Comparing sixteen scoring functions for predicting biological activities of ligands for protein targets

Abstract

Accurately predicting relative binding affinities and biological potencies for ligands that interact with proteins remains a significant challenge for computational chemists. Most evaluations of docking and scoring algorithms have focused on enhancing ligand affinity for a protein by optimizing docking poses and enrichment factors during virtual screening. However, there is still relatively limited information on the accuracy of commercially available docking and scoring software programs for correctly predicting binding affinities and biological activities of structurally related inhibitors of different enzyme classes. Presented here is a comparative evaluation of eight molecular docking programs (Autodock Vina, Fitted, FlexX, Fred, Glide, GOLD, LibDock, MolDock) using sixteen docking and scoring functions to predict the rank-order activity of different ligand series for six pharmacologically important protein and enzyme targets (Factor Xa, Cdk2 kinase, Aurora A kinase, COX-2, pla2g2a, β Estrogen receptor). Use of Fitted gave an excellent correlation (Pearson 0.86, Spearman 0.91) between predicted and experimental binding only for Cdk2 kinase inhibitors. FlexX and GOLDScore produced good correlations (Pearson>0.6) for hydrophilic targets such as Factor Xa, Cdk2 kinase and Aurora A kinase. By contrast, pla2g2a and COX-2 emerged as difficult targets for scoring functions to predict ligand activities. Although possessing a high hydrophobicity in its binding site, β Estrogen receptor produced reasonable correlations using LibDock (Pearson 0.75, Spearman 0.68). These findings can assist medicinal chemists to better match scoring functions with ligand-target systems for hit-to-lead optimization using computer-aided drug design approaches.

Continuous microfluidic assortment of interactive ligands (CMAIL)

“…provides the key to a wide spectrum of applications, including drug development, genetic engineering, biochemistry, biotechnology, molecular biology, etc 123456…”

Comparing Drug Images and Repurposing Drugs with BioGPS and FLAPdock: The Thymidylate Synthase Case

“…The retained compounds were visually inspected and further filtered according to the complementarity of the pocket MIFs with the ligand pseudo‐MIFs, and to the number of hydrogen bonds formed with the residues lining the cavity. According to the literature and to studies we previously performed, the visual inspection of the results by trained operators can, indeed, strongly improve the success rate of screening and docking experiments …”

“…Onlym olecules with as core value highert han 0.90 werer etained, based on previous observations [data not shown].T he retained compounds were visually inspected and further filtered according to the complementarity of the pocket MIFs with the ligand pseudo-MIFs, andt ot he number of hydrogen bonds formed with the residues lining the cavity.A ccording to the literature and to studies we previously performed, the visual inspection of the resultsb yt rained operators can, indeed, strongly improve the successr ate of screening and docking experiments. [69][70][71][72] The ten most promising molecules were selected and are reportedi nF igure 6a nd Ta ble 1. Ligandsw erer etrieved from casein kinase IIa,L FA-1 integrin,h eat shock protein 90, b-secre- The ligands, quite different from each other in terms of shape, volumea nd chemical properties, present, predictably, diversei nteractions with the pocket residues.…”

Role of computer-aided drug design in modern drug discovery

“…Even though current scoring functions have greatly advanced, more development is necessary to increase accuracy in hit ranking. Performance of scoring functions varies depending on the purpose (scoring or ranking) and on the protein families and ligand series being considered (Wang et al 2003;Warren et al 2006;Cheng et al 2009;Cross et al 2009;Xu et al 2015). Combining the results from two or more scoring functions and forming a consensus has proved to be more beneficial in scoring and ranking compounds.…”