Literature DB >> 19396737

Databases of protein-protein interactions and their use in drug discovery.

Gloria Fuentes1, Julen Oyarzabal, Ana M Rojas.   

Abstract

Proteins rarely act alone. With the development of experimental technologies, researchers have started to map the interactions of proteins in different organisms. The data gathered constitute potential frameworks for system-based drug discovery. The possibility of targeting protein-protein interactions with specific drugs raises expectations of huge impact in the therapeutics field, despite the large quantity of research still necessary to delineate the complete interactome of a single cell. This review summarizes some concepts relating to protein-protein interfaces in relation to drug discovery, and discusses studies aiming to develop protein-protein interaction modulators through the combination of in silico and in vitro screening experiments.

Mesh:

Substances:

Year:  2009        PMID: 19396737

Source DB:  PubMed          Journal:  Curr Opin Drug Discov Devel        ISSN: 1367-6733


  10 in total

Review 1.  A network perspective on unraveling the role of TRP channels in biology and disease.

Authors:  Jung Nyeo Chun; Jin Muk Lim; Young Kang; Eung Hee Kim; Young-Cheul Shin; Hong-Gee Kim; Dayk Jang; Dongseop Kwon; Soo-Yong Shin; Insuk So; Ju-Hong Jeon
Journal:  Pflugers Arch       Date:  2013-05-16       Impact factor: 3.657

Review 2.  The role of HTS in drug discovery at the University of Michigan.

Authors:  Martha J Larsen; Scott D Larsen; Andrew Fribley; Jolanta Grembecka; Kristoff Homan; Anna Mapp; Andrew Haak; Zaneta Nikolovska-Coleska; Jeanne A Stuckey; Duxin Sun; David H Sherman
Journal:  Comb Chem High Throughput Screen       Date:  2014-03       Impact factor: 1.339

Review 3.  An overview of computational life science databases & exchange formats of relevance to chemical biology research.

Authors:  Aaron Smalter Hall; Yunfeng Shan; Gerald Lushington; Mahesh Visvanathan
Journal:  Comb Chem High Throughput Screen       Date:  2013-03       Impact factor: 1.339

Review 4.  Artificial intelligence and machine-learning approaches in structure and ligand-based discovery of drugs affecting central nervous system.

Authors:  Vertika Gautam; Anand Gaurav; Neeraj Masand; Vannajan Sanghiran Lee; Vaishali M Patil
Journal:  Mol Divers       Date:  2022-07-11       Impact factor: 3.364

5.  Impact of nonnatural amino acid mutagenesis on the in vivo function and binding modes of a transcriptional activator.

Authors:  Chinmay Y Majmudar; Lori W Lee; Jody K Lancia; Adaora Nwokoye; Qian Wang; Amberlyn M Wands; Lei Wang; Anna K Mapp
Journal:  J Am Chem Soc       Date:  2009-10-14       Impact factor: 15.419

6.  Sequence context and crosslinking mechanism affect the efficiency of in vivo capture of a protein-protein interaction.

Authors:  Jody K Lancia; Adaora Nwokoye; Amanda Dugan; Cassandra Joiner; Rachel Pricer; Anna K Mapp
Journal:  Biopolymers       Date:  2014-04       Impact factor: 2.505

Review 7.  Physiologically based pharmacokinetic models: integration of in silico approaches with micro cell culture analogues.

Authors:  A Chen; M L Yarmush; T Maguire
Journal:  Curr Drug Metab       Date:  2012-07       Impact factor: 3.731

8.  TRIP Database: a manually curated database of protein-protein interactions for mammalian TRP channels.

Authors:  Young-Cheul Shin; Soo-Yong Shin; Insuk So; Dongseop Kwon; Ju-Hong Jeon
Journal:  Nucleic Acids Res       Date:  2010-09-17       Impact factor: 16.971

9.  Targeting protein-protein interactions for parasite control.

Authors:  Christina M Taylor; Kerstin Fischer; Sahar Abubucker; Zhengyuan Wang; John Martin; Daojun Jiang; Marc Magliano; Marie-Noëlle Rosso; Ben-Wen Li; Peter U Fischer; Makedonka Mitreva
Journal:  PLoS One       Date:  2011-04-27       Impact factor: 3.240

10.  Masking MALT1: the paracaspase's potential for cancer therapy.

Authors:  Domagoj Vucic; Vishva M Dixit
Journal:  J Exp Med       Date:  2009-10-19       Impact factor: 14.307

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.