Explaining why Gleevec is a specific and potent inhibitor of Abl kinase

Unexpected off-targets and paradoxical pathway activation by kinase inhibitors

Protein kinase inhibitors are an increasingly important class of targeted anticancer therapeutics. More than two dozen new drugs of this class have entered routine clinical use over the past decade. This review article focuses on how the development of methods to study the kinome- and proteome-wide selectivity of kinase inhibitors, in conjunction with advances in the structural understanding of kinase inhibitor binding modes, has resulted in a better appreciation of the mechanism of action of clinical kinase inhibitors. I provide examples of how this has led to the discovery of unexpected off-target effects, intriguing cases in which kinase inhibitors may cause pathway activation, and new mechanisms responsible for resistance to kinase inhibitors. Finally, I illustrate that although certain kinase targets may be pharmacologically easily tractable, a better understanding of the regulation and biology of the targets is required to generate drugs that are efficacious in cancer patients.

Targeting conformational plasticity of protein kinases

The quest for ever more selective kinase inhibitors as potential future drugs has yielded a large repertoire of chemical probes that are selective for specific kinase conformations. These probes have been useful tools to obtain structural snapshots of kinase conformational plasticity. Similarly, kinetic and thermodynamic inhibitor binding experiments provide glimpses at the time scales and energetics of conformational interconversions. These experimental insights are complemented by computational predictions of conformational energy landscapes and simulations of conformational transitions and of the process of inhibitors binding to the protein kinase domain. A picture emerges in which highly selective inhibitors capitalize on the dynamic nature of kinases.

Computational study of the "DFG-flip" conformational transition in c-Abl and c-Src tyrosine kinases

Protein tyrosine kinases are crucial to cellular signaling pathways regulating cell growth, proliferation, metabolism, differentiation, and migration. To maintain normal regulation of cellular signal transductions, the activities of tyrosine kinases are also highly regulated. The conformation of a three-residue motif Asp-Phe-Gly (DFG) near the N-terminus of the long “activation” loop covering the catalytic site is known to have a critical impact on the activity of c-Abl and c-Src tyrosine kinases. A conformational transition of the DFG motif can switch the enzyme from an active (DFG-in) to an inactive (DFG-out) state. In the present study, the string method with swarms-of-trajectories was used to computationally determine the reaction pathway connecting the two end-states, and umbrella sampling calculations were carried out to characterize the thermodynamic factors affecting the conformations of the DFG motif in c-Abl and c-Src kinases. According to the calculated free energy landscapes, the DFG-out conformation is clearly more favorable in the case of c-Abl than that of c-Src. The calculations also show that the protonation state of the aspartate residue in the DFG motif strongly affects the in/out conformational transition in c-Abl, although it has a much smaller impact in the case of c-Src due to local structural differences.

Small-world networks of residue interactions in the Abl kinase complexes with cancer drugs: topology of allosteric communication pathways can determine drug resistance effects

Computational modelling of efficiency and robustness of the residue interaction networks and allosteric pathways in kinase structures can characterize protein kinase sensitivity to drug binding and drug resistance effects.

Molecular modeling of peptides

This article presents a review of the field of molecular modeling of peptides. The main focus is on atomistic modeling with molecular mechanics potentials. The description of peptide conformations and solvation through potentials is discussed. Several important computer simulation methods are briefly introduced, including molecular dynamics, accelerated sampling approaches such as replica-exchange and metadynamics, free energy simulations and kinetic network models like Milestoning. Examples of recent applications for predictions of structure, kinetics, and interactions of peptides with complex environments are described. The reliability of current simulation methods is analyzed by comparison of computational predictions obtained using different models with each other and with experimental data. A brief discussion of coarse-grained modeling and future directions is also presented.

Computational modeling of membrane proteins

The determination of membrane protein (MP) structures has always trailed that of soluble proteins due to difficulties in their overexpression, reconstitution into membrane mimetics, and subsequent structure determination. The percentage of MP structures in the protein databank (PDB) has been at a constant 1-2% for the last decade. In contrast, over half of all drugs target MPs, only highlighting how little we understand about drug-specific effects in the human body. To reduce this gap, researchers have attempted to predict structural features of MPs even before the first structure was experimentally elucidated. In this review, we present current computational methods to predict MP structure, starting with secondary structure prediction, prediction of trans-membrane spans, and topology. Even though these methods generate reliable predictions, challenges such as predicting kinks or precise beginnings and ends of secondary structure elements are still waiting to be addressed. We describe recent developments in the prediction of 3D structures of both α-helical MPs as well as β-barrels using comparative modeling techniques, de novo methods, and molecular dynamics (MD) simulations. The increase of MP structures has (1) facilitated comparative modeling due to availability of more and better templates, and (2) improved the statistics for knowledge-based scoring functions. Moreover, de novo methods have benefited from the use of correlated mutations as restraints. Finally, we outline current advances that will likely shape the field in the forthcoming decade.

Conformational analysis of the DFG-out kinase motif and biochemical profiling of structurally validated type II inhibitors

Structural coverage of the human kinome has been steadily increasing over time. The structures provide valuable insights into the molecular basis of kinase function and also provide a foundation for understanding the mechanisms of kinase inhibitors. There are a large number of kinase structures in the PDB for which the Asp and Phe of the DFG motif on the activation loop swap positions, resulting in the formation of a new allosteric pocket. We refer to these structures as “classical DFG-out” conformations in order to distinguish them from conformations that have also been referred to as DFG-out in the literature but that do not have a fully formed allosteric pocket. We have completed a structural analysis of almost 200 small molecule inhibitors bound to classical DFG-out conformations; we find that they are recognized by both type I and type II inhibitors. In contrast, we find that nonclassical DFG-out conformations strongly select against type II inhibitors because these structures have not formed a large enough allosteric pocket to accommodate this type of binding mode. In the course of this study we discovered that the number of structurally validated type II inhibitors that can be found in the PDB and that are also represented in publicly available biochemical profiling studies of kinase inhibitors is very small. We have obtained new profiling results for several additional structurally validated type II inhibitors identified through our conformational analysis. Although the available profiling data for type II inhibitors is still much smaller than for type I inhibitors, a comparison of the two data sets supports the conclusion that type II inhibitors are more selective than type I. We comment on the possible contribution of the DFG-in to DFG-out conformational reorganization to the selectivity.

Computational study of Gleevec and G6G reveals molecular determinants of kinase inhibitor selectivity

Gleevec is a potent inhibitor of Abl tyrosine kinase but not of the highly homologous c-Src kinase. Because the ligand binds to an inactive form of the protein in which an Asp-Phe-Gly structural motif along the activation loop adopts a so-called DFG-out conformation, it was suggested that binding specificity was controlled by a "conformational selection" mechanism. In this context, the binding affinity displayed by the kinase inhibitor G6G poses an intriguing challenge. Although it possesses a chemical core very similar to that of Gleevec, G6G is a potent inhibitor of both Abl and c-Src kinases. Both inhibitors bind to the DFG-out conformation of the kinases, which seems to be in contradiction with the conformational selection mechanism. To address this issue and display the hidden thermodynamic contributions affecting the binding selectivity, molecular dynamics free energy simulations with explicit solvent molecules were carried out. Relative to Gleevec, G6G forms highly favorable van der Waals dispersive interactions upon binding to the kinases via its triazine functional group, which is considerably larger than the corresponding pyridine moiety in Gleevec. Upon binding of G6G to c-Src, these interactions offset the unfavorable free energy cost of the DFG-out conformation. When binding to Abl, however, G6G experiences an unfavorable free energy penalty due to steric clashes with the phosphate-binding loop, yielding an overall binding affinity that is similar to that of Gleevec. Such steric clashes are absent when G6G binds to c-Src, due to the extended conformation of the phosphate-binding loop.

Energetic dissection of Gleevec's selectivity toward human tyrosine kinases

Protein kinases are obvious drug targets against cancer due to their central role in cellular regulation. Since the discovery of Gleevec, a potent and specific inhibitor of Abl kinase, as a highly successful cancer therapeutic, the ability of this drug to distinguish between Abl and other tyrosine kinases like Src has been intensely investigated, but without much success. Using NMR and fast kinetics, we establish a novel model that solves this longstanding question of two tyrosine kinases adopting almost identical structures when bound to Gleevec, yet having vastly different affinities. In contrast to all other proposed models we show that the origin of Abl’s high affinity lies predominantly in a conformational change after binding. An energy landscape that provides tight affinity via an induced-fit and binding plasticity via conformational selection mechanism is likely to be general for many inhibitors.

Measurement of small molecule binding kinetics on a protein microarray by plasmonic-based electrochemical impedance imaging

We report on a quantitative study of small molecule binding kinetics on protein microarrays with plasmonic-based electrochemical impedance microscopy (P-EIM). P-EIM measures electrical impedance optically with high spatial resolution by converting a surface charge change to a surface plasmon resonance (SPR) image intensity change, and the signal is not scaled to the mass of the analyte. Using P-EIM, we measured binding kinetics and affinity between small molecule drugs (imatinib and SB202190) and their target proteins (kinases Abl1 and p38-α). The measured affinity values are consistent with reported values measured by an indirect competitive binding assay. We also found that SB202190 has weak bindings to ABL1 with KD > 10 μM, which is not reported in the literature. Furthermore, we found that P-EIM is less prone to nonspecific binding, a long-standing issue in SPR. Our results show that P-EIM is a novel method for high-throughput measurement of small molecule binding kinetics and affinity, which is critical to the understanding of small molecules in biological systems and discovery of small molecule drugs.

Protonation effects on the UV/Vis absorption spectra of imatinib: a theoretical and experimental study

An experimental and theoretical investigation of protonation effects on the UV/Vis absorption spectra of imatinib showed systematic changes of absorption depending on the pH, and a new absorption band appeared below pH 2. These changes in the UV/Vis absorption spectra were interpreted using quantum chemical calculations. The geometry of various imatinib cations in the gas phase and in ethanol solution was optimized with the DFT/B3LYP method. The resultant geometries were compared to the experimentally determined crystal structures of imatinib salts. The semi-empirical ZINDO-CI method was employed to calculate the absorption lines and electronic transitions. Our study suggests that the formation of the extra near-UV absorption band resulted from an increase of imatinib trication concentration in the solution, while the rapid increase of the first absorption maximum could be attributed to both the formation of imatinib trication and tetracation.

Mechanistic insights into Pin1 peptidyl-prolyl cis-trans isomerization from umbrella sampling simulations

The peptidyl-proyl isomerase Pin1 plays a key role in the regulation of phospho(p)-Ser/Thr-Pro proteins, acting as a molecular timer of the cell cycle. After recognition of these motifs, Pin1 catalyzes the rapid cis-trans isomerization of proline amide bonds of substrates, contributing to maintain the equilibrium between the two conformations. Although a great interest has arisen on this enzyme, its catalytic mechanism has long been debated. Here, the cis-trans isomerization of a model peptide system was investigated by means of umbrella sampling simulations in the Pin1-bound and unbound states. We obtained free energy barriers consistent with experimental data, and identified several enzymatic features directly linked to the acceleration of the prolyl bond isomerization. In particular, an enhanced autocatalysis, the stabilization of perturbed ground state conformations, and the substrate binding in a procatalytic conformation were found as main contributions to explain the lowering of the isomerization free energy barrier.

P-loop conformation governed crizotinib resistance in G2032R-mutated ROS1 tyrosine kinase: clues from free energy landscape

Tyrosine kinases are regarded as excellent targets for chemical drug therapy of carcinomas. However, under strong purifying selection, drug resistance usually occurs in the cancer cells within a short term. Many cases of drug resistance have been found to be associated with secondary mutations in drug target, which lead to the attenuated drug-target interactions. For example, recently, an acquired secondary mutation, G2032R, has been detected in the drug target, ROS1 tyrosine kinase, from a crizotinib-resistant patient, who responded poorly to crizotinib within a very short therapeutic term. It was supposed that the mutation was located at the solvent front and might hinder the drug binding. However, a different fact could be uncovered by the simulations reported in this study. Here, free energy surfaces were characterized by the drug-target distance and the phosphate-binding loop (P-loop) conformational change of the crizotinib-ROS1 complex through advanced molecular dynamics techniques, and it was revealed that the more rigid P-loop region in the G2032R-mutated ROS1 was primarily responsible for the crizotinib resistance, which on one hand, impaired the binding of crizotinib directly, and on the other hand, shortened the residence time induced by the flattened free energy surface. Therefore, both of the binding affinity and the drug residence time should be emphasized in rational drug design to overcome the kinase resistance.

Cancers can eventually confer drug resistance to the continued medication. In most cases, mutations occurred in a drug target can attenuate the binding affinity of the drugs. Here, we studied the drug resistance mechanisms of the mutations G2032R in the ROS1 tyrosine kinase in fusion-type NSCLC. It is well known that the phosphate-binding loop (P-loop) plays a vital role in the binding of competitive inhibitors in tyrosine kinases, and numerous mutations have been found occurred around the P-loop, which may affect the binding/unbinding process of a drug. Free energy surfaces were constructed to characterize the impact of the mutation to the binding/unbinding process of a well-known NSCLC drug, crizotinib. Two advanced free energy calculation methods, namely funnel based well-tempered metadynamics and umbrella sampling based absolute binding free energy calculation achieved consistent results with the experimental data, suggesting that the rigid P-loop of the mutated target was mainly responsible for the crizotinib resistance to ROS1 tyrosine kinase.

An Overview of Electrostatic Free Energy Computations for Solutions and Proteins

Free energy simulations for electrostatic and charging processes in complex molecular systems encounter specific difficulties owing to the long-range, 1/r Coulomb interaction. To calculate the solvation free energy of a simple ion, it is essential to take into account the polarization of nearby solvent but also the electrostatic potential drop across the liquid-gas boundary, however distant. The latter does not exist in a simulation model based on periodic boundary conditions because there is no physical boundary to the system. An important consequence is that the reference value of the electrostatic potential is not an ion in a vacuum. Also, in an infinite system, the electrostatic potential felt by a perturbing charge is conditionally convergent and dependent on the choice of computational conventions. Furthermore, with Ewald lattice summation and tinfoil conducting boundary conditions, the charges experience a spurious shift in the potential that depends on the details of the simulation system such as the volume fraction occupied by the solvent. All these issues can be handled with established computational protocols, as reviewed here and illustrated for several small ions and three solvated proteins.

Canonical and new generation anticancer drugs also target energy metabolism

Significant efforts have been made for the development of new anticancer drugs (protein kinase or proteasome inhibitors, monoclonal humanized antibodies) with presumably low or negligible side effects and high specificity. However, an in-depth analysis of the side effects of several currently used canonical (platin-based drugs, taxanes, anthracyclines, etoposides, antimetabolites) and new generation anticancer drugs as the first line of clinical treatment reveals significant perturbation of glycolysis and oxidative phosphorylation. Canonical and new generation drug side effects include decreased (1) intracellular ATP levels, (2) glycolytic/mitochondrial enzyme/transporter activities and/or (3) mitochondrial electrical membrane potentials. Furthermore, the anti-proliferative effects of these drugs are markedly attenuated in tumor rho (0) cells, in which functional mitochondria are absent; in addition, several anticancer drugs directly interact with isolated mitochondria affecting their functions. Therefore, several anticancer drugs also target the energy metabolism, and hence, the documented inhibitory effect of anticancer drugs on cancer growth should also be linked to the blocking of ATP supply pathways. These often overlooked effects of canonical and new generation anticancer drugs emphasize the role of energy metabolism in maintaining cancer cells viable and its targeting as a complementary and successful strategy for cancer treatment.

Activation pathway of Src kinase reveals intermediate states as targets for drug design

Unregulated activation of Src kinases leads to aberrant signaling, uncontrolled growth, and differentiation of cancerous cells. Reaching a complete mechanistic understanding of large scale conformational transformations underlying the activation of kinases could greatly help in the development of therapeutic drugs for the treatment of these pathologies. In principle, the nature of conformational transition could be modeled in silico via atomistic molecular dynamics simulations, although this is very challenging due to the long activation timescales. Here, we employ a computational paradigm that couples transition pathway techniques and Markov state model-based massively distributed simulations for mapping the conformational landscape of c-src tyrosine kinase. The computations provide the thermodynamics and kinetics of kinase activation for the first time, and help identify key structural intermediates. Furthermore, the presence of a novel allosteric site in an intermediate state of c-src that could be potentially utilized for drug design is predicted.

BCR-ABL residues interacting with ponatinib are critical to preserve the tumorigenic potential of the oncoprotein

Patients with chronic myeloid leukemia in whom tyrosine kinase inhibitors (TKIs) fail often present mutations in the BCR-ABL catalytic domain. We noticed a lack of substitutions involving 4 amino acids (E286, M318, I360, and D381) that form hydrogen bonds with ponatinib. We therefore introduced mutations in each of these residues, either preserving or altering their physicochemical properties. We found that E286, M318, I360, and D381 are dispensable for ABL and BCR-ABL protein stability but are critical for preserving catalytic activity. Indeed, only a "conservative" I360T substitution retained kinase proficiency and transforming potential. Molecular dynamics simulations of BCR-ABL(I360T) revealed differences in both helix αC dynamics and protein-correlated motions, consistent with a modified ATP-binding pocket. Nevertheless, this mutant remained sensitive to ponatinib, imatinib, and dasatinib. These results suggest that changes in the 4 BCR-ABL residues described here would be selected against by a lack of kinase activity or by maintained responsiveness to TKIs. Notably, amino acids equivalent to those identified in BCR-ABL are conserved in 51% of human tyrosine kinases. Hence, these residues may represent an appealing target for the design of pharmacological compounds that would inhibit additional oncogenic tyrosine kinases while avoiding the emergence of resistance due to point mutations.

c-Abl phosphorylates α-synuclein and regulates its degradation: implication for α-synuclein clearance and contribution to the pathogenesis of Parkinson's disease

Increasing evidence suggests that the c-Abl protein tyrosine kinase could play a role in the pathogenesis of Parkinson's disease (PD) and other neurodegenerative disorders. c-Abl has been shown to regulate the degradation of two proteins implicated in the pathogenesis of PD, parkin and α-synuclein (α-syn). The inhibition of parkin's neuroprotective functions is regulated by c-Abl-mediated phosphorylation of parkin. However, the molecular mechanisms by which c-Abl activity regulates α-syn toxicity and clearance remain unknown. Herein, using NMR spectroscopy, mass spectrometry, in vitro enzymatic assays and cell-based studies, we established that α-syn is a bona fide substrate for c-Abl. In vitro studies demonstrate that c-Abl directly interacts with α-syn and catalyzes its phosphorylation mainly at tyrosine 39 (pY39) and to a lesser extent at tyrosine 125 (pY125). Analysis of human brain tissues showed that pY39 α-syn is detected in the brains of healthy individuals and those with PD. However, only c-Abl protein levels were found to be upregulated in PD brains. Interestingly, nilotinib, a specific inhibitor of c-Abl kinase activity, induces α-syn protein degradation via the autophagy and proteasome pathways, whereas the overexpression of α-syn in the rat midbrains enhances c-Abl expression. Together, these data suggest that changes in c-Abl expression, activation and/or c-Abl-mediated phosphorylation of Y39 play a role in regulating α-syn clearance and contribute to the pathogenesis of PD.

Conformation-selective inhibitors reveal differences in the activation and phosphate-binding loops of the tyrosine kinases Abl and Src

Over the past decade, an increasingly diverse array of potent and selective inhibitors that target the ATP-binding sites of protein kinases have been developed. Many of these inhibitors, like the clinically approved drug imatinib (Gleevec), stabilize a specific catalytically inactive ATP-binding site conformation of their kinases targets. Imatinib is notable in that it is highly selective for its kinase target, Abl, over other closely related tyrosine kinases, such as Src. In addition, imatinib is highly sensitive to the phosphorylation state of Abl's activation loop, which is believed to be a general characteristic of all inhibitors that stabilize a similar inactive ATP-binding site conformation. In this report, we perform a systematic analysis of a diverse series of ATP-competitive inhibitors that stabilize a similar inactive ATP-binding site conformation as imatinib with the tyrosine kinases Src and Abl. In contrast to imatinib, many of these inhibitors have very similar potencies against Src and Abl. Furthermore, only a subset of this class of inhibitors is sensitive to the phosphorylation state of the activation loop of these kinases. In attempting to explain this observation, we have uncovered an unexpected correlation between Abl's activation loop and another flexible active site feature, called the phosphate-binding loop (p-loop). These studies shed light on how imatinib is able to obtain its high target selectivity and reveal how the conformational preference of flexible active site regions can vary between closely related kinases.

Oncology meets immunology: the cancer-immunity cycle

The genetic and cellular alterations that define cancer provide the immune system with the means to generate T cell responses that recognize and eradicate cancer cells. However, elimination of cancer by T cells is only one step in the Cancer-Immunity Cycle, which manages the delicate balance between the recognition of nonself and the prevention of autoimmunity. Identification of cancer cell T cell inhibitory signals, including PD-L1, has prompted the development of a new class of cancer immunotherapy that specifically hinders immune effector inhibition, reinvigorating and potentially expanding preexisting anticancer immune responses. The presence of suppressive factors in the tumor microenvironment may explain the limited activity observed with previous immune-based therapies and why these therapies may be more effective in combination with agents that target other steps of the cycle. Emerging clinical data suggest that cancer immunotherapy is likely to become a key part of the clinical management of cancer.

Computational analysis of the binding specificity of Gleevec to Abl, c-Kit, Lck, and c-Src tyrosine kinases

Gleevec, a well-known cancer therapeutic agent, is an effective inhibitor of several tyrosine kinases, including Abl and c-Kit, but displays less potency to inhibit closely homologous tyrosine kinases, such as Lck and c-Src. Because many structural features of the binding site are highly conserved in these homologous kinases, the molecular determinants responsible for the binding specificity of Gleevec remain poorly understood. To address this issue, free energy perturbation molecular dynamics (FEP/MD) simulations with explicit solvent was used to compute the binding affinity of Gleevec to Abl, c-Kit, Lck, and c-Src. The results of the FEP/MD calculations are in good agreement with experiments, enabling a detailed and quantitative dissection of the absolute binding free energy in terms of various thermodynamic contributions affecting the binding specificity of Gleevec to the kinases. Dominant binding free energy contributions arises from the van der Waals dispersive interaction, compensating about two-thirds of the unfavorable free energy penalty associated with the loss of translational, rotational, and conformational freedom of the ligand upon binding. In contrast, the contributions from electrostatic and repulsive interactions nearly cancel out due to solvent effects. Furthermore, the calculations show the importance of the conformation of the kinase activation loop. Among the kinases examined, Abl provides the most favorable binding environment for Gleevec via optimal protein-ligand interactions and a small free energy cost for loss of the translational, rotational, and conformational freedom upon ligand binding. The FEP/MD calculations additionally reveal that Lck and c-Src provide similar nonbinding interactions with the bound-Gleevec, but the former pays less entropic penalty for the ligand losing its translational, rotational, and conformational motions to bind, examining the empirically observed differential binding affinities of Gleevec between the two Src-family kinases.

Calculating the sensitivity and robustness of binding free energy calculations to force field parameters

Binding free energy calculations offer a thermodynamically rigorous method to compute protein-ligand binding, and they depend on empirical force fields with hundreds of parameters. We examined the sensitivity of computed binding free energies to the ligand's electrostatic and van der Waals parameters. Dielectric screening and cancellation of effects between ligand-protein and ligand-solvent interactions reduce the parameter sensitivity of binding affinity by 65%, compared with interaction strengths computed in the gas-phase. However, multiple changes to parameters combine additively on average, which can lead to large changes in overall affinity from many small changes to parameters. Using these results, we estimate that random, uncorrelated errors in force field nonbonded parameters must be smaller than 0.02 e per charge, 0.06 Å per radius, and 0.01 kcal/mol per well depth in order to obtain 68% (one standard deviation) confidence that a computed affinity for a moderately-sized lead compound will fall within 1 kcal/mol of the true affinity, if these are the only sources of error considered.