Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation

Jones, Gareth R.; Willett, Peter; Glen, Robert C.

doi:10.1016/s0022-2836(95)80037-9

Cited by 1,503 publications

(1,223 citation statements)

References 33 publications

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“…In 2003, Cavasotto and coworkers demonstrated the applicability of this scoring function to the identification of the binding site of retinal in bovine rhodopsin and to the discrimination between binders and nonbinders of rhodopsin [67]. Similarly, using molecular databases spiked with known binders, a number of studies based on combinations of different scoring functions (such as Gold [68], Dock [69], CScore (Tripos), Fresno [70], Score [71], FlexX [72], and PMF [66]) have demonstrated the applicability of molecular docking at GPCR models to virtual screening [9,10,73]. In agreement with the expectations set by these studies, a variety of docking programs and scoring functions have been successfully applied to the discovery of novel ligands for a plethora of GPCRs, including neurorokinin [74,75], adrenergic [76], chemokine [75,77], dopamine [75], serotonin [75,78], cannabinoid [79], and free fatty acid receptors [80], among others.…”

Section: Structure-based Methodologiesmentioning

confidence: 99%

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Costanzi

Tikhonova

Harden

2008

J Comput Aided Mol Des

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SummaryAccurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

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Section: Structure-based Methodologiesmentioning

confidence: 99%

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Costanzi

Tikhonova

Harden

2008

J Comput Aided Mol Des

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“…For this process, we used the molecular docking program GOLD (Genetic Optimization for Ligand Docking) [19,20] from the Cambridge Crystallographic Data Center. The X-ray structure of FP2 with its bound inhibitor E64 (PDB code: 3BPF) [21] was used and prepared for docking with Sybyl X 1.3 software.…”

Section: Molecular Dockingmentioning

confidence: 99%

Molecular docking and 3D-quantitative structure activity relationship analyses of peptidyl vinyl sulfones: Plasmodium Falciparum cysteine proteases inhibitors

Teixeira

Gomes

Couesnon

et al. 2011

J Comput Aided Mol Des

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Comparative molecular field analysis (CoM-FA) and comparative molecular similarity indices analysis (CoMSIA) based on three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were conducted on a series (39 molecules) of peptidyl vinyl sulfone derivatives as potential Plasmodium Falciparum cysteine proteases inhibitors. Two different methods of alignment were employed: (i) a receptor-docked alignment derived from the structure-based docking algorithm GOLD and (ii) a ligand-based alignment using the structure of one of the ligands derived from a crystal structure from the PDB databank. The best predictions were obtained for the receptor-docked alignment with a CoMFA standard model (q 2 = 0.696 and r 2 = 0.980) and with CoMSIA combined electrostatic, and hydrophobic fields (q 2 = 0.711 and r 2 = 0.992). Both models were validated by a test set of nine compounds and gave satisfactory predictive r 2 pred values of 0.76 and 0.74, respectively. CoMFA and CoM-SIA contour maps were used to identify critical regions where any change in the steric, electrostatic, and hydrophobic fields may affect the inhibitory activity, and to highlight the key structural features required for biological activity. Moreover, the results obtained from 3D-QSAR analyses were superimposed on the Plasmodium Falciparum cysteine proteases active site and the main interactions were studied. The present work provides extremely useful guidelines for future structural modifications of this class of compounds towards the development of superior antimalarials.

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“…In order to confirm the interacting capability of these compounds towards hAChE, the manual docking analysis was carried out using the Genetic Optimization for Ligand Docking (GOLD) V4.0.1 [45,46] docking suite, which employs a genetic algorithm to find the different ligand binding modes. The crystal structure of hAChE (PDB ID: 1B41) [47] was chosen for docking analysis.…”

Section: Molecular Dockingmentioning

confidence: 99%

Synthesis and in silico evaluation of 1N-methyl-1S-methyl-2-nitroethylene (NMSM) derivatives against Alzheimer disease: to understand their interacting mechanism with acetylcholinesterase

et al. 2012

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Anomalous action of human acetylcholinesterase (hAChE) in Alzheimer's disease (AD) was restrained by various AChE inhibitors, of which the specific and potent lead candidate Donepezil is used for treating the disease AD. Besides the specificity, the observed undesirable side effects caused by Donepezil invoked the quest for new lead molecules with the increased potency and specificity for AChE. The present study elucidates the potency of six 1N-methyl-1S-methyl-2-nitroethylene (NMSM) derivatives to form a specific interaction with the peripheral anionic site and catalytic anionic subsite residues of hAChE. The NMSMs were prepared in good yield from 1,1-di(methylsulfanyl)-2-nitroethylene and primary amine (or) amino acid esters. In silico interaction analysis reveals specific and potent interactions between hAChE and selected ligand molecules. The sitespecific interactions formed between these molecules also results in a conformational change in the orientation of active site residues of hAChE, which prevents them from being accessed by beta-amyloid protein (Aβ), which is a causative agent for amyloid plaque formation and acetylcholine (ACh). In silico interaction analysis between the ligand-bounded hAChE with Aß and ACh confirms this observation. The variation in the conformation of hAChE associated with the decreased ability of Aβ and ACh to access the respective functional residues of hAChE induced by the novel NMSMs favors their selection for in vivo analysis to present themselves as new members of hAChE inhibitors.

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Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation

Cited by 1,503 publications

References 33 publications

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Molecular docking and 3D-quantitative structure activity relationship analyses of peptidyl vinyl sulfones: Plasmodium Falciparum cysteine proteases inhibitors

Synthesis and in silico evaluation of 1N-methyl-1S-methyl-2-nitroethylene (NMSM) derivatives against Alzheimer disease: to understand their interacting mechanism with acetylcholinesterase

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