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

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.

Exploring Molecular Mechanisms of Paradoxical Activation in the BRAF Kinase Dimers: Atomistic Simulations of Conformational Dynamics and Modeling of Allosteric Communication Networks and Signaling Pathways

“…Highly coevolving residues were primarily assembled in the ATP binding site, in the catalytic loop region and near the substrate binding motif (residues 619-WMAPE-623). Structural mapping of the high cMI residues revealed a well-connected network with a characteristic θ-like shape [ 99,124 ] in which coevolutionary networks connected the ATP binding site with the substrate binding region through the hydrophobic spines ( Fig 8C ). In this network, the dimer interface residues R506 and R509 may be directly coupled with the R-spine residues L505 an F516.…”

“…All crystal structures were obtained from the Protein Data Bank (RCSB PDB www.rcsb.org) [ 131 ]. Structure preparation process included several important steps that were previously reported in detail in our studies of protein kinases [ 77,109,124,132 ] and molecular chaperones [ 133,134 ]. In this protocol, hydrogen atoms and missing residues were assigned using the WHATIF program [ 135 ].…”

“…MD simulations were carried out using NAMD 2.6 package [ 142 ] with the CHARMM22 force field [ 143,144 ] and the explicit TIP3P water model [ 145 ]. The employed MD protocol was previously reported in detail in our studies of protein kinases [ 77,109,124 ] and molecular chaperones [ 133,134 ]. The initial structures were solvated in a water box with the buffering distance of 10 Å.…”

CBT profiles of cabozantinib approved for advanced renal cell carcinomas

“…Decisive molecules and biological biomarkers for binding specificities of cabozantinib should be considered as an important issue to monitor the efficacy and toxicity of the drug in clinical practice, which can be measured by the integration of molecular simulations and computational alanine scanning with network-based approaches (Tse and Verkhivker 2015). It is helpful to understand the interaction network of RTK inhibitors with ligands, the tension between bindings, and elements within networks, since each RTK inhibitor has its own regulatory residues, energetic hot spots, and residue interaction network constructions.…”

“…It is helpful to understand the interaction network of RTK inhibitors with ligands, the tension between bindings, and elements within networks, since each RTK inhibitor has its own regulatory residues, energetic hot spots, and residue interaction network constructions. We believe that cabozantinib may have residue interaction networks and network-bridging effects with a special stability and conformational equilibrium between inactive and active states, although further evidence to determine the reality and accuracy of such a theoretical framework between ligand binding and inhibitor-mediated changes within residue interaction networks (Tse and Verkhivker 2015). Small molecule kinase inhibitors approved by the FDA are classified on the basis of binding mechanisms and common structural features.…”