The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Alchemical free energy methods for drug discovery: progress and challenges
Open accessAbstract
Improved rational drug design methods are needed to lower the cost and increase the success rate of drug discovery and development. Alchemical binding free energy calculations, one potential tool for rational design, have progressed rapidly over the last decade, but still fall short of providing robust tools for pharmaceutical engineering. Recent studies, especially on model receptor systems, have clarified many of the challenges that must be overcome for robust predictions of binding affnity to be useful in rational design. In this review, inspired by a recent joint academic/industry meeting organized by the authors, we discuss these challenges and suggest a number of promising approaches for overcoming them.
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Cites
Scalable molecular dynamics with NAMD
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How to improve R&D productivity: the pharmaceutical industry's grand challenge
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Current Status of the AMOEBA Polarizable Force Field
Ponder, J. W., Wu, C., Ren, P., Pande, V. S., Chodera, J. D., Schnieders, M. J., Haque, I., Mobley, D. L., Lambrecht, D. S., DiStasio, R. A., et al. (2010) · The Journal of Physical Chemistry B · doi:10.1021/jp910674d · Cited by 1,440
Self-citationMobley, D. L., Chodera, J. D., & Dill, K. A. (2006) · The Journal of Chemical Physics · doi:10.1063/1.2221683 · Cited by 316
Self-citationPredicting Absolute Ligand Binding Free Energies to a Simple Model Site
Mobley, D. L., Graves, A. P., Chodera, J. D., McReynolds, A. C., Shoichet, B. K., & Dill, K. A. (2007) · Journal of Molecular Biology · doi:10.1016/j.jmb.2007.06.002 · Cited by 310 · cited 2×
“Despite the simplicity of the small apolar binding site and relative rigidity of the protein, this system has proven surprisingly challenging for rapid virtual screening methods like docking [37], and has been nontrivial for free energy methods to quantitatively predict affinity [21].”
BackgroundSelf-citationMartin, Y. C. (2009) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-009-9303-2 · Cited by 237
Cited by
Molecular Dynamics Simulation for All
Hollingsworth, S. A., & Dror, R. O. (2018) · Neuron · doi:10.1016/j.neuron.2018.08.011 · Cited by 3,257
Wang, L., Wu, Y., Deng, Y., Kim, B., Pierce, L., Krilov, G., Lupyan, D., Robinson, S., Dahlgren, M. K., Greenwood, J., et al. (2015) · Journal of the American Chemical Society · doi:10.1021/ja512751q · Cited by 1,313
Self-citationImproved Peptide and Protein Torsional Energetics with the OPLS-AA Force Field
Robertson, M. J., Tirado-Rives, J., & Jorgensen, W. L. (2015) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.5b00356 · Cited by 854
Entropy-Enthalpy Compensation: Role and Ramifications in Biomolecular Ligand Recognition and Design
Chodera, J. D., & Mobley, D. L. (2013) · Annual Review of Biophysics · doi:10.1146/annurev-biophys-083012-130318 · Cited by 531
Self-citationFreeSolv: a database of experimental and calculated hydration free energies, with input files
Mobley, D. L., & Guthrie, J. P. (2014) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-014-9747-x · Cited by 517
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Metadata
- Authors
- Chodera, J. D., Mobley, D. L., Shirts, M. R., Dixon, R. W., Branson, K., & Pande, V. S.
- Venue
- Current Opinion in Structural Biology
- Publisher
- Elsevier BV
- Published
- 2011-04
- Volume
- 21
- Issue
- 2
- Pages
- 150-160
- ISSN
- 0959-440X (ISSN-L)
- OpenAlex
- W2043383571
- Cited by
- 546
- References
- 6
- FWCI
- 2.39
- Type
- journal article
- Language
- en
- Open access
- green
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- Chodera, J. D., Mobley, D. L., Shirts, M. R., Dixon, R. W., Branson, K., & Pande, V. S. (2011). Alchemical free energy methods for drug discovery: progress and challenges. Current Opinion in Structural Biology. https://doi.org/10.1016/j.sbi.2011.01.011
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
