Literature DB >> 33084889

KLIFS: an overhaul after the first 5 years of supporting kinase research.

Georgi K Kanev1,2, Chris de Graaf3, Bart A Westerman2, Iwan J P de Esch1, Albert J Kooistra4.   

Abstract

Kinases are a prime target of drug development efforts with >60 drug approvals in the past two decades. Due to the research into this protein family, a wealth of data has been accumulated that keeps on growing. KLIFS-Kinase-Ligand Interaction Fingerprints and Structures-is a structural database focusing on how kinase inhibitors interact with their targets. The aim of KLIFS is to support (structure-based) kinase research through the systematic collection, annotation, and processing of kinase structures. Now, 5 years after releasing the initial KLIFS website, the database has undergone a complete overhaul with a new website, new logo, and new functionalities. In this article, we start by looking back at how KLIFS has been used by the research community, followed by a description of the renewed KLIFS, and conclude with showcasing the functionalities of KLIFS. Major changes include the integration of approved drugs and inhibitors in clinical trials, extension of the coverage to atypical kinases, and a RESTful API for programmatic access. KLIFS is available at the new domain https://klifs.net.
© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.

Entities:  

Year:  2021        PMID: 33084889      PMCID: PMC7778968          DOI: 10.1093/nar/gkaa895

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  41 in total

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Authors:  Susan S Taylor; Alexandr P Kornev
Journal:  Trends Biochem Sci       Date:  2010-10-23       Impact factor: 13.807

2.  KLIFS: a knowledge-based structural database to navigate kinase-ligand interaction space.

Authors:  Oscar P J van Linden; Albert J Kooistra; Rob Leurs; Iwan J P de Esch; Chris de Graaf
Journal:  J Med Chem       Date:  2013-09-20       Impact factor: 7.446

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Journal:  J Am Chem Soc       Date:  2018-11-06       Impact factor: 15.419

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Journal:  J Med Chem       Date:  2017-12-30       Impact factor: 7.446

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Journal:  Nucleic Acids Res       Date:  2019-01-08       Impact factor: 16.971

10.  Comparative Assessment of Protein Kinase Inhibitors in Public Databases and in PKIDB.

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Journal:  Molecules       Date:  2020-07-15       Impact factor: 4.411

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Review 5.  Druggable Transient Pockets in Protein Kinases.

Authors:  Koji Umezawa; Isao Kii
Journal:  Molecules       Date:  2021-01-27       Impact factor: 4.411

6.  Prediction of kinase inhibitors binding modes with machine learning and reduced descriptor sets.

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Review 10.  Trends in kinase drug discovery: targets, indications and inhibitor design.

Authors:  Misty M Attwood; Doriano Fabbro; Aleksandr V Sokolov; Stefan Knapp; Helgi B Schiöth
Journal:  Nat Rev Drug Discov       Date:  2021-08-05       Impact factor: 84.694

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