Literature DB >> 23260675

The influence of R and S configurations of a series of amphetamine derivatives on quantitative structure-activity relationship models.

Maíra A C Fresqui1, Márcia M C Ferreira, Milan Trsic.   

Abstract

Chiral molecules need special attention in drug design. In this sense, the R and S configurations of a series of thirty-four amphetamines were evaluated by quantitative structure-activity relationship (QSAR). This class of compounds has antidepressant, anti-Parkinson and anti-Alzheimer effects against the enzyme monoamine oxidase A (MAO A). A set of thirty-eight descriptors, including electronic, steric and hydrophobic ones, were calculated. Variable selection was performed through the correlation coefficients followed by the ordered predictor selection (OPS) algorithm. Six descriptors (CHELPG atomic charges C3, C4 and C5, electrophilicity, molecular surface area and logP) were selected for both configurations and a satisfactory model was obtained by PLS regression with three latent variables with R(2)=0.73 and Q(2)=0.60, with external predictability Q(2)=0.68, and R(2)=0.76 and Q(2)=0.67 with external predictability Q(2)=0.50, for R and S configurations, respectively. To confirm the robustness of each model, leave-N-out cross validation (LNO) was carried out and the y-randomization test was used to check if these models present chance correlation. Moreover, both automated or a manual molecular docking indicate that the reaction of ligands with the enzyme occurs via pi-pi stacking interaction with Tyr407, inclined face-to-face interaction with Tyr444, while aromatic hydrogen-hydrogen interactions with Tyr197 are preferable for R instead of S configurations.
Copyright © 2012 Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 23260675     DOI: 10.1016/j.aca.2012.11.004

Source DB:  PubMed          Journal:  Anal Chim Acta        ISSN: 0003-2670            Impact factor:   6.558


  3 in total

Review 1.  In Silico Studies in Drug Research Against Neurodegenerative Diseases.

Authors:  Farahnaz Rezaei Makhouri; Jahan B Ghasemi
Journal:  Curr Neuropharmacol       Date:  2018       Impact factor: 7.363

2.  3D-QSAR and in-silico Studies of Natural Products and Related Derivatives as Monoamine Oxidase Inhibitors.

Authors:  Priyanka Dhiman; Neelam Malik; Anurag Khatkar
Journal:  Curr Neuropharmacol       Date:  2018       Impact factor: 7.363

Review 3.  Amphetamine Derivatives as Monoamine Oxidase Inhibitors.

Authors:  Miguel Reyes-Parada; Patricio Iturriaga-Vasquez; Bruce K Cassels
Journal:  Front Pharmacol       Date:  2020-01-23       Impact factor: 5.810

  3 in total

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