[JunkDNA]

A few random thoughts I'm curious about (full disclosure: I worked in anti-infectives R&D as a bioinformatician early in my career for a major pharma)

1) One big challenge in synthesis is ensuring compound purity. Even when I was working in pharma, it was often the case that some of the compounds in the screening library could be contaminated with intermediates. This is murder for any kind of anti-infectives research because you end up with false-positives for toxic intermediates. Since your assay is often, "does the compound kill the bug?" the answer for most chemicals is, "yes!". How do you ensure the purity of what you deliver to your customers? If I'm a medicinal chemist wanting to try this, I want to know that I'm not getting a vial of brick dust back.

2) Just because you have a mechanism to synthesize, doesn't mean the yield is going to be great. Does your algorithm factor in yield when selecting the route?

3) When I started reading your post I thought, "Hats off to these folks, this is a super hard problem that no shortage of extremely smart people have spent years trying to solve." Then I got to the moonshot section! The number of small molecule antiviral drugs with efficacy is vanishingly small. I understand why you would try to tackle this, but it truly is a moonshot.

4) I can't help but wonder what Derek Lowe (https://blogs.sciencemag.org/pipeline/) thinks of all this, have you guys tried to reach out to him?

[morraa]

1. We ensure that the compound is pure using analytical methods like NMR and LC/MS. In our Moonshot project, the assay cascade comprises biochemical assays against the main protease (2 different assay methodologies, run in Oxford and Weizmann Institute) and live virus assays, thus we should be able to infer whether the activity is caused by impurities killing the virus. In addition, we also perform high-throughput x-ray crystallography to determine the structures of all the protein-ligand complexes, which serves an an orthogonal assay.

2. Yes, our algorithm does factor in the yield when it decides which reaction to use.

3. You're absolutely right. It is very ambitious but we've realized that even if we don't get our compounds into human trials (currently aiming for in-vivo testing in next few weeks) that we will still have generated a lot of useful data that is there in the open for when the next pandemic comes around. This has been a real weakness from prior pandemic where research wasn't continued and certainly wasn't stored in clean accessible ways. As I'm sure you know SARS has super high genetic similarity to current COV-2 so having prior data accessible and cleaned would have given researchers a real head start.

4. Yes Derek is aware of COVID Moonshot and is also of the opinion that is it both ambitious but sadly necessary. We continue to follow his posts as healthy skepticism particularly in the area of AI for drug discovery is always helpful.

[JunkDNA]

It didn't come across in my post in retrospect, but just want to say clearly I love this idea and the ambitious nature of it. I think when someone works in drug discovery, it's hard to escape this feeling that there has to be a better, faster, cheaper way. But at the same time, the reality of seeing how little we actually understand about biological systems on display each and every day tends to be quite a downer! The world sorely needs more of this kind of thinking.

[kayhi]

4) He has touched on this topic to varying degrees: https://blogs.sciencemag.org/pipeline/archives/2018/01/30/au...

[morraa]

Ah yes, industrializing the Chemistry part of drug discovery is certainly a blue sky dream but a field nonetheless we try to stay updated on -- hardware to do automated synthesis continues to make incremental improvements.