ArticleCommunications biology2018
Predicting resistance of clinical Abl mutations to targeted kinase inhibitors using alchemical free-energy calculations.
Article in Communications biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
49 citing papers in PubMed, 100 citations in OpenAlex.
- Systematic evaluation of computational tools to predict the effects of mutations on protein-ligand binding affinity in the absence of experimental structures.Briefings in bioinformatics · 2026Article
- Rapid, accurate, and reproduciblemSphere · 2025Article
- Zidesamtinib Selective Targeting of Diverse ROS1 Drug-Resistant Mutations.Molecular cancer therapeutics · 2025Article
- Multiple Molecule λ-Dynamics: Probing Drug Resistance with Concurrent Protein and Ligand Perturbations.The journal of physical chemistry letters · 2025Article
- A Thermodynamic Cycle to Predict the Competitive Inhibition Outcomes of an Evolving Enzyme.Journal of chemical theory and computation · 2025Article
- Prospective Evaluation of Structure-Based Simulations Reveal Their Ability to Predict the Impact of Kinase Mutations on Inhibitor Binding.The journal of physical chemistry. B · 2025Article
- Prospective evaluation of structure-based simulations reveal their ability to predict the impact of kinase mutations on inhibitor binding.bioRxiv : the preprint server for biology · 2025Article
- Fine-tuning molecular mechanics force fields to experimental free energy measurements.bioRxiv : the preprint server for biology · 2025Article
- Evaluating data partitioning strategies for accurate prediction of protein-ligand binding free energy changes in mutated proteins.Computational and structural biotechnology journal · 2025Article
- Binding Selectivity Analysis from Alchemical Receptor Hopping and Swapping Free Energy Calculations.The journal of physical chemistry. B · 2024Article
- Protein engineering in the computational age: An open source framework for exploring mutational landscapesEngineering biology · 2023Article
- Discovery of Nirmatrelvir Resistance Mutations in SARS-CoV-2 3CLpro: A Computational-Experimental Approach.Journal of chemical information and modeling · 2023Article
- The maximal and current accuracy of rigorous protein-ligand binding free energy calculations.Communications chemistry · 2023Article
- In silico Analysis of Two Novel Variants in the Pyruvate Carboxylase (PC) Gene Associated with the Severe Form of PC Deficiency.Iranian biomedical journal · 2023Article
- Prediction of Amino Acid Substitutions in ABL1 Protein Leading to Tumor Drug Resistance Based on "Structure-Property" Relationship Classification Models.Life (Basel, Switzerland) · 2023Article
- Evaluating the ability of end-point methods to predict the binding affinity tendency of protein kinase inhibitors.RSC advances · 2023Article
- Identifying and Overcoming the Sampling Challenges in Relative Binding Free Energy Calculations of a Model Protein:Protein Complex.Journal of chemical theory and computation · 2023Article
- Identifying and overcoming the sampling challenges in relative binding free energy calculations of a model protein:protein complex.bioRxiv : the preprint server for biology · 2023Article
- A mutation-induced drug resistance database (MdrDB).Communications chemistry · 2023Article
- NVL-520 Is a Selective, TRK-Sparing, and Brain-Penetrant Inhibitor of ROS1 Fusions and Secondary Resistance Mutations.Cancer discovery · 2023Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
The therapeutic effect of targeted kinase inhibitors can be significantly reduced by intrinsic or acquired resistance mutations that modulate the affinity of the drug for the kinase. In cancer, the majority of missense mutations are rare, making it difficult to predict their impact on inhibitor affinity. This complicates the practice of precision medicine, pairing of patients with clinical trials, and development of next-generation inhibitors. Here, we examine the potential for alchemical free-energy calculations to predict how kinase mutations modulate inhibitor affinities to Abl, a major target in chronic myelogenous leukemia (CML). We find these calculations can achieve useful accuracy in predicting resistance for a set of eight FDA-approved kinase inhibitors across 144 clinically-identified point mutations, achieving a root mean square error in binding free energy changes of
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.