But Murcko thought it prudent to not name the scientist!
Yesterday, randomly flipping through a review by a well-known scientist, I came across this statement
"The ability to design drugs (so-called ‘ rational drug design ’) has been one of the long-term objectives of chemistry for 50 years. It is an exceptionally difficult problem, and many of its parts lie outside the expertise of chemistry. The much more limited problem – how to design tight-binding ligands (rational ligand design) – would seem to be one that chemistry could solve, but has also proved remarkably recalcitrant. The question is ‘Why is it so difficult ? ’ and the answer is ‘We still don’t entirely know’."Needless to say, I get the very strong feeling that Murcko was talking about this particular scientist. I have to say that my own opinions swing toward those enumerated by the scientist. Care to guess who?? (One hint: conference and company location...)
http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=450904
ReplyDeleteDo you have a copy of this you could share?
Do you really want a copy though? Leave your mail ID!
ReplyDeleteYes I would.
ReplyDeleteWhile attaining high enrichments has been fairly easy, I do think achieving a precise ranking of binding affinities has been recalcitrant.
Sure, there have been some FEP successes reported in the literature going back almost a decade, but I think the consensus is that the successes in these paper are not typical.
My take is that while concepts like induced fit docking are certainly an improvement over previous methods, we need to go further still if we want to accurately predict binding affinities.
I enjoy checking in on your blog from time to time and would enjoy discussing this matter in more detail offline.
You can send the paper to jlowrie8_*at*_comcast.net.
-Jeff
You are quite right that rank-ordering ligands still poses a problem. I don't even think the general problem has a computational solution (or otherwise). But what we can hope is that there will at least be enough generlization to handle a reasonable number of phrmaceutically relevant cases. I think of the philosophical principles that drives belief in looking for a solution is that there's got to be a finite number of ways, even if it's a large number, in which a ligand interacts with a protein. In theory, if we could understand all those ways, we could possibly predict binding affinities for the general case. In practice of course, we don't even understand all the subtleties, and that's what's really hampering progress in binding affinity prediction.
ReplyDeleteThanks for the comments!
Whilst I agree getting precise rank ordering computationally is a problem we should not lose sight of the fact that it is also a problem experimetally. Different conditions can give widely different results.
ReplyDeleteActually I'd be quite happy with a robust 50-fold enrichment.
With regard to ligand versus drug, I took Mark's comment to reflect our emerging understanding of molecular interactions in contrast to our poor understanding of toxicity, and the fact that it seems the biggest reason for attrition in drug development is lack of efficacy in man. Predicting the correct molecular target is still a major issue.
You are quite right. That's a point which I always think about; is our ability to experimentally determine rank ordering predictive? If not, somthing is better than nothing.
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