Literature DB >> 18636071

Pseudoreceptor models in drug design: bridging ligand- and receptor-based virtual screening.

Yusuf Tanrikulu1, Gisbert Schneider.   

Abstract

Rational drug design is based on explicit or implicit structure-activity relationship models. Typically, receptor-based or ligand-based strategies are pursued, depending on the information available about known ligands and the receptor structure. Pseudoreceptor models combine the advantages of these two strategies and represent a unifying concept for both receptor mapping and ligand matching. They can provide an entry point for structure-based modelling in drug discovery projects that lack a high-resolution structure of the target. Here, we review the field of pseudoreceptor modelling techniques along with recent hit and lead finding applications, and critically discuss prerequisites, advantages and limitations of the various approaches.

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Year:  2008        PMID: 18636071     DOI: 10.1038/nrd2615

Source DB:  PubMed          Journal:  Nat Rev Drug Discov        ISSN: 1474-1776            Impact factor:   84.694


  24 in total

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6.  Binary image representation of a ligand binding site: its application to efficient sampling of a conformational ensemble.

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8.  Synthetic inhibitor leads of human tropomyosin receptor kinase A (hTrkA).

Authors:  Govindan Subramanian; Rajendran Vairagoundar; Scott J Bowen; Nicole Roush; Theresa Zachary; Christopher Javens; Tracey Williams; Ann Janssen; Andrea Gonzales
Journal:  RSC Med Chem       Date:  2020-01-10

Review 9.  The importance of discerning shape in molecular pharmacology.

Authors:  Sandhya Kortagere; Matthew D Krasowski; Sean Ekins
Journal:  Trends Pharmacol Sci       Date:  2009-01-31       Impact factor: 14.819

10.  SiMMap: a web server for inferring site-moiety map to recognize interaction preferences between protein pockets and compound moieties.

Authors:  Yen-Fu Chen; Kai-Cheng Hsu; Shen-Rong Lin; Wen-Ching Wang; Yu-Chi Huang; Jinn-Moon Yang
Journal:  Nucleic Acids Res       Date:  2010-06-02       Impact factor: 16.971

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