Structural insights into the role of deleterious mutations at the dimeric interface of Toll-like receptor interferon-ß related adaptor protein.

Toll-like receptors (TLRs) are major players in the innate immune system-recognizing pathogens and differentiating self/non-self components of immunity. These proteins are present either on the plasma membrane or endosome and recognize pathogens at their extracellular domains. They are characterized by a single transmembrane helix and an intracellular toll-interleukin-1 receptor (TIR) domain. Few TIRs directly invoke downstream signaling, while others require other TIR domains of adaptors like TIR domain-containing adaptor-inducing interferon-ß (TRIF) and TRIF-related adaptor molecule (TRAM). On recognizing pathogenic lipopolysaccharides, TLR4 dimerises and interacts with the intracellular TRAM dimer through the TIR domain to recruit a downstream signaling adaptor (TRIF). We have performed an in-depth study of the structural effect of two mutations (P116H and C117H) at the dimeric interface of the adaptor TRAM, which are known to abrogate downstream signaling. We modeled the structure and performed molecular dynamics studies in order to decipher the structural basis of this effect. We observed that these mutations led to an increased radius of gyration of the complex and resulted in several changes to the interaction energy values when compared against the wild type (WT) and positive control mutants. We identified highly interacting residues as hubs in the WT dimer, and a few such hubs that were lost in the mutant dimers. Changes in the protein residue path, hampering the information flow between the crucial A86/E87/D88/D89 and T155/S156 sites, were observed for the mutants. Overall, we show that such residue changes can have subtle but long-distance effects, impacting the signaling path allosterically.

Microsecond dynamics of H10N7 influenza neuraminidase reveals the plasticity of loop regions and drug resistance due to the R292K mutation.

At the beginning of the last century, multiple pandemics caused by influenza (flu) viruses severely impacted public health. Despite the development of vaccinations and antiviral medications to prevent and control impending flu outbreaks, unforeseen novel strains and continuously evolving old strains continue to represent a serious threat to human life. Therefore, the recently identified H10N7, for which not much data is available for rational structure-based drug design, needs to be further explored. Here, we investigated the structural dynamics of neuraminidase N7 upon binding of inhibitors, and the drug resistance mechanisms against the oseltamivir (OTV) and laninamivir (LNV) antivirals due to the crucial R292K mutation on the N7 using the computational microscope, molecular dynamics (MD) simulations. In this study, each system underwent long 2 × 1 µs MD simulations to answer the conformational changes and drug resistance mechanisms. These long time-scale dynamics simulations and free energy landscapes demonstrated that the mutant systems showed a high degree of conformational variation compared to their wildtype (WT) counterparts, and the LNV-bound mutant exhibited an extended 150-loop conformation. Further, the molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) calculation and MM/GBSA free energy decomposition were used to characterize the binding of OTV and LNV with WT, and R292K mutated N7, revealing the R292K mutation as drug-resistant, facilitated by a decline in binding interaction and a reduction in the dehydration penalty. Due to the broader binding pocket cavity of the smaller K292 mutant residue relative to the wildtype, the drug carboxylate to K292 hydrogen bonding was lost, and the area surrounding the K292 residue was more accessible to water molecules. This implies that drug resistance could be reduced by strengthening the hydrogen bond contacts between N7 inhibitors and altered N7, creating inhibitors that can form a hydrogen bond to the mutant K292, or preserving the closed cavity conformations.

Comparative protein structure network analysis on 3CLpro from SARS-CoV-1 and SARS-CoV-2.

The main protease Mpro , 3CLpro is an important target from coronaviruses. In spite of having 96% sequence identity among Mpros from SARS-CoV-1 and SARS-CoV-2; the inhibitors used to block the activity of SARS-CoV-1 Mpro so far, were found to have differential inhibitory effect on Mpro of SARS-CoV-2. The possible reason could be due to the difference of few amino acids among the peptidases. Since, overall 3-D crystallographic structure of Mpro from SARS-CoV-1 and SARS-CoV-2 is quite similar and mapping a subtle structural variation is seemingly impossible. Hence, we have attempted to study a structural comparison of SARS-CoV-1 and SARS-CoV-2 Mpro in apo and inhibitor bound states using protein structure network (PSN) based approach at contacts level. The comparative PSNs analysis of apo Mpros from SARS-CoV-1 and SARS-CoV-2 uncovers small but significant local changes occurring near the active site region and distributed throughout the structure. Additionally, we have shown how inhibitor binding perturbs the PSG and the communication pathways in Mpros . Moreover, we have also investigated the network connectivity on the quaternary structure of Mpro and identified critical residue pairs for complex formation using three centrality measurement parameters along with the modularity analysis. Taken together, these results on the comparative PSN provide an insight into conformational changes that may be used as an additional guidance towards specific drug development.

Structural deformability induced in proteins of potential interest associated with COVID-19 by binding of homologues present in ivermectin: Comparative study based in elastic networks models.

The COVID-19 pandemic has accelerated the study of the potential of multi-target drugs (MTDs). The mixture of homologues called ivermectin (avermectin-B1a + avermectin-B1b) has been shown to be a MTD with potential antiviral activity against SARS-CoV-2 in vitro. However, there are few reports on the effect of each homologue on the flexibility and stiffness of proteins associated with COVID-19, described as ivermectin targets. We observed that each homologue was stably bound to the proteins studied and was able to induce detectable changes with Elastic Network Models (ENM). The perturbations induced by each homologue were characteristic of each compound and, in turn, were represented by a disruption of native intramolecular networks (interactions between residues). The homologues were able to slightly modify the conformation and stability of the connection points between the Cα atoms of the residues that make up the structural network of proteins (nodes), compared to free proteins. Each homologue was able to modified differently the distribution of quasi-rigid regions of the proteins, which could theoretically alter their biological activities. These results could provide a biophysical-computational view of the potential MTD mechanism that has been reported for ivermectin.

Dissecting intrinsic and ligand-induced structural communication in the ß3 headpiece of integrins.

BACKGROUND: Graph theory is widely used to dissect structural communication in biomolecular systems. Here, graph theory-based approaches were applied to the headpiece of integrins, adhesion cell-surface receptors that transmit signals across the plasma membranes. METHODS: Protein Structure Network (PSN) analysis incorporating dynamic information either from molecular dynamics simulations or from Elastic Network Models was applied to the ß3 domains from integrins αVß3 and αIIbß3 in their apo and ligand-bound states. RESULTS: Closed and open states of the ß headpiece are characterized by distinct allosteric communication pathways involving highly conserved amino acids at the two different α/ß interfaces in the ßI domain, the closed state being prompted to the closed-to-open transition. In the closed state, pure antagonism is associated with the establishment of communication pathways that start from the ligand, pass through the ß1/α3,α4 interface, and end up in the hybrid domain by involving the Y110-Q82 link, which is weakened in the agonist-bound states. CONCLUSIONS: Allosteric communication in integrins relies on highly conserved and functionally relevant amino acid residues. The αßα-sandwich architecture of integrin ßI domain dictates the structural communication between ligand binding site and hybrid domain. Differently from agonists, pure antagonists are directly involved in allosteric communication pathways and exert long-distance strengthening of the ßI/hybrid interface. Release of the structure network in the ligand binding site is associated with the close-to-open transition accompanying the activation process. GENERAL SIGNIFICANCE: The study strengthens the power of graph-based analyses to decipher allosteric communication intrinsic to protein folds and modified by functionally different ligands.

Structure prediction and network analysis of chitinases from the Cape sundew, Drosera capensis.

BACKGROUND: Carnivorous plants possess diverse sets of enzymes with novel functionalities applicable to biotechnology, proteomics, and bioanalytical research. Chitinases constitute an important class of such enzymes, with future applications including human-safe antifungal agents and pesticides. Here, we compare chitinases from the genome of the carnivorous plant Drosera capensis to those from related carnivorous plants and model organisms. METHODS: Using comparative modeling, in silico maturation, and molecular dynamics simulation, we produce models of the mature enzymes in aqueous solution. We utilize network analytic techniques to identify similarities and differences in chitinase topology. RESULTS: Here, we report molecular models and functional predictions from protein structure networks for eleven new chitinases from D. capensis, including a novel class IV chitinase with two active domains. This architecture has previously been observed in microorganisms but not in plants. We use a combination of comparative and de novo structure prediction followed by molecular dynamics simulation to produce models of the mature forms of these proteins in aqueous solution. Protein structure network analysis of these and other plant chitinases reveal characteristic features of the two major chitinase families. GENERAL SIGNIFICANCE: This work demonstrates how computational techniques can facilitate quickly moving from raw sequence data to refined structural models and comparative analysis, and to select promising candidates for subsequent biochemical characterization. This capability is increasingly important given the large and growing body of data from high-throughput genome sequencing, which makes experimental characterization of every target impractical.

Fascin - F-actin interaction studied by molecular dynamics simulation and protein network analysis.

Actin bundles are an important component of cellular cytoskeleton and participate in the movement of cells. The formation of actin bundles requires the participation of many actin binding proteins (ABPs). Fascin is a member of ABPs, which plays a key role in bundling filamentous actin (F-actin) to bundles. However, the detailed interactions between fascin and F-actin are unclear. In this study, we construct an atomic-level structure of fascin - F-actin complex based on a rather poor cryo-EM data with resolution of 20 nm. We first optimized the geometries of the complex by molecular dynamics (MD) simulation and analyzed the binding site and pose of fascin which bundles two F-actin chains. Next, binding free energy of fascin was calculated by MM/GBSA method. Finally, protein structure network analysis (PSNs) was performed to analyze the key residues for fascin binding. Our results show that residues of K22, E27, E29, K41, K43, R110, R149, K358, R408 and K471 on fascin are important for its bundling, which are in good agreement with the experimental data. On the other hand, the consistent results indicate that the atomic-level model of fascin - F-actin complex is reliable. In short, this model can be used to understand the detailed interactions between fascin and F-actin, and to develop novel potential drugs targeting fascin.Communicated by Ramaswamy H. Sarma.

Molecular insights into mutation-induced conformational changes in Acetyl CoA Carboxylase for improved activity.

Acetyl-CoA carboxylase (ACCase) is crucial for fatty acid biosynthesis and has potential applications in lipid accumulation and advanced biofuel production. Mutations like S659A and S1157A in Saccharomyces cerevisiae ACCase remove the Snf1-regulation sites, resulting in increased enzyme activity with positive effects on the fatty acid pathway. However, the molecular-level understanding of these mutations on ACCase activity remains unexplored. Here, molecular dynamics simulation was conducted to investigate the mutations-induced conformational changes in S. cerevisiae ACCase. The wild-type ACCase was observed to have significant deviation in structure compared to mutant. Additionally, fluctuation of residues associated with biotin binding and Snf1-recognition were reduced in mutant compared to wild-type. Furthermore, the wild-type demonstrated opening motions of the domains, whereas the mutant showed closing movement. The mutation-induced conformational changes were analysed using network parameters, i.e., cliques/communities. The mutant showed an increase in sizes of several communities in AC3-AC4-AC5 domains leading to rigidification. Also, a new community was added in AC1-BT in the mutant, which suggested a substantial shift in the protein conformation. Thus, this study provides a theoretical understanding of the increased activity of ACCase due to two mutations, which can pave the path for enzyme engineering towards improved fatty acid-based fuel and chemical production.

Cancer-related Mutations with Local or Long-range Effects on an Allosteric Loop of p53.

The tumor protein 53 (p53) is involved in transcription-dependent and independent processes. Several p53 variants related to cancer have been found to impact protein stability. Other variants, on the contrary, might have little impact on structural stability and have local or long-range effects on the p53 interactome. Our group previously identified a loop in the DNA binding domain (DBD) of p53 (residues 207-213) which can recruit different interactors. Experimental structures of p53 in complex with other proteins strengthen the importance of this interface for protein-protein interactions. We here characterized with structure-based approaches somatic and germline variants of p53 which could have a marginal effect in terms of stability and act locally or allosterically on the region 207-213 with consequences on the cytosolic functions of this protein. To this goal, we studied 1132 variants in the p53 DBD with structure-based approaches, accounting also for protein dynamics. We focused on variants predicted with marginal effects on structural stability. We then investigated each of these variants for their impact on DNA binding, dimerization of the p53 DBD, and intramolecular contacts with the 207-213 region. Furthermore, we identified variants that could modulate long-range the conformation of the region 207-213 using a coarse-grain model for allostery and all-atom molecular dynamics simulations. Our predictions have been further validated using enhanced sampling methods for 15 variants. The methodologies used in this study could be more broadly applied to other p53 variants or cases where conformational changes of loop regions are essential in the function of disease-related proteins.

Solvent induced conformational changes for the altered activity of laccase: A molecular dynamics study.

The growing demands of solvent-based industries like paint, pharmaceutical, petrochemical, paper and pulp, etc., have directly increased the release of effluents that are rich in hazardous aromatic compounds in the environment. A sustainable biotechnological approach utilizing laccases as biocatalyst enable in biodegradation of these aromatic toxin-rich effluents. However, this enzymatic process is ineffective as laccases lose their stability and catalytic activity at high organic solvent concentrations. In this study, molecular dynamic simulations of a novel solvent tolerant laccase, DLac from Cerrena sp. RSD1 was performed to explore the molecular-level understanding of DLac in 30%(v/v) acetone and acetonitrile. Solvent-induced conformational changes were analyzed via protein structure network, which was illustrated with respect to cliques and communities. In the presence of acetonitrile, the cliques around the active site and substrate-binding site were disjoined, thus the communities lost their network integrity. Whereas with acetone, the community near the substrate-binding site gained new residues and formed a rigidified network that corresponded to enhanced DLac's activity. Moreover, prominent solvent binding sites were speculated, which can be probable mutation targets to further improve solvent tolerance and catalytic activity. The molecular basis behind solvent induced catalytic activity will further aid in engineering laccase for its industrial application.

Calmodulin variants associated with congenital arrhythmia impair selectivity for ryanodine receptors.

Among its many molecular targets, the ubiquitous calcium sensor protein calmodulin (CaM) recognizes and regulates the activity of ryanodine receptors type 1 (RyR1) and 2 (RyR2), mainly expressed in skeletal and cardiac muscle, respectively. Such regulation is essential to achieve controlled contraction of muscle cells. To unravel the molecular mechanisms underlying the target recognition process, we conducted a comprehensive biophysical investigation of the interaction between two calmodulin variants associated with congenital arrhythmia, namely N97I and Q135P, and a highly conserved calmodulin-binding region in RyR1 and RyR2. The structural, thermodynamic, and kinetic properties of protein-peptide interactions were assessed together with an in-depth structural and topological investigation based on molecular dynamics simulations. This integrated approach allowed us to identify amino acids that are crucial in mediating allosteric processes, which enable high selectivity in molecular target recognition. Our results suggest that the ability of calmodulin to discriminate between RyR1 an RyR2 targets depends on kinetic discrimination and robust allosteric communication between Ca2+-binding sites (EF1-EF3 and EF3-EF4 pairs), which is perturbed in both N97I and Q135P arrhythmia-associated variants.

Structural communication between the GTPase Sec4p and its activator Sec2p: Determinants of GEF activity and early deformations to nucleotide release.

Ras GTPases are molecular switches that cycle between OFF and ON states depending on the bound nucleotide (i.e. GDP-bound and GTP-bound, respectively). The Rab GTPase, Sec4p, plays regulatory roles in multiple steps of intracellular vesicle trafficking. Nucleotide release is catalyzed by the Guanine Nucleotide Exchange Factor (GEF) Sec2p. Here, the integration of structural information with molecular dynamics (MD) simulations addressed a number of questions concerning the intrinsic and stimulated dynamics of Sec2p and Sec4p as well as the chain of structural deformations leading to GEF-assisted activation of the Rab GTPase. Sec2p holds an intrinsic ability to adopt the conformation found in the crystallographic complexes with Sec4p, thus suggesting that the latter selects and shifts the conformational equilibrium towards a pre-existing bound-like conformation of Sec2p. The anchoring of Sec4p to a suitable conformation of Sec2p favors the Sec2p-assisted pulling on itself of the α1/switch 1 (SWI) loop and of SWI, which loose any contact with GDP. Those deformations of Sec4p would occur earlier. Formation of the final Sec2p-Sec4p hydrophobic interface, accomplishes later. Disruption of the nucleotide cage would cause firstly loss of interactions with the guanine ring and secondly loss of interactions with the phosphates. The ease in sampling the energy landscape and adopting a bound-like conformation likely favors the catalyzing ability of GEFs for Ras GTPases.

Binding mode characterization of 13b in the monomeric and dimeric states of SARS-CoV-2 main protease using molecular dynamics simulations.

The main protease, Mpro/3CLpro, plays an essential role in processing polyproteins translated from viral RNA to produce functional viral proteins and therefore serve as an attractive target for discovering COVID-19 therapeutics. The availability of both monomer and dimer crystal bound with a common ligand, '13b' (α-ketoamide inhibitor), opened up opportunities to understand the Mpro mechanism of action. A comparative analysis of both forms of Mpro was carried out to elucidate the binding site architectural differences in the presence and absence of '13b'. Molecular dynamics simulations suggest that the presence of '13b' enhances the stability of Mpro than the unbound APO form. The N- and C- terminals of both the protomers stabilize each other, and making it's interface essential for the active form of Mpro. In comparison to monomer, the relatively high affinity of '13b' is gained in dimer pocket due to the high stability of the pocket by the interaction of S1 residue of chain B with residues F140, E166 and H172 of chain A, which is absent in monomer. The comprehensive essential dynamics, protein structure network analysis and thermodynamic profiling highlight the hot-spots, pivotal in molecular recognition process at protein-ligand and protein-protein interaction levels, cross-validated through computational alanine scanning study. A comparative description of '13b' binding mechanism in both forms illustrates valuable insights into the inhibition mechanism and the selection of critical residues suitable for the structure-based approaches for the identification of more potent Mpro inhibitors.Communicated by Ramaswamy H. Sarma.

Protein conformational switch discerned via network centrality properties.

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

Structure network-based landscape of rhodopsin misfolding by mutations and algorithmic prediction of small chaperone action.

Failure of a protein to achieve its functional structural state and normal cellular location contributes to the etiology and pathology of heritable human conformational diseases. The autosomal dominant form of retinitis pigmentosa (adRP) is an incurable blindness largely linked to mutations of the membrane protein rod opsin. While the mechanisms underlying the noxious effects of the mutated protein are not completely understood, a common feature is the functional protein conformational loss. Here, the wild type and 39 adRP rod opsin mutants were subjected to mechanical unfolding simulations coupled to the graph theory-based protein structure network analysis. A robust computational model was inferred and in vitro validated in its ability to predict endoplasmic reticulum retention of adRP mutants, a feature linked to the mutation-caused misfolding. The structure-based approach could also infer the structural determinants of small chaperone action on misfolded protein mutants with therapeutic implications. The approach is exportable to conformational diseases linked to missense mutations in any membrane protein.

The conformational and mutational landscape of the ubiquitin-like marker for autophagosome formation in cancer.

Macroautophagy/autophagy is a cellular process to recycle damaged cellular components, and its modulation can be exploited for disease treatments. A key autophagy player is the ubiquitin-like protein MAP1LC3B/LC3B. Mutations and changes in MAP1LC3B expression occur in cancer samples. However, the investigation of the effects of these mutations on MAP1LC3B protein structure is still missing. Despite many LC3B structures that have been solved, a comprehensive study, including dynamics, has not yet been undertaken. To address this knowledge gap, we assessed nine physical models for biomolecular simulations for their capabilities to describe the structural ensemble of MAP1LC3B. With the resulting MAP1LC3B structural ensembles, we characterized the impact of 26 missense mutations from pan-cancer studies with different approaches, and we experimentally validated our prediction for six variants using cellular assays. Our findings shed light on damaging or neutral mutations in MAP1LC3B, providing an atlas of its modifications in cancer. In particular, P32Q mutation was found detrimental for protein stability with a propensity to aggregation. In a broader context, our framework can be applied to assess the pathogenicity of protein mutations or to prioritize variants for experimental studies, allowing to comprehensively account for different aspects that mutational events alter in terms of protein structure and function.Abbreviations: ATG: autophagy-related; Cα: alpha carbon; CG: coarse-grained; CHARMM: Chemistry at Harvard macromolecular mechanics; CONAN: contact analysis; FUNDC1: FUN14 domain containing 1; FYCO1: FYVE and coiled-coil domain containing 1; GABARAP: GABA type A receptor-associated protein; GROMACS: Groningen machine for chemical simulations; HP: hydrophobic pocket; LIR: LC3 interacting region; MAP1LC3B/LC3B microtubule associated protein 1 light chain 3 B; MD: molecular dynamics; OPTN: optineurin; OSF: open software foundation; PE: phosphatidylethanolamine, PLEKHM1: pleckstrin homology domain-containing family M 1; PSN: protein structure network; PTM: post-translational modification; SA: structural alphabet; SLiM: short linear motif; SQSTM1/p62: sequestosome 1; WT: wild-type.

Investigating Conformational Dynamics and Allostery in the p53 DNA-Binding Domain Using Molecular Simulations.

The p53 tumor suppressor is a multifaceted context-dependent protein, which is involved in multiple cellular pathways, with the ability to either keep the cells alive or to kill them through mechanisms such as apoptosis. To complicate this picture, cancer cells that express mutant p53 becomes addicted to the mutant activity, so that the mutant variant features a myriad of gain-of-function activities, opening different venues for therapy. This makes essential to think outside the box and apply new approaches to the study of p53 structure-(mis)function relationship to find new critical components of its pathway or to understand how known parts are interconnected, compete, or cooperate. In this context, I will here illustrate how to integrate different computational methods to the identification of possible allosteric effects transmitted from the DNA binding interface of p53 to regions for cofactor recruitment. The protocol can be extended to any other cases of study. Indeed, it does not necessarily apply only to the study of DNA-induced effects, but more broadly to the investigation of long-range effects induced by a biological partner that binds to a biomolecule of interest.

The Bio3D packages for structural bioinformatics.

Bio3D is a family of R packages for the analysis of biomolecular sequence, structure, and dynamics. Major functionality includes biomolecular database searching and retrieval, sequence and structure conservation analysis, ensemble normal mode analysis, protein structure and correlation network analysis, principal component, and related multivariate analysis methods. Here, we review recent package developments, including a new underlying segregation into separate packages for distinct analysis, and introduce a new method for structure analysis named ensemble difference distance matrix analysis (eDDM). The eDDM approach calculates and compares atomic distance matrices across large sets of homologous atomic structures to help identify the residue wise determinants underlying specific functional processes. An eDDM workflow is detailed along with an example application to a large protein family. As a new member of the Bio3D family, the Bio3D-eddm package supports both experimental and theoretical simulation-generated structures, is integrated with other methods for dissecting sequence-structure-function relationships, and can be used in a highly automated and reproducible manner. Bio3D is distributed as an integrated set of platform independent open source R packages available from: http://thegrantlab.org/bio3d/.

Exploring the Activation Mechanism of a Metabotropic Glutamate Receptor Homodimer via Molecular Dynamics Simulation.

Metabotropic glutamate receptors of class C GPCRs exist as constitutive dimers, which play important roles in activating excitatory synapses of the central nervous system. However, the activation mechanism induced by agonists has not been clarified in experiments. To address the problem, we used microsecond all-atom molecular dynamics (MD) simulation couple with protein structure network (PSN) to explore the glutamate-induced activation for the mGluR1 homodimer. The results indicate that glutamate binding stabilizes not only the closure of Venus flytrap domains but also the polar interaction of LB2-LB2, in turn keeping the extracelluar domain in the active state. The activation of the extracelluar domain drives transmembrane domains (TMDs) of the two protomers closer and induces asymmetric activation for the TMD domains of the two protomers. One protomer with lower binding affinity to the agonist is activated, while the other protomer with higher binding energy is still in the inactive state. The PSN analysis identifies the allosteric regulation pathway from the ligand-binding pocket in the extracellular domain to the G-protein binding site in the intracellular TMD region and further reveals that the asymmetric activation is attributed to a combination of trans-pathway and cis-pathway regulations from two glumatates, rather than a single activation pathway. These observations could provide valuable molecular information for understanding of the structure and the implications in drug efficacy for the class C GPCR dimers.

Evolutionary-Conserved Allosteric Properties of Three Neuronal Calcium Sensor Proteins.

Neuronal Calcium Sensors (NCS) are highly conserved proteins specifically expressed in neurons. Calcium (Ca2+)-binding to their EF-hand motifs results in a conformational change, which is crucial for the recognition of a specific target and the downstream biological process. Here we present a comprehensive analysis of the allosteric communication between Ca2+-binding sites and the target interfaces of three NCS, namely NCS1, recoverin (Rec), and GCAP1. In particular, Rec was investigated in different Ca2+-loading states and in complex with a peptide from the Rhodopsin Kinase (GRK1) while NCS1 was studied in a Ca2+-loaded state in complex with either the same GRK1 target or a peptide from the D2 Dopamine receptor. A Protein Structure Network (PSN) accounting for persistent non-covalent interactions between amino acids was built for each protein state based on exhaustive Molecular Dynamics simulations. Structural network analysis helped unveiling the role of key amino acids in allosteric mechanisms and their evolutionary conservation among homologous proteins. Results for NCS1 highlighted allosteric inter-domain interactions between Ca2+-binding motifs and residues involved in target recognition. Robust long range, allosteric protein-target interactions were found also in Rec, in particular originating from the EF3 motif. Interestingly, Tyr 86, involved the hydrophobic packing of the N-terminal domain, was found to be a key residue for both intra- and inter-molecular communication with EF3, regardless of the presence of target or Ca2+ ions. Finally, based on a comprehensive topological PSN analysis for Rec, NCS1, and GCAP1 and multiple sequence alignments with homolog proteins, we propose that an evolution-driven correlation may exist between the amino acids mediating the highest number of persistent interactions (high-degree hubs) and their conservation. Such conservation is apparently fundamental for the specific structural dynamics required in signaling events.