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

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 dif...

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Autores principales: Putz, Mihai V., Duda-Seiman, Corina, Duda-Seiman, Daniel, Putz, Ana-Maria, Alexandrescu, Iulia, Mernea, Maria, Avram, Speranta
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4964463/
https://www.ncbi.nlm.nih.gov/pubmed/27399692
http://dx.doi.org/10.3390/ijms17071087
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author Putz, Mihai V.
Duda-Seiman, Corina
Duda-Seiman, Daniel
Putz, Ana-Maria
Alexandrescu, Iulia
Mernea, Maria
Avram, Speranta
author_facet Putz, Mihai V.
Duda-Seiman, Corina
Duda-Seiman, Daniel
Putz, Ana-Maria
Alexandrescu, Iulia
Mernea, Maria
Avram, Speranta
author_sort Putz, Mihai V.
collection PubMed
description 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.
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spelling pubmed-49644632016-08-03 Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions Putz, Mihai V. Duda-Seiman, Corina Duda-Seiman, Daniel Putz, Ana-Maria Alexandrescu, Iulia Mernea, Maria Avram, Speranta Int J Mol Sci Review 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. MDPI 2016-07-08 /pmc/articles/PMC4964463/ /pubmed/27399692 http://dx.doi.org/10.3390/ijms17071087 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Putz, Mihai V.
Duda-Seiman, Corina
Duda-Seiman, Daniel
Putz, Ana-Maria
Alexandrescu, Iulia
Mernea, Maria
Avram, Speranta
Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions
title Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions
title_full Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions
title_fullStr Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions
title_full_unstemmed Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions
title_short Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions
title_sort chemical structure-biological activity models for pharmacophores’ 3d-interactions
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4964463/
https://www.ncbi.nlm.nih.gov/pubmed/27399692
http://dx.doi.org/10.3390/ijms17071087
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