Generalized correlation for biomolecular dynamics

AlloViz: A tool for the calculation and visualisation of protein allosteric communication networks

Allostery, the presence of functional interactions between distant parts of proteins, is a critical concept in the field of biochemistry and molecular biology, particularly in the context of protein function and regulation. Understanding the principles of allosteric regulation is essential for advancing our knowledge of biology and developing new therapeutic strategies. This paper presents AlloViz, an open-source Python package designed to quantitatively determine, analyse, and visually represent allosteric communication networks on the basis of molecular dynamics (MD) simulation data. The software integrates well-known techniques for understanding allosteric properties simplifying the process of accessing, rationalising, and representing protein allostery and communication routes. It overcomes the inefficiency of having multiple methods with heterogeneous implementations and showcases the advantages of using MD simulations and multiple replicas to obtain statistically sound information on protein dynamics; it also enables the calculation of "consensus-like" scores aggregating methods that consider multiple structural aspects of allosteric networks. We demonstrate the features of AlloViz on two proteins: β-arrestin 1, a key player for regulating G protein-coupled receptor (GPCR) signalling, and the protein tyrosine phosphatase 1B, an important pharmaceutical target for allosteric inhibitors. The software includes comprehensive documentation and examples, tutorials, and a user-friendly graphical interface.

Allosteric pathways of SARS and SARS-CoV-2 spike protein identified by neural relational inference

The receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein must undergo a crucial conformational transition to invade human cells. It is intriguing that this transition is accompanied by a synchronized movement of the entire spike protein. Therefore, it is possible to design allosteric regulators targeting non-RBD but hindering the conformational transition of RBD. To understand the allosteric mechanism in detail, we establish a computational framework by integrating coarse-grained molecular dynamic simulations and a state-of-the-art neural network model called neural relational inference. Leveraging this framework, we have elucidated the allosteric pathway of the SARS-CoV-2 spike protein at the residue level and identified the molecular mechanisms involved in the transmission of allosteric signals. The movement of D614 is coupled with that of Q321. This interaction subsequently influences the movement of K528/K529, ultimately coupling with the movement of RBD during conformational changes. Mutations that weaken the interactions within this pathway naturally block the allosteric signal transmission, thereby modulating the conformational transitions. This observation also offers a rationale for the distinct allosteric patterns observed in the SARS-CoV spike protein. Our result provides a useful method for analyzing the dynamics of potential viral variants in the future.

Exploring transmembrane allostery in the MexB: DB08385 variant as a promising inhibitor-like candidate against Pseudomonas aeruginosa antibiotic resistance: a computational study

Pseudomonas aeruginosa, a formidable pathogen renowned for its antimicrobial resistance, poses a significant threat to immunocompromised individuals. In this regard, the MexAB-OprM efflux pump acts as a pivotal line of defense by extruding antimicrobials from bacterial cells. The inner membrane homotrimeric protein MexB captures antibiotics and translocates them into the outer membrane OprM channel protein connected through the MexA adaptor protein. Despite extensive efforts, competitive inhibitors targeting the tight (T) protomer of the MexB protein have not received FDA approval for medical use. Over the past few years, allosteric inhibitors have become popular as alternatives to the classical competitive inhibitor-based approach because of their higher specificity, lower dosage, and reduced toxicological effects. Hence, in this study, we unveiled the existence of a transmembrane allosteric binding pocket of MexB inspired by the recent discovery of an important allosteric inhibitor, BDM88855, for the homolog AcrB protein. While repurposing BDM88855 proved ineffective in controlling the MexB loose (L) protomer, our investigation identified a promising alternative: a chlorine-containing variant of DB08385 (2-Cl DB08385 or Variant 1). Molecular dynamics simulations, including binding free energy estimation coupled with heterogeneous dielectric implicit membrane model (implicit-membrane MM/PBSA), interaction entropy (IE) analysis and potential of mean force (PMF) calculation, demonstrated Variant 1's superior binding affinity to the transmembrane pocket, displaying the highest energy barrier in the ligand unbinding process. To elucidate the allosteric crosstalk between the transmembrane and porter domain of MexB, we employed the 'eigenvector centrality' measure in the linear mutual information obtained from the protein correlation network. Notably, this study confirmed the presence of an allosteric transmembrane site in the MexB L protomer. In addition to this, Variant 1 emerged as a potent regulator of allosteric crosstalk, inducing an 'O-L intermediate state' in the MexB L protomer. This induced state might hold the potential to diminish substrate intake into the access pocket, leading to the ineffective efflux of antibiotics.

Probing allosteric communication with combined molecular dynamics simulations and network analysis

Understanding the allosteric mechanisms within biomolecules involved in diseases is of paramount importance for drug discovery. Indeed, characterizing communication pathways and critical hotspots in signal transduction can guide a rational approach to leverage allosteric modulation for therapeutic purposes. While the atomistic signatures of allosteric processes are difficult to determine experimentally, computational methods can be a remarkable resource. Network analysis built on Molecular Dynamics simulation data is particularly suited in this respect and is gradually becoming of routine use. Herein, we collect the recent literature in the field, discussing different aspects and available options for network construction and analysis. We further highlight interesting refinements and extensions, eventually providing our perspective on this topic.

Evolutionary rewiring of the dynamic network underpinning allosteric epistasis in NS1 of influenza A virus

Viral proteins frequently mutate to evade or antagonize host innate immune responses, yet the impact of these mutations on the molecular energy landscape remains unclear. Epistasis, the intramolecular communications between mutations, often renders the combined mutational effects unpredictable. Nonstructural protein 1 (NS1) is a major virulence factor of the influenza A virus (IAV) that activates host PI3K by binding to its p85β subunit. Here, we present the deep analysis for the impact of evolutionary mutations in NS1 that emerged between the 1918 pandemic IAV strain and its descendant PR8 strain. Our analysis reveal how the mutations rewired inter-residue communications which underlies long-range allosteric and epistatic networks in NS1. Our findings show that PR8 NS1 binds to p85β with approximately 10-fold greater affinity than 1918 NS1 due to allosteric mutational effects. Notably, these mutations also exhibited long-range epistatic effects. NMR chemical shift perturbation and methyl-axis order parameter analyses revealed that the mutations induced long-range structural and dynamic changes in PR8 NS1, enhancing its affinity to p85β. Complementary MD simulations and graph-based network analysis uncover how these mutations rewire dynamic residue interaction networks, which underlies the long-range epistasis and allosteric effects on p85β-binding affinity. Significantly, we find that conformational dynamics of residues with high betweenness centrality play a crucial role in communications between network communities and are highly conserved across influenza A virus evolution. These findings advance our mechanistic understanding of the allosteric and epistatic communications between distant residues and provides insight into their role in the molecular evolution of NS1.

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.

Modeling allosteric mechanisms of eukaryotic type II topoisomerases

Type II topoisomerases (TopoIIs) are ubiquitous enzymes that are involved in crucial nuclear processes such as genome organization, chromosome segregation, and other DNA metabolic processes. These enzymes function as large, homodimeric complexes that undergo a complex cycle of binding and hydrolysis of two ATP molecules in their ATPase domains, which regulates the capture and passage of one DNA double-helix through a second, cleaved DNA molecule. This process requires the transmission of information about the state of the bound nucleotide over vast ranges in the TopoII complex. How this information is transmitted at the molecular level to regulate TopoII functions and how protein substitutions disrupt these mechanisms remains largely unknown. Here, we employed extensive microsecond-scale molecular dynamics simulations of the yeast TopoII enzyme in multiple nucleotide-bound states and with amino acid substitutions near both the N and C termini of the complex. Simulation results indicate that the ATPase domains are remarkably flexible on the sub-microsecond timescale and that these dynamics are modulated by the identity of the bound nucleotides and both local and distant amino acid substitutions. Network analyses point toward specific allosteric networks that transmit information about the hydrolysis cycle throughout the complex, which include residues in both the protein and the bound DNA molecule. Amino acid substitutions weaken many of these pathways. Together, our results provide molecular level details on how the TopoII catalytic cycle is controlled through nucleotide binding and hydrolysis and how mutations may disrupt this process.

Synergy and anti-cooperativity in allostery: Molecular dynamics study of WT and oncogenic KRAS-RGL1

This study focuses on investigating the effects of an oncogenic mutation (G12V) on the stability and interactions within the KRAS-RGL1 protein complex. The KRAS-RGL1 complex is of particular interest due to its relevance to KRAS-associated cancers and the potential for developing targeted drugs against the KRAS system. The stability of the complex and the allosteric effects of specific residues are examined to understand their roles as modulators of complex stability and function. Using molecular dynamics simulations, we calculate the mutual information, MI, between two neighboring residues at the interface of the KRAS-RGL1 complex, and employ the concept of interaction information, II, to measure the contribution of a third residue to the interaction between interface residue pairs. Negative II indicates synergy, where the presence of the third residue strengthens the interaction, while positive II suggests anti-cooperativity. Our findings reveal that MI serves as a dominant factor in determining the results, with the G12V mutation increasing the MI between interface residues, indicating enhanced correlations due to the formation of a more compact structure in the complex. Interestingly, although II plays a role in understanding three-body interactions and the impact of distant residues, it is not significant enough to outweigh the influence of MI in determining the overall stability of the complex. Nevertheless, II may nonetheless be a relevant factor to consider in future drug design efforts. This study provides valuable insights into the mechanisms of complex stability and function, highlighting the significance of three-body interactions and the impact of distant residues on the binding stability of the complex. Additionally, our findings demonstrate that constraining the fluctuations of a third residue consistently increases the stability of the G12V variant, making it challenging to weaken complex formation of the mutated species through allosteric manipulation. The novel perspective offered by this approach on protein dynamics, function, and allostery has potential implications for understanding and targeting other protein complexes involved in vital cellular processes. The results contribute to our understanding of the effects of oncogenic mutations on protein-protein interactions and provide a foundation for future therapeutic interventions in the context of KRAS-associated cancers and beyond.

SARS-CoV-2 Mpro oligomerization as a potential target for therapy

The main protease (Mpro) of SARS-CoV-2 is critical in the virus's replication cycle, facilitating the maturation of polyproteins into functional units. Due to its conservation across taxa, Mpro is a promising target for broad-spectrum antiviral drugs. Targeting Mpro with small molecule inhibitors, such as nirmatrelvir combined with ritonavir (Paxlovid™), which the FDA has approved for post-exposure treatment and prophylaxis, can effectively interrupt the replication process of the virus. A key aspect of Mpro's function is its ability to form a functional dimer. However, the mechanics of dimerization and its influence on proteolytic activity remain less understood. In this study, we utilized biochemical, structural, and molecular modelling approaches to explore Mpro dimerization. We evaluated critical residues, specifically Arg4 and Arg298, that are essential for dimerization. Our results show that changes in the oligomerization state of Mpro directly affect its enzymatic activity and dimerization propensity. We discovered a synergistic relationship influencing dimer formation, involving both intra- and intermolecular interactions. These findings highlight the potential for developing allosteric inhibitors targeting Mpro, offering promising new directions for therapeutic strategies.

Dynamically driven correlations in elastic net models reveal sequence of events and causality in proteins

An explicit analytic solution is given for the Langevin equation applied to the Gaussian Network Model of a protein subjected to both a random and a deterministic periodic force. Synchronous and asynchronous components of time correlation functions are derived and an expression for phase differences in the time correlations of residue pairs is obtained. The synchronous component enables the determination of dynamic communities within the protein structure. The asynchronous component reveals causality, where the time correlation function between residues i and j differs depending on whether i is observed before j or vice versa, resulting in directional information flow. Driver and driven residues in the allosteric process of cyclophilin A and human NAD-dependent isocitrate dehydrogenase are determined by a perturbation-scanning technique. Factors affecting phase differences between fluctuations of residues, such as network topology, connectivity, and residue centrality, are identified. Within the constraints of the isotropic Gaussian Network Model, our results show that asynchronicity increases with viscosity and distance between residues, decreases with increasing connectivity, and decreases with increasing levels of eigenvector centrality.

G Protein Activation Occurs via a Largely Universal Mechanism

Understanding how signaling proteins like G proteins are allosterically activated is a long-standing challenge with significant biological and medical implications. Because it is difficult to directly observe such dynamic processes, much of our understanding is based on inferences from a limited number of static snapshots of relevant protein structures, mutagenesis data, and patterns of sequence conservation. Here, we use computer simulations to directly interrogate allosteric coupling in six G protein α-subunit isoforms covering all four G protein families. To analyze this data, we introduce automated methods for inferring allosteric networks from simulation data and assessing how allostery is conserved or diverged among related protein isoforms. We find that the allosteric networks in these six G protein α subunits are largely conserved and consist of two pathways, which we call pathway-I and pathway-II. This analysis predicts that pathway-I is generally dominant over pathway-II, which we experimentally corroborate by showing that mutations to pathway-I perturb nucleotide exchange more than mutations to pathway-II. In the future, insights into unique elements of each G protein family could inform the design of isoform-specific drugs. More broadly, our tools should also be useful for studying allostery in other proteins and assessing the extent to which this allostery is conserved in related proteins.

Exploring the Super-Relaxed State of Human Cardiac β-Myosin by Molecular Dynamics Simulations

Human β-cardiac myosin plays a critical role in generating the mechanical forces necessary for cardiac muscle contraction. This process relies on a delicate dynamic equilibrium between the disordered relaxed state (DRX) and the super-relaxed state (SRX) of myosin. Disruptions in this equilibrium due to mutations can lead to heart diseases. However, the structural characteristics of SRX and the molecular mechanisms underlying pathogenic mutations have remained elusive. To bridge this gap, we conducted molecular dynamics simulations and free energy calculations to explore the conformational changes in myosin. Our findings indicate that the size of the phosphate-binding pocket can serve as a valuable metric for characterizing the transition from the DRX to SRX state. Importantly, we established a global dynamic coupling network within the myosin motor head at the residue level, elucidating how the pathogenic mutation E483K impacts the equilibrium between SRX and DRX through allosteric effects. Our work illuminates molecular details of SRX and offers valuable insights into disease treatment through the regulation of SRX.

Investigating the structural basis of piperine targeting AKT1 against prostate cancer through in vitro and molecular dynamics simulations

AkT1, significantly impacts many tumours cell functions, like transcription, apoptosis, glucose metabolism, cell proliferation, and cell migration. For tumours to develop and spread, aberrant activation of AKT1 is essential. Therefore, a major focus of molecularly targeted PCa treatment is AKT1. The present study investigates the effect of piperine compared to SDF using in-vitro studies, viz colony formation assay, comet assay and AKT1 gene expression studies using human PCa cell line PC3. A cluster of approximately at least 50 cells constitutes a colony. The clonogenic assay showed that the number and size of colonies significantly decreased when treated with compounds (SDF and piperine) in comparison to the untreated cells which effectively proliferated to form more colonies. Piperine treatment showed significant inhibition of colony formation than SDF. Effective genotoxicity was observed in piperine-treated PC3 cells with an increased Tail length of 120 µm and it was moderately observed in SDF with a Tail length of 30 µm treated on PC3 cells. The control group did not show any considerable genotoxicity with a Tail length of 6 µm. Our data, both in vitro and in silico, suggested that piperine would be a good starting point for developing novel drugs for the treatment of PCa. The downstream functions of Akt1 may be inhibited by these effects, which could impede the proliferation of PCa cells. High stability of the piperine-AKT1 complex was found by the MD simulation. Higher hydrophilic residues like Lys268 and Ser205 at the active pocket may be the cause of the binding stability. Overall, the observed results confirmed the anti-PCa effect of piperine by causing effective DNA damage and proved to be genotoxic in nature against the human PCa. These effects may impede the downstream activities of Akt1 and result in PCa cell growth regression.Communicated by Ramaswamy H. Sarma.

High-fidelity, hyper-accurate, and evolved mutants rewire atomic-level communication in CRISPR-Cas9

The high-fidelity (HF1), hyper-accurate (Hypa), and evolved (Evo) variants of the CRISPR-associated protein 9 (Cas9) endonuclease are critical tools to mitigate off-target effects in the application of CRISPR-Cas9 technology. The mechanisms by which mutations in recognition subdomain 3 (Rec3) mediate specificity in these variants are poorly understood. Here, solution nuclear magnetic resonance and molecular dynamics simulations establish the structural and dynamic effects of high-specificity mutations in Rec3, and how they propagate the allosteric signal of Cas9. We reveal conserved structural changes and dynamic differences at regions of Rec3 that interface with the RNA:DNA hybrid, transducing chemical signals from Rec3 to the catalytic His-Asn-His (HNH) domain. The variants remodel the communication sourcing from the Rec3 α helix 37, previously shown to sense target DNA complementarity, either directly or allosterically. This mechanism increases communication between the DNA mismatch recognition helix and the HNH active site, shedding light on the structure and dynamics underlying Cas9 specificity and providing insight for future engineering principles.

FMO-guided design of darunavir analogs as HIV-1 protease inhibitors

The prevalence of HIV-1 infection continues to pose a significant global public health issue, highlighting the need for antiretroviral drugs that target viral proteins to reduce viral replication. One such target is HIV-1 protease (PR), responsible for cleaving viral polyproteins, leading to the maturation of viral proteins. While darunavir (DRV) is a potent HIV-1 PR inhibitor, drug resistance can arise due to mutations in HIV-1 PR. To address this issue, we developed a novel approach using the fragment molecular orbital (FMO) method and structure-based drug design to create DRV analogs. Using combinatorial programming, we generated novel analogs freely accessible via an on-the-cloud mode implemented in Google Colab, Combined Analog generator Tool (CAT). The designed analogs underwent cascade screening through molecular docking with HIV-1 PR wild-type and major mutations at the active site. Molecular dynamics (MD) simulations confirmed the assess ligand binding and susceptibility of screened designed analogs. Our findings indicate that the three designed analogs guided by FMO, 19-0-14-3, 19-8-10-0, and 19-8-14-3, are superior to DRV and have the potential to serve as efficient PR inhibitors. These findings demonstrate the effectiveness of our approach and its potential to be used in further studies for developing new antiretroviral drugs.

Decoupling the dynamic mechanism revealed by FGFR2 mutation-induced population shift

The fibroblast growth factor receptor 2 (FGFR2) is a key component in cellular signaling networks, and its dysfunctional activation has been implicated in various diseases including cancer and developmental disorders. Mutations at the activation loop (A-loop) have been suggested to trigger an increased basal kinase activity. However, the molecular mechanism underlying this highly dynamic process has not been fully understood due to the limitation of static structural information. Here, we conducted multiple, large-scale Gaussian accelerated molecular dynamics simulations of five (K659E, K659N, K659M, K659Q, and K659T) FGFR2 mutants at the A-loop, and comprehensively analyzed the dynamic molecular basis of FGFR2 activation. The results quantified the population shift of each system, revealing that all mutants had a higher proportion of active-like states. Using Markov state models, we extracted the representative structure of different conformational states and identified key residues related to the increased kinase activity. Furthermore, community network analysis showed enhanced information connections in the mutants, highlighting the long-range allosteric communication between the A-loop and the hinge region. Our findings may provide insights into the dynamic mechanism for FGFR2 dysfunctional activation and allosteric drug discovery.Communicated by Ramaswamy H. Sarma.

Dynamic correlations: exact and approximate methods for mutual information

MOTIVATION

Proteins are dynamic entities that undergo conformational changes critical for their functions. Understanding the communication pathways and information transfer within proteins is crucial for elucidating allosteric interactions in their mechanisms. This study utilizes mutual information (MI) analysis to probe dynamic allostery. Using two cases, Ubiquitin and PLpro, we have evaluated the accuracy and limitations of different approximations including the exact anisotropic and isotropic models, multivariate Gaussian model, isotropic Gaussian model, and the Gaussian Network Model (GNM) in revealing allosteric interactions.

RESULTS

Our findings emphasize the required trajectory length for capturing accurate mutual information profiles. Long molecular dynamics trajectories, 1 ms for Ubiquitin and 100 µs for PLpro are used as benchmarks, assuming they represent the ground truth. Trajectory lengths of approximately 5 µs for Ubiquitin and 1 µs for PLpro marked the onset of convergence, while the multivariate Gaussian model accurately captured mutual information with trajectories of 5 ns for Ubiquitin and 350 ns for PLpro. However, the isotropic Gaussian model is less successful in representing the anisotropic nature of protein dynamics, particularly in the case of PLpro, highlighting its limitations. The GNM, however, provides reasonable approximations of long-range information exchange as a minimalist network model based on a single crystal structure. Overall, the optimum trajectory lengths for effective Gaussian approximations of long-time dynamic behavior depend on the inherent dynamics within the protein's topology. The GNM, by showcasing dynamics across relatively diverse time scales, can be used either as a standalone method or to gauge the adequacy of MD simulation lengths.

AVAILABILITY AND IMPLEMENTATION

Mutual information codes are available at https://github.com/kemaldemirtas/prc-MI.git.

Unveiling the RNA-mediated allosteric activation discloses functional hotspots in CRISPR-Cas13a

Cas13a is a recent addition to the CRISPR-Cas toolkit that exclusively targets RNA, which makes it a promising tool for RNA detection. It utilizes a CRISPR RNA (crRNA) to target RNA sequences and trigger a composite active site formed by two 'Higher Eukaryotes and Prokaryotes Nucleotide' (HEPN) domains, cleaving any solvent-exposed RNA. In this system, an intriguing form of allosteric communication controls the RNA cleavage activity, yet its molecular details are unknown. Here, multiple-microsecond molecular dynamics simulations are combined with graph theory to decipher this intricate activation mechanism. We show that the binding of a target RNA acts as an allosteric effector, by amplifying the communication signals over the dynamical noise through interactions of the crRNA at the buried HEPN1-2 interface. By introducing a novel Signal-to-Noise Ratio (SNR) of communication efficiency, we reveal critical allosteric residues-R377, N378, and R973-that rearrange their interactions upon target RNA binding. Alanine mutation of these residues is shown to select target RNA over an extended complementary sequence beyond guide-target duplex for RNA cleavage, establishing the functional significance of these hotspots. Collectively our findings offer a fundamental understanding of the Cas13a mechanism of action and pave new avenues for the development of highly selective RNA-based cleavage and detection tools.

Biased Signaling in Mutated Variants of β2-Adrenergic Receptor: Insights from Molecular Dynamics Simulations

The molecular basis of receptor bias in G protein-coupled receptors (GPCRs) caused by mutations that preferentially activate specific intracellular transducers over others remains poorly understood. Two experimentally identified biased variants of β2-adrenergic receptors (β2AR), a prototypical GPCR, are a triple mutant (T68F, Y132A, and Y219A) and a single mutant (Y219A); the former bias the receptor toward the β-arrestin pathway by disfavoring G protein engagement, while the latter induces G protein signaling explicitly due to selection against GPCR kinases (GRKs) that phosphorylate the receptor as a prerequisite of β-arrestin binding. Though rigorous characterizations have revealed functional implications of these mutations, the atomistic origin of the observed transducer selectivity is not clear. In this study, we investigated the allosteric mechanism of receptor bias in β2AR using microseconds of all-atom Gaussian accelerated molecular dynamics (GaMD) simulations. Our observations reveal distinct rearrangements in transmembrane helices, intracellular loop 3, and critical residues R1313.50 and Y3267.53 in the conserved motifs D(E)RY and NPxxY for the mutant receptors, leading to their specific transducer interactions. Moreover, partial dissociation of G protein from the receptor core is observed in the simulations of the triple mutant in contrast to the single mutant and wild-type receptor. The reorganization of allosteric communications from the extracellular agonist BI-167107 to the intracellular receptor-transducer interfaces drives the conformational rearrangements responsible for receptor bias in the single and triple mutants. The molecular insights into receptor bias of β2AR presented here could improve the understanding of biased signaling in GPCRs, potentially opening new avenues for designing novel therapeutics with fewer side-effects and superior efficacy.

A computational model for structural dynamics and reconfiguration of DNA assemblies

Recent advances in constructing a structured DNA assembly whose configuration can be dynamically changed in response to external stimuli have demanded the development of an efficient computational modeling approach to expedite its design process. Here, we present a computational framework capable of analyzing both equilibrium and non-equilibrium dynamics of structured DNA assemblies at the molecular level. The framework employs Langevin dynamics with structural and hydrodynamic finite element models that describe mechanical, electrostatic, base stacking, and hydrodynamic interactions. Equilibrium dynamic analysis for various problems confirms the solution accuracy at a near-atomic resolution, comparable to molecular dynamics simulations and experimental measurements. Furthermore, our model successfully simulates a long-time-scale close-to-open-to-close dynamic reconfiguration of the switch structure in response to changes in ion concentration. We expect that the proposed model will offer a versatile way of designing responsive and reconfigurable DNA machines.

Folding correctors can restore CFTR posttranslational folding landscape by allosteric domain-domain coupling

The folding/misfolding and pharmacological rescue of multidomain ATP-binding cassette (ABC) C-subfamily transporters, essential for organismal health, remain incompletely understood. The ABCC transporters core consists of two nucleotide binding domains (NBD1,2) and transmembrane domains (TMD1,2). Using molecular dynamic simulations, biochemical and hydrogen deuterium exchange approaches, we show that the mutational uncoupling or stabilization of NBD1-TMD1/2 interfaces can compromise or facilitate the CFTR(ABCC7)-, MRP1(ABCC1)-, and ABCC6-transporters posttranslational coupled domain-folding in the endoplasmic reticulum. Allosteric or orthosteric binding of VX-809 and/or VX-445 folding correctors to TMD1/2 can rescue kinetically trapped CFTR posttranslational folding intermediates of cystic fibrosis (CF) mutants of NBD1 or TMD1 by global rewiring inter-domain allosteric-networks. We propose that dynamic allosteric domain-domain communications not only regulate ABCC-transporters function but are indispensable to tune the folding landscape of their posttranslational intermediates. These allosteric networks can be compromised by CF-mutations, and reinstated by correctors, offering a framework for mechanistic understanding of ABCC-transporters (mis)folding.

Folding correctors can restore CFTR posttranslational folding landscape by allosteric domain-domain coupling

The folding/misfolding and pharmacological rescue of multidomain ATP-binding cassette (ABC) C-subfamily transporters, essential for organismal health, remain incompletely understood. The ABCC transporters core consists of two nucleotide binding domains (NBD1,2) and transmembrane domains (TMD1,2). Using molecular dynamic simulations, biochemical and hydrogen deuterium exchange approaches, we show that the mutational uncoupling or stabilization of NBD1-TMD1/2 interfaces can compromise or facilitate the CFTR(ABCC7)-, MRP1(ABCC1)-, and ABCC6-transporters posttranslational coupled domain-folding in the endoplasmic reticulum. Allosteric or orthosteric binding of VX-809 and/or VX-445 folding correctors to TMD1/2 can rescue kinetically trapped CFTR post-translational folding intermediates of cystic fibrosis (CF) mutants of NBD1 or TMD1 by global rewiring inter-domain allosteric-networks. We propose that dynamic allosteric domain-domain communications not only regulate ABCC-transporters function but are indispensable to tune the folding landscape of their post-translational intermediates. These allosteric networks can be compromised by CF-mutations, and reinstated by correctors, offering a framework for mechanistic understanding of ABCC-transporters (mis)folding.

One-Sentence Summary

Allosteric interdomain communication and its modulation are critical determinants of ABCC-transporters post-translational conformational biogenesis, misfolding, and pharmacological rescue.

The Molecular Mechanism of PSMα3 Aggregation: A New View

The emergence of a novel cross-α fibrillar structure, unlike the commonly observed sequence-independent cross-β one, of a 22-residue bacterial virulent amphipathic α-helical peptide of the phenol soluble modulin (PSM) family, PSMα3, with many deleterious effects on human life, has infused uncertainty to the paradigm of the intrinsically polymorphic, multivariate, multiphasic, and cross-sequence-cross-disease entangled protein aggregation landscape and hence on the identity of the therapeutic target. We, here, deconvolute the factors contributing to the genesis and hence the transition of lower to higher order aggregates of PSMα3 in its natural state and three noncanonical designed variants using conventional and enhanced sampling approach-based atomistic simulations. PSMα3 shows structural polymorphism with nominal α-helicity, substantial β-propensity, and dominant random-coil features, irrespective of the extent of aggregation. Moreover, the individual features of the overall amphipathicity operate alternatively depending on the extent and organization of aggregation; the dominance gradually moves from charged to hydrophobic residues with the progressive generation of higher order aggregates (dimer to oligomer to fibril) and with increasing orderedness of the self-assembled construct (oligomer vs dimer/fibril). Similarly, the contribution of interchain salt bridges decreases with increasing order of aggregation (dimer to oligomer to fibril). However, the intrachain salt bridges consistently display their role in all phases of aggregation. Such phase-independent features also include equivalent roles of electrostatic and van der Waals forces on intrachain interactions, sole contribution of van der Waals forces on interchain cross-talk, and negligible peptide-water relationship. Finally, we propose a conjugate peptide-based aggregation suppressor having a single-point proline mutation.

High-Fidelity, Hyper-Accurate, and Evolved Mutants Rewire Atomic Level Communication in CRISPR-Cas9

The Cas9-HF1, HypaCas9, and evoCas9 variants of the Cas9 endonuclease are critical tools to mitigate off-target effects in the application of CRISPR-Cas9 technology. The mechanisms by which mutations in the Rec3 domain mediate specificity in these variants are poorly understood. Here, solution NMR and molecular dynamics simulations establish the structural and dynamic effects of high-specificity mutations in Rec3, and how they propagate the allosteric signal of Cas9. We reveal conserved structural changes and peculiar dynamic differences at regions of Rec3 that interface with the RNA:DNA hybrid, transducing chemical signals from Rec3 to the catalytic HNH domain. The variants remodel the communication sourcing from the Rec3 α-helix 37, previously shown to sense target DNA complementarity, either directly or allosterically. This mechanism increases communication between the DNA mismatch recognition helix and the HNH active site, shedding light on the structure and dynamics underlying Cas9 specificity and providing insight for future engineering principles.

New Insights into the Cooperativity and Dynamics of Dimeric Enzymes

A survey of protein databases indicates that the majority of enzymes exist in oligomeric forms, with about half of those found in the UniProt database being homodimeric. Understanding why many enzymes are in their dimeric form is imperative. Recent developments in experimental and computational techniques have allowed for a deeper comprehension of the cooperative interactions between the subunits of dimeric enzymes. This review aims to succinctly summarize these recent advancements by providing an overview of experimental and theoretical methods, as well as an understanding of cooperativity in substrate binding and the molecular mechanisms of cooperative catalysis within homodimeric enzymes. Focus is set upon the beneficial effects of dimerization and cooperative catalysis. These advancements not only provide essential case studies and theoretical support for comprehending dimeric enzyme catalysis but also serve as a foundation for designing highly efficient catalysts, such as dimeric organic catalysts. Moreover, these developments have significant implications for drug design, as exemplified by Paxlovid, which was designed for the homodimeric main protease of SARS-CoV-2.

Toward a Benchmark for Markov State Models: The Folding of HP35

Adopting a 300 μs long MD trajectory of the folding of villin headpiece (HP35) by D. E. Shaw Research, we recently constructed a Markov state model (MSM) based on inter-residue contacts. The model reproduces the folding time and predicts that the native basin and unfolded region consist of metastable substates that are structurally well-characterized. Recognizing the need to establish well-defined benchmark problems, we study to what extent and in what sense this MSM can be employed as a reference model. Hence, we test the robustness of the MSM by comparing it to models that use alternative combinations of features, dimensionality reduction methods, and clustering schemes. The study suggests some main characteristics of the folding of HP35 that should be reproduced by other competitive models. Moreover, the discussion reveals which parts of the MSM workflow matter most for the considered problem and illustrates the promises and pitfalls of state-based models for the interpretation of biomolecular simulations.

Examining the origins of observed terahertz modes from an optically pumped atomistic model protein in aqueous solution

The microscopic origins of terahertz (THz) vibrational modes in biological systems are an active and open area of current research. Recent experiments [Phys Rev X. 8, 031061 (2018)] have revealed the presence of a pronounced mode at ∼0.3 THz in fluorophore-decorated bovine serum albumin (BSA) protein in aqueous solution under nonequilibrium conditions induced by optical pumping. This result was heuristically interpreted as a collective elastic fluctuation originating from the activation of a low-frequency phonon mode. In this work, we show that the sub-THz spectroscopic response emerges in a statistically significant manner (> 2 σ ) from such collective behavior, illustrating how photoexcitation can alter specific THz vibrational modes. We revisit the theoretical analysis with proof-of-concept molecular dynamics that introduce optical excitations into the simulations. Using information theory techniques, we show that these excitations can give rise to a multiscale response involving two optically excited chromophores (tryptophans), other amino acids in the protein, ions, and water. Our results motivate new experiments and fully nonequilibrium simulations to probe these phenomena, as well as the refinement of atomistic models of Fröhlich condensates that are fundamentally determined by nonlinear interactions in biology.

RNA-mediated Allosteric Activation in CRISPR-Cas13a

Cas13a is a recent addition to the CRISPR-Cas toolkit that exclusively targets RNA, which makes it a promising tool for RNA detection. The protein uses a CRISPR RNA (crRNA) to target RNA sequences, which are cleaved by a composite active site formed by two 'Higher Eukaryotes and Prokaryotes Nucleotide' (HEPN) catalytic domains. In this system, an intriguing form of allosteric communication controls RNA cleavage activity, yet its molecular details are unknown. Here, multiple-microsecond molecular dynamics simulations are combined with graph theory and RNA cleavage assays to decipher this activation mechanism. We show that the binding of a target RNA acts as an allosteric effector of the spatially distant HEPN catalytic cleft, by amplifying the allosteric signals over the dynamical noise, that passes through the buried HEPN interface. Critical residues in this region - N378, R973, and R377 - rearrange their interactions upon target RNA binding, and alter allosteric signalling. Alanine mutation of these residues is experimentally shown to select target RNA over an extended complementary sequence beyond guide-target duplex, for RNA cleavage. Altogether, our findings offer a fundamental understanding of the Cas13a mechanism of action and pave new avenues for the development of more selective RNA-based cleavage and detection tools.

Unveiling the interdomain dynamics of type II DNA topoisomerase through all-atom simulations: Implications for understanding its catalytic cycle

Type IIA DNA topoisomerases are complex molecular nanomachines that manage topological states of the DNA molecule in the cell and play a crucial role in cellular processes such as cell division and transcription. They are also established targets of cancer chemotherapy. Starting from the available crystal structure of a fully catalytic topoisomerase IIA homodimer from Saccharomyces cerevisiae, we constructed three states of this molecular motor primarily changing the configurations of the DNA segment bound in the DNA gate and performed μs-long all-atom molecular simulations. A comprehensive analysis revealed a sliding motion within the DNA gate and a teamwork between the N-gate and DNA gate that may be associated with the necessary molecular events that allow passage of the T-segment of DNA. The observed movement of the ATPase dimer relative to the DNA domain was reflected in different interaction patterns between the K-loops of the transducer domain and the B-A-B form of the bound DNA. Based on the obtained results, we mapped simulated configurations to the structures in the proposed catalytic cycle through which type IIA topoisomerases exert their function and discussed the possible transition events. The results extend our understanding of the mechanism of action of type IIA topoisomerases and provide an atomistic interpretation of some of the observed features of these molecular motors.

Allosteric Determinants in High Temperature Requirement A Enzymes Are Conserved and Regulate the Population of Active Conformations

High temperature requirement A (HtrA) are allosterically regulated enzymes wherein effector binding to the PDZ domain triggers proteolytic activity. Yet, it remains unclear if the inter-residue network governing allostery is conserved across HtrA enzymes. Here, we investigated and identified the inter-residue interaction networks by molecular dynamics simulations on representative HtrA proteases, Escherichia coli DegS and Mycobacterium tuberculosis PepD, in effector-bound and free forms. This information was used to engineer mutations that could potentially perturb allostery and conformational sampling in a different homologue, M. tuberculosis HtrA. Mutations in HtrA perturbed allosteric regulation─a finding consistent with the hypothesis that the inter-residue interaction network is conserved across HtrA enzymes. Electron density from data collected on cryo-protected HtrA crystals revealed that mutations altered the topology of the active site. Ensemble models fitted into electron density calculated from room-temperature diffraction data showed that only a fraction of these models had a catalytically competent active site conformation alongside a functional oxyanion hole thus providing experimental evidence that these mutations influenced conformational sampling. Mutations at analogous positions in the catalytic domain of DegS perturbed the coupling between effector binding and proteolytic activity, thus confirming the role of these residues in the allosteric response. The finding that a perturbation in the conserved inter-residue network alters conformational sampling and the allosteric response suggests that an ensemble allosteric model best describes regulated proteolysis in HtrA enzymes.

Allosteric activation of vinculin by talin

The talin-vinculin axis is a key mechanosensing component of cellular focal adhesions. How talin and vinculin respond to forces and regulate one another remains unclear. By combining single-molecule magnetic tweezers experiments, Molecular Dynamics simulations, actin-bundling assays, and adhesion assembly experiments in live cells, we here describe a two-ways allosteric network within vinculin as a regulator of the talin-vinculin interaction. We directly observe a maturation process of vinculin upon talin binding, which reinforces the binding to talin at a rate of 0.03 s^-1. This allosteric transition can compete with force-induced dissociation of vinculin from talin only at forces up to 10 pN. Mimicking the allosteric activation by mutation yields a vinculin molecule that bundles actin and localizes to focal adhesions in a force-independent manner. Hence, the allosteric switch confines talin-vinculin interactions and focal adhesion build-up to intermediate force levels. The 'allosteric vinculin mutant' is a valuable molecular tool to further dissect the mechanical and biochemical signalling circuits at focal adhesions and elsewhere.

Phosphorylation at Ser65 modulates ubiquitin conformational dynamics

Ubiquitin phosphorylation at Ser65 increases the population of a rare C-terminally retracted (CR) conformation. Transition between the Major and CR ubiquitin conformations is critical for promoting mitochondrial degradation. The mechanisms by which the Major and CR conformations of Ser65-phosphorylated (pSer65) ubiquitin interconvert, however, remain unresolved. Here, we perform all-atom molecular dynamics simulations using the string method with swarms of trajectories to calculate the lowest free-energy path between these two conformers. Our analysis reveals the existence of a Bent intermediate in which the C-terminal residues of the β5 strand shift to resemble the CR conformation, while pSer65 retains contacts resembling the Major conformation. This stable intermediate was reproduced in well-tempered metadynamics calculations but was less stable for a Gln2Ala mutant that disrupts contacts with pSer65. Lastly, dynamical network modeling reveals that the transition from the Major to CR conformations involves a decoupling of residues near pSer65 from the adjacent β1 strand.

MDiGest: A Python package for describing allostery from molecular dynamics simulations

Many biological processes are regulated by allosteric mechanisms that communicate with distant sites in the protein responsible for functionality. The binding of a small molecule at an allosteric site typically induces conformational changes that propagate through the protein along allosteric pathways regulating enzymatic activity. Elucidating those communication pathways from allosteric sites to orthosteric sites is, therefore, essential to gain insights into biochemical processes. Targeting the allosteric pathways by mutagenesis can allow the engineering of proteins with desired functions. Furthermore, binding small molecule modulators along the allosteric pathways is a viable approach to target reactions using allosteric inhibitors/activators with temporal and spatial selectivity. Methods based on network theory can elucidate protein communication networks through the analysis of pairwise correlations observed in molecular dynamics (MD) simulations using molecular descriptors that serve as proxies for allosteric information. Typically, single atomic descriptors such as α-carbon displacements are used as proxies for allosteric information. Therefore, allosteric networks are based on correlations revealed by that descriptor. Here, we introduce a Python software package that provides a comprehensive toolkit for studying allostery from MD simulations of biochemical systems. MDiGest offers the ability to describe protein dynamics by combining different approaches, such as correlations of atomic displacements or dihedral angles, as well as a novel approach based on the correlation of Kabsch-Sander electrostatic couplings. MDiGest allows for comparisons of networks and community structures that capture physical information relevant to allostery. Multiple complementary tools for studying essential dynamics include principal component analysis, root mean square fluctuation, as well as secondary structure-based analyses.

Disease mutations and phosphorylation alter the allosteric pathways involved in autoinhibition of protein phosphatase 2A

Mutations in protein phosphatase 2A (PP2A) are connected to intellectual disability and cancer. It has been hypothesized that these mutations might disrupt the autoinhibition and phosphorylation-induced activation of PP2A. Since they are located far from both the active and substrate binding sites, it is unclear how they exert their effect. We performed allosteric pathway analysis based on molecular dynamics simulations and combined it with biochemical experiments to investigate the autoinhibition of PP2A. In the wild type (WT), the C-arm of the regulatory subunit B56δ obstructs the active and substrate binding sites exerting a dual autoinhibition effect. We find that the disease mutant, E198K, severely weakens the allosteric pathways that stabilize the C-arm in the WT. Instead, the strongest allosteric pathways in E198K take a different route that promotes exposure of the substrate binding site. To facilitate the allosteric pathway analysis, we introduce a path clustering algorithm for lumping pathways into channels. We reveal remarkable similarities between the allosteric channels of E198K and those in phosphorylation-activated WT, suggesting that the autoinhibition can be alleviated through a conserved mechanism. In contrast, we find that another disease mutant, E200K, which is in spatial proximity of E198, does not repartition the allosteric pathways leading to the substrate binding site; however, it may still induce exposure of the active site. This finding agrees with our biochemical data, allowing us to predict the activity of PP2A with the phosphorylated B56δ and provide insight into how disease mutations in spatial proximity alter the enzymatic activity in surprisingly different mechanisms.

All-Atom Simulations Reveal the Intricacies of Signal Transduction upon Binding of the HLA-E Ligand to the Transmembrane Inhibitory CD94/NKG2A Receptor

Natural killer (NK) cells play an important role in the innate immune response against tumors and various pathogens such as viruses and bacteria. Their function is controlled by a wide array of activating and inhibitory receptors, which are expressed on their cell surface. Among them is a dimeric NKG2A/CD94 inhibitory transmembrane (TM) receptor which specifically binds to the non-classical MHC I molecule HLA-E, which is often overexpressed on the surface of senescent and tumor cells. Using the Alphafold 2 artificial intelligence system, we constructed the missing segments of the NKG2A/CD94 receptor and generated its complete 3D structure comprising extracellular (EC), TM, and intracellular regions, which served as a starting point for the multi-microsecond all-atom molecular dynamics simulations of the receptor with and without the bound HLA-E ligand and its nonameric peptide. The simulated models revealed that an intricate interplay of events is taking place between the EC and TM regions ultimately affecting the intracellular immunoreceptor tyrosine-based inhibition motif (ITIM) regions that host the point at which the signal is transmitted further down the inhibitory signaling cascade. Signal transduction through the lipid bilayer was also coupled with the changes in the relative orientation of the NKG2A/CD94 TM helices in response to linker reorganization, mediated by fine-tuned interactions in the EC region of the receptor, taking place after HLA-E binding. This research provides atomistic details of the cells' protection mechanism against NK cells and broadens the knowledge regarding the TM signaling of ITIM-bearing receptors.

Structural Insights into Phosphorylation-Mediated Polymerase Function Loss for DNA Polymerase β Bound to Gapped DNA

DNA polymerase β is a member of the X-family of DNA polymerases, playing a critical role in the base excision repair (BER) pathway in mammalian cells by implementing the nucleotide gap-filling step. In vitro phosphorylation of DNA polymerase β with PKC on S44 causes loss in the enzyme's DNA polymerase activity but not single-strand DNA binding. Although these studies have shown that single-stranded DNA binding is not affected by phosphorylation, the structural basis behind the mechanism underlying phosphorylation-induced activity loss remains poorly understood. Previous modeling studies suggested phosphorylation of S44 was sufficient to induce structural changes that impact the enzyme's polymerase function. However, the S44 phosphorylated-enzyme/DNA complex has not been modeled so far. To address this knowledge gap, we conducted atomistic molecular dynamics simulations of pol β complexed with gapped DNA. Our simulations, which used explicit solvent and lasted for microseconds, revealed that phosphorylation at the S44 site, in the presence of Mg ions, induced significant conformational changes in the enzyme. Specifically, these changes led to the transformation of the enzyme from a closed to an open structure. Additionally, our simulations identified phosphorylation-induced allosteric coupling between the inter-domain region, suggesting the existence of a putative allosteric site. Taken together, our results provide a mechanistic understanding of the conformational transition observed due to phosphorylation in DNA polymerase β interactions with gapped DNA. Our simulations shed light on the mechanisms of phosphorylation-induced activity loss in DNA polymerase β and reveal potential targets for the development of novel therapeutics aimed at mitigating the effects of this post-translational modification.

Selecting Features for Markov Modeling: A Case Study on HP35

Markov state models represent a popular means to interpret molecular dynamics trajectories in terms of memoryless transitions between metastable conformational states. To provide a mechanistic understanding of the considered biomolecular process, these states should reflect structurally distinct conformations and ensure a time scale separation between fast intrastate and slow interstate dynamics. Adopting the folding of villin headpiece (HP35) as a well-established model problem, here we discuss the selection of suitable input coordinates or "features", such as backbone dihedral angles and interresidue distances. We show that dihedral angles account accurately for the structure of the native energy basin of HP35, while the unfolded region of the free energy landscape and the folding process are best described by tertiary contacts of the protein. To construct a contact-based model, we consider various ways to define and select contact distances and introduce a low-pass filtering of the feature trajectory as well as a correlation-based characterization of states. Relying on input data that faithfully account for the mechanistic origin of the studied process, the states of the resulting Markov model are clearly discriminated by the features, describe consistently the hierarchical structure of the free energy landscape, and─as a consequence─correctly reproduce the slow time scales of the process.

Turning up the heat mimics allosteric signaling in imidazole-glycerol phosphate synthase

Allosteric drugs have the potential to revolutionize biomedicine due to their enhanced selectivity and protection against overdosage. However, we need to better understand allosteric mechanisms in order to fully harness their potential in drug discovery. In this study, molecular dynamics simulations and nuclear magnetic resonance spectroscopy are used to investigate how increases in temperature affect allostery in imidazole glycerol phosphate synthase. Results demonstrate that temperature increase triggers a cascade of local amino acid-to-amino acid dynamics that remarkably resembles the allosteric activation that takes place upon effector binding. The differences in the allosteric response elicited by temperature increase as opposed to effector binding are conditional to the alterations of collective motions induced by either mode of activation. This work provides an atomistic picture of temperature-dependent allostery, which could be harnessed to more precisely control enzyme function.

Computational insights into ligand-induced G protein and β-arrestin signaling of the dopamine D1 receptor

The dopamine D1 receptor (D1R), is a class A G protein coupled-receptor (GPCR) which has been a promising drug target for psychiatric and neurological disorders such as Parkinson's disease (PD). Previous studies have suggested that therapeutic effects can be realized by targeting the β-arrestin signaling pathway of dopamine receptors, while overactivation of the G protein-dependent pathways leads to side effects, such as dyskinesias. Therefore, it is highly desirable to develop a D1R ligand that selectively regulates the β-arrestin pathway. Currently, most D1R agonists are signaling-balanced and stimulate both G protein and β-arrestin pathways, with a few reports of G protein biased ligands. However, identification and characterization of β-arrestin biased D1R agonists has been a challenge thus far. In this study, we implemented Gaussian accelerated molecular dynamics (GaMD) simulations to provide valuable computational insights into the possible underlying molecular mechanism of the different signaling properties of two catechol and two non-catechol D1R agonists that are either G protein biased or signaling-balanced. Dynamic network analysis further identified critical residues in the allosteric signaling network of D1R for each ligand at different conformational or binding states. Some of these residues are crucial for G protein or arrestin signals of GPCRs based on previous studies. Finally, we provided a molecular design strategy which can be utilized by medicinal chemists to develop potential β-arrestin biased D1R ligands. The proposed hypotheses are experimentally testable and can guide the development of safer and more effective medications for a variety of CNS disorders.

Extended regulation interface coupled to the allosteric network and disease mutations in the PP2A-B56δ holoenzyme

An increasing number of mutations associated with devastating human diseases are diagnosed by whole-genome/exon sequencing. Recurrent de novo missense mutations have been discovered in B56δ (encoded by PPP2R5D), a regulatory subunit of protein phosphatase 2A (PP2A), that cause intellectual disabilities (ID), macrocephaly, Parkinsonism, and a broad range of neurological symptoms. Single-particle cryo-EM structures show that the PP2A-B56δ holoenzyme possesses closed latent and open active forms. In the closed form, the long, disordered arms of B56δ termini fold against each other and the holoenzyme core, establishing dual autoinhibition of the phosphatase active site and the substrate-binding protein groove. The resulting interface spans over 190 Å and harbors unfavorable contacts, activation phosphorylation sites, and nearly all residues with ID-associated mutations. Our studies suggest that this dynamic interface is close to an allosteric network responsive to activation phosphorylation and altered globally by mutations. Furthermore, we found that ID mutations perturb the activation phosphorylation rates, and the severe variants significantly increase the mitotic duration and error rates compared to the wild variant.

Ligand-induced conformational changes enable intersubunit communications in D-dopachrome tautomerase

D-Dopachrome tautomerase (D-DT; or MIF-2) is a multifunctional protein with immunomodulatory properties and a documented pathogenic role in inflammation and cancer that is associated with activation of the cell surface receptor CD74. Alongside D-DT, macrophage migration inhibitory factor (MIF) is also known to activate CD74, promoting pathogenesis. While the role of the MIF/CD74 axis has been extensively studied in various disease models, the late discovery of the D-DT/CD74 axis has led to a poor investigation into the D-DT-induced activation mechanism of CD74. A previous study has identified 4-(3-carboxyphenyl)-2,5-pyridinedicarboxylic acid (4-CPPC) as the first selective and reversible inhibitor of D-DT and reported its potency to block the D-DT-induced activation of CD74 in a cell-based model. In this study, we employ molecular dynamics simulations and nuclear magnetic resonance experiments to study 4-CPPC-induced changes to the dynamic profile of D-DT. We found that binding of the inhibitor remarkably promotes the conformational flexibility of C-terminal without impacting the structural stability of the biological assembly. Consequently, long-range intrasubunit (>11 Å) and intersubunit (>30 Å) communications are enabled between distal regions. Communication across the three subunits is accomplished via 4-CPPC, which serves as a communication bridge after Val113 is displaced from its hydrophobic pocket. This previously unrecognized structural property of D-DT is not shared with its human homolog, MIF, which exhibits an impressive C-terminal rigidity even in the presence of an inhibitor. Considering the previously reported role of MIF's C-terminal in the activation of CD74, our results break new ground for understanding the functionality of D-DT in health and disease.

The quaternary question: Determining allostery in spastin through dynamics classification learning and bioinformatics

The nanomachine from the ATPases associated with various cellular activities superfamily, called spastin, severs microtubules during cellular processes. To characterize the functionally important allostery in spastin, we employed methods from evolutionary information, to graph-based networks, to machine learning applied to atomistic molecular dynamics simulations of spastin in its monomeric and the functional hexameric forms, in the presence or absence of ligands. Feature selection, using machine learning approaches, for transitions between spastin states recognizes all the regions that have been proposed as allosteric or functional in the literature. The analysis of the composition of the Markov State Model macrostates in the spastin monomer, and the analysis of the direction of change in the top machine learning features for the transitions, indicate that the monomer favors the binding of ATP, which primes the regions involved in the formation of the inter-protomer interfaces for binding to other protomer(s). Allosteric path analysis of graph networks, built based on the cross-correlations between residues in simulations, shows that perturbations to a hub specific for the pre-hydrolysis hexamer propagate throughout the structure by passing through two obligatory regions: the ATP binding pocket, and pore loop 3, which connects the substrate binding site to the ATP binding site. Our findings support a model where the changes in the terminal protomers due to the binding of ligands play an active role in the force generation in spastin. The secondary structures in spastin, which are found to be highly degenerative within the network paths, are also critical for feature transitions of the classification models, which can guide the design of allosteric effectors to enhance or block allosteric signaling.

2,5-Pyridinedicarboxylic acid is a bioactive and highly selective inhibitor of D-dopachrome tautomerase

Macrophage migration inhibitory factor (MIF) and D-dopachrome tautomerase (D-DT) are two pleotropic cytokines, which are coexpressed in various cell types to activate the cell surface receptor CD74. Via the MIF/CD74 and D-DT/CD74 axes, the two proteins exhibit either beneficial or deleterious effect on human diseases. In this study, we report the identification of 2,5-pyridinedicarboxylic acid (a.k.a. 1) that effectively blocks the D-DT-induced activation of CD74 and demonstrates an impressive 79-fold selectivity for D-DT over MIF. Crystallographic characterization of D-DT-1 elucidates the binding features of 1 and reveals previously unrecognized differences between the MIF and D-DT active sites that explain the ligand's functional selectivity. The commercial availability, low cost, and high selectivity make 1 the ideal tool for studying the pathophysiological functionality of D-DT in disease models. At the same time, our comprehensive biochemical, computational, and crystallographic analyses serve as a guide for generating highly potent and selective D-DT inhibitors.

The "violin model": Looking at community networks for dynamic allostery

Allosteric regulation of proteins continues to be an engaging research topic for the scientific community. Models describing allosteric communication have evolved from focusing on conformation-based descriptors of protein structural changes to appreciating the role of internal protein dynamics as a mediator of allostery. Here, we explain a "violin model" for allostery as a contemporary method for approaching the Cooper-Dryden model based on redistribution of protein thermal fluctuations. Based on graph theory, the violin model makes use of community network analysis to functionally cluster correlated protein motions obtained from molecular dynamics simulations. This Review provides the theory and workflow of the methodology and explains the application of violin model to unravel the workings of protein kinase A.

Conformational and Thermodynamic Differences Underlying Wild-Type and Mutant Eleven-Nineteen-Leukemia YEATS Domain Specificity for Epigenetic Marks

Histone post-translational modifications (PTMs) are interpreted by multiple reader domains and proteins to regulate gene expression. The eleven-nineteen-leukemia (ENL) YEATS domain is a prototypical PTM reader that recognizes multiple lysine acetylation marks on the histone H3 tails as a way of recruiting chromatin remodellers. Two ENL YEATS mutations have been identified which have been linked with leukemia, Wilms tumor, and other forms of cancer and result in either an insertion or deletion of residues in the loop connecting beta sheets distant from the protein active site. In vitro experiments have shown that these mutations modulate the selectivities of YEATS domains for various lysine acetylation marks, although different experiments have provided contrasting views on the abilities of the insertion and deletion mutants to discern specific PTMs. Here, we have performed multiple molecular dynamics simulations of wild-type and insertion and deletion mutant YEATS domains free from and in complex with two PTM peptides: one that is acetylated at K9 of H3 and the other that is acetylated at residue K27 of H3. Results show that these two peptides have distinct flexibilities and binding energetics when bound to YEATS domains and that these properties are affected by interactions with residues within and outside of the peptide consensus motif. Furthermore, these properties are modulated by the YEATS insertion and deletion mutants, which results in disparate binding effects in these systems. Together, these results suggest that only the partial exposure of histone tails is sufficient in the context of nucleosomes for YEATS-mediated recognition of acetylation marks on histone tails. They also caution against the overinterpretation of results obtained from experiments on reader domain-histone peptide binding in isolation and not in the full-length nucleosome context.

All-Atom Molecular Dynamics Simulations Indicated the Involvement of a Conserved Polar Signaling Channel in the Activation Mechanism of the Type I Cannabinoid Receptor

The type I cannabinoid G protein-coupled receptor (CB1, GPCR) is an intensely investigated pharmacological target, owing to its involvement in numerous physiological functions as well as pathological processes such as cancers, neurodegenerative diseases, metabolic disorders and neuropathic pain. In order to develop modern medications that exert their effects through binding to the CB1 receptor, it is essential to understand the structural mechanism of activation of this protein. The pool of atomic resolution experimental structures of GPCRs has been expanding rapidly in the past decade, providing invaluable information about the function of these receptors. According to the current state of the art, the activity of GPCRs involves structurally distinct, dynamically interconverting functional states and the activation is controlled by a cascade of interconnecting conformational switches in the transmembrane domain. A current challenge is to uncover how different functional states are activated and what specific ligand properties are responsible for the selectivity towards those different functional states. Our recent studies of the μ-opioid and β₂-adrenergic receptors (MOP and β₂AR, respectively) revealed that the orthosteric binding pockets and the intracellular surfaces of these receptors are connected through a channel of highly conserved polar amino acids whose dynamic motions are in high correlation in the agonist- and G protein-bound active states. This and independent literature data led us to hypothesize that, in addition to consecutive conformational transitions, a shift of macroscopic polarization takes place in the transmembrane domain, which is furnished by the rearrangement of polar species through their concerted movements. Here, we examined the CB1 receptor signaling complexes utilizing microsecond scale, all-atom molecular dynamics (MD) simulations in order to see if our previous assumptions could be applied to the CB1 receptor too. Apart from the identification of the previously proposed general features of the activation mechanism, several specific properties of the CB1 have been indicated that could possibly be associated with the signaling profile of this receptor.

A new approach for extracting information from protein dynamics

Increased ability to predict protein structures is moving research focus towards understanding protein dynamics. A promising approach is to represent protein dynamics through networks and take advantage of well-developed methods from network science. Most studies build protein dynamics networks from correlation measures, an approach that only works under very specific conditions, instead of the more robust inverse approach. Thus, we apply the inverse approach to the dynamics of protein dihedral angles, a system of internal coordinates, to avoid structural alignment. Using the well-characterized adhesion protein, FimH, we show that our method identifies networks that are physically interpretable, robust, and relevant to the allosteric pathway sites. We further use our approach to detect dynamical differences, despite structural similarity, for Siglec-8 in the immune system, and the SARS-CoV-2 spike protein. Our study demonstrates that using the inverse approach to extract a network from protein dynamics yields important biophysical insights.

Wordom update 2: A user-friendly program for the analysis of molecular structures and conformational ensembles

We present the second update of Wordom, a user-friendly and efficient program for manipulation and analysis of conformational ensembles from molecular simulations. The actual update expands some of the existing modules and adds 21 new modules to the update 1 published in 2011. The new adds can be divided into three sets that: 1) analyze atomic fluctuations and structural communication; 2) explore ion-channel conformational dynamics and ionic translocation; and 3) compute geometrical indices of structural deformation. Set 1 serves to compute correlations of motions, find geometrically stable domains, identify a dynamically invariant core, find changes in domain-domain separation and mutual orientation, perform wavelet analysis of large-scale simulations, process the output of principal component analysis of atomic fluctuations, perform functional mode analysis, infer regions of mechanical rigidity, analyze overall fluctuations, and perform the perturbation response scanning. Set 2 includes modules specific for ion channels, which serve to monitor the pore radius as well as water or ion fluxes, and measure functional collective motions like receptor twisting or tilting angles. Finally, set 3 includes tools to monitor structural deformations by computing angles, perimeter, area, volume, β-sheet curvature, radial distribution function, and center of mass. The ring perception module is also included, helpful to monitor supramolecular self-assemblies. This update places Wordom among the most suitable, complete, user-friendly, and efficient software for the analysis of biomolecular simulations. The source code of Wordom and the relative documentation are available under the GNU general public license at http://wordom.sf.net.

Elucidating the molecular determinants in the process of gastrin C-terminal pentapeptide amide end activating cholecystokinin 2 receptor by Gaussian accelerated molecular dynamics simulations

Gastrin plays important role in stimulating the initiation and development of many gastrointestinal diseases through interacting with the cholecystokinin 2 receptor (CCK2R). The smallest bioactive unit of gastrin activating CCK2R is the C-terminal tetrapeptide capped with an indispensable amide end. Understanding the mechanism of this smallest bioactive unit interacting with CCK2R on a molecular basis could provide significant insights for designing CCK2R antagonists, which can be used to treat gastrin-related diseases. To this end, we performed extensive Gaussian accelerated molecular dynamics simulations to investigate the interaction between gastrin C-terminal pentapeptide capped with/without amide end and CCK2R. The amide cap influences the binding modes of the pentapeptide with CCK2R by weakening the electrostatic attractions between the C-terminus of the pentapeptide and basic residues near the extracellular domain in CCK2R. The C-terminus with the amide cap penetrates into the transmembrane domain of CCK2R while floating at the extracellular domain without the amide cap. Different binding modes induced different conformational dynamics of CCK2R. Residue pairs in CCK2R had stronger correlated motions when binding with the amidated pentapeptide. Key residues and interactions important for CCK2R binding with the amidated pentagastrin were also identified. Our results provide molecular insights into the determinants of the bioactive unit of gastrin activating CCK2R, which would be of great help for the design of CCK2R antagonists.

Mutual information analysis of mutation, nonlinearity, and triple interactions in proteins

Mutations are the cause of several diseases as well as the underlying force of evolution. A thorough understanding of their biophysical consequences is essential. We present a computational framework for evaluating different levels of mutual information (MI) and its dependence on mutation. We used molecular dynamics trajectories of the third PDZ domain and its different mutations. Nonlinear MI between all residue pairs are calculated by tensor Hermite polynomials up to the fifth order and compared with results from multivariate Gaussian distribution of joint probabilities. We show that MI is written as the sum of a Gaussian and a nonlinear component. Results for the PDZ domain show that the Gaussian term gives a sufficiently accurate representation of MI when compared with nonlinear terms up to the fifth order. Changes in MI between residue pairs show the characteristic patterns resulting from specific mutations. Emergence of new peaks in the MI versus residue index plots of mutated PDZ shows how mutation may change allosteric pathways. Triple correlations are characterized by evaluating MI between triplets of residues. We observed that certain triplets are strongly affected by mutation. Susceptibility of residues to perturbation is obtained by MI and discussed in terms of linear response theory.