Field of Science

The right questions about modeling in drug discovery

There's been a fair bit of discussion recently about the role of modeling in drug design, and as a modeler I have found it encouraging to see people recognize the roles that modeling to varying extents plays in the whole "rational" drug design paradigm. But sometimes I also see a question being asked that's not quite how it should be pitched.

This question is usually along the lines of "Would you (as a medicinal chemist) or would you not make a compound that a modeler recommends?". Firstly, the way the question is set up ignores the statistical process evident in all kinds of drug design and not just modeling. You never recommend a single compound or even five of them but usually a series, often built around a common scaffold. Now suppose the chemist makes fifty compounds and finds only one of them to be active. Does this mean the modeling was useful? It depends. If the one hit that you get is a novel scaffold, or a compound with better properties, or one without that pesky unstable ester, or even a compound similar to ones that you have made that nonetheless picks up some hitherto unexplored interactions with the protein, then modeling would not have been in vain in spite of what is technically a low hit rate. The purpose of modeling is to provide interesting ideas, not rock-solid predictions. Plus you always have to ask the other question: "How likely is it that you would have come up with this structure without the aid of modeling or structural information"? As with almost everything else in drug discovery, the value of a particular approach is not absolute and you have to judge it in the context of alternatives.

The other problem I have is that it's frequently just not possible to objectively quantify the value of modeling or any specific approach for that matter in drug design. That's because anyone who has contributed to the design of a successful drug or even a potent ligand knows how haphazard and multifaceted the process is, with contributions flying in from every direction in many guises. Every project that I have contributed to which has resulted in more potent ligands has involved a patchwork process with an essential back-and-forth exchange with the chemists. Typically I will recommend a particular compound based on some modeling metric and then the synthetic chemist will modify parts of it based on synthetic accessibility, cost of building blocks, ease of purification etc. I might then remodel it and preserve or extend the synthetic modifications.

But it can also be the other way round. The synthetic chemist will recommend a scaffold and I will suggest tweaks based on what I see on the computer, which will lead to another round of suggestions and counter-suggestions. The creative process goes both ways and the point is that it's hard to put a number on the individual contributions that go into the making of the final product. Sometimes there may be a case where one individual recommends that magic fluorine which makes all the difference, but this is usually the exception rather than the rule and more importantly, it's often not possible to trace that suggestion to a strictly rational thought process. Finally, it's key to realize that my suggestions themselves will very often be based as much on my knowledge of physical and organic chemistry as on any specific modeling technique. Thus, even internally it's not always possible for me to separate modeling-based suggestions from other kinds. On a related note, the frequent necessity of this interactive process is why I tend to find the "modeling vs medicinal chemistry" turf wars a little irksome (although they sometimes do help in fleshing out the details); the fact of the matter is that both kinds of scientists are ultimately an important part of successful drug discovery projects involving any kind of model-building.

Now this rather unmethodical approach makes it difficult to pin down the role of any specific technology in the drug discovery process, and this usually makes me skeptical every time someone writes a paper trying to assess "The contribution of HTS/virtual screening/fragment-based drug design in the discovery of major drugs during the last decade". But that's how drug discovery is, a hodgepodge of recommendations and tweaks made by a variety of rational and irrational human beings in an environment where any kind of idea from any corner is welcome.


  1. Well written points and insightful. Those iterative and combinative contributions of differing backgrounds is something I have also seen as useful in modeling that creates progress or value.

  2. All models are wrong but some are useful :)

    For me the biggest point was to ensure wet-lab chemists to believe in modeling.


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