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Int. J. Mol. Sci. 2016, 17(7), 1087; doi:10.3390/ijms17071087

Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions

1
Laboratory of Computational and Structural Physical-Chemistry for Nanosciences and QSAR, Department of Biology-Chemistry, West University of Timişoara, Pestalozzi Str. 16, RO-300115 Timisoara, Romania
2
Laboratory of Renewable Energies-Photovoltaics, R & D National Institute for Electrochemistry and Condensed Matter, Dr. A. Paunescu Podeanu Str. No. 144, RO-300569 Timisoara, Romania
3
Department of Medical Ambulatory, and Medical Emergencies, University of Medicine and Pharmacy “Victor Babes”, Avenue C. D. Loga No. 49, RO-300020 Timisoara, Romania
4
Institute of Chemistry Timișoara of the Romanian Academy, 24 Mihai Viteazul Bld., RO-300223 Timisoara, Romania
5
Department of Anatomy, Animal Physiology and Biophysics, Faculty of Biology, University of Bucharest, Str. 91-95th Independentei, RO-050095 Bucharest, Romania
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Tatyana Karabencheva-Christova
Received: 31 May 2016 / Revised: 20 June 2016 / Accepted: 27 June 2016 / Published: 8 July 2016
(This article belongs to the Special Issue Computational Eco, Bio, and Pharmaco-Toxicity 2016)
View Full-Text   |   Download PDF [3146 KB, uploaded 8 July 2016]   |  

Abstract

Within medicinal chemistry nowadays, the so-called pharmaco-dynamics seeks for qualitative (for understanding) and quantitative (for predicting) mechanisms/models by which given chemical structure or series of congeners actively act on biological sites either by focused interaction/therapy or by diffuse/hazardous influence. To this aim, the present review exposes three of the fertile directions in approaching the biological activity by chemical structural causes: the special computing trace of the algebraic structure-activity relationship (SPECTRAL-SAR) offering the full analytical counterpart for multi-variate computational regression, the minimal topological difference (MTD) as the revived precursor for comparative molecular field analyses (CoMFA) and comparative molecular similarity indices analysis (CoMSIA); all of these methods and algorithms were presented, discussed and exemplified on relevant chemical medicinal systems as proton pump inhibitors belonging to the 4-indolyl,2-guanidinothiazole class of derivatives blocking the acid secretion from parietal cells in the stomach, the 1-[(2-hydroxyethoxy)-methyl]-6-(phenylthio)thymine congeners’ (HEPT ligands) antiviral activity against Human Immunodeficiency Virus of first type (HIV-1) and new pharmacophores in treating severe genetic disorders (like depression and psychosis), respectively, all involving 3D pharmacophore interactions. View Full-Text
Keywords: quantitative structure-activity relationship (QSAR); multi-linear correlation; statistical correlation; chemical stericity; ligand binding; cross-validation; hydrophobicity; van der Waals interaction; molecular mechanism; drug design quantitative structure-activity relationship (QSAR); multi-linear correlation; statistical correlation; chemical stericity; ligand binding; cross-validation; hydrophobicity; van der Waals interaction; molecular mechanism; drug design
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MDPI and ACS Style

Putz, M.V.; Duda-Seiman, C.; Duda-Seiman, D.; Putz, A.-M.; Alexandrescu, I.; Mernea, M.; Avram, S. Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions. Int. J. Mol. Sci. 2016, 17, 1087.

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