Towards a Molecular Understanding of the Link between Imatinib Resistance and Kinase Conformational Dynamics

Unraveling Extremely Damaging IRAK4 Variants and Their Potential Implications for IRAK4 Inhibitor Efficacy

Interleukin-1-receptor-associated kinase 4 (IRAK4) possesses a crucial function in the toll-like receptor (TLR) signaling pathway, and the dysfunction of this molecule could lead to various infectious and immune-related diseases in addition to cancers. IRAK4 genetic variants have been linked to various types of diseases. Therefore, we conducted a comprehensive analysis to recognize the missense variants with the most damaging impacts on IRAK4 with the employment of diverse bioinformatics tools to study single-nucleotide polymorphisms' effects on function, stability, secondary structures, and 3D structure. The residues' location on the protein domain and their conservation status were investigated as well. Moreover, docking tools along with structural biology were engaged in analyzing the SNPs' effects on one of the developed IRAK4 inhibitors. By analyzing IRAK4 gene SNPs, the analysis distinguished ten variants as the most detrimental missense variants. All variants were situated in highly conserved positions on an important protein domain. L318S and L318F mutations were linked to changes in IRAK4 secondary structures. Eight SNPs were revealed to have a decreasing effect on the stability of IRAK4 via both I-Mutant 2.0 and Mu-Pro tools, while Mu-Pro tool identified a decreasing effect for the G198E SNP. In addition, detrimental effects on the 3D structure of IRAK4 were also discovered for the selected variants. Molecular modeling studies highlighted the detrimental impact of these identified SNP mutant residues on the druggability of the IRAK4 ATP-binding site towards the known target inhibitor, HG-12-6, as compared to the native protein. The loss of important ligand residue-wise contacts, altered protein global flexibility, increased steric clashes, and even electronic penalties at the ligand-binding site interfaces were all suggested to be associated with SNP models for hampering the HG-12-6 affinity towards IRAK4 target protein. This given model lays the foundation for the better prediction of various disorders relevant to IRAK4 malfunction and sheds light on the impact of deleterious IRAK4 variants on IRAK4 inhibitor efficacy.

Genetic alterations in the BCR-ABL1 fusion gene related to imatinib resistance in chronic myeloid leukemia

Use of the potent tyrosine kinase inhibitor imatinib as the first-line treatment in chronic myeloid leukemia (CML) has decreased mortality from 20% to 2%. Approximately 30% of CML patients experience imatinib resistance, however, largely because of point mutations in the kinase domain of the BCR-ABL1 fusion gene. The aim of this study was to use next-generation sequencing (NGS) to identify mutations related to imatinib resistance. The study included 22 patients diagnosed with CML and experiencing no clinical response to imatinib. Total RNA was used for cDNA synthesis, with amplification of a fragment encompassing the BCR-ABL1 kinase domain using a nested-PCR approach. Sanger and NGS were applied to detect genetic alterations. HaplotypeCaller was used for variant calling, and STAR-Fusion software was applied for fusion breakpoint identification. After sequencing analysis, F311I, F317L, and E450K mutations were detected respectively in three different participants, and in another two patients, single nucleotide variants in BCR (rs9608100, rs140506, rs16802) and ABL1 (rs35011138) were detected. Eleven patients carried e14a2 transcripts, nine had e13a2 transcripts, and both transcripts were identified in one patient. One patient had co-expression of e14a2 and e14a8 transcripts. The results identify candidate single nucleotide variants and co-expressed BCR-ABL1 transcripts in cellular resistance to imatinib.

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.

Evaluation of residue variability in a conformation-specific context and during evolutionary sequence reconstruction narrows drug resistance selection in Abl1 tyrosine kinase

Diseases with readily available therapies may eventually prevail against the specific treatment by the acquisition of resistance. The constitutively active Abl1 tyrosine kinase known to cause chronic myeloid leukemia is an example, where patients may experience relapse after small inhibitor drug treatment. Mutations in the Abl1 tyrosine kinase domain (Abl1-KD) are a critical source of resistance and their emergence depends on the conformational states that have been observed experimentally: the inactive state, the active state, and the intermediate inactive state that resembles Src kinase. Understanding how resistant positions and amino acid identities are determined by selection pressure during drug treatment is necessary to improve future drug development or treatment decisions. We carry out in silico site-saturation mutagenesis over the Abl1-KD structure in a conformational context to evaluate the in situ and conformational stability energy upon mutation. Out of the 11 studied resistant positions, we determined that 7 of the resistant mutations favored the active conformation of Abl1-KD with respect to the inactive state. When, instead, the sequence optimization was modeled simultaneously at resistant positions, we recovered five known resistant mutations in the active conformation. These results suggested that the Abl1 resistance mechanism targeted substitutions that favored the active conformation. Further sequence variability, explored by ancestral reconstruction in Abl1-KD, showed that neutral genetic drift, with respect to amino acid variability, was specifically diminished in the resistant positions. Since resistant mutations are susceptible to chance with a certain probability of fixation, combining methodologies outlined here may narrow and limit the available sequence space for resistance to emerge, resulting in more robust therapeutic treatments over time.

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.

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

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

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.

Computer Simulations of the Dissociation Mechanism of Gleevec from Abl Kinase with Milestoning

Gleevec (a.k.a., imatinib) is an important anticancer (e.g., chronic myeloid leukemia) chemotherapeutic drug due to its inhibitory interaction with the Abl kinase. Here, we use atomically detailed simulations within the Milestoning framework to study the molecular dissociation mechanism of Gleevec from Abl kinase. We compute the dissociation free energy profile, the mean first passage time for unbinding, and explore the transition state ensemble of conformations. The milestones form a multidimensional network with average connectivity of about 2.93, which is significantly higher than the connectivity for a one-dimensional reaction coordinate. The free energy barrier for Gleevec dissociation is estimated to be ∼10 kcal/mol, and the exit time is ∼55 ms. We examined the transition state conformations using both, the committor and transition function. We show that near the transition state the highly conserved salt bridge K217 and E286 is transiently broken. Together with the calculated free energy profile, these calculations can advance the understanding of the molecular interaction mechanisms between Gleevec and Abl kinase and play a role in future drug design and optimization studies.

Loop Dynamics and Enzyme Catalysis in Protein Tyrosine Phosphatases

Protein tyrosine phosphatases (PTPs) play an important role in cellular signaling and have been implicated in human cancers, diabetes, and obesity. Despite shared catalytic mechanisms and transition states for the chemical steps of catalysis, catalytic rates within the PTP family vary over several orders of magnitude. These rate differences have been implied to arise from differing conformational dynamics of the closure of a protein loop, the WPD-loop, which carries a catalytically critical residue. The present work reports computational studies of the human protein tyrosine phosphatase 1B (PTP1B) and YopH from Yersinia pestis, for which NMR has demonstrated a link between their respective rates of WPD-loop motion and catalysis rates, which differ by an order of magnitude. We have performed detailed structural analysis, both conventional and enhanced sampling simulations of their loop dynamics, as well as empirical valence bond simulations of the chemical step of catalysis. These analyses revealed the key residues and structural features responsible for these differences, as well as the residues and pathways that facilitate allosteric communication in these enzymes. Curiously, our wild-type YopH simulations also identify a catalytically incompetent hyper-open conformation of its WPD-loop, sampled as a rare event, previously only experimentally observed in YopH-based chimeras. The effect of differences within the WPD-loop and its neighboring loops on the modulation of loop dynamics, as revealed in this work, may provide a facile means for the family of PTP enzymes to respond to environmental changes and regulate their catalytic activities.

Identification of tyrosine kinase inhibitors that halt Plasmodium falciparum parasitemia

Although current malaria therapies inhibit pathways encoded in the parasite’s genome, we have looked for anti-malaria drugs that can target an erythrocyte component because development of drug resistance might be suppressed if the parasite cannot mutate the drug’s target. In search for such erythrocyte targets, we noted that human erythrocytes express tyrosine kinases, whereas the Plasmodium falciparum genome encodes no obvious tyrosine kinases. We therefore screened a library of tyrosine kinase inhibitors from Eli Lilly and Co. in a search for inhibitors with possible antimalarial activity. We report that although most tyrosine kinase inhibitors exerted no effect on parasite survival, a subset of tyrosine kinase inhibitors displayed potent anti-malarial activity. Moreover, all inhibitors found to block tyrosine phosphorylation of band 3 specifically suppressed P. falciparum survival at the parasite egress stage of its intra-erythrocyte life cycle. Conversely, tyrosine kinase inhibitors that failed to block band 3 tyrosine phosphorylation but still terminated the parasitemia were observed to halt parasite proliferation at other stages of the parasite’s life cycle. Taken together these results suggest that certain erythrocyte tyrosine kinases may be important to P. falciparum maturation and that inhibitors that block these kinases may contribute to novel therapies for P. falciparum malaria.

Diversity of Long-Lived Intermediates along the Binding Pathway of Imatinib to Abl Kinase Revealed by MD Simulations

Imatinib, a drug used for the treatment of chronic myeloid leukemia and other cancers, works by blocking the catalytic site of pathological constitutively active Abl kinase. While the binding pose is known from X-ray crystallography, the different steps leading to the formation of the complex are not well understood. The results from extensive molecular dynamics simulations show that imatinib can primarily exit the known crystallographic binding pose through the cleft of the binding site or by sliding under the αC helix. Once displaced from the crystallographic binding pose, imatinib becomes trapped in intermediate states. These intermediates are characterized by a high diversity of ligand orientations and conformations, and relaxation timescales within this region may exceed 3-4 ms. Analysis indicates that the metastable intermediate states should be spectroscopically indistinguishable from the crystallographic binding pose, in agreement with tryptophan stopped-flow fluorescence experiments.

TRK xDFG Mutations Trigger a Sensitivity Switch from Type I to II Kinase Inhibitors

On-target resistance to next-generation TRK inhibitors in TRK fusion-positive cancers is largely uncharacterized. In patients with these tumors, we found that TRK xDFG mutations confer resistance to type I next-generation TRK inhibitors designed to maintain potency against several kinase domain mutations. Computational modeling and biochemical assays showed that TRKA^G667 and TRKC^G696 xDFG substitutions reduce drug binding by generating steric hindrance. Concurrently, these mutations stabilize the inactive (DFG-out) conformations of the kinases, thus sensitizing these kinases to type II TRK inhibitors. Consistently, type II inhibitors impede the growth and TRK-mediated signaling of xDFG-mutant isogenic and patient-derived models. Collectively, these data demonstrate that adaptive conformational resistance can be abrogated by shifting kinase engagement modes. Given the prior identification of paralogous xDFG resistance mutations in other oncogene-addicted cancers, these findings provide insights into rational type II drug design by leveraging inhibitor class affinity switching to address recalcitrant resistant alterations. SIGNIFICANCE: In TRK fusion-positive cancers, TRK xDFG substitutions represent a shared liability for type I TRK inhibitors. In contrast, they represent a potential biomarker of type II TRK inhibitor activity. As all currently available type II agents are multikinase inhibitors, rational drug design should focus on selective type II inhibitor creation.This article is highlighted in the In This Issue feature, p. 1.

Temperature does matter-an additional dimension in kinase inhibitor development

Kinase inhibitors are a major focus in drug development. Recent work shows that subtle temperature changes in the physiologically relevant temperature range can dramatically alter kinase activity and specificity. We argue that temperature is an essential factor that should be considered in inhibitor screening campaigns. In many cases, high-throughput screening is performed at room temperature or 30 °C, which may lead to many false positives and false negatives when evaluating potential inhibitors in the physiological temperature range. As one example, we discuss a new antimalaria compound that inhibits the highly temperature-sensitive kinase CLK3 (CDC2-like kinase 3) from Plasmodium falciparum.

Cumulative mechanism of several major imatinib-resistant mutations in Abl kinase

Despite the outstanding success of the cancer drug imatinib, one obstacle in prolonged treatment is the emergence of resistance mutations within the kinase domain of its target, Abl. We noticed that many patient-resistance mutations occur in the dynamic hot spots recently identified to be responsible for imatinib's high selectivity toward Abl. In this study, we provide an experimental analysis of the mechanism underlying drug resistance for three major resistance mutations (G250E, Y253F, and F317L). Our data settle controversies, revealing unexpected resistance mechanisms. The mutations alter the energy landscape of Abl in complex ways: increased kinase activity, altered affinity, and cooperativity for the substrates, and, surprisingly, only a modestly decreased imatinib affinity. Only under cellular adenosine triphosphate (ATP) concentrations, these changes cumulate in an order of magnitude increase in imatinib's half-maximal inhibitory concentration (IC50). These results highlight the importance of characterizing energy landscapes of targets and its changes by drug binding and by resistance mutations developed by patients.

Combining Machine Learning and Enhanced Sampling Techniques for Efficient and Accurate Calculation of Absolute Binding Free Energies

Calculating absolute binding free energies is challenging and important. In this paper, we test some recently developed metadynamics-based methods and develop a new combination with a Hamiltonian replica-exchange approach. The methods were tested on 18 chemically diverse ligands with a wide range of different binding affinities to a complex target; namely, human soluble epoxide hydrolase. The results suggest that metadynamics with a funnel-shaped restraint can be used to calculate, in a computationally affordable and relatively accurate way, the absolute binding free energy for small fragments. When used in combination with an optimal pathlike variable obtained using machine learning or with the Hamiltonian replica-exchange algorithm SWISH, this method can achieve reasonably accurate results for increasingly complex ligands, with a good balance of computational cost and speed. An additional benefit of using the combination of metadynamics and SWISH is that it also provides useful information about the role of water in the binding mechanism.

Revealing Acquired Resistance Mechanisms of Kinase-Targeted Drugs Using an on-the-Fly, Function-Site Interaction Fingerprint Approach

Although kinase-targeted drugs have achieved significant clinical success, they are frequently subject to the limitations of drug resistance, which has become a primary vulnerability to targeted drug therapy. Therefore, deciphering resistance mechanisms is an important step in designing more efficacious, antiresistant drugs. Here we studied two FDA-approved kinase drugs: Crizotinib and Ceritinib, which are first- and second-generation anaplastic lymphoma kinase (ALK) targeted inhibitors, to unravel drug-resistance mechanisms. We used an on-the-fly, function-site interaction fingerprint (on-the-fly Fs-IFP) approach, combining binding free-energy surface calculations with the Fs-IFPs. Establishing the potentials of mean force and monitoring the atomic-scale protein-ligand interactions, before and after L1196M-induced drug resistance, revealed insights into drug-resistance/antiresistant mechanisms. Crizotinib prefers to bind the wild-type ALK kinase domain, whereas Ceritinib binds more favorably to the mutated ALK kinase domain, in agreement with experimental results. We determined that ALK kinase-drug interactions in the region of the front pocket are associated with drug resistance. Additionally, we find that the L1196M mutation does not simply alter the binding modes of inhibitors but also affects the flexibility of the entire ALK kinase domain. Our work provides an understanding of the mechanisms of ALK drug resistance, confirms the usefulness of the on-the-fly Fs-IFP approach, and provides a practical paradigm to study drug-resistance mechanisms in prospective drug discovery.

Dynamics-function relationship in the catalytic domains of N-terminal acetyltransferases

N-terminal acetyltransferases (NATs) belong to the superfamily of acetyltransferases. They are enzymes catalysing the transfer of an acetyl group from acetyl coenzyme A to the N-terminus of polypeptide chains. N-terminal acetylation is one of the most common protein modifications. To date, not much is known on the molecular basis for the exclusive substrate specificity of NATs. All NATs share a common fold called GNAT. A characteristic of NATs is the β6β7 hairpin loop covering the active site and forming with the α1α2 loop a narrow tunnel surrounding the catalytic site in which cofactor and polypeptide meet and exchange an acetyl group. We investigated the dynamics-function relationships of all available structures of NATs covering the three domains of Life. Using an elastic network model and normal mode analysis, we found a common dynamics pattern conserved through the GNAT fold; a rigid V-shaped groove formed by the β4 and β5 strands and splitting the fold in two dynamical subdomains. Loops α1α2, β3β4 and β6β7 all show clear displacements in the low frequency normal modes. We characterized the mobility of the loops and show that even limited conformational changes of the loops along the low-frequency modes are able to significantly change the size and shape of the ligand binding sites. Based on the fact that these movements are present in most low-frequency modes, and common to all NATs, we suggest that the α1α2 and β6β7 loops may regulate ligand uptake and the release of the acetylated polypeptide.

Enhanced Molecular Dynamics Simulations of Intrinsically Disordered Proteins

Molecular dynamics simulations represent a powerful tool to gain insights into structural and dynamical features of biomolecular systems. Nevertheless, their recognized limitation in terms of achievable timescales becomes particularly severe when dealing with slow processes. In such cases, the employment of enhanced sampling methods, which allow accelerating the characterization of rare events in a timeframe consistent with conventional computational resources, results as crucial. In particular, such advanced techniques have proven highly valuable in the context of protein folding and, specifically, to explore the conformational ensemble spanned by intrinsically disordered proteins (IDPs). Here, we describe how to set up molecular dynamics simulations with one of these enhanced sampling approaches (namely, Parallel Tempering Metadynamics in the Well-Tempered Ensemble) using the N_TAIL peptide as a test case.

Interleukin-1β drives NEDD8 nuclear-to-cytoplasmic translocation, fostering parkin activation via NEDD8 binding to the P-ubiquitin activating site

Background

Neuroinflammation, typified by elevated levels of interleukin-1 (IL-1) α and β, and deficits in proteostasis, characterized by accumulation of polyubiquitinated proteins and other aggregates, are associated with neurodegenerative disease independently and through interactions of the two phenomena. We investigated the influence of IL-1β on ubiquitination via its impact on activation of the E3 ligase parkin by either phosphorylated ubiquitin (P-Ub) or NEDD8.

Methods

Immunohistochemistry and Proximity Ligation Assay were used to assess colocalization of parkin with P-tau or NEDD8 in hippocampus from Alzheimer patients (AD) and controls. IL-1β effects on PINK1, P-Ub, parkin, P-parkin, and GSK3β—as well as phosphorylation of parkin by GSK3β—were assessed in cell cultures by western immunoblot, using two inhibitors and siRNA knockdown to suppress GSK3β. Computer modeling characterized the binding and the effects of P-Ub and NEDD8 on parkin. IL-1α, IL-1β, and parkin gene expression was assessed by RT-PCR in brains of 2- and 17-month-old PD-APP mice and wild-type littermates.

Results

IL-1α, IL-1β, and parkin mRNA levels were higher in PD-APP mice compared with wild-type littermates, and IL-1α-laden glia surrounded parkin- and P-tau-laden neurons in human AD. Such neurons showed a nuclear-to-cytoplasmic translocation of NEDD8 that was mimicked in IL-1β-treated primary neuronal cultures. These cultures also showed higher parkin levels and GSK3β-induced parkin phosphorylation; PINK1 levels were suppressed. In silico simulation predicted that binding of either P-Ub or NEDD8 at a singular position on parkin opens the UBL domain, exposing Ser₆₅ for parkin activation.

Conclusions

The promotion of parkin- and NEDD8-mediated ubiquitination by IL-1β is consistent with an acute neuroprotective role. However, accumulations of P-tau and P-Ub and other elements of proteostasis, such as translocated NEDD8, in AD and in response to IL-1β suggest either over-stimulation or a proteostatic failure that may result from chronic IL-1β elevation, easily envisioned considering its early induction in Down’s syndrome and mild cognitive impairment. The findings further link autophagy and neuroinflammation, two important aspects of AD pathogenesis, which have previously been only loosely related.

Conformational modifications induced by internal tandem duplications on the FLT3 kinase and juxtamembrane domains

The aberrant expression of FLT3 tyrosine kinase is associated primarily with acute myeloid leukaemia. This blood malignancy is often related to the onset of internal tandem duplications (ITDs) in the native sequence of the protein. The ITDs occur mainly in the juxtamembrane domain of the protein and alter the normal activity of the enzyme. In this work, we have studied the native form of FLT3 and six mutants by molecular dynamics simulations. The catalytic activity of FLT3 is exerted by the tyrosine kinase domain (KD) and regulated by the juxtamembrane (JM) domain. Analysis of the dynamics of these two domains have shown that the introduction of ITDs in the JM domain alters both structural and dynamic parameters. The presence of ITDs allowed the protein to span a larger portion of the conformational space, particularly in the JM domain and the activation loop. The FLT3 mutants were found to adopt more stable configurations than the native enzyme. This was due to the different arrangements assumed by the JM domain. Larger fluctuations of the activation loop were found in four of the six mutants. In the native FLT3, the key residue Tyr572 is involved in a strong and stable interaction with an ion pair. This interaction, which is thought to keep the JM in place hence regulating the activity of the enzyme, was found to break in all FLT3 mutants.

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.

Ligand-Binding Calculations with Metadynamics

All-atom molecular dynamics simulations can capture the dynamic degrees of freedom that characterize molecular recognition, the knowledge of which constitutes the cornerstone of rational approaches to drug design and optimization. In particular, enhanced sampling algorithms, such as metadynamics, are powerful tools to dramatically reduce the computational cost required for a mechanistic description of the binding process. Here, we describe the essential details characterizing these simulation strategies, focusing on the critical step of identifying suitable reaction coordinates, as well as on the different analysis algorithms to estimate binding affinity and residence times. We conclude with a survey of published applications that provides explicit examples of successful simulations for several targets.

Activation and Inactivation of the FLT3 Kinase: Pathway Intermediates and the Free Energy of Transition

The aberrant expression of kinases is often associated with pathologies such as cancer and autoimmune diseases. Like other types of enzymes, kinases can adopt active and inactive states, where a shift toward more stable active state often leads to disease. Dozens of kinase inhibitors are, therefore, used as drugs. Most of these bind to either the inactive or active state. In this work, we study the transitions between these two states in FLT3, an important drug target in leukemias. Kinases are composed of two lobes (N- and C-terminal lobes) with the catalytic site in-between. Through projection of the largest motions obtained through molecular dynamics (MD) simulations, we show that each of the end-states (active or inactive) already possess the ability for transition as the two lobes rotate which initiates the transition. A targeted simulation approach known as essential dynamics sampling (EDS) was used to speed up the transition between the two protein states. Coupling the EDS to implicit-solvent MD was performed to estimate the free energy barriers of the transitions. The activation energies were found in good agreement with previous estimates obtained for other kinases. Finally, we identified FLT3 intermediates that assumed configurations that resemble that of the c-Src nonreceptor tyrosine kinase. The intermediates show better binding to the drug ponatinib than c-Src and the inactive state of FLT3. This suggests that targeting intermediate states can be used to explain the drug-binding patterns of kinases and for rational drug design.

Coevolutionary Landscape of Kinase Family Proteins: Sequence Probabilities and Functional Motifs

The protein kinase catalytic domain is one of the most abundant domains across all branches of life. Although kinases share a common core function of phosphoryl-transfer, they also have wide functional diversity and play varied roles in cell signaling networks, and for this reason are implicated in a number of human diseases. This functional diversity is primarily achieved through sequence variation, and uncovering the sequence-function relationships for the kinase family is a major challenge. In this study we use a statistical inference technique inspired by statistical physics, which builds a coevolutionary "Potts" Hamiltonian model of sequence variation in a protein family. We show how this model has sufficient power to predict the probability of specific subsequences in the highly diverged kinase family, which we verify by comparing the model's predictions with experimental observations in the Uniprot database. We show that the pairwise (residue-residue) interaction terms of the statistical model are necessary and sufficient to capture higher-than-pairwise mutation patterns of natural kinase sequences. We observe that previously identified functional sets of residues have much stronger correlated interaction scores than are typical.

ABL1 tyrosine kinase domain mutations in chronic myeloid leukemia treatment resistance

The development of mutations in the BCR-ABL1 fusion gene transcript causes resistance to tyrosine kinase inhibitors (TKIs) based therapy in chronic myeloid leukemia (CML). Thereby, screening for BCR-ABL1 mutations is advised especially in patients undergoing poor response to treatment. In the current study the authors investigated 43 patients with CML that failed or had suboptimal response to TKIs treatment. Blood samples were collected from patients that were treated with TKIs. The analysis of genetic mutations was performed using a semi-nested PCR assay, followed by Sanger sequencing. The analysis revealed 15 mutations (32.55%): 14 point mutations and an exon 7 deletion. In roughly 30% of cases, mutations in the BCR-ABL1 fusion gene are common causes for treatment resistance.

Structure and Dynamics of the EGF Receptor as Revealed by Experiments and Simulations and Its Relevance to Non-Small Cell Lung Cancer

The epidermal growth factor receptor (EGFR) is historically the prototypical receptor tyrosine kinase, being the first cloned and the first where the importance of ligand-induced dimer activation was ascertained. However, many years of structure determination has shown that EGFR is not completely understood. One challenge is that the many structure fragments stored at the PDB only provide a partial view because full-length proteins are flexible entities and dynamics play a key role in their functionality. Another challenge is the shortage of high-resolution data on functionally important higher-order complexes. Still, the interest in the structure/function relationships of EGFR remains unabated because of the crucial role played by oncogenic EGFR mutants in driving non-small cell lung cancer (NSCLC). Despite targeted therapies against EGFR setting a milestone in the treatment of this disease, ubiquitous drug resistance inevitably emerges after one year or so of treatment. The magnitude of the challenge has inspired novel strategies. Among these, the combination of multi-disciplinary experiments and molecular dynamic (MD) simulations have been pivotal in revealing the basic nature of EGFR monomers, dimers and multimers, and the structure-function relationships that underpin the mechanisms by which EGFR dysregulation contributes to the onset of NSCLC and resistance to treatment.

2-Aminothiazole Derivatives as Selective Allosteric Modulators of the Protein Kinase CK2. 2. Structure-Based Optimization and Investigation of Effects Specific to the Allosteric Mode of Action

Protein CK2 has gained much interest as an anticancer drug target in the past decade. We had previously described the identification of a new allosteric site on the catalytic α-subunit, along with first small molecule ligands based on the 4-(4-phenylthiazol-2-ylamino)benzoic acid scaffold. In the present work, structure optimizations guided by a binding model led to the identification of the lead compound 2-hydroxy-4-((4-(naphthalen-2-yl)thiazol-2-yl)amino)benzoic acid (27), showing a submicromolar potency against purified CK2α (IC₅₀ = 0.6 μM). Furthermore, 27 induced apoptosis and cell death in 786-O renal cell carcinoma cells (EC₅₀ = 5 μM) and inhibited STAT3 activation even more potently than the ATP-competitive drug candidate CX-4945 (EC₅₀ of 1.6 μM vs 5.3 μM). Notably, the potencies of our allosteric ligands to inhibit CK2 varied depending on the individual substrate. Altogether, the novel allosteric pocket was proved a druggable site, offering an excellent perspective to develop efficient and selective allosteric CK2 inhibitors.

Dynamics fingerprints of active conformers of epidermal growth factor receptor kinase

Epidermal growth factor receptor (EGFR) is a prototypical cell-surface receptor that plays a key role in the regulation of cellular signaling, proliferation and differentiation. Mutations of its kinase domain have been associated with the development of a variety of cancers and, therefore, it has been the target of drug design. Single amino acid substitutions (SASs) in this domain have been proven to alter the equilibrium of pre-existing conformer populations. Despite the advances in structural descriptions of its so-called active and inactive conformations, the associated dynamics aspects that characterize them have not been thoroughly studied yet. As the dynamic behaviors and molecular motions of proteins are important for a complete understanding of their structure-function relationships we present a novel procedure, using (or based on) normal mode analysis, to identify the collective dynamics shared among different conformers in EGFR kinase. The method allows the comparison of patterns of low-frequency vibrational modes defining representative directions of motions. Our procedure is able to emphasize the main similarities and differences between the collective dynamics of different conformers. In the case of EGFR kinase, two representative directions of motions have been found as dynamics fingerprints of the active conformers. Protein motion along both directions reveals to have a significant impact on the cavity volume of the main pocket of the active site. Otherwise, the inactive conformers exhibit a more heterogeneous distribution of collective motions. © 2018 Wiley Periodicals, Inc.

Remarkable similarity in Plasmodium falciparum and Plasmodium vivax geranylgeranyl diphosphate synthase dynamics and its implication for antimalarial drug design

Malaria, mainly caused by Plasmodium falciparum and Plasmodium vivax, has been a growing cause of morbidity and mortality. P. falciparum is more lethal than is P. vivax, but there is a vital need for effective drugs against both species. Geranylgeranyl diphosphate synthase (GGPPS) is an enzyme involved in the biosynthesis of quinones and in protein prenylation and has been proposed to be a malaria drug target. However, the structure of P. falciparumGGPPS (PfGGPPS) has not been determined, due to difficulties in crystallization. Here, we created a PfGGPPS model using the homologous P.vivaxGGPPS X-ray structure as a template. We simulated the modeled PfGGPPS as well as PvGGPPS using conventional and Gaussian accelerated molecular dynamics in both apo- and GGPP-bound states. The MD simulations revealed a striking similarity in the dynamics of both enzymes with loop 9-10 controlling access to the active site. We also found that GGPP stabilizes PfGGPPS and PvGGPPS into closed conformations and via similar mechanisms. Shape-based analysis of the binding sites throughout the simulations suggests that the two enzymes will be readily targeted by the same inhibitors. Finally, we produced three MD-validated conformations of PfGGPPS to be used in future virtual screenings for potential new antimalarial drugs acting on both PvGGPPS and PfGGPPS.

Role of Molecular Interactions and Protein Rearrangement in the Dissociation Kinetics of p38α MAP Kinase Type-I/II/III Inhibitors

Understanding the governing factors of fast or slow inhibitor binding/unbinding assists in developing drugs with preferred kinetic properties. For inhibitors with the same binding affinity targeting different binding sites of the same protein, the kinetic behavior can profoundly differ. In this study, we investigated unbinding kinetics and mechanisms of fast (type-I) and slow (type-II/III) binders of p38α mitogen-activated protein kinase, where the crystal structures showed that type-I and type-II/III inhibitors bind to pockets with different conformations of the Asp-Phe-Gly (DFG) motif. The work used methods that combine conventional molecular dynamics (MD), accelerated molecular dynamics (AMD) simulations, and the newly developed pathway search guided by internal motions (PSIM) method to find dissociation pathways. The study focuses on revealing key interactions and molecular rearrangements that hinder ligand dissociation by using umbrella sampling and post-MD processing to examine changes in free energy during ligand unbinding. As anticipated, the initial dissociation steps all require breaking interactions that appeared in crystal structures of the bound complexes. Interestingly, for type-I inhibitors such as SB2, p38α keeps barrier-free conformational fluctuation in the ligand-bound complex and during ligand dissociation. In contrast, with a type-II/III inhibitor such as BIRB796, with the rearrangements of p38α in its bound state, ligand unbinding features energetically unfavorable protein-ligand concerted movement. Our results also show that the type-II/III inhibitors preferred dissociation pathways through the allosteric channel, which is consistent with an existing publication. The study suggests that the level of required protein rearrangement is one major determining factor of drug binding kinetics in p38α systems, providing useful information for development of inhibitors.

Predicting the Conformational Variability of Abl Tyrosine Kinase using Molecular Dynamics Simulations and Markov State Models

Understanding protein conformational variability remains a challenge in drug discovery. The issue arises in protein kinases, whose multiple conformational states can affect the binding of small-molecule inhibitors. To overcome this challenge, we propose a comprehensive computational framework based on Markov state models (MSMs). Our framework integrates the information from explicit-solvent molecular dynamics simulations to accurately rank-order the accessible conformational variants of a target protein. We tested the methodology using Abl kinase with a reference and blind-test set. Only half of the Abl conformational variants discovered by our approach are present in the disclosed X-ray structures. The approach successfully identified a protein conformational state not previously observed in public structures but evident in a retrospective analysis of Lilly in-house structures: the X-ray structure of Abl with WHI-P154. Using a MSM-derived model, the free energy landscape and kinetic profile of Abl was analyzed in detail highlighting opportunities for targeting the unique metastable states.

A Catalytically Disabled Double Mutant of Src Tyrosine Kinase Can Be Stabilized into an Active-Like Conformation

Tyrosine kinases are enzymes playing a critical role in cellular signaling. Molecular dynamics umbrella sampling potential of mean force computations are used to quantify the impact of activating and inactivating mutations of c-Src kinase. The potential of mean force computations predict that a specific double mutant can stabilize c-Src kinase into an active-like conformation while disabling the binding of ATP in the catalytic active site. The active-like conformational equilibrium of this catalytically dead kinase is affected by a hydrophobic unit that connects to the hydrophobic spine network via the C-helix. The αC-helix plays a crucial role in integrating the hydrophobic residues, making it a hub for allosteric regulation of kinase activity and the active conformation. The computational free-energy landscapes reported here illustrate novel design principles focusing on the important role of the hydrophobic spines. The relative stability of the spines could be exploited in future efforts to artificially engineer active-like but catalytically dead forms of protein kinases.

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.

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.

An Efficient Metadynamics-Based Protocol To Model the Binding Affinity and the Transition State Ensemble of G-Protein-Coupled Receptor Ligands

A generally applicable metadynamics scheme for predicting the free energy profile of ligand binding to G-protein-coupled receptors (GPCRs) is described. A common and effective collective variable (CV) has been defined using the ideally placed and highly conserved Trp6.48 as a reference point for ligand-GPCR distance measurement and the common orientation of GPCRs in the cell membrane. Using this single CV together with well-tempered multiple-walker metadynamics with a funnel-like boundary allows an efficient exploration of the entire ligand binding path from the extracellular medium to the orthosteric binding site, including vestibule and intermediate sites. The protocol can be used with X-ray structures or high-quality homology models (based on a high-quality template and after thorough refinement) for the receptor and is universally applicable to agonists, antagonists, and partial and reverse agonists. The root-mean-square error (RMSE) in predicted binding free energies for 12 diverse ligands in five receptors (a total of 23 data points) is surprisingly small (less than 1 kcal mol^-1). The RMSEs for simulations that use receptor X-ray structures and homology models are very similar.

Changes in the free-energy landscape of p38α MAP kinase through its canonical activation and binding events as studied by enhanced molecular dynamics simulations

p38α is a Ser/Thr protein kinase involved in a variety of cellular processes and pathological conditions, which makes it a promising pharmacological target. Although the activity of the enzyme is highly regulated, its molecular mechanism of activation remains largely unexplained, even after decades of research. By using state-of-the-art molecular dynamics simulations, we decipher the key elements of the complex molecular mechanism refined by evolution to allow for a fine tuning of p38α kinase activity. Our study describes for the first time the molecular effects of different regulators of the enzymatic activity, and provides an integrative picture of the activation mechanism that explains the seemingly contradictory X-ray and NMR data.

DOI:http://dx.doi.org/10.7554/eLife.22175.001

The opening/closure of the P-loop and hinge of BCR-ABL1 decodes the low/high bioactivities of dasatinib and axitinib

The open/closed conformations reveal the low/high bioactivities of the ligands.

Insight on Mutation-Induced Resistance from Molecular Dynamics Simulations of the Native and Mutated CSF-1R and KIT

The receptors tyrosine kinases (RTKs) for the colony stimulating factor-1, CSF-1R, and for the stem cell factor, SCFR or KIT, are important mediators of signal transduction. The abnormal function of these receptors, promoted by gain-of-function mutations, leads to their constitutive activation, associated with cancer or other proliferative diseases. A secondary effect of the mutations is the alteration of receptors' sensitivity to tyrosine kinase inhibitors, compromising effectiveness of these molecules in clinical treatment. In particular, the mutation V560G in KIT increases its sensitivity to Imatinib, while the D816V in KIT, and D802V in CSF-1R, triggers resistance to the drug. We analyzed the Imatinib binding affinity to the native and mutated KIT (mutations V560G, S628N and D816V) and CSF-1R (mutation D802V) by using molecular dynamics simulations and energy calculations of Imatinib•target complexes. Further, we evaluated the sensitivity of the studied KIT receptors to Imatinib by measuring the inhibition of KIT phosphorylation. Our study showed that (i) the binding free energy of Imatinib to the targets is highly correlated with their experimentally measured sensitivity; (ii) the electrostatic interactions are a decisive factor affecting the binding energy; (iii) the most deleterious impact to the Imatinib sensitivity is promoted by D802V (CSF-1R) and D816V (KIT) mutations; (iv) the role of the juxtamembrane region, JMR, in the imatinib binding is accessory. These findings contribute to a better description of the mutation-induced effects alternating the targets sensitivity to Imatinib.

Changes in the folding landscape of the WW domain provide a molecular mechanism for an inherited genetic syndrome

WW domains are small domains present in many human proteins with a wide array of functions and acting through the recognition of proline-rich sequences. The WW domain belonging to polyglutamine tract-binding protein 1 (PQBP1) is of particular interest due to its direct involvement in several X chromosome-linked intellectual disabilities, including Golabi-Ito-Hall (GIH) syndrome, where a single point mutation (Y65C) correlates with the development of the disease. The mutant cannot bind to its natural ligand WBP11, which regulates mRNA processing. In this work we use high-field high-resolution NMR and enhanced sampling molecular dynamics simulations to gain insight into the molecular causes the disease. We find that the wild type protein is partially unfolded exchanging among multiple beta-strand-like conformations in solution. The Y65C mutation further destabilizes the residual fold and primes the protein for the formation of a disulphide bridge, which could be at the origin of the loss of function.

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.

An Allosteric Cross-Talk Between the Activation Loop and the ATP Binding Site Regulates the Activation of Src Kinase

Phosphorylation of the activation loop is a fundamental step in the activation of most protein kinases. In the case of the Src tyrosine kinase, a prototypical kinase due to its role in cancer and its historic importance, phosphorylation of tyrosine 416 in the activation loop is known to rigidify the structure and contribute to the switch from the inactive to a fully active form. However, whether or not phosphorylation is able per-se to induce a fully active conformation, that efficiently binds ATP and phosphorylates the substrate, is less clear. Here we employ a combination of solution NMR and enhanced-sampling molecular dynamics simulations to fully map the effects of phosphorylation and ATP/ADP cofactor loading on the conformational landscape of Src tyrosine kinase. We find that both phosphorylation and cofactor binding are needed to induce a fully active conformation. What is more, we find a complex interplay between the A-loop and the hinge motion where the phosphorylation of the activation-loop has a significant allosteric effect on the dynamics of the C-lobe.