Virtual screening strategies in drug design – methods and applications

Abstract

Virtual screening (VS) overcomes the limitations of traditional high-throughput screening (HTS) by applying computer-based methods in drug discovery. VS takes advantage of fast algorithms to filter chemical space and successfully select potential drug candidates. A key aspect in structure-based VS is the sampling of ligand-receptor conformations and the evaluation of these poses to predict near-native binding modes. The development of fast and accurate algorithms during the last few years has allowed VS to become an important tool in drug discovery and design. Herein, an overview of widely used ligand-based (e.g., similarity, pharmacophore searches) and structurebased (protein-ligand docking) VS methods is discussed. Their strengths and limitations are described, along with many successful stories. This review not only serves as an introductory guide for inexperienced VS users but also presents a general overview of the current state and scope of these powerful tools.

Isozyme-Specific Ligands for O-acetylserine sulfhydrylase, a Novel Antibiotic Target

“…Given the available computational resource, and good results previously obtained, the FLAP software represented to us the best choice for performing rapid and profitable virtual screening analysis. The application of other methods, such as docking, might result in the identification of different compounds, given their powerful search in the conformational space [75].…”

“…The main strength of these approaches lies in their ability of comparing multiple fingerprints, i.e. a mathematical representation of a molecule, and computing their similarity using similarity coefficients [75]. Given the increased availability of computer power, docking approaches have been also exploited for screening and for investigating the binding mode of small molecules into the target binding pocket.…”

“…Docking methods that have been developed and successfully applied in virtual screening experiments include AutoDock and AutoDock Vina [76]–[78]; DOCK [79]–[81]; FlexX [82]; Glide [83]; GOLD [84], [85]; Surflex [86], [87]. Their strengths and weaknesses, along with applications, have been reported by Bielska et al [75]. Our choice of using FLAP was based on the available computational resource and on the positive results previously obtained [88]–[97].…”

Insight into the Meligethes aeneus voltage‐sensitive sodium channel structure and an attempt to select the best pyrethroid ligands

“…20 'Protomol' generation and docking simulations were carried out with Surflex-Dock 2.6 software 34 [which predicts the binding affinity of the ligand-protein complex in the form of − log(K d )], based on the 'anchor-and-grow' algorithm for optimised structures of small molecules. 34,35 The top twenty conformations were obtained and scored, giving the information about certain pose docking affinity (the higher the score, the better the docking affinity). Based on scores and visual inspection, the best docking poses were selected.…”

eFindSite: Enhanced Fingerprint‐Based Virtual Screening Against Predicted Ligand Binding Sites in Protein Models

“…Of particular interest in modern drug discovery, this technique is cost‐effective in predicting potential hit compounds before undertaking experimental drug screening. Therefore, ligand virtual screening has become a standard practice in pharmaceutical industry as well as in drug related research 1. Currently, one of the most commonly used techniques in computer‐aided drug design is ligand virtual screening by molecular docking, which predicts physical interactions between receptor proteins and drug candidates at the atomic level 2,3.…”