Molecular Dynamics Simulations and Structural Network Analysis of c-Abl and c-Src Kinase Core Proteins: Capturing Allosteric Mechanisms and Communication Pathways from Residue Centrality

Role of Mutual Information Profile Shifts in Assessing the Pathogenicity of Mutations on Protein Functions: The Case of Pyrin Variants Associated With Familial Mediterranean Fever

This study presents a novel method to assess the pathogenicity of pyrin protein mutations by using mutual information (MI) as a measure to quantify the correlation between residue motions or fluctuations and associated changes affecting the phenotype. The concept of MI profile shift is presented to quantify changes in MI upon mutation, revealing insights into residue-residue interactions at critical positions. We apply this method to the pyrin protein variants, which are associated with an autosomal recessively inherited disease called familial Mediterranean fever (FMF) since the available tools do not help predict the pathogenicity of the most penetrant variants. We demonstrate the utility of MI profile shifts in assessing the effects of mutations on protein stability, function, and disease phenotype. The importance of MI shifts, particularly the negative shifts observed in the pyrin example, as indicators of severe functional effects is emphasized. Additionally, the exploration of potential compensatory mechanisms suggested by positive MI shifts, which are otherwise random and inconsequential, is highlighted. The study also discusses challenges in relating MI profile changes to disease severity and advocates for comprehensive analysis considering genetic, environmental, and stochastic factors. Overall, this study provides insights into the molecular mechanisms underlying the pathogenesis of FMF and offers a framework for identifying potential therapeutic targets based on MI profile changes induced by mutations.

Natural Flavonoids from Licorice as Potent Inhibitors of β-Glucuronidase Elucidated Through Computational Studies

Gut bacterial β-glucuronidase is an important molecular target in several therapeutic applications. β-glucuronidase inhibitors can effectively alleviate gastrointestinal toxicity caused by certain drugs. Licorice, a traditional Chinese medicine, harmonizes various herbs and mitigates the toxicity of hundreds of herbs. In this study, a comprehensive computational strategy was employed to evaluate four licorice flavonoids (liquiritigenin, isoliquiritigenin, liquiritin, and isoliquiritin) as potential Escherichia coli β-glucuronidase (EcGUS) inhibitors. Density functional theory was used to determine their geometries, thermal parameters, dipole moments, polarizabilities, and molecular electrostatic potentials. The inhibitory mechanisms of these four flavonoids on EcGUS were investigated using molecular docking, molecular dynamics simulations, and free energy calculations. The results show that all four flavonoids stably bind to EcGUS. Moreover, all molecules, except liquiritigenin, are potent and selective inhibitors of EcGUS. Further calculations suggest that isoliquiritin exhibits the strongest binding affinity for EcGUS among the four licorice flavonoids. Thus, isoliquiritin is a promising candidate for the development of EcGUS inhibitors. These findings will aid in designing and developing novel flavonoid-based inhibitors of EcGUS to alleviate gastrointestinal toxicity caused by drugs.

Elucidating the linagliptin and fibroblast activation protein binding mechanism through molecular dynamics and binding free energy analysis

Fibroblast activation protein (FAP) is highly expressed in solid tumors and may be a potential diagnostic and therapeutic target in solid cancers. Linagliptin inhibits FAP; however, the interaction mechanism between linagliptin and FAP remains unclear. In this study, the binding free energy for linagliptin with human FAP was estimated at -13.66 kcal/mol, and the dissociation constant was 243 nM based on surface plasmon resonance analyses. E203, E204, and Y656 formed hydrogen bonds with ammonium. Y625 formed an unstable hydrogen bond with the carbonyl group. W623 and Y541 interacted with the quinazoline and pyrimidine-2,4-dione rings, respectively, via π-π interactions. The butyne group formed hydrophobic interactions with residues V650, Y653, Y656, and Y660. ZINC000299754517 and ZINC000299754576 were identified as potential FAP inhibitors. The R1 and R4 regions of linagliptin could be optimized to increase its FAP binding affinity. These findings can guide linagliptin structural optimization to improve its FAP binding affinity.

Free energy landscape of the PI3Kα C-terminal activation

The gene PIK3CA, encoding the catalytic subunit p110α of PI3Kα, is the second most frequently mutated gene in cancer, with the highest frequency oncogenic mutants occurring in the C-terminus of the kinase domain. The C-terminus has a dual function in regulating the kinase, playing a putative auto-inhibitory role for kinase activity and being absolutely essential for binding to the cell membrane. However, the molecular mechanisms by which these C-terminal oncogenic mutations cause PI3Kα overactivation remain unclear. To understand how a spectrum of C-terminal mutations of PI3Kα alter kinase activity compared to the WT, we perform unbiased and biased Molecular Dynamics simulations of several C-terminal mutants and report the free energy landscapes for the C-terminal "closed-to-open" transition in the WT, H1047R, G1049R, M1043L and N1068KLKR mutants. Results are consistent with HDX-MS experimental data and provide a molecular explanation why H1047R and G1049R reorient the C-terminus with a different mechanism compared to the WT and M1043L and N1068KLKR mutants. Moreover, we show that in the H1047R mutant, the cavity, where the allosteric ligands STX-478 and RLY-2608 bind, is more accessible contrary to the WT. This study provides insights into the molecular mechanisms underlying activation of oncogenic PI3Kα by C-terminal mutations and represents a valuable resource for continued efforts in the development of mutant selective inhibitors as therapeutics.

Reviewing the Structure-Function Paradigm in Polyglutamine Disorders: A Synergistic Perspective on Theoretical and Experimental Approaches

Polyglutamine (polyQ) disorders are a group of neurodegenerative diseases characterized by the excessive expansion of CAG (cytosine, adenine, guanine) repeats within host proteins. The quest to unravel the complex diseases mechanism has led researchers to adopt both theoretical and experimental methods, each offering unique insights into the underlying pathogenesis. This review emphasizes the significance of combining multiple approaches in the study of polyQ disorders, focusing on the structure-function correlations and the relevance of polyQ-related protein dynamics in neurodegeneration. By integrating computational/theoretical predictions with experimental observations, one can establish robust structure-function correlations, aiding in the identification of key molecular targets for therapeutic interventions. PolyQ proteins' dynamics, influenced by their length and interactions with other molecular partners, play a pivotal role in the polyQ-related pathogenic cascade. Moreover, conformational dynamics of polyQ proteins can trigger aggregation, leading to toxic assembles that hinder proper cellular homeostasis. Understanding these intricacies offers new avenues for therapeutic strategies by fine-tuning polyQ kinetics, in order to prevent and control disease progression. Last but not least, this review highlights the importance of integrating multidisciplinary efforts to advancing research in this field, bringing us closer to the ultimate goal of finding effective treatments against polyQ disorders.

Prediction of Conformational Ensembles and Structural Effects of State-Switching Allosteric Mutants in the Protein Kinases Using Comparative Analysis of AlphaFold2 Adaptations with Sequence Masking and Shallow Subsampling

Despite the success of AlphaFold2 approaches in predicting single protein structures, these methods showed intrinsic limitations in predicting multiple functional conformations of allosteric proteins and have been challenged to accurately capture of the effects of single point mutations that induced significant structural changes. We systematically examined several implementations of AlphaFold2 methods to predict conformational ensembles for state-switching mutants of the ABL kinase. The results revealed that a combination of randomized alanine sequence masking with shallow multiple sequence alignment subsampling can significantly expand the conformational diversity of the predicted structural ensembles and capture shifts in populations of the active and inactive ABL states. Consistent with the NMR experiments, the predicted conformational ensembles for M309L/L320I and M309L/H415P ABL mutants that perturb the regulatory spine networks featured the increased population of the fully closed inactive state. On the other hand, the predicted conformational ensembles for the G269E/M309L/T334I and M309L/L320I/T334I triple ABL mutants that share activating T334I gate-keeper substitution are dominated by the active ABL form. The proposed adaptation of AlphaFold can reproduce the experimentally observed mutation-induced redistributions in the relative populations of the active and inactive ABL states and capture the effects of regulatory mutations on allosteric structural rearrangements of the kinase domain. The ensemble-based network analysis complemented AlphaFold predictions by revealing allosteric mediating centers that often directly correspond to state-switching mutational sites or reside in their immediate local structural proximity, which may explain the global effect of regulatory mutations on structural changes between the ABL states. This study suggested that attention-based learning of long-range dependencies between sequence positions in homologous folds and deciphering patterns of allosteric interactions may further augment the predictive abilities of AlphaFold methods for modeling of alternative protein sates, conformational ensembles and mutation-induced structural transformations.

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

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

Selectivity Mechanism of Pyrrolopyridone Analogues Targeting Bromodomain 2 of Bromodomain-Containing Protein 4 from Molecular Dynamics Simulations

Bromodomain and extra-terminal domain (BET) proteins play an important role in epigenetic regulation and are linked to several diseases; therefore, they are interesting targets. BET has two bromodomains: bromodomain 1 (BD1) and BD2. Selective targeting of BD1 or BD2 may produce different activities and greater effects than pan-BD inhibitors. However, the selective mechanism of the specific core must be studied at the atomic level. This study determined the effectiveness of pyrrolopyridone analogues to selectively inhibit BD2 using a pan-BD inhibitor (ABBV-075) and a selective-BD2 inhibitor (ABBV-744). Molecular dynamics simulations and calculations of binding free energies were used to systematically study the selectivity of BD2 inhibition by the pyrrolopyridone analogues. Overall, the pyrrolopyridone analogue inhibitors targeting BD2 interacted mainly with the following amino acid pairs between bromodomain-containing protein 4 (BRD4)-BD1 and BRD4-BD2 complexes: I146/V439, N140/N433, D144/H437, P82/P375, V87/V380, D88/D381, and Y139/Y432. The pyrrolopyridone analogues targeting BRD4-BD2 were divided into five regions based on selectivity mechanism. These results suggest that the R3 and R5 regions of pyrrolopyridone analogues can be modified to improve the selectivity between BRD4-BD1 and BRD4-BD2. The selectivity of BD2 inhibition by pyrrolopyridone analogues can be used to design novel BD2 inhibitors based on a pyrrolopyridone core.

Identification of abemaciclib derivatives targeting cyclin-dependent kinase 4 and 6 using molecular dynamics, binding free energy calculation, synthesis, and pharmacological evaluation

CDK4/6 plays a crucial role in various cancers and is an effective anticancer drug target. However, the gap between clinical requirements and approved CDK4/6 drugs is unresolved. Thus, there is an urgent need to develop selective and oral CDK4/6 inhibitors, particularly for monotherapy. Here, we studied the interaction between abemaciclib and human CDK6 using molecular dynamics simulations, binding free energy calculations, and energy decomposition. V101 and H100 formed stable hydrogen bonds with the amine-pyrimidine group, and K43 interacted with the imidazole ring via an unstable hydrogen bond. Meanwhile, I19, V27, A41, and L152 interacted with abemaciclib through π-alkyl interactions. Based on the binding model, abemaciclib was divided into four regions. With one region modification, 43 compounds were designed and evaluated using molecular docking. From each region, three favorable groups were selected and combined with each other to obtain 81 compounds. Among them, C2231-A, which was obtained by removing the methylene group from C2231, showed better inhibition than C2231. Kinase profiling revealed that C2231-A showed inhibitory activity similar to that of abemaciclib; additionally, C2231-A inhibited the growth of MDA-MB-231 cells to a greater extent than did abemaciclib. Based on molecular dynamics simulation, C2231-A was identified as a promising candidate compound with considerable inhibitory effects on human breast cancer cell lines.

Structural basis of constitutive c-Src kinase activity due to R175L and W118A mutations

Cellular Src (c-Src) belongs to a non-receptor membrane-associated tyrosine kinase family that plays essential roles in cellular processes. Growing evidence suggests that R175L and W118A mutations in SH2/SH3 domains of c-Src functionally inactivate these domains leading to constitutive activation of kinase domain (KD). Here we modeled c-Src^R175L, c-Src^W118A and c-Src^W118A+R175L structures by inducing phosphorylation at Y416 or Y527, respectively to characterize the comparative dynamics in the active versus inactive states through molecular dynamics simulation assay. We observed more conformational readjustments in c-Src^open than its close variants. In particular, C-terminal tail residues of c-Src^W118A-open and c-Src^{W118A+R175L-open} demonstrate significantly higher transitions. The cross-correlation analysis revealed an anticorrelation behavior in the motion of KD with respect to SH2, SH3 and the linker region of Src^{W118A+R175L-open}, while in c-Src^WT-open, SH2 and SH3 domains were anticorrelated, while KD and C-terminal tail motions were correlated. Due to these conformational differences, c-Src open forms exhibited lower interaction between pY527 and SH2 domain. Through detailed structural analysis, we observed a uniform myristate binding cavity in c-Src^WT-open, while the myristoyl pockets of mutant forms were deformed. We propose that constitutive activation of mutant Src forms may presumably be achieved by the prolonged membrane binding due to unusual conformations of C-terminal and myristoyl switch residues that may result in a higher dephosphorylation rate at pY527 in the myristoylated c-Src. Thus, our study establishes novel clues to decipher the constitutive activation status of c-Src in response to known mutations that may help in devising novel therapeutic strategies for cancer metastasis treatment.Communicated by Ramaswamy H. Sarma.

psnGPCRdb: The Structure-network Database of G Protein Coupled Receptors

G protein coupled receptors (GPCRs) are critical eukaryotic signal transduction gatekeepers and represent the largest protein superfamily in the human proteome, with more than 800 members. They share seven transmembrane helices organized in an up-down bundle architecture. GPCR-mediated signaling pathways have been linked to numerous human diseases, and GPCRs are the targets of approximately 35% of all drugs currently on the market. Structure network analysis, a graph theory-based approach, represents a cutting-edge tool to deeply understand GPCR function, which strongly relies on communication between the extracellular and intracellular poles of their structure. psnGPCRdb stores the structure networks (i.e., linked nodes, hubs, communities and communication pathways) computed on all updated GPCR structures in the Protein Data Bank, in their isolated states or in complex with extracellular and/or intracellular molecules. The structure communication signatures of a sub-family or family of GPCRs as well as of their small-molecule activators or inhibitors are stored as consensus networks. The database stores also all meaningful structure network-based comparisons (i.e., difference networks) of functionally different states (i.e., inactive or active) of a given receptor sub-type, or of consensus networks representative of a receptor sub-type, type, sub-family or family. Single or consensus GPCR networks hold also information on amino acid conservation. The database allows to graphically analyze 3D structure networks together with interactive data-tables. Ligand-centric networks can be analyzed as well. psnGPCRdb is unique and represents a powerful resource to unravel GPCR function with important implications in cell signaling and drug design. psnGPCRdb is freely available at: http://webpsn.hpc.unimo.it/psngpcr.php.

Interactions between curcumin and human salt-induced kinase 3 elucidated from computational tools and experimental methods

Natural products are widely used for treating mitochondrial dysfunction-related diseases and cancers. Curcumin, a well-known natural product, can be potentially used to treat cancer. Human salt-induced kinase 3 (SIK3) is one of the target proteins for curcumin. However, the interactions between curcumin and human SIK3 have not yet been investigated in detail. In this study, we studied the binding models for the interactions between curcumin and human SIK3 using computational tools such as homology modeling, molecular docking, molecular dynamics simulations, and binding free energy calculations. The open activity loop conformation of SIK3 with the ketoenol form of curcumin was the optimal binding model. The I72, V80, A93, Y144, A145, and L195 residues played a key role for curcumin binding with human SIK3. The interactions between curcumin and human SIK3 were also investigated using the kinase assay. Moreover, curcumin exhibited an IC₅₀ (half-maximal inhibitory concentration) value of 131 nM, and it showed significant antiproliferative activities of 9.62 ± 0.33 µM and 72.37 ± 0.37 µM against the MCF-7 and MDA-MB-23 cell lines, respectively. This study provides detailed information on the binding of curcumin with human SIK3 and may facilitate the design of novel salt-inducible kinases inhibitors.

Probing conformational landscapes and mechanisms of allosteric communication in the functional states of the ABL kinase domain using multiscale simulations and network-based mutational profiling of allosteric residue potentials

In the current study, multiscale simulation approaches and dynamic network methods are employed to examine the dynamic and energetic details of conformational landscapes and allosteric interactions in the ABL kinase domain that determine the kinase functions. Using a plethora of synergistic computational approaches, we elucidate how conformational transitions between the active and inactive ABL states can employ allosteric regulatory switches to modulate intramolecular communication networks between the ATP site, the substrate binding region, and the allosteric binding pocket. A perturbation-based network approach that implements mutational profiling of allosteric residue propensities and communications in the ABL states is proposed. Consistent with biophysical experiments, the results reveal functionally significant shifts of the allosteric interaction networks in which preferential communication paths between the ATP binding site and substrate regions in the active ABL state become suppressed in the closed inactive ABL form, which in turn features favorable allosteric coupling between the ATP site and the allosteric binding pocket. By integrating the results of atomistic simulations with dimensionality reduction methods and Markov state models, we analyze the mechanistic role of macrostates and characterize kinetic transitions between the ABL conformational states. Using network-based mutational scanning of allosteric residue propensities, this study provides a comprehensive computational analysis of long-range communications in the ABL kinase domain and identifies conserved regulatory hotspots that modulate kinase activity and allosteric crosstalk between the allosteric pocket, ATP binding site, and substrate binding regions.

Allosteric regulation of autoinhibition and activation of c-Abl

c-Abl, a non-receptor tyrosine kinase, regulates cell growth and survival in healthy cells and causes chronic myeloid leukemia (CML) when fused by Bcr. Its activity is blocked in the assembled inactive state, where the SH3 and SH2 domains dock into the kinase domain, reducing its conformational flexibility, resulting in the autoinhibited state. It is active in an extended 'open' conformation. Allostery governs the transitions between the autoinhibited and active states. Even though experiments revealed the structural hallmarks of the two states, a detailed grasp of the determinants of c-Abl autoinhibition and activation at the atomic level, which may help innovative drug discovery, is still lacking. Here, using extensive molecular dynamics simulations, we decipher exactly how these determinants regulate it. Our simulations confirm and extend experimental data that the myristoyl group serves as the switch for c-Abl inhibition/activation. Its dissociation from the kinase domain promotes the SH2-SH3 release, initiating c-Abl activation. We show that the precise SH2/N-lobe interaction is required for full activation of c-Abl. It stabilizes a catalysis-favored conformation, priming it for catalytic action. Bcr-Abl allosteric drugs elegantly mimic the endogenous myristoyl-mediated autoinhibition state of c-Abl 1b. Allosteric activating mutations shift the ensemble to the active state, blocking ATP-competitive drugs. Allosteric drugs alter the active-site conformation, shifting the ensemble to re-favor ATP-competitive drugs. Our work provides a complete mechanism of c-Abl activation and insights into critical parameters controlling at the atomic level c-Abl inactivation, leading us to propose possible strategies to counter reemergence of drug resistance.

Mechanistic Studies on the Stereoselectivity of FFAR1 Modulators

Free fatty acid receptor 1 (FFAR1) is a potential therapeutic target for the treatment of type 2 diabetes (T2D). It has been validated that agonists targeting FFAR1 can achieve the initial therapeutic endpoints of T2D, and the epimer agonists (R,S) AM-8596 can activate FFAR1 differently, with one acting as a partial agonist and the other as a full agonist. Up to now, the origin of the stereoselectivity of FFAR1 agonists remains elusive. In this work, we used molecular simulation methods to elucidate the mechanism of the stereoselectivity of the FFAR1 agonists (R)-AM-8596 and (S)-AM-8596. We found that the full agonist (R)-AM-8596 disrupts the residue interaction network around the receptor binding pocket and promotes the opening of the binding site for the G-protein, thereby resulting in the full activation of FFAR1. In contrast, the partial agonist (S)-AM-8596 forms stable electrostatic interactions with FFAR1, which stabilizes the residue network and hinders the conformational transition of the receptor. Our work thus clarifies the selectivity and underlying molecular activation mechanism of FFAR1 agonists.

Molecular dynamics simulations of the conformational plasticity in the active pocket of salt-inducible kinase 2 (SIK2) multi-state binding with bosutinib

The kinase domain is highly conserved among protein kinases 'in terms of both sequence and structure. Conformational rearrangements of the kinase domain are affected by the phosphorylation of residues and the binding of kinase inhibitors. Interestingly, the conformational rearrangement of the active pocket plays an important role in kinase activity and can be used to design novel kinase inhibitors. We characterized the conformational plasticity of the active pocket when bosutinib was bound to salt-inducible kinase 2 (SIK2) using homology modeling and molecular dynamics simulations. Ten different initial complex models were constructed using the Morph server, ranging from open to closed conformations of SIK2 binding with bosutinib. Our simulation showed that bosutinib binds SIK2 with up or down conformations of the P-loop and with all the conformations of the activation loop. In addition, the αC-helix conformation was induced by the conformation of the activation loop, and the salt bridge formed only with its open conformation. The binding affinity of the models was also determined using the molecular mechanics generalized Born surface area method. Bosutinib was found to form a strong binding model with SIK2 and hydrophobic interactions were the dominant factor. This discovery may help guide the design of novel SIK2 inhibitors.

Phosphorylation-Induced Conformational Dynamics and Inhibition of Janus Kinase 1 by Suppressors of Cytokine Signaling 1

The dysfunction of the JAK/STAT (Janus kinase/signal transducers and activators of transcription) pathway results in several pathophysiological conditions, including autoimmune disorders. The negative feedback regulators of the JAK/STAT signaling pathway, suppressors of cytokine signaling (SOCS), act as a natural inhibitor of JAK and inhibit aberrant activity. SOCS1 is the most potent member of the SOCS family, whose kinase inhibitory region targets the substrate-binding groove of JAK with high affinity and blocks the phosphorylation of JAK kinases. Overall, we performed an aggregate of 13 μs molecular dynamics simulations on the activation loop's three different phosphorylation (double and single) states. Results from our simulations show that the single Tyr¹⁰³⁴ phosphorylation could stabilize the JAK1/SOCS1 complex as well as the flexible activation segment. The phosphate-binding loop (P-loop) shows conformational variability at dual and single phosphorylated states. Principal component analysis and protein structure network (PSN) analysis reveal that the different phosphorylation states and SOCS1 binding induce intermediate inactive conformations of JAK1, which could be a better target for future JAK1 selective drug design. PSN analysis suggests that the com-pY1034 system is stabilized due to higher values of network hubs than the other two complex systems. Moreover, the binding free energy calculations suggest that pTyr¹⁰³⁴ states show a higher affinity toward SOCS1 than the dual and pTyr¹⁰³⁵ states. We believe that the mechanistic understanding of JAK1/SOCS1 complexation will aid future studies related to peptide inhibitors based on SOCS1.

The binding mechanism of NHWD-870 to bromodomain-containing protein 4 based on molecular dynamics simulations and free energy calculation

Bromodomain and extra-terminal (BET) proteins (BRD2, BRD3, BRD4, and BRDT) are epigenetic readers with tandem bromodomains.

Computational design of a cutinase for plastic biodegradation by mining molecular dynamics simulations trajectories

Polyethylene terephthalate (PET) has caused serious environmental concerns but could be degraded at high temperature. Previous studies show that cutinase from Thermobifida fusca KW3 (TfCut2) is capable of degrading and upcycling PET but is limited by its thermal stability. Nowadays, Popular protein stability modification methods rely mostly on the crystal structures, but ignore the fact that the actual conformation of protein is complex and constantly changing. To solve these problems, we developed a computational approach to design variants with enhanced protein thermal stability by mining Molecular Dynamics simulation trajectories using Machine Learning methods (MDL). The optimal classification accuracy and the optimal Pearson correlation coefficient of MDL model were 0.780 and 0.716, respectively. And we successfully designed variants with high ΔT_m values using MDL method. The optimal variant S121P/D174S/D204P had the highest ΔT_m value of 9.3 °C, and the PET degradation ratio increased by 46.42-fold at 70℃, compared with that of wild type TfCut2. These results deepen our understanding on the complex conformations of proteins and may enhance the plastic recycling and sustainability at glass transition temperature.

PSNtools for standalone and web-based structure network analyses of conformational ensembles

Structure graphs, in which interacting amino acids/nucleotides correspond to linked nodes, represent cutting-edge tools to investigate macromolecular function.

The graph-based approach defined as Protein Structure Network (PSN) was initially implemented in the Wordom software and subsequently in the webPSN server. PSNs are computed either on a molecular dynamics (MD) trajectory (PSN-MD) or on a single structure. In the latter case, information on atomic fluctuations is inferred from the Elastic Network Model-Normal Mode Analysis (ENM-NMA) (PSN-ENM). While Wordom performs both PSN-ENM and PSN-MD analyses but without output post-processing, the webPSN server performs only single-structure PSN-EMN but assisting the user in input setup and output analysis.

Here we release for the first time the standalone software PSNtools, which allows calculation and post-processing of PSN analyses carried out either on single structures or on conformational ensembles. Relevant unique and novel features of PSNtools are either comparisons of two networks or computations of consensus networks on sets of homologous/analogous macromolecular structures or conformational ensembles. Network comparisons and consensus serve to infer differences in functionally different states of the same system or network-based signatures in groups of bio-macromolecules sharing either the same functionality or the same fold.

In addition to the new software, here we release also an updated version of the webPSN server, which allows performing an interactive graphical analysis of PSN-MD, following the upload of the PSNtools output.

PSNtools, the auxiliary binary version of Wordom software, and the WebPSN server are freely available at http://webpsn.hpc.unimo.it/wpsn3.php.

Unraveling the Molecular Mechanism of Recognition of Human Interferon-Stimulated Gene Product 15 by Coronavirus Papain-Like Proteases: A Multiscale Simulation Study

The papain-like protease (PLpro) of the coronavirus (CoV) family plays an essential role in processing the viral polyprotein and immune evasion. Additional proteolytic activities of PLpro include deubiquitination and deISGylation, which can reverse the post-translational modification of cellular proteins conjugated with ubiquitin or (Ub) or Ub-like interferon-stimulated gene product 15 (ISG15). These activities regulate innate immune responses against viral infection. Thus, PLpro is a potential antiviral target. Here, we have described the structural and energetic basis of recognition of PLpro by the human ISG15 protein (hISG15) using atomistic molecular dynamics simulation across the CoV family, i.e., MERS-CoV (MCoV), SARS-CoV (SCoV), and SARS-CoV-2 (SCoV2). The cumulative simulation length for all trajectories was 32.0 μs. In the absence of the complete crystal structure of complexes, protein-protein docking was used. A mutation (R167E) was introduced across all three PLpro to study the effect of mutation on the protein-protein binding. Our study reveals that the apo-ISG15 protein remains closed while it adopts an open conformation when bound to PLpro, although the degree of openness varies across the CoV family. The binding free energy analysis suggests that hISG15 binds more strongly with SCoV2-PLpro compared to SCoV or MCoV. The intermolecular electrostatic interaction drives the hISG15-PLpro complexation. Our study showed that SCoV or MCoV-PLpro binds more strongly with the C-domain of hISG15, while SCoV2-PLpro binds more favorably the N-domain of hISG15. Overall, our study explains the molecular basis of differential deISGylating activities of PLpro among the CoV family and the specificity of SCoV2-PLpro toward hISG15.

Exploring the stability of inhibitor binding to SIK2 using molecular dynamics simulation and binding free energy calculation

Salt inducible kinase 2 (SIK2) is a calcium/calmodulin-dependent protein kinase-like kinase that is implicated in a variety of biological phenomena, including cellular metabolism, growth, and apoptosis. SIK2 is the key target for various cancers, including ovarian, breast, prostate, and lung cancers. Although potent inhibitors of SIK2 are being developed, their binding stability and functional role are not presently known. In this work, we studied the detailed interactions between SIK2 and four of its inhibitors, HG-9-91-01, KIN112, MRT67307, and MRT199665, using molecular docking, molecular dynamics simulation, binding free energy calculation, and interaction fingerprint analysis. Intermolecular interactions revealed that HG-9-91-01 and KIN112 have stronger interactions with SIK2 than those of MRT199665 and MRT67307. The key residues involved in binding with SIK2 are conserved among all four inhibitors. Our results explain the detailed interaction of SIK2 with its inhibitors at the molecular level, thus paving the way for the development of targeted efficient anti-cancer drugs.

Protein conformational switch discerned via network centrality properties

Network analysis has emerged as a powerful tool for examining structural biology systems. The spatial organization of the components of a biomolecular structure has been rendered as a graph representation and analyses have been performed to deduce the biophysical and mechanistic properties of these components. For proteins, the analysis of protein structure networks (PSNs), especially via network centrality measurements and cluster coefficients, has led to identifying amino acid residues that play key functional roles and classifying amino acid residues in general. Whether these network properties examined in various studies are sensitive to subtle (yet biologically significant) conformational changes remained to be addressed. Here, we focused on four types of network centrality properties (betweenness, closeness, degree, and eigenvector centralities) for conformational changes upon ligand binding of a sensor protein (constitutive androstane receptor) and an allosteric enzyme (ribonucleotide reductase). We found that eigenvector centrality is sensitive and can distinguish salient structural features between protein conformational states while other centrality measures, especially closeness centrality, are less sensitive and rather generic with respect to the structural specificity. We also demonstrated that an ensemble-informed, modified PSN with static edges removed (which we term PSN*) has enhanced sensitivity at discerning structural changes.

Elucidation of Structural Determinants Delineates the Residues Playing Key Roles in Differential Dynamics and Selective Inhibition of Sirt1-3

Sirt1-3 are the most studied sirtuins, playing a key role in caloric-dependent epigenetic modifications. Since they are localized in distinct cellular compartments and act differently under various pathological conditions, selective inhibition would be a promising strategy to understand their biological function and to discover effective therapeutics. Here, sirtuin's inhibitor Ex527* is used as a probe to speculate the possible root cause of selective inhibition and differential structural dynamics of Sirt1-3. Comparative energetics and mutational studies revealed the criticality of residues I279 and I316 for the Sirt1 selectivity toward Ex527*. Furthermore, essential dynamics and residue network analysis revealed that the side-chain reorientation in residue F190 due to nonconserved residue Y191 played a major role in the formation of an extended selectivity pocket in Sirt2. These changes at the dynamical and residual level, which impact the internal wiring significantly, might help in rationally designing selective inhibitors against Sirt1-3.

Surveying the Side-Chain Network Approach to Protein Structure and Dynamics: The SARS-CoV-2 Spike Protein as an Illustrative Case

Network theory-based approaches provide valuable insights into the variations in global structural connectivity between different dynamical states of proteins. Our objective is to review network-based analyses to elucidate such variations, especially in the context of subtle conformational changes. We present technical details of the construction and analyses of protein structure networks, encompassing both the non-covalent connectivity and dynamics. We examine the selection of optimal criteria for connectivity based on the physical concept of percolation. We highlight the advantages of using side-chain-based network metrics in contrast to backbone measurements. As an illustrative example, we apply the described network approach to investigate the global conformational changes between the closed and partially open states of the SARS-CoV-2 spike protein. These conformational changes in the spike protein is crucial for coronavirus entry and fusion into human cells. Our analysis reveals global structural reorientations between the two states of the spike protein despite small changes between the two states at the backbone level. We also observe some differences at strategic locations in the structures, correlating with their functions, asserting the advantages of the side-chain network analysis. Finally, we present a view of allostery as a subtle synergistic-global change between the ligand and the receptor, the incorporation of which would enhance drug design strategies.

webPSN v2.0: a webserver to infer fingerprints of structural communication in biomacromolecules

A mixed Protein Structure Network (PSN) and Elastic Network Model-Normal Mode Analysis (ENM-NMA)-based strategy (i.e. PSN-ENM) was developed to investigate structural communication in bio-macromolecules. Protein Structure Graphs (PSGs) are computed on a single structure, whereas information on system dynamics is supplied by ENM-NMA. The approach was implemented in a webserver (webPSN), which was significantly updated herein. The webserver now handles both proteins and nucleic acids and relies on an internal upgradable database of network parameters for ions and small molecules in all PDB structures. Apart from the radical restyle of the server and some changes in the calculation setup, other major novelties concern the possibility to: a) compute the differences in nodes, links, and communication pathways between two structures (i.e. network difference) and b) infer links, hubs, communities, and metapaths from consensus networks computed on a number of structures. These new features are useful to identify commonalties and differences between two different functional states of the same system or structural-communication signatures in homologous or analogous systems. The output analysis relies on 3D-representations, interactive tables and graphs, also available for download. Speed and accuracy make this server suitable to comparatively investigate structural communication in large sets of bio-macromolecular systems. URL: http://webpsn.hpc.unimore.it.

Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning

Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the "second secret of life." The fundamental biological importance and complexity of these processes require a multi-faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of allosteric modulators. The unifying theme and overarching goal of allosteric regulation studies in recent years have been integration between emerging experiment and computational approaches and technologies to advance quantitative characterization of allosteric mechanisms in proteins. Despite significant advances, the quantitative characterization and reliable prediction of functional allosteric states, interactions, and mechanisms continue to present highly challenging problems in the field. In this review, we discuss simulation-based multiscale approaches, experiment-informed Markovian models, and network modeling of allostery and information-theoretical approaches that can describe the thermodynamics and hierarchy allosteric states and the molecular basis of allosteric mechanisms. The wealth of structural and functional information along with diversity and complexity of allosteric mechanisms in therapeutically important protein families have provided a well-suited platform for development of data-driven research strategies. Data-centric integration of chemistry, biology and computer science using artificial intelligence technologies has gained a significant momentum and at the forefront of many cross-disciplinary efforts. We discuss new developments in the machine learning field and the emergence of deep learning and deep reinforcement learning applications in modeling of molecular mechanisms and allosteric proteins. The experiment-guided integrated approaches empowered by recent advances in multiscale modeling, network science, and machine learning can lead to more reliable prediction of allosteric regulatory mechanisms and discovery of allosteric modulators for therapeutically important protein targets.

Network analysis of hydroxymethylbilane synthase dynamics

Hydroxymethylbilane synthase (HMBS) is one of the key enzymes of the heme biosynthetic pathway that catalyzes porphobilinogen to form the linear tetrapyrrole 1-hydroxymethylbilane through four intermediate steps. Mutations in the human HMBS (hHMBS) can lead to acute intermittent porphyria (AIP), a lethal metabolic disorder. The molecular basis of importance of the amino acid residues at the catalytic site of hHMBS has been well studied. However, the role of non-active site residues toward the activity of the enzyme and hence the association of their mutations with AIP is not known. Network-based analyses of protein structures provide a systems approach to understand the correlations of the residues through a series of inter-residue interactions. We analyzed the dynamic network representation of HMBS protein derived from five molecular dynamics trajectories corresponding to the five steps of pyrrole polymerization. We analyzed the network clusters for each stage and identified the amino acid residues and interactions responsible for the structural stability and catalytic function of the protein. The analysis of high betweenness nodes and interaction paths from the active site help in understanding the molecular basis of the effect of non-active site AIP-causing mutations on the catalytic activity.

Both intra and inter-domain interactions define the intrinsic dynamics and allosteric mechanism in DNMT1s

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Dynamics and allosteric potentials of the RFTS domain are proposed.

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Hinge sites located at the RFTS-CD interface are key regulators for inter-domain interactions.

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Network analysis reveals local allosteric networks and inter-domain communication pathways in DNMT1.

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A potential allosteric site at the TRD interface for DNMT1 is identified.

DNA methyltransferase 1 (DNMT1), a large multidomain enzyme, is believed to be involved in the passive transmission of genomic methylation patterns via methylation maintenance. Yet, the molecular mechanism of interaction networks underlying DNMT1 structures, dynamics, and its biological significance has yet to be fully characterized. In this work, we used an integrated computational strategy that combined coarse-grained and atomistic simulations with coevolution information and network modeling of the residue interactions for the systematic investigation of allosteric dynamics in DNMT1. The elastic network modeling has proposed that the high plasticity of RFTS has strengthened the correlated behaviors of DNMT1 structures through the hinge sites located at the RFTS-CD interface, which mediate the collective motions between domains. The perturbation response scanning (PRS) analysis combined with the enrichment analysis of disease mutations have further highlighted the allosteric potential of the RFTS domain. Furthermore, the long-range paths connect the intra-domain interactions through the TRD interface and catalytic interface, emphasizing some key inter-domain interactions as the bridges in the global allosteric regulation of DNMT1. The observed interplay between conserved intra-domain networks and dynamical plasticity encoded by inter-domain interactions provides insights into the intrinsic dynamics and functional evolution, as well as the design of allosteric modulators of DNMT1 based on the TRD interface.

Allosteric Activation of PI3Kα Results in Dynamic Access to Catalytically Competent Conformations

Class I phosphoinositide-3-kinases (PI3Ks) phosphorylate PIP₂ at its 3' inositol position to generate PIP₃, a second messenger that influences signaling cascades regulating cellular growth, survival, and proliferation. Previous studies have suggested that PI3Kα activation involves dislodging the p85α nSH2 domain from the p110α catalytic subunit by binding activated receptor tyrosine kinases. We carried out molecular dynamics simulations to determine, mechanistically and structurally, how PI3Kα conformations are influenced by physiological effectors and the nSH2 domain. We demonstrate that changes in protein dynamics mediated by allosteric regulation significantly increase the population of catalytically competent states without changing the enzyme ground-state structure. Furthermore, we demonstrate that modulation of active-site residue interactions with enzyme substrates can reciprocally influence nSH2 domain dynamics. Together, these results suggest that dynamic allostery plays a role in populating the catalytically competent conformation of PI3Kα, and provide a key platform for the design of novel chemotherapeutic PI3Kα inhibitors.

Dynamic properties of oligomers that characterize low-frequency normal modes

Dynamics of oligomeric proteins (one trimer, two tetramers, and one hexamer) were studied by elastic network model-based normal mode analysis to characterize their large-scale concerted motions. First, the oligomer motions were simplified by considering rigid-body motions of individual subunits. The subunit motions were resolved into three components in a cylindrical coordinate system: radial, tangential, and axial ones. Single component is dominant in certain normal modes. However, more than one component is mixed in others. The subunits move symmetrically in certain normal modes and as a standing wave with several wave nodes in others. Secondly, special attention was paid to atoms on inter-subunit interfaces. Their displacement vectors were decomposed into intra-subunit deformative (internal) and rigid-body (external) motions in individual subunits. The fact that most of the cosines of the internal and external motion vectors were negative for the atoms on the inter-subunit interfaces, indicated their opposing movements. Finally, a structural network of residues defined for each normal mode was investigated; the network was constructed by connecting two residues in contact and moving coherently. The centrality measure “betweenness” of each residue was calculated for the networks. Several residues with significantly high betweenness were observed on the inter-subunit interfaces. The results indicate that these residues are responsible for oligomer dynamics. It was also observed that amino acid residues with significantly high betweenness were more conservative. This supports that the betweenness is an effective characteristic for identifying an important residue in protein dynamics.

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

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

ProSNEx: a web-based application for exploration and analysis of protein structures using network formalism

ProSNEx (Protein Structure Network Explorer) is a web service for construction and analysis of Protein Structure Networks (PSNs) alongside amino acid flexibility, sequence conservation and annotation features. ProSNEx constructs a PSN by adding nodes to represent residues and edges between these nodes using user-specified interaction distance cutoffs for either carbon-alpha, carbon-beta or atom-pair contact networks. Different types of weighted networks can also be constructed by using either (i) the residue-residue interaction energies in the format returned by gRINN, resulting in a Protein Energy Network (PEN); (ii) the dynamical cross correlations from a coarse-grained Normal Mode Analysis (NMA) of the protein structure; (iii) interaction strength. Upon construction of the network, common network metrics (such as node centralities) as well as shortest paths between nodes and k-cliques are calculated. Moreover, additional features of each residue in the form of conservation scores and mutation/natural variant information are included in the analysis. By this way, tool offers an enhanced and direct comparison of network-based residue metrics with other types of biological information. ProSNEx is free and open to all users without login requirement at http://prosnex-tool.com.

Thermostability of Lipase A and Dynamic Communication Based on Residue Interaction Network

OBJECTIVE

Dynamic communication caused by mutation affects protein stability. The main objective of this study is to explore how mutations affect communication and to provide further insight into the relationship between heat resistance and signal propagation of Bacillus subtilis lipase (Lip A).

METHODS

The relationship between dynamic communication and Lip A thermostability is studied by long-time MD simulation and residue interaction network. The Dijkstra algorithm is used to get the shortest path of each residue pair. Subsequently, time-series frequent paths and spatio-temporal frequent paths are mined through an Apriori-like algorithm.

RESULTS

Time-series frequent paths show that the communication between residue pairs, both in wild-type lipase (WTL) and mutant 6B, becomes chaotic with an increase in temperature; however, more residues in 6B can maintain stable communication at high temperature, which may be associated with the structural rigidity. Furthermore, spatio-temporal frequent paths reflect the interactions among secondary structures. For WTL at 300K, β7, αC, αB, the longest loop, αA and αF contact frequently. The 310-helix between β3 and αA is penetrated by spatio-temporal frequent paths. At 400K, only αC can be frequently transmitted. For 6B, when at 300K, αA and αF are in more tight contact by spatio-temporal frequent paths though I157M and N166Y. Moreover, the rigidity of the active site His156 and the C-terminal of Lip A are increased, as reflected by the spatio-temporal frequent paths. At 400K, αA and αF, 310-helix between β3 and αA, the longest loop, and the loop where the active site Asp133 is located can still maintain stable communication.

CONCLUSION

From the perspective of residue dynamic communication, it is obviously found that mutations cause changes in interactions between secondary structures and enhance the rigidity of the structure, contributing to the thermal stability and functional activity of 6B.

Atomistic Modeling of the ABL Kinase Regulation by Allosteric Modulators Using Structural Perturbation Analysis and Community-Based Network Reconstruction of Allosteric Communications

In this work, we have examined the molecular mechanisms of allosteric regulation of the ABL tyrosine kinase at the atomic level. Atomistic modeling of the ABL complexes with a panel of allosteric modulators has been performed using a combination of molecular dynamics simulations, structural residue perturbation scanning, and a novel community analysis of the residue interaction networks. Our results have indicated that allosteric inhibitors and activators may exert a differential control on allosteric signaling between the kinase binding sites and functional regions. While the inhibitor binding can strengthen the closed ABL state and induce allosteric communications directed from the allosteric pocket to the ATP binding site, the DPH activator may induce a more dynamic open form and activate allosteric couplings between the ATP and substrate binding sites. By leveraging a network-centric theoretical framework, we have introduced a novel community analysis method and global topological parameters that have unveiled the hierarchical modularity and the intercommunity bridging sites in the residue interaction network. We have found that allosteric functional hotspots responsible for the kinase regulation may serve the intermodular bridges in the global interaction network. The central conclusion from this analysis is that the regulatory switch centers play a fundamental role in the modular network organization of ABL as the unique intercommunity bridges that connect the SH2 and SH3 domains with the catalytic core into a functional kinase assembly. The hierarchy of network organization in the ABL regulatory complexes may allow for the synergistic action of dense intercommunity links required for the robust signal transfer in the catalytic core and sparse network bridges acting as the regulatory control points that orchestrate allosteric transitions between the inhibited and active kinase forms.

New insights into the structural dynamics of the kinase JNK3

In this work, we study the dynamics and the energetics of the all-atom structure of a neuronal-specific serine/threonine kinase c-Jun N-terminal kinase 3 (JNK3) in three states: unphosphorylated, phosphorylated, and ATP-bound phosphorylated. A series of 2 µs atomistic simulations followed by a conformational landscape mapping and a principal component analysis supports the mechanistic understanding of the JNK3 inactivation/activation process and also indicates key structural intermediates. Our analysis reveals that the unphosphorylated JNK3 undergoes the ‘open-to-closed’ movement via a two-step mechanism. Furthermore, the phosphorylation and ATP-binding allow the JNK3 kinase to attain a fully active conformation. JNK3 is a widely studied target for small-drugs used to treat a variety of neurological disorders. We believe that the mechanistic understanding of the large-conformational changes upon the activation of JNK3 will aid the development of novel targeted therapeutics.

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.

Allosteric Communication Networks in Proteins Revealed through Pocket Crosstalk Analysis

The detection and characterization of binding pockets and allosteric communication in proteins is crucial for studying biological regulation and performing drug design. Nowadays, ever-longer molecular dynamics (MD) simulations are routinely used to investigate the spatiotemporal evolution of proteins. Yet, there is no computational tool that can automatically detect all the pockets and potential allosteric communication networks along these extended MD simulations. Here, we use a novel and fully automated algorithm that examines pocket formation, dynamics, and allosteric communication embedded in microsecond-long MD simulations of three pharmaceutically relevant proteins, namely, PNP, A2A, and Abl kinase. This dynamic analysis uses pocket crosstalk, defined as the temporal exchange of atoms between adjacent pockets, along the MD trajectories as a fingerprint of hidden allosteric communication networks. Importantly, this study indicates that dynamic pocket crosstalk analysis provides new mechanistic understandings on allosteric communication networks, enriching the available experimental data. Thus, our results suggest the prospective use of this unprecedented dynamic analysis to characterize transient binding pockets for structure-based drug design.

The molecular mechanism behind resistance of the kinase FLT3 to the inhibitor quizartinib

Fms-like tyrosine kinase 3 (FLT3) is a receptor tyrosine kinase that is a drug target for leukemias. Several potent inhibitors of FLT3 exist, and bind to the inactive form of the enzyme. Unfortunately, resistance due to mutations in the kinase domain of FLT3 limits the therapeutic effects of these inhibitors. As in many other cases, it is not straightforward to explain why certain mutations lead to drug resistance. Extensive fully atomistic molecular dynamics (MD) simulations of FLT3 were carried out with an inhibited form (FLT-quizartinib complex), a free (apo) form, and an active conformation. In all cases, both the wild type (wt) proteins and two resistant mutants (D835F and Y842H) were studied. Analysis of the simulations revealed that impairment of protein-drug interactions cannot explain the resistance mutations in question. Rather, it appears that the active state of the mutant forms is perturbed by the mutations. It is therefore likely that perturbation of deactivation of the protein (which is necessary for drug binding) is responsible for the reduced affinity of the drug to the mutants. Importantly, this study suggests that it is possible to explain the source of resistance by mutations in FLT3 by an analysis of unbiased MD simulations.

Selective inhibition mechanism of RVX-208 to the second bromodomain of bromo and extraterminal proteins: insight from microsecond molecular dynamics simulations

RVX-208 is a recently reported inhibitor of bromo and extraterminal (BET) family proteins (including BRD2-4 and BRDT) with selectivity for the second bromodomain (BD2), currently in phase III clinical trials. Despite of its promising antitumor activity, due to the conserved folds of the first and second bromodomains (BD1 and BD2), the detailed selectivity mechanism of RVX-208 towards BD2 over BD1 is still unknown. To elucidate selective inhibition mechanism of RVX-208 to BD2, microsecond molecular dynamics simulations were performed in this study for BRD2-BD1, BRD2-BD2 and BRD4-BD1 with and without RVX-208, respectively. Binding free energy calculations show that there exists strongest interaction between RVX-208 and BRD2-BD2. Leu383 and Asn429 are two most important residues of BRD2-BD2 for binding to RVX-208. Structural network analysis reveals that RVX-208 can shorten the communication path of ZA and BC loops in BRD2-BD2 pocket, making pocket more suitable to accommodate RVX-208. Additionally, different behaviors of His433 (Asp160 in BRD2-BD1) and Val435 (Ile162 in BRD2-BD1) in BRD2-BD2 are key factors responsible for selective binding of RVX-208 to BRD2-BD2. The proposed selective inhibition mechanism of RVX-208 to BRD2-BD2 can be helpful for rational design of novel selective inhibitors of the second bromodomain of BET family proteins.

P2X7 receptor antagonism: Implications in diabetic retinopathy

Diabetic retinopathy (DR) is the most frequent complication of diabetes and one of leading causes of blindness worldwide. Early phases of DR are characterized by retinal pericyte loss mainly related to concurrent inflammatory process. Recently, an important link between P2X7 receptor (P2X7R) and inflammation has been demonstrated indicating this receptor as potential pharmacological target in DR. Here we first carried out an in silico molecular modeling study in order to characterize the allosteric pocket in P2X7R, and identify a suitable P2X7R antagonist through molecular docking. JNJ47965567 was identified as the hit compound in docking calculations, as well as for its absorption, distribution, metabolism and excretion (ADME) profile. As an in vitro model of early diabetic retinopathy, human retinal pericytes were exposed to high glucose (25mM, 48h) that caused a significant (p<0.05) release of IL-1β and LDH. The block of P2X7R by JNJ47965567 significantly (p<0.05) reverted the damage elicited by high glucose, detected as IL-1β and LDH release. Overall, our findings suggest that the P2X7R represents an attractive pharmacological target to manage the early phase of diabetic retinopathy, and the compound JNJ47965567 is a good template to discover other P2X7R selective antagonists.

Network-based modelling and percolation analysis of conformational dynamics and activation in the CDK2 and CDK4 proteins: dynamic and energetic polarization of the kinase lobes may determine divergence of the regulatory mechanisms

Network modeling and percolation analysis of conformational dynamics and energetics of regulatory mechanisms in cyclin-dependent kinases.

Exploring Molecular Mechanisms of Paradoxical Activation in the BRAF Kinase Dimers: Atomistic Simulations of Conformational Dynamics and Modeling of Allosteric Communication Networks and Signaling Pathways

The recent studies have revealed that most BRAF inhibitors can paradoxically induce kinase activation by promoting dimerization and enzyme transactivation. Despite rapidly growing number of structural and functional studies about the BRAF dimer complexes, the molecular basis of paradoxical activation phenomenon is poorly understood and remains largely hypothetical. In this work, we have explored the relationships between inhibitor binding, protein dynamics and allosteric signaling in the BRAF dimers using a network-centric approach. Using this theoretical framework, we have combined molecular dynamics simulations with coevolutionary analysis and modeling of the residue interaction networks to determine molecular determinants of paradoxical activation. We have investigated functional effects produced by paradox inducer inhibitors PLX4720, Dabrafenib, Vemurafenib and a paradox breaker inhibitor PLX7904. Functional dynamics and binding free energy analyses of the BRAF dimer complexes have suggested that negative cooperativity effect and dimer-promoting potential of the inhibitors could be important drivers of paradoxical activation. We have introduced a protein structure network model in which coevolutionary residue dependencies and dynamic maps of residue correlations are integrated in the construction and analysis of the residue interaction networks. The results have shown that coevolutionary residues in the BRAF structures could assemble into independent structural modules and form a global interaction network that may promote dimerization. We have also found that BRAF inhibitors could modulate centrality and communication propensities of global mediating centers in the residue interaction networks. By simulating allosteric communication pathways in the BRAF structures, we have determined that paradox inducer and breaker inhibitors may activate specific signaling routes that correlate with the extent of paradoxical activation. While paradox inducer inhibitors may facilitate a rapid and efficient communication via an optimal single pathway, the paradox breaker may induce a broader ensemble of suboptimal and less efficient communication routes. The central finding of our study is that paradox breaker PLX7904 could mimic structural, dynamic and network features of the inactive BRAF-WT monomer that may be required for evading paradoxical activation. The results of this study rationalize the existing structure-functional experiments by offering a network-centric rationale of the paradoxical activation phenomenon. We argue that BRAF inhibitors that amplify dynamic features of the inactive BRAF-WT monomer and intervene with the allosteric interaction networks may serve as effective paradox breakers in cellular environment.

NAPS: Network Analysis of Protein Structures

Traditionally, protein structures have been analysed by the secondary structure architecture and fold arrangement. An alternative approach that has shown promise is modelling proteins as a network of non-covalent interactions between amino acid residues. The network representation of proteins provide a systems approach to topological analysis of complex three-dimensional structures irrespective of secondary structure and fold type and provide insights into structure-function relationship. We have developed a web server for network based analysis of protein structures, NAPS, that facilitates quantitative and qualitative (visual) analysis of residue-residue interactions in: single chains, protein complex, modelled protein structures and trajectories (e.g. from molecular dynamics simulations). The user can specify atom type for network construction, distance range (in Å) and minimal amino acid separation along the sequence. NAPS provides users selection of node(s) and its neighbourhood based on centrality measures, physicochemical properties of amino acids or cluster of well-connected residues (k-cliques) for further analysis. Visual analysis of interacting domains and protein chains, and shortest path lengths between pair of residues are additional features that aid in functional analysis. NAPS support various analyses and visualization views for identifying functional residues, provide insight into mechanisms of protein folding, domain-domain and protein-protein interactions for understanding communication within and between proteins. URL:http://bioinf.iiit.ac.in/NAPS/.

Advanced molecular dynamics simulation methods for kinase drug discovery

Interest in the application of molecular dynamics (MD) simulations has increased in the field of protein kinase (PK) drug discovery. PKs belong to an important drug target class because they are directly involved in a number of diseases, including cancer. MD methods simulate dynamic biological and chemical events at an atomic level. This information can be combined with other in silico and experimental methods to efficiently target selected receptors. In this review, we present common and advanced methods of MD simulations and we focus on the recent applications of MD-based methodologies that provided significant insights into the elucidation of biological mechanisms involving PKs and into the discovery of novel kinase inhibitors.

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

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

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