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OpenSourceMalaria / Series4_PredictiveModel

Can we Predict Active Compounds in OSM Series 4?
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Evariste Technologies compounds #29

Open abrennan5 opened 3 years ago

abrennan5 commented 3 years ago

Hi all,

We’ve already caught up with @mattodd about this but will just give a quick intro for everybody else. Evariste Technologies is a start-up focusing on a probabilistic approach to drug discovery. Briefly, the platform we’ve built, Frobenius, takes an existing dataset and identifies the most promising starting point/s, then designs a bunch of new compounds and scores them according to the likelihood of achieving a set of pre-specified endpoints.

We were really interested in the recent publication detailing the open competition run by the OSM team and thought we’d have a crack at the problem ourselves. The compounds attached are the output generated by Frobenius when it’s presented with the series 4 data. More specifically, we’ve taken the two most promising starting points, applied the various compound designers and selected a subset of the highest scoring compounds (filtered by a medicinal chemist for synthetic feasibility etc). The number associated with each compound is the probability of it achieving a pIC50 of 8.

As we mentioned to Mat, we’re keen to get some of these synthesised and are able to contribute towards cost of synthesis. We’re also more than happy for anyone interested in these compounds to use them as inspiration for similar structures, if this is the case, we’d really appreciate being kept in the loop as we can very readily score the idea in Frobenius.

If anyone’s interested in knowing more about the modelling than the (very) brief overview I’ve given here we’re happy to discuss in detail.

Best wishes, Alfie

https://www.evaristetechnologies.com https://www.linkedin.com/in/alfie-brennan-746ba6b1

Evariste Suggestions

Series4_EVT_Suggestions.xlsx

Malaria suggestions pIC50 8 .pdf

abrennan5 commented 2 years ago

Thanks @edwintse and @mattodd, this looks promising and there seems to be some interesting SAR to discuss. A lot of us are away on holiday at the minute but I'll follow up with an assessment of the predictions next week.

So far this project has been a real test of the modelling so it's great to see some fairly potent molecules. Thanks again!

MFernflower commented 2 years ago

@edwintse http://www.fluorochem.co.uk/Products/Product?Code=209754 (4‐cyclopropoxyphenyl)boronic acid is commercially available - might be worth trying to make something with it since it seems like para position is important for potency?

abrennan5 commented 2 years ago

@edwintse @mattodd Hi both,

Image attached shows our predicted 50% confidence intervals for the new, non-biphenyl molecules. A comparison of 11 and 12 is illustrative for why we think predicting model error is so important. 11 has the highest mean prediction but a low confidence interval (exploiting well understood chemical space) whereas 12 has a modest mean prediction but significant uncertainty (more explorative) and as it turns out it's the best compound in the whole set. Overall really pleased with the results and very grateful for your help so far.

We're more than happy to do another round but I appreciate you might well need some time to focus on the suggestions from @miquelduranfrigola and @GemmaTuron, which is absolutely fair enough given the amount of compounds that have already been made based on our modelling. Happy to discuss this whenever you think would be suitable.

Link below is to a blog that we've just put on our website writing up a summary of the work so far.

https://www.evaristetechnologies.com/post/automated-design-of-potent-antimalarials

image