Literature DB >> 22130009

Yeast two-hybrid methods and their applications in drug discovery.

Amel Hamdi1, Pierre Colas.   

Abstract

The yeast two-hybrid (Y2H) method was first described over 20 years ago. It soon appeared as a major methodological breakthrough in the discovery and analysis of protein interactions, which play a pivotal role in all biological phenomena. Since its inception the Y2H method has constantly evolved and has inspired various assays that have found multiple applications of interest for drug discovery. Y2H methods are used to identify and validate therapeutic targets, discover protein interaction modulators, identify drug targets, and select combinatorial recognition molecules, which themselves find a wide range of applications. We review here the different transcriptional Y2H methods that are directly useful to drug discovery. Most should be increasingly used in the future as they continue to evolve to harness other methodological and conceptual advances.
Copyright © 2011 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2011        PMID: 22130009     DOI: 10.1016/j.tips.2011.10.008

Source DB:  PubMed          Journal:  Trends Pharmacol Sci        ISSN: 0165-6147            Impact factor:   14.819


  23 in total

1.  FKBP12: A partner of Snx10 required for vesicular trafficking in osteoclasts.

Authors:  Ricardo A Battaglino; Prakash Jha; Farhath Sultana; Weimin Liu; Leslie R Morse
Journal:  J Cell Biochem       Date:  2019-03-19       Impact factor: 4.429

Review 2.  Protein-protein interactions: switch from classical methods to proteomics and bioinformatics-based approaches.

Authors:  Armand G Ngounou Wetie; Izabela Sokolowska; Alisa G Woods; Urmi Roy; Katrin Deinhardt; Costel C Darie
Journal:  Cell Mol Life Sci       Date:  2013-04-12       Impact factor: 9.261

Review 3.  An overview of bioinformatics methods for modeling biological pathways in yeast.

Authors:  Jie Hou; Lipi Acharya; Dongxiao Zhu; Jianlin Cheng
Journal:  Brief Funct Genomics       Date:  2015-10-17       Impact factor: 4.241

Review 4.  Cell-Based Assay Design for High-Content Screening of Drug Candidates.

Authors:  Gregory Nierode; Paul S Kwon; Jonathan S Dordick; Seok-Joon Kwon
Journal:  J Microbiol Biotechnol       Date:  2016-02       Impact factor: 2.351

Review 5.  Peptide aptamers: development and applications.

Authors:  Sergey Reverdatto; David S Burz; Alexander Shekhtman
Journal:  Curr Top Med Chem       Date:  2015       Impact factor: 3.295

6.  Reverse yeast two-hybrid system to identify mammalian nuclear receptor residues that interact with ligands and/or antagonists.

Authors:  Hao Li; Wei Dou; Emil Padikkala; Sridhar Mani
Journal:  J Vis Exp       Date:  2013-11-15       Impact factor: 1.355

Review 7.  Investigation of stable and transient protein-protein interactions: Past, present, and future.

Authors:  Armand G Ngounou Wetie; Izabela Sokolowska; Alisa G Woods; Urmi Roy; Joseph A Loo; Costel C Darie
Journal:  Proteomics       Date:  2013-01-18       Impact factor: 3.984

Review 8.  The Methods Employed in Mass Spectrometric Analysis of Posttranslational Modifications (PTMs) and Protein-Protein Interactions (PPIs).

Authors:  Rama R Yakubu; Edward Nieves; Louis M Weiss
Journal:  Adv Exp Med Biol       Date:  2019       Impact factor: 2.622

9.  Utilizing graph machine learning within drug discovery and development.

Authors:  Thomas Gaudelet; Ben Day; Arian R Jamasb; Jyothish Soman; Cristian Regep; Gertrude Liu; Jeremy B R Hayter; Richard Vickers; Charles Roberts; Jian Tang; David Roblin; Tom L Blundell; Michael M Bronstein; Jake P Taylor-King
Journal:  Brief Bioinform       Date:  2021-11-05       Impact factor: 11.622

10.  Kinase Substrate Sensor (KISS), a mammalian in situ protein interaction sensor.

Authors:  Sam Lievens; Sarah Gerlo; Irma Lemmens; Dries J H De Clercq; Martijn D P Risseeuw; Nele Vanderroost; Anne-Sophie De Smet; Elien Ruyssinck; Eric Chevet; Serge Van Calenbergh; Jan Tavernier
Journal:  Mol Cell Proteomics       Date:  2014-08-25       Impact factor: 5.911

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