The impact of inhibitor size and flexibility on the binding pathways to c-Src kinase
Shinobu, A.; Re, S.; Sugita, Y.
Show abstract
Considering dynamical aspects of protein-drug binding processes is inevitable in current drug compound design. Conformational plasticity of protein kinases poses a challenge for the design of their inhibitors, and therefore, atomistic molecular dynamics (MD) simulations have often been utilized. While protein conformational changes have been increasingly discussed, a fundamental yet non-trivial question remains for the effect of drug compound flexibility, which is hardly detectable from experiments. In this study, we apply two-dimensional replica-exchange MD simulations as enhanced sampling to investigate how c-Src kinase can bind PP1, a small inhibitor, and dasatinib, a larger inhibitor with greater flexibility. 600 microseconds simulations in total sample binding and unbinding events of these inhibitors much more frequently than conventional MD simulation, resulting in statistically converged binding pathways. While the two inhibitors adopt a similar mechanism of multiple binding pathways, the non-canonical binding poses become less feasible for dasatinib. A notable difference is apparent in their energetics where dasatinib stabilizes at intermediate states more than PP1 to raise the barrier toward the canonical pose. Conformational analysis shows that dasatinib adopts linear and bent forms for which relative populations are altered upon binding. We further find hidden conformations of dasatinib at intermediate regions, and unexpectedly one of them could efficiently bypasses the intermediate-to-bound state transition. The results demonstrate that inhibitor size and flexibility impact the binding mechanism, which could potentially modulate inhibitor residence time.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Deep Mutational Scanning of Dynamic Interaction Networks in the SARS-CoV-2 Spike Protein Complexes: Allosteric Hotspots Control Functional Mimicry and Resilience to Mutational Escape 97%
- Computational investigation of BMAA and its carbamate adducts as potential GluR2 modulators 97%
- Probing the Structural Dynamics of the Unbound MAX Protein: Insights from Well-Tempered Metadynamics 97%
Similar papers in this journal
- Coarse-graining the recognition of a glycolipid by the C-type lectin Mincle receptor 97%
- Molecular Mechanism of Brassinosteroids Perception by the Plant Growth Receptor BRI1 97%
- Coevolution-driven method for efficiently simulating conformational changes in proteins reveals molecular details of ligand effects in the beta2AR receptor 96%
Similar papers in this journal
- Dissection of ligand-CDK8/CycC unbinding free energy barriers and kinetics by molecular simulations 98%
- G Protein-Coupled Receptor-Ligand Dissociation Rates and Mechanisms from {tau}RAMD Simulations 97%
- A linear response theory based method for prediction of large scale protein conformational changes upon ligand binding 97%
Similar papers in this journal
- Critical interactions for SARS-CoV-2 spike protein binding to ACE2 identified by machine learning 97%
- Capturing Protein-Ligand Recognition Pathways in Coarse-grained Simulation 97%
- Prediction of Threonine-Tyrosine Kinase Receptor-LigandUnbinding Kinetics with Multiscale Milestoning andMetadynamics 96%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.