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

The α C helix is a central regulator of PKR activation

Protein kinase R (PKR) functions in the eukaryotic innate immune system as a first-line defense against viral infections. PKR binds viral dsRNA, leading to autophosphorylation and activation. In its active state, PKR can phosphorylate its primary substrate, eIF2 α , which blocks initiation of translation in the infected cell. It has been established that PKR activation occurs when the kinase domain dimerizes in a back-to-back configuration. However, the mechanism by which dimerization leads to enzymatic activation is not fully understood. Here, we investigate the structural mechanistic basis and energy landscape for PKR activation, with a focus on the α C helix - a kinase activation and signal integration hub - using all-atom equilibrium and enhanced sampling molecular dynamics simulations. By employing window-exchange umbrella sampling, we compute free energy profiles of activation which show that back-to-back dimerization stabilizes a catalytically competent conformation of PKR. Key hydrophobic residues in the homodimer interface contribute to stabilization of the α C helix in an active conformation and the position of its glutamate residue. Using linear mutual information analysis, we analyze allosteric communication connecting the protomers' N-lobes and the α C helix dimer interface with the α C helix.

Structure and regulation of full-length human leucine-rich repeat kinase 1

The human leucine-rich repeat kinases (LRRKs), LRRK1 and LRRK2 are large and unusually complex multi-domain kinases, which regulate fundamental cellular processes and have been implicated in human disease. Structures of LRRK2 have recently been determined, but the structure and molecular mechanisms regulating the activity of the LRRK1 as well as differences in the regulation of LRRK1 and LRRK2 remain unclear. Here, we report a cryo-EM structure of the LRRK1 monomer and a lower-resolution cryo-EM map of the LRRK1 dimer. The monomer structure, in which the kinase is in an inactive conformation, reveals key interdomain interfaces that control kinase activity as we validate experimentally. Both the LRRK1 monomer and dimer are structurally distinct compared to LRRK2. Overall, our results provide structural insights into the activation of the human LRRKs, which advance our understanding of their physiological and pathological roles.

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

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

Fungal CFEM effectors negatively regulate a maize wall-associated kinase by interacting with its alternatively spliced variant to dampen resistance

The fungus Fusarium graminearum causes a devastating disease Gibberella stalk rot of maize. Our knowledge of molecular interactions between F. graminearum effectors and maize immunity factors is lacking. Here, we show that a group of cysteine-rich common in fungal extracellular membrane (CFEM) domain proteins of F. graminearum are required for full virulence in maize stalk infection and that they interact with two secreted maize proteins, ZmLRR5 and ZmWAK17ET. ZmWAK17ET is an alternative splicing isoform of a wall-associated kinase ZmWAK17. Both ZmLRR5 and ZmWAK17ET interact with the extracellular domain of ZmWAK17. Transgenic maize overexpressing ZmWAK17 shows increased resistance to F. graminearum, while ZmWAK17 mutants exhibit enhanced susceptibility to F. graminearum. Transient expression of ZmWAK17 in Nicotiana benthamiana triggers hypersensitive cell death, whereas co-expression of CFEMs with ZmWAK17ET or ZmLRR5 suppresses the ZmWAK17-triggered cell death. Our results show that ZmWAK17 mediates stalk rot resistance and that F. graminearum delivers apoplastic CFEMs to compromise ZmWAK17-mediated resistance.

Csk αC Helix: A Computational Analysis of an Essential Region for Conformational Transitions

Conformational changes are an essential feature for the function of some dynamic proteins. Understanding the mechanism of such motions may allow us to identify important properties, which may be directly related to the regulatory function of a protein. Also, this knowledge may be employed for a rational design of drugs that can shift the balance between active and inactive conformations, as well as affect the kinetics of the activation process. Here, the conformational changes in carboxyl-terminal Src kinase, the major catalytic repressor to the Src family of kinases, was investigated, and it was proposed as a functionally related hypothesis. A Cα Structure-Based Model (Cα-SBM) was applied to provide a description of the overall conformational landscape and further analysis complemented by detailed molecular dynamics simulations. As a first approach to Cα-SBM simulations, reversible transitions between active (closed) and inactive (open) forms were modeled as fluctuations between these two energetic basins. It was found that, in addition to the interdomain Carboxyl-terminal SRC Kinase (Csk) correlated motions, a conformational change in the αC helix is required for a complete conformational transition. The result reveals this as an important region of transition control and domain coordination. Restrictions in the αC helix region of the Csk protein were performed, and the analyses showed a direct correlation with the global conformational changes, with this location being propitious for future studies of ligands. Also, the Src Homology 3 (SH3) and SH3 plus Src Homology 2 (SH2) domains were excluded for a direct comparison with experimental results previously published. Simulations where the SH3 was deleted presented a reduction of the transitions during the simulations, while the SH3-SH2 deletion vanishes the Csk transitions, corroborating the experimental results mentioned and linking the conformational changes with the catalytic functionality of Csk. The study was complemented by the introduction of a known kinase inhibitor close to the Csk αC helix region where its consequences for the kinetic behavior and domain displacement of Csk were verified through detailed molecular dynamics. The findings describe the mechanisms involving the Csk αC helix for the transitions and also support the dynamic correlation between SH3 and SH2 domains against the Csk lobes and how local energetic restrictions or interactions in the Csk αC helix can play an important role for long-range motions. The results also allow speculation if the Csk activity is restricted to one specific conformation or a consequence of a state transition, this point being a target for future studies. However, the αC helix is revealed as a potential region for rational drug design.

Reply to Correspondence on "Synergy and Antagonism between Allosteric and Active-Site Inhibitors of Abl Tyrosine Kinase"

Manley and co-workers provide data demonstrating that, at super-pharmacological concentrations (300 μM), a ternary complex between Abl, asciminib, and ATP-competitive inhibitors is possible. The work in our manuscript concerns the interplay of asciminib (and GNF-2) with ATP-competitive inhibitors at pharmacologically relevant concentrations (Cmax =1.6-3.7 μM for asciminib). Manley and co-workers do not question any of the studies that we reported, nor do they provide explanations for how our work fits into their preferred model. Herein, we consider the data presented by Manley and co-workers. In addition, we provide new data supporting the findings in our Communication. Asciminib and ATP-competitive inhibitors do not simultaneously bind Abl at pharmacologically relevant concentrations unless the conformation selectivity for both ligands is matched.

Validation of an allosteric binding site of Src kinase identified by unbiased ligand binding simulations

Allostery plays a primary role in regulating protein activity, making it an important mechanism in human disease and drug discovery. Identifying allosteric regulatory sites to explore their biological significance and therapeutic potential is invaluable to drug discovery; however, identification remains a challenge. Allosteric sites are often "cryptic" without clear geometric or chemical features. Since allosteric regulatory sites are often less conserved in protein kinases than the orthosteric ATP binding site, allosteric ligands are commonly more specific than ATP competitive inhibitors. We present a generalizable computational protocol to predict allosteric ligand binding sites based on unbiased ligand binding simulation trajectories. We demonstrate the feasibility of this protocol by revisiting our previously published ligand binding simulations using the first identified viral proto-oncogene, Src kinase, as a model system. The binding paths for kinase inhibitor PP1 uncovered three metastable intermediate states before binding the high-affinity ATP-binding pocket, revealing two previously known allosteric sites and one novel site. Herein, we validate the novel site using a combination of virtual screening and experimental assays to identify a v-type allosteric small-molecule inhibitor that targets this novel site with specificity for Src over closely related kinases. This study provides a proof-of-concept for employing unbiased ligand binding simulations to identify cryptic allosteric binding sites and is widely applicable to other protein-ligand systems.

A Companion Guide to the String Method with Swarms of Trajectories: Characterization, Performance, and Pitfalls

The string method with swarms of trajectories (SMwST) is an algorithm that identifies a physically meaningful transition pathway─a one-dimensional curve, embedded within a high-dimensional space of selected collective variables. The SMwST algorithm leans on a series of short, unbiased molecular dynamics simulations spawned at different locations of the discretized path, from whence an average dynamic drift is determined to evolve the string toward an optimal pathway. However conceptually simple in both its theoretical formulation and practical implementation, the SMwST algorithm is computationally intensive and requires a careful choice of parameters for optimal cost-effectiveness in applications to challenging problems in chemistry and biology. In this contribution, the SMwST algorithm is presented in a self-contained manner, discussing with a critical eye its theoretical underpinnings, applicability, inherent limitations, and use in the context of path-following free-energy calculations and their possible extension to kinetics modeling. Through multiple simulations of a prototypical polypeptide, combining the search of the transition pathway and the computation of the potential of mean force along it, several practical aspects of the methodology are examined with the objective of optimizing the computational effort, yet without sacrificing accuracy. In light of the results reported here, we propose some general guidelines aimed at improving the efficiency and reliability of the computed pathways and free-energy profiles underlying the conformational transitions at hand.

Evolution of CDK1 Paralog Specializations in a Lineage With Fast Developing Planktonic Embryos

The active site of the essential CDK1 kinase is generated by core structural elements, among which the PSTAIRE motif in the critical αC-helix, is universally conserved in the single CDK1 ortholog of all metazoans. We report serial CDK1 duplications in the chordate, Oikopleura. Paralog diversifications in the PSTAIRE, activation loop substrate binding platform, ATP entrance site, hinge region, and main Cyclin binding interface, have undergone positive selection to subdivide ancestral CDK1 functions along the S-M phase cell cycle axis. Apparent coevolution of an exclusive CDK1d:Cyclin Ba/b pairing is required for oogenic meiosis and early embryogenesis, a period during which, unusually, CDK1d, rather than Cyclin Ba/b levels, oscillate, to drive very rapid cell cycles. Strikingly, the modified PSTAIRE of odCDK1d shows convergence over great evolutionary distance with plant CDKB, and in both cases, these variants exhibit increased specialization to M-phase.

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.

Substrate binding to Src: A new perspective on tyrosine kinase substrate recognition from NMR and molecular dynamics

Most signal transduction pathways in humans are regulated by protein kinases through phosphorylation of their protein substrates. Typical eukaryotic protein kinases are of two major types: those that phosphorylate-specific sequences containing tyrosine (~90 kinases) and those that phosphorylate either serine or threonine (~395 kinases). The highly conserved catalytic domain of protein kinases comprises a smaller N lobe and a larger C lobe separated by a cleft region lined by the activation loop. Prior studies find that protein tyrosine kinases recognize peptide substrates by binding the polypeptide chain along the C-lobe on one side of the activation loop, while serine/threonine kinases bind their substrates in the cleft and on the side of the activation loop opposite to that of the tyrosine kinases. Substrate binding structural studies have been limited to four families of the tyrosine kinase group, and did not include Src tyrosine kinases. We examined peptide-substrate binding to Src using paramagnetic-relaxation-enhancement NMR combined with molecular dynamics simulations. The results suggest Src tyrosine kinase can bind substrate positioning residues C-terminal to the phosphoacceptor residue in an orientation similar to serine/threonine kinases, and unlike other tyrosine kinases. Mutagenesis corroborates this new perspective on tyrosine kinase substrate recognition. Rather than an evolutionary split between tyrosine and serine/threonine kinases, a change in substrate recognition may have occurred within the TK group of the human kinome. Protein tyrosine kinases have long been therapeutic targets, but many marketed drugs have deleterious off-target effects. More accurate knowledge of substrate interactions of tyrosine kinases has the potential for improving drug selectivity.

How Electrostatic Coupling Enables Conformational Plasticity in a Tyrosine Kinase

Protein kinases are important cellular signaling molecules involved in cancer and a multitude of other diseases. It is well-known that inactive kinases display a remarkable conformational plasticity; however, the molecular mechanisms remain poorly understood. Conformational heterogeneity presents an opportunity but also a challenge in kinase drug discovery. The ability to predictively model various conformational states could accelerate selective inhibitor design. Here we performed a proton-coupled molecular dynamics study to explore the conformational landscape of a c-Src kinase. Starting from a completely inactive structure, the simulations captured all major types of conformational states without the use of a target structure, mutation, or bias. The simulations allowed us to test the experimental hypotheses regarding the mechanism of DFG flip, its coupling to the αC-helix movement, and the formation of regulatory spine. Perhaps the most significant finding is how key titratable residues, such as DFG-Asp, αC-Glu, and HRD-Asp, change protonation states dependent on the DFG, αC, and activation loop conformations. Our data offer direct evidence to support a long-standing hypothesis that protonation of Asp favors the DFG-out state and explain why DFG flip is also possible in simulations with deprotonated Asp. The simulations also revealed intermediate states, among which a unique DFG-out/α-C state formed as DFG-Asp is moved into a back pocket forming a salt bridge with catalytic Lys, which can be tested in selective inhibitor design. Our finding of how proton coupling enables the remarkable conformational plasticity may shift the paradigm of computational studies of kinases which assume fixed protonation states. Understanding proton-coupled conformational dynamics may hold a key to further innovation in kinase drug discovery.

MARK4 protein can explore the active-like conformations in its non-phosphorylated state

Microtubule affinity-regulating kinase 4 (MARK4) is a Ser/Thr protein kinase, best known for its role in phosphorylating microtubule associated proteins, causing their detachment from microtubules. In the current study, the non-phosphorylated conformation of the activation loop was modeled in a structure representing the enzymatically inactive form of this protein, and its dynamics were evaluated through a 100 ns initial all-atom simulation, which was prolonged by another 2 μs. Although the activation loop was folding on itself and was leaning toward ATP site in the initial modeled structure, soon after the initiating the simulation, this loop stretched away from the ATP binding site and stably settled in its new position for the rest of simulation time. A network of hydrogen bonds, mainly between the activation segment residues, αC-helix and the catalytic loop reinforced this conformation. Interestingly, several features of active kinase conformation such as formation of R-spine, Glu106-Lys88 salt-bridge, and DFG-In motif were observed during a considerable number of trajectory frames. However, they were not sustainably established during the simulation time, except for the DFG-In motif. Consequently, this study introduces a stable conformation of the non-phosphorylated form of MARK4 protein with a partially stretched activation loop conformation as well as partial formation of R-spine, closely resembling the active kinase.

Allosteric Regulation of Protein Kinases Downstream of PI3-Kinase Signalling

Allostery is a basic principle that enables proteins to process and transmit cellular information. Protein kinases evolved allosteric mechanisms to transduce cellular signals to downstream signalling components or effector molecules. Protein kinases catalyse the transfer of the terminal phosphate from ATP to protein substrates upon specific stimuli. Protein kinases are targets for the development of small molecule inhibitors for the treatment of human diseases. Drug development has focussed on ATP-binding site, while there is increase interest in the development of drugs targeting alternative sites, i.e. allosteric sites. Here, we review the mechanism of regulation of protein kinases, which often involve the allosteric modulation of the ATP-binding site, enhancing or inhibiting activity. We exemplify the molecular mechanism of allostery in protein kinases downstream of PI3-kinase signalling with a focus on phosphoinositide-dependent protein kinase 1 (PDK1), a model kinase where small compounds can allosterically modulate the conformation of the kinase bidirectionally.

Protein Conformational Transitions from All-Atom Adaptively Biased Path Optimization

Simulation methods are valuable for elucidating protein conformational transitions between functionally diverse states given that transition pathways are difficult to capture experimentally. Nonetheless, specific computational algorithms are required because of the high free energy barriers between these different protein conformational states. Adaptively biased path optimization (ABPO) is an unrestrained, transition-path optimization method that works in a reduced-variable space to construct an adaptive biasing potential to aid convergence. ABPO was previously applied using a coarse-grained Go̅-model to study conformational activation of Lyn, a Src family tyrosine kinase. How effectively ABPO can be applied at the higher resolution of an all-atom model to explore protein conformational transitions is not yet known. Here, we report the all-atom conformational transition paths of three protein systems constructed using the ABPO methodology. Two systems, triose phosphate isomerase and dihydrofolate reductase, undergo local flipping of a short loop that promotes ligand binding. The third system, estrogen receptor α ligand binding domain, has a helix that adopts different conformations when the protein is bound to an agonist or an antagonist. For each protein, distance-based or torsion-angle reduced variables were identified from unbiased trajectories. ABPO was computed in this reduced variable space to obtain the transition path between the two states. The all-atom ABPO is shown to successfully converge an optimal transition path for each of the three systems.

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.

Redefining the Protein Kinase Conformational Space with Machine Learning

Protein kinases are dynamic, adopting different conformational states that are critical for their catalytic activity. We assess a range of structural features derived from the conserved αC helix and DFG motif to define the conformational space of the catalytic domain of protein kinases. We then construct Kinformation, a random forest classifier, to annotate the conformation of 3,708 kinase structures in the PDB. Our classification scheme captures known active and inactive kinase conformations and defines an additional conformational state, thereby refining the current understanding of the kinase conformational space. Furthermore, network analysis of the small molecules recognized by each conformation captures chemical substructures that are associated with each conformation type. Our description of the kinase conformational space is expected to improve modeling of protein kinase structures, as well as guide the development of conformation-specific kinase inhibitors with optimal pharmacological profiles.

Allosteric Control of a Plant Receptor Kinase through S-Glutathionylation

Growing evidence supports the importance of protein S-glutathionylation as a regulatory post-translational modification with functional consequences for proteins. Discoveries of redox-state-dependent protein kinase S-glutathionylation have fueled discussion of redox-sensitive signaling. Following previously published experimental evidence for S-glutathionylation induced deactivation of the Arabidopsis thaliana kinase BRASSINOSTEROID INSENSITIVE 1-ASSOCIATED RECEPTOR-LIKE KINASE 1 (BAK1), we investigated the consequences of S-glutathionylation on the equilibrium conformational ensemble of BAK1 using all-atom molecular dynamics simulations. We found that glutathionylation of C408 allosterically destabilizes the active-like state of BAK1 and stabilizes an inactive conformation known to recur in protein kinases. Glutathionylation of C408 also has structural consequences throughout the BAK1 kinase domain, whereas glutathionylation of C353 in the N-lobe and C374 near the ATP-binding site have few notable effects on BAK1 compared with the unmodified protein. Our results suggest an allosteric mechanism for inhibition of BAK1 by C408 S-glutathionylation, and more generally, support the notion of protein kinase S-glutathionylation as a means of redox signaling in plant cells.

A minimization principle for transition paths of maximum flux for collective variables

Considered is the construction of transition paths of conformational changes for proteins and other macromolecules, using methods that do not require the generation of dynamics trajectories. Special attention is given to the use of a reduced set of collective variables for describing such paths. A favored way to define transition paths is to seek channels through the transition state having cross sections with a high reactive flux (density of last hitting points of reactive trajectories). Given here is a formula for reactive flux that is independent of the parameterization of "collective variable space." This formula is needed for the principal curve of the reactive flux (as in the revised finite temperature string method) and for the maximum flux transition (MaxFlux) path. Additionally, a resistance functional is derived for narrow tubes, which when minimized yields a MaxFlux path. A strategy for minimization is outlined in the spirit of the string method. Finally, alternative approaches based on determining trajectories of high probability are considered, and it is observed that they yield paths that depend on the parameterization of collective variable space, except in the case of zero temperature, where such a path coincides with a MaxFlux path.

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.

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.

Structural propensities of kinase family proteins from a Potts model of residue co-variation

Understanding the conformational propensities of proteins is key to solving many problems in structural biology and biophysics. The co-variation of pairs of mutations contained in multiple sequence alignments of protein families can be used to build a Potts Hamiltonian model of the sequence patterns which accurately predicts structural contacts. This observation paves the way to develop deeper connections between evolutionary fitness landscapes of entire protein families and the corresponding free energy landscapes which determine the conformational propensities of individual proteins. Using statistical energies determined from the Potts model and an alignment of 2896 PDB structures, we predict the propensity for particular kinase family proteins to assume a "DFG-out" conformation implicated in the susceptibility of some kinases to type-II inhibitors, and validate the predictions by comparison with the observed structural propensities of the corresponding proteins and experimental binding affinity data. We decompose the statistical energies to investigate which interactions contribute the most to the conformational preference for particular sequences and the corresponding proteins. We find that interactions involving the activation loop and the C-helix and HRD motif are primarily responsible for stabilizing the DFG-in state. This work illustrates how structural free energy landscapes and fitness landscapes of proteins can be used in an integrated way, and in the context of kinase family proteins, can potentially impact therapeutic design strategies.

Conformational Selection and Induced Fit Mechanisms in the Binding of an Anticancer Drug to the c-Src Kinase

Understanding the conformational changes associated with the binding of small ligands to their biological targets is a fascinating and meaningful question in chemistry, biology and drug discovery. One of the most studied and important is the so-called "DFG-flip" of tyrosine kinases. The conserved three amino-acid DFG motif undergoes an "in to out" movement resulting in a particular inactive conformation to which "type II" kinase inhibitors, such as the anti-cancer drug Imatinib, bind. Despite many studies, the details of this prototypical conformational change are still debated. Here we combine various NMR experiments and surface plasmon resonance with enhanced sampling molecular dynamics simulations to shed light into the conformational dynamics associated with the binding of Imatinib to the proto-oncogene c-Src. We find that both conformational selection and induced fit play a role in the binding mechanism, reconciling opposing views held in the literature. Moreover, an external binding pose and local unfolding (cracking) of the aG helix are observed.

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.

DFGmodel: predicting protein kinase structures in inactive states for structure-based discovery of type-II inhibitors

Protein kinases exist in equilibrium of active and inactive states, in which the aspartate-phenylalanine-glycine motif in the catalytic domain undergoes conformational changes that are required for function. Drugs targeting protein kinases typically bind the primary ATP-binding site of an active state (type-I inhibitors) or utilize an allosteric pocket adjacent to the ATP-binding site in the inactive state (type-II inhibitors). Limited crystallographic data of protein kinases in the inactive state hampers the application of rational drug discovery methods for developing type-II inhibitors. Here, we present a computational approach to generate structural models of protein kinases in the inactive conformation. We first perform a comprehensive analysis of all protein kinase structures deposited in the Protein Data Bank. We then develop DFGmodel, a method that takes either a known structure of a kinase in the active conformation or a sequence of a kinase without a structure, to generate kinase models in the inactive conformation. Evaluation of DFGmodel's performance using various measures indicates that the inactive kinase models are accurate, exhibiting RMSD of 1.5 Å or lower. The kinase models also accurately distinguish type-II kinase inhibitors from likely nonbinders (AUC > 0.70), suggesting that they are useful for virtual screening. Finally, we demonstrate the applicability of our approach with three case studies. For example, the models are able to capture inhibitors with unintended off-target activity. Our computational approach provides a structural framework for chemical biologists to characterize kinases in the inactive state and to explore new chemical spaces with structure-based drug design.

A Gaussian network model study suggests that structural fluctuations are higher for inactive states than active states of protein kinases

Protein kinases participate extensively in cellular signalling. Using Gaussian normal mode analysis of kinases in active and diverse inactive forms, authors show that structural fluctuations are significantly higher in inactive forms and are localized in functionally sensitive sites.

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

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

Conformational Transition Pathways of Epidermal Growth Factor Receptor Kinase Domain from Multiple Molecular Dynamics Simulations and Bayesian Clustering

The epidermal growth factor receptor (EGFR) is aberrantly activated in various cancer cells and an important target for cancer treatment. Deep understanding of EGFR conformational changes between the active and inactive states is of pharmaceutical interest. Here we present a strategy combining multiply targeted molecular dynamics simulations, unbiased molecular dynamics simulations, and Bayesian clustering to investigate transition pathways during the activation/inactivation process of EGFR kinase domain. Two distinct pathways between the active and inactive forms are designed, explored, and compared. Based on Bayesian clustering and rough two-dimensional free energy surfaces, the energy-favorable pathway is recognized, though DFG-flip happens in both pathways. In addition, another pathway with different intermediate states appears in our simulations. Comparison of distinct pathways also indicates that disruption of the Lys745-Glu762 interaction is critically important in DFG-flip while movement of the A-loop significantly facilitates the conformational change. Our simulations yield new insights into EGFR conformational transitions. Moreover, our results verify that this approach is valid and efficient in sampling of protein conformational changes and comparison of distinct pathways.

Modeling conformational transitions in kinases by molecular dynamics simulations: achievements, difficulties, and open challenges

Protein kinases work because their flexibility allows to continuously switch from inactive to active form. Despite the large number of structures experimentally determined in such states, the mechanism of their conformational transitions as well as the transition pathways are not easily to capture. In this regard, computational methods can help to shed light on such an issue. However, due to the intrinsic sampling limitations, much efforts have been done to model in a realistic way the conformational changes occurring in protein kinases. In this review we will address the principal biological achievements and structural aspects in studying kinases conformational transitions and will focus on the main challenges related to computational approaches such as molecular modeling and MD simulations.

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.

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.

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.