How Electrostatic Coupling Enables Conformational Plasticity in a Tyrosine Kinase

Mechanism of dimer selectivity and binding cooperativity of BRAF inhibitors

Aberrant signaling of BRAFV600E is a major cancer driver. Current FDA-approved RAF inhibitors selectively inhibit the monomeric BRAFV600E and suffer from tumor resistance. Recently, dimer-selective and equipotent RAF inhibitors have been developed; however, the mechanism of dimer selectivity is poorly understood. Here, we report extensive molecular dynamics (MD) simulations of the monomeric and dimeric BRAFV600E in the apo form or in complex with one or two dimer-selective (PHI1) or equipotent (LY3009120) inhibitor(s). The simulations uncovered the unprecedented details of the remarkable allostery in BRAFV600E dimerization and inhibitor binding. Specifically, dimerization retrains and shifts the αC helix inward and increases the flexibility of the DFG motif; dimer compatibility is due to the promotion of the αC-in conformation, which is stabilized by a hydrogen bond formation between the inhibitor and the αC Glu501. A more stable hydrogen bond further restrains and shifts the αC helix inward, which incurs a larger entropic penalty that disfavors monomer binding. This mechanism led us to propose an empirical way based on the co-crystal structure to assess the dimer selectivity of a BRAFV600E inhibitor. Simulations also revealed that the positive cooperativity of PHI1 is due to its ability to preorganize the αC and DFG conformation in the opposite protomer, priming it for binding the second inhibitor. The atomically detailed view of the interplay between BRAF dimerization and inhibitor allostery as well as cooperativity has implications for understanding kinase signaling and contributes to the design of protomer selective RAF inhibitors.

The role of ribosomal protein networks in ribosome dynamics

Accurate protein synthesis requires ribosomes to integrate signals from distant functional sites and execute complex dynamics. Despite advances in understanding ribosome structure and function, two key questions remain: how information is transmitted between these distant sites, and how ribosomal movements are synchronized? We recently highlighted the existence of ribosomal protein networks, likely evolved to participate in ribosome signaling. Here, we investigate the relationship between ribosomal protein networks and ribosome dynamics. Our findings show that major motion centers in the bacterial ribosome interact specifically with r-proteins, and that ribosomal RNA exhibits high mobility around each r-protein. This suggests that periodic electrostatic changes in the context of negatively charged residues (Glu and Asp) induce RNA-protein 'distance-approach' cycles, controlling key ribosomal movements during translocation. These charged residues play a critical role in modulating electrostatic repulsion between RNA and proteins, thus coordinating ribosomal dynamics. We propose that r-protein networks synchronize ribosomal dynamics through an 'electrostatic domino' effect, extending the concept of allostery to the regulation of movements within supramolecular assemblies.

Mechanism of Dimer Selectivity and Binding Cooperativity of BRAF Inhibitors

Aberrant signaling of BRAFV600E is a major cancer driver. Current FDA-approved RAF inhibitors selectively inhibit the monomeric BRAFV600E and suffer from tumor resistance. Recently, dimer-selective and equipotent RAF inhibitors have been developed; however, the mechanism of dimer selectivity is poorly understood. Here, we report extensive molecular dynamics (MD) simulations of the monomeric and dimeric BRAFV600E in the apo form or in complex with one or two dimer-selective (PHI1) or equipotent (LY3009120) inhibitor(s). The simulations uncovered the unprecedented details of the remarkable allostery in BRAFV600E dimerization and inhibitor binding. Specifically, dimerization retrains and shifts the αC helix inward and increases the flexibility of the DFG motif; dimer compatibility is due to the promotion of the αC-in conformation, which is stabilized by a hydrogen bond formation between the inhibitor and the αC Glu501. A more stable hydrogen bond further restrains and shifts the αC helix inward, which incurs a larger entropic penalty that disfavors monomer binding. This mechanism led us to propose an empirical way based on the co-crystal structure to assess the dimer selectivity of a BRAFV600E inhibitor. Simulations also revealed that the positive cooperativity of PHI1 is due to its ability to preorganize the αC and DFG conformation in the opposite protomer, priming it for binding the second inhibitor. The atomically detailed view of the interplay between BRAF dimerization and inhibitor allostery as well as cooperativity has implications for understanding kinase signaling and contributes to the design of protomer selective RAF inhibitors.

The multiple-action allosteric inhibition of TYK2 by deucravacitinib: Insights from computational simulations

Participating in the Janus kinase-signal transducer and activator of transcription (JAK-STAT) pathway, TYK2 emerges as a promising therapy target in controlling various autoimmune diseases, including psoriasis and multiple sclerosis. Deucravacitinib (DEU) is a novel oral TYK2-specific inhibitor approved in 2022 that is clinically effective in moderate to severe psoriasis trials. Upon the AlphaFold2 predicted TYK2 pseudokinase domain (JH2) and kinase domain (JH1), we explored the details of the underlined allosteric inhibition mechanism on TYK2 JH2-JH1 with the aid of molecular dynamics simulation. Our results suggest that the allosteric inhibition of DEU on TYK2 is accomplished by affecting the JH2-JH1 interface and hampering the state transition and ATP binding in JH1. Particularly, DEU binding stabilized the autoinhibitory interface between JH2 and JH1 while disrupting the formation of the activation interface. As a result, the negative regulation of JH2 on JH1 was greatly enhanced. These findings offer additional details on the pseudokinase-dependent autoinhibition of the JAK kinase domain and provide theoretical support for the JH2-targeted drug discovery in JAK members.

Allosteric Changes in the Conformational Landscape of Src Kinase upon Substrate Binding

Precise regulation of protein kinase activity is crucial in cell functions, and its loss is implicated in various diseases. The kinase activity is regulated by interconverting active and inactive states in the conformational landscape. However, how protein kinases switch conformations in response to different signals such as the binding at distinct sites remains incompletely understood. Here, we predict the binding mode for the peptide substrate to Src tyrosine kinase using enhanced conformational sampling simulations (totaling 24 μs) and then investigate changes in the conformational landscape upon substrate binding by conducting unbiased molecular dynamics simulations (totaling 50 μs) initiated from the apo and substrate-bound forms. Unexpectedly, the peptide substrate binding significantly facilitates the transitions from active to inactive conformations in which the αC helix is directed outward, the regulatory spine is broken, and the ATP-binding domain is perturbed. We also explore an underlying residue-contact network responsible for the allosteric conformational changes. Our results are in accord with the recent experiments reporting the negative cooperativity between the peptide substrate and ATP binding to tyrosine kinases and will contribute to advancing our understanding of the regulation mechanisms for kinase activity.

Dynamic Interplay of Loop Motions Governs the Molecular Level Regulatory Dynamics in Spleen Tyrosine Kinase: Insights from Molecular Dynamics Simulations

The spleen tyrosine kinase (Syk) is a key regulator in immune cell signaling and is linked to various mechanisms in cancer and neurodegenerative diseases. Although most computational research on Syk focuses on novel drug design, the molecular-level regulatory dynamics remain unexplored. In this study, we utilized 5 × 1 μs all-atom molecular dynamics simulations of the Syk kinase domain, examining it in combinations of activation segment phosphorylated/unphosphorylated (at Tyr525, Tyr526) and the "DFG"-Asp protonated/deprotonated (at Asp512) states to investigate conformational variations and regulatory dynamics of various loops and motifs within the kinase domain. Our findings revealed that the formation and disruption of several electrostatic interactions among residues within and near the activation segment likely influenced its dynamics. The protein structure network analysis indicated that the N-terminal and C-terminal anchors were stabilized by connections with the nearby stable helical regions. The P-loop showed conformational variation characterized by movements toward and away from the conserved "HRD"-motif. Additionally, there was a significant correlation between the movement of the β3-αC loop and the P-loop, which controls the dimensions of the adenine-binding cavity of the C-spine region. Overall, understanding these significant motions of the Syk kinase domain enhances our knowledge of its functional regulatory mechanism and can guide future research.

DFT/MM Simulations for Cycloreversion Reaction of Cyclobutane Pyrimidine Dimer with Deprotonated and Protonated E283

DNA photolyase targets the primary ultraviolet (UV)-induced DNA lesion─cyclobutane pyrimidine dimer (CPD), attaches to it, and catalyzes its dissociation. The catalytic mechanism of DNA photolyase and the role of the conserved residue E283 remain subjects of debate. This study employs two-dimensional potential energy surface maps and minimum free energy paths calculated at the ωB97XD/6-31G/MM level to elucidate these mechanisms. Results suggest that the catalytic process follows a sequential, stepwise reaction in which the C5-C5 and C6-C6 bonds are cleaved in order, facilitated by a protonated E283. Activation free energies for these cleavages are calculated at 4.4 and 4.2 kcal·mol-1, respectively. Protonation of E283 reduces electrostatic repulsion with CPD and forms dual hydrogen bonds with it and provides better solvation, stabilizing the CPD radical anion, particularly during intermediate state. This stabilization renders the initial splitting step exergonic, slows reverse reactions of the C5-C5 bond cleavage and electron transfer, and ensures a high quantum yield. Furthermore, the protonation state of E283 significantly affects the type of bond cleavage. Other residues in the active site were also investigated for their roles in the mechanism.

Multistate Method to Efficiently Account for Tautomerism and Protonation in Alchemical Free-Energy Calculations

The majority of drug-like molecules contain at least one ionizable group, and many common drug scaffolds are subject to tautomeric equilibria. Thus, these compounds are found in a mixture of protonation and/or tautomeric states at physiological pH. Intrinsically, standard classical molecular dynamics (MD) simulations cannot describe such equilibria between states, which negatively impacts the prediction of key molecular properties in silico. Following the formalism described by de Oliveira and co-workers (J. Chem. Theory Comput. 2019, 15, 424-435) to consider the influence of all states on the binding process based on alchemical free-energy calculations, we demonstrate in this work that the multistate method replica-exchange enveloping distribution sampling (RE-EDS) is well suited to describe molecules with multiple protonation and/or tautomeric states in a single simulation. We apply our methodology to a series of eight inhibitors of factor Xa with two protonation states and a series of eight inhibitors of glycogen synthase kinase 3β (GSK3β) with two tautomeric states. In particular, we show that given a sufficient phase-space overlap between the states, RE-EDS is computationally more efficient than standard pairwise free-energy methods.

The role of kinases in peripheral nerve regeneration: mechanisms and implications

Peripheral nerve injury disease is a prevalent traumatic condition in current medical practice. Despite the present treatment approaches, encompassing surgical sutures, autologous nerve or allograft nerve transplantation, tissue engineering techniques, and others, an effective clinical treatment method still needs to be discovered. Exploring novel treatment methods to improve peripheral nerve regeneration requires more effort in investigating the cellular and molecular mechanisms involved. Many factors are associated with the regeneration of injured peripheral nerves, including the cross-sectional area of the injured nerve, the length of the nerve gap defect, and various cellular and molecular factors such as Schwann cells, inflammation factors, kinases, and growth factors. As crucial mediators of cellular communication, kinases exert regulatory control over numerous signaling cascades, thereby participating in various vital biological processes, including peripheral nerve regeneration after nerve injury. In this review, we examined diverse kinase classifications, distinct nerve injury types, and the intricate mechanisms involved in peripheral nerve regeneration. Then we stressed the significance of kinases in regulating autophagy, inflammatory response, apoptosis, cell cycle, oxidative processes, and other aspects in establishing conductive microenvironments for nerve tissue regeneration. Finally, we briefly discussed the functional roles of kinases in different types of cells involved in peripheral nerve regeneration.

Classifying protein kinase conformations with machine learning

Protein kinases are key actors of signaling networks and important drug targets. They cycle between active and inactive conformations, distinguished by a few elements within the catalytic domain. One is the activation loop, whose conserved DFG motif can occupy DFG-in, DFG-out, and some rarer conformations. Annotation and classification of the structural kinome are important, as different conformations can be targeted by different inhibitors and activators. Valuable resources exist; however, large-scale applications will benefit from increased automation and interpretability of structural annotation. Interpretable machine learning models are described for this purpose, based on ensembles of decision trees. To train them, a set of catalytic domain sequences and structures was collected, somewhat larger and more diverse than existing resources. The structures were clustered based on the DFG conformation and manually annotated. They were then used as training input. Two main models were constructed, which distinguished active/inactive and in/out/other DFG conformations. They considered initially 1692 structural variables, spanning the whole catalytic domain, then identified ("learned") a small subset that sufficed for accurate classification. The first model correctly labeled all but 3 of 3289 structures as active or inactive, while the second assigned the correct DFG label to all but 17 of 8826 structures. The most potent classifying variables were all related to well-known structural elements in or near the activation loop and their ranking gives insights into the conformational preferences. The models were used to automatically annotate 3850 kinase structures predicted recently with the Alphafold2 tool, showing that Alphafold2 reproduced the active/inactive but not the DFG-in proportions seen in the Protein Data Bank. We expect the models will be useful for understanding and engineering kinases.

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.

Deciphering the molecular choreography of Janus kinase 2 inhibition via Gaussian accelerated molecular dynamics simulations: a dynamic odyssey

The Janus kinases (JAK) are crucial targets in drug development for several diseases. However, accounting for the impact of possible structural rearrangements on the binding of different kinase inhibitors is complicated by the extensive conformational variability of their catalytic kinase domain (KD). The dynamic KD contains mainly four prominent mobile structural motifs: the phosphate-binding loop (P-loop), the αC-helix within the N-lobe, the Asp-Phe-Gly (DFG) motif, and the activation loop (A-loop) within the C-lobe. These distinct structural orientations imply a complex signal transmission path for regulating the A-loop's flexibility and conformational preference for optimal JAK function. Nevertheless, the precise dynamical features of the JAK induced by different types of inhibitors still remain elusive. We performed comparative, microsecond-long, Gaussian accelerated molecular dynamics simulations in triplicate of three phosphorylated JAK2 systems: the KD alone, type-I ATP-competitive inhibitor (CI) bound KD in the catalytically active DFG-in conformation, and the type-II inhibitor (AI) bound KD in the catalytically inactive DFG-out conformation. Our results indicate significant conformational variations observed in the A-loop and αC helix motions upon inhibitor binding. Our studies also reveal that the DFG-out inactive conformation is characterized by the closed A-loop rearrangement, open catalytic cleft of N and C-lobe, the outward movement of the αC helix, and open P-loop states. Moreover, the outward positioning of the αC helix impacts the hallmark salt bridge formation between Lys882 and Glu898 in an inactive conformation. Finally, we compared their ligand binding poses and free energy by the MM/PBSA approach. The free energy calculations suggested that the AI's binding affinity is higher than CI against JAK2 due to an increased favorable contribution from the total non-polar interactions and the involvement of the αC helix. Overall, our study provides the structural and energetic insights crucial for developing more promising type I/II JAK2 inhibitors for treating JAK-related diseases.

Molecular Simulations of Conformational Transitions within the Insulin Receptor Kinase Reveal Consensus Features in a Multistep Activation Pathway

Modulating the transitions between active and inactive conformations of protein kinases is the primary means of regulating their catalytic activity, achieved by phosphorylation of the activation loop (A-loop). To elucidate the mechanism of this conformational activation, we applied the string method to determine the conformational transition path of insulin receptor kinase between the active and inactive conformations and the corresponding free-energy profiles with and without A-loop phosphorylation. The conformational change was found to proceed in three sequential steps: first, the flipping of the DFG motif of the active site; second, rotation of the A-loop; finally, the inward movement of the αC helix. The main energetic bottleneck corresponds to the conformational change in the A-loop, while changes in the DFG motif and αC helix occur before and after A-loop conformational change, respectively. In accordance with this, two intermediate states are identified, the first state just after the DFG flipping and the second state after the A-loop rotation. These intermediates exhibit structural features characteristic of the corresponding inactive and active conformations of other protein kinases. To understand the impact of A-loop phosphorylation on kinase conformation, the free energies of A-loop phosphorylation were determined at several states along the conformational transition path using the free-energy perturbation simulations. The calculated free energies reveal that while the unphosphorylated kinase interconverts between the inactive and active conformations, A-loop phosphorylation restricts access to the inactive conformation, thereby increasing the active conformation population. Overall, this study suggests a consensus mechanism of conformational activation between different protein kinases.

Basis for Accurate Protein pKa Prediction with Machine Learning

pH regulates protein structures and the associated functions in many biological processes via protonation and deprotonation of ionizable side chains where the titration equilibria are determined by pK_a's. To accelerate pH-dependent molecular mechanism research in the life sciences or industrial protein and drug designs, fast and accurate pK_a prediction is crucial. Here we present a theoretical pK_a data set PHMD549, which was successfully applied to four distinct machine learning methods, including DeepKa, which was proposed in our previous work. To reach a valid comparison, EXP67S was selected as the test set. Encouragingly, DeepKa was improved significantly and outperforms other state-of-the-art methods, except for the constant-pH molecular dynamics, which was utilized to create PHMD549. More importantly, DeepKa reproduced experimental pK_a orders of acidic dyads in five enzyme catalytic sites. Apart from structural proteins, DeepKa was found applicable to intrinsically disordered peptides. Further, in combination with solvent exposures, it is revealed that DeepKa offers the most accurate prediction under the challenging circumstance that hydrogen bonding or salt bridge interaction is partly compensated by desolvation for a buried side chain. Finally, our benchmark data qualify PHMD549 and EXP67S as the basis for future developments of protein pK_a prediction tools driven by artificial intelligence. In addition, DeepKa built on PHMD549 has been proven an efficient protein pK_a predictor and thus can be applied immediately to, for example, pK_a database construction, protein design, drug discovery, and so on.

Mechanistic Modeling of Lys745 Sulfonylation in EGFR C797S Reveals Chemical Determinants for Inhibitor Activity and Discriminates Reversible from Irreversible Agents

Targeted covalent inhibitors hold promise for drug discovery, particularly for kinases. Targeting the catalytic lysine of epidermal growth factor receptor (EGFR) has attracted attention as a new strategy to overcome resistance due to the emergence of C797S mutation. Sulfonyl fluoride derivatives able to inhibit EGFR^{L858R/T790M/C797S} by sulfonylation of Lys745 have been reported. However, atomistic details of this process are still poorly understood. Here, we describe the mechanism of inhibition of an innovative class of compounds that covalently engage the catalytic lysine of EGFR, through a sulfur(VI) fluoride exchange (SuFEx) process, with the help of hybrid quantum mechanics/molecular mechanics (QM/MM) and path collective variables (PCVs) approaches. Our simulations identify the chemical determinants accounting for the irreversible activity of agents targeting Lys745 and provide hints for the further optimization of sulfonyl fluoride agents.

Constant pH molecular dynamics simulations: Current status and recent applications

Many important protein functions are carried out through proton-coupled conformational dynamics. Thus, the ability to accurately model protonation states dynamically has wide-ranging implications. Over the past two decades, two main types of constant pH methods (discrete and continuous) have been developed to enable proton-coupled molecular dynamics (MD) simulations. In this short review, we discuss the current status of the development and highlight recent applications that have advanced our understanding of protein structure-function relationships. We conclude the review by outlining the remaining challenges in the method development and projecting important areas for future applications.

Finding inhibitors and deciphering inhibitor-induced conformational plasticity in the Janus kinase via multiscale simulations

The Janus kinase (JAK) is a master regulator of the JAK/STAT pathway. Dysregulation of this signalling cascade causes neuroinflammation and autoimmune disorders. Therefore, JAKs have been characterized as an attractive target for developing anti-inflammatory drugs. Nowadays, designing efficient, effective, and specific targeted therapeutics without being cytotoxic has gained interest. We performed the virtual screening of natural products in combination with pharmacological analyses. Subsequently, we performed molecular dynamics simulations to study the stability of the ligand-bound complexes and ligand-induced inactive conformations. Notably, inactive kinases display remarkable conformational plasticity; however, ligand-induced molecular mechanisms of these conformations are still poorly understood. Herein, we performed a free energy landscape analysis to explore the conformational plasticity of the JAK1 kinase. Leonurine, STOCK1N-68642, STOCK1N-82656, and STOCK1N-85809 bound JAK1 exhibited a smooth transition from an active (αC-in) to a completely inactive conformation (αC-out). Ligand binding induces disorders in the αC-helix. Molecular mechanics Poisson Boltzmann surface area (MM/PBSA) calculation suggested three phytochemicals, namely STOCK1N-68642, Epicatechin, and STOCK1N-98615, have higher binding affinity compared to other ligand molecules. The ligand-induced conformational plasticity revealed by our simulations differs significantly from the available crystal structures, which might help in designing allosteric drugs.

A Guide to the Continuous Constant pH Molecular Dynamics Methods in Amber and CHARMM [Article v1.0]

Like temperature and pressure, solution pH is an important environmental variable in biomolecular simulations. Virtually all proteins depend on pH to maintain their structure and function. In conventional molecular dynamics (MD) simulations of proteins, pH is implicitly accounted for by assigning and fixing protonation states of titratable sidechains. This is a significant limitation, as the assigned protonation states may be wrong and they may change during dynamics. In this tutorial, we guide the reader in learning and using the various continuous constant pH MD methods in Amber and CHARMM packages, which have been applied to predict pK a values and elucidate proton-coupled conformational dynamics of a variety of proteins including enzymes and membrane transporters.

The Conformational Transition Pathways and Hidden Intermediates in DFG-Flip Process of c-Met Kinase Revealed by Metadynamics Simulations

Protein kinases intrinsically translate their conformations between active and inactive states, which is key to their enzymatic activities. The conformational flipping of the three-residue conservative motif, Asp-Phe-Gly (DFG), is crucial for many kinases' biological functions. Obtaining a detailed demonstration of the DFG flipping process and its corresponding dynamical and thermodynamical features could broaden our understanding of kinases' conformation-activity relationship. In this study, we employed metadynamics simulation, a widely used enhanced sampling technique, to analyze the conformational transition pathways of the DFG flipping for the c-Met kinase. The corresponding free energy landscape suggested two distinct transition pathways between the "DFG-in" and "DFG-out" states of the DFG-flip from c-Met. On the basis of the orientation direction of the F1223 residue, we correspondingly named the two pathways the "DFG-up" path, featuring forming a commonly discovered "DFG-up" transition state, and the "DFG-down" path, a unique transition pathway with F1223 rotating along the opposite direction away from the hydrophobic cavity. The free energies along the two pathways were then calculated using the Path Collective Variable (PCV) metadynamics simulation. The simulation results showed that, though having similar free energy barriers, the free energy cuve for the DFG-down path suggested a two-step conformational transition mechanism, while that for the DFG-up path showed the one-step transition feature. The c-Met DFG flipping mechanism and the new intermediate state discovered in this work could provide a deeper understanding of the conformation-activity relationship for c-Met and, possibly, reveal a new conformational state as the drug target for c-Met and other similar kinases.

Phosphorylation-Induced Conformational Dynamics and Inhibition of Janus Kinase 1 by Suppressors of Cytokine Signaling 1

The dysfunction of the JAK/STAT (Janus kinase/signal transducers and activators of transcription) pathway results in several pathophysiological conditions, including autoimmune disorders. The negative feedback regulators of the JAK/STAT signaling pathway, suppressors of cytokine signaling (SOCS), act as a natural inhibitor of JAK and inhibit aberrant activity. SOCS1 is the most potent member of the SOCS family, whose kinase inhibitory region targets the substrate-binding groove of JAK with high affinity and blocks the phosphorylation of JAK kinases. Overall, we performed an aggregate of 13 μs molecular dynamics simulations on the activation loop's three different phosphorylation (double and single) states. Results from our simulations show that the single Tyr¹⁰³⁴ phosphorylation could stabilize the JAK1/SOCS1 complex as well as the flexible activation segment. The phosphate-binding loop (P-loop) shows conformational variability at dual and single phosphorylated states. Principal component analysis and protein structure network (PSN) analysis reveal that the different phosphorylation states and SOCS1 binding induce intermediate inactive conformations of JAK1, which could be a better target for future JAK1 selective drug design. PSN analysis suggests that the com-pY1034 system is stabilized due to higher values of network hubs than the other two complex systems. Moreover, the binding free energy calculations suggest that pTyr¹⁰³⁴ states show a higher affinity toward SOCS1 than the dual and pTyr¹⁰³⁵ states. We believe that the mechanistic understanding of JAK1/SOCS1 complexation will aid future studies related to peptide inhibitors based on SOCS1.

Mechanical force can enhance c-Src kinase activity by impairing autoinhibition

Cellular mechanosensing is pivotal for virtually all biological processes, and many molecular mechano-sensors and their way of function are being uncovered. In this work, we suggest that c-Src kinase acts as a direct mechano-sensor. c-Src is responsible for, among others, cell proliferation, and shows increased activity in stretched cells. In its native state, c-Src has little basal activity, because its kinase domain binds to an SH2 and SH3 domain. However, it is known that c-Src can bind to p130Cas, through which force can be transmitted to the membrane. Using molecular dynamics simulations, we show that force acting between the membrane-bound N-terminus of the SH3 domain and p130Cas induces partial SH3 unfolding, thereby impeding rebinding of the kinase domain onto SH2/SH3 and effectively enhancing kinase activity. Forces involved in this process are slightly lower or similar to the forces required to pull out c-Src from the membrane through the myristoyl linker, and key interactions involved in this anchoring are salt bridges between negative lipids and nearby basic residues in c-Src. Thus, c-Src appears to be a candidate for an intriguing mechanosensing mechanism of impaired kinase inhibition, which can be potentially tuned by membrane composition and other environmental factors.

Profiling MAP kinase cysteines for targeted covalent inhibitor design

Mitogen-activated protein kinases (MAPK) are important therapeutic targets, and yet no inhibitors have advanced to the market. Here we applied the GPU-accelerated continuous constant pH molecular dynamics (CpHMD) to calculate the pK a's and profile the cysteine reactivities of all 14 MAPKs for assisting the targeted covalent inhibitor design. The simulations not only recapitulated but also rationalized the reactive cysteines in the front pocket of JNK1/2/3 and the extended front pocket of p38α. Interestingly, the DFG - 1 cysteine in the DFG-in conformation of ERK1/ERK2 was found somewhat reactive or unreactive; however, simulations of MKK7 showed that switching to the DFG-out conformation makes the DFG - 1 cysteine reactive, suggesting the advantage of type II covalent inhibitors. Additionally, the simulations prospectively predicted several druggable cysteine and lysine sites, including the αH head cysteine in JNK1/3 and DFG + 6 cysteine in JNK2, corroborating the chemical proteomic screening data. Given the low cost and the ability to offer physics-based rationales, we envision CpHMD simulations to complement the chemo-proteomic platform for systematic profiling cysteine reactivities for targeted covalent drug discovery.

Activation of Abl1 Kinase Explored Using Well-Tempered Metadynamics Simulations on an Essential Dynamics Sampled Path

Well-tempered metadynamics (wT-metaD) simulations using path collective variables (CVs) have been successfully applied in recent years to explore conformational transitions in protein kinases and other biomolecular systems. While this methodology has the advantage of describing the transitions with a limited number of predefined path CVs, it requires as an input a reference path connecting the initial and target states of the system. It is desirable to automate the path generation using approaches that do not rely on the choice of geometric CVs to describe the transition of interest. To this end, we developed an approach that couples essential dynamics sampling with wT-metaD simulations. We used this newly developed procedure to explore the activation mechanism of Abl1 kinase and compute the associated free energy barriers. Through these simulations, we identified a three-step mechanism for the activation that involved two metastable intermediates that possessed a partially open activation loop and differed primarily in the “in” or “out” conformation of the aspartate residue of the DFG motif. One of these states is similar to a conformation that was detected in previous spectroscopic studies of Abl1 kinase, albeit its mechanistic role in the activation was hitherto not well understood. The present study establishes its intermediary role in the activation and predicts a rate-determining free energy barrier of 13.8 kcal/mol that is in good agreement with previous experimental and computational estimates. Overall, our study demonstrates the usability of essential dynamics sampling as a path CV in wT-metaD to conveniently study conformational transitions and accurately calculate the associated barriers.

Reactivities of the Front Pocket N-Terminal Cap Cysteines in Human Kinases

The front pocket (FP) N-terminal cap (Ncap) cysteine is the most popular site of covalent modification in kinases. A long-standing hypothesis associates the Ncap position with cysteine hyper-reactivity; however, traditional computational predictions suggest that the FP Ncap cysteines are predominantly unreactive. Here we applied the state-of-the-art continuous constant pH molecular dynamics (CpHMD) to test the Ncap hypothesis. Simulations found that the Ncap cysteines of BTK/BMX/TEC/ITK/TXK, JAK3, and MKK7 are reactive to varying degrees; however, those of BLK and EGFR/ERBB2/ERBB4 possessing a Ncap+3 aspartate are unreactive. Analysis suggested that hydrogen bonding and electrostatic interactions drive the reactivity, and their absence renders the Ncap cysteine unreactive. To further test the Ncap hypothesis, we examined the FP Ncap+2 cysteines in JNK1/JNK2/JNK3 and CASK. Our work offers a systematic understanding of the cysteine structure-reactivity relationship and illustrates the use of CpHMD to differentiate cysteines toward the design of targeted covalent inhibitors with reduced chemical reactivities.

Reduced efficacy of a Src kinase inhibitor in crowded protein solution

The inside of a cell is highly crowded with proteins and other biomolecules. How proteins express their specific functions together with many off-target proteins in crowded cellular environments is largely unknown. Here, we investigate an inhibitor binding with c-Src kinase using atomistic molecular dynamics (MD) simulations in dilute as well as crowded protein solution. The populations of the inhibitor, 4-amino-5-(4-methylphenyl)-7-(t-butyl)pyrazolo[3,4-d]pyrimidine (PP1), in bulk solution and on the surface of c-Src kinase are reduced as the concentration of crowder bovine serum albumins (BSAs) increases. This observation is consistent with the reduced PP1 inhibitor efficacy in experimental c-Src kinase assays in addition with BSAs. The crowded environment changes the major binding pathway of PP1 toward c-Src kinase compared to that in dilute solution. This change is explained based on the population shift mechanism of local conformations near the inhibitor binding site in c-Src kinase.

Atomistic dynamics of a viral infection process: Release of membrane lytic peptides from a non-enveloped virus

Molecular simulations have played an instrumental role in uncovering the structural dynamics and physical properties of virus capsids. In this work, we move beyond equilibrium physicochemical characterization of a virus system to study a stage of the infection process that is required for viral proliferation. Despite many biochemical and functional studies, the molecular mechanism of host cell entry by non-enveloped viruses remains largely unresolved. Flock House virus (FHV) is a model system for non-enveloped viruses and is the subject of the current study. FHV infects through the acid-dependent endocytic pathway, where low pH triggers externalization of membrane-disrupting (γ) peptides from the capsid interior. Using all-atom equilibrium and enhanced sampling simulations, the mechanism and energetics of γ peptide liberation and the effect of pH on this process are investigated. Our computations agree with experimental findings and reveal nanoscopic details regarding the pH control mechanism, which are not readily accessible in experiments.

Type II Binders Targeting the "GLR-Out" Conformation of the Pseudokinase STRADα

Pseudokinases play important roles in signal transduction and cellular processes similar to those of catalytically competent kinases. However, pseudokinase pharmacological tractability and conformational space accessibility are poorly understood. Pseudokinases have only recently been suggested to adopt "inactive" conformations or interact with conformation-specific kinase inhibitors (e.g., type II compounds). In this work, the heavily substituted pseudokinase STRADα, which possesses a DFG → GLR substitution in the catalytic site that permits nucleotide binding while impairing divalent cation coordination, is used as a test case to demonstrate the potential applicability of conformation-specific, type II compounds to pseudokinase pharmacology. Integrated structural modeling is employed to generate a "GLR-out" conformational ensemble. Likely interacting type II compounds are identified through virtual screening against this ensemble model. Biophysical validation of compound binding is demonstrated through protein thermal stabilization and ATP competition. Localization of a top-performing compound through surface methylation strongly suggests that STRADα can adopt the "GLR-out" conformation and interact with compounds that comply with the standard type II pharmacophore. These results suggest that, despite a loss of catalytic function, some pseudokinases, including STRADα, may retain the conformational switching properties of conventional protein kinases.

Continuous Constant pH Molecular Dynamics Simulations of Transmembrane Proteins

Many membrane channels, transporters, and receptors utilize a pH gradient or proton coupling to drive functionally relevant conformational transitions. Conventional molecular dynamics simulations employ fixed protonation states, thus neglecting the coupling between protonation and conformational equilibria. Here we describe the membrane-enabled hybrid-solvent continuous constant pH molecular dynamics method for capturing atomic details of proton-coupled conformational dynamics of transmembrane proteins. Example protocols from our recent application studies of proton channels and ion/substrate transporters are discussed.

All-atom adaptively biased path optimization of Src kinase conformational inactivation: Switched electrostatic network in the concerted motion of αC helix and the activation loop

A method to optimize a conformational pathway through a space of well-chosen reduced variables is employed to advance our understanding of protein conformational equilibrium. The adaptively biased path optimization strategy utilizes unrestricted, enhanced sampling in the region of a path in the reduced-variable space to identify a broad path between two stable end-states. Application to the inactivation transition of the Src tyrosine kinase catalytic domain reveals new insight into this well studied conformational equilibrium. The mechanistic description gained from identifying the motions and structural features along the path includes details of the switched electrostatic network found to underpin the transition. The free energy barrier along the path results from rotation of a helix, αC, that is tightly correlated with motions in the activation loop (A-loop) as well as distal regions in the C-lobe. Path profiles of the reduced variables clearly demonstrate the strongly correlated motions. The exchange of electrostatic interactions among residues in the network is key to these interdependent motions. In addition, the increased resolution from an all-atom model in defining the path shows multiple components for the A-loop motion and that different parts of the A-loop contribute throughout the length of the path.

Protonation-Induced Dynamic Allostery in PDZ Domain: Evidence of Perturbation-Independent Universal Response Network

Dynamic allostery is a relatively new paradigm where certain external perturbations may lead to modulation of conformational dynamics at a distant part of a protein without significant changes in the overall structure. While most well-characterized examples of dynamic allostery involve binding with other entities like small molecules, peptides, or nucleic acids, in this work we demonstrate that chemical modifications like protonation may lead to significant dynamical allosteric response in a PDZ domain protein. Tuning the protonation states of two histidine residues (H317 and H372), we identify the allosteric pathways responsible for the dynamic response. Interestingly, the same set of residues that constitute the allosteric response network upon ligand binding seem to be responsible for protonation-induced dynamic allostery. Thus, we propose the existence of an inherent universal response network in signaling proteins, where the same set of residues can respond to varying types of external perturbations in terms of rearrangement of hydrogen-bonded network and redistribution of electrostatic interaction energies.

Alternative proton-binding site and long-distance coupling in Escherichia coli sodium-proton antiporter NhaA

Escherichia coli NhaA is a prototypical sodium-proton antiporter responsible for maintaining cellular ion and volume homeostasis by exchanging two protons for one sodium ion; despite two decades of research, the transport mechanism of NhaA remains poorly understood. Recent crystal structure and computational studies suggested Lys300 as a second proton-binding site; however, functional measurements of several K300 mutants demonstrated electrogenic transport, thereby casting doubt on the role of Lys300. To address the controversy, we carried out state-of-the-art continuous constant pH molecular dynamics simulations of NhaA mutants K300A, K300R, K300Q/D163N, and K300Q/D163N/D133A. Simulations suggested that K300 mutants maintain the electrogenic transport by utilizing an alternative proton-binding residue Asp133. Surprisingly, while Asp133 is solely responsible for binding the second proton in K300R, Asp133 and Asp163 jointly bind the second proton in K300A, and Asp133 and Asp164 jointly bind two protons in K300Q/D163N. Intriguingly, the coupling between Asp133 and Asp163 or Asp164 is enabled through the proton-coupled hydrogen-bonding network at the flexible intersection of two disrupted helices. These data resolve the controversy and highlight the intricacy of the compensatory transport mechanism of NhaA mutants. Alternative proton-binding site and proton sharing between distant aspartates may represent important general mechanisms of proton-coupled transport in secondary active transporters.

Proton-sensing G protein-coupled receptors: detectors of tumor acidosis and candidate drug targets

Cells in tumor microenvironments (TMEs) use several mechanisms to sense their low pH (<7.0), including via proton-sensing G protein-coupled receptors (psGPCRs): GPR4, GPR65/TDAG8, GPR68/OGR1 and GPR132/G2A. Numerous cancers have increased expression of psGPCRs. The psGPCRs may contribute to features of the malignant phenotype via actions on specific cell-types in the TME and thereby promote tumor survival and growth. Here, we review data regarding psGPCR expression in tumors and cancer cells, impact of psGPCRs on survival in solid tumors and a bioinformatics approach to infer psGPCR expression in cell types in the TME. New tools are needed to help define contributions of psGPCRs in tumor biology and to identify potentially novel therapeutic agents for a variety of cancers.

Discovery of candesartan cilexetic as a novel neddylation inhibitor for suppressing tumor growth

Protein neddylation is a posttranslational modification of conjugating the neuronal precursor cell-expressed developmentally down-regulated protein 8 (Nedd8) to substrates. Our previous work revealed that neddylation pathway is overactivated in various human lung cancers and correlates with the disease progression, whereas pharmacologically targeting this pathway has emerged as an attractive therapeutic strategy. As a follow-up research, 1331 approved drugs were investigated the inhibitory activities of cullin1 neddylation for screening the hit compounds via an improved enzyme-based assay. An antihypertensive agent, candesartan cilexetic (CDC), was identified as a novel neddylation inhibitor that ATP-competitively suppressing Nedd8-activating enzyme (NAE, E1) in mechanism, which inhibited the cullins neddylation superior than two representative non-covalent NAE inhibitors, M22 and mitoxantrone. Following with the findings such as apoptotic induction and tumor growth suppression in human lung cancer A549 in vitro and in vivo, CDC represents a potential anticancer lead compound with promising neddylation inhibitory activity.