Src kinase activation: A switched electrostatic network

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.

Molecular dynamics simulations reveal phosphorylation-induced conformational dynamics of the fibroblast growth factor receptor 1 kinase

The Fibroblast Growth Factor Receptor1 (FGFR1) kinase wields exquisite control on cell fate, proliferation, differentiation, and homeostasis. An imbalance of FGFR1 signaling leads to several pathogeneses of diseases ranging from multiple cancers to allergic and neurodegenerative disorders. In this study, we investigated the phosphorylation-induced conformational dynamics of FGFR1 in apo and ATP-bound states via all-atom molecular dynamics simulations. All simulations were performed for 2 × 2 µs. We have also investigated the energetics of the binding of ATP to FGFR1 using the molecular mechanics Poisson-Boltzmann scheme. Our study reveals that the FGFR1 kinase can reach a fully active configuration through phosphorylation and ATP binding. A 3-10 helix formation in the activation loop signifies its rearrangement leading to stability upon ATP binding. The interaction of phosphorylated tyrosine (pTyr654) with positively charged residues forms strong salt-bridge interactions, driving the compactness of the structure. The dynamic cross-correlation map reveals phosphorylation enhances correlated motions and reduces anti-correlated motions between different domains. We believe that the mechanistic understanding of large-conformational changes upon the activation of the FGFR1 kinase will aid the development of novel targeted therapeutics.Communicated by Ramaswamy H. Sarma.

Role of c-Src in Carcinogenesis and Drug Resistance

The aberrant transformation of normal cells into cancer cells, known as carcinogenesis, is a complex process involving numerous genetic and molecular alterations in response to innate and environmental stimuli. The Src family kinases (SFK) are key components of signaling pathways implicated in carcinogenesis, with c-Src and its oncogenic counterpart v-Src often playing a significant role. The discovery of c-Src represents a compelling narrative highlighting groundbreaking discoveries and valuable insights into the molecular mechanisms underlying carcinogenesis. Upon oncogenic activation, c-Src activates multiple downstream signaling pathways, including the PI3K-AKT pathway, the Ras-MAPK pathway, the JAK-STAT3 pathway, and the FAK/Paxillin pathway, which are important for cell proliferation, survival, migration, invasion, metastasis, and drug resistance. In this review, we delve into the discovery of c-Src and v-Src, the structure of c-Src, and the molecular mechanisms that activate c-Src. We also focus on the various signaling pathways that c-Src employs to promote oncogenesis and resistance to chemotherapy drugs as well as molecularly targeted agents.

Native mass spectrometry of proteoliposomes containing integral and peripheral membrane proteins

Cellular membranes are critical to the function of membrane proteins, whether they are associated (peripheral) or embedded (integral) within the bilayer. While detergents have contributed to our understanding of membrane protein structure and function, there remains challenges in characterizing protein-lipid interactions within the context of an intact membrane. Here, we developed a method to prepare proteoliposomes for native mass spectrometry (MS) studies. We first use native MS to detect the encapsulation of soluble proteins within liposomes. We then find the peripheral Gβ1γ2 complex associated with the membrane can be ejected and analyzed using native MS. Four different integral membrane proteins (AmtB, AqpZ, TRAAK, and TREK2), all of which have previously been characterized in detergent, eject from the proteoliposomes as intact complexes bound to lipids that have been shown to tightly associate in detergent, drawing a correlation between the two approaches. We also show the utility of more complex lipid environments, such as a brain polar lipid extract, and show TRAAK ejects from liposomes of this extract bound to lipids. These findings underscore the capability to eject protein complexes from membranes bound to both lipids and metal ions, and this approach will be instrumental in the identification of key protein-lipid interactions.

Evolutionary divergence in the conformational landscapes of tyrosine vs serine/threonine kinases

Inactive conformations of protein kinase catalytic domains where the DFG motif has a "DFG-out" orientation and the activation loop is folded present a druggable binding pocket that is targeted by FDA-approved 'type-II inhibitors' in the treatment of cancers. Tyrosine kinases (TKs) typically show strong binding affinity with a wide spectrum of type-II inhibitors while serine/threonine kinases (STKs) usually bind more weakly which we suggest here is due to differences in the folded to extended conformational equilibrium of the activation loop between TKs vs. STKs. To investigate this, we use sequence covariation analysis with a Potts Hamiltonian statistical energy model to guide absolute binding free-energy molecular dynamics simulations of 74 protein-ligand complexes. Using the calculated binding free energies together with experimental values, we estimated free-energy costs for the large-scale (~17-20 Å) conformational change of the activation loop by an indirect approach, circumventing the very challenging problem of simulating the conformational change directly. We also used the Potts statistical potential to thread large sequence ensembles over active and inactive kinase states. The structure-based and sequence-based analyses are consistent; together they suggest TKs evolved to have free-energy penalties for the classical 'folded activation loop' DFG-out conformation relative to the active conformation, that is, on average, 4-6 kcal/mol smaller than the corresponding values for STKs. Potts statistical energy analysis suggests a molecular basis for this observation, wherein the activation loops of TKs are more weakly 'anchored' against the catalytic loop motif in the active conformation and form more stable substrate-mimicking interactions in the inactive conformation. These results provide insights into the molecular basis for the divergent functional properties of TKs and STKs, and have pharmacological implications for the target selectivity of type-II inhibitors.

Src family kinases (SFKs): critical regulators of microglial homeostatic functions and neurodegeneration in Parkinson's and Alzheimer's diseases

c-Src was the first protein kinase to be described as capable of phosphorylating tyrosine residues. Subsequent identification of other tyrosine-phosphorylating protein kinases with a similar structure to c-Src gave rise to the concept of Src family kinases (SFKs). Microglia are the resident innate immune cell population of the CNS. Under physiological conditions, microglia actively participate in brain tissue homeostasis, continuously patrolling the neuronal parenchyma and exerting neuroprotective actions. Activation of pathogen-associated molecular pattern (PAMP) and damage-associated molecular pattern (DAMP) receptors induces microglial proliferation, migration toward pathological foci, phagocytosis, and changes in gene expression, concurrent with the secretion of cytokines, chemokines, and growth factors. A significant body of literature shows that SFK stimulation positively associates with microglial activation and neuropathological conditions, including Alzheimer's and Parkinson's diseases. Here, we review essential microglial homeostatic functions regulated by SFKs, including phagocytosis, environmental sensing, and secretion of inflammatory mediators. In addition, we discuss the potential of SFK modulation for microglial homeostasis in Parkinson's and Alzheimer's diseases.

Metabolic adaption of cancer cells toward autophagy: Is there a role for ER-phagy?

Autophagy is an evolutionary conserved catabolic pathway that uses a unique double-membrane vesicle, called autophagosome, to sequester cytosolic components, deliver them to lysosomes and recycle amino-acids. Essentially, autophagy acts as a cellular cleaning system that maintains metabolic balance under basal conditions and helps to ensure nutrient viability under stress conditions. It is also an important quality control mechanism that removes misfolded or aggregated proteins and mediates the turnover of damaged and obsolete organelles. In this regard, the idea that autophagy is a non-selective bulk process is outdated. It is now widely accepted that forms of selective autophagy are responsible for metabolic rewiring in response to cellular demand. Given its importance, autophagy plays an essential role during tumorigenesis as it sustains malignant cellular growth by acting as a coping-mechanisms for intracellular and environmental stress that occurs during malignant transformation. Cancer development is accompanied by the formation of a peculiar tumor microenvironment that is mainly characterized by hypoxia (oxygen < 2%) and low nutrient availability. Such conditions challenge cancer cells that must adapt their metabolism to survive. Here we review the regulation of autophagy and selective autophagy by hypoxia and the crosstalk with other stress response mechanisms, such as UPR. Finally, we discuss the emerging role of ER-phagy in sustaining cellular remodeling and quality control during stress conditions that drive tumorigenesis.

Identifying a Feasible Transition Pathway between Two Conformational States for a Protein

Proteins usually need to transit between different conformational states to fulfill their biological functions. In the mechanistic study of such transition processes by molecular dynamics simulations, identification of the minimum free energy path (MFEP) can substantially reduce the sampling space, thus enabling rigorous thermodynamic evaluation of the process. Conventionally, the MFEP is derived by iterative local optimization from an initial path, which is typically generated by simple brute force techniques like the targeted molecular dynamics (tMD). Therefore, the quality of the initial path determines the successfulness of MFEP estimation. In this work, we propose a method to improve derivation of the initial path. Through iterative relaxation-biasing simulations in a bidirectional manner, this method can construct a feasible transition pathway connecting two known states for a protein. Evaluation on small, fast-folding proteins against long equilibrium trajectories supports the good sampling efficiency of our method. When applied to larger proteins including the catalytic domain of human c-Src kinase as well as the converter domain of myosin VI, the paths generated by our method deviate significantly from those computed with the generic tMD approach. More importantly, free energy profiles and intermediate states obtained from our paths exhibit remarkable improvements over those from tMD paths with respect to both physical rationality and consistency with a priori knowledge.

Phosphoregulation of Kinesins Involved in Long-Range Intracellular Transport

Kinesins, the microtubule-dependent mechanochemical enzymes, power a variety of intracellular movements. Regulation of Kinesin activity and Kinesin-Cargo interactions determine the direction, timing and flux of various intracellular transports. This review examines how phosphorylation of Kinesin subunits and adaptors influence the traffic driven by Kinesin-1, -2, and -3 family motors. Each family of Kinesins are phosphorylated by a partially overlapping set of serine/threonine kinases, and each event produces a unique outcome. For example, phosphorylation of the motor domain inhibits motility, and that of the stalk and tail domains induces cargo loading and unloading effects according to the residue and context. Also, the association of accessory subunits with cargo and adaptor proteins with the motor, respectively, is disrupted by phosphorylation. In some instances, phosphorylation by the same kinase on different Kinesins elicited opposite outcomes. We discuss how this diverse range of effects could manage the logistics of Kinesin-dependent, long-range intracellular transport.

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.

Investigating Phosphorylation-Induced Conformational Changes in WNK1 Kinase by Molecular Dynamics Simulations

The With-No-Lysine (WNK) kinase is considered to be a master regulator for various cation-chloride cotransporters involved in maintaining cell-volume and ion homeostasis. Here, we have investigated the phosphorylation-induced structural dynamics of the WNK1 kinase bound to an inhibitor via atomistic molecular dynamics simulations. Results from our simulations show that the phosphorylation at Ser³⁸² could stabilize the otherwise flexible activation loop (A-loop). The intrahelix salt-bridge formed between Arg²⁶⁴ and Glu²⁶⁸ in the unphosphorylated system is disengaged after the phosphorylation, and Glu²⁶⁸ reorients itself and forms a stable salt-bridge with Arg³⁴⁸. The dynamic cross-correlation analysis shows that phosphorylation diminishes anticorrelated motions and increases correlated motions between different domains. Structural network analysis reveals that the phosphorylation causes structural rearrangements and shortens the communication path between the αC-helix and catalytic loop, making the binding pocket more suitable for accommodating the ligand. Overall, we have characterized the structural changes in the WNK kinase because of phosphorylation in the A-loop, which might help in designing rational drugs.

Binding site comparisons for target-centered drug discovery

INTRODUCTION

The success of binding site comparisons in drug discovery is based on the recognized fact that many different proteins have similar binding sites. Indeed, binding site comparisons have found many uses in drug development and have the potential to dramatically cut the cost and shorten the time necessary for the development of new drugs. Areas covered: The authors review recent methods for comparing protein binding sites and their use in drug repurposing and polypharmacology. They examine emerging fields including the use of binding site comparisons in precision medicine, the prediction of structured water molecules, the search for targets of natural compounds, and their application in the development of protein-based drugs by loop modeling and for comparison of RNA binding sites. Expert opinion: Binding site comparisons have produced many interesting results in drug development, but relatively little work has been done on protein-protein interaction sites, which are particularly relevant in view of the success of biological drugs. Growth of protein loop modeling for modulating biological drugs is anticipated. The fusion of currently distinct methods for the comparison of RNA and protein binding sites into a single comprehensive approach could allow the search for new selective ribosomal antibiotics and initiate pharmaceutical research into other nucleoproteins.

The Src module: an ancient scaffold in the evolution of cytoplasmic tyrosine kinases

Tyrosine kinases were first discovered as the protein products of viral oncogenes. We now know that this large family of metazoan enzymes includes nearly one hundred structurally diverse members. Tyrosine kinases are broadly classified into two groups: the transmembrane receptor tyrosine kinases, which sense extracellular stimuli, and the cytoplasmic tyrosine kinases, which contain modular ligand-binding domains and propagate intracellular signals. Several families of cytoplasmic tyrosine kinases have in common a core architecture, the "Src module," composed of a Src-homology 3 (SH3) domain, a Src-homology 2 (SH2) domain, and a kinase domain. Each of these families is defined by additional elaborations on this core architecture. Structural, functional, and evolutionary studies have revealed a unifying set of principles underlying the activity and regulation of tyrosine kinases built on the Src module. The discovery of these conserved properties has shaped our knowledge of the workings of protein kinases in general, and it has had important implications for our understanding of kinase dysregulation in disease and the development of effective kinase-targeted therapies.

Hypoxia and Selective Autophagy in Cancer Development and Therapy

Low oxygen availability, a condition known as hypoxia, is a common feature of various pathologies including stroke, ischemic heart disease, and cancer. Hypoxia adaptation requires coordination of intricate pathways and mechanisms such as hypoxia-inducible factors (HIFs), the unfolded protein response (UPR), mTOR, and autophagy. Recently, great effort has been invested toward elucidating the interplay between hypoxia-induced autophagy and cancer cell metabolism. Although novel types of selective autophagy have been identified, including mitophagy, pexophagy, lipophagy, ERphagy and nucleophagy among others, their potential interface with hypoxia response mechanisms remains poorly understood. Autophagy activation facilitates the removal of damaged cellular compartments and recycles components, thus promoting cell survival. Importantly, tumor cells rely on autophagy to support self-proliferation and metastasis; characteristics related to poor disease prognosis. Therefore, a deeper understanding of the molecular crosstalk between hypoxia response mechanisms and autophagy could provide important insights with relevance to cancer and hypoxia-related pathologies. Here, we survey recent findings implicating selective autophagy in hypoxic responses, and discuss emerging links between these pathways and cancer pathophysiology.

Using molecular simulation to explore the nanoscale dynamics of the plant kinome

Eukaryotic protein kinases (PKs) are a large family of proteins critical for cellular response to external signals, acting as molecular switches. PKs propagate biochemical signals by catalyzing phosphorylation of other proteins, including other PKs, which can undergo conformational changes upon phosphorylation and catalyze further phosphorylations. Although PKs have been studied thoroughly across the domains of life, the structures of these proteins are sparsely understood in numerous groups of organisms, including plants. In addition to efforts towards determining crystal structures of PKs, research on human PKs has incorporated molecular dynamics (MD) simulations to study the conformational dynamics underlying the switching of PK function. This approach of experimental structural biology coupled with computational biophysics has led to improved understanding of how PKs become catalytically active and why mutations cause pathological PK behavior, at spatial and temporal resolutions inaccessible to current experimental methods alone. In this review, we argue for the value of applying MD simulation to plant PKs. We review the basics of MD simulation methodology, the successes achieved through MD simulation in animal PKs, and current work on plant PKs using MD simulation. We conclude with a discussion of the future of MD simulations and plant PKs, arguing for the importance of molecular simulation in the future of plant PK research.

A switch in nucleotide affinity governs activation of the Src and Tec family kinases

The Tec kinases, closely related to Src family kinases, are essential for lymphocyte function in the adaptive immune system. Whilst the Src and Abl kinases are regulated by tail phosphorylation and N-terminal myristoylation respectively, the Tec kinases are notable for the absence of either regulatory element. We have found that the inactive conformations of the Tec kinase Itk and Src preferentially bind ADP over ATP, stabilising both proteins. We demonstrate that Itk adopts the same conformation as Src and that the autoinhibited conformation of Src is independent of its C-terminal tail. Allosteric activation of both Itk and Src depends critically on the disruption of a conserved hydrophobic stack that accompanies regulatory domain displacement. We show that a conformational switch permits the exchange of ADP for ATP, leading to efficient autophosphorylation and full activation. In summary, we propose a universal mechanism for the activation and autoinhibition of the Src and Tec kinases.

Parameterization of Palmitoylated Cysteine, Farnesylated Cysteine, Geranylgeranylated Cysteine, and Myristoylated Glycine for the Martini Force Field

Peripheral membrane proteins go through various post-translational modifications that covalently bind fatty acid tails to specific amino acids. These post-translational modifications significantly alter the lipophilicity of the modified proteins and allow them to anchor to biological membranes. Over 1000 different proteins have been identified to date that require such membrane-protein interactions to carry out their biological functions, including members of the Src and Ras superfamilies that play key roles in cell signaling and carcinogenesis. We have used all-atom simulations with the CHARMM36 force field to parameterize four of the most common post-translational modifications for the Martini 2.2 force field: palmitoylated cysteine, farnesylated cysteine, geranylgeranylated cysteine, and myristoylated glycine. The parameters reproduce the key features of clusters of configurations of the different anchors in lipid membranes as well as the water-octanol partitioning free energies of the anchors, which are crucial for the correct reproduction of the expected biophysical behavior of peripheral membrane proteins at the membrane-water interface. Implementation in existing Martini setup tools facilitates the use of the new parameters.

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.

Piezoelectric allostery of protein

Allostery is indispensable for a protein to work, where a locally applied stimulus is transmitted to a distant part of the molecule. While the allostery due to chemical stimuli such as ligand binding has long been studied, the growing interest in mechanobiology prompts the study of the mechanically stimulated allostery, the physical mechanism of which has not been established. By molecular dynamics simulation of a motor protein myosin, we found that a locally applied mechanical stimulus induces electrostatic potential change at distant regions, just like the piezoelectricity. This novel allosteric mechanism, "piezoelectric allostery", should be of particularly high value for mechanosensor/transducer proteins.

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.

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.

Autoinhibition of Bruton's tyrosine kinase (Btk) and activation by soluble inositol hexakisphosphate

Bruton's tyrosine kinase (Btk), a Tec-family tyrosine kinase, is essential for B-cell function. We present crystallographic and biochemical analyses of Btk, which together reveal molecular details of its autoinhibition and activation. Autoinhibited Btk adopts a compact conformation like that of inactive c-Src and c-Abl. A lipid-binding PH-TH module, unique to Tec kinases, acts in conjunction with the SH2 and SH3 domains to stabilize the inactive conformation. In addition to the expected activation of Btk by membranes containing phosphatidylinositol triphosphate (PIP3), we found that inositol hexakisphosphate (IP6), a soluble signaling molecule found in both animal and plant cells, also activates Btk. This activation is a consequence of a transient PH-TH dimerization induced by IP6, which promotes transphosphorylation of the kinase domains. Sequence comparisons with other Tec-family kinases suggest that activation by IP6 is unique to Btk.

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.

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.

Multiple steps to activate FAK's kinase domain: adaptation to confined environments?

Protein kinases regulate cell signaling by phosphorylating their substrates in response to environment-specific stimuli. Using molecular dynamics, we studied the catalytically active and inactive conformations of the kinase domain of the focal adhesion kinase (FAK), which are distinguished by displaying a structured or unstructured activation loop, respectively. Upon removal of an ATP analog, we show that the nucleotide-binding pocket in the catalytically active conformation is structurally unstable and fluctuates between an open and closed configuration. In contrast, the pocket remains open in the catalytically inactive form upon removal of an inhibitor from the pocket. Because temporal pocket closures will slow the ATP on-rate, these simulations suggest a multistep process in which the kinase domain is more likely to bind ATP in the catalytically inactive than in the active form. Transient closures of the ATP-binding pocket might allow FAK to slow down its catalytic cycle. These short cat naps could be adaptions to crowded or confined environments by giving the substrate sufficient time to diffuse away. The simulations show further how either the phosphorylation of the activation loop or the activating mutations of the so-called SuperFAK influence the electrostatic switch that controls kinase activity.

Conformational stability of inositol 1,3,4,5,6-pentakisphosphate 2-kinase (IPK1) dictates its substrate selectivity

Inositol 1,3,4,5,6-pentakisphosphate 2-kinase (IPK1) converts inositol 1,3,4,5,6-pentakisphosphate(IP5) to inositol hexakisphosphate (IP6). IPK1 shares structural similarity with protein kinases and is suspected to employ a similar mechanism of activation. Previous studies revealed roles for the 1- and 3-phosphates of IP5 in IPK1 activation and revealed that the N-lobe of IPK1 is unstable in the absence of inositol phosphate (IP). Here, we demonstrate the link between IPK1 substrate specificity and the stability of its N-lobe. Limited proteolysis of IPK1 revealed that N-lobe stability is dependent on the presence of the 1-phosphate of the substrate, whereas overall stability of IPK1 was increased in ternary complexes with nucleotide and IPs possessing 1- and 3-phosphates that engage the N-lobe of IPK1. Thus, the 1- and 3-phosphates possess dual roles in both IPK1 activation and IPK1 stability. To test whether kinase stability directly contributed to substrate selectivity of the kinase, we engineered IPK1 mutants with disulfide bonds that artificially stabilized the N-lobe in an IP-independent manner thereby mimicking its substrate-bound state in the absence of IP. IPK1 E82C/S142C exhibited a DTT-sensitive 5-fold increase in kcat for 3,4,5,6-inositol tetrakisphosphate (3,4,5,6-IP4) as compared with wild-type IPK1. The crystal structure of the IPK1 E82C/S142C mutant confirmed the presence of the disulfide bond and revealed a small shift in the N-lobe. Finally, we determined that IPK1 E82C/S142C is substantially more stable than wild-type IPK1 under nonreducing conditions, revealing that increased stability of IPK1 E82C/S142C correlates with changes in substrate specificity by allowing IPs lacking the stabilizing 1-phosphate to be used. Taken together, our results show that IPK1 substrate selection is linked to the ability of each potential substrate to stabilize IPK1.

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.

Roles of phosphate recognition in inositol 1,3,4,5,6-pentakisphosphate 2-kinase (IPK1) substrate binding and activation

Inositol phosphate kinases (IPKs) sequentially phosphorylate inositol phosphates (IPs) to yield a group of small signaling molecules involved in diverse cellular processes. IPK1 (inositol 1,3,4,5,6-pentakisphosphate 2-kinase) phosphorylates inositol 1,3,4,5,6-pentakisphosphate to inositol 1,2,3,4,5,6-hexakisphosphate; however, the mechanism of IP recognition employed by IPK1 is currently unresolved. We demonstrated previously that IPK1 possesses an unstable N-terminal lobe in the absence of IP, which led us to propose that the phosphate profile of the IP was linked to stabilization of IPK1. Here, we describe a systematic study to determine the roles of the 1-, 3-, 5-, and 6-phosphate groups of inositol 1,3,4,5,6-pentakisphosphate in IP binding and IPK1 activation. The 5- and 6-phosphate groups were the most important for IP binding to IPK1, and the 1- and 3-phosphate groups were more important for IPK1 activation than the others. Moreover, we demonstrate that there are three critical residues (Arg-130, Lys-170, and Lys-411) necessary for IPK1 activity. Arg-130 is the only substrate-binding N-terminal lobe residue that can render IPK1 inactive; its 1-phosphate is critical for full IPK1 activity and for stabilization of the active conformation of IPK1. Taken together, our results support the model for recognition of the IP substrate by IPK1 in which (i) the 4-, 5-, and 6-phosphates are initially recognized by the C-terminal lobe, and subsequently, (ii) the interaction between the 1-phosphate and Arg-130 stabilizes the N-terminal lobe and activates IPK1. This model of IP recognition, believed to be unique among IPKs, could be exploited for selective inhibition of IPK1 in future studies that investigate the role of higher IPs.

Transitions to catalytically inactive conformations in EGFR kinase

The epidermal growth factor receptor (EGFR) is a key protein in cellular signaling, and its kinase domain (EGFR kinase) is an intensely pursued target of small-molecule drugs. Although both catalytically active and inactive conformations of EGFR kinase have been resolved crystallographically, experimental characterization of the transitions between these conformations remains difficult. Using unbiased, all-atom molecular dynamics simulations, we observed EGFR kinase spontaneously transition from the active to the so-called "Src-like inactive" conformation by way of two sets of intermediate conformations: One corresponds to a previously identified locally disordered state and the other to previously undescribed "extended" conformations, marked by the opening of the ATP-binding site between the two lobes of the kinase domain. We also simulated the protonation-dependent transition of EGFR kinase to another ["Asp-Phe-Gly-out" ("DFG-out")] inactive conformation and observed similar intermediate conformations. A key element observed in the simulated transitions is local unfolding, or "cracking," which supports a prediction of energy landscape theory. We used hydrogen-deuterium (H/D) exchange measurements to corroborate our simulations and found that the simulated intermediate conformations correlate better with the H/D exchange data than existing active or inactive EGFR kinase crystal structures. The intermediate conformations revealed by our simulations of the transition process differ significantly from the existing crystal structures and may provide unique possibilities for structure-based drug discovery.

Unrestrained computation of free energy along a path

We apply the adaptive biasing potential (ABP) method to optimize the principal curve defining a conformational transition between two known end states and to subsequently compute the one-dimensional potential of mean force as a function of arc length along the principal curve. This approach allows the use of the ABP method in a collective variable space of arbitrary dimension and offers several advantages over line-search methods. First, configurations are neither generated along an initial path for the transition nor equilibrated during evolution of the path. Second, and most importantly, the powerful sampling provided by the ABP serves to accelerate the dynamics during the optimization and computation of the free energy. Finally, the free energy is formulated as a potential of mean force that captures changes in the reaction channel along the principal curve, in contrast to the free energy profile evaluated from the local free-energy gradient in restrained path optimization methods. We first demonstrate the ABP formulation of path optimization using a two-dimensional potential surface and then with a more complex system of Src protein tyrosine kinase. The method is shown to be efficient and robust in the case of rugged, free-energy landscapes.

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.

Inositol phosphate-induced stabilization of inositol 1,3,4,5,6-pentakisphosphate 2-kinase and its role in substrate specificity

Inositol phosphate kinases (IPKs) sequentially phosphorylate inositol phosphates (IPs) on their inositol rings to yield an array of signaling molecules. IPKs must possess the ability to recognize their physiological substrates from among a pool of over 30 cellular IPs that differ in numbers and positions of phosphates. Crystal structures from IPK subfamilies have revealed structural determinants for IP discrimination, which vary considerably between IPKs. However, recent structures of inositol 1,3,4,5,6-pentakisphosphate 2-kinase (IPK1) did not reveal how IPK1 selectively recognizes its physiological substrate, IP5, while excluding others. Here, we report that limited proteolysis has revealed the presence of multiple conformational states in the IPK1 catalytic cycle, with notable protection from protease only in the presence of IP. Further, a 3.1-Å crystal structure of IPK1 bound to ADP in the absence of IP revealed decreased order in residues 110-140 within the N-lobe of the kinase compared with structures in which IP is bound. Using this solution and crystallographic data, we propose a model for recognition of IP substrate by IPK1 wherein phosphate groups at the 4-, 5-, and 6-positions are recognized initially by the C-lobe with subsequent interaction of the 1-position phosphate by Arg130 that stabilizes this residue and the N-lobe. This model explains how IPK1 can be highly specific for a single IP substrate by linking its interactions with substrate phosphate groups to the stabilization of the N- and C-lobes and kinase activation.

Expression and purification of Src-family kinases for solution NMR studies

NMR analyses of the structure, dynamics, and interactions of the Src family kinases (SFKs) have been hindered by the limited ability to obtain sufficient amounts of properly folded, soluble protein from bacterial expression systems, to allow these studies to be performed in an economically viable manner. In this chapter, we detail our attempts to overcome these difficulties using the catalytic domain (SrcCD) of c-Src, the prototypical SFK, as an illustrative example. We describe in detail two general methods to express and purify SrcCD from Escherichia coli expression systems in both fully active wild-type and kinase-deficient mutant forms, allowing the efficient and cost-effective labeling by NMR-active isotopes for solution NMR studies.

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.

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.