
‘Virtual Pharmacology’ Advance Tackles Universe of Unknown Drugs - rbanffy
https://www.ucsf.edu/news/2019/02/413236/virtual-pharmacology-advance-tackles-universe-unknown-drugs
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daddylonglegs
When I see a paper like this one of my first thoughts is "What will Derek Lowe
say about this?" He is a chemist in the drug industry and excellent writer. On
his blog he regularly tears apart overhyped claims for how software searches
for targets and automated synthesis of chemicals are going to find perfect
cures for everything at the press of a button. His take on this paper is
actually positive, though with some important caveats:

[http://blogs.sciencemag.org/pipeline/archives/2019/02/11/vir...](http://blogs.sciencemag.org/pipeline/archives/2019/02/11/virtual-
screening-as-big-as-it-currently-gets)

~~~
higginsc
I have been out of this space for a few years (transitioned to data science
from drug discovery), but from my time doing in silico and in vitro work, a
major issue with docking was rank ordering. His comments are right on the mark
IMO. Especially this paragraph:

>Another point is that high-middle-low effort on the D4 case. The binding
assay results compared to the docking scores are shown at right. You can see
that the number of potent compounds (better than 50% displacement, below that
dashed line) decreases as the scores get worse; the lowest bin doesn’t have
any at all. But at the same time, there are a few false-negative outliers with
binding activity at pretty low scores, and at the other end of the scale, the
top three bins look basically undistinguishable. So the broad strokes are
there, but the details are of course smeared out a bit.

These methods can filter millions of compounds down to hundreds, but as an
academic lab, it's still a herculean effort to synthesize hundreds of
compounds. And out of those hundreds, you might get a couple that are active.
This study is a combination hard work, yes, but also a lot of money and luck.

That being said, good for the team, and good for science. I have nothing but
respect for Shoichet and Roth. Didn't ever cross paths with Irwin.

~~~
cowsandmilk
> I have nothing but respect for Shoichet and Roth. Didn't ever cross paths
> with Irwin.

This makes me laugh since Shoichet was childhood friends with Irwin and
they've worked together on almost everything together since 2000 when Irwin
went to Northwestern to join his lab.

~~~
higginsc
That is pretty funny. The more you know. I was just a grad student and met
Shoichet at conferences.

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arkades
Link to the actual article, not the press release;

[https://www.nature.com/articles/s41586-019-0917-9](https://www.nature.com/articles/s41586-019-0917-9)

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roomey
"The four structures of AmpC determined with the new docking hits are
available from the PDB with accession numbers 6DPZ, 6DPY, 6DPX and 6DPT."

Are we in a situation now where, if I have a bad anti-botic resistant
infection I can just order these molecules on the off chance that they will
help me?

Can I order a toxin?

Or are these molecules just impractical to use outside of a lab setting

~~~
fabian2k
They only determined whether those specific molecules bind to the target. They
didn't test if they are toxic, if they are able to actually get to the target,
how stable they are under real conditions, into which metabolites they are
processed in humans, ...

This is the very first step towards developing potential drugs, it's very,
very far from an actual drug. And drug development wasn't the goal of this
paper anyway.

And the idea behind this paper was to find molecules that aren't in any
catalogue, so you would still have to synthesize them yourself or pay someone
to do a custom synthesis for you.

~~~
daddylonglegs
I thought the point of the library of molecules used was the supplier
(Enamine) has a systematic method of synthesizing the molecules they've
listed. It appears that, in practice, they can supply 90% of the molecules
they offer, synthesized on demand:

> Of the 589 molecules selected, 549 (93%) were successfully synthesized
> (Supplementary Table 10 and Supplementary Data 11, 13)

I fully agree your main points.

~~~
fabian2k
That's still custom synthesis and not off-the-shelf compounds. No idea how
expensive they are in this case.

~~~
daddylonglegs
About $100 apparently:

> Over the past decade, Kiev-based Enamine Ltd has innovated an efficient
> pipeline to produce any of over a billion never-before-made drug-like
> compounds on demand — at a cost of about $100 per molecule — by combining
> any of tens of thousands of standard chemical building blocks with one
> another using over a hundred established chemical reactions.

~~~
justtopost
'Per molecule' gives no real indication of cost, that appears to be a
'tooling' charge, to design the reaction chain. I doubt $100 will buy you any
useful quantity of any research chemical, much less a custom mfg one.

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melbourner
as a computational chemist I must say end-use might differ significantly from
these screening studies, it is more of a statement on current computing
capabilities and a little bit of science icing

~~~
dekhn
it's not even a statement of current computing capabilities if they used 1
CPU-day on 1,500 machines. That's a pittance.

~~~
momeara
Co-author here (AMA)--A large-scale docking screen of 116M molecules takes
~1100 cpu days on our cluster, working out to about 1 mol/sec, which is very
fast for virtual screening. What this doesn't account for is this requires
about 30 minutes per compound to precompute information (conformations,
partial charges, etc.). So this works out to ~6M cpu/hours to prepare the
library for screening, which is a substantial amount of computation. We're
loading about 1M molecules a day and have a 2-3 year backlog of compounds to
load from Enamine.

The good news is that once the library is prepared, it is quick to screen at
more targets--and we make the pre-computed library available at
zinc15.docking.org.

Interestingly, as the library grows a limiting factor is storing the library
on disk. It is now ~20T. We've set up several mirrors around the world for
groups that are actively using it. An interesting problem will be to see if
preparing compounds for screening on the fly (e.g. with machine learning
models) can overcome this limitation to keep up with library growth.

A big question for us is what will the return on investment in screening
larger and larger libraries be? One of the take aways from this work is if
docking has moderate enrichment, than screening larger libraries not only
gives more hits but actually can increase the hit-rate for the top scoring
compounds.

~~~
cing
I know that docking using GPU is about an order of magnitude faster than CPU
(see today's Schrodinger 2019-1 release notes,
[https://youtu.be/K4AYdBvuOe4?t=90](https://youtu.be/K4AYdBvuOe4?t=90)). Is
there a way of doing GPU accelerated precomputation though?

~~~
momeara
Hey Chris--We're right now using a mix of commercial and open source software
like Omega, Corina, AMSOL, and Mol2DB. Probably the slowest step is generating
the partial charges for each conformer with a reasonably high quality semi-
empirical forcefield. I'm not sure if there are competitive (in terms of
quality) GPU based methods, but if there were methods that were ~1000 times
faster as can be the case for GPU based methods, it would definitely speed up
the pre-computation or make on-the-fly prep feasible. Do you have any ideas of
where we should look?

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radicaldreamer
This is right up Zymergen's alley, at least when it comes to in vitro testing
of these compounds.

