

lost.
melzai_a: Exactly. And they are. So you

have to first influence to grant writing
institutes that there are grants out so

that this software can read is reversed.
And this software is not easy. So that's

not your typical web page, so you need to
work together in such groups. And so it's

a very interesting piece of the problem, I
have to say. So sadly, as a PhD student went,

we weren't we were looking into this for
the second. Ah.. This is too big of a cake

to eat. <i>laughing</i> It was very
interesting. So I can also this and you

let you do it. The nudel tool suite, and
that's also only maintained by, I think,

three people also. So even that one, it's
with many more. It's still not good. So

just my sense of that one.
Andrea: So I brought my Ph.D. thesis. I

worked on chalex?? and that faces similar
problems.

melzai_a: Yeah, it's it's just used in the
entire world to solve every small molecule

structure. There is more or less it was
like, Yeah, so questions were the

questions. Frankly, we ain't got a first
question, I think around 20 or 30 minutes

ago, if we yeah, that's that's why that
was so great as a signal angel, she's

picking up all of these points. And so the
first question was how do the virus

variants affect the shape or form of the
virus?

Andrea: I think they so no matter like,
OK, this is the old model as we know, then

there should be fewer spikes and should be
a bit smaller. But nothing would change on

this view, like the scale is way too
large. The mutations each change about 10

atoms, so every like amino acid at this
different, it's about 10 atoms. And those

changes would be so small you could not
see them on the virus model. You'd

actually need to look at the head of the
spike in order to see the mutation and

what it actually does. So the changes are
too small to show them in the model. That

doesn't mean they're not meaningful. So as
you've seen, like the head of the spike

binds to the host, to the host cell, to
ACE2 receptor, and that binding is highly

influenced by this by the mutations. Now
we found that we may end up lucky because

the same paths were to antibody as binding
is also the piece that binds to the host

cell. So everything that would mate
despite change in a way that the antibody

couldn't bind any more to it. For its head
would have also changed how it bound to

the host cell. However, it seems that
Omicron is still able to bind human cells

very efficiently, while antibodies cannot
recognize it so easily. That may have to

do with like this finger's actually like
packed and you could imagine like putting

cotton wool around it. That's called
glycosylation. It's got long sugar changes

that are rule, and they're there to
obscure the immune system, like the

antibody goes like orders, wool. I can't
really find where I'm on to bind. Is it

here? I don't know. And that's changed in
Omicron, but it's not fully understand

yet. I saw there was a new structure this
week, but I haven't looked at it yet.

However, the changes are too small to show
it in the virus model. They're like really

tiny changes. And another change that
happens in Omicron as well is the

proofreading mechanism. When the RNA is
copied is like damaged and we think it's

damaged. So their so-called eNd RNA, which
is a proofreading protein, its sharp is

like to go like a star and correct? Yes,
correct, correct. Correct. That seems to

be a little bit broken. So it could be
that Omicron is accumulating so many

mutations because it's RNA copy machine.
It's like not working as it should is

basically not proofreading. That would
mean that more viruses are produced that

are not viable and cannot survive. But it
would also mean that it mutates much

faster, and we think that may have an
influence. But that's just theory. So far

this hypothesis, we haven't proven it yet.
So this is why I haven't tweeted about it

yet, because it's just a theory, but it
would make sense, right?

melzai_a: Connected to that, I would have
a question the ice receptor of small children

is a little bit different than that one
of the adults to you do know about that

because all the concern to what's more,
the smaller children are the defense.

Andrea: I can't. I have read that, but I
haven't looked into it properly. So I'm

I'm afraid I'm not going to answer this
question because I feel I would rather not

say anything about it than say something
that's wrong especially.

melzai_a: Well. We're looking forward to
the secretary's right in the public PDB so

that everybody can look at them and.
Andrea: Know we live in an age of

preprint, and very often the PDB papers
are there when a preprint comes out, which

is how we called so many errors, right?
They published a preprint, they put out a

structure. We went like, there's errors in
the structures. And then when they

published actual paper, everything was
corrected.

melzai_a: And she's agreed that believe
the changes, I think are checked on the

PDB.
melzai_a: This is, in fact, because yes,

that's that's what IT people like
because then that, you know, there's a

history is very important. And there's a
second question and it goes towards the

tools that I use to simulate those
molecules.

Andrea: Wait, wait, wait, wait. I have a
follow up to this: thing that I would

really like to see, but it hasn't happened
yet. The PDB is a very static repository

where only original offers are allowed to
change their structures. Now, imagine if

the protein data bank would be like GitHub
with pull requests. We could go like, go

like, changed the molecule around. Go
like, no, it's a better fit to your data.

Please pull.
Herald: That would be a very subversive

proposition. I would say.
Andrea: Yeah, wouldn't that be nice? I'm

like, Why aren't we doing this? It's like
the system is already there. It happens

that we have like repositories for a while
in software development. We could do the

same thing with models fitted to our
experimental data. But I think I need to

go into more committees.
melzai_a: Yeah, it sounds like this. I

would agree for that proposal. There was a
person that was asking about the toolsset

that you would use to simulate those
molecules and structures and so on. And if

you then create these more usable pictures
for the public, how do you balance

artist's impression simplified models and while keeping the scientific truth as

much as well as possible.
Andrea: The question you don't need the

public even to have this problem. You have
it already when you make pictures

scientifically. Because sometimes you want
to show our certain aspects of a molecule

very clearly, which means you have to cut
away, for example, a part of the molecule.

So one answer to this is the program that
does. The modeling is not a program that

you use to make the pictures. That's the
first thing you do. So you make your model

with one program and then you take all the
coordinates of the atoms and you throw

them into a professional rendering program
that like, we'll do it all pretty. But you

still have to make an executive decision
on what to show in your graphics, in your

paper. And I think that in particular,
structural biologists, who deal with three

dimensional and two-dimensional pictures,
we would do very well to think a lot more

about scientific illustration. So all my
team likes thinking about these things,

which is, I think, how we got where we are
now, right? They actually like stuff like

this. They go like, Oh, we can print it 3D
and we can put a magnet on it and it's

going to stick. But it turns out that
scientists also need these tools to

understand what's going on. It's like
actually having a 3D model helps you so

much with thinking about things. Crick and
Watson. They build a model of their DNA in

metal for a reason. Because we're looking
at three dimensional things, making them

like understandable with our hands. So
yes, as a good researcher, you're not only

able to explain your research to the
cleaning woman, you should also be able to

visualize it properly. And it's part of
the art. If you are a structural biologist

and you're not able to make good pictures
of your molecules, you're not a good

structural biologist. End of story. You're
in the wrong discipline, you should have

possibly chosen something where you need
less graphics.

melzai_a: And I think one of your industry
does is actually a of biologist by

training. Right? I think you've got...
Andrea: Tomasello is a proper biologist.

Thomas Splettstössersplit shrews as a prop about like a
Ph.D. in bioinformatics and Janet Erosa,

and LiU are both scientists who are having
a group that only deals with illustration.

So it's actually in science. We have
several groups in the world and structural

biology who only do illustration as
science. So David Goodsell with his

watercolors, is very well known, but Janet
Erosa is another one. So actually making

these animations and pictures is so
complicated that television can't do it.

And the ZDF made a series of animations,
so they made very nice ones for Planet E

Rizzo and Nano with us. But then they
asked my expertize to make another

animation. And they only had like a call
with us, and they never came back and then

published a completely wrong animation of
the entire viral mechanism under my name.

And I'm still sad every time I see it
three times a day. Heute Journal shows a

wrong structure of the virus for which
they claim that I helped them make it, and

I wrote to them and told them, Your
depiction of the virus is wrong. I can

help you make a new one. But it seems that
it's 2. deutsche Fernsehen der heute Journal at least didn't

care on. I guess they think it's not
important enough, but I think with a

threat like this where we really cannot
see the virus, it is important to bring to

the public the best possible depiction we
can deliver. Sometimes, however, as I

said, you omit certain aspects, for
example, to show the effects of a mutation

yet only showed a side of the mutation.
You don't show all the atoms. But. That's

really an important part of what we are
doing. Like pointing out the important

bits of ...
melzai_a: Scientific information is so

important, I think we have one final
question, which I would say comes out

comes towards the direction of the immune
system. And the question would be can you

can you define vaccine on purpose so that
the immune system can forget how to

produce the antibodies after a defined
period of time? And I think the concern

here is about increasing your 
financial gain in the crisis, for example.

So programed obsolescence, as both of
those mentioned. So you're a bit late. So

if you could keep it short, that would be
great. OK? Andrea: The quick answer is no,

that's not possible. You can make. You can
enhance how long vaccines and how much

immune response you get from a vaccine or
certain additives. But you can not, like

make them a definite time because
everybody is different. So even when you

get your booster shot, they say six
months, but you may need it after three

months or you may need it after 12
authorityto. It's very hard to tell. And

pharma industry does not have tools that
would allow them that, to my knowledge. So

I think that's not a risk.
melzai_a: I mean, it's it's a human

system, and so complex is the rocket to
the Moon. So.

Andrea: I think it's a it's a valid
concern. It's just technologically not

possible. Luckily, I guess. 
melzai_a: The final and really last question, I think,

is where can somebody find the 3D models
out there?

Andrea: Oh, you can go to inside
Corona..de and find a blog post about a 3D

thing or you go to Thingy Reuss and you
look for inside corona. I can. Yeah. Yeah.

I just go to. I just put it in. Why not
that? That's our home page and then on

thingy worse. It's also called inside
corona. And you can also write me a

message on Twitter if you don't find it at
a turn up. And remember, we're going to

put out a new model soon in January, but
I'm still waiting for the final files and

holiday. So it will be a few more weeks.
melzai_a: So but that trend in January,

not in December 2008. Yeah, exactly. Or
printed?

Andrea: Yes. So thank you very much for
having me.

melzai_a: Yeah, it was good. Thank you.
And I think if they are no more questions.

Everybody. All right. Oh, you know how it
looks like? I think that's really

important. I think one and a half years
ago, I came across the first pictures was

like, This is how it looks like. Now I can
tell it to the people who who don't read

the scientific original papers because
they are so difficult to read. So. Yeah.

Good. You know. And thanks for being here
and looking forward to hearing and seeing

more and hopefully once this will be over.
I think

Andrea: I hope so too. Going back out of
the spotlight to being just a Methods

developer, that would be nice. 
Herald: That would be nice, yes.

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