Mapping the intramolecular signal transduction of G-protein coupled receptors

Ternary model structural complex of C5a, C5aR2, and β-arrestin1

Complement component fragment 5a (C5a) is one of the potent proinflammatory modulators of the complement system. C5a recruits two genomically related G protein-coupled receptors (GPCRs), like C5aR1 and C5aR2, constituting a binary complex. The C5a-C5aR1/C5aR2 binary complexes involve other transducer proteins like heterotrimeric G-proteins and β-arrestins to generate the fully active ternary complexes that trigger intracellular signaling through downstream effector molecules in tissues. In the absence of structural data, we had recently developed highly refined model structures of C5aR2 in its inactive (free), meta-active (complexed to the CT-peptide of C5a), and active (complexed to C5a) state embedded to a model palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayer. Compared to C5aR1, C5aR2 is established as a noncanonical GPCR, as it recruits and signals through β-arrestins rather than G-proteins. Notably, structural understanding of the ternary complex involving C5a-C5aR2-β-arrestin is currently unknown. The current study has attempted to fill the gap by generating a highly refined, fully active ternary model structural complex of the C5a-C5aR2-β-arrestin1 embedded in a model POPC bilayer. The computational modeling, 500 ns molecular dynamics (MD) studies, and the principal component analysis (PCA), including the molecular mechanics Poisson-Boltzmann surface area (MM PBSA) based data presented in this study, provide an experimentally testable hypothesis about C5a-C5aR2-β-arrestin1 extendable to other such ternary systems. The model ternary complex of C5a-C5aR2-β-arrestin1 will further enrich the current structural understanding related to the interaction of β-arrestins with the C5a-C5aR2 system.Communicated by Ramaswamy H. Sarma.

Kinetic Model for the Desensitization of G Protein-Coupled Receptor

Desensitization of G-protein-coupled receptors (GPCR) is a general regulatory mechanism adopted by biological organisms against overstimulation of G protein signaling. Although the details of the mechanism are extensively studied, it is not easy to gain an overarching understanding of the process constituted by a multitude of molecular events with vastly differing time scales. To offer a semiquantitative yet predictive understanding of the mechanism, we formulate a kinetic model for the G protein signaling and desensitization by considering essential biochemical steps from ligand binding to receptor internalization. The internalization, followed by receptor depletion from the plasma membrane, attenuates the downstream signal. Together with the kinetic model and its full numerics of the expression derived for the dose-response relation, an approximated form of the expression clarifies the role played by the individual biochemical processes and allows us to identify four distinct regimes for the downregulation that emerge from the balance between phosphorylation, dephosphorylation, and the cellular level of β-arrestin.

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

G-protein coupled receptors (GPCRs) present specific activation pathways and signaling among receptor subtypes. Hence, an extensive knowledge of the structural dynamics of the receptor is critical for the development of therapeutics. Here, we target the adenosine A1 receptor (A1R), for which a negligible number of drugs have been approved. We combine molecular dynamics simulations, enhanced sampling techniques, network theory and pocket detection to decipher the activation pathway of A1R, decode the allosteric networks and identify transient pockets. The A1R activation pathway 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 and 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 transient pockets and energy networks uncover how the allosteric coupling between pockets and distinct functional regions of the receptor is altered along activation. By an in-depth analysis of the bridge between activation pathway, energy networks and transient pockets, we provide a further understanding of A1R. This information can be useful to ease the design of allosteric modulators for A1R.

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.

Systematic analyses of the sequence conservation and ligand interaction patterns of purinergic P1 and P2Y receptors provide a structural basis for receptor selectivity

Purinergic receptors are membrane proteins that regulate numerous cellular functions by catalyzing reactions involving purine nucleotides or nucleosides. Among the three receptor families, i.e., P1, P2X, and P2Y, the P1 and P2Y receptors share common structural features of class A GPCR. Comprehensive sequence and structural analysis revealed that the P1 and P2Y receptors belong to two distinct groups. They exhibit different ligand-binding site features that can distinguish between specific activators. These specific amino acid residues in the binding cavity may be involved in the selectivity and unique pharmacological behavior of each subtype. In this study, we conducted a structure-based analysis of purinergic P1 and P2Y receptors to identify their evolutionary signature and obtain structural insights into ligand recognition and selectivity. The structural features of the P1 and P2Y receptor classes were compared based on sequence conservation and ligand interaction patterns. Orthologous protein sequences were collected for the P1 and P2Y receptors, and sequence conservation was calculated based on Shannon entropy to identify highly conserved residues. To analyze the ligand interaction patterns, we performed docking studies on the P1 and P2Y receptors using known ligand information extracted from the ChEMBL database. We analyzed how the conserved residues are related to ligand-binding sites and how the key interacting residues differ between P1 and P2Y receptors, or between agonists and antagonists. We extracted new similarities and differences between the receptor subtypes, and the results can be used for designing new ligands by predicting hotspot residues that are important for functional selectivity.

Amyotrophic lateral sclerosis disease-related mutations disrupt the dimerization of superoxide dismutase 1 - A comparative molecular dynamics simulation study

More than 150 genes are involved in amyotrophic lateral sclerosis (ALS), with superoxide dismutase 1 (SOD1) being one of the most studied. Mutations in SOD1 gene, which encodes the enzyme SOD1 is the second most prevalent and studied cause of familial ALS. SOD1 is a ubiquitous, homodimeric metalloenzyme that forms a critical component of the cellular defense against reactive oxygen species. Several mutations in the SOD1 enzyme cause misfolding, dimerization instability, and increased aggregate formation in ALS. However, there is a lack of information on the dimerization of SOD1 monomers and the mechanistic underpinnings on how the pathogenic mutations disrupt the dimerization mechanism. Here, we presented microsecond-scale molecular dynamics (MD) simulations to unravel how interface-based mutations compromise SOD1 dimerization and provide mechanistic understanding into the corresponding process using WT and three interface-based mutant systems (A4V, T54R, and I113T). Structural stability analysis showed that the mutant systems displayed disparate variations in the catalytic sites which may directly alter the stability and activity of the SOD1 enzyme. Based on the dynamic network analysis and principal component analysis, it has been identified that the mutations weakened the correlated motions along the dimer interface and altered the protein conformational behavior, thus weakening the stability of dimer formation. Moreover, the simulation results identified crucial residues such as G51, D52, G114, I151, and Q153 in establishing the dimerization interaction network, which were weakened or absent in the presence of interfacial mutants. Surface potential analysis on mutant systems also displayed changes in the dimerization potential, thus showing the unfavorable dimer formation. Furthermore, network analysis identified the hotspot residues necessary for SOD1 signal transduction which were surprisingly found in the catalytic sites rather than the anticipated dimerization interface.

Energy Transport in Class B GPCRs: Role of Protein-Water Dynamics and Activation

We compute energy exchange networks (EENs) through glucagon-like peptide-1 receptor (GLP-1R), a class B G-protein-coupled receptor (GPCR), in inactive and two active states, one activated by a peptide ligand and the other by a small molecule agonist, from results of molecular dynamics simulations. The reorganized network upon activation contains contributions from structural as well as from dynamic changes and corresponding entropic contributions to the free energy of activation, which are estimated in terms of the change in rates of energy transfer across non-covalent contacts. The role of water in the EENs and in activation of GLP-1R is also investigated. The dynamics of water in contact with the central polar network of the transmembrane region is found to be significantly slower for both activated states compared to the inactive state. This result is consistent with the contribution of water molecules to activation of GLP-1R previously suggested and resembles water dynamics in parts of the transmembrane region found in earlier studies of rhodopsin-like GPCRs.

A Statistical Journey through the Topological Determinants of the β2 Adrenergic Receptor Dynamics

Activation of G-protein-coupled receptors (GPCRs) is mediated by molecular switches throughout the transmembrane region of the receptor. In this work, we continued along the path of a previous computational study wherein energy transport in the β2 Adrenergic Receptor (β2-AR) was examined and allosteric switches were identified in the molecular structure through the reorganization of energy transport networks during activation. In this work, we further investigated the allosteric properties of β2-AR, using Protein Contact Networks (PCNs). In this paper, we report an extensive statistical analysis of the topological and structural properties of β2-AR along its molecular dynamics trajectory to identify the activation pattern of this molecular system. The results show a distinct character to the activation that both helps to understand the allosteric switching previously identified and confirms the relevance of the network formalism to uncover relevant functional features of protein molecules.

In Silico Study of Allosteric Communication Networks in GPCR Signaling Bias

Signaling bias is a promising characteristic of G protein-coupled receptors (GPCRs) as it provides the opportunity to develop more efficacious and safer drugs. This is because biased ligands can avoid the activation of pathways linked to side effects whilst still producing the desired therapeutic effect. In this respect, a deeper understanding of receptor dynamics and implicated allosteric communication networks in signaling bias can accelerate the research on novel biased drug candidates. In this review, we aim to provide an overview of computational methods and techniques for studying allosteric communication and signaling bias in GPCRs. This includes (i) the detection of allosteric communication networks and (ii) the application of network theory for extracting relevant information pipelines and highly communicated sites in GPCRs. We focus on the most recent research and highlight structural insights obtained based on the framework of allosteric communication networks and network theory for GPCR signaling bias.

Insights into the dynamic interactions at chemokine-receptor interfaces and mechanistic models of chemokine binding

Chemokine receptors are the central signaling hubs of several processes such as cell migration, chemotaxis and cell positioning. In this graphical review, we provide an overview of the structural and mechanistic principles governing chemokine recognition that are currently emerging. Structural models of chemokine-receptor co-complexes with endogenous chemokines, viral chemokines and therapeutics have been resolved that highlight multiple interaction sites, termed as CRS1, CRS1.5 etc. The first site of interaction has been shown to be the N-terminal domain of the receptors (CRS1 site). A large structural flexibility of the N-terminal domain has been reported that was supported by both experimental and simulation studies. Upon chemokine binding, the N-terminal domain appears to show constricted dynamics and opens up to interact with the chemokine via a large interface. The subsequent sites such as CRS1.5 and CRS2 sites have been structurally well resolved although differences arise such as the localization of the N-terminus of the ligand to a major or minor pocket of the orthosteric binding site. Several computational studies have highlighted the dynamic protein-protein interface at the CRS1 site that seemingly appears to resolve the differences in NMR and mutagenesis studies. Interestingly, the differential dynamics at the CRS1 site suggests a mixed model of binding with complex signatures of both conformational selection and induced fit models. Integrative experimental and computational approaches could help unravel the structural basis of promiscuity and specificity in chemokine-receptor binding and open up new avenues of therapeutic design.

Phosphorylation Induced Conformational Transitions in DNA Polymerase β

DNA polymerase β (pol β) is a member of the X- family of DNA polymerases that catalyze the distributive addition of nucleoside triphosphates during base excision DNA repair. Previous studies showed that the enzyme was phosphorylated in vitro with PKC at two serines (44 and 55), causing loss of DNA polymerase activity but not DNA binding. In this work, we have investigated the phosphorylation-induced conformational changes in DNA polymerase β in the presence of Mg ions. We report a comprehensive atomic resolution study of wild type and phosphorylated DNA polymerase using molecular dynamics (MD) simulations. The results are examined via novel methods of internal dynamics and energetics analysis to reveal the underlying mechanism of conformational transitions observed in DNA pol β. The results show drastic conformational changes in the structure of DNA polymerase β due to S44 phosphorylation. Phosphorylation-induced conformational changes transform the enzyme from a closed to an open structure. The dynamic cross-correlation shows that phosphorylation enhances the correlated motions between the different domains. Centrality network analysis reveals that the S44 phosphorylation causes structural rearrangements and modulates the information pathway between the Lyase domain and base pair binding domain. Further analysis of our simulations reveals that a critical hydrogen bond (between S44 and E335) disruption and the formation of three additional salt bridges are potential drivers of these conformational changes. In addition, we found that two of these additional salt bridges form in the presence of Mg ions on the active sites of the enzyme. These results agree with our previous study of DNA pol β S44 phosphorylation without Mg ions which predicted the deactivation of DNA pol β. However, the phase space of structural transitions induced by S44 phosphorylation is much richer in the presence of Mg ions.

Biophysical Insight into the SARS-CoV2 Spike-ACE2 Interaction and Its Modulation by Hepcidin through a Multifaceted Computational Approach

At the center of the SARS-CoV2 infection, the spike protein and its interaction with the human receptor ACE2 play a central role in the molecular machinery of SARS-CoV2 infection of human cells. Vaccine therapies are a valuable barrier to the worst effects of the virus and to its diffusion, but the need of purposed drugs is emerging as a core target of the fight against COVID19. In this respect, the repurposing of drugs has already led to discovery of drugs thought to reduce the effects of the cytokine storm, but still a drug targeting the spike protein, in the infection stage, is missing. In this work, we present a multifaceted computational approach strongly grounded on a biophysical modeling of biological systems, so to disclose the interaction of the SARS-CoV2 spike protein with ACE2 with a special focus to an allosteric regulation of the spike-ACE2 interaction. Our approach includes the following methodologies: Protein Contact Networks and Network Clustering, Targeted Molecular Dynamics, Elastic Network Modeling, Perturbation Response Scanning, and a computational analysis of energy flow and SEPAS as a protein-softness and monomer-based affinity predictor. We applied this approach to free (closed and open) states of spike protein and spike-ACE2 complexes. Eventually, we analyzed the interactions of free and bound forms of spike with hepcidin (HPC), the major hormone in iron regulation, recently addressed as a central player in the COVID19 pathogenesis, with a special emphasis to the most severe outcomes. Our results demonstrate that, compared with closed and open states, the spike protein in the ACE2-bound state shows higher allosteric potential. The correspondence between hinge sites and the Allosteric Modulation Region (AMR) in the S-ACE complex suggests a molecular basis for hepcidin involvement in COVID19 pathogenesis. We verify the importance of AMR in different states of spike and then study its interactions with HPC and the consequence of the HPC-AMR interaction on spike dynamics and its affinity for ACE2. We propose two complementary mechanisms for HPC effects on spike of SARS-CoV-2; (a) HPC acts as a competitive inhibitor when spike is in a preinfection state (open and with no ACE2), (b) the HPC-AMR interaction pushes the spike structure into the safer closed state. These findings need clear molecular in vivo verification beside clinical observations.

Subtle Chemical Changes Cross the Boundary between Agonist and Antagonist: New A3 Adenosine Receptor Homology Models and Structural Network Analysis Can Predict This Boundary

Distinguishing compounds' agonistic or antagonistic behavior would be of great utility for the rational discovery of selective modulators. We synthesized truncated nucleoside derivatives and discovered 6c (K_i = 2.40 nM) as a potent human A₃ adenosine receptor (hA₃AR) agonist, and subtle chemical modification induced a shift from antagonist to agonist. We elucidated this shift by developing new hA₃AR homology models that consider the pharmacological profiles of the ligands. Taken together with molecular dynamics (MD) simulation and three-dimensional (3D) structural network analysis of the receptor-ligand complex, the results indicated that the hydrogen bonding with Thr94^3.36 and His272^7.43 could make a stable interaction between the 3'-amino group with TM3 and TM7, and the corresponding induced-fit effects may play important roles in rendering the agonistic effect. Our results provide a more precise understanding of the compounds' actions at the atomic level and a rationale for the design of new drugs with specific pharmacological profiles.

Activation-Induced Reorganization of Energy Transport Networks in the β2 Adrenergic Receptor

We compute energy exchange networks (EENs) through the β₂ adrenergic receptor (β₂AR), a G-protein coupled receptor (GPCR), in inactive and active states, based on the results of molecular dynamics simulations of this membrane bound protein. We introduce a new definition for the reorganization of EENs upon activation that depends on the relative change in rates of energy transfer across noncovalent contacts throughout the protein. On the basis of the reorganized network that we obtain for β₂AR upon activation, we identify a branched pathway between the agonist binding site and the cytoplasmic region, where a G-protein binds to the receptor when activated. The pathway includes all of the motifs containing molecular switches previously identified as contributing to the allosteric transition of β₂AR upon agonist binding. EENs and their reorganization upon activation are compared with structure-based contact networks computed for the inactive and active states of β₂AR.

Mapping the Intramolecular Communications among Different Glutamate Dehydrogenase States Using Molecular Dynamics

Glutamate dehydrogenase (GDH) is a ubiquitous enzyme that catalyzes the reversible oxidative deamination of glutamate to α-ketoglutarate. It acts as an important branch-point enzyme between carbon and nitrogen metabolisms. Due to the multifaceted roles of GDH in cancer, hyperinsulinism/hyperammonemia, and central nervous system development and pathologies, tight control of its activity is necessitated. To date, several GDH structures have been solved in its closed form; however, intrinsic structural information in its open and apo forms are still deficient. Moreover, the allosteric communications and conformational changes taking place in the three different GDH states are not well studied. To mitigate these drawbacks, we applied unbiased molecular dynamic simulations (MD) and network analysis to three different GDH states i.e., apo, active, and inactive forms, for investigating their modulatory mechanisms. In this paper, based on MD and network analysis, crucial residues important for signal transduction, conformational changes, and maps of information flow among the different GDH states were elucidated. Moreover, with the recent findings of allosteric modulators, an allosteric wiring illustration of GDH intramolecular signal transductions would be of paramount importance to obtain the process of this enzyme regulation. The structural insights gained from this study will pave way for large-scale screening of GDH regulators and could support researchers in the design and development of new and potent GDH ligands.

Energy flow and intersubunit signalling in GSAM: A non-equilibrium molecular dynamics study

Non-equilibrium molecular dynamics simulations of vibrational energy flow induced by the imposition of a thermal gradient have been performed on the μ2-dimeric enzyme glutamate-1-semialdehyde aminomutase (GSAM), the key enzyme in the biosynthesis of chlorophyll, in order to identify energy transport pathways and to elucidate their role as potential allosteric communication networks for coordinating functional dynamics, specifically the negative cooperativity observed in the motion of the two active site gating loops. Fully atomistic MD simulations of thermal diffusion were executed with a GROMACS simulation package on a fully solvated GSAM enzyme by heating various active site target ligands (initially, catalytic intermediates and cofactors) to 300K while holding the remainder of the protein and the solvent bath at 10K and monitoring the temperature T(t) of all the enzyme residues as a function of time over a 1ns observation window. Energy is observed to be deposited in a relatively small number of discrete chains of residues most of which contribute to specific structural or biochemical functionality. Thermal linkages between all thermally active chains were established by isolating a specific pair of chains and performing a thermal diffusion simulation on the pair, one held at 300K and the other at 10K, with the rest of the protein frozen in its initial atomic configuration and thus thermally unresponsive. Proceeding in this way, it was possible to map out multiple pathways of vibrational energy flow leading from one of the active sites through a network of contiguous residues, many of which were evolutionarily conserved and linked by hydrogen bonds, into the other active site and ultimately to the other gating loop.

Conformational Changes Induced by S34Y and R98C Variants in the Death Domain of Myd88

Myeloid differentiating factor 88 (Myd88) is a universal adaptor protein that plays a critical role in innate immunity by mediating TLR downstream signaling. Myd88 death domain (DD) forms an oligomeric complex by association with other DD-containing proteins such as IRAK4. Despite its universal role, polymorphisms in Myd88 can result in several diseases. Previous studies have suggested that, out of several non-synonymous single-nucleotide polymorphisms (nsSNPs), the variants S34Y and R98C in the DD of Myd88 disrupt the formation of the Myddosome complex. Therefore, we performed molecular dynamics (MD) simulations on wild-type (Myd88^WT) and mutant (Myd88^S34Y, Myd88^R98C) DDs to evaluate the subtle conformational changes induced by these mutations. Our results suggest that the S34Y variant induces large structural transitions compared to the R98C variant as evidenced by residual flexibility at the variable loop regions, particularly in the H1-H2 loop, and variations in the collective modes of motion observed for wild-type and mutant Myd88 DDs. The residue interaction network strongly suggests a distortion in the interaction pattern at the location of the mutated residue between the wild type and mutants. Moreover, betweenness centrality values indicate that variations in the distribution of functionally important residues may be reflected by distinct residue signal transductions in both wild-type and mutant Myd88 DDs, which may influence the interaction with other DDs in TLR downstream signaling.

Molecular Dynamics Simulations of Adenosine Receptors: Advances, Applications and Trends

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Adenosine receptors (ARs) are transmembrane proteins that belong to the G protein-coupled receptors (GPCRs) superfamily and mediate the biological functions of adenosine. To date, four AR subtypes are known, namely A1, A2A, A2B and A3 that exhibit different signaling pathways, tissue localization, and mechanisms of activation. Moreover, the widespread ARs and their implication in numerous physiological and pathophysiological conditions had made them pivotal therapeutic targets for developing clinically effective agents.

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The crystallographic success in identifying the 3D crystal structures of A2A and A1 ARs has dramatically enriched our understanding of their structural and functional properties such as ligand binding and signal transduction. This, in turn, has provided a structural basis for a larger contribution of computational methods, particularly molecular dynamics (MD) simulations, toward further investigation of their molecular properties and designing bioactive ligands with therapeutic potential. MD simulation has been proved to be an invaluable tool in investigating ARs and providing answers to some critical questions. For example, MD has been applied in studying ARs in terms of ligand-receptor interactions, molecular recognition, allosteric modulations, dimerization, and mechanisms of activation, collectively aiding in the design of subtype selective ligands.

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In this review, we focused on the advances and different applications of MD simulations utilized to study the structural and functional aspects of ARs that can foster the structure-based design of drug candidates. In addition, relevant literature was briefly discussed which establishes a starting point for future advances in the field of drug discovery to this pivotal group of drug targets.

Transmembrane 4 L Six Family Member 5 Senses Arginine for mTORC1 Signaling

The mechanistic target of rapamycin complex (mTORC1) is a signaling hub on the lysosome surface, responding to lysosomal amino acids. Although arginine is metabolically important, the physiological arginine sensor that activates mTOR remains unclear. Here, we show that transmembrane 4 L six family member 5 (TM4SF5) translocates from plasma membrane to lysosome upon arginine sufficiency and senses arginine, culminating in mTORC1/S6K1 activation. TM4SF5 bound active mTOR upon arginine sufficiency and constitutively bound amino acid transporter SLC38A9. TM4SF5 binding to the cytosolic arginine sensor Castor1 decreased upon arginine sufficiency, thus allowing TM4SF5-mediated sensing of metabolic amino acids. TM4SF5 directly bound free L-arginine via its extracellular loop possibly for the efflux, being supported by mutant study and homology and molecular docking modeling. Therefore, we propose that lysosomal TM4SF5 senses and enables arginine efflux for mTORC1/S6K1 activation, and arginine-auxotroph in hepatocellular carcinoma may be targeted by blocking the arginine sensing using anti-TM4SF5 reagents.

A Molecular Dynamics Approach to Explore the Intramolecular Signal Transduction of PPAR-α

Dynamics and functions of the peroxisome proliferator-activated receptor (PPAR)-α are modulated by the types of ligands that bind to the orthosteric sites. While several X-ray crystal structures of PPAR-α have been determined in their agonist-bound forms, detailed structural information in their apo and antagonist-bound states are still lacking. To address these limitations, we apply unbiased molecular dynamics simulations to three different PPAR-α systems to determine their modulatory mechanisms. Herein, we performed hydrogen bond and essential dynamics analyses to identify the important residues involved in polar interactions and conformational structural variations, respectively. Furthermore, betweenness centrality network analysis was carried out to identify key residues for intramolecular signaling. The differences observed in the intramolecular signal flow between apo, agonist- and antagonist-bound forms of PPAR-α will be useful for calculating maps of information flow and identifying key residues crucial for signal transductions. The predictions derived from our analysis will be of great help to medicinal chemists in the design of effective PPAR-α modulators and additionally in understanding their regulation and signal transductions.

Insights into the dynamic nature of the dsRNA-bound TLR3 complex

Toll-like receptor 3 (TLR3), an endosomal receptor crucial for immune responses upon viral invasion. The TLR3 ectodomain (ECD) is responsible for double-stranded RNA (dsRNA) recognition and mutational analysis suggested that TLR3 ECD C-terminal dimerization is essential for dsRNA binding. Moreover, the L412F polymorphism of TLR3 is associated with human diseases. Although the mouse structure of the TLR3-dsRNA complex provides valuable insights, the structural dynamic behavior of the TLR3-dsRNA complex in humans is not completely understood. Hence, in this study, we performed molecular dynamic simulations of human wild-type and mutant TLR3 complexes. Our results suggested that apoTLR3 ECD dimers are unlikely to be stable due to the distance between the monomers are largely varied during simulations. The observed interaction energies and hydrogen bonds in dsRNA-bound TLR3 wild-type and mutant complexes indicate the presence of a weak dimer interface at the TLR3 ECD C-terminal site, which is required for effective dsRNA binding. The L412F mutant exhibited similar dominant motion compared to wild-type. Additionally, we identified the distribution of crucial residues for signal propagation in TLR3-dsRNA complex through the evaluation of residue betweenness centrality (C_B). The results of this study extend our understanding of TLR3-dsRNA complex, which may assist in TLR3 therapeutics.

Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery

The advent of advanced molecular modeling software, big data analytics, and high-speed processing units has led to the exponential evolution of modern drug discovery and better insights into complex biological processes and disease networks. This has progressively steered current research interests to understanding protein-protein interaction (PPI) systems that are related to a number of relevant diseases, such as cancer, neurological illnesses, metabolic disorders, etc. However, targeting PPIs are challenging due to their "undruggable" binding interfaces. In this review, we focus on the current obstacles that impede PPI drug discovery, and how recent discoveries and advances in in silico approaches can alleviate these barriers to expedite the search for potential leads, as shown in several exemplary studies. We will also discuss about currently available information on PPI compounds and systems, along with their usefulness in molecular modeling. Finally, we conclude by presenting the limits of in silico application in drug discovery and offer a perspective in the field of computer-aided PPI drug discovery.

Implications for human odor sensing revealed from the statistics of odorant-receptor interactions

Binding of odorants to olfactory receptors (ORs) elicits downstream chemical and neural signals, which are further processed to odor perception in the brain. Recently, Mainland and colleagues have measured more than 500 pairs of odorant-OR interaction by a high-throughput screening assay method, opening a new avenue to understanding the principles of human odor coding. Here, using a recently developed minimal model for OR activation kinetics, we characterize the statistics of OR activation by odorants in terms of three empirical parameters: the half-maximum effective concentration EC₅₀, the efficacy, and the basal activity. While the data size of odorants is still limited, the statistics offer meaningful information on the breadth and optimality of the tuning of human ORs to odorants, and allow us to relate the three parameters with the microscopic rate constants and binding affinities that define the OR activation kinetics. Despite the stochastic nature of the response expected at individual OR-odorant level, we assess that the confluence of signals in a neuron released from the multitude of ORs is effectively free of noise and deterministic with respect to changes in odorant concentration. Thus, setting a threshold to the fraction of activated OR copy number for neural spiking binarizes the electrophysiological signal of olfactory sensory neuron, thereby making an information theoretic approach a viable tool in studying the principles of odor perception.

Despite the decades of research, quantitative details of human olfaction have remained largely unexplored. However, a high-throughput measurement has recently been carried out to produce dose-response data between a set of odorants and a repertoire of human olfactory receptors. We characterized each pair of odorant-receptor interaction in terms of EC50, efficacy, and basal level, a strategy often adopted in biochemical, pharmacological sciences to describe the response of receptors to cognate ligands. The distributions of EC50 values and efficacies acquired from the analysis provide glimpses into how human olfactory receptors are tuned to odorants. Specifically, the response of human ORs is optimized around ∼ 100μM of odorant. Next, the efficacies of OR responses to odorants are bi-exponentially distributed, which indicates that the strength of odorant-OR interaction is classified into strong and weak subgroups. By showing that the stochastic response of individual receptor to odorant can effectively be binarized at cellular level through olfactory processes, we also provide a theoretical basis for an information theoretical approach in studying the principles of odor perception.

Understanding G Protein-Coupled Receptor Allostery via Molecular Dynamics Simulations: Implications for Drug Discovery

Unraveling the mystery of protein allostery has been one of the greatest challenges in both structural and computational biology. However, recent advances in computational methods, particularly molecular dynamics (MD) simulations, have led to its utility as a powerful and popular tool for the study of protein allostery. By capturing the motions of a protein's constituent atoms, simulations can enable the discovery of allosteric hot spots and the determination of the mechanistic basis for allostery. These structural and dynamic studies can provide a foundation for a wide range of applications, including rational drug design and protein engineering. In our laboratory, the use of MD simulations and network analysis assisted in the elucidation of the allosteric hotspots and intracellular signal transduction of G protein-coupled receptors (GPCRs), primarily on one of the adenosine receptor subtypes, A_2A adenosine receptor (A_2AAR). In this chapter, we describe a method for calculating the map of allosteric signal flow in different GPCR conformational states and illustrate how these concepts have been utilized in understanding the mechanism of GPCR allostery. These structural studies will provide valuable insights into the allosteric and orthosteric modulations that would be of great help to design novel drugs targeting GPCRs in pathological states.

Computational study to understand the energy transfer pathways within amicyanin

Vibrational energy diffusivities between the residues present in Amicyanin copper protein are calculated and presented in form of communication map. From those results energy flow pathways from the copper metal ion to the inter protein residue Glu31 are identified. Our finding suggests many different pathways are possible and copper metal ion in oxidized and reduced state switches the pathways. Our finding also suggests the cooperative nature of surrounding residues and water molecules towards selecting the pathways. The major transport channels in the oxidised state are, Cu²⁺---> MET28---> LYS29---> TYR30---> GLU31 and Cu²⁺---> MET98---> TYR30--- > GLU31. And in the reduced state Cu⁺---> CYS9---> TYR30---> GLU31 and Cu⁺---> MET28---> LYS2---> TYR30---> GLU31. We studied further the interaction energies between the copper ion and neighbouring residues using B3LYP/QZVP method. Both the methods complement each other in predicting the energy flow pathways and the cooperative nature of residues.

An information theoretic framework reveals a tunable allosteric network in group II chaperonins

ATP-dependent allosteric regulation of the ring-shaped group II chaperonins remains ill defined, in part because their complex oligomeric topology has limited the success of structural techniques in suggesting allosteric determinants. Further, their high sequence conservation has hindered the prediction of allosteric networks using mathematical covariation approaches. Here, we develop an information theoretic strategy that is robust to residue conservation and apply it to group II chaperonins. We identify a contiguous network of covarying residues that connects all nucleotide-binding pockets within each chaperonin ring. An interfacial residue between the networks of neighboring subunits controls positive cooperativity by communicating nucleotide occupancy within each ring. Strikingly, chaperonin allostery is tunable through single mutations at this position. Naturally occurring variants at this position that double the extent of positive cooperativity are less prevalent in nature. We propose that being less cooperative than attainable allows chaperonins to support robust folding over a wider range of metabolic conditions.

Signaling within Allosteric Machines: Signal Transmission Pathways Inside G Protein-Coupled Receptors

In recent years, our understanding of function of G protein-coupled receptors (GPCRs) has changed from a picture of simple signal relays, transmitting only a particular signal to a particular G protein heterotrimer, to versatile machines, capable of various responses to different stimuli and being modulated by various factors. Some recent reports provide not only the data on ligands/modulators and resultant signals induced by them, but also deeper insights into exact pathways of signal migration and mechanisms of signal transmission through receptor structure. Combination of these computational and experimental data sheds more light on underlying mechanisms of signal transmission and signaling bias in GPCRs. In this review we focus on available clues on allosteric pathways responsible for complex signal processing within GPCRs structures, with particular emphasis on linking compatible in silico- and in vitro-derived data on the most probable allosteric connections.

Ultraslow Water-Mediated Transmembrane Interactions Regulate the Activation of A2A Adenosine Receptor

Water molecules inside a G-protein coupled receptor (GPCR) have recently been spotlighted in a series of crystal structures. To decipher the dynamics and functional roles of internal water molecules in GPCR activity, we studied the A2A adenosine receptor using microsecond molecular-dynamics simulations. Our study finds that the amount of water flux across the transmembrane (TM) domain varies depending on the receptor state, and that the water molecules of the TM channel in the active state flow three times more slowly than those in the inactive state. Depending on the location in solvent-protein interface as well as the receptor state, the average residence time of water in each residue varies from ∼O(10(2)) ps to ∼O(10(2)) ns. Especially, water molecules, exhibiting ultraslow relaxation (∼O(10(2)) ns) in the active state, are found around the microswitch residues that are considered activity hotspots for GPCR function. A continuous allosteric network spanning the TM domain, arising from water-mediated contacts, is unique in the active state, underscoring the importance of slow water molecules in the activation of GPCRs.

Gorge Motions of Acetylcholinesterase Revealed by Microsecond Molecular Dynamics Simulations

Acetylcholinesterase, with a deep, narrow active-site gorge, attracts enormous interest due to its particularly high catalytic efficiency and its inhibitors used for treatment of Alzheimer’s disease. To facilitate the massive pass-through of the substrate and inhibitors, “breathing” motions to modulate the size of the gorge are an important prerequisite. However, the molecular mechanism that governs such motions is not well explored. Here, to systematically investigate intrinsic motions of the enzyme, we performed microsecond molecular dynamics simulations on the monomer and dimer of Torpedo californica acetylcholinesterase (TcAChE) as well as the complex of TcAChE bound with the drug E2020. It has been revealed that protein-ligand interactions and dimerization both keep the gorge in bulk, and opening events of the gorge increase dramatically compared to the monomer. Dynamics of three subdomains, S3, S4 and the Ω-loop, are tightly associated with variations of the gorge size while the dynamics can be changed by ligand binding or protein dimerization. Moreover, high correlations among these subdomains provide a basis for remote residues allosterically modulating the gorge motions. These observations are propitious to expand our understanding of protein structure and function as well as providing clues for performing structure-based drug design.

Network topology of NaV1.7 mutations in sodium channel-related painful disorders

BACKGROUND

Gain-of-function mutations in SCN9A gene that encodes the voltage-gated sodium channel NaV1.7 have been associated with a wide spectrum of painful syndromes in humans including inherited erythromelalgia, paroxysmal extreme pain disorder and small fibre neuropathy. These mutations change the biophysical properties of NaV1.7 channels leading to hyperexcitability of dorsal root ganglion nociceptors and pain symptoms. There is a need for better understanding of how gain-of-function mutations alter the atomic structure of Nav1.7.

RESULTS

We used homology modeling to build an atomic model of NaV1.7 and a network-based theoretical approach, which can predict interatomic interactions and connectivity arrangements, to investigate how pain-related NaV1.7 mutations may alter specific interatomic bonds and cause connectivity rearrangement, compared to benign variants and polymorphisms. For each amino acid substitution, we calculated the topological parameters betweenness centrality (B ct ), degree (D), clustering coefficient (CC ct ), closeness (C ct ), and eccentricity (E ct ), and calculated their variation (Δ value  = mutant value -WT value ). Pathogenic NaV1.7 mutations showed significantly higher variation of |ΔB ct | compared to benign variants and polymorphisms. Using the cut-off value ±0.26 calculated by receiver operating curve analysis, we found that ΔB ct correctly differentiated pathogenic NaV1.7 mutations from variants not causing biophysical abnormalities (nABN) and homologous SNPs (hSNPs) with 76% sensitivity and 83% specificity.

CONCLUSIONS

Our in-silico analyses predict that pain-related pathogenic NaV1.7 mutations may affect the network topological properties of the protein and suggest |ΔB ct | value as a potential in-silico marker.

Biophysical and computational methods to analyze amino acid interaction networks in proteins

Globular proteins are held together by interacting networks of amino acid residues. A number of different structural and computational methods have been developed to interrogate these amino acid networks. In this review, we describe some of these methods, including analyses of X-ray crystallographic data and structures, computer simulations, NMR data, and covariation among protein sequences, and indicate the critical insights that such methods provide into protein function. This information can be leveraged towards the design of new allosteric drugs, and the engineering of new protein function and protein regulation strategies.

Water-Mediated Energy Dynamics in a Homodimeric Hemoglobin

We examine energy dynamics in the unliganded and liganded states of the homodimeric hemoglobin from Scapharca inaequivalvis (HbI), which exhibits cooperativity mediated by the cluster of water molecules at the interface upon ligand binding and dissociation. We construct and analyze a dynamic network in which nodes representing the residues, hemes, and water cluster are connected by edges that represent energy transport times, as well as a nonbonded network (NBN) indicating regions that respond rapidly to local strain within the protein via nonbonded interactions. One of the two largest NBNs includes the Lys30-Asp89 salt bridge critical for stabilizing the dimer. The other includes the hemes and surrounding residues, as well as, in the unliganded state, the cluster of water molecules between the globules. Energy transport in the protein appears to be controlled by the Lys30-Asp89 salt bridge critical for stabilizing the dimer, as well as the interface water cluster in the unliganded state. Possible connections between energy transport dynamics in response to local strain identified here and allosteric transitions in HbI are discussed.

Transient receptor potential vanilloid type 1 antagonists: a patent review (2011 - 2014)

INTRODUCTION

Transient receptor potential vanilloid type 1 (TRPV1) is a nonselective cation channel that can be activated by noxious heat, low pH and vanilloid compounds such as capsaicin. Since TRPV1 acts as an integrator of painful stimuli, TRPV1 antagonists can be used as promising therapeutics for new types of analgesics.

AREAS COVERED

This review article covers the patents that claim TRPV1 antagonists and were published during 2011 - 2014. The patent evaluation is organized according to the applicant companies, and the representative chemical entities with important in vitro and in vivo data are summarized.

EXPERT OPINION

Many pharmaceutical companies showed promising results in the discovery of potent small molecule TRPV1 antagonists, and recently, a number of small molecule TRPV1 antagonists have been advanced into clinical trials. Unfortunately, several candidate molecules showed critical side effects such as hyperthermia and impaired noxious heat sensation in humans, leading to their withdrawal from clinical trials. Some TRPV1 antagonists patented in recent years (2011 - 2014) overcame these undesirable side effects, making the development of TRPV1 antagonists much more promising.

Decoding Structural Properties of a Partially Unfolded Protein Substrate: En Route to Chaperone Binding

Many proteins comprising of complex topologies require molecular chaperones to achieve their unique three-dimensional folded structure. The E.coli chaperone, GroEL binds with a large number of unfolded and partially folded proteins, to facilitate proper folding and prevent misfolding and aggregation. Although the major structural components of GroEL are well defined, scaffolds of the non-native substrates that determine chaperone-mediated folding have been difficult to recognize. Here we performed all-atomistic and replica-exchange molecular dynamics simulations to dissect non-native ensemble of an obligate GroEL folder, DapA. Thermodynamics analyses of unfolding simulations revealed populated intermediates with distinct structural characteristics. We found that surface exposed hydrophobic patches are significantly increased, primarily contributed from native and non-native β-sheet elements. We validate the structural properties of these conformers using experimental data, including circular dichroism (CD), 1-anilinonaphthalene-8-sulfonic acid (ANS) binding measurements and previously reported hydrogen-deutrium exchange coupled to mass spectrometry (HDX-MS). Further, we constructed network graphs to elucidate long-range intra-protein connectivity of native and intermediate topologies, demonstrating regions that serve as central “hubs”. Overall, our results implicate that genomic variations (or mutations) in the distinct regions of protein structures might disrupt these topological signatures disabling chaperone-mediated folding, leading to formation of aggregates.

Several non-native proteins require molecular chaperones for proper folding. Many unfolded proteins if not folded accurately, become causal factors in various types of misfolding or aggregation induced diseases such as Alzheimer′s, Huntington′s and several other neurodegenerative disorders. However, structural information of non-folded proteins especially chaperone-dependent proteins is difficult to probe experimentally due to their inherent aggregation propensities. In this work, we study DapA protein, which exhibits obligate requirement on GroEL chaperonin machinery for its folding. We use molecular dynamics simulations to reveal populated intermediate structures of DapA in atomic details. The most plausible intermediate was found to be in agreement with recently reported hydrogen-exchange experimental data. Significant increase in surface exposed hydrophobicity was observed in intermediates compared to native, which was further validated using ANS binding experiments. We also constructed network model of these intermediates that provides remarkable insights into stable hubs (or important residues) underlying diverse states of unfolded proteins. In summary, our work provides a molecular picture of an unfolded protein that is en route to chaperone binding, and these underlying structural properties might act as a molecular signal for their productive folding.

Communication over the network of binary switches regulates the activation of A2A adenosine receptor

Dynamics and functions of G-protein coupled receptors (GPCRs) are accurately regulated by the type of ligands that bind to the orthosteric or allosteric binding sites. To glean the structural and dynamical origin of ligand-dependent modulation of GPCR activity, we performed total ~ 5 μsec molecular dynamics simulations of A_2A adenosine receptor (A_2AAR) in its apo, antagonist-bound, and agonist-bound forms in an explicit water and membrane environment, and examined the corresponding dynamics and correlation between the 10 key structural motifs that serve as the allosteric hotspots in intramolecular signaling network. We dubbed these 10 structural motifs “binary switches” as they display molecular interactions that switch between two distinct states. By projecting the receptor dynamics on these binary switches that yield 2¹⁰ microstates, we show that (i) the receptors in apo, antagonist-bound, and agonist-bound states explore vastly different conformational space; (ii) among the three receptor states the apo state explores the broadest range of microstates; (iii) in the presence of the agonist, the active conformation is maintained through coherent couplings among the binary switches; and (iv) to be most specific, our analysis shows that W246, located deep inside the binding cleft, can serve as both an agonist sensor and actuator of ensuing intramolecular signaling for the receptor activation. Finally, our analysis of multiple trajectories generated by inserting an agonist to the apo state underscores that the transition of the receptor from inactive to active form requires the disruption of ionic-lock in the DRY motif.

As the key signal transmitters of a number of physiological processes, G-protein coupled receptors (GPCRs) are arguably one of the most important therapeutic targets. Orchestration of the intra-molecular signaling across transmembrane domain is key for the function of GPCRs. To investigate the microscopic underpinnings of intramolecular signaling that regulates the activation of GPCRs, we performed molecular dynamics simulations of the receptor in three distinct ligand-bound states using A_2A adenosine receptor as a model system of GPCRs. Statistical analyses on the dynamics of and correlation among the 10 “binary switches” reveal that the three receptor states retain distinct dynamic properties. The antagonist- and agonist-bound forms of the receptors explore vastly different conformational space, and the apo form lies between them, yet located closer to the antagonist-bound form. In regard to the agonist-binding triggered activation mechanism, the correlation map among the 10 binary switches unequivocally shows that direct sensing of agonist ligand by the indole ring of W246 actuates the rest of intramolecular signaling.