ArticleNucleic acids research2016
KLIFS: a structural kinase-ligand interaction database.
Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers.
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Who cites it
70 citing papers in PubMed.
- DeepKinomeWeb: a quantitative, panel-level platform for kinase inhibitor screening and selectivity profiling.Nucleic acids research · 2026Article
- Contact-Network Phenotyping of the CDK Family Reveals Selective Distal C-Lobe Contact Redistribution by Modern CDK5 Inhibitors and a Quantitative Selectivity Landscape against CDK2 and CDK1.Journal of chemical information and modeling · 2026Article
- Structure-Based Identification of JAK1-Selective Candidates Using Ensemble Docking and Interaction Analysis.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Natural Product-like Fragments Unlock Novel Chemotypes for a Kinase Target─Exploring Options beyond the Flatland.Journal of chemical information and modeling · 2026Article
- Frags2Drugs: A Novel In Silico Fragment-Based Approach to the Discovery of Kinase Inhibitors.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Assessing the accuracy of binding pose prediction for kinase proteins and 7-azaindole inhibitors: a study with AutoDock4, Vina, DOCK 6, and GNINA 1.0.RSC advances · 2025Article
- Leveraging artificial intelligence and machine learning in kinase inhibitor development: advances, challenges, and future prospects.RSC medicinal chemistry · 2025Review
- Unsupervised learning reveals landscape of local structural motifs across protein classes.Bioinformatics (Oxford, England) · 2025Article
- KinaseFusionDB: an integrative knowledge of kinase fusion proteins in multi-scales.Briefings in bioinformatics · 2025Article
- mdciao: Accessible Analysis and Visualization of Molecular Dynamics Simulation Data.PLoS computational biology · 2025Article
- Article
- Identification of a Potent CDK8 Inhibitor Using Structure-Based Virtual Screening.Journal of chemical information and modeling · 2025Article
- Docking-Informed Machine Learning for Kinome-wide Affinity Prediction.Journal of chemical information and modeling · 2024Article
- Exploring Extended Warheads toward Developing Cysteine-Targeted Covalent Kinase Inhibitors.Journal of chemical information and modeling · 2024Article
- Benchmarking Cross-Docking Strategies in Kinase Drug Discovery.Journal of chemical information and modeling · 2024Article
- A web portal for exploring kinase-substrate interactions.NPJ systems biology and applications · 2024Article
- Lessons learned during the journey of data: from experiment to model for predicting kinase affinity, selectivity, polypharmacology, and resistance.bioRxiv : the preprint server for biology · 2024Article
- Classifying protein kinase conformations with machine learning.Protein science : a publication of the Protein Society · 2024Article
- Computational Characterization of Membrane Proteins as Anticancer Targets: Current Challenges and Opportunities.International journal of molecular sciences · 2024Review
- Receptor-based pharmacophore modeling, molecular docking, synthesis and biological evaluation of novel VEGFR-2, FGFR-1, and BRAF multi-kinase inhibitors.BMC chemistry · 2024Article
10 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Protein kinases play a crucial role in cell signaling and are important drug targets in several therapeutic areas. The KLIFS database contains detailed structural kinase-ligand interaction information derived from all (>2900) structures of catalytic domains of human and mouse protein kinases deposited in the Protein Data Bank in order to provide insights into the structural determinants of kinase-ligand binding and selectivity. The kinase structures have been processed in a consistent manner by systematically analyzing the structural features and molecular interaction fingerprints (IFPs) of a predefined set of 85 binding site residues with bound ligands. KLIFS has been completely rebuilt and extended (>65% more structures) since its first release as a data set, including: novel automated annotation methods for (i) the assessment of ligand-targeted subpockets and the analysis of (ii) DFG and (iii) αC-helix conformations; improved and automated protocols for (iv) the generation of sequence/structure alignments, (v) the curation of ligand atom and bond typing for accurate IFP analysis and (vi) weekly database updates. KLIFS is now accessible via a website (http://klifs.vu-compmedchem.nl) that provides a comprehensive visual presentation of different types of chemical, biological and structural chemogenomics data, and allows the user to easily access, compare, search and download the data.
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