Article

Docking and scoring in virtual screening for drug discovery: Methods and applications. Nat. Rev. Drug Discov. 3, 935-949

Department of Computer-Aided Drug Discovery, Albany Molecular Research, Inc., 21 Corporate Circle, Albany, New York 12212-5098, USA.
Nature Reviews Drug Discovery (Impact Factor: 41.91). 12/2004; 3(11):935-49. DOI: 10.1038/nrd1549
Source: PubMed

ABSTRACT

Computational approaches that 'dock' small molecules into the structures of macromolecular targets and 'score' their potential complementarity to binding sites are widely used in hit identification and lead optimization. Indeed, there are now a number of drugs whose development was heavily influenced by or based on structure-based design and screening strategies, such as HIV protease inhibitors. Nevertheless, there remain significant challenges in the application of these approaches, in particular in relation to current scoring schemes. Here, we review key concepts and specific features of small-molecule-protein docking methods, highlight selected applications and discuss recent advances that aim to address the acknowledged limitations of established approaches.

Download full-text

Full-text

Available from: Douglas B Kitchen
  • Source
    • "Nevertheless, there remain significant challenges in the application of these approaches, in particular in relation to current scoring schemes. Here, we review key concepts and specific features of small-molecule–protein docking methods, highlight selected applications and discuss recent advances that aim to address the acknowledged limitations of established approaches (Kitchen et al., 2004). The aim of the present study to predict whether Podocarpusflavone A (isolated from "
    [Show abstract] [Hide abstract]
    ABSTRACT: This study aims to predict whether Podocarpusflavone A (isolated from Podocarpus imbricatus), Podocarpusflavone B (isolated from Psilotum nudum), Robustaflavone (isolated from Selaginella sellowii), Robustaflavone-7-methyl ether (isolated from Podocarpus imbricatus), Sciadopitysin (isolated from Taxus cuspidata) and β-sitosterol (isolated from Rubus suavissimus) have thrombolytic effects, which were done by using two in silico tools PASS prediction and Molecular docking. These six were analyzed by the PASS prediction for their thrombolytic activity and found wide range of activity. Podocarpusflavone A and Podocarpusflavone B was the best compound for thrombolytic effect from all the compounds, though it had much bigger Pa value (0.256) than Pi value (0.022). As a result, Podocarpusflavone A and Podocarpusflavone B both had 11.64 ratio (Pa : Pi) value. A wide range of docking score found during molecular docking by CPI server. Podocarpusflavone A, Podocarpusflavone B, Robustaflavone, Robustaflavone-7-methyl ether, Sciadopitysin and β-sitosterol showed the docking score -9.5, -9.5, -9.2, -9.6, -9.9 and -7.9, respectively. Data from the both in silico models showed similar value for the same compound, because Podocarpusflavone A and B showed high value and β-sitosterol showed low value in both in silico models. All the dates showed that Podocarpusflavone A and B are the best compounds for thrombosis management, as they possessed higher value both in PASS prediction and Molecular docking. Sciadopitysin also showed well docking score (-9.9) and probability of activity (0.243) for thrombolytic activity in PASS prediction. Further in vitro and in vivo investigation need to identify whether Podocarpusflavone compounds, Sciadopitysin and other compounds have thrombolytic effect or not and from them, which is best one for thrombosis treatment.
    Full-text · Article · Feb 2016
  • Source
    • "In general terms, it is usually a problem of selection of predicted models that are closest to the native (real) complex out of a large set of diverse models. There are three kinds of scoring functions: physics-based [65], empirical [66], and knowledge-based [67]. The former two calculate binding energy as a sum of individual energy terms. "

    Full-text · Dataset · Oct 2015
  • Source
    • "The first one is an aaNAT product and shows that this enzyme holds a special place in the insect cuticle sclerotization [24] [25]. Molecular Docking studies allow us to analyze the orientation of the molecule (ligand/inhibitor), describing the affinity of a given molecule to a protein-binding site [26]. Virtual screening of chemicals is one of the main techniques currently used in Drug Discovery, testing natural and synthesized compounds [27] [28]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Background: Dengue is a Neglected tropical disease (NTDs) with high incidence in Brazil. This disease is caused by Dengue virus and is transmitted by Aedes aegypti mosquito. The search for new approaches for controlling of this disease is the subject of numerous studies. The aaNAT is a key enzyme in the metabolism of A. aegypti and is crucial in the sclerotization process, as well as regulation of circadian rhythm and inactivation of neurotransmitters. Computational techniques applied to studies of biological systems become an effective weapon in the mapping and manage- ment of 3D data structures, giving direction and guidance of potential ligands that can form stable complexes with targets of interest, using a Molecular Docking approach. The present study was conducted by a virtual screening, followed by docking calculations, in order to find molecules that could inhibit aaNAT. In this study, we used available compounds in SAM database (Bioinformatics and Medicinal Chemistry Laboratory—Southwest Bahia State University, Jequié-Bahia, Brazil), PubChem and ZINC. Results: The result of dockings with selected ligands showed good energy af- finities, presenting potential inhibitory interactions with the enzyme active site. Conclusions: The Coa-S-acetyl-tryptamine and 3-indoleacriloil-coenzyme-A showed the same binding energies −8.9 Kcal/Mol and were described as possible inhibitors of aaNAT.
    Full-text · Article · Sep 2015 · Computational Molecular Bioscience
Show more