Literature DB >> 22970894

GRID-based three-dimensional pharmacophores I: FLAPpharm, a novel approach for pharmacophore elucidation.

Simon Cross1, Massimo Baroni, Laura Goracci, Gabriele Cruciani.   

Abstract

Pharmacophore elucidation approaches are routinely used in drug discovery, primarily with the aim of determining the three-dimensional arrangement of common features shared by ligands interacting at the site of interest; these features can then be used to investigate the structure-activity relationship between the ligands and also to screen for other molecules possessing the relevant features. Here we present a novel approach based on GRID molecular interaction fields and the derivative method FLAP that has been previously described, which provides a common reference framework to compare both small molecule ligands and macromolecular protein targets. Unlike classical pharmacophore elucidation approaches that extract simplistic molecular features, determine those which are common across the data set, and use these features to align the structures, FLAPpharm first aligns the structures and subsequently extracts the common interacting features in terms of their molecular interaction fields, pseudofields, and atomic points, representing the common pharmacophore as a more comprehensive pharmacophoric pseudomolecule. The approach is applied to a number of data sets to investigate performance in terms of reproducing the X-ray crystallography-based alignment, in terms of its discriminatory ability when applied to virtual screening and also to illustrate its ability to explain alternative binding modes. In part two of this publication, a comprehensive benchmark data set for pharmacophore elucidation is presented and the performance of FLAPpharm discussed.

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Year:  2012        PMID: 22970894     DOI: 10.1021/ci300153d

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  21 in total

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Authors:  Wenbo Yu; Sirish Kaushik Lakkaraju; E Prabhu Raman; Lei Fang; Alexander D MacKerell
Journal:  J Chem Inf Model       Date:  2015-02-06       Impact factor: 4.956

3.  MolAlign: an algorithm for aligning multiple small molecules.

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4.  Site-Identification by Ligand Competitive Saturation (SILCS) assisted pharmacophore modeling.

Authors:  Wenbo Yu; Sirish Kaushik Lakkaraju; E Prabhu Raman; Alexander D MacKerell
Journal:  J Comput Aided Mol Des       Date:  2014-03-08       Impact factor: 3.686

5.  AlphaSpace 2.0: Representing Concave Biomolecular Surfaces Using β-Clusters.

Authors:  Joseph Katigbak; Haotian Li; David Rooklin; Yingkai Zhang
Journal:  J Chem Inf Model       Date:  2020-02-11       Impact factor: 4.956

6.  Combining machine learning and quantum mechanics yields more chemically aware molecular descriptors for medicinal chemistry applications.

Authors:  Sara Tortorella; Emanuele Carosati; Giulia Sorbi; Giovanni Bocci; Simon Cross; Gabriele Cruciani; Loriano Storchi
Journal:  J Comput Chem       Date:  2021-08-19       Impact factor: 3.672

Review 7.  Application of Mathematical Modeling and Computational Tools in the Modern Drug Design and Development Process.

Authors:  Md Rifat Hasan; Ahad Amer Alsaiari; Burhan Zain Fakhurji; Mohammad Habibur Rahman Molla; Amer H Asseri; Md Afsar Ahmed Sumon; Moon Nyeo Park; Foysal Ahammad; Bonglee Kim
Journal:  Molecules       Date:  2022-06-29       Impact factor: 4.927

8.  Pharmacophore-based discovery of inhibitors of a novel drug/proton antiporter in human brain endothelial hCMEC/D3 cell line.

Authors:  Hélène Chapy; Laura Goracci; Philippe Vayer; Yannick Parmentier; Pierre-Alain Carrupt; Xavier Declèves; Jean-Michel Scherrmann; Salvatore Cisternino; Gabriele Cruciani
Journal:  Br J Pharmacol       Date:  2015-10-13       Impact factor: 8.739

9.  BioGPS descriptors for rational engineering of enzyme promiscuity and structure based bioinformatic analysis.

Authors:  Valerio Ferrario; Lydia Siragusa; Cynthia Ebert; Massimo Baroni; Marco Foscato; Gabriele Cruciani; Lucia Gardossi
Journal:  PLoS One       Date:  2014-10-29       Impact factor: 3.240

10.  Isozyme-specific ligands for O-acetylserine sulfhydrylase, a novel antibiotic target.

Authors:  Francesca Spyrakis; Ratna Singh; Pietro Cozzini; Barbara Campanini; Enea Salsi; Paolo Felici; Samanta Raboni; Paolo Benedetti; Gabriele Cruciani; Glen E Kellogg; Paul F Cook; Andrea Mozzarelli
Journal:  PLoS One       Date:  2013-10-22       Impact factor: 3.240

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