Rational Approaches to Improving Selectivity in Drug Design

By D. Huggins, Woody Sherman, B. Tidor. Journal of Medicinal Chemistry, 2012

321 citations recorded by the source corpus.

David J. Huggins,*,†,‡,∞ Woody Sherman,* and Bruce Tidor* †Department of Oncology, Hutchison/MRC Research Centre, University of Cambridge, Hills Road, Cambridge, CB2 0XZ, United Kingdom ‡Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, United Kingdom Schrödinger Inc., 120 West 45th Street, New York, New York 10036, United States Computer Science and Artificial Intelligence Laboratory, Department of Biological Engineering, and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States

Subfields: Computational Theory and Mathematics, Molecular Biology, Organic Chemistry

View Paper: https://www.semanticscholar.org/paper/5a02add8644d51ed1e3622d4dd6257ef23af936b

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Citations in the corpus

• Alchemical Binding Free Energy Calculations in AMBER20: Advances and Best Practices for Drug Discovery (2020, unknown): “In particular, ABFE (as opposed to RBFE) is not restricted to perturbations on a common core and is thus amenable for use in virtual screening, 4 selectivity screening, 123 and core hopping.”
• DeepAffinity: Interpretable Deep Learning of Compound-Protein Affinity through Unified Recurrent and Convolutional Neural Networks (2018, background): “For selective compounds that interact with factor Xa over thrombin, position 192 has been identified: it is a charge-neutral polar glutamine (Gln192) in Xa but a negatively-charged glutamate (Glu192) in thrombin (Huggins et al., 2012).”
• GAMESS as a free quantum-mechanical platform for drug research. (2012, background): “Contribution of hydration to the thermodynamics of ligand binding has been a topic of considerable interest for recent years [217, 218].”