Comparative Binding Energy Analysis of HIV-1 Protease Inhibitors:  Incorporation of Solvent Effects and Validation as a Powerful Tool in Receptor-Based Drug Design

Abstract

A comparative binding energy (COMBINE) analysis (Ortiz et al. J. Med. Chem. 1995, 38, 2681-2691 has been performed on a training set of 33 HIV-1 protease inhibitors, and the resulting regression models have been validated using an additional external set of 16 inhibitors. This data set was originally reported by Holloway et al. (J. Med. Chem. 1995, 38, 305-317), who showed the usefulness of molecular mechanics interaction energies for predicting the activity of novel HIV-1 protease inhibitors within the framework of the MM2X force field and linear regression techniques. We first used the AMBER force field on the same set of threedimensional structures to check up on any possible force-field dependencies. In agreement with the previous findings, the calculated raw ligand-receptor interaction energies were highly correlated with the inhibitory activities (r 2 ) 0.81), and the linear regression model relating both magnitudes had an acceptable predictive ability both in internal validation tests (q 2 ) 0.79, SDEP cv ) 0.61) and when applied to the external set of 16 different inhibitors (SDEP ex ) 1.08). When the interaction energies were further analyzed using the COMBINE formalism, the resulting PLS model showed improved fitting properties (r 2 ) 0.89) and provided better estimations for the activity of the compounds in the external data set (SDEP ex ) 0.83). Computation of the electrostatic part of the ligand-receptor interactions by numerically solving the Poisson-Boltzmann equation did not improve the quality of the linear regression model. On the contrary, incorporation of the solvent-screened residue-based electrostatic interactions and two additional descriptors representing the electrostatic energy contributions to the partial desolvation of both the ligands and the receptor resulted in a COMBINE model that achieved a remarkable predictive ability, as assessed by both internal (q 2 ) 0.73, SDEP cv ) 0.69) and external validation tests (SDEP ex ) 0.59). Finally, when all the inhibitors studied were merged into a single expanded set, a new model was obtained that explained 91% of the variance in biological activity (r 2 ) 0.91), with very high predictive ability (q 2 ) 0.81, SDEP cv ) 0.66). In addition, the COMBINE analysis provided valuable information about the relative importance of the contributions to the activity of individual residues that can be fruitfully used to design better inhibitors. All in all, COMBINE analysis is validated as a powerful methodology for predicting binding affinities and pharmacological activities of congeneric ligands that bind to a common receptor.

Structural Basis for the Binding of Didemnins to Human Elongation Factor eEF1A and Rationale for the Potent Antitumor Activity of These Marine Natural Products

“…Intermolecular van der Waals energies for individual residues were calculated with the ANAL module, whereas the solvent-corrected residue-based electrostatic interaction energies were calculated with DelPhi, following the procedure described in detail elsewhere. 78 …”

Modulation of Binding Strength in Several Classes of Active Site Inhibitors of Acetylcholinesterase Studied by Comparative Binding Energy Analysis

“…Finite difference solutions to the linearized Poisson-Boltzmann equation, 59 as implemented in the DelPhi module of Insight II, 43 were used to describe the electrostatic effects of ligand binding in a format appropriate for use in COMBINE analysis, as reported previously. 11 In brief, following the classical approach, 9 the change in electrostatic free energy on molecular association (∆Gele) was split into three separate components: (i) the ligand-receptor interaction energy in the presence of the surrounding solvent (E ele LR ), (ii) the change in solvation energy of the ligand upon binding (∆G desolv L ), and (iii) the change in solvation energy of the receptor upon binding (∆G desolv R ):…”

A Study on Docking Mode of HIV Protease and Their Inhibitors.

“…This information is crucial, and during the drug design cycle, experimental structures for a target protein complexed to ligand(s) can afford researchers to examine the detailed picture of the binding site and to design more active analogues [1]. A number of computer docking softwares have been utilized successfully to fulfill the purpose of this computer-based drug design [2].…”