title: Advanced Modeling Reconciles Counterintuitive Decisions in Lead Optimization.
abstract: Lead optimization (LO) is essential to fulfill the efficacy and safety requirements of drug-based targeted therapy. The ease with which water may be locally removed from around the target protein crucially influences LO decisions. However, inferred binding sites often defy intuition and the resulting LO decisions are often counterintuitive, with nonpolar groups in the drug placed next to polar groups in the target. We first introduce biophysical advances to reconcile these apparent mismatches. We incorporate three-body energy terms that account for the net stabilization of preformed target structures upon removal of interfacial water concurrent with drug binding. These unexplored drug-induced environmental changes enhancing the target electrostatics are validated against drug-target affinity data, yielding superior computational accuracy required to improve drug design.
authors.affiliation: Argentine Institute of Mathematics, National Research Council, CONICET, Buenos Aires 1083, Argentina; AF Innovation, GmbH, a pharmaceutical consultancy, Avenida del Libertador 1092, Buenos Aires 1112, Argentina. Electronic address: ariel@afinnovation.com.
authors.forename: Ariel
authors.initials: A
authors.lastname: Fernández
authors.affiliation: Institute for Biophysical Dynamics, The Computation Institute and Departments of Computer Science and Mathematics, University of Chicago, Chicago, IL 60637, USA.
authors.forename: L Ridgway
authors.initials: LR
authors.lastname: Scott
mesh_terms: D000818:Animals; D003657:Decision Making; D016503:Drug Delivery Systems / Q000379:methods*; D015195:Drug Design; D006801:Humans; D008956:Models, Chemical
keywords: drug design; drug–target mismatches; lead optimization; protein–water interface; three-body effects