ArticlePloS one2015
Molecular Determinants Underlying Binding Specificities of the ABL Kinase Inhibitors: Combining Alanine Scanning of Binding Hot Spots with Network Analysis of Residue Interactions and Coevolution.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 37 citations in OpenAlex.
- Exploring proteins and protein-ligand complexes through residue interaction networks.Nature protocols · 2026Review
- Decoding the allosteric grammar of protein kinases: A dual-stream framework integrating protein language models and energy landscape frustration analysis.Protein science : a publication of the Protein Society · 2026Article
- Electric Field-Driven Modulation of Nanomechanical Interactions Between Tyrosine Kinase Inhibitors and Human Serum Albumin: Insights from AFM-Based Force Spectroscopy.Molecules (Basel, Switzerland) · 2025Article
- Key interaction networks: Identifying evolutionarily conserved non-covalent interaction networks across protein families.Protein science : a publication of the Protein Society · 2024Article
- Probing conformational landscapes and mechanisms of allosteric communication in the functional states of the ABL kinase domain using multiscale simulations and network-based mutational profiling of allosteric residue potentials.The Journal of chemical physics · 2022Article
- Coevolution, Dynamics and Allostery Conspire in Shaping Cooperative Binding and Signal Transmission of the SARS-CoV-2 Spike Protein with Human Angiotensin-Converting Enzyme 2.International journal of molecular sciences · 2020Article
- Spectral analysis of molecular dynamics simulations on PDZ: MD sectors.Journal of biomolecular structure & dynamics · 2020Article
- A combined computational and experimental strategy identifies mutations conferring resistance to drugs targeting the BCR-ABL fusion protein.Communications biology · 2020Article
- Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning.Frontiers in molecular biosciences · 2020Review
- Combining the Allosteric Inhibitor Asciminib with Ponatinib Suppresses Emergence of and Restores Efficacy against Highly Resistant BCR-ABL1 Mutants.Cancer cell · 2019Article
- ProSNEx: a web-based application for exploration and analysis of protein structures using network formalism.Nucleic acids research · 2019Article
- Network Analysis of RAD51 Proteins in Metazoa and the Evolutionary Relationships With Their Archaeal Homologs.Frontiers in genetics · 2018Article
- Protein Kinase Targets in Breast Cancer.International journal of molecular sciences · 2017Review
- Evolutionary, computational, and biochemical studies of the salicylaldehyde dehydrogenases in the naphthalene degradation pathway.Scientific reports · 2017Article
- Computational Analysis of Residue Interaction Networks and Coevolutionary Relationships in the Hsp70 Chaperones: A Community-Hopping Model of Allosteric Regulation and Communication.PLoS computational biology · 2017Article
- Integrative View of the Diversity and Evolution of SWEET and SemiSWEET Sugar Transporters.Frontiers in plant science · 2017Article
- c-Abl and Parkinson's Disease: Mechanisms and Therapeutic Potential.Journal of Parkinson's disease · 2017Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantifying binding specificity and drug resistance of protein kinase inhibitors is of fundamental importance and remains highly challenging due to complex interplay of structural and thermodynamic factors. In this work, molecular simulations and computational alanine scanning are combined with the network-based approaches to characterize molecular determinants underlying binding specificities of the ABL kinase inhibitors. The proposed theoretical framework unveiled a relationship between ligand binding and inhibitor-mediated changes in the residue interaction networks. By using topological parameters, we have described the organization of the residue interaction networks and networks of coevolving residues in the ABL kinase structures. This analysis has shown that functionally critical regulatory residues can simultaneously embody strong coevolutionary signal and high network centrality with a propensity to be energetic hot spots for drug binding. We have found that selective (Nilotinib) and promiscuous (Bosutinib, Dasatinib) kinase inhibitors can use their energetic hot spots to differentially modulate stability of the residue interaction networks, thus inhibiting or promoting conformational equilibrium between inactive and active states. According to our results, Nilotinib binding may induce a significant network-bridging effect and enhance centrality of the hot spot residues that stabilize structural environment favored by the specific kinase form. In contrast, Bosutinib and Dasatinib can incur modest changes in the residue interaction network in which ligand binding is primarily coupled only with the identity of the gate-keeper residue. These factors may promote structural adaptability of the active kinase states in binding with these promiscuous inhibitors. Our results have related ligand-induced changes in the residue interaction networks with drug resistance effects, showing that network robustness may be compromised by targeted mutations of key mediating residues. This study has outlined mechanisms by which inhibitor binding could modulate resilience and efficiency of allosteric interactions in the kinase structures, while preserving structural topology required for catalytic activity and regulation.
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