Evaluating Docking Methods for Prediction of Binding Affinities of Small Molecules to the G Protein<i>βγ</i>Subunits

Park, Min Sun; Dessal, Axel L.; Smrcka, Alan V.; Stern, Harry A.

doi:10.1021/ci800384q

Cited by 14 publications

(12 citation statements)

References 69 publications

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“…Albeit in some publications certain correlation between IC 50 and docking scores can be found, it must be considered that for the above reason, a high correlation between docking score and IC 50 must not be always expected [37].…”

Section: Enzyme Inhibition Assaymentioning

confidence: 99%

Novel inhibitors to Taenia solium Cu/Zn superoxide dismutase identified by virtual screening

García-Gutiérrez

Landa-Piedra

Rodrı́guez-Romero

et al. 2011

J Comput Aided Mol Des

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We describe in this work a successful virtual screening and experimental testing aimed to the identification of novel inhibitors of superoxide dismutase of the worm Taenia solium (TsCu/Zn-SOD), a human parasite. Conformers from LeadQuest(®) database of drug-like compounds were selected and then docked on the surface of TsCu/Zn-SOD. Results were screened looking for ligand contacts with receptor side-chains not conserved in the human homologue, with a subsequent development of a score optimization by a set of energy minimization steps, aimed to identify lead compounds for in vitro experiments. Six out of fifty experimentally tested compounds showed μM inhibitory activity toward TsCu/Zn-SOD. Two of them showed species selectivity since did not inhibit the homologous human enzyme when assayed in vitro.

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Section: Enzyme Inhibition Assaymentioning

confidence: 99%

Novel inhibitors to Taenia solium Cu/Zn superoxide dismutase identified by virtual screening

García-Gutiérrez

Landa-Piedra

Rodrı́guez-Romero

et al. 2011

J Comput Aided Mol Des

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“…The CS strategy could overcome to some extent the limitations faced by the single-scoring approach, for example, the inconsistent performances across different protein targets and chemical classes ( Moitessier et al, 2009 ). Moreover, CS is frequently used in some extent together with ensemble docking methodology, where different scores are predicted for different conformations of the protein target under investigation ( Park et al, 2009 , 2010 ; Paulsen and Anderson, 2009 ; Kelemen et al, 2016 ; Baumgartner and Evans, 2018 ; Li D.-D. et al, 2018 ).…”

Section: Challenging Topics and Promising Strategiesmentioning

confidence: 99%

Empirical Scoring Functions for Structure-Based Virtual Screening: Applications, Critical Aspects, and Challenges

2018

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Structure-based virtual screening (VS) is a widely used approach that employs the knowledge of the three-dimensional structure of the target of interest in the design of new lead compounds from large-scale molecular docking experiments. Through the prediction of the binding mode and affinity of a small molecule within the binding site of the target of interest, it is possible to understand important properties related to the binding process. Empirical scoring functions are widely used for pose and affinity prediction. Although pose prediction is performed with satisfactory accuracy, the correct prediction of binding affinity is still a challenging task and crucial for the success of structure-based VS experiments. There are several efforts in distinct fronts to develop even more sophisticated and accurate models for filtering and ranking large libraries of compounds. This paper will cover some recent successful applications and methodological advances, including strategies to explore the ligand entropy and solvent effects, training with sophisticated machine-learning techniques, and the use of quantum mechanics. Particular emphasis will be given to the discussion of critical aspects and further directions for the development of more accurate empirical scoring functions.

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“…eral research groups for virtual screening, 14,15) CONSEN-SUS-DOCK calculates these three scoring functions simultaneously. The consensus score of score 1, score 2 and score 3 is defined by MAX (score 1, score 2, score 3), where MAX ( ) means the maximum value.…”

Section: Evaluation Of Docking Calculations On X-ray Structures Usingmentioning

confidence: 99%

Evaluation of Docking Calculations on X-Ray Structures Using CONSENSUS-DOCK

Okamoto

Masuda

Muroya

et al. 2010

CHEMICAL & PHARMACEUTICAL BULLETIN

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NoteDuring the past decade, in silico approaches for seeking active compounds to target proteins have become more popular in drug discovery due to significant advances in computer hardware and software. There are a large number of docking programs (e.g., DOCK, 1) AutoDock, 2) GOLD, 3) GLIDE, 4) Ph-DOCK 5) ), and many applications of these programs have been reported by various research groups. In major pharmaceutical companies, in silico approaches have been used to solve complicated drug design problems, leading to an increased appreciation and understanding of in silico approaches among medicinal chemists, pharmacological scientists and other researchers. 6,7)We have applied several in silico approaches to advance our drug discovery efforts, including structure-based virtual screening (SBVS), ligand-based drug design (LBDD), fragment-based drug design (FBDD), and assessment of proteinprotein interactions (PPI). 8) We have been particularly successful in efficiently finding active compounds for various target proteins (e.g., GPCR, kinase) by SBVS, and have generally used an in-house docking program, CONSENSUS-DOCK.9) CONSENSUS-DOCK is a customized version of the DOCK4 program in which three scoring functions (DOCK4, FlexX 10) and PMF 11) ) and consensus scoring have been implemented. We previously reported the advantages of CONSENSUS-DOCK over DOCK4 in SBVS for a target protein, death-associated protein kinases (DAPKs).9) To confirm the advantages of CONSENSUS-DOCK by using other types of proteins, we compare the docking calculation results obtained using CONSENSUS-DOCK and DOCK4 for 16 Xray crystal structures in this paper. We report that CONSEN-SUS-DOCK provided better docking calculations than DOCK4 for most of the 16 X-ray structures chosen from the Protein Data Bank (PDB). 12)In CONSENSUS-DOCK, three scoring functions (DOCK4, FlexX and PMF) are implemented in the DOCK4 program and consensus scoring 13) is performed in the pose selection, and the compounds are ranked to reduce the weaknesses of each scoring function. DOCK4 is a force field based docking program developed by Kuntz et al. 1) and is used for automated molecular docking of flexible molecules. DOCK4 uses electrostatic and van der Waals interactions evaluated over a grid to calculate the binding energy of a docked conformation. FlexX is an empirical scoring function and is implemented in the SYBYL package. Standard parameters of FlexX's scoring function are used for iterative growing and subsequent scoring of docking poses. PMF is a knowledge-based scoring function that combines the accuracy of empirical scoring functions with the advantage of higher generality and therefore wider applicability.Various kinds of consensus scores have been used by sev- We are participating in the challenge of identifying active compounds for target proteins using structurebased virtual screening (SBVS). We use an in-house customized docking program, CONSENSUS-DOCK, which is a customized version of the DOCK4 program in which three scoring functions (DOCK4, FlexX a...

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Evaluating Docking Methods for Prediction of Binding Affinities of Small Molecules to the G ProteinβγSubunits

Cited by 14 publications

References 69 publications

Novel inhibitors to Taenia solium Cu/Zn superoxide dismutase identified by virtual screening

Novel inhibitors to Taenia solium Cu/Zn superoxide dismutase identified by virtual screening

Empirical Scoring Functions for Structure-Based Virtual Screening: Applications, Critical Aspects, and Challenges

Evaluation of Docking Calculations on X-Ray Structures Using CONSENSUS-DOCK

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