An electrostatic network and long-range regulation of Src kinases

Computational analysis of regulatory regions in human protein kinases

Eukaryotic proteins often feature modular domain structures comprising globular domains that are connected by linker regions and intrinsically disordered regions that may contain important functional motifs. The intramolecular interactions of globular domains and nonglobular regions can play critical roles in different aspects of protein function. However, studying these interactions and their regulatory roles can be challenging due to the flexibility of nonglobular regions, the long insertions separating interacting modules, and the transient nature of some interactions. Obtaining the experimental structures of multiple domains and functional regions is more difficult than determining the structures of individual globular domains. High-quality structural models generated by AlphaFold offer a unique opportunity to study intramolecular interactions in eukaryotic proteins. In this study, we systematically explored intramolecular interactions between human protein kinase domains (KDs) and potential regulatory regions, including globular domains, N- and C-terminal tails, long insertions, and distal nonglobular regions. Our analysis identified intramolecular interactions between human KDs and 35 different types of globular domains, exhibiting a variety of interaction modes that could contribute to orthosteric or allosteric regulation of kinase activity. We also identified prevalent interactions between human KDs and their flanking regions (N- and C-terminal tails). These interactions exhibit group-specific characteristics and can vary within each specific kinase group. Although long-range interactions between KDs and nonglobular regions are relatively rare, structural details of these interactions offer new insights into the regulation mechanisms of several kinases, such as HASPIN, MAPK7, MAPK15, and SIK1B.

TYROSINE KINASES: COMPLEX MOLECULAR SYSTEMS CHALLENGING COMPUTATIONAL METHODOLOGIES

Classical molecular dynamics (MD) simulations based on atomic models play an increasingly important role in a wide range of applications in physics, biology, and chemistry. Nonetheless, generating genuine knowledge about biological systems using MD simulations remains challenging. Protein tyrosine kinases are important cellular signaling enzymes that regulate cell growth, proliferation, metabolism, differentiation, and migration. Due to the large conformational changes and long timescales involved in their function, these kinases present particularly challenging problems to modern computational and theoretical frameworks aimed at elucidating the dynamics of complex biomolecular systems. Markov state models have achieved limited success in tackling the broader conformational ensemble and biased methods are often employed to examine specific long timescale events. Recent advances in machine learning continue to push the limitations of current methodologies and provide notable improvements when integrated with the existing frameworks. A broad perspective is drawn from a critical review of recent studies.

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.

Entropy Hotspots for the Binding of Intrinsically Disordered Ligands to a Receptor Domain

Proline-rich motifs (PRMs) are widely used for mediating protein-protein interactions with weak binding affinities. Because they are intrinsically disordered when unbound, conformational entropy plays a significant role for the binding. However, residue-level differences of the entropic contribution in the binding of different ligands remain not well understood. We use all-atom molecular dynamics simulation and the maximal information spanning tree formalism to analyze conformational entropy associated with the binding of two PRMs, one from the Abl kinase and the other from the nonstructural protein 1 of the 1918 Spanish influenza A virus, to the N-terminal SH3 (nSH3) domain of the CrkII protein. Side chains of the stably folded nSH3 experience more entropy change upon ligand binding than the backbone, whereas PRMs involve comparable but heterogeneous entropy changes among the backbone and side chains. In nSH3, two conserved nonpolar residues forming contacts with the PRM experience the largest side-chain entropy loss. In contrast, the C-terminal charged residues of PRMs that form polar contacts with nSH3 experience the greatest side-chain entropy loss, although their "fuzzy" nature is attributable to the backbone that remains relatively flexible. Thus, residues that form high-occupancy contacts between nSH3 and PRM do not reciprocally contribute to entropy loss. Furthermore, certain surface residues of nSH3 distal to the interface with PRMs gain entropy, indicating a nonlocal effect of ligand binding. Comparing between the PRMs from cAbl and nonstructural protein 1, the latter involves a larger side-chain entropy loss and forms more contacts with nSH3. Consistent with experiments, this indicates stronger binding of the viral ligand at the expense of losing the flexibility of side chains, whereas the backbone experiences less entropy loss. The entropy "hotspots" as identified in this study will be important for tuning the binding affinity of various ligands to a receptor.

Towards simple kinetic models of functional dynamics for a kinase subfamily

Kinases are ubiquitous enzymes involved in the regulation of critical cellular pathways. However, in silico modelling of the conformational ensembles of these enzymes is difficult due to inherent limitations and the cost of computational approaches. Recent algorithmic advances combined with homology modelling and parallel simulations have enabled researchers to address this computational sampling bottleneck. Here, we present the results of molecular dynamics studies for seven Src family kinase (SFK) members: Fyn, Lyn, Lck, Hck, Fgr, Yes and Blk. We present a sequence invariant extension to Markov state models, which allows us to quantitatively compare the structural ensembles of the seven kinases. Our findings indicate that in the absence of their regulatory partners, SFK members have similar in silico dynamics with active state populations ranging from 4 to 40% and activation timescales in the hundreds of microseconds. Furthermore, we observe several potentially druggable intermediate states, including a pocket next to the adenosine triphosphate binding site that could potentially be targeted via a small-molecule inhibitor.

Millisecond dynamics of BTK reveal kinome-wide conformational plasticity within the apo kinase domain

Bruton tyrosine kinase (BTK) is a key enzyme in B-cell development whose improper regulation causes severe immunodeficiency diseases. Design of selective BTK therapeutics would benefit from improved, in-silico structural modeling of the kinase’s solution ensemble. However, this remains challenging due to the immense computational cost of sampling events on biological timescales. In this work, we combine multi-millisecond molecular dynamics (MD) simulations with Markov state models (MSMs) to report on the thermodynamics, kinetics, and accessible states of BTK’s kinase domain. Our conformational landscape links the active state to several inactive states, connected via a structurally diverse intermediate. Our calculations predict a kinome-wide conformational plasticity, and indicate the presence of several new potentially druggable BTK states. We further find that the population of these states and the kinetics of their inter-conversion are modulated by protonation of an aspartate residue, establishing the power of MD & MSMs in predicting effects of chemical perturbations.

Functional validation reveals the novel missense V419L variant in TGFBR2 associated with Loeys-Dietz syndrome (LDS) impairs canonical TGF-β signaling

TGF-β-related heritable connective tissue disorders are characterized by a similar pattern of cardiovascular defects, including aortic root dilatation, mitral valve prolapse, vascular aneurysms, and vascular dissections and exhibit incomplete penetrance and variable expressivity. Because of the phenotypic overlap of these disorders, panel-based genetic testing is frequently used to confirm the clinical findings. Unfortunately in many cases, variants of uncertain significance (VUSs) obscure the genetic diagnosis until more information becomes available. Here, we describe and characterize the functional impact of a novel VUS in the TGFBR2 kinase domain (c.1255G>T; p.Val419Leu), in a patient with the clinical diagnosis of Marfan syndrome spectrum. We assessed the structural and functional consequence of this VUS using molecular modeling, molecular dynamic simulations, and in vitro cell-based assays. A high-quality homology-based model of TGFBR2 was generated and computational mutagenesis followed by refinement and molecular dynamics simulations were used to assess structural and dynamic changes. Relative to wild type, the V419L induced conformational and dynamic changes that may affect ATP binding, increasing the likelihood of adopting an inactive state, and, we hypothesize, alter canonical signaling. Experimentally, we tested this by measuring the canonical TGF-β signaling pathway activation at two points; V419L significantly delayed SMAD2 phosphorylation by western blot and significantly decreased TGF-β-induced gene transcription by reporter assays consistent with known pathogenic variants in this gene. Thus, our results establish that the V419L variant leads to aberrant TGF-β signaling and confirm the diagnosis of Loeys-Dietz syndrome in this patient.

Molecular dynamics simulations reveal the conformational dynamics of Arabidopsis thaliana BRI1 and BAK1 receptor-like kinases

The structural motifs responsible for activation and regulation of eukaryotic protein kinases in animals have been studied extensively in recent years, and a coherent picture of their activation mechanisms has begun to emerge. In contrast, non-animal eukaryotic protein kinases are not as well understood from a structural perspective, representing a large knowledge gap. To this end, we investigated the conformational dynamics of two key Arabidopsis thaliana receptor-like kinases, brassinosteroid-insensitive 1 (BRI1) and BRI1-associated kinase 1 (BAK1), through extensive molecular dynamics simulations of their fully phosphorylated kinase domains. Molecular dynamics simulations calculate the motion of each atom in a protein based on classical approximations of interatomic forces, giving researchers insight into protein function at unparalleled spatial and temporal resolutions. We found that in an otherwise "active" BAK1 the αC helix is highly disordered, a hallmark of deactivation, whereas the BRI1 αC helix is moderately disordered and displays swinging behavior similar to numerous animal kinases. An analysis of all known sequences in the A. thaliana kinome found that αC helix disorder may be a common feature of plant kinases.

Tyrosine Kinase Activation and Conformational Flexibility: Lessons from Src-Family Tyrosine Kinases

Protein kinases are enzymes that catalyze the covalent transfer of the γ-phosphate of an adenosine triphosphate (ATP) molecule onto a tyrosine, serine, threonine, or histidine residue in the substrate and thus send a chemical signal to networks of downstream proteins. They are important cellular signaling enzymes that regulate cell growth, proliferation, metabolism, differentiation, and migration. Unregulated protein kinase activity is often associated with a wide range of diseases, therefore making protein kinases major therapeutic targets. A prototypical system of central interest to understand the regulation of kinase activity is provided by tyrosine kinase c-Src, which belongs to the family of Src-related non-receptor tyrosine kinases (SFKs). Although the broad picture of autoinhibition via the regulatory domains and via the phosphorylation of the C-terminal tail is well characterized from a structural point of view, a detailed mechanistic understanding at the atomic-level is lacking. Advanced computational methods based on all-atom molecular dynamics (MD) simulations are employed to advance our understanding of tyrosine kinase activation. The computational studies suggest that the isolated kinase domain (KD) is energetically most favorable in the inactive conformation when the activation loop (A-loop) of the KD is not phosphorylated. The KD makes transient visits to a catalytically competent active-like conformation. The process of bimolecular trans-autophosphorylation of the A-loop eventually locks the KD in the active state. Activating point mutations may act by slightly increasing the population of the active-like conformation, enhancing the availability of the A-loop to be phosphorylated. The Src-homology 2 (SH2) and Src-homology 3 (SH3) regulatory domains, depending upon their configuration, either promote the inactive or the active state of the kinase domain. In addition to the roles played by the SH3, SH2, and KD, the Src-homology 4-Unique domain (SH4-U) region also serves as a key moderator of substrate specificity and kinase function. Thus, a fundamental understanding of the conformational propensity of the SH4-U region and how this affects the association to the membrane surface are likely to lead to the discovery of new intermediate states and alternate strategies for inhibition of kinase activity for drug discovery. The existence of a multitude of KD conformations poses a great challenge aimed at the design of specific inhibitors. One promising computational strategy to explore the conformational flexibility of the KD is to construct Markov state models from aggregated MD data.

Dynamic, structural and thermodynamic basis of insulin-like growth factor 1 kinase allostery mediated by activation loop phosphorylation

Despite the importance of kinases' catalytic activity regulation in cell signaling, detailed mechanisms underlying their activity regulation are poorly understood. Herein, using insulin-like growth factor 1 receptor kinase (IGF-1RK) as a model, the mechanisms of kinase regulation by its activation loop (A-loop) phosphorylation were investigated through molecular dynamics (MD) and alchemical free energy simulations. Analyses of the simulation results and free energy landscapes determined for the entire catalytic cycle of the kinase revealed that A-loop phosphorylation affects each step in the IGF-1RK catalytic cycle, including conformational change, substrate binding/product release and catalytic phosphoryl transfer. Specifically, the conformational equilibrium of the kinase is shifted by 13.2 kcal mol-1 to favor the active conformation after A-loop phosphorylation, which increases substrate binding affinity of the activated kinase. This free energy shift is achieved primarily via destabilization of the inactive conformation. The free energy of the catalytic reaction is also changed by 3.3 kcal mol-1 after the phosphorylation and in the end, facilitates product release. Analyses of MD simulations showed that A-loop phosphorylation produces these energetic effects by perturbing the side chain interactions around each A-loop tyrosine. These interaction changes are propagated to the remainder of the kinase to modify the orientations and dynamics of the αC-helix and A-loop, and together yield the observed free energy changes. Since many protein kinases share similar interactions identified in this work, the mechanisms of kinase allostery and catalysis unraveled here can be applicable to them.

The Activation of c-Src Tyrosine Kinase: Conformational Transition Pathway and Free Energy Landscape

Tyrosine kinases are important cellular signaling allosteric enzymes that regulate cell growth, proliferation, metabolism, differentiation, and migration. Their activity must be tightly controlled, and malfunction can lead to a variety of diseases, particularly cancer. The nonreceptor tyrosine kinase c-Src, a prototypical model system and a representative member of the Src-family, functions as complex multidomain allosteric molecular switches comprising SH2 and SH3 domains modulating the activity of the catalytic domain. The broad picture of self-inhibition of c-Src via the SH2 and SH3 regulatory domains is well characterized from a structural point of view, but a detailed molecular mechanism understanding is nonetheless still lacking. Here, we use advanced computational methods based on all-atom molecular dynamics simulations with explicit solvent to advance our understanding of kinase activation. To elucidate the mechanism of regulation and self-inhibition, we have computed the pathway and the free energy landscapes for the "inactive-to-active" conformational transition of c-Src for different configurations of the SH2 and SH3 domains. Using the isolated c-Src catalytic domain as a baseline for comparison, it is observed that the SH2 and SH3 domains, depending upon their bound orientation, promote either the inactive or active state of the catalytic domain. The regulatory structural information from the SH2-SH3 tandem is allosterically transmitted via the N-terminal linker of the catalytic domain. Analysis of the conformational transition pathways also illustrates the importance of the conserved tryptophan 260 in activating c-Src, and reveals a series of concerted events during the activation process.

Hsp90 dependence of a kinase is determined by its conformational landscape

Heat shock protein 90 (Hsp90) is an abundant molecular chaperone, involved in the folding and activation of 60% of the human kinome. The oncogenic tyrosine kinase v-Src is one of the most stringent client proteins of Hsp90, whereas its almost identical homolog c-Src is only weakly affected by the chaperone. Here, we perform atomistic molecular simulations and in vitro kinase assays to explore the mechanistic differences in the activation of v-Src and c-Src. While activation in c-Src is strictly controlled by ATP-binding and phosphorylation, we find that activating conformational transitions are spontaneously sampled in Hsp90-dependent Src mutants. Phosphorylation results in an enrichment of the active conformation and in an increased affinity for Hsp90. Thus, the conformational landscape of the mutated kinase is reshaped by a broken “control switch”, resulting in perturbations of long-range electrostatics, higher activity and increased Hsp90-dependence.

Molecular modeling and molecular dynamic simulation of the effects of variants in the TGFBR2 kinase domain as a paradigm for interpretation of variants obtained by next generation sequencing

Variants in the TGFBR2 kinase domain cause several human diseases and can increase propensity for cancer. The widespread application of next generation sequencing within the setting of Individualized Medicine (IM) is increasing the rate at which TGFBR2 kinase domain variants are being identified. However, their clinical relevance is often uncertain. Consequently, we sought to evaluate the use of molecular modeling and molecular dynamics (MD) simulations for assessing the potential impact of variants within this domain. We documented the structural differences revealed by these models across 57 variants using independent MD simulations for each. Our simulations revealed various mechanisms by which variants may lead to functional alteration; some are revealed energetically, while others structurally or dynamically. We found that the ATP binding site and activation loop dynamics may be affected by variants at positions throughout the structure. This prediction cannot be made from the linear sequence alone. We present our structure-based analyses alongside those obtained using several commonly used genomics-based predictive algorithms. We believe the further mechanistic information revealed by molecular modeling will be useful in guiding the examination of clinically observed variants throughout the exome, as well as those likely to be discovered in the near future by clinical tests leveraging next-generation sequencing through IM efforts.

An electrostatic selection mechanism controls sequential kinase signaling downstream of the T cell receptor

The sequence of events that initiates T cell signaling is dictated by the specificities and order of activation of the tyrosine kinases that signal downstream of the T cell receptor. Using a platform that combines exhaustive point-mutagenesis of peptide substrates, bacterial surface-display, cell sorting, and deep sequencing, we have defined the specificities of the first two kinases in this pathway, Lck and ZAP-70, for the T cell receptor ζ chain and the scaffold proteins LAT and SLP-76. We find that ZAP-70 selects its substrates by utilizing an electrostatic mechanism that excludes substrates with positively-charged residues and favors LAT and SLP-76 phosphosites that are surrounded by negatively-charged residues. This mechanism prevents ZAP-70 from phosphorylating its own activation loop, thereby enforcing its strict dependence on Lck for activation. The sequence features in ZAP-70, LAT, and SLP-76 that underlie electrostatic selectivity likely contribute to the specific response of T cells to foreign antigens.

Ensembler: Enabling High-Throughput Molecular Simulations at the Superfamily Scale

The rapidly expanding body of available genomic and protein structural data provides a rich resource for understanding protein dynamics with biomolecular simulation. While computational infrastructure has grown rapidly, simulations on an omics scale are not yet widespread, primarily because software infrastructure to enable simulations at this scale has not kept pace. It should now be possible to study protein dynamics across entire (super)families, exploiting both available structural biology data and conformational similarities across homologous proteins. Here, we present a new tool for enabling high-throughput simulation in the genomics era. Ensembler takes any set of sequences—from a single sequence to an entire superfamily—and shepherds them through various stages of modeling and refinement to produce simulation-ready structures. This includes comparative modeling to all relevant PDB structures (which may span multiple conformational states of interest), reconstruction of missing loops, addition of missing atoms, culling of nearly identical structures, assignment of appropriate protonation states, solvation in explicit solvent, and refinement and filtering with molecular simulation to ensure stable simulation. The output of this pipeline is an ensemble of structures ready for subsequent molecular simulations using computer clusters, supercomputers, or distributed computing projects like Folding@home. Ensembler thus automates much of the time-consuming process of preparing protein models suitable for simulation, while allowing scalability up to entire superfamilies. A particular advantage of this approach can be found in the construction of kinetic models of conformational dynamics—such as Markov state models (MSMs)—which benefit from a diverse array of initial configurations that span the accessible conformational states to aid sampling. We demonstrate the power of this approach by constructing models for all catalytic domains in the human tyrosine kinase family, using all available kinase catalytic domain structures from any organism as structural templates. Ensembler is free and open source software licensed under the GNU General Public License (GPL) v2. It is compatible with Linux and OS X. The latest release can be installed via the conda package manager, and the latest source can be downloaded from https://github.com/choderalab/ensembler.

Proteins are the workhorses of the human body, and are involved in essentially every biological process. Many diseases are caused by proteins malfunctioning. To understand how a protein functions, it is necessary to know its physical properties. The field of structural biology provides many techniques for determining the three-dimensional structure of a protein. The dynamics of a protein, i.e. the way it moves, are of equal importance, but are more difficult to uncover with traditional experimental techniques. Computer simulations are an effective alternative method for understanding protein dynamics, but require experimental structural information as a starting point. While recent advances in genomics and experimental techniques have provided a wealth of such structural data, the appropriate software for using this data effectively has been lacking. To tackle this problem, we have developed a software package called Ensembler, which allows a user to automatically select appropriate experimentally derived structures for a given protein or family of proteins, and to use them to prepare a series of simulations. The resultant simulation data can then used to investigate the dynamics of the protein(s) in question, and their involvement in disease.

Dynamic Allostery Mediated by a Conserved Tryptophan in the Tec Family Kinases

Bruton’s tyrosine kinase (Btk) is a Tec family non-receptor tyrosine kinase that plays a critical role in immune signaling and is associated with the immunological disorder X-linked agammaglobulinemia (XLA). Our previous findings showed that the Tec kinases are allosterically activated by the adjacent N-terminal linker. A single tryptophan residue in the N-terminal 17-residue linker mediates allosteric activation, and its mutation to alanine leads to the complete loss of activity. Guided by hydrogen/deuterium exchange mass spectrometry results, we have employed Molecular Dynamics simulations, Principal Component Analysis, Community Analysis and measures of node centrality to understand the details of how a single tryptophan mediates allostery in Btk. A specific tryptophan side chain rotamer promotes the functional dynamic allostery by inducing coordinated motions that spread across the kinase domain. Either a shift in the rotamer population, or a loss of the tryptophan side chain by mutation, drastically changes the coordinated motions and dynamically isolates catalytically important regions of the kinase domain. This work also identifies a new set of residues in the Btk kinase domain with high node centrality values indicating their importance in transmission of dynamics essential for kinase activation. Structurally, these node residues appear in both lobes of the kinase domain. In the N-lobe, high centrality residues wrap around the ATP binding pocket connecting previously described Catalytic-spine residues. In the C-lobe, two high centrality node residues connect the base of the R- and C-spines on the αF-helix. We suggest that the bridging residues that connect the catalytic and regulatory architecture within the kinase domain may be a crucial element in transmitting information about regulatory spine assembly to the catalytic machinery of the catalytic spine and active site.

Bruton’s tyrosine kinase (Btk) belongs to the Tec family of protein tyrosine kinases, and plays a crucial role in the signaling pathway in B-cells. Alteration of Btk activity results in the serious immunological disorder, X-linked agammaglobulinemia. Btk is a multi-domain protein and the activity of the kinase domain is regulated by the adjacent non-catalytic domains, which mediate their effect by means of a conserved tryptophan residue. In this work, we have investigated the mechanism of regulation by this tryptophan residue, W395, in the linker preceding the Btk kinase domain. Using hydrogen-deuterium exchange mass spectrometry and molecular dynamics simulations we identify structural elements within the kinase domain that are required for function by transmitting the allosteric effects of W395. Molecular Dynamics simulations further guided us to delineate the kinase domain into dynamically correlated sets of residues using community analysis, thereby identifying the important communication nodes that connect the various elements of the kinase domain required for function. The analyses performed indicate clearly how the W395A mutant changes the communication pathway required for function.

Evaluating the dynamics and electrostatic interactions of folded proteins in implicit solvents

Three implicit solvent models, namely GBMVII, FACTS, and SCPISM, were evaluated for their abilities to emulate an explicit solvent environment by comparing the simulated conformational ensembles, dynamics, and electrostatic interactions of the Src SH2 domain and the Lyn kinase domain. This assessment in terms of structural features in folded proteins expands upon the use of hydration energy as a metric for comparison. All-against-all rms coordinate deviation, average positional fluctuations, and ion-pair distance distribution were used to compare the implicit solvent models with the TIP3P explicit solvent model. Our study shows that the Src SH2 domains solvated with TIP3P, GBMVII, and FACTS sample similar global conformations. Additionally, the Src SH2 ion-pair distance distributions of solvent-exposed side chains corresponding to TIP3P, GBMVII, and FACTS do not differ substantially, indicating that GBMVII and FACTS are capable of modeling these electrostatic interactions. The ion-pair distance distributions of SCPISM are distinct from others, demonstrating that these electrostatic interactions are not adequately reproduced with the SCPISM model. On the other hand, for the Lyn kinase domain, a non-globular protein with bilobal structure and a large concavity on the surface, implicit solvent does not accurately model solvation to faithfully reproduce partially buried electrostatic interactions and lobe-lobe conformations. Our work reveals that local structure and dynamics of small, globular proteins are modeled well using FACTS and GBMVII. Nonetheless, global conformations and electrostatic interactions in concavities of multi-lobal proteins resulting from simulations with implicit solvent models do not match those obtained from explicit water simulations.

Lack of Dependence of the Sizes of the Mesoscopic Protein Clusters on Electrostatics

Protein-rich clusters of steady submicron size and narrow size distribution exist in protein solutions in apparent violation of the classical laws of phase equilibrium. Even though they contain a minor fraction of the total protein, evidence suggests that they may serve as essential precursors for the nucleation of ordered solids such as crystals, sickle-cell hemoglobin polymers, and amyloid fibrils. The cluster formation mechanism remains elusive. We use the highly basic protein lysozyme at nearly neutral and lower pH as a model and explore the response of the cluster population to the electrostatic forces, which govern numerous biophysical phenomena, including crystallization and fibrillization. We tune the strength of intermolecular electrostatic forces by varying the solution ionic strength I and pH and find that despite the weaker repulsion at higher I and pH, the cluster size remains constant. Cluster responses to the presence of urea and ethanol demonstrate that cluster formation is controlled by hydrophobic interactions between the peptide backbones, exposed to the solvent after partial protein unfolding that may lead to transient protein oligomers. These findings reveal that the mechanism of the mesoscopic clusters is fundamentally different from those underlying the two main classes of ordered protein solid phases, crystals and amyloid fibrils, and partial unfolding of the protein chain may play a significant role.

Heat dissipation guides activation in signaling proteins

Life is fundamentally a nonequilibrium phenomenon. At the expense of dissipated energy, living things perform irreversible processes that allow them to propagate and reproduce. Within cells, evolution has designed nanoscale machines to do meaningful work with energy harnessed from a continuous flux of heat and particles. As dictated by the Second Law of Thermodynamics and its fluctuation theorem corollaries, irreversibility in nonequilibrium processes can be quantified in terms of how much entropy such dynamics produce. In this work, we seek to address a fundamental question linking biology and nonequilibrium physics: can the evolved dissipative pathways that facilitate biomolecular function be identified by their extent of entropy production in general relaxation processes? We here synthesize massive molecular dynamics simulations, Markov state models (MSMs), and nonequilibrium statistical mechanical theory to probe dissipation in two key classes of signaling proteins: kinases and G-protein-coupled receptors (GPCRs). Applying machinery from large deviation theory, we use MSMs constructed from protein simulations to generate dynamics conforming to positive levels of entropy production. We note the emergence of an array of peaks in the dynamical response (transient analogs of phase transitions) that draw the proteins between distinct levels of dissipation, and we see that the binding of ATP and agonist molecules modifies the observed dissipative landscapes. Overall, we find that dissipation is tightly coupled to activation in these signaling systems: dominant entropy-producing trajectories become localized near important barriers along known biological activation pathways. We go on to classify an array of equilibrium and nonequilibrium molecular switches that harmonize to promote functional dynamics.

Computational study of the W260A activating mutant of Src tyrosine kinase

Tyrosine kinases are enzymes playing a critical role in cellular signaling. Mutations causing increased in kinase activity are often associated with cancer and various pathologies. One example in Src tyrosine kinases is offered by the substitution of the highly conserved tryptophan 260 by an alanine (W260A), which has been shown to cause an increase in activity. Here, molecular dynamics simulations based on atomic models are carried out to characterize the conformational changes in the linker region and the catalytic (kinase) domain of Src kinase to elucidate the impact of the W260A mutation. Umbrella sampling calculations show that the conformation of the linker observed in the assembled down-regulated state of the kinase is most favored when the kinase domain is in the inactive state, whereas the conformation of the linker observed in the re-assembled up-regulated state of the kinase is favored when the kinase domain is in the unphosphorylated active-like state. The calculations further indicate that there are only small differences between the WT and W260A mutant. In both cases, the intermediates states are very similar and the down-regulated inactive conformation is the most stable state. However, the calculations also show that the free energy cost to reach the unphosphorylated active-like conformation is slightly smaller for the W260A mutant compared with WT. A simple kinetic model is developed and submitted to a Bayesian Monte Carlo analysis to illustrate how such small differences can contribute to accelerate the trans-autophosphorylation reaction and yield a large increase in the activity of the mutant as observed experimentally.

Conformational processing of oncogenic v-Src kinase by the molecular chaperone Hsp90

Hsp90 is a molecular chaperone involved in the activation of numerous client proteins, including many kinases. The most stringent kinase client is the oncogenic kinase v-Src. To elucidate how Hsp90 chaperones kinases, we reconstituted v-Src kinase chaperoning in vitro and show that its activation is ATP-dependent, with the cochaperone Cdc37 increasing the efficiency. Consistent with in vivo results, we find that Hsp90 does not influence the almost identical c-Src kinase. To explain these findings, we designed Src kinase chimeras that gradually transform c-Src into v-Src and show that their Hsp90 dependence correlates with compactness and folding cooperativity. Molecular dynamics simulations and hydrogen/deuterium exchange of Hsp90-dependent Src kinase variants further reveal increased transitions between inactive and active states and exposure of specific kinase regions. Thus, Hsp90 shifts an ensemble of conformations of v-Src toward high activity states that would otherwise be metastable and poorly populated.

A dynamically coupled allosteric network underlies binding cooperativity in Src kinase

Protein tyrosine kinases are attractive drug targets because many human diseases are associated with the deregulation of kinase activity. However, how the catalytic kinase domain integrates different signals and switches from an active to an inactive conformation remains incompletely understood. Here we identify an allosteric network of dynamically coupled amino acids in Src kinase that connects regulatory sites to the ATP- and substrate-binding sites. Surprisingly, reactants (ATP and peptide substrates) bind with negative cooperativity to Src kinase while products (ADP and phosphopeptide) bind with positive cooperativity. We confirm the molecular details of the signal relay through the allosteric network by biochemical studies. Experiments on two additional protein tyrosine kinases indicate that the allosteric network may be largely conserved among these enzymes. Our work provides new insights into the regulation of protein tyrosine kinases and establishes a potential conduit by which resistance mutations to ATP-competitive kinase inhibitors can affect their activity.

Protein tyrosine kinases are subject to multiple regulatory mechanisms. Foda et al. show that reactants and products of the tyrosine kinase Src bind its catalytic domain with opposite cooperativity, and identify an allosteric network of dynamically coupled amino acids that underlie this behaviour.

Recent advances in the understanding of two-step nucleation of protein crystals

The two-step mechanism of nucleation of crystals in solutions posits that the formation of crystal nuclei occurs within structures of extended lifetimes, in which the nucleating solute is at high concentration. The validity of this mechanism has been demonstrated for proteins, small-molecule organic and inorganic materials, colloids, and polymers. Due to large molecule sizes, proteins are an ideal system to study the details of this nucleation pathway, in particular the formation mechanisms of the nucleation precursors and the associated physico-chemical rules. The precursors of protein crystal nuclei are protein-rich clusters of sizes ∼100 nm that contain 10 000–100 000 molecules and occupy less than 10⁻³of the total solution volume. Here we demonstrate, using oblique illumination microscopy, the liquid nature of the clusters of the protein lysozyme and reveal their inhomogeneous structure. We test a hypothesis put forth by theory that clusters primarily consist of transient protein oligomers. For this, we explore how varying the strength of the Coulomb interaction affects the cluster characteristics. We find that the cluster’s size is insensitive to variations of pH and ionic strength. In contrast, the addition of urea, a chaotropic agent that leads to protein unfolding, strongly decreases the cluster size. Shear stress, a known protein denaturant, induced by bubbling of the solutions with an inert gas, elicits a similar response. These observations support partial protein unfolding, followed by dimerization, as the mechanism of cluster formation. The amide hydrogen–deuterium exchange, monitored by nuclear magnetic resonance, highlights that lysozyme conformational flexibility is a condition for the formation of the protein-rich clusters and facilitates the nucleation of protein crystals.

Automatic Selection of Order Parameters in the Analysis of Large Scale Molecular Dynamics Simulations

Given the large number of crystal structures and NMR ensembles that have been solved to date, classical molecular dynamics (MD) simulations have become powerful tools in the atomistic study of the kinetics and thermodynamics of biomolecular systems on ever increasing time scales. By virtue of the high-dimensional conformational state space that is explored, the interpretation of large-scale simulations faces difficulties not unlike those in the big data community. We address this challenge by introducing a method called clustering based feature selection (CB-FS) that employs a posterior analysis approach. It combines supervised machine learning (SML) and feature selection with Markov state models to automatically identify the relevant degrees of freedom that separate conformational states. We highlight the utility of the method in the evaluation of large-scale simulations and show that it can be used for the rapid and automated identification of relevant order parameters involved in the functional transitions of two exemplary cell-signaling proteins central to human disease states.

Hotspot mutations in KIT receptor differentially modulate its allosterically coupled conformational dynamics: impact on activation and drug sensitivity

Receptor tyrosine kinase KIT controls many signal transduction pathways and represents a typical allosterically regulated protein. The mutation-induced deregulation of KIT activity impairs cellular physiological functions and causes serious human diseases. The impact of hotspots mutations (D816H/Y/N/V and V560G/D) localized in crucial regulatory segments, the juxtamembrane region (JMR) and the activation (A-) loop, on KIT internal dynamics was systematically studied by molecular dynamics simulations. The mutational outcomes predicted in silico were correlated with in vitro and in vivo activation rates and drug sensitivities of KIT mutants. The allosteric regulation of KIT in the native and mutated forms is described in terms of communication between the two remote segments, JMR and A-loop. A strong correlation between the communication profile and the structural and dynamical features of KIT in the native and mutated forms was established. Our results provide new insight on the determinants of receptor KIT constitutive activation by mutations and resistance of KIT mutants to inhibitors. Depiction of an intra-molecular component of the communication network constitutes a first step towards an integrated description of vast communication pathways established by KIT in physiopathological contexts.

Receptor tyrosine kinase KIT plays a crucial role in the regulation of cell signaling. This allosterically controlled activity may be affected by gain-of-function mutations that promote the development of several cancers. Identification of the molecular basis of KIT constitutive activation and allosteric regulation has inspired computational study of KIT hotspot mutations. In the present contribution, we investigated the mutation-induced effects on KIT conformational dynamics and intra-protein communication conditionally on the mutation location and the nature of the substituting amino acid. Our data elucidate that all studied mutations stabilize an inactive non-autoinhibited state of KIT over the inactive auto-inhibited state prevalent for the native protein. This shift in the protein conformational landscape promotes KIT constitutive activation. Our in silico analysis established correlations between the structural and dynamical effects induced by oncogenic mutations and the mutants auto-activation rates and drug sensitivities measured in vitro and in vivo. Particularly, the A-loop mutations stabilize the drug-resistant forms, while the JMR mutations may facilitate inhibitors binding to the active site. Cross-correlations established between local and long-range structural and dynamical effects demonstrate the allosteric character of the gain-of-function mutations mode of action.

Myelin architecture: zippering membranes tightly together

Rapid nerve conduction requires the coating of axons by a tightly packed multilayered myelin membrane. In the central nervous system, myelin is formed from cellular processes that extend from oligodendrocytes and wrap in a spiral fashion around an axon, resulting in the close apposition of adjacent myelin membrane bilayers. In this review, we discuss the physical principles underlying the zippering of the plasma membrane of oligodendrocytes at the cytoplasmic and extracellular leaflet. We propose that the interaction of the myelin basic protein with the cytoplasmic leaflet of the myelin bilayer triggers its polymerization into a fibrous network that drives membrane zippering and protein extrusion. In contrast, the adhesion of the extracellular surfaces of myelin requires the down-regulation of repulsive components of the glycocalyx, in order to uncover weak and unspecific attractive forces that bring the extracellular surfaces into close contact. Unveiling the mechanisms of myelin membrane assembly at the cytoplasmic and extracelluar sites may help to understand how the myelin bilayers are disrupted and destabilized in the different demyelinating diseases.

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.

Locking the active conformation of c-Src kinase through the phosphorylation of the activation loop

Molecular dynamics umbrella sampling simulations are used to compare the relative stability of the active conformation of the catalytic domain of c-Src kinase while the tyrosine 416 in the activation loop (A-loop) is either unphosphorylated or phosphorylated. When the A-loop is unphosphorylated, there is considerable flexibility of the kinase. While the active conformation of the kinase is not forbidden and can be visited transiently, it is not the predominant state. This is consistent with the view that c-Src displays some catalytic activity even when the A-loop is unphosphorylated. In contrast, phosphorylation of the A-loop contributes to stabilize several structural features that are critical for catalysis, such as the hydrophobic regulatory spine, the HRD motif, and the electrostatic switch. In summary, the free-energy landscape calculations demonstrate that phosphorylation of tyrosine 416 in the A-loop essentially "locks" the kinase into its catalytically competent conformation.

Computational insights for the discovery of non-ATP competitive inhibitors of MAP kinases

Due to their role in cellular signaling mitogen activated protein (MAP) kinases represent targets of pharmaceutical interest. However, the majority of known MAP kinase inhibitors compete with cellular ATP and target an ATP binding pocket that is highly conserved in the 500 plus representatives of the human protein kinase family. Here we review progress toward the development of non-ATP competitive MAP kinase inhibitors for the extracellular signal regulated kinases (ERK1/2), the c-jun N-terminal kinases (JNK1/2/3) and the p38 MAPKs (α, β, γ, and δ). Special emphasis is placed on the role of computational methods in the drug discovery process for MAP kinases. Topics include recent advances in X-ray crystallography theory that improve the MAP kinase structures essential to structurebased drug discovery, the use of molecular dynamics to understand the conformational heterogeneity of the activation loop and inhibitors discovered by virtual screening. The impact of an advanced polarizable force field such as AMOEBA used in conjunction with sophisticated kinetic and thermodynamic simulation methods is also discussed.

αC helix as a switch in the conformational transition of Src/CDK-like kinase domains

One mechanism of regulating the catalytic activity of protein kinases is through conformational transitions. Despite great diversity in the structural changes involved in the transitions, a certain set of changes within the kinase domain (KD) has been observed for many kinases including Src and CDK2. We investigated this conformational transition computationally to identify the topological features that are energetically critical to the transition. Results from both molecular dynamics sampling and transition path optimization highlight the displacement of the αC helix as the major energy barrier, mediating the switch of the KD between the active and down-regulated states. The critical role of the αC helix is noteworthy by providing a rationale for a number of activation and deactivation mechanisms known to occur in cells. We find that kinases with the αC helix displacement exist throughout the kinome, suggesting that this feature may have emerged early in evolution.

Insights into the conformational switching mechanism of the human vascular endothelial growth factor receptor type 2 kinase domain

Human vascular endothelial growth factor receptor type 2 (h-VEFGR2) is a receptor tyrosine kinase involved in the angiogenesis process and regarded as an interesting target for the design of anticancer drugs. Its activation/inactivation mechanism is related to conformational changes in its cytoplasmatic kinase domain, involving first among all the αC-helix in N-lobe and the A-loop in C-lobe. Affinity of inhibitors for the active or inactive kinase form could dictate the open or closed conformation of the A-loop, thus making the different conformations of the kinase domain receptor (KDR) domain different drug targets in drug discovery. In this view, a detailed knowledge of the conformational landscape of KDR domain is of central relevance to rationalize the efficiency and selectivity of kinase inhibitors. Here, molecular dynamics simulations were used to gain insight into the conformational switching activity of the KDR domain and to identify intermediate conformations between the two limiting active and inactive conformations. Specific energy barriers have been selectively removed to induce, and hence highlight at the atomistic level, the regulation mechanism of the A-loop opening. The proposed strategy allowed to repeatedly observe the escape of the KDR domain from the DFG-out free energy basin and to identify rare intermediate conformations between the DFG-out and the DFG-in structures to be employed in a structure-based drug discovery process.

Mutations in the catalytic loop HRD motif alter the activity and function of Drosophila Src64

The catalytic loop HRD motif is found in most protein kinases and these amino acids are predicted to perform functions in catalysis, transition to, and stabilization of the active conformation of the kinase domain. We have identified mutations in a Drosophila src gene, src64, that alter the three HRD amino acids. We have analyzed the mutants for both biochemical activity and biological function during development. Mutation of the aspartate to asparagine eliminates biological function in cytoskeletal processes and severely reduces fertility, supporting the amino acid's critical role in enzymatic activity. The arginine to cysteine mutation has little to no effect on kinase activity or cytoskeletal reorganization, suggesting that the HRD arginine may not be critical for coordinating phosphotyrosine in the active conformation. The histidine to leucine mutant retains some kinase activity and biological function, suggesting that this amino acid may have a biochemical function in the active kinase that is independent of its side chain hydrogen bonding interactions in the active site. We also describe the phenotypic effects of other mutations in the SH2 and tyrosine kinase domains of src64, and we compare them to the phenotypic effects of the src64 null allele.

Computational modeling of allosteric communication reveals organizing principles of mutation-induced signaling in ABL and EGFR kinases

The emerging structural information about allosteric kinase complexes and the growing number of allosteric inhibitors call for a systematic strategy to delineate and classify mechanisms of allosteric regulation and long-range communication that control kinase activity. In this work, we have investigated mechanistic aspects of long-range communications in ABL and EGFR kinases based on the results of multiscale simulations of regulatory complexes and computational modeling of signal propagation in proteins. These approaches have been systematically employed to elucidate organizing molecular principles of allosteric signaling in the ABL and EGFR multi-domain regulatory complexes and analyze allosteric signatures of the gate-keeper cancer mutations. We have presented evidence that mechanisms of allosteric activation may have universally evolved in the ABL and EGFR regulatory complexes as a product of a functional cross-talk between the organizing αF-helix and conformationally adaptive αI-helix and αC-helix. These structural elements form a dynamic network of efficiently communicated clusters that may control the long-range interdomain coupling and allosteric activation. The results of this study have unveiled a unifying effect of the gate-keeper cancer mutations as catalysts of kinase activation, leading to the enhanced long-range communication among allosterically coupled segments and stabilization of the active kinase form. The results of this study can reconcile recent experimental studies of allosteric inhibition and long-range cooperativity between binding sites in protein kinases. The presented study offers a novel molecular insight into mechanistic aspects of allosteric kinase signaling and provides a quantitative picture of activation mechanisms in protein kinases at the atomic level.

Despite recent progress in computational and experimental studies of dynamic regulation in protein kinases, a mechanistic understanding of long-range communication and mechanisms of mutation-induced signaling controlling kinase activity remains largely qualitative. In this study, we have performed a systematic modeling and analysis of allosteric activation in ABL and EGFR kinases at the increasing level of complexity - from catalytic domain to multi-domain regulatory complexes. The results of this study have revealed organizing structural and mechanistic principles of allosteric signaling in protein kinases. Although activation mechanisms in ABL and EGFR kinases have evolved through acquisition of structurally different regulatory complexes, we have found that long-range interdomain communication between common functional segments (αF-helix and αC-helix) may be important for allosteric activation. The results of study have revealed molecular signatures of activating cancer mutations and have shed the light on general mechanistic aspects of mutation-induced signaling in protein kinases. An advanced understanding and further characterization of molecular signatures of kinase mutations may aid in a better rationalization of mutational effects on clinical outcomes and facilitate molecular-based therapeutic strategies to combat kinase mutation-dependent tumorigenesis.

Molecular dynamics analysis of conserved hydrophobic and hydrophilic bond-interaction networks in ErbB family kinases

The EGFR (epidermal growth factor receptor)/ErbB/HER (human EGFR) family of kinases contains four homologous receptor tyrosine kinases that are important regulatory elements in key signalling pathways. To elucidate the atomistic mechanisms of dimerization-dependent activation in the ErbB family, we have performed molecular dynamics simulations of the intracellular kinase domains of three members of the ErbB family (those with known kinase activity), namely EGFR, ErbB2 (HER2) and ErbB4 (HER4), in different molecular contexts: monomer against dimer and wild-type against mutant. Using bioinformatics and fluctuation analyses of the molecular dynamics trajectories, we relate sequence similarities to correspondence of specific bond-interaction networks and collective dynamical modes. We find that in the active conformation of the ErbB kinases, key subdomain motions are co-ordinated through conserved hydrophilic interactions: activating bond-networks consisting of hydrogen bonds and salt bridges. The inactive conformations also demonstrate conserved bonding patterns (albeit less extensive) that sequester key residues and disrupt the activating bond network. Both conformational states have distinct hydrophobic advantages through context-specific hydrophobic interactions. We show that the functional (activating) asymmetric kinase dimer interface forces a corresponding change in the hydrophobic and hydrophilic interactions that characterize the inactivating bond network, resulting in motion of the αC-helix through allostery. Several of the clinically identified activating kinase mutations of EGFR act in a similar fashion to disrupt the inactivating bond network. The present molecular dynamics study reveals a fundamental difference in the sequence of events in EGFR activation compared with that described for the Src kinase Hck.

On the role of electrostatics in protein-protein interactions

The role of electrostatics in protein-protein interactions and binding is reviewed in this paper. A brief outline of the computational modeling, in the framework of continuum electrostatics, is presented and the basic electrostatic effects occurring upon the formation of the complex are discussed. The effect of the salt concentration and pH of the water phase on protein-protein binding free energy is demonstrated which indicates that the increase of the salt concentration tends to weaken the binding, an observation that is attributed to the optimization of the charge-charge interactions across the interface. It is pointed out that the pH-optimum (pH of optimal binding affinity) varies among the protein-protein complexes, and perhaps is a result of their adaptation to particular subcellular compartments. The similarities and differences between hetero- and homo-complexes are outlined and discussed with respect to the binding mode and charge complementarity.

Analysis of Somatic Mutations in Cancer: Molecular Mechanisms of Activation in the ErbB Family of Receptor Tyrosine Kinases

The ErbB/EGFR/HER family of kinases consists of four homologous receptor tyrosine kinases which are important regulatory elements in many cellular processes, including cell proliferation, differentiation, and migration. Somatic mutations in, or over-expression of, the ErbB family is found in many cancers and is correlated with a poor prognosis; particularly, clinically identified mutations found in non-small-cell lung cancer (NSCLC) of ErbB1 have been shown to increase its basal kinase activity and patients carrying these mutations respond remarkably to the small tyrosine kinase inhibitor gefitinib. Here, we analyze the potential effects of the currently catalogued clinically identified mutations in the ErbB family kinase domains on the molecular mechanisms of kinase activation. Recently, we identified conserved networks of hydrophilic and hydrophobic interactions characteristic to the active and inactive conformation, respectively. Here, we show that the clinically identified mutants influence the kinase activity in distinctive fashion by affecting the characteristic interaction networks.

Maximum Flux Transition Paths of Conformational Change

Given two metastable states A and B of a biomolecular system, the problem is to calculate the likely paths of the transition from A to B. Such a calculation is more informative and more manageable if done for a reduced set of collective variables chosen so that paths cluster in collective variable space. The computational task becomes that of computing the "center" of such a cluster. A good way to define the center employs the concept of a committor, whose value at a point in collective variable space is the probability that a trajectory at that point will reach B before A. The committor "foliates" the transition region into a set of isocommittors. The maximum flux transition path is defined as a path that crosses each isocommittor at a point which (locally) has the highest crossing rate of distinct reactive trajectories. This path is based on the same principle as the minimum resistance path of Berkowitz et al (1983), but it has two advantages: (i) the path is invariant with respect to a change of coordinates in collective variable space and (ii) the differential equations that define the path are simpler. It is argued that such a path is nearer to an ideal path than others that have been proposed with the possible exception of the finite-temperature string method path. To make the calculation tractable, three approximations are introduced, yielding a path that is the solution of a nonsingular two-point boundary-value problem. For such a problem, one can construct a simple and robust algorithm. One such algorithm and its performance is discussed.

BlockMaster: partitioning protein kinase structures using normal-mode analysis

Protein kinases are key signaling enzymes which are dysregulated in many health disorders and therefore represent major targets of extensive drug discovery efforts. Their regulation in the cell is exerted via various mechanisms, including control of the 3D conformation of their catalytic domains. We developed a procedure, BlockMaster, for partitioning protein structures into semirigid blocks and flexible regions based on residue-residue correlations calculated from normal modes. BlockMaster provided correct partitioning into domains and subdomains of several test set proteins for which documented expert annotation of subdomains exists. When applied to representative structures of protein kinases, BlockMaster identified semirigid blocks within the traditional N-terminal and C-terminal lobes of the kinase domain. In general, the block regions had elevated helical content and reduced, but significant, coil content compared to the nonblock (flexible) regions. The specificity-determining regions, previously used to derive inhibitory peptides, were found to be more flexible in the tyrosine kinases than in serine/threonine kinases. Two blocks were identified which spanned both lobes. The first, which we termed the "pivot" block, included the alphaC-beta4 loop in the N-terminal lobe and part of the activation loop in the C-terminal lobe and appeared in both the active and inactive conformations of the kinases. The second, which we termed the "loop" block, differed between the active and inactive conformations. In the structures of active kinases, this block included part of the activation loop in the C-terminal lobe and the alphaC helix in the N-terminal lobe, representing a known interaction that stabilizes the active conformation. In the inactive structures, this block included G loop residues instead of the alphaC residues. This novel inactive "loop" block may stabilize the inactive conformation and thus downregulate kinase activity.

Sequence and structure signatures of cancer mutation hotspots in protein kinases

Protein kinases are the most common protein domains implicated in cancer, where somatically acquired mutations are known to be functionally linked to a variety of cancers. Resequencing studies of protein kinase coding regions have emphasized the importance of sequence and structure determinants of cancer-causing kinase mutations in understanding of the mutation-dependent activation process. We have developed an integrated bioinformatics resource, which consolidated and mapped all currently available information on genetic modifications in protein kinase genes with sequence, structure and functional data. The integration of diverse data types provided a convenient framework for kinome-wide study of sequence-based and structure-based signatures of cancer mutations. The database-driven analysis has revealed a differential enrichment of SNPs categories in functional regions of the kinase domain, demonstrating that a significant number of cancer mutations could fall at structurally equivalent positions (mutational hotspots) within the catalytic core. We have also found that structurally conserved mutational hotspots can be shared by multiple kinase genes and are often enriched by cancer driver mutations with high oncogenic activity. Structural modeling and energetic analysis of the mutational hotspots have suggested a common molecular mechanism of kinase activation by cancer mutations, and have allowed to reconcile the experimental data. According to a proposed mechanism, structural effect of kinase mutations with a high oncogenic potential may manifest in a significant destabilization of the autoinhibited kinase form, which is likely to drive tumorigenesis at some level. Structure-based functional annotation and prediction of cancer mutation effects in protein kinases can facilitate an understanding of the mutation-dependent activation process and inform experimental studies exploring molecular pathology of tumorigenesis.

Hierarchical modeling of activation mechanisms in the ABL and EGFR kinase domains: thermodynamic and mechanistic catalysts of kinase activation by cancer mutations

Structural and functional studies of the ABL and EGFR kinase domains have recently suggested a common mechanism of activation by cancer-causing mutations. However, dynamics and mechanistic aspects of kinase activation by cancer mutations that stimulate conformational transitions and thermodynamic stabilization of the constitutively active kinase form remain elusive. We present a large-scale computational investigation of activation mechanisms in the ABL and EGFR kinase domains by a panel of clinically important cancer mutants ABL-T315I, ABL-L387M, EGFR-T790M, and EGFR-L858R. We have also simulated the activating effect of the gatekeeper mutation on conformational dynamics and allosteric interactions in functional states of the ABL-SH2-SH3 regulatory complexes. A comprehensive analysis was conducted using a hierarchy of computational approaches that included homology modeling, molecular dynamics simulations, protein stability analysis, targeted molecular dynamics, and molecular docking. Collectively, the results of this study have revealed thermodynamic and mechanistic catalysts of kinase activation by major cancer-causing mutations in the ABL and EGFR kinase domains. By using multiple crystallographic states of ABL and EGFR, computer simulations have allowed one to map dynamics of conformational fluctuations and transitions in the normal (wild-type) and oncogenic kinase forms. A proposed multi-stage mechanistic model of activation involves a series of cooperative transitions between different conformational states, including assembly of the hydrophobic spine, the formation of the Src-like intermediate structure, and a cooperative breakage and formation of characteristic salt bridges, which signify transition to the active kinase form. We suggest that molecular mechanisms of activation by cancer mutations could mimic the activation process of the normal kinase, yet exploiting conserved structural catalysts to accelerate a conformational transition and the enhanced stabilization of the active kinase form. The results of this study reconcile current experimental data with insights from theoretical approaches, pointing to general mechanistic aspects of activating transitions in protein kinases.

Mutations in protein kinases are implicated in many cancers, and an important goal of cancer research is to elucidate molecular effects of mutated kinase genes that contribute to tumorigenesis. We present a comprehensive computational study of molecular mechanisms of kinase activation by cancer-causing mutations. Using a battery of computational approaches, we have systematically investigated the effects of clinically important cancer mutants on dynamics of the ABL and EGFR kinase domains and regulatory multi-protein complexes. The results of this study have illuminated common and specific features of the activation mechanism in the normal and oncogenic forms of ABL and EGFR. We have found that mutants with the higher oncogenic activity may cause a partial destabilization of the inactive structure, while simultaneously facilitating activating transitions and the enhanced stabilization of the active conformation. Our results provided useful insights into thermodynamic and mechanistic aspects of the activation mechanism and highlighted the role of structurally distinct conformational states in kinase regulation. Ultimately, molecular signatures of activation mechanisms in the normal and oncogenic states may aid in the correlation of mutational effects with clinical outcomes and facilitate the development of therapeutic strategies to combat kinase mutation-dependent tumorigenesis.

Atomistic view of the conformational activation of Src kinase using the string method with swarms-of-trajectories

The inactive-to-active conformational transition of the catalytic domain of human c-Src tyrosine kinase is characterized using the string method with swarms-of-trajectories with all-atom explicit solvent molecular dynamics simulations. The activation process occurs in two main steps in which the activation loop (A-loop) opens first, followed by the rotation of the alphaC helix. The computed potential of mean force energy along the activation pathway displays a local minimum, which allows the identification of an intermediate state. These results show that the string method with swarms-of-trajectories is an effective technique to characterize complex and slow conformational transitions in large biomolecular systems.

The effect of the cosolvent trifluoroethanol on a tryptophan side chain orientation in the hydrophobic core of troponin C

The unique biophysical properties of tryptophan residues have been exploited for decades to monitor protein structure and dynamics using a variety of spectroscopic techniques, such as fluorescence and nuclear magnetic resonance (NMR). We recently designed a tryptophan mutant in the regulatory N-domain of cardiac troponin C (F77W-cNTnC) to study the domain orientation of troponin C in muscle fibers using solid-state NMR. In our previous study, we determined the NMR structure of calcium-saturated mutant F77W-V82A-cNTnC in the presence of 19% 2,2,2-trifluoroethanol (TFE). TFE is a widely used cosolvent in the biophysical characterization of the solution structures of peptides and proteins. It is generally assumed that the structures are unchanged in the presence of cosolvents at relatively low concentrations, and this has been verified for TFE at the level of the overall secondary and tertiary structure for several calcium regulatory proteins. Here, we present the NMR solution structure of the calcium saturated F77W-cNTnC in presence of its biological binding partner troponin I peptide (cTnI(144-163)) and in the absence of TFE. We have also characterized a panel of six F77W-cNTnC structures in the presence and absence TFE, cTnI(144-163), and the extra mutation V82A, and used (19)F NMR to characterize the effect of TFE on the F77(5fW) analog. Our results show that although TFE did not perturb the overall protein structure, TFE did induce a change in the orientation of the indole ring of the buried tryptophan side chain from the anticipated position based upon homology with other proteins, highlighting the potential dangers of the use of cosolvents.

Computational studies of H5N1 influenza virus resistance to oseltamivir

Influenza A (H5N1) virus is one of the world's greatest pandemic threats. Neuraminidase (NA) inhibitors, oseltamivir and zanamivir, prevent the spread of influenza, but drug-resistant viruses have reduced their effectiveness. Resistance depends on the binding properties of NA-drug complexes. Key residue mutations within the active site of NA glycoproteins diminish binding, thereby resulting in drug resistance. We performed molecular simulations and calculations to characterize the mechanisms of H5N1 influenza virus resistance to oseltamivir and predict potential drug-resistant mutations. We examined two resistant NA mutations, H274Y and N294S, and one non-drug-resistant mutation, E119G. Six-nanosecond unrestrained molecular dynamic simulations with explicit solvent were performed using NA-oseltamivir complexes containing either NA wild-type H5N1 virus or a variant. MM_PBSA techniques were then used to rank the binding free energies of these complexes. Detailed analyses indicated that conformational change of E276 in the Pocket 1 region of NA is a key source of drug resistance in the H274Y mutant but not in the N294S mutant.

A Comparison of Three Perturbation Molecular Dynamics Methods for Modeling Conformational Transitions

Targeted, steered, and biased molecular dynamics (MD) are widely used methods for studying transition processes of biomolecules. They share the common feature of adding external perturbations along a conformational progress variable to guide the transition in a predefined direction in conformational space, yet differ in how these perturbations are applied. In the present paper, we report a comparison of these three methods on generating transition paths for two different processes: the unfolding of the B domain of protein A and a conformational transition of the catalytic domain of a Src kinase Lyn. Transition pathways were calculated with different simulation parameters including the choice of progress variable and the simulation length or biasing force constant. A comparison of the generated paths based on structural similarity finds that the three perturbation MD methods generate similar transition paths for a given progress variable in most cases. On the other hand, the path depends more strongly on the choice of progress variable used to move the system between the initial and final states. Potentials of mean force (PMF) were calculated starting from unfolding trajectories to estimate the relative probabilities of the paths. A lower PMF was found for the lowest biasing force constant with BMD.

Protein conformational transitions: the closure mechanism of a kinase explored by atomistic simulations

Kinase large-scale conformational rearrangement is an issue of enormous biological and pharmacological relevance. Atomistic simulations able to capture the dynamics and the energetics of kinase large-scale motions are still in their infancy. Here, we present a computational study in which the atomistic dynamics of the "open-to-closed" movement of the cyclin-dependent kinase 5 (CDK5) have been simulated. Simulations were carried out using a new sampling method that is able to find the lowest free-energy channel between an initial state and a final state. This large-scale movement has a two-step mechanism: first, the alphaC-helix rotates by approximately 45 degrees , allowing the interaction between Glu51 and Arg149; then the CDK5 activation loop refolds to assume the closed conformation. We have also estimated the free-energy profile associated with the global motion and identified a CDK5 intermediate, which could be exploited for drug-design purposes. Our new sampling method turned out to be well-suited for investigating at an atomistic level the energetics and dynamics of kinase large-scale conformational motions.

Mapping the conformational transition in Src activation by cumulating the information from multiple molecular dynamics trajectories

The Src-family kinases are allosteric enzymes that play a key role in the regulation of cell growth and proliferation. In response to cellular signals, they undergo large conformational changes to switch between distinct inactive and active states. A computational strategy for characterizing the conformational transition pathway is presented to bridge the inactive and active states of the catalytic domain of Hck. The information from a large number (78) of independent all-atom molecular dynamics trajectories with explicit solvent is combined together to assemble a connectivity map of the conformational transition. Two intermediate states along the activation pathways are identified, and their structural features are characterized. A coarse free-energy landscape is built in terms of the collective motions corresponding to the opening of the activation loop (A-loop) and the rotation of the alphaC helix. This landscape shows that the protein can adopt a multitude of conformations in which the A-loop is partially open, while the alphaC helix remains in the orientation characteristic of the inactive conformation. The complete transition leading to the active conformation requires a concerted movement involving further opening of the A-loop, the relative alignment of N-lobe and C-lobe, and the rotation of the alphaC helix needed to recruit the residues necessary for catalysis in the active site. The analysis leads to a dynamic view of the full-length kinase activation, whereby transitions of the catalytic domain to intermediate configurations with a partially open A-loop are permitted, even while the SH2-SH3 clamp remains fully engaged. These transitions would render Y416 available for the transphosphorylation event that ultimately locks down the active state. The results provide a broad framework for picturing the conformational transitions leading to kinase activation.