Machine learning and protein allostery.

The fundamental biological importance and complexity of allosterically regulated proteins stem from their central role in signal transduction and cellular processes. Recently, machine-learning approaches have been developed and actively deployed to facilitate theoretical and experimental studies of protein dynamics and allosteric mechanisms. In this review, we survey recent developments in applications of machine-learning methods for studies of allosteric mechanisms, prediction of allosteric effects and allostery-related physicochemical properties, and allosteric protein engineering. We also review the applications of machine-learning strategies for characterization of allosteric mechanisms and drug design targeting SARS-CoV-2. Continuous development and task-specific adaptation of machine-learning methods for protein allosteric mechanisms will have an increasingly important role in bridging a wide spectrum of data-intensive experimental and theoretical technologies.

ß-sheets mediate the conformational change and allosteric signal transmission between the AsLOV2 termini.

Avena sativa phototropin 1 light-oxygen-voltage 2 domain (AsLOV2) is a model protein of Per-Arnt-Sim (PAS) superfamily, characterized by conformational changes in response to external environmental stimuli. This conformational change begins with the unfolding of the N-terminal A'α helix in the dark state followed by the unfolding of the C-terminal Jα helix. The light state is characterized by the unfolded termini and the subsequent modifications in hydrogen bond patterns. In this photoreceptor, ß-sheets are identified as crucial components for mediating allosteric signal transmission between the two termini. Through combined experimental and computational investigations, the Hß and Iß strands are recognized as the most critical and influential ß-sheets in AsLOV2's allosteric mechanism. To elucidate the role of these ß-sheets, we introduced 13 distinct mutations (F490L, N492A, L493A, F494L, H495L, L496F, Q497A, R500A, F509L, Q513A, L514A, D515V, and T517V) and conducted comprehensive molecular dynamics simulations. In-depth hydrogen bond analyses emphasized the role of two hydrogen bonds, Asn482-Leu453 and Gln479-Val520, in the observed distinct behaviors of L493A, L496F, Q497A, and D515V mutants. This illustrates the role of ß-sheets in the transmission of the allosteric signal upon the photoactivation of the light state.

Exploring and Learning the Universe of Protein Allostery Using Artificial Intelligence Augmented Biophysical and Computational Approaches.

Allosteric mechanisms are commonly employed regulatory tools used by proteins to orchestrate complex biochemical processes and control communications in cells. The quantitative understanding and characterization of allosteric molecular events are among major challenges in modern biology and require integration of innovative computational experimental approaches to obtain atomistic-level knowledge of the allosteric states, interactions, and dynamic conformational landscapes. The growing body of computational and experimental studies empowered by emerging artificial intelligence (AI) technologies has opened up new paradigms for exploring and learning the universe of protein allostery from first principles. In this review we analyze recent developments in high-throughput deep mutational scanning of allosteric protein functions; applications and latest adaptations of Alpha-fold structural prediction methods for studies of protein dynamics and allostery; new frontiers in integrating machine learning and enhanced sampling techniques for characterization of allostery; and recent advances in structural biology approaches for studies of allosteric systems. We also highlight recent computational and experimental studies of the SARS-CoV-2 spike (S) proteins revealing an important and often hidden role of allosteric regulation driving functional conformational changes, binding interactions with the host receptor, and mutational escape mechanisms of S proteins which are critical for viral infection. We conclude with a summary and outlook of future directions suggesting that AI-augmented biophysical and computer simulation approaches are beginning to transform studies of protein allostery toward systematic characterization of allosteric landscapes, hidden allosteric states, and mechanisms which may bring about a new revolution in molecular biology and drug discovery.

Novel Allosteric Effectors Targeting Human Transcription Factor TEAD.

The Hippo pathway is an evolutionary conserved signaling network involved in several cellular regulatory processes. Dephosphorylation and overexpression of Yes-associated proteins (YAPs) in the Hippo-off state are common in several types of solid tumors. YAP overexpression results in its nuclear translocation and interaction with transcriptional enhanced associate domain 1-4 (TEAD1-4) transcription factors. Covalent and non-covalent inhibitors have been developed to target several interaction sites between TEAD and YAP. The most targeted and effective site for these developed inhibitors is the palmitate-binding pocket in the TEAD1-4 proteins. Screening of a DNA-encoded library against the TEAD central pocket was performed experimentally to identify six new allosteric inhibitors. Inspired by the structure of the TED-347 inhibitor, chemical modification was performed on the original inhibitors by replacing secondary methyl amide with a chloromethyl ketone moiety. Various computational tools, including molecular dynamics, free energy perturbation, and Markov state model analysis, were employed to study the effect of ligand binding on the protein conformational space. Four of the six modified ligands were associated with enhanced allosteric communication between the TEAD4 and YAP1 domains indicated by the relative free energy perturbation to original molecules. Phe229, Thr332, Ile374, and Ile395 residues were revealed to be essential for the effective binding of the inhibitors.

Integration of network models and evolutionary analysis into high-throughput modeling of protein dynamics and allosteric regulation: theory, tools and applications.

Proteins are dynamical entities that undergo a plethora of conformational changes, accomplishing their biological functions. Molecular dynamics simulation and normal mode analysis methods have become the gold standard for studying protein dynamics, analyzing molecular mechanism and allosteric regulation of biological systems. The enormous amount of the ensemble-based experimental and computational data on protein structure and dynamics has presented a major challenge for the high-throughput modeling of protein regulation and molecular mechanisms. In parallel, bioinformatics and systems biology approaches including genomic analysis, coevolution and network-based modeling have provided an array of powerful tools that complemented and enriched biophysical insights by enabling high-throughput analysis of biological data and dissection of global molecular signatures underlying mechanisms of protein function and interactions in the cellular environment. These developments have provided a powerful interdisciplinary framework for quantifying the relationships between protein dynamics and allosteric regulation, allowing for high-throughput modeling and engineering of molecular mechanisms. Here, we review fundamental advances in protein dynamics, network theory and coevolutionary analysis that have provided foundation for rapidly growing computational tools for modeling of allosteric regulation. We discuss recent developments in these interdisciplinary areas bridging computational biophysics and network biology, focusing on promising applications in allosteric regulations, including the investigation of allosteric communication pathways, protein-DNA/RNA interactions and disease mutations in genomic medicine. We conclude by formulating and discussing future directions and potential challenges facing quantitative computational investigations of allosteric regulatory mechanisms in protein systems.

Landscape-Based Protein Stability Analysis and Network Modeling of Multiple Conformational States of the SARS-CoV-2 Spike D614G Mutant: Conformational Plasticity and Frustration-Induced Allostery as Energetic Drivers of Highly Transmissible Spike Variants.

The structural and functional studies of the SARS-CoV-2 spike protein variants revealed an important role of the D614G mutation that is shared across many variants of concern (VOCs), suggesting the effect of this mutation on the enhanced virus infectivity and transmissibility. The recent structural and biophysical studies provided important evidence about multiple conformational substates of the D614G spike protein. The development of a plausible mechanistic model that can explain the experimental observations from a more unified thermodynamic perspective is an important objective of the current work. In this study, we employed efficient and accurate coarse-grained simulations of multiple structural substates of the D614G spike trimers together with the ensemble-based mutational frustration analysis to characterize the dynamics signatures of the conformational landscapes. By combining the local frustration profiling of the conformational states with residue-based mutational scanning of protein stability and network analysis of allosteric interactions and communications, we determine the patterns of mutational sensitivity in the functional regions and sites of variants. We found that the D614G mutation may induce a considerable conformational adaptability of the open states in the SARS-CoV-2 spike protein without compromising the folding stability and integrity of the spike protein. The results suggest that the D614G mutant may employ a hinge-shift mechanism in which the dynamic couplings between the site of mutation and the interprotomer hinge modulate the interdomain interactions, global mobility change, and the increased stability of the open form. This study proposes that mutation-induced modulation of the conformational flexibility and energetic frustration at the interprotomer interfaces may serve as an efficient mechanism for allosteric regulation of the SARS-CoV-2 spike proteins.

Frustration-driven allosteric regulation and signal transmission in the SARS-CoV-2 spike omicron trimer structures: a crosstalk of the omicron mutation sites allosterically regulates tradeoffs of protein stability and conformational adaptability.

Dissecting the regulatory principles underlying function and activity of the SARS-CoV-2 spike protein at the atomic level is of paramount importance for understanding the mechanisms of virus transmissibility and immune escape. In this work, we introduce a hierarchical computational approach for atomistic modeling of allosteric mechanisms in the SARS-CoV-2 Omicron spike proteins and present evidence of a frustration-based allostery as an important energetic driver of the conformational changes and spike activation. By examining conformational landscapes and the residue interaction networks in the SARS-CoV-2 Omicron spike protein structures, we have shown that the Omicron mutational sites are dynamically coupled and form a central engine of the allosterically regulated spike machinery that regulates the balance and tradeoffs between conformational plasticity, protein stability, and functional adaptability. We have found that the Omicron mutational sites at the inter-protomer regions form regulatory hotspot clusters that control functional transitions between the closed and open states. Through perturbation-based modeling of allosteric interaction networks and diffusion analysis of communications in the closed and open spike states, we have quantified the allosterically regulated activation mechanism and uncover specific regulatory roles of the Omicron mutations. Atomistic reconstruction of allosteric communication pathways and kinetic modeling using Markov transient analysis reveal that the Omicron mutations form the inter-protomer electrostatic bridges that operate as a network of coupled regulatory switches that could control global conformational changes and signal transmission in the spike protein. The results of this study have revealed distinct and yet complementary roles of the Omicron mutation sites as a network of hotspots that enable allosteric modulation of structural stability and conformational changes which are central for spike activation and virus transmissibility.

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.

Comparative Perturbation-Based Modeling of the SARS-CoV-2 Spike Protein Binding with Host Receptor and Neutralizing Antibodies: Structurally Adaptable Allosteric Communication Hotspots Define Spike Sites Targeted by Global Circulating Mutations.

In this study, we used an integrative computational approach to examine molecular mechanisms and determine functional signatures underlying the role of functional residues in the SARS-CoV-2 spike protein that are targeted by novel mutational variants and antibody-escaping mutations. Atomistic simulations and functional dynamics analysis are combined with alanine scanning and mutational sensitivity profiling of the SARS-CoV-2 spike protein complexes with the ACE2 host receptor and the REGN-COV2 antibody cocktail(REG10987+REG10933). Using alanine scanning and mutational sensitivity analysis, we have shown that K417, E484, and N501 residues correspond to key interacting centers with a significant degree of structural and energetic plasticity that allow mutants in these positions to afford the improved binding affinity with ACE2. Through perturbation-based network modeling and community analysis of the SARS-CoV-2 spike protein complexes with ACE2, we demonstrate that E406, N439, K417, and N501 residues serve as effector centers of allosteric interactions and anchor major intermolecular communities that mediate long-range communication in the complexes. The results provide support to a model according to which mutational variants and antibody-escaping mutations constrained by the requirements for host receptor binding and preservation of stability may preferentially select structurally plastic and energetically adaptable allosteric centers to differentially modulate collective motions and allosteric interactions in the complexes with the ACE2 enzyme and REGN-COV2 antibody combination. This study suggests that the SARS-CoV-2 spike protein may function as a versatile and functionally adaptable allosteric machine that exploits the plasticity of allosteric regulatory centers to fine-tune response to antibody binding without compromising the activity of the spike protein.

Allosteric Control of Structural Mimicry and Mutational Escape in the SARS-CoV-2 Spike Protein Complexes with the ACE2 Decoys and Miniprotein Inhibitors: A Network-Based Approach for Mutational Profiling of Binding and Signaling.

We developed a computational framework for comprehensive and rapid mutational scanning of binding energetics and residue interaction networks in the SARS-CoV-2 spike protein complexes. Using this approach, we integrated atomistic simulations and conformational landscaping of the SARS-CoV-2 spike protein complexes with ensemble-based mutational screening and network modeling to characterize mechanisms of structure-functional mimicry and resilience toward mutational escape by the ACE2 protein decoy and de novo designed miniprotein inhibitors. A detailed analysis of structural plasticity of the SARS-CoV-2 spike proteins obtained from atomistic simulations of conformational landscapes and sequence-based profiling of the disorder propensities revealed the intrinsically flexible regions that harbor key functional sites targeted by circulating variants. The conservation of collective dynamics in the SARS-CoV-2 spike protein complexes showed that mutational escape positions are important for modulation of functional motions and that mutational changes in these sites can alter allosteric interaction networks. Through mutational profiling of binding and allosteric propensities in the SARS-CoV-2 spike protein complexes, we identified the key binding and regulatory hotspots that collectively determine functional response and resilience of miniproteins to mutational variants. The results suggest that binding affinities and allosteric signatures of the SARS-CoV-2 complexes can be determined by dynamic crosstalk between structurally stable regulatory centers and conformationally adaptable allosteric hotspots that collectively control the resilience toward mutational escape. This may underlie a mechanism in which moderate perturbations in the mutational escape positions can induce global allosteric changes and alter functional protein response by modulating signaling in the residue interaction networks.

Molecular Simulations and Network Modeling Reveal an Allosteric Signaling in the SARS-CoV-2 Spike Proteins.

The development of computational strategies for the quantitative characterization of the functional mechanisms of SARS-CoV-2 spike proteins is of paramount importance in efforts to accelerate the discovery of novel therapeutic agents and vaccines combating the COVID-19 pandemic. Structural and biophysical studies have recently characterized the conformational landscapes of the SARS-CoV-2 spike glycoproteins in the prefusion form, revealing a spectrum of stable and more dynamic states. By employing molecular simulations and network modeling approaches, this study systematically examined functional dynamics and identified the regulatory centers of allosteric interactions for distinct functional states of the wild-type and mutant variants of the SARS-CoV-2 prefusion spike trimer. This study presents evidence that the SARS-CoV-2 spike protein can function as an allosteric regulatory engine that fluctuates between dynamically distinct functional states. Perturbation-based modeling of the interaction networks revealed a key role of the cross-talk between the effector hotspots in the receptor binding domain and the fusion peptide proximal region of the SARS-CoV-2 spike protein. The results have shown that the allosteric hotspots of the interaction networks in the SARS-CoV-2 spike protein can control the dynamic switching between functional conformational states that are associated with virus entry to the host receptor. This study offers a useful and novel perspective on the underlying mechanisms of the SARS-CoV-2 spike protein through the lens of allosteric signaling as a regulatory apparatus of virus transmission that could open up opportunities for targeted allosteric drug discovery against SARS-CoV-2 proteins and contribute to the rapid response to the current and potential future pandemic scenarios.

Dynamic View of Allosteric Regulation in the Hsp70 Chaperones by J-Domain Cochaperone and Post-Translational Modifications: Computational Analysis of Hsp70 Mechanisms by Exploring Conformational Landscapes and Residue Interaction Networks.

Structural and biochemical studies of Hsp70 chaperones have provided a molecular view of the chaperone biochemical cycle by revealing a complex interplay between allosteric conformational states that controls the feedback loop between stimulation of the adenosinetriphosphatase (ATPase) activity and the substrate release. Allosteric regulation in the Hsp70 chaperones and efficient substrate targeting are mediated by J-domain cochaperones through a dynamic interaction network controlled by the regulatory hotspots. In the current work, we have simulated conformational landscapes and residue interaction networks in the open, closed, and cochaperone-bound DnaK structures. The results of this work have shown that J-domain can selectively enhance direction-specific signal propagation from the substrate-binding domain to the catalytic center and promote the structural environment required for ATP hydrolysis. By employing different network-based approaches, we examined the role and contribution of post-translational modification sites in allosteric regulation of human Hsp70. The central finding of this analysis indicated that conserved phosphorylation sites localized preferentially in the nucleotide-binding domain regions are often aligned with the allosteric control points and serve as effector centers in Hsp70. We have found that cooperation of post-translational modifications sites is based on the governing role of phosphorylation sites in dictating regulatory switching functions, whereas the bulk of acetylation sites can be involved in sensing the long-range signals and executing allosteric changes during the ATPase cycle. The results of this study highlight the important role of phosphorylation sites in exerting control over allosteric changes in Hsp70. The network-centric framework for the analysis of conformational dynamics and chaperone landscapes can explain a range of structural and functional experiments, providing a robust dynamic model of Hsp70 regulation by cochaperones and sites of post-translational modifications.

Allosteric Mechanism of the Hsp90 Chaperone Interactions with Cochaperones and Client Proteins by Modulating Communication Spines of Coupled Regulatory Switches: Integrative Atomistic Modeling of Hsp90 Signaling in Dynamic Interaction Networks.

Conformational landscapes of the Hsp90 chaperones have revealed that the intrinsic plasticity and functional adaptability of these molecular chaperones to a large cohort of cochaperones and a vast protein clientele can be regulated by a number of single switch points broadly dispersed in the chaperone structure. A detailed dynamic view of the allosteric changes mediated by conformational switches and the mechanism of their coupling during the ATPase cycle remains poorly understood and presents an important area of investigation. In this work, we employed integrative computational modeling that included evolutionary and coevolutionary analyses, experiment-guided protein docking and structure modeling, molecular simulations, energetic analysis, and network modeling to perform a systematic characterization of molecular and network signatures of conformational switch points and dissect their allosteric cross-talk in the Hsp90 complexes with cochaperones and client proteins. Using a hierarchical modeling of dynamic interaction networks, we show that the allosteric regulation of the Hsp90 interactions with p23 and Aha1 cochaperones and p53 client protein may be determined by the intramolecular communication "spines" of spatially separated and allosterically coupled regulatory switches. Using a battery of computational approaches, we examined how p23, Aha1, and p53 proteins can modulate signal transmission in the Hsp90 by exploiting communication spines of regulatory switches in the global allosteric network. This study proposes a community-chain mechanism of allosteric coupling between conformational switch centers and identifies key regulatory control points that mediate long-range interactions and communications in the Hsp90 chaperone. The results of this investigation provide novel insights into the nature of allosteric regulation mechanisms in the Hsp90 chaperones and offer a simple mechanistic model of the Hsp90 communications and adaptation to binding partners during the functional cycle.

Impact of Early Pandemic Stage Mutations on Molecular Dynamics of SARS-CoV-2 Mpro.

A new coronavirus (SARS-CoV-2) is a global threat to world health and economy. Its dimeric main protease (Mpro), which is required for the proteolytic cleavage of viral precursor proteins, is a good candidate for drug development owing to its conservation and the absence of a human homolog. Improving our understanding of Mpro behavior can accelerate the discovery of effective therapies to reduce mortality. All-atom molecular dynamics (MD) simulations (100 ns) of 50 mutant Mpro dimers obtained from filtered sequences from the GISAID database were analyzed using root-mean-square deviation, root-mean-square fluctuation, Rg, averaged betweenness centrality, and geometry calculations. The results showed that SARS-CoV-2 Mpro essentially behaves in a similar manner to its SAR-CoV homolog. However, we report the following new findings from the variants: (1) Residues GLY15, VAL157, and PRO184 have mutated more than once in SARS CoV-2; (2) the D48E variant has lead to a novel "TSEEMLN"" loop at the binding pocket; (3) inactive apo Mpro does not show signs of dissociation in 100 ns MD; (4) a non-canonical pose for PHE140 widens the substrate binding surface; (5) dual allosteric pockets coinciding with various stabilizing and functional components of the substrate binding pocket were found to display correlated compaction dynamics; (6) high betweenness centrality values for residues 17 and 128 in all Mpro samples suggest their high importance in dimer stability-one such consequence has been observed for the M17I mutation whereby one of the N-fingers was highly unstable. (7) Independent coarse-grained Monte Carlo simulations suggest a relationship between the rigidity/mutability and enzymatic function. Our entire approach combining database preparation, variant retrieval, homology modeling, dynamic residue network (DRN), relevant conformation retrieval from 1-D kernel density estimates from reaction coordinates to other existing approaches of structural analysis, and data visualization within the coronaviral Mpro is also novel and is applicable to other coronaviral proteins.

Comparative Dynamics and Functional Mechanisms of the CYP17A1 Tunnels Regulated by Ligand Binding.

As an important member of cytochrome P450 (CYP) enzymes, CYP17A1 is a dual-function monooxygenase with a critical role in the synthesis of many human steroid hormones, making it an attractive therapeutic target. The emerging structural information about CYP17A1 and the growing number of inhibitors for these enzymes call for a systematic strategy to delineate and classify mechanisms of ligand transport through tunnels that control catalytic activity. In this work, we applied an integrated computational strategy to different CYP17A1 systems with a panel of ligands to systematically study at the atomic level the mechanism of ligand-binding and tunneling dynamics. Atomistic simulations and binding free energy computations identify the dynamics of dominant tunnels and characterize energetic properties of critical residues responsible for ligand binding. The common transporting pathways including S, 3, and 2c tunnels were identified in CYP17A1 binding systems, while the 2c tunnel is a newly formed pathway upon ligand binding. We employed and integrated several computational approaches including the analysis of functional motions and sequence conservation, atomistic modeling of dynamic residue interaction networks, and perturbation response scanning analysis to dissect ligand tunneling mechanisms. The results revealed the hinge-binding and sliding motions as main functional modes of the tunnel dynamic, and a group of mediating residues as key regulators of tunnel conformational dynamics and allosteric communications. We have also examined and quantified the mutational effects on the tunnel composition, conformational dynamics, and long-range allosteric behavior. The results of this investigation are fully consistent with the experimental data, providing novel rationale to the experiments and offering valuable insights into the relationships between the structure and function of the channel networks and a robust atomistic model of activation mechanisms and allosteric interactions in CYP enzymes.

Interrogating Regulatory Mechanisms in Signaling Proteins by Allosteric Inhibitors and Activators: A Dynamic View Through the Lens of Residue Interaction Networks.

Computational studies of allosteric interactions have witnessed a recent renaissance fueled by the growing interest in modeling of the complex molecular assemblies and biological networks. Allosteric interactions in protein structures allow for molecular communication in signal transduction networks. In this chapter, we discuss recent developments in understanding of allosteric mechanisms and interactions of protein systems, particularly in the context of structural, functional, and computational studies of allosteric inhibitors and activators. Computational and experimental approaches and advances in understanding allosteric regulatory mechanisms are reviewed to provide a systematic and critical view of the current progress in the development of allosteric modulators and highlight most challenging questions in the field. The abundance and diversity of genetic, structural, and biochemical data underlies the complexity of mechanisms by which targeted and personalized drugs can combat mutational profiles in protein kinases. Structural and computational studies of protein kinases have generated in recent decade significant insights that allowed leveraging knowledge about conformational diversity and allosteric regulation of protein kinases in the design and discovery of novel kinase drugs. We discuss recent developments in understanding multilayered allosteric regulatory machinery of protein kinases and provide a systematic view of the current state in understanding molecular basis of allostery mediated by kinase inhibitors and activators. In conclusion, we highlight the current status and future prospects of computational biology approaches in bridging the basic science of protein kinases with the discovery of anticancer therapies.

Establishing Computational Approaches Towards Identifying Malarial Allosteric Modulators: A Case Study of Plasmodium falciparum Hsp70s.

Combating malaria is almost a never-ending battle, as Plasmodium parasites develop resistance to the drugs used against them, as observed recently in artemisinin-based combination therapies. The main concern now is if the resistant parasite strains spread from Southeast Asia to Africa, the continent hosting most malaria cases. To prevent catastrophic results, we need to find non-conventional approaches. Allosteric drug targeting sites and modulators might be a new hope for malarial treatments. Heat shock proteins (HSPs) are potential malarial drug targets and have complex allosteric control mechanisms. Yet, studies on designing allosteric modulators against them are limited. Here, we identified allosteric modulators (SANC190 and SANC651) against P. falciparum Hsp70-1 and Hsp70-x, affecting the conformational dynamics of the proteins, delicately balanced by the endogenous ligands. Previously, we established a pipeline to identify allosteric sites and modulators. This study also further investigated alternative approaches to speed up the process by comparing all atom molecular dynamics simulations and dynamic residue network analysis with the coarse-grained (CG) versions of the calculations. Betweenness centrality (BC) profiles for PfHsp70-1 and PfHsp70-x derived from CG simulations not only revealed similar trends but also pointed to the same functional regions and specific residues corresponding to BC profile peaks.

Dynamics-based community analysis and perturbation response scanning of allosteric interaction networks in the TRAP1 chaperone structures dissect molecular linkage between conformational asymmetry and sequential ATP hydrolysis.

Allosteric interactions of the Hsp90 chaperones with cochaperones and diverse protein clients can often exhibit distinct asymmetric features that determine regulatory mechanisms and cellular functions in many signaling networks. The recent crystal structures of the mitochondrial Hsp90 isoform TRAP1 in complexes with ATP analogs have provided first evidence of significant asymmetry in the closed dimerized state that triggers independent activity of the chaperone protomers, whereby preferential hydrolysis of the buckled protomer is followed by conformational flipping between protomers and hydrolysis of the second protomer. Despite significant insights in structural characterizations of the TRAP1 chaperone, the atomistic details and mechanics of allosteric interactions that couple sequential ATP hydrolysis with asymmetric conformational switching in the TRAP1 protomers remain largely unknown. In this work, we explored atomistic and coarse-grained simulations of the TRAP1 dimer structures in combination with the ensemble-based network modeling and perturbation response scanning of residue interaction networks to probe salient features underlying allosteric signaling mechanism. This study has revealed that key effector sites that orchestrate allosteric interactions occupy the ATP binding region and N-terminal interface of the buckled protomer, whereas the main sensors of allosteric signals that drive functional conformational changes during ATPase cycle are consolidated near the client binding region of the straight protomer, channeling the energy of ATP hydrolysis for client remodeling. The community decomposition analysis of the interaction networks and reconstruction of allosteric communication pathways in the TRAP1 structures have quantified mechanism of allosteric regulation, revealing control points and interactions that coordinate asymmetric switching during ATP hydrolysis.

Computational Analysis of Residue Interaction Networks and Coevolutionary Relationships in the Hsp70 Chaperones: A Community-Hopping Model of Allosteric Regulation and Communication.

Allosteric interactions in the Hsp70 proteins are linked with their regulatory mechanisms and cellular functions. Despite significant progress in structural and functional characterization of the Hsp70 proteins fundamental questions concerning modularity of the allosteric interaction networks and hierarchy of signaling pathways in the Hsp70 chaperones remained largely unexplored and poorly understood. In this work, we proposed an integrated computational strategy that combined atomistic and coarse-grained simulations with coevolutionary analysis and network modeling of the residue interactions. A novel aspect of this work is the incorporation of dynamic residue correlations and coevolutionary residue dependencies in the construction of allosteric interaction networks and signaling pathways. We found that functional sites involved in allosteric regulation of Hsp70 may be characterized by structural stability, proximity to global hinge centers and local structural environment that is enriched by highly coevolving flexible residues. These specific characteristics may be necessary for regulation of allosteric structural transitions and could distinguish regulatory sites from nonfunctional conserved residues. The observed confluence of dynamics correlations and coevolutionary residue couplings with global networking features may determine modular organization of allosteric interactions and dictate localization of key mediating sites. Community analysis of the residue interaction networks revealed that concerted rearrangements of local interacting modules at the inter-domain interface may be responsible for global structural changes and a population shift in the DnaK chaperone. The inter-domain communities in the Hsp70 structures harbor the majority of regulatory residues involved in allosteric signaling, suggesting that these sites could be integral to the network organization and coordination of structural changes. Using a network-based formalism of allostery, we introduced a community-hopping model of allosteric communication. Atomistic reconstruction of signaling pathways in the DnaK structures captured a direction-specific mechanism and molecular details of signal transmission that are fully consistent with the mutagenesis experiments. The results of our study reconciled structural and functional experiments from a network-centric perspective by showing that global properties of the residue interaction networks and coevolutionary signatures may be linked with specificity and diversity of allosteric regulation mechanisms.

Functional Role and Hierarchy of the Intermolecular Interactions in Binding of Protein Kinase Clients to the Hsp90-Cdc37 Chaperone: Structure-Based Network Modeling of Allosteric Regulation.

A fundamental role of the Hsp90-Cdc37 chaperone machinery in mediating conformational development and activation of diverse protein kinase clients is essential for signal transduction. Structural and biochemical studies have demonstrated that characterization of global conformational changes and allosteric interactions in the Hsp90-Cdc37-kinase complexes are central to our understanding of the mechanisms underlying kinase recruitment and processing by the Hsp90-Cdc37 chaperone. The recent cryo-electron microscopy structure of the Hsp90-Cdc37-Cdk4 kinase complex has provided a framework for dissecting regulatory principles underlying differentiation and recruitment of protein kinase clients to the chaperone machinery. In this work, we have characterized functional role and hierarchy of the intermolecular interactions in binding of protein kinase clients to the Hsp90-Cdc37 system. The network analysis revealed important relationships between structural stability, global centrality, and functional significance of regulatory hotspots in chaperone regulation and client recognition. A unique asymmetric topography of the intermolecular communities in the chaperone-kinase complex has quantified a central mediating role of Cdc37 in client recognition and allosteric regulation of the chaperone-kinase complex. Modeling of allosteric pathways in the chaperone complex has further clarified structural and energetic signatures of allosteric hotspots, particularly linking sites of post-translational modifications in Hsp90 with their role in allosteric interactions and client regulation. The results of this integrative computational study are compared with a wide range of structural, biochemical, and cell-based experiments, offering a robust network-centric model of allosteric regulation and client kinase recognition by the Hsp90-Cdc37 chaperone machine.