Literature DB >> 20838973

Pharmacophore-based virtual screening.

Dragos Horvath1.   

Abstract

This chapter is a review of the most recent developments in the field of pharmacophore modeling, covering both methodology and application. Pharmacophore-based virtual screening is nowadays a mature technology, very well accepted in the medicinal chemistry laboratory. Nevertheless, like any empirical approach, it has specific limitations and efforts to improve the methodology are still ongoing. Fundamentally, the core idea of "stripping" functional groups of their actual chemical nature in order to classify them into very few pharmacophore types, according to their dominant physico-chemical features, is both the main advantage and the main drawback of pharmacophore modeling. The advantage is the one of simplicity - the complex nature of noncovalent ligand binding interactions is rendered intuitive and comprehensible by the human mind. Although computers are much better suited for comparisons of pharmacophore patterns, a chemist's intuition is primarily scaffold-oriented. Its underlying simplifications render pharmacophore modeling unable to provide perfect predictions of ligand binding propensities - not even if all its subsisting technical problems would be solved. Each step in pharmacophore modeling and exploitation has specific drawbacks: from insufficient or inaccurate conformational sampling to ambiguities in pharmacophore typing (mainly due to uncertainty regarding the tautomeric/protonation status of compounds), to computer time limitations in complex molecular overlay calculations, and to the choice of inappropriate anchoring points in active sites when ligand cocrystals structures are not available. Yet, imperfections notwithstanding, the approach is accurate enough in order to be practically useful and actually is the most used virtual screening technique in medicinal chemistry - notably for "scaffold hopping" approaches, allowing the discovery of new chemical classes carriers of a desired biological activity.

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Year:  2011        PMID: 20838973     DOI: 10.1007/978-1-60761-839-3_11

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  10 in total

1.  Self-organizing ontology of biochemically relevant small molecules.

Authors:  Leonid L Chepelev; Janna Hastings; Marcus Ennis; Christoph Steinbeck; Michel Dumontier
Journal:  BMC Bioinformatics       Date:  2012-01-06       Impact factor: 3.169

2.  Benchmarking methods and data sets for ligand enrichment assessment in virtual screening.

Authors:  Jie Xia; Ermias Lemma Tilahun; Terry-Elinor Reid; Liangren Zhang; Xiang Simon Wang
Journal:  Methods       Date:  2014-12-03       Impact factor: 3.608

3.  Maximal Unbiased Benchmarking Data Sets for Human Chemokine Receptors and Comparative Analysis.

Authors:  Jie Xia; Terry-Elinor Reid; Song Wu; Liangren Zhang; Xiang Simon Wang
Journal:  J Chem Inf Model       Date:  2018-05-08       Impact factor: 4.956

Review 4.  G-quadruplex virtual drug screening: A review.

Authors:  Robert C Monsen; John O Trent
Journal:  Biochimie       Date:  2018-06-30       Impact factor: 4.079

5.  Fragment-based Shape Signatures: a new tool for virtual screening and drug discovery.

Authors:  Randy J Zauhar; Eleonora Gianti; William J Welsh
Journal:  J Comput Aided Mol Des       Date:  2013-12-24       Impact factor: 3.686

6.  Electrostatic similarities between protein and small molecule ligands facilitate the design of protein-protein interaction inhibitors.

Authors:  Arnout Voet; Francois Berenger; Kam Y J Zhang
Journal:  PLoS One       Date:  2013-10-10       Impact factor: 3.240

7.  An unbiased method to build benchmarking sets for ligand-based virtual screening and its application to GPCRs.

Authors:  Jie Xia; Hongwei Jin; Zhenming Liu; Liangren Zhang; Xiang Simon Wang
Journal:  J Chem Inf Model       Date:  2014-05-01       Impact factor: 4.956

8.  WONKA: objective novel complex analysis for ensembles of protein-ligand structures.

Authors:  A R Bradley; I D Wall; F von Delft; D V S Green; C M Deane; B D Marsden
Journal:  J Comput Aided Mol Des       Date:  2015-09-19       Impact factor: 3.686

Review 9.  Hierarchical virtual screening approaches in small molecule drug discovery.

Authors:  Ashutosh Kumar; Kam Y J Zhang
Journal:  Methods       Date:  2014-07-27       Impact factor: 3.608

10.  Pharmacophore-based virtual screening, synthesis, biological evaluation, and molecular docking study of novel pyrrolizines bearing urea/thiourea moieties with potential cytotoxicity and CDK inhibitory activities.

Authors:  Ahmed M Shawky; Nashwa A Ibrahim; Mohammed A S Abourehab; Ashraf N Abdalla; Ahmed M Gouda
Journal:  J Enzyme Inhib Med Chem       Date:  2021-12       Impact factor: 5.051

  10 in total

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