I summarise here what I think are three interesting questions & discussion topics for progress in current chemistry and informatics research in Drug Discovery & Development.
Computational chemistry methods have now been applied with success and significant contributions to drug discovery research and development. Nevertheless current methods are not yet able to comprehensively or easily meet the needs of medicinal chemists, or on certain kinds of problems are failing or have challenges or complications. We ask the question:
Where do we currently stand with cheminformatics-driven medicinal chemistry?
More at http://barryhardy.blogs.com/cheminfostream/2006/10/where_do_we_cur.html
(This includes a presentation and discussion of the discovery and development of low molecular weight non-peptidic beta-secretase inhibitors as potential new therapeutics against Alzheimer's Disease.)
After twenty years of undeniable progress, molecular docking seems to have plateaued. A recent paper by Tirado-Rives and Jorgensen [1] dashes some of the few hopes we had left by showing that conformational energetics alone make it impossible to rank order diverse compounds in high throughput virtual screening. In a Perspective in the same issue [2], Leach, Shoichet and Pieshoff summarize the stagnating state of the art that is docking, and suggest a pragmatic way forward, through measurement and benchmarking. Again in the same issue, a laborious evaluation of 10 docking programs, using 37 scoring functions was applied to seven protein types for three tasks: binding mode prediction, virtual screening for lead identification, and rank-ordering by affinity for lead optimization [3]. Among some encouraging results and upbeat analysis, the paper makes a number of worrying observations, including that "high fidelity in the reproduction of observed binding poses did not automatically impart success in virtual screening". Moreover, for eight diverse systems, "no statistically significant relationship existed between docking scores and ligand affinity."
John Irwin and I are asking the following question:
Could we take a Community Approach to Comparing Virtual Screening Methods?
More at http://barryhardy.blogs.com/cheminfostream/2006/10/could_we_take_a.html
The ability to make informed decisions during the early phases of drug discovery is the key to decreasing hit-to-lead and lead optimization cycle times. The motto “fail early, and fail cheap” represents the need to identify problematic chemotypes early in the development process so that more productive lines of inquiry may be followed. The field of predictive modeling has reached a point where there is a realistic expectation that troublesome moieties can be flagged through computational virtual screening. The next major step in the development of predictive methods is to be able to also use these modeling techniques to suggest productive courses of action to identify and correct ADME and PK problems during lead compound optimization. Thus, the use of validated, interpretable models may serve both as a way of identifying ADME/Tox and PK failures, and also provide a means for correcting them. Predictive Toxicology is therefore one area that potentially can contribute significantly more in the future than it has in the past to improving our confidence in the safety of new drug candidates in clinical development [6].
We ask the question:
How can we improve our Confidence in the Drug Safety of potential new Therapeutics through Predictive Toxicology?
More at: http://barryhardy.blogs.com/cheminfostream/2006/09/appyling_predic.html
Barry Hardy
References
[1] Tirado-Rives & Jorgensen, Contribution of Conformer Focusing to the Uncertainty in Predicting Free Energies for Protein-Ligand Binding, J. Med. Chem, 2006, 59,5880-5884.
[2] Leach, Shoichet, Pieshoff, Prediction of Protein-Ligand Interactions. Docking and Scoring: Successes and Gaps., J Med Chem, 2006, 49, 5851-5855.
[3] Warren et al, A Critical Assessment of Docking Programs and Scoring Functions, J Med Chem, 2006, 49, 5912-5931.
[4] http://www.nigms.nih.gov/News/Reports/DockingMeeting022406.htm
[5] Huang, Shoichet, Irwin, Benchmarking Sets for Molecular Docking, J. Med. Chem, 2006, in press.
[6] B. Hardy, P. Elkin, J. Averback, A.L. Fontaine, S. Kahn, Improving Confidence in Safety in Clinical Drug Development: The Science of Knowledge Management, The Monitor, Association of Clinical Research Professionals, p. 37-41, October 2006.
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