Integrating Structure‐ and Ligand‐Based Virtual Screening: Comparison of Individual, Parallel, and Fused Molecular Docking and Similarity Search Calculations on Multiple Targets

Abstract

Similarity searching is often used to preselect compounds for docking, thereby decreasing the size of screening databases. However, integrated structure- and ligand-based screening schemes are rare at present. Docking and similarity search calculations using 2D fingerprints were carried out in a comparative manner on nine target enzymes, for which significant numbers of diverse inhibitors could be obtained. In the absence of knowledge-based docking constraints and target-directed parameter optimisation, fingerprint searching displayed a clear preference over docking calculations. Alternative combinations of docking and similarity search results were investigated and found to further increase compound recall of individual methods in a number of instances. When the results of similarity searching and docking were combined, parallel selection of candidate compounds from individual rankings was generally superior to rank fusion. We suggest that complementary results from docking and similarity searching can be captured by integrated compound selection schemes.

In silicoscreening strategies for novel inhibitors of parasitic diseases

“…More recently, the combination of computational and experimental techniques has been explored as a useful approach for the identification of high quality 55 hits [9,[11][12][13]. This perspective paper outlines the progresses and applications of in silico screening strategies for the discovery of innovative chemotherapy agents for a variety of parasitic diseases, highlighting the challenges, limitations and future perspectives in medicinal chemistry.…”

“…Challenges in the field include: i) the generation of models 75 able to identify ligands that significantly differ from the original set of known actives and ii) the complexity to deal with the presence of activity cliffs (i.e., substantial differences in biological activity in very similar compounds) within structure--activity relationship (SAR) guided series [17]. However, 80 recent approaches using LBVS highlight its power and versatility for drug discovery being applied to the identification of new classes of compounds that significantly differ from the ligands used to derive the models or integrated with scaffold hopping as a relevant tool to increase structural diversity 85 and exploit unpatented chemical space [12,13,16].…”

“…The power of these integrated approaches is demonstrated by their enhanced performance, (5) as demonstrated by the discovery of a large number of biologically active compounds [9,13,29]. Fundamentally, these 295 methods differ in their speed and the necessary resources for their application.…”

“…The programs AUTODOCK and X-PLORE were 315 used to dock the molecules within the enzyme binding site, leading to the selection of a final set of 19 compounds for biochemical evaluation. Of these, 10 compounds were active against T. cruzi trypanothione reductase, 6 of which with IC 50 < 50 µM (e.g., 13 --18, Figure 3) [12]. The high hit rates 320 obtained and the novelty of the compounds discovered underscore the power of the application of LBVS as an efficient filter to rationally prioritize compounds for SBVS.…”

“…In this context, both approaches can be applied to the same library of compounds and the final prioritization is based on 360 a consensus scoring and comparison of the methods (e.g., the sum of the normalized scores or the combination of the ranked compounds lists) [13]. Similarly, the benefits of combining in silico and experimental HTS campaigns have recently been evaluated [4,29].…”