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

Piperine's potential in treating polycystic ovarian syndrome explored through in-silico docking

Polycystic Ovarian Syndrome (PCOS) is a multifaceted metabolic and hormonal condition that impacts women in their procreative ages, identified by ovarian dysfunction, hyperandrogenaemia overweight and insulin insensitivity. The piperine, an important alkaloid compound of black pepper has shown promise in modulating various physiological processes. In this work, employed computational docking studies to explore the potential of piperine as a treatment for PCOS. Utilizing computational methods, we analyzed the binding interactions between piperine and key molecular targets implicated in PCOS pathogenesis, including hyperandrogenism, and "oligomenorrhea. The network pharmacology analysis report found 988 PCOS-related genes, 108 hyperandrogenism-related genes, and 377 oligomenorrhea-related genes, and we finally shortlisted 5 common genes in PCOS, hyperandrogenism, and "oligomenorrhea": NR3C1, PPARG, FOS, CYP17A1, and H6PD. Our results reveal favorable binding affinities with PPARG (-8.34 Kcal/mol) and H6PD (-8.70 Kcal/mol) and interaction patterns, suggesting the potential of piperine to modulate these targets. Moreover, the reliability of the piperine-target interactions was revealed by molecular simulations studies. These findings support further experimental investigations to validate the therapeutic efficacy of piperine in PCOS management. The integration of computational approaches with experimental studies has the potential to lay the groundwork for the creation of new therapies specifically targeting PCOS and related endocrine disorders.

Activating mutations drive human MEK1 kinase using a gear-shifting mechanism

There is an unmet need to classify cancer-promoting kinase mutations in a mechanistically cognizant way. The challenge is to understand how mutations stabilize different kinase configurations to alter function, and how this influences pathogenic potential of the kinase and its responses to therapeutic inhibitors. This goal is made more challenging by the complexity of the mutational landscape of diseases, and is further compounded by the conformational plasticity of each variant where multiple conformations coexist. We focus here on the human MEK1 kinase, a vital component of the RAS/MAPK pathway in which mutations cause cancers and developmental disorders called RASopathies. We sought to explore how these mutations alter the human MEK1 kinase at atomic resolution by utilizing enhanced sampling simulations and free energy calculations. We computationally mapped the different conformational stabilities of individual mutated systems by delineating the free energy landscapes, and showed how this relates directly to experimentally quantified developmental transformation potentials of the mutations. We conclude that mutations leverage variations in the hydrogen bonding network associated with the conformational plasticity to progressively stabilize the active-like conformational state of the kinase while destabilizing the inactive-like state. The mutations alter residue-level internal molecular correlations by differentially prioritizing different conformational states, delineating the various modes of MEK1 activation reminiscent of a gear-shifting mechanism. We define the molecular basis of conversion of this kinase from its inactive to its active state, connecting structure, dynamics, and function by delineating the energy landscape and conformational plasticity, thus augmenting our understanding of MEK1 regulation.

Screening and identification of phytochemical drug molecules against mutant BRCA1 receptor of breast cancer using computational approaches

The American Cancer Society claims that breast cancer is the second most significant cause of cancer-related death, with over one million women diagnosed each year. Breast cancer linked to the BRCA1 gene has a significant risk of mortality and recurrence and is susceptible to alteration or over-expression, which can lead to hereditary breast cancer. Given the shortage of effective and possibly curative treatments for breast cancer, the present study combined molecular and computational analysis to find prospective phytochemical substances that can suppress the mutant gene (BRCA1) that causes the disease. Virtual screening and Molecular docking approaches are utilized to find probable phytochemicals from the ZINC database. The 3D structure of mutant BRCA1 protein with the id 3PXB was extracted from the NCBI-PDB. Top 10 phytochemical compounds shortlisted based on molecular docking score between - 11.6 and - 13.0. Following the ADMET properties, only three (ZINC000085490903 = - 12.50, ZINC000085490832 = - 12.44, and ZINC000070454071 = - 11.681) of the 10 selected compounds have drug-like properties. The molecular dynamic simulation study of the top three potential phytochemicals showed stabilized RMSD and RMSF values as compared to the APO form of the BRCA1 receptor. Further, trajectory analysis revealed that approximately similar radius of gyration score tends to the compactness of complex structure, and principal component and cross-correlation analysis suggest that the residues move in a strong correlation. Thermostability of the target complex (B-factor) provides information on the stable energy minimized structure. The findings suggest that the top three ligands show potential as breast cancer inhibitors.

HER2 splice variants in breast cancer: investigating their impact on diagnosis and treatment outcomes

Overexpression of the HER2 receptor occurs in approximately 20% of breast cancer patients. HER2 positivity is associated with poor prognosis and aggressive tumour phenotypes, which led to rapid progress in HER2 targeted therapeutics and diagnostic testing. Whilst these advances have greatly increased patients' chances of survival, resistance to HER2 targeted therapies, be that intrinsic or acquired, remains a problem. Different forms of the HER2 protein exist within tumours in tandem and can display altered biological activities. Interest in HER2 variants in breast cancer increased when links between resistance to anti-HER2 therapies and a particular variant, Δ16-HER2, were identified. Moreover, the P100 variant potentially reduces the efficacy of the anti-HER2 therapy trastuzumab. Another variant, Herstatin, exhibits 'auto-inhibitory' behaviour. More recently, new HER2 variants have been identified and are currently being assessed for their pro- and anti-cancer properties. It is important when directing the care of patients to consider HER2 variants collectively. This review considers HER2 variants in the context of the tumour environment where multiple variants are co-expressed at altered ratios. This study also provides an up to date account of the landscape of HER2 variants and links this to patterns of resistance against HER2 therapies and treatment plans.

Genome-wide and structural analyses of pseudokinases encoded in the genome of Arabidopsis thaliana provide functional insights

Protein Kinase-Like Non-Kinases (PKLNKs), commonly known as "pseudokinases", are homologous to eukaryotic Ser/Thr/Tyr protein kinases (PKs) but lack the crucial aspartate residue in the catalytic loop, indispensable for phosphotransferase activity. Therefore, they are predicted to be "catalytically inactive" enzyme homologs. Analysis of protein-kinase like sequences from Arabidopsis thaliana led to the identification of more than 120 pseudokinases lacking catalytic aspartate, majority of which are closely related to the plant-specific receptor-like kinase family. These pseudokinases engage in different biological processes, enabled by their diverse domain architectures and specific subcellular localizations. Structural comparison of pseudokinases with active and inactive conformations of canonical PKs, belonging to both plant and animal origin, revealed unique structural differences. The currently available crystal structures of pseudokinases show that the loop topologically equivalent to activation segment of PKs adopts a distinct-folded conformation, packing against the pseudoenzyme core, in contrast to the extended and inhibitory geometries observed for active and inactive states, respectively, of catalytic PKs. Salt-bridge between ATP-binding Lys and DFG-Asp as well as hydrophobic interactions between the conserved nonpolar residue C-terminal to the equivalent DFG motif and nonpolar residues in C-helix mediate such a conformation in pseudokinases. This results in enhanced solvent accessibility of the pseudocatalytic loop in pseudokinases that can possibly serve as an interacting surface while associating with other proteins. Specifically, our analysis identified several residues that may be involved in pseudokinase regulation and hints at the repurposing of pseudocatalytic residues to achieve mechanistic control over noncatalytic functions of pseudoenzymes.

Computational algorithms for in silico profiling of activating mutations in cancer

Methods to catalog and computationally assess the mutational landscape of proteins in human cancers are desirable. One approach is to adapt evolutionary or data-driven methods developed for predicting whether a single-nucleotide polymorphism (SNP) is deleterious to protein structure and function. In cases where understanding the mechanism of protein activation and regulation is desired, an alternative approach is to employ structure-based computational approaches to predict the effects of point mutations. Through a case study of mutations in kinase domains of three proteins, namely, the anaplastic lymphoma kinase (ALK) in pediatric neuroblastoma patients, serine/threonine-protein kinase B-Raf (BRAF) in melanoma patients, and erythroblastic oncogene B 2 (ErbB2 or HER2) in breast cancer patients, we compare the two approaches above. We find that the structure-based method is most appropriate for developing a binary classification of several different mutations, especially infrequently occurring ones, concerning the activation status of the given target protein. This approach is especially useful if the effects of mutations on the interactions of inhibitors with the target proteins are being sought. However, many patients will present with mutations spread across different target proteins, making structure-based models computationally demanding to implement and execute. In this situation, data-driven methods-including those based on machine learning techniques and evolutionary methods-are most appropriate for recognizing and illuminate mutational patterns. We show, however, that, in the present status of the field, the two methods have very different accuracies and confidence values, and hence, the optimal choice of their deployment is context-dependent.

Structural insight into the binding mechanism of ATP to EGFR and L858R, and T790M and L858R/T790 mutants

The L858R mutation in EGFR is particularly responsive to small tyrosine kinase inhibitors (TKIs) such as gefitinib and erlotinib. This efficacy decreases due to drug resistance conferred by a second mutation, T790M, which subsequently produces a double mutant, L858R/T790M. Although this resistance was initially attributed to steric blocking by the T790M mutation, experimental studies have demonstrated that differences in the binding affinities of TKIs to T790M and L858R/T790M mutants are more a result of the increased sensitivity of these mutants to ATP than to a decrease in the affinity to TKIs. Regrettably, detailed information at the atomic level on the origins of the increased binding affinity of mutants for ATP is lacking. In this study, we have combined structural data and molecular dynamics simulations with the MMGBSA approach to determine how the L858R, T790M and L858R/T790 mutations impact the binding mechanism of ATP with respect to wild-type EGFR. Structural and energetic analyses provided novel information that helps to explain the increased affinity of ATP to T790M and L858R/T790 mutants with respect to L858R and wild-type systems. In addition, it was observed that dimerization of the wild-type and mutant systems exerts dissimilar effects on the ATP binding affinity characteristic of negative cooperativity. Communicated by Ramaswamy H. Sarma.

Polymer-Nucleic Acid Interactions

Gene therapy is an important therapeutic strategy in the treatment of a wide range of genetic disorders. Polymers forming stable complexes with nucleic acids (NAs) are non-viral gene carriers. The self-assembly of polymers and nucleic acids is typically a complex process that involves many types of interaction at different scales. Electrostatic interaction, hydrophobic interaction, and hydrogen bonds are three important and prevalent interactions in the polymer/nucleic acid system. Electrostatic interactions and hydrogen bonds are the main driving forces for the condensation of nucleic acids, while hydrophobic interactions play a significant role in the cellular uptake and endosomal escape of polymer-nucleic acid complexes. To design high-efficiency polymer candidates for the DNA and siRNA delivery, it is necessary to have a detailed understanding of the interactions between them in solution. In this chapter, we survey the roles of the three important interactions between polymers and nucleic acids during the formation of polyplexes and summarize recent understandings of the linear polyelectrolyte-NA interactions and dendrimer-NA interactions. We also review recent progress optimizing the gene delivery system by tuning these interactions.

Computational and Experimental Characterization of Patient Derived Mutations Reveal an Unusual Mode of Regulatory Spine Assembly and Drug Sensitivity in EGFR Kinase

The catalytic activation of protein kinases requires precise positioning of key conserved catalytic and regulatory motifs in the kinase core. The Regulatory Spine (RS) is one such structural motif that is dynamically assembled upon kinase activation. The RS is also a mutational hotspot in cancers; however, the mechanisms by which cancer mutations impact RS assembly and kinase activity are not fully understood. In this study, through mutational analysis of patient derived mutations in the RS of EGFR kinase, we identify an activating mutation, M766T, at the RS3 position. RS3 is located in the regulatory αC-helix, and a series of mutations at the RS3 position suggest a strong correlation between the amino acid type present at the RS3 position and ligand (EGF) independent EGFR activation. Small polar amino acids increase ligand independent activity, while large aromatic amino acids decrease kinase activity. M766T relies on the canonical asymmetric dimer for full activation. Molecular modeling and molecular dynamics simulations of WT and mutant EGFR suggest a model in which M766T activates the kinase domain by disrupting conserved autoinhibitory interactions between M766 and hydrophobic residues in the activation segment. In addition, a water mediated hydrogen bond network between T766, the conserved K745-E762 salt bridge, and the backbone amide of the DFG motif is identified as a key determinant of M766T-mediated activation. M766T is resistant to FDA approved EGFR inhibitors such as gefitinib and erlotinib, and computational estimation of ligand binding free energy identifies key residues associated with drug sensitivity. In sum, our studies suggest an unusual mode of RS assembly and oncogenic EGFR activation, and provide new clues for the design of allosteric protein kinase inhibitors.

Molecular Dynamics Analysis of Binding of Kinase Inhibitors to WT EGFR and the T790M Mutant

Epidermal growth factor receptor (EGFR) inhibitors interrupt EGFR-dependent cellular signaling pathways that lead to accelerated tumor growth and proliferation. Mutation of a threonine in the inhibitor binding pocket, known as the "gatekeeper", to methionine (T790M) confers acquired resistance to several EGFR-selective inhibitors. We studied interactions between EGFR inhibitors and the gatekeeper residues of the target protein. Thermodynamic integration (TI) with Amber14 indicates that the binding energies of gefitinib and AEE788 to the active state of the T790M mutant EGFR is 3 kcal/mol higher than to the wild type (WT), whereas ATP binding energy to the mutant is similar to the WT. Using metadynamics MD simulations with NAMD v2.9, the conformational equilibrium between the inactive resting state and the catalytically competent activate state was determined for the WT EGFR. When combined with the results obtained by Sutto and Gervasio, our simulations showed that the T790M point mutation lowers the free energy of the active state by 5 kcal/mol relative to the inactive state of the enzyme. Relative to the WT, the T790M mutant binds gefitinib more strongly. The T790M mutation is nevertheless resistant due to its increased binding of ATP. By contrast, the binding of AEE788 to the active state causes a conformational change in the αC-helix adjacent to the inhibitor binding pocket, that results in a 2 kcal/mol energy penalty. The energy penalty explains why the binding of AEE788 to the T790M mutant is unfavorable relative to binding to WT EGFR. These results establish the role of the gatekeeper mutation on inhibitor selectivity. Additional molecular dynamics (MD) simulations, TI, and metadynamics MD simulations reveal the origins of the changes in binding energy of WT and mutants.

Mechanistic Insights into R776H Mediated Activation of Epidermal Growth Factor Receptor Kinase

The epidermal growth factor receptor (EGFR) kinase is activated by a variety of mutations in human cancers. R776H is one such recurrent mutation (R752H in another numbering system) in the αC-β4 loop of the tyrosine kinase domain that activates EGFR in the absence of the activating EGF ligand. However, the mechanistic details of how R776H contributes to kinase activation are not well understood. Here using cell-based cotransfection assays, we show that the R776H mutation activates EGFR in a dimerization-dependent manner by preferentially adopting the acceptor position in the asymmetric dimer. The acceptor function, but not the donor function, is enhanced for the R776H mutant, supporting the "superacceptor" hypothesis proposed for oncogenic mutations in EGFR. We also find that phosphorylation of monomeric EGFR is increased by R776H mutation, providing insights into EGFR lateral phosphorylation and oligomerization. On the basis of molecular modeling and molecular dynamics simulation, we propose a model in which loss of key autoinhibitory αC-helix capping interaction and alteration of coconserved cis regulatory interactions between the kinase domain and the flanking regulatory segments contribute to mutational activation. Since the R776 equivalent position is mutated in ErbB2 and ErbB4, our studies have implications for understanding kinase mutational activation in other ErbB family members as well.

Structure-based network analysis of activation mechanisms in the ErbB family of receptor tyrosine kinases: the regulatory spine residues are global mediators of structural stability and allosteric interactions

The ErbB protein tyrosine kinases are among the most important cell signaling families and mutation-induced modulation of their activity is associated with diverse functions in biological networks and human disease. We have combined molecular dynamics simulations of the ErbB kinases with the protein structure network modeling to characterize the reorganization of the residue interaction networks during conformational equilibrium changes in the normal and oncogenic forms. Structural stability and network analyses have identified local communities integrated around high centrality sites that correspond to the regulatory spine residues. This analysis has provided a quantitative insight to the mechanism of mutation-induced “superacceptor” activity in oncogenic EGFR dimers. We have found that kinase activation may be determined by allosteric interactions between modules of structurally stable residues that synchronize the dynamics in the nucleotide binding site and the αC-helix with the collective motions of the integrating αF-helix and the substrate binding site. The results of this study have pointed to a central role of the conserved His-Arg-Asp (HRD) motif in the catalytic loop and the Asp-Phe-Gly (DFG) motif as key mediators of structural stability and allosteric communications in the ErbB kinases. We have determined that residues that are indispensable for kinase regulation and catalysis often corresponded to the high centrality nodes within the protein structure network and could be distinguished by their unique network signatures. The optimal communication pathways are also controlled by these nodes and may ensure efficient allosteric signaling in the functional kinase state. Structure-based network analysis has quantified subtle effects of ATP binding on conformational dynamics and stability of the EGFR structures. Consistent with the NMR studies, we have found that nucleotide-induced modulation of the residue interaction networks is not limited to the ATP site, and may enhance allosteric cooperativity with the substrate binding region by increasing communication capabilities of mediating residues.

ALK mutations confer differential oncogenic activation and sensitivity to ALK inhibition therapy in neuroblastoma

Genetic studies have established anaplastic lymphoma kinase (ALK), a cell surface receptor tyrosine kinase, as a tractable molecular target in neuroblastoma. We describe comprehensive genomic, biochemical, and computational analyses of ALK mutations across 1,596 diagnostic neuroblastoma samples. ALK tyrosine kinase domain mutations occurred in 8% of samples--at three hot spots and 13 minor sites--and correlated significantly with poorer survival in high- and intermediate-risk neuroblastoma. Biochemical and computational studies distinguished oncogenic (constitutively activating) from nononcogenic mutations and allowed robust computational prediction of their effects. The mutated variants also showed differential in vitro crizotinib sensitivities. Our studies identify ALK genomic status as a clinically important therapeutic stratification tool in neuroblastoma and will allow tailoring of ALK-targeted therapy to specific mutations.

Molecular modeling of ErbB4/HER4 kinase in the context of the HER4 signaling network helps rationalize the effects of clinically identified HER4 somatic mutations on the cell phenotype

In the ErbB/HER family of receptor tyrosine kinases, the deregulation of the EGFR/ErbB1/HER1, HER2/ErbB2, and HER3/ErbB3 kinases is associated with several cancers, while the HER4/ErbB4 kinase has been shown to play an anti-carcinogenic role in certain tumors. We present molecular and network models of HER4/ErbB4 activation and signaling in order to elucidate molecular mechanisms of activation and rationalize the effects of the clinically identified HER4 somatic mutants. Our molecular-scale simulations identify the important role played by the interactions within the juxtamembrane region during the activation process. Our results also support the hypothesis that the HER4 mutants may heterodimerize but not activate, resulting in blockage of the HER4-STAT5 differentiation pathway, in favor of the proliferative PI3K/AKT pathway. Translating our molecular simulation results into a cellular pathway model of wild type versus mutant HER4 signaling, we are able to recapitulate the major features of the PI3K/AKT and JAK/STAT activation downstream of HER4. Our model predicts that the signaling downstream of the wild type HER4 is enriched for the JAK-STAT pathway, whereas downstream of the mutant HER4 is enriched for the PI3K/AKT pathway. HER4 mutations may hence constitute a cellular shift from a program of differentiation to that of proliferation.

Ligand binding and dynamics of the monomeric epidermal growth factor receptor ectodomain

The ectodomain of the human epidermal growth factor receptor (hEGFR) controls input to several cell signalling networks via binding with extracellular growth factors. To gain insight into the dynamics and ligand binding of the ectodomain, the hEGFR monomer was subjected to molecular dynamics simulation. The monomer was found to be substantially more flexible than the ectodomain dimer studied previously. Simulations where the endogeneous ligand EGF binds to either Subdomain I or Subdomain III, or where hEGFR is unbound, show significant differences in dynamics. The molecular mechanics Poisson-Boltzmann surface area method has been used to derive relative free energies of ligand binding, and we find that the ligand is capable of binding either subdomain with a slight preference for III. Alanine-scanning calculations for the effect of selected ligand mutants on binding reproduce the trends of affinity measurements. Taken together, these results emphasize the possible role of the ectodomain monomer in the initial step of ligand binding, and add details to the static picture obtained from crystal structures.

Ligand binding induces a conformational change in epidermal growth factor receptor dimers

The activation of the epidermal growth factor receptor (EGFR) kinase requires ligand binding to the extracellular domain (ECD). Previous reports demonstrate that the EGFR-ECD can be crystallized in two conformations - a tethered monomer or, in the presence of ligand, an untethered back-to-back dimer. We use Biosensor analysis to demonstrate that even in the monomeric state different C-terminal extensions of both truncated (EGFR(1-501))-ECD and full-length EGFR(1-621)-ECD can change the conformation of the ligand-binding site. The binding of a monoclonal antibody mAb806, which recognizes the dimer interface, to the truncated EGFR(1-501)-Fc fusion protein is reduced in the presence of ligand, consistent with a change in conformation. On the cell surface, the presence of erythroblastosis B2 (erbB2) increases the binding of mAb806 to the EGFR. The conformation of the erbB2: EGFR heterodimer interface changes when the cells are treated with epidermal growth factor (EGF). We propose that ligand induces kinase-inactive, pre-formed EGFR dimers and heterodimers to change conformation leading to kinase-active tetramers, where kinase activation occurs via an asymmetric interaction between EGFR dimers.

Mechanism of drug efficacy within the EGF receptor revealed by microsecond molecular dynamics simulation

The EGF receptor (EGFR) regulates important cellular processes including proliferation, differentiation, and apoptosis. EGFR is frequently overexpressed in a range of cancers and is associated with disease progression and treatment. Clinical studies have shown that EGFR mutations confer tumor sensitivity to tyrosine kinase inhibitors in patients with non-small cell lung cancer. In this study, we have conducted molecular dynamics simulations over several microseconds for wild-type and L858R mutant forms of EGFR in the ligand-free state. Close inspection of the conformations and interactions within the binding pocket reveals, converse to the wild type, that the mutant EGFR prefers to bind gefitinib, a targeted anticancer drug, rather than ATP, offering an explanation for why gefitinib is more effective in patients with EGFR mutations than those without.

Structural systems biology and multiscale signaling models

We review current advances in experimental as well as computational modeling and simulation approaches to structural systems biology, whose overall aim is to build quantitative models of signaling networks while retaining the crucial elements of molecular specificity. We briefly discuss the current and emerging experimental and computational methods, particularly focusing on hybrid and multiscale methods, and highlight several applications in cell signaling with quantitative and predictive capabilities. The scope of such models range from delineating protein-protein interactions to describing clinical implications.

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

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

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

A multiscale modeling approach to investigate molecular mechanisms of pseudokinase activation and drug resistance in the HER3/ErbB3 receptor tyrosine kinase signaling network

Multiscale modeling provides a powerful and quantitative platform for investigating the complexity inherent in intracellular signaling pathways and rationalizing the effects of molecular perturbations on downstream signaling events and ultimately, on the cell phenotype. Here we describe the application of a multiscale modeling scheme to the HER3/ErbB3 receptor tyrosine kinase (RTK) signaling network, which regulates critical cellular processes including proliferation, migration and differentiation. The HER3 kinase is a topic of current interest and investigation, as it has been implicated in mechanisms of resistance to tyrosine kinase inhibition (TKI) of EGFR and HER2 in the treatment of many human malignancies. Moreover, the commonly regarded status of HER3 as a catalytically inactive 'pseudokinase' has recently been challenged by our previous study, which demonstrated robust residual kinase activity for HER3. Through our multiscale model, we investigate the most significant molecular interactions that contribute to potential mechanisms of HER3 activity and the physiological relevance of this activity to mechanisms of drug resistance in an ErbB-driven tumor cell in silico. The results of our molecular-scale simulations support the characterization of HER3 as a weakly active kinase that, in contrast to its fully-active ErbB family members, depends upon a unique hydrophobic interface to coordinate the alignment of specific catalytic residues required for its activity. Translating our molecular simulation results of the uniquely active behavior of the HER3 kinase into a physiologically relevant environment, our HER3 signaling model demonstrates that even a weak level of HER3 activity may be sufficient to induce AKT signaling and TKI resistance in the context of an ErbB signaling-dependent tumor cell, and therefore therapeutic targeting of HER3 may represent a superior treatment strategy for specific ErbB-driven cancers.

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

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

Investigating Molecular Mechanisms of Activation and Mutation of the HER2 Receptor Tyrosine Kinase through Computational Modeling and Simulation

Human epidermal growth factor receptor 2 (HER2)/ErbB2 is a receptor tyrosine kinase belonging to the EGFR/ErbB family and is overexpressed in 20-30% of human breast cancers. Since there is a growing effort to develop pharmacological inhibitors of the HER2 kinase for the treatment of breast cancer, it is clinically valuable to rationalize how specific mutations impact the molecular mechanism of receptor activation. Although several crystal structures of the ErbB kinases have been solved, the precise mechanism of HER2 activation remains unknown, and it has been suggested that HER2 is unique in its requirement for phosphorylation of Y877, a key tyrosine residue located in the activation loop (A-loop). In our studies, discussed here, we have investigated the mechanisms that are important in HER2 kinase domain regulation and compared them with the other ErbB family members, namely EGFR and ErbB4, to determine the molecular basis for HER2's unique mode of activation. We apply computational simulation techniques at the atomic level and at the electronic structure (quantum mechanical) level to elucidate details of the mechanisms governing the kinase domains of these ErbB members. Through analysis of our simulation results, we have discovered potential regulatory mechanisms common to EGFR, HER2, and ErbB4, including a tight coupling between the A-loop and catalytic loop that may contribute to alignment of residues required for catalysis in the active kinase. We further postulate an autoinhibitory mechanism whereby the inactive kinase is stabilized through sequestration of catalytic residues. In HER2, we also predict a role for phosphorylated Y877 in bridging a network of hydrogen bonds that fasten the A-loop in its active conformation, suggesting that HER2 may be unique among the ErbB members in requiring A-loop tyrosine phosphorylation for functionality. In EGFR, HER2, and ErbB4, we discuss the possible effects of activating mutations. Delineation of the activation mechanism of HER2 in the context of the other ErbB members is crucial for understanding how the activated kinase might interact with downstream molecules and couple to signaling cascades that promote cancer. Our comparative analysis furthers insight into the mechanics of activation of the HER2 kinase and enables us to predict the effect of an identified insertion mutation on HER2 activation. Further understanding of the mechanism of HER2 kinase activation at the atomic scale and how it couples to downstream signaling at the cellular scale will elucidate predictive molecular phenotypes that may indicate likelihood of response to specific therapies for HER2-mediated cancers.