Allosteric Communication Research Articles

Ionic displacement of Ca2+ by Pb2+ in calmodulin is affected by arrhythmia-associated mutations

Lead is a highly toxic metal that severely perturbs physiological processes even at sub-micromolar levels, often by disrupting the Ca2+ signaling pathways. Recently, Pb2+-associated cardiac toxicity has emerged, with potential involvement of both the ubiquitous Ca2+ sensor protein calmodulin (CaM) and ryanodine receptors. In this work, we explored the hypothesis that Pb2+ contributes to the pathological phenotype of CaM variants associated with congenital arrhythmias. We performed a thorough spectroscopic and computational characterization of CaM conformational switches in the co-presence of Pb2+ and four missense mutations associated with congenital arrhythmias, namely N53I, N97S, E104A and F141L, and analyzed their effects on the recognition of a target peptide of RyR2. When bound to any of the CaM variants, Pb2+ is difficult to displace even under equimolar Ca2+ concentrations, thus locking all CaM variants in a specific conformation, which exhibits characteristics of coiled-coil assemblies. All arrhythmia-associated variants appear to be more susceptible to Pb2+ than wild type (WT) CaM, as the conformational transition towards the coiled-coil conformation occurs at lower Pb2+, regardless of the presence of Ca2+, with altered cooperativity. The presence of arrhythmia-associated mutations specifically alters the cation coordination of CaM variants, in some cases involving allosteric communication between the EF-hands in the two domains. Finally, while WT CaM increases the affinity for the RyR2 target in the presence of Pb2+, no specific pattern could be detected for all other variants, ruling out a synergistic effect of Pb2+ and mutations in the recognition process.

Nonlocal Effects of Antibiotic-Resistance-Causing Mutations Reveal an Alternative Region for Targeting on FtsW-Penicillin-Binding Protein 3 Complex of Haemophilus influenzae.

Currently prescribed antibiotics target the catalytic sites of wild-type bacterial proteins; however, bacteria adopt mutations at this site, eventually leading to the emergence of resistance. Therefore, the identification of alternative drug binding sites is crucial, which requires knowledge of the dynamics of the mutant protein. Here, we set out to investigate the impact of a high-resistance-causing triple mutation (S385T + L389F + N526K) on the dynamics of a prioritized resistant pathogen, Haemophilus influenzae, using computational techniques. We studied penicillin-binding protein 3 (PBP3) and its complex with FtsW, which display resistance toward β-lactam antibiotics. We showed that mutations displayed local and nonlocal effects. In terms of the former, the orientation of the β-sheet, which surrounds the active site of PBP3, was impacted and the catalytic site was exposed to the periplasmic region. In addition, the flexibility of the β3-β4 loop, which modulates the catalysis of the enzyme, increased in the mutant FtsW-PBP3 complex. As for nonlocal effects, the dynamics of the pedestal domain (N-terminal periplasmic modulus (N-t)), i.e., the opening of the fork, was different between the wild-type and mutant enzymes. We showed the closed fork caused a greater number of residues to participate in the hypothesized allosteric communication network connecting N-t to the transpeptidase domain in the mutant enzyme. Finally, we demonstrated that the closed fork results in more favorable binding with β-lactam antibiotics, particularly cefixime, suggesting that small therapeutics that can stabilize the closed fork of mutant PBP3 may lead to the development of more effective molecules to combat resistant bacteria.

Allosteric communication between ligand binding domains modulates substrate inhibition in adenylate kinase

Enzymes play a vital role in life processes; they control chemical reactions and allow functional cycles to be synchronized. Many enzymes harness large-scale motions of their domains to achieve tremendous catalytic prowess and high selectivity for specific substrates. One outstanding example is provided by the three-domain enzyme adenylate kinase (AK), which catalyzes phosphotransfer between ATP to AMP. Here we study the phenomenon of substrate inhibition by AMP and its correlation with domain motions. Using single-molecule FRET spectroscopy, we show that AMP does not block access to the ATP binding site, neither by competitive binding to the ATP cognate site nor by directly closing the LID domain. Instead, inhibitory concentrations of AMP lead to a faster and more cooperative domain closure by ATP, leading in turn to an increased population of the closed state. The effect of AMP binding can be modulated through mutations throughout the structure of the enzyme, as shown by the screening of an extensive AK mutant library. The mutation of multiple conserved residues reduces substrate inhibition, suggesting that substrate inhibition is an evolutionary well conserved feature in AK. Combining these insights, we developed a model that explains the complex activity of AK, particularly substrate inhibition, based on the experimentally observed opening and closing rates. Notably, the model indicates that the catalytic power is affected by the microsecond balance between the open and closed states of the enzyme. Our findings highlight the crucial role of protein motions in enzymatic activity.

Computational and structural insights into the pre- and post-hydrolysis states of bovine multidrug resistance-associated protein 1.

ATP-binding cassette C-family drug membrane transporters play an important role in local pharmacokinetics, that is, drug concentration in cellular compartments. From the structural point of view, only the bovine ortholog of the multidrug resistance-associated protein 1 (bMRP1) has been resolved. We here used μs-scaled molecular dynamics simulations to investigate the structure and dynamics of the bovine multidrug resistance-associated protein 1 in pre- and post-hydrolysis functional states. The present work aims to examine the slight but likely relevant structural differences between pre- and post-hydrolysis states of outward-facing conformations as well as the interactions between the multidrug resistance-associated protein 1 and the surrounding lipid bilayer. Global conformational dynamics show unfavourable extracellular opening associated with nucleotide-binding domain dimerization indicating that the post-hydrolysis state adopts a close-cleft conformation rather than an outward-open conformation. Our present simulations also highlight persistent interactions with annular cholesterol molecules and the expected active role of lipid bilayer in the allosteric communication between distant domains of the transporter.

AlloReverse: multiscale understanding among hierarchical allosteric regulations.

Increasing data in allostery are requiring analysis of coupling relationships among different allosteric sites on a single protein. Here, based on our previous efforts on reversed allosteric communication theory, we have developed AlloReverse, a web server for multiscale analysis of multiple allosteric regulations. AlloReverse integrates protein dynamics and machine learning to discover allosteric residues, allosteric sites and regulation pathways. Especially, AlloReverse could reveal hierarchical relationships between different pathways and couplings among allosteric sites, offering a whole map of allostery. The web server shows a good performance in re-emerging known allostery. Moreover, we applied AlloReverse to explore global allostery on CDC42 and SIRT3. AlloReverse predicted novel allosteric sites and allosteric residues in both systems, and the functionality of sites was validated experimentally. It also suggests a possible scheme for combined therapy or bivalent drugs on SIRT3. Taken together, AlloReverse is a novel workflow providing a complete regulation map and is believed to aid target identification, drug design and understanding of biological mechanisms. AlloReverse is freely available to all users at https://mdl.shsmu.edu.cn/AlloReverse/ or http://www.allostery.net/AlloReverse/.

Capturing Differences in the Regulation of LRRK2 Dynamics and Conformational States by Small Molecule Kinase Inhibitors.

Mutations in the human leucine rich repeat protein kinase-2 (LRRK2) create risk factors for Parkinson's disease, and pathological functions of LRRK2 are often correlated with aberrant kinase activity. Past research has focused on developing selective LRRK2 kinase inhibitors. In this study, we combined enhanced sampling simulations with HDX-MS to characterize the inhibitor-induced dynamic changes and the allosteric communications within the C-terminal domains of LRRK2, LRRK2RCKW. We find that the binding of MLi-2 (a type I kinase inhibitor) stabilizes a closed kinase conformation and reduces the global dynamics of LRRK2RCKW, leading to a more compact LRRK2RCKW structure. In contrast, the binding of Rebastinib (a type II kinase inhibitor) stabilizes an open kinase conformation, which promotes a more extended LRRK2RCKW structure. By probing the distinct effects of the type I and type II inhibitors, key interdomain interactions are found to regulate the communication between the kinase domain and the GTPase domain. The intermediate states revealed in our simulations facilitate the efforts toward in silico design of allosteric modulators that control LRRK2 conformations and potentially mediate the oligomeric states of LRRK2 and its interactions with other proteins.

Sequence-dependent model of allosteric communication.

The omnipresence and diversity of allosteric regulation in proteins and protein associations complemented by the potential for the design of allosterically acting biologics and drugs call for the development of a new generation of computational models for the analysis of allostery and rational engineering/design of desired signaling and effector molecules determining it. One of the most important challenges is the consideration of the role of amino acid sequence in forming the protein's allosteric communication, including the mode and strength of the allosteric signal that is communicated to the regulated functional site. Here, we present the network-based model with a sequence dependence added in consideration of allosteric communication by combining the structure-based statistical mechanical model of allostery with the Miyazawa-Jernigan residue-residue potential. Applying the model in the analysis of five classical allosteric proteins, we found that it is necessary to consider the following two major determinants: (i) the free energy exerted by the allosteric site on the regulated one and (ii) the background (average) change in dynamics of the overall structure. We show that working together these two components determine the allosteric modulation, calling one to study their dependence on structures, oligomerization states, and sequence divergence in different proteins.

Study of the Allosteric Mechanism of Human Mitochondrial Phenylalanyl-tRNA Synthetase by Transfer Entropy via an Improved Gaussian Network Model and Co-evolution Analyses.

We propose an improved transfer entropy approach called the dynamic version of the force constant fitted Gaussian network model based on molecular dynamics ensemble (dfcfGNMMD) to explore the allosteric mechanism of human mitochondrial phenylalanyl-tRNA synthetase (hmPheRS), one of the aminoacyl-tRNA synthetases that play a crucial role in translation of the genetic code. The dfcfGNMMD method can provide reliable estimates of the transfer entropy and give new insights into the role of the anticodon binding domain in driving the catalytic domain in aminoacylation activity and into the effects of tRNA binding and residue mutation on the enzyme activity, revealing the causal mechanism of the allosteric communication in hmPheRS. In addition, we incorporate the residue dynamic and co-evolutionary information to further investigate the key residues in hmPheRS allostery. This study sheds light on the mechanisms of hmPheRS allostery and can provide important information for related drug design.

Coarse-Grained Molecular Simulations and Ensemble-Based Mutational Profiling of Protein Stability in the Different Functional Forms of the SARS-CoV-2 Spike Trimers: Balancing Stability and Adaptability in BA.1, BA.2 and BA.2.75 Variants

Evolutionary and functional studies have suggested that the emergence of Omicron variants can be determined by multiple fitness tradeoffs including immune escape, binding affinity, conformational plasticity, protein stability, and allosteric modulation. In this study, we embarked on a systematic comparative analysis of the conformational dynamics, electrostatics, protein stability, and allostery in the different functional states of spike trimers for BA.1, BA.2, and BA.2.75 variants. Using efficient and accurate coarse-grained simulations and atomistic reconstruction of the ensembles, we examined the conformational dynamics of the spike trimers that agree with the recent functional studies, suggesting that BA.2.75 trimers are the most stable among these variants. A systematic mutational scanning of the inter-protomer interfaces in the spike trimers revealed a group of conserved structural stability hotspots that play a key role in the modulation of functional dynamics and are also involved in the inter-protomer couplings through local contacts and interaction networks with the Omicron mutational sites. The results of mutational scanning provided evidence that BA.2.75 trimers are more stable than BA.2 and comparable in stability to the BA.1 variant. Using dynamic network modeling of the S Omicron BA.1, BA.2, and BA.2.75 trimers, we showed that the key network mediators of allosteric interactions are associated with the major stability hotspots that are interconnected along potential communication pathways. The network analysis of the BA.1, BA.2, and BA.2.75 trimers suggested that the increased thermodynamic stability of the BA.2.75 variant may be linked with the organization and modularity of the residue interaction network that allows for allosteric communications between structural stability hotspots and Omicron mutational sites. This study provided a plausible rationale for a mechanism in which Omicron mutations may evolve by targeting vulnerable sites of conformational adaptability to elicit immune escape while maintaining their control on balancing protein stability and functional fitness through robust allosteric communications with the stability hotspots.

Allosteric communication in the gating mechanism for controlled protein degradation by the bacterial ClpP peptidase.

Proteolysis is essential for the control of metabolic pathways and the cell cycle. Bacterial caseinolytic proteases (Clp) use peptidase components, such as ClpP, to degrade defective substrate proteins and to regulate cellular levels of stress-response proteins. To ensure selective degradation, access to the proteolytic chamber of the double-ring ClpP tetradecamer is controlled by a critical gating mechanism of the two axial pores. The binding of conserved loops of the Clp ATPase component of the protease or small molecules, such as acyldepsipeptide (ADEP), at peripheral ClpP ring sites, triggers axial pore opening through dramatic conformational transitions of flexible N-terminal loops between disordered conformations in the "closed" pore state and ordered hairpins in the "open" pore state. In this study, we probe the allosteric communication underlying these conformational changes by comparing residue-residue couplings in molecular dynamics simulations of each configuration. Both principal component and normal mode analyses highlight large-scale conformational changes in the N-terminal loop regions and smaller amplitude motions of the peptidase core. Community network analysis reveals a switch between intra- and inter-protomer coupling in the open-closed pore transition. Allosteric pathways that connect the ADEP binding sites to N-terminal loops are rewired in this transition, with shorter network paths in the open pore configuration supporting stronger intra- and inter-ring coupling. Structural perturbations, either through the removal of ADEP molecules or point mutations, alter the allosteric network to weaken the coupling.

An NMR portrait of functional and dysfunctional allosteric cooperativity in cAMP-dependent protein kinase A.

The cAMP-dependent protein kinase A (PKA) is the archetypical eukaryotic kinase. The catalytic subunit (PKA-C) structure is highly conserved among the AGC-kinase family. PKA-C is a bilobal enzyme with a dynamic N-lobe, harbouring the Adenosine-5'-triphosphate (ATP) binding site and a more rigid helical C-lobe. The substrate-binding groove resides at the interface of the two lobes. A distinct feature of PKA-C is the positive binding cooperativity between nucleotide and substrate. Several PKA-C mutations lead to the development of adenocarcinomas, myxomas, and other rare forms of liver tumours. Nuclear magnetic resonance (NMR) spectroscopy shows that these mutations disrupt the allosteric communication between the two lobes, causing a drastic decrease in binding cooperativity. The loss of cooperativity correlates with changes in substrate fidelity and reduced kinase affinity for the endogenous protein kinase inhibitor (PKI). The similarity between PKI and the inhibitory sequence of the kinase regulatory subunits suggests that the overall mechanism of regulation of the kinase may be disrupted. We surmise that a reduced or obliterated cooperativity may constitute a common trait for both orthosteric and allosteric mutations of PKA-C that may lead to dysregulation and disease.

Substrate binding and lipid-mediated allostery in the human organic anion transporter 1 at the atomic-scale

The Organic Anion Transporter 1 is a membrane transporter known for its central role in drug elimination by the kidney. hOAT1 is an antiporter translocating substrate in exchange for a-ketoglutarate. The understanding of hOAT1 structure and function remains limited due to the absence of resolved structure of hOAT1. Benefiting from conserved structural and functional patterns shared with other Major Facilitator Superfamily transporters, the present study intended to investigate fragments of hOAT1 transport function and modulation of its activity in order to make a step forward the understanding of its transport cycle. μs-long molecular dynamics simulation of hOAT1 were carried out suggesting two plausible binding sites for a typical substrate, adefovir, in line with experimental observations. The well-known B-like motif binding site was observed in line with previous studies. However, we here propose a new inner binding cavity which is expected to be involved in substrate translocation event. Binding modes of hOAT1 co-substrate α-ketoglutarate were also investigated suggesting that it may bind to highly conserved intracellular motifs. We here hypothesise that α-ketoglutarate may disrupt the pseudo-symmetrical intracellular charge-relay system which in turn may participate to the destabilisation of OF conformation. Investigations regarding allosteric communications along hOAT1 also suggest that substrate binding event might modulate the dynamics of intracellular charge relay system, assisted by surrounding lipids as active partners. We here proposed a structural rationalisation of transport impairments observed for two single nucleotide polymorphisms, p.Arg50His and p.Arg454Gln suggesting that the present model may be used to transport dysfunctions arising from hOAT1 mutations.

On the interplay between lipids and asymmetric dynamics of an NBS degenerate ABC transporter

Multidrug resistance-associated proteins are ABC C-family exporters. They are crucial in pharmacology as they transport various substrates across membranes. However, the role of the degenerate nucleotide-binding site (NBS) remains unclear likewise the interplay with the surrounding lipid environment. Here, we propose a dynamic and structural overview of MRP1 from ca. 110 μs molecular dynamics simulations. ATP binding to NBS1 is likely maintained along several transport cycles. Asymmetric NBD behaviour is ensured by lower signal transduction from NBD1 to the rest of the protein owing to the absence of ball-and-socket conformation between NBD1 and coupling helices. Even though surrounding lipids play an active role in the allosteric communication between the substrate-binding pocket and NBDs, our results suggest that lipid composition has a limited impact, mostly by affecting transport kinetics. We believe that our work can be extended to other degenerate NBS ABC proteins and provide hints for deciphering mechanistic differences among ABC transporters.

From elucidating mechanisms of allosteric signaling to designing allosteric drugs and biologics.

Allostery is a pervasive phenomenon underlies a multitude of cellular processes. We have previously developed a Structure-Based Statistical Mechanical Model of Allostery (SBSMMA) to quantitatively describe the causality and energetics of allosteric signaling due to perturbations such as ligand binding, mutations, disorder-order transition and post-translational modifications. The computational model was implemented in the AlloSigMA server and AlloMAPS database, which allow one to explore allosteric effects of perturbations in form of the exhaustive Allosteric Signaling/Probing Map (ASM/APM), to identify potential allosteric sites, and to facilitate effector design. Here, we demonstrate some recent work on applying our broadly applicable framework to different aspects of allostery. First, analysis of communication between different sites/regions of the Spike protein from SARS-CoV-2 revealed mutations harbored by variants of concern, as well as glycosylation, that originate strong signaling to the distant receptor-binding domain despite the separation. Using reverse perturbation of allosteric communication and ASM/APM, we identified potential druggable sites that can induce tunable allosteric responses in different functional regions of Spike. Second, while the strengths of allosteric medicines are widely recognized, rational design of effectors remains a challenging problem. We demonstrated with GPCRs and kinases that effector design should begin with the search/design for latent/non-natural binding sites, followed by fragment-based design of ligands, and consequently mutual adjustments of site-ligand pairs to obtain and tune the desired binding affinity and allosteric signals. Third, rapid progress in harnessing allostery calls for an understanding of how communication is established by different structural elements and how it can be modified. We obtained a picture of conserved allosteric communication characteristic in major folds, alterations of structure-driven signaling via sequence-determined divergence to distinct functions, and its diversification in multi-domain proteins and oligomers, which will facilitate engineering/design of allosteric communication.

Dynamic allosteric networks drive adenosine A1 receptor activation and G-protein coupling.

Biological receptors respond to environmental changes through allosteric regulation. In G-protein coupled receptors (GPCRs), the binding of ligands establishes chemical and dynamic communication networks resulting in key structural changes of a transmembrane helix that promotes the coupling and activation of G-proteins. The activation pathways and allosteric mechanisms of GPCRs present system-specific profiles among subtypes. Hence, the development of novel allosteric drugs clearly benefits from a complete characterization of the structural dynamics of the target receptor. In this work, we focus on the adenosine A1 receptor (A1R), for which regardless the progress made in understanding its allosteric modulation though experimental and computational studies, essential knowledge of the allosteric mechanism and communication networks that activates the receptor remains unknown. In particular, we have developed a computational strategy that combines molecular dynamics simulations, enhanced sampling techniques, network theory and pocket detection in order to decipher the interplay between the activation pathway of A1R, the allosteric networks and the transient pockets. Our simulations reveal hidden intermediate and pre-active states together with the inactive and fully-active states observed experimentally. The protein energy networks computed throughout these conformational states successfully unravel the extra and intracellular allosteric centers together with the communication pathways that couples them. We observe that the allosteric networks are dynamic, being increased along activation and fine-tuned in presence of the trimeric G-proteins. Overlap of the transient pockets detected and energy networks uncover how the allosteric coupling between pockets and distinct functional regions of the receptor is altered along activation. This complete dynamic picture provides essential information to ease the design of efficient allosteric modulators for A1R. Our computational workflow can be also applied to other GPCRs and related receptors.

Regulation of LRRK2 dynamics and conformation states by small molecules.

Mutations in LRRK2 is a risk factor for Parkinson's disease (PD), and the aberrant kinase activity is the main cause for pathological functions of LRRK2. Research have been focused on developing selective inhibitors for the LRRK2 kinase. However, we now know that in addition to the intrinsic kinase activity, the conformation of the LRRK2 protein plays important roles in regulate LRRK2 function. We have shown that the kinase domain serves as a central hub for inter-domain communication, and is the major driver for LRRK2 conformation transitions. In this study, we used GaMD simulations coupled with HDX-MS to analyze the dynamic changes and the inter-domain allosteric communications of C-terminal half of the LRRK2, LRRK2RCKW. Specifically, when the kinase domain is locked into a closed, active conformation or an open, inactive conformation by binding of the type I (MLi-2) and type II (Rebastinib) inhibitors, respectively. While both type I and type II inhibitor reduced the kinase activity effectively, they drive the LRRK2 in different conformation. Binding of MLi-2 stabilizes the kinase domain, and reduces the dynamic of LRRK2RCKW globally, thus stabilizes the compact domain orientations of LRRK2RCKW. In contrast, binding of Rebastinib resulted in a more dynamic kinase domain, which promoted the extended conformation of LRRK2RCKW. We also reveal the importance of the Dk-helix, which plays crucial roles in bridging the kinase and GTPase domain. The dynamic changes in the kinase domain that propagate through the DK-helix would lead to different conformations of the ROC domain, which potentially affect the GTPase activity, which is crucial for the cellular function of LRRK2.

Pressure-based mapping of Arf1 switch transition.

Biomolecular functions are often associated with complex conformational reorganization. These concerted, nontrivial rearrangements among various regions of proteins are essential for their biological functions. Although crystal structures of proteins can provide snapshots of end states essential for their function, a thorough understanding of the structural mechanics of conformational ensemble associated with protein function remains elusive for most proteins. A combination of experimental and computational techniques can assist in understanding these processes. ADP-ribosylation factor 1 (Arf1) is a small GTPase that is implicated in cellular trafficking from the endoplasmic reticulum to the Golgi complex. The transition of Arf1 from its GDP-bound inactive state to the GTP-bound, active state involves a series of conformational transitions resulting in GDP dissociation, a shift in the register of the β-strands in the inter-switch region, and reorganization of the N-terminal helix, and the switch 1 and switch 2 regions. Here we use a combination of molecular modelling, extensive molecular dynamic simulations, pressure perturbation NMR-constrained simulations and pressure perturbation SAXS guided ensemble optimization methods to obtain a comprehensive picture of the functional dynamics of Arf1. Our approach illuminates the events associated with the allosteric communication required for the activation of Arf1.

Laws: Local alignment of water sites-Describing allosteric water networks in enzymes.

Water is an essential component of biological systems; it affects the structure and stability of biological machinery. Highly conserved water networks have been shown to play a crucial role in the motion of protein domains and affect protein function by mediating allosteric communication. Perturbations to these networks have also been implicated in human diseases. Data from x-ray crystallography provide the locations of crystallographic water sites (CWS) coordinated by the protein which can be potentially used to study the conserved water networks. Here, we propose a computational method called local alignment for water sites (LAWS) to identify conserved water networks in molecular dynamics (MD) simulations. This method is based on multilateration — an algorithm widely used in GPS tracking. LAWS considers the contacts formed by CWS and protein atoms in the crystal structure and uses these interaction distances to track ordered waters in a simulation. We apply our method to simulations of an enzyme, fluoroacetate dehalogenase, and analyze the occupancy, residence times and correlated motions of individual water molecules coupled to the protein. Our results help to determine a highly conserved water network involved in allosteric regulation.

Revealing the allosteric mechanism of pH-dependence in the proton-activated chloride channel.

The ability of the Proton-activated chloride (PAC) channel to perform its chloride transfer function across the membrane was shown to be dependent on the pH in the extracellular environment. Thus, an increase of extracellular pH from pH 4.5 to pH 8 results in a conformational change in transmembrane domain (TMD) of PAC and abolishes chloride conductivity. Mutagenesis of various extracellular domain (ECD) regions of PAC, including the Acidic Pocket, the beta 3 sheet of the “finger region” and the distal end of the ECD, altered the pH-sensitivity of PAC without revealing how such changes affect the pH sensitivity and its effect on the structure and dynamics of the distal end of the TMD. To understand this mechanism we used molecular pH-specific molecular dynamics (MD) simulations of PAC protein with the ECpH-MD method, capturing the pH-dependent conformational transitions between the active and inactive forms of PAC protein. The effect of changes in protonation states of a number of experimentally determined pH-sensor residues revealed their specific structural roles in the mechanism of conformational change underlying the changes in PAC activity. The allosteric pathways connecting these pH-sensors in the ECD to the TMD at different pH values revealed and quantified from analyses of the various MD trajectories with the rigorous N-body information theory (NbIT) method. Together with the structural data determined for various states of PAC (inactive, active, desensitized), the atomistic level of the dynamics driving the allosteric communication offers a comprehensive mechanistic understanding of the pH-dependence in PAC function.

MDigest: A comprehensive toolkit for detection of allosteric communication from molecular dynamics simulations of biochemical systems.

Molecular interactions are key to regulating cellular processes by transferring information between distant sites, promoting protein complex formation or enzyme activation. Understanding how biomolecules orchestrate this information transfer is critical to gaining insight into biochemical processes, modulating them through bioengineering, or even controlling reactions through small-molecule activators. In the past decade, network theory has been applied to identify molecular features and allosteric hubs essential for establishing information transfer in biomolecules. Molecular dynamics simulations often are the source of time-correlated data that is used to construct protein networks, which can be rationalized in terms of different correlation metrics. The specific molecular features and correlation metrics to use for reliably describing the coupled motions underlying allostery are often overlooked concepts. In this work, we provide a Python software package for performing network analysis on the molecular dynamics of biological systems. MDigest has a modular structure that allows for rapid evaluation and straightforward comparison of residue couplings obtained from different molecular features and various correlation metrics. In addition to commonly used features such as generalized correlation based on atomic displacements or covariance of dihedral angle fluctuations, we include a new network approach that relies on the correlation of electrostatic couplings over time, resulting in a coordinate-independent and physically relevant representation of the allosteric network. Besides allowing for efficient comparison of different networks at custom distance thresholding, our implementation allows the user to compare and contrast the underlying community structures and determine optimal paths for the most informative graph. Our enhanced and extended protocol allows for rigorous and comprehensive analysis of MD trajectories from small to large macromolecular complexes.