Accurate and Reliable Prediction of Relative Ligand Binding Potency in Prospective Drug Discovery by Way of a Modern Free-Energy Calculation Protocol and Force Field
| Autor: | Yuqing Deng, Edward Harder, Lingle Wang, Bruce J. Berne, Ramy Farid, Ron Wester, Richard A. Friesner, Levi C. T. Pierce, Teng-Yi Lin, Donna L. Romero, William L. Jorgensen, Mark L. Brewer, Murcko Mark A, Shaughnessy Robinson, Robert Abel, Jeremy R. Greenwood, Jennifer L. Knight, Thijs Beuming, Byungchan Kim, Goran Krilov, Leah L. Frye, Dmitry Lupyan, David L. Mobley, Wolfgang Damm, Yujie Wu, Thomas Steinbrecher, Craig E. Masse, Markus K. Dahlgren, Woody Sherman |
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| Rok vydání: | 2015 |
| Předmět: |
Models
Molecular Chemical substance Protein Conformation Bioengineering Nanotechnology Ligands Biochemistry Catalysis Force field (chemistry) Search engine Colloid and Surface Chemistry Affordable and Clean Energy Models Drug Discovery False positive paradox Drug discovery Chemistry Molecular Computational Biology Proteins General Chemistry Ligand (biochemistry) Drug Design Proteins metabolism Chemical Sciences Thermodynamics Generic health relevance Biochemical engineering Protein Binding |
| Zdroj: | Journal of the American Chemical Society, vol 137, iss 7 Wang, L; Wu, Y; Deng, Y; Kim, B; Pierce, L; Krilov, G; et al.(2015). Accurate and reliable prediction of relative ligand binding potency in prospective drug discovery by way of a modern free-energy calculation protocol and force field. Journal of the American Chemical Society, 137(7), 2695-2703. doi: 10.1021/ja512751q. UC Irvine: Retrieved from: http://www.escholarship.org/uc/item/5061663w |
| ISSN: | 1520-5126 0002-7863 |
| DOI: | 10.1021/ja512751q |
| Popis: | © 2015 American Chemical Society. Designing tight-binding ligands is a primary objective of small-molecule drug discovery. Over the past few decades, free-energy calculations have benefited from improved force fields and sampling algorithms, as well as the advent of low-cost parallel computing. However, it has proven to be challenging to reliably achieve the level of accuracy that would be needed to guide lead optimization (5× in binding affinity) for a wide range of ligands and protein targets. Not surprisingly, widespread commercial application of free-energy simulations has been limited due to the lack of large-scale validation coupled with the technical challenges traditionally associated with running these types of calculations. Here, we report an approach that achieves an unprecedented level of accuracy across a broad range of target classes and ligands, with retrospective results encompassing 200 ligands and a wide variety of chemical perturbations, many of which involve significant changes in ligand chemical structures. In addition, we have applied the method in prospective drug discovery projects and found a significant improvement in the quality of the compounds synthesized that have been predicted to be potent. Compounds predicted to be potent by this approach have a substantial reduction in false positives relative to compounds synthesized on the basis of other computational or medicinal chemistry approaches. Furthermore, the results are consistent with those obtained from our retrospective studies, demonstrating the robustness and broad range of applicability of this approach, which can be used to drive decisions in lead optimization. |
| Databáze: | OpenAIRE |
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