Intra and Inter-Molecular Communications Through Protein Structure Network

GraSp-PSN: A web server for graph spectra based analysis of protein structure networks

The function of a protein is most of the time achieved due to minute conformational changes in its structure due to ligand binding or environmental changes or other interactions. Hence the analysis of structure of proteins should go beyond the analysis of mere atom contacts and should include the emergent global structure as a whole. This can be achieved by graph spectra based analysis of protein structure networks. GraSp-PSN is a web server that can assist in (1) acquiring weighted protein structure network (PSN) and network parameters ranging from atomic level to global connectivity from the three dimensional coordinates of a protein, (2) generating scores for comparison of a pair of protein structures with detailed information of local to global connectivity, and (3) assigning perturbation scores to the residues and their interactions, that can prioritise them in terms of residue clusters. The methods implemented in the server are generic in nature and can be used for comparing networks in any discipline by uploading adjacency matrices in the server. The webserver can be accessed using the following link: https://pople.mbu.iisc.ac.in/.

Unveiling the intricacies of allosteric regulation in aspartate kinase from the Wolbachia endosymbiont of Brugia Malayi: Mechanistic and therapeutic insights

Aspartate kinase (AK), an enzyme from the Wolbachia endosymbiont of Brugia malayi (WBm), plays a pivotal role in the bacterial cell wall and amino acid biosynthesis, rendering it an attractive candidate for therapeutic intervention. Allosteric inhibition of aspartate kinase is a prevalent mode of regulation across microorganisms and plants, often modulated by end products such as lysine, threonine, methionine, or meso-diaminopimelate. The intricate and diverse nature of microbial allosteric regulation underscores the need for rigorous investigation. This study employs a combined experimental and computational approach to decipher the allosteric regulation of WBmAK. Molecular Dynamics (MD) simulations elucidate that ATP (cofactor) and ASP (substrate) binding induce a closed conformation, promoting enzymatic activity. In contrast, the binding of lysine (allosteric inhibitor) leads to enzyme inactivation and an open conformation. The enzymatic assay demonstrates the optimal activity of WBmAK at 28 °C and a pH of 8.0. Notably, the allosteric inhibition study highlights lysine as a more potent inhibitor compared to threonine. Importantly, this investigation sheds light on the allosteric mechanism governing WBmAK and imparts novel insights into structure-based drug discovery, paving the way for the development of effective inhibitors against filarial pathogens.

Interfacial residues in protein-protein complexes are in the eyes of the beholder

Interactions between proteins are vital in almost all biological processes. The characterization of protein-protein interactions helps us understand the mechanistic basis of biological processes, thereby enabling the manipulation of proteins for biotechnological and clinical purposes. The interface residues of a protein-protein complex are assumed to have the following two properties: (a) they always interact with a residue of a partner protein, which forms the basis for distance-based interface residue identification methods, and (b) they are solvent-exposed in the isolated form of the protein and become buried in the complex form, which forms the basis for Accessible Surface Area (ASA)-based methods. The study interrogates this popular assumption by recognizing interface residues in protein-protein complexes through these two methods. The results show that a few residues are identified uniquely by each method, and the extent of conservation, propensities, and their contribution to the stability of protein-protein interaction varies substantially between these residues. The case study analyses showed that interface residues, unique to distance, participate in crucial interactions that hold the proteins together, whereas the interface residues unique to the ASA method have a potential role in the recognition, dynamics, and specificity of the complex and can also be a hotspot. Overall, the study recommends applying both distance and ASA methods so that some interface residues missed by either method but crucial to the stability, recognition, dynamics, and function of protein-protein complexes are identified in a complementary manner.

ARID3a from the ARID family: structure, role in autoimmune diseases and drug discovery

The AT-rich interaction domain (ARID) family of DNA-binding proteins is a group of transcription factors and chromatin regulators with a highly conserved ARID domain that recognizes specific AT-rich DNA sequences. Dysfunction of ARID family members has been implicated in various human diseases including cancers and intellectual disability. Among them, ARID3a has gained increasing attention due to its potential involvement in autoimmunity. In this article we provide an overview of the ARID family, focusing on the structure and biological functions of ARID3a. It explores the role of ARID3a in autoreactive B cells and its contribution to autoimmune diseases such as systemic lupus erythematosus and primary biliary cholangitis. Furthermore, we also discuss the potential for drug discovery targeting ARID3a and present a plan for future research in this field.

Elucidating the Ionic Liquid-Induced Mixed Inhibition of GH1 β-Glucosidase H0HC94

Deciphering the ionic liquid (IL) tolerance of glycoside hydrolases (GHs) to improve their hydrolysis efficiency for fermentable sugar synthesis in the "one-pot" process has long been a hurdle for researchers. In this work, we employed experimental and theoretical approaches to investigate the 1-ethyl-3-methylimidazolium acetate ([C2C1im][MeCO2])-induced inhibition of GH1 β-glucosidase (H0HC94) from Agrobacterium tumefaciens 5A. At 10-15% [C2C1im][MeCO2] concentration, H0HC94 experiences competitive inhibition (R2 = 0.97, alpha = 2.8). As the IL content increased to 20-25%, the inhibition pattern shifted to mixed-type inhibition (R2 = 0.98, alpha = 3.4). These findings were further confirmed through characteristic inhibition plots using Lineweaver-Burk plots. Atomistic molecular dynamics simulations conducted with 0% [C2C1im][MeCO2], 10% [C2C1im][MeCO2], and 25% [C2C1im][MeCO2] revealed the accumulation of [C2C1im]+ at the negatively charged active site of H0HC94 in 10% [C2C1im][MeCO2], supporting the occurrence of competitive inhibition at lower IL concentrations. At higher IL concentrations, the cations and anions bound to the secondary binding sites (SBSs) of H0HC94, leading to a tertiary conformational change, as captured by the principal component analysis based on the free-energy landscape and protein structure networks. The altered conformation of H0HC94 affected the interaction with [C2C1im][MeCO2], which could possibly shift the inhibition from competitive to more mixed-type (competitive + noncompetitive) inhibition, as observed in the experiments. For the first time, we report a combined experimental and theoretical insight behind the mixed inhibition of a GH1 β-glucosidase. Our findings indicated the role of SBS in IL-induced inhibition, which could aid in developing more IL-tolerant β-glucosidases for biorefinery applications.

Insights into molecular docking and dynamics to reveal therapeutic potential of natural compounds against P53 protein

P53 is eminent tumour suppressor protein that plays a prominent role in cell cycle arrest, DNA repair, senescence, differentiation and initiation of apoptosis. P53 is an attractive drug target and the high toxicity of some cancer chemotherapy drugs increase the demand for new anti-cancer drugs from natural products. In this current scenario, identification of promising anticancer compounds from natural sources by repurposing approach is still relevant for the early prevention and effective management of cancer. In present study, we docked natural compounds like podophyllotoxin, quercetin and rutin along standard drugs (MG-132 and Bay 61-3606) against p53 protein. ADME/T analysis predicted toxicity of phytochemicals and drugs. In silico docking analysis of podophyllotoxin, quercetin and rutin gave HDOCK docking scores of -187.87, -148. 97 and -143.85, whereas control drugs MG-132 and Bay 61-3606 showed docking scores of -159.59 and -140.71 against p53 respectively. AutoDock analysis of rutin and MG-132 showed highest binding affinity scores of -7.3 and -6.8 kcal/mol against p53. Molecular dynamic simulation for p53 protein displayed stable conformation and convergence. In this study, P53-rutin complex showed free binding energy score of 11.84 kcal/mol and P53-MG-132 complex reported free energy score of 16.3 kcal/mol. Protein contacts atlas gives non-covalent contacts framework by exploring interfaces of individual subunits and protein-ligand interactions. STRING tool predicts physical and functional interactions between proteins. The results of this study revealed that rutin and MG-132 could be promising inhibitors against targeted p53 protein and this could prove detrimental for molecular therapeutics and drug-designing strategies.Communicated by Ramaswamy H. Sarma.

In silico analysis and molecular docking studies of natural compounds of Withania somnifera against bovine NLRP9

CONTEXT

NLRP9 is a member of nucleotide-binding domain leucine-rich repeat-containing receptors and is found to be associated with many inflammatory diseases. In the current scenario, the identification of promising anti-inflammatory compounds from natural sources by repurposing approach is still relevant for the early prevention and effective management of the disease.

METHODS

In the present study, we docked bioactives of Ashwagandha (Withanoside IV, Withanoside V, Withanolide A, Withanolide B, and Sitoindoside IX) and two control drugs against bovine NLRP9 protein. ADME/T analysis was used to determine the physiochemical properties of compounds and standard drugs. Molecular modeling was used to evaluate the correctness and quality of protein structures. In silico docking analysis revealed Withanolide B had the highest binding affinity score of -10.5 kcal/mol, whereas, among control drugs, doxycycline hydrochloride was most effective (-10.3 kcal/mol). The results of this study revealed that bioactives of Withania somnifera could be promising inhibitors against bovine NLRP9. In the present study, molecular simulation was used to measure protein conformational changes over time. The Rg value was found to be 34.77A°. RMSD and B-factor were also estimated to provide insights into the flexibility and mobile regions of protein structure. A functional protein network interaction was constructed from information collected from non-curative sources as protein-protein interactions (PPI) that play an important role in determining the function of the target protein and the ability of the drug molecule. Thus, in the present situation, it is important to identify bioactives with the potential to combat inflammatory diseases and provide strength and immunity to the host. However, there is still a need to study in vitro and in vivo to further support these findings.

Intermediate-aided allostery mechanism for α-glucosidase by Xanthene-11v as an inhibitor using residue interaction network analysis

Exploring allosteric inhibition and the discovery of new inhibitor binding sites are important studies in protein regulation mechanisms and drug discovery. Structural and network-based analyses of trajectories resulting from molecular dynamics (MD) simulations have been developed to discover protein dynamics, landscape, functions, and allosteric regions. Here, an experimentally suggested non-competitive inhibitor, xanthene-11v, was considered to explore its allosteric inhibition mechanism in α-glucosidase MAL12. Comparative structural and network analyses were applied to eight 250 ns independent MD simulations, four of which were performed in the free state and four of which were performed in ligand-bound forms. Projected two-dimensional free energy landscapes (FEL) were constructed from the probabilistic distribution of conformations along the first two principal components. The post-simulation analyses of the coordinates, side-chain torsion angles, non-covalent interaction networks, network communities, and their centralities were performed on α-glucosidase conformations and the intermediate sub-states. Important communities of residues have been found that connect the allosteric site to the active site. Some of these residues like Thr307, Arg312, TYR344, ILE345, Phe357, Asp406, Val407, Asp408, and Leu436 are the key messengers in the transition pathway between allosteric and active sites. Evaluating the probability distribution of distances between gate residues including Val407 in one community and Phe158, and Pro65 in another community depicted the closure of this gate due to the inhibitor binding. Six macro states of protein were deduced from the topology of FEL and analysis of conformational preference of free and ligand-bound systems to these macro states shows a combination of lock-and-key, conformational selection, and induced fit mechanisms are effective in ligand binding. All these results reveal structural states, allosteric mechanisms, and key players in the inhibition pathway of α-glucosidase by xanthene-11v.

Comparative Protein Structural Network Analysis Reveals C-Terminal Tail Phosphorylation Structural Communication Fingerprint in PTEN-Associated Mutations in Autism and Cancer

PTEN (phosphatase and tensin homolog deleted on chromosome 10) is a tightly regulated dual-specificity phosphatase and key regulator of the PI3K/AKT/mTOR signaling pathway. PTEN phosphorylation at its carboxy-terminal tail (CTT) serine/threonine cluster negatively regulates its tumor suppressor function by inducing a stable, closed, and inactive conformation. Germline PTEN mutations predispose individuals to PTEN hamartoma tumor syndrome (PHTS), a rare inherited cancer syndrome and, intriguingly, one of the most common causes of autism spectrum disorder (ASD). However, the mechanistic details that govern phosphorylated CTT catalytic conformational dynamics in the context of PHTS-associated mutations are unknown. Here, we utilized a comparative protein structure network (PSN)-based approach to investigate PTEN CTT phosphorylation-induced conformational dynamics specific to PTEN-ASD compared to PTEN-cancer phenotypes. Results from our study show differences in structural flexibility, inter-residue contacts, and allosteric communication patterns mediated by CTT phosphorylation, differentiating PTEN-ASD and PTEN-cancer phenotypes. Further, we identified perturbations among global metapaths and community network connections within the active site and inter-domain regions, indicating the significance of these regions in transmitting information across the PSN. Together, our studies provide a mechanistic underpinning of allosteric regulation through the coupled interplay of CTT phosphorylation conformational dynamics in PTEN-ASD and PTEN-cancer mutations. Importantly, the detailed atomistic interactions and structural consequences of PTEN variants reveal potential allosteric druggable target sites as a viable and currently unexplored treatment approach for individuals with different PHTS-associated mutations.

psnGPCRdb: The Structure-network Database of G Protein Coupled Receptors

G protein coupled receptors (GPCRs) are critical eukaryotic signal transduction gatekeepers and represent the largest protein superfamily in the human proteome, with more than 800 members. They share seven transmembrane helices organized in an up-down bundle architecture. GPCR-mediated signaling pathways have been linked to numerous human diseases, and GPCRs are the targets of approximately 35% of all drugs currently on the market. Structure network analysis, a graph theory-based approach, represents a cutting-edge tool to deeply understand GPCR function, which strongly relies on communication between the extracellular and intracellular poles of their structure. psnGPCRdb stores the structure networks (i.e., linked nodes, hubs, communities and communication pathways) computed on all updated GPCR structures in the Protein Data Bank, in their isolated states or in complex with extracellular and/or intracellular molecules. The structure communication signatures of a sub-family or family of GPCRs as well as of their small-molecule activators or inhibitors are stored as consensus networks. The database stores also all meaningful structure network-based comparisons (i.e., difference networks) of functionally different states (i.e., inactive or active) of a given receptor sub-type, or of consensus networks representative of a receptor sub-type, type, sub-family or family. Single or consensus GPCR networks hold also information on amino acid conservation. The database allows to graphically analyze 3D structure networks together with interactive data-tables. Ligand-centric networks can be analyzed as well. psnGPCRdb is unique and represents a powerful resource to unravel GPCR function with important implications in cell signaling and drug design. psnGPCRdb is freely available at: http://webpsn.hpc.unimo.it/psngpcr.php.

Computational models, databases and tools for antibiotic combinations

Antibiotic combination is a promising strategy to extend the lifetime of antibiotics and thereby combat antimicrobial resistance. However, screening for new antibiotic combinations is both time-consuming and labor-intensive. In recent years, an increasing number of researchers have used computational models to predict effective antibiotic combinations. In this review, we summarized existing computational models for antibiotic combinations and discussed the limitations and challenges of these models in detail. In addition, we also collected and summarized available data resources and tools for antibiotic combinations. This study aims to help computational biologists design more accurate and interpretable computational models.

A Comparative Molecular Dynamics Study of Selected Point Mutations in the Shwachman–Bodian–Diamond Syndrome Protein SBDS

The Shwachman–Diamond Syndrome (SDS) is an autosomal recessive disease whose majority of patients display mutations in a ribosome assembly protein named Shwachman–Bodian–Diamond Syndrome protein (SBDS). A specific therapy for treating this rare disease is missing, due to the lack of knowledge of the molecular mechanisms responsible for its pathogenesis. Starting from the observation that SBDS single-point mutations, localized in different domains of the proteins, are responsible for an SDS phenotype, we carried out the first comparative Molecular Dynamics simulations on three SBDS mutants, namely R19Q, R126T and I212T. The obtained 450-ns long trajectories were compared with those returned by both the open and closed forms of wild type SBDS and strongly indicated that two distinct conformations (open and closed) are both necessary for the proper SBDS function, in full agreement with recent experimental observations. Our study supports the hypothesis that the SBDS function is governed by an allosteric mechanism involving domains I and III and provides new insights into SDS pathogenesis, thus offering a possible starting point for a specific therapeutic option.

Shape shifting: The multiple conformational substates of the PTEN N-terminal PIP2 -binding domain

The Phosphatase and TENsin homolog deleted on chromosome 10 (PTEN) is a chief regulator of a variety of cellular processes including cell proliferation, migration, growth, and death. It is also a major tumor suppressor gene that is frequently mutated or lost under cancerous conditions. PTEN encodes a dual-specificity (lipid and protein) phosphatase that negatively regulates the PI3K/AKT/mTOR signaling pathway where the PIP2 -binding domain (PBD) regulates the lipid phosphatase function. Unfortunately, despite two decades of research, a full-length structure of PTEN remains elusive, leaving open questions regarding PTEN's disordered regions that mediate protein stability, post-translational modifications, protein-protein interactions, while also hindering the design of small molecules that can regulate PTEN's function. Here, we utilized a combination of crosslinking mass spectrometry, in silico predicted structural modeling (including AlphaFold2), molecular docking, molecular dynamics simulations, and residue interaction network modeling to obtain structural details and molecular insight into the behavior of the PBD of PTEN. Our study shows that the PBD exists in multiple conformations which suggests its ability to regulate PTEN's variety of functions. Studying how these specific conformational substates contribute to PTEN function is imperative to defining its function in disease pathogenesis, and to delineate ways to modulate its tumor suppressor activity.

Prediction of Synergistic Antibiotic Combinations by Graph Learning

Antibiotic resistance is a major public health concern. Antibiotic combinations, offering better efficacy at lower doses, are a useful way to handle this problem. However, it is difficult for us to find effective antibiotic combinations in the vast chemical space. Herein, we propose a graph learning framework to predict synergistic antibiotic combinations. In this model, a network proximity method combined with network propagation was used to quantify the relationships of drug pairs, and we found that synergistic antibiotic combinations tend to have smaller network proximity. Therefore, network proximity can be used for building an affinity matrix. Subsequently, the affinity matrix was fed into a graph regularization model to predict potential synergistic antibiotic combinations. Compared with existing methods, our model shows a better performance in the prediction of synergistic antibiotic combinations and interpretability.

A Case Study of the Glycoside Hydrolase Enzyme Mechanism Using an Automated QM-Cluster Model Building Toolkit

Glycoside hydrolase enzymes are important for hydrolyzing the β-1,4 glycosidic bond in polysaccharides for deconstruction of carbohydrates. The two-step retaining reaction mechanism of Glycoside Hydrolase Family 7 (GH7) was explored with different sized QM-cluster models built by the Residue Interaction Network ResidUe Selector (RINRUS) software using both the wild-type protein and its E217Q mutant. The first step is the glycosylation, in which the acidic residue 217 donates a proton to the glycosidic oxygen leading to bond cleavage. In the subsequent deglycosylation step, one water molecule migrates into the active site and attacks the anomeric carbon. Residue interaction-based QM-cluster models lead to reliable structural and energetic results for proposed glycoside hydrolase mechanisms. The free energies of activation for glycosylation in the largest QM-cluster models were predicted to be 19.5 and 31.4 kcal mol⁻¹ for the wild-type protein and its E217Q mutant, which agree with experimental trends that mutation of the acidic residue Glu217 to Gln will slow down the reaction; and are higher in free energy than the deglycosylation transition states (13.8 and 25.5 kcal mol⁻¹ for the wild-type protein and its mutant, respectively). For the mutated protein, glycosylation led to a low-energy product. This thermodynamic sink may correspond to the intermediate state which was isolated in the X-ray crystal structure. Hence, the glycosylation is validated to be the rate-limiting step in both the wild-type and mutated enzyme.

Exploring species-specific inhibitors with multiple target sites on S. aureus pyruvate kinase using a computational workflow

Experimental evidence indicated that bacterial pyruvate kinase of glycolysis can be evaluated as an alternative target to eliminate infections, while antibiotic resistance poses a global threat. Here, we use a computational workflow to reveal and investigate the potential allosteric sites of methicillin-resistant S. aureus PK, which can help in designing species-specific drugs to inhibit activity of this organism. Residue interaction networks point to a known allosteric site at the small C-C interface, a potential allosteric site near the small interface (site #1), and a second potential allosteric site at the large interface (site #2). 2 µs-long molecular dynamics (MD) simulations with AMBER16 generate different conformations of one narrow target site. Known and potential allosteric sites on the selected conformers are investigated using ensemble docking with AutoDock Vina and a library of 2447 FDA-approved drugs. We determine 18 hits, comprising ergot-alkaloids, anti-cancer-agents, antivirals, analgesics, cardiac glycosides, all with a high docking z-score for three sites. 5 selected compounds with high, average and low z-scores are subjected to 50 ns-long MD simulations for MM-GBSA calculations. ΔG_bind values up to -49.3 kcal/mol at the C-C interface, up to -32.7 kcal/mol at site #1, and up to -53.3 kcal/mol at site #2 support the docking calculations. We investigate mitapivat and TT-232 as reference compounds under clinical trial, targeting human PK isomers. We suggest 18 FDA-approved hits from the docking calculations and TT-232 as potential inhibitors with multiple target sites on S. aureus PK. This study also proposes pharmacophores models for de novo drug design.Communicated by Ramaswamy H. Sarma.

Molecular insights into the allosteric coupling mechanism between an agonist and two different transducers for μ-opioid receptors

G protein-coupled receptors (GPCRs) as the most important class of pharmacological targets regulate G-protein and β-arrestin-mediated signaling through allosteric interplay, which are responsible for different biochemical and physiological actions like therapeutic efficacy and side effects. However, the allosteric mechanism underlying preferentially recruiting one transducer versus the other has been poorly understood, limiting drug design. Motivated by this issue, we utilize accelerated molecular dynamics simulation coupled with potential of mean force (PMF), molecular mechanics Poisson Boltzmann surface area (MM/PBSA) and protein structure network (PSN) to study two ternary complex systems of a representative class A GPCR (μ-opioid receptor (μOR)) bound by an agonist and one specific transducer (G-protein and β-arrestin). The results show that no significant difference exists in the whole structure of μOR between two transducer couplings, but displays transducer-dependent changes in the intracellular binding region of μOR, where the β-arrestin coupling results in a narrower crevice with TM7 inward movement compared with the G-protein. In addition, both the G-protein and β-arrestin coupling can increase the binding affinity of the agonist to the receptor. However, the interactions between the agonist and μOR also exhibit transducer-specific changes, in particular for the interaction with ECL2 that plays an important role in recruiting β-arrestin. The allosteric network analysis further indicates that Y148^3.33, F152^3.37, F156^3.41, N191^4.49, T160^3.45, Y106^2.42, W293^6.48, F289^6.44, I248^5.54 and Y252^5.58 play important roles in equally activating G-protein and β-arrestin. In contrast, M161^3.46 and R165^3.50 devote important contributions to preferentially recruit G-protein while D164^3.49 and R179^ICL2 are revealed to be important for selectively activating β-arrestin. The observations provide useful information for understanding the biased activation mechanism.

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.

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.

PSNtools for standalone and web-based structure network analyses of conformational ensembles

Structure graphs, in which interacting amino acids/nucleotides correspond to linked nodes, represent cutting-edge tools to investigate macromolecular function.

The graph-based approach defined as Protein Structure Network (PSN) was initially implemented in the Wordom software and subsequently in the webPSN server. PSNs are computed either on a molecular dynamics (MD) trajectory (PSN-MD) or on a single structure. In the latter case, information on atomic fluctuations is inferred from the Elastic Network Model-Normal Mode Analysis (ENM-NMA) (PSN-ENM). While Wordom performs both PSN-ENM and PSN-MD analyses but without output post-processing, the webPSN server performs only single-structure PSN-EMN but assisting the user in input setup and output analysis.

Here we release for the first time the standalone software PSNtools, which allows calculation and post-processing of PSN analyses carried out either on single structures or on conformational ensembles. Relevant unique and novel features of PSNtools are either comparisons of two networks or computations of consensus networks on sets of homologous/analogous macromolecular structures or conformational ensembles. Network comparisons and consensus serve to infer differences in functionally different states of the same system or network-based signatures in groups of bio-macromolecules sharing either the same functionality or the same fold.

In addition to the new software, here we release also an updated version of the webPSN server, which allows performing an interactive graphical analysis of PSN-MD, following the upload of the PSNtools output.

PSNtools, the auxiliary binary version of Wordom software, and the WebPSN server are freely available at http://webpsn.hpc.unimo.it/wpsn3.php.

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.

Probing Allosteric Regulation Mechanism of W7.35 on Agonist-Induced Activity for μOR by Mutation Simulation

The residue located at 15 positions before the most conserved residue in TM7 (7.35 of Ballesteros-Weinstein number) plays important roles in ligand binding and the receptor activity for class A GPCRs. Nevertheless, its regulation mechanism has not been clearly clarified in experiments, and some controversies also exist for its impact on μ-opioid receptors (μOR) bound by agonists. Thus, we chose the μ-opioid receptor (μOR) of class A GPCRs as a representative and utilized a microsecond accelerated molecular dynamics simulation (aMD) coupled with a protein structure network (PSN) to explore the effect of W318^7.35 on its functional activity induced by the agonist endomorphin2 mainly by a comparison of the wild system and its W7.35A mutant. When endomorphin2 binds to the wild-type μOR, TM6 in μOR moves outward to form an open intracellular conformation that is beneficial to accommodating the β-arrestin transducer, rather than the G-protein transducer due to the clash with the α5 helix of G-protein, thus acting as a β-arrestin biased agonist. However, the W318A mutation induces the intracellular part of μOR to form a closed state, which disfavors coupling with either G-protein or β-arrestin. The allosteric pathway analysis further reveals that the binding of endomorphin2 to the wild-type μOR transmits more activation signals to the β-arrestin binding site while the W318A mutation induces more structural signals to transmit to common binding residues of the G protein and β-arrestin. More interestingly, the residue at the 7.35 position regulates the shortest allosteric pathway in indirect ways by influencing the interactions between other ligand-binding residues and endomorphin2. W293^6.48 and F289^6.44 are important for regulating the different activities of μOR induced either by the agonist or by the mutation. Y336^7.53, F343^8.50, and D340^8.47 play crucial roles in activating the β-arrestin biased signal induced by the agonist endomorphin2, while L158^3.43 and V286^6.41 devote important contributions to the change in the activity of endomorphin2 from the β-arrestin biased agonist to the antagonist upon the W318A mutation.

Molecular Communications in Viral Infections Research: Modeling, Experimental Data, and Future Directions

Hundreds of millions of people worldwide are affected by viral infections each year, and yet, several of them neither have vaccines nor effective treatment during and post-infection. This challenge has been highlighted by the COVID-19 pandemic, showing how viruses can quickly spread and impact society as a whole. Novel interdisciplinary techniques must emerge to provide forward-looking strategies to combat viral infections, as well as possible future pandemics. In the past decade, an interdisciplinary area involving bioengineering, nanotechnology and information and communication technology (ICT) has been developed, known as Molecular Communications. This new emerging area uses elements of classical communication systems to molecular signalling and communication found inside and outside biological systems, characterizing the signalling processes between cells and viruses. In this paper, we provide an extensive and detailed discussion on how molecular communications can be integrated into the viral infectious diseases research, and how possible treatment and vaccines can be developed considering molecules as information carriers. We provide a literature review on molecular communications models for viral infection (intra-body and extra-body), a deep analysis on their effects on immune response, how experimental can be used by the molecular communications community, as well as open issues and future directions.

Role of Conformational Change and Glucose Binding Sites in the Enhanced Glucose Tolerance of Agrobacterium tumefaciens 5A GH1 β-Glucosidase Mutants

β-Glucosidases are often inhibited by their reaction product glucose and a barrier to the efficient lignocellulosic biomass hydrolysis to glucose. We had previously reported the mutants, C174V, and H229S, with a nearly 2-fold increased glucose tolerance over the wild type (WT), H0HC94, encoded in Agrobacterium tumefaciens 5A (apparent K_i,_Glc = 686 mM). We report our steady-state and time-resolved intrinsic fluorescence spectroscopy, circular dichroism, and isothermal titration calorimetry (ITC) studies to further understand increased glucose tolerance. Changes in the mutants' emission intensity and the differential change in quenching rate in the absence and presence of glucose reflect changes in protein conformation by glucose. Time-resolved lifetime and anisotropy measurements further indicated the microenvironment differences across solvent-exposed tryptophan residues and a higher hydrodynamic radius due to glucose binding, respectively. ITC measurements confirmed the increase of glucose binding sites in the mutants. The experiment results were supported by molecular dynamics simulations, which revealed significant variations in the glucose-protein hydrogen-bonding profiles. Protein structure network analysis of the simulated structures further indicates the mutants' conformation change than the WT. Computational studies also indicated additional glucose binding sites in mutants. Our results indicate the role of glucose binding in modulating the enzyme response to glucose.

Comparative Molecular Dynamics Investigation of the Electromotile Hearing Protein Prestin

The mammalian protein prestin is expressed in the lateral membrane wall of the cochlear hair outer cells and is responsible for the electromotile response of the basolateral membrane, following hyperpolarisation or depolarisation of the cells. Its impairment marks the onset of severe diseases, like non-syndromic deafness. Several studies have pointed out possible key roles of residues located in the Transmembrane Domain (TMD) that differentiate mammalian prestins as incomplete transporters from the other proteins belonging to the same solute-carrier (SLC) superfamily, which are classified as complete transporters. Here, we exploit the homology of a prototypical incomplete transporter (rat prestin, rPres) and a complete transporter (zebrafish prestin, zPres) with target structures in the outward open and inward open conformations. The resulting models are then embedded in a model membrane and investigated via a rigorous molecular dynamics simulation protocol. The resulting trajectories are analyzed to obtain quantitative descriptors of the equilibration phase and to assess a structural comparison between proteins in different states, and between different proteins in the same state. Our study clearly identifies a network of key residues at the interface between the gate and the core domains of prestin that might be responsible for the conformational change observed in complete transporters and hindered in incomplete transporters. In addition, we study the pathway of Cl− ions in the presence of an applied electric field towards their putative binding site in the gate domain. Based on our simulations, we propose a tilt and shift mechanism of the helices surrounding the ion binding cavity as the working principle of the reported conformational changes in complete transporters.

Centrality Measures in Residue Interaction Networks to Highlight Amino Acids in Protein–Protein Binding

Residue interaction networks (RINs) describe a protein structure as a network of interacting residues. Central nodes in these networks, identified by centrality analyses, highlight those residues that play a role in the structure and function of the protein. However, little is known about the capability of such analyses to identify residues involved in the formation of macromolecular complexes. Here, we performed six different centrality measures on the RINs generated from the complexes of the SKEMPI 2 database of changes in protein–protein binding upon mutation in order to evaluate the capability of each of these measures to identify major binding residues. The analyses were performed with and without the crystallographic water molecules, in addition to the protein residues. We also investigated the use of a weight factor based on the inter-residue distances to improve the detection of these residues. We show that for the identification of major binding residues, closeness, degree, and PageRank result in good precision, whereas betweenness, eigenvector, and residue centrality analyses give a higher sensitivity. Including water in the analysis improves the sensitivity of all measures without losing precision. Applying weights only slightly raises the sensitivity of eigenvector centrality analysis. We finally show that a combination of multiple centrality analyses is the optimal approach to identify residues that play a role in protein–protein interaction.

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.

QM-Cluster Model Study of the Guaiacol Hydrogen Atom Transfer and Oxygen Rebound with Cytochrome P450 Enzyme GcoA

The key step of the O-demethylation of guaiacol by GcoA of the cytochrome P450-reductase pair was studied with DFT using two 10-residue and three 15-residue QM-cluster models. For each model, two reaction pathways were examined, beginning with a different guaiacol orientation. Based on this study, His354, Phe349, Glu249, and Pro250 residues were found to be important for keeping the heme in a planar geometry throughout the reaction. Val241 and Gly245 residues were needed in the QM-cluster models to provide the hydrophobic pocket for an appropriate guaiacol pose in the reaction. The aromatic triad Phe75, Phe169, and Phe395 may be necessary to facilitate guaiacol migrating into the enzyme active site, but it does not qualitatively affect kinetics and thermodynamics of the proposed mechanism. All QM-cluster models created by RINRUS agree very well with previous experimental work. This study provides details for better understanding enzymatic O-demethylation of lignins to form catechol derivatives by GcoA.

Insight into Shared Properties and Differential Dynamics and Specificity of Secretory Phospholipase A2 Family Members

Understanding generic mechanisms of functions shared by the secretory phospholipase A₂ (sPLA₂) family involved in the lipid metabolism and cell signaling and the molecular basis of function specificity for family members is an intriguing but challenging problem for biologists. Here, we explore the issue through extensive analyses using a combination of structure-based methods and bioinformatics tools on130 sPLA₂ family members. The principal component analysis of the structure ensemble reveals that the enzyme has an open-close motion which helps widen the substrate binding channel, facilitating its binding to phospholipid. Performing elastic network model and sequence analyses found that the residues critical for family functions, such as cysteine and catalytic residues, are highly conserved and undergo minimal movements, which is evolutionarily essential as their perturbation would impact the function, while the four residue regions involved in the association with the calcium ion/membrane are lowly conserved and of high mobility and large variations in low-to-intermediate frequency modes, which reflects the specificity of members. The analyses from perturbation response scanning also reveal that the above four regions with high sensitivity to an external perturbation are member-specific, suggesting their different roles in allosteric modulation, while the minimal sensitive residues are the shared characteristics across family members, which play an important role in maintaining structural stability as the folding core. This study is helpful for understanding how sequences, structures, and dynamics of sPLA₂ family members evolve to ensure their common and specific functions and can provide a guide for accurate design of proteins with finely tuned activities.

Structural aspects of rod opsin and their implication in genetic diseases

Vision in dim-light conditions is triggered by photoactivation of rhodopsin, the visual pigment of rod photoreceptor cells. Rhodopsin is made of a protein, the G protein coupled receptor (GPCR) opsin, and the chromophore 11-cis-retinal. Vertebrate rod opsin is the GPCR best characterized at the atomic level of detail. Since the release of the first crystal structure 20 years ago, a huge number of structures have been released that, in combination with valuable spectroscopic determinations, unveiled most aspects of the photobleaching process. A number of spontaneous mutations of rod opsin have been found linked to vision-impairing diseases like autosomal dominant or autosomal recessive retinitis pigmentosa (adRP or arRP, respectively) and autosomal congenital stationary night blindness (adCSNB). While adCSNB is mainly caused by constitutive activation of rod opsin, RP shows more variegate determinants affecting different aspects of rod opsin function. The vast majority of missense rod opsin mutations affects folding and trafficking and is linked to adRP, an incurable disease that awaits light on its molecular structure determinants. This review article summarizes all major structural information available on vertebrate rod opsin conformational states and the insights gained so far into the structural determinants of adCSNB and adRP linked to rod opsin mutations. Strategies to design small chaperones with therapeutic potential for selected adRP rod opsin mutants will be discussed as well.

DNA-Guided Programmable Protein Assemblies for Biomedical Applications

While the protein assemblies have been found widely existing and playing significant roles in biological systems, their imitation and re-construction is further boosting more applications in biomedical research, such as enzymatic reaction regulation, sensing, and biomedicine. DNA nanotechnology provides a programmable strategy for the fabrication of nanostructures with unprecedented accuracy on the nanoscale. By linking the DNA nanotechnology with proteins of different functions, the precise construction of DNA-guided protein assemblies can be achieved for various biomedical applications. This minireview summarizes the recent advances in the programmable protein assemblies on DNA nanoplatforms and discusses the outlook of DNA-guided protein assemblies in the biomedical research.

Interplay among Structural Stability, Plasticity, and Energetics Determined by Conformational Attuning of Flexible Loops in PD-1

The dynamics and plasticity of the PD-1/PD-L1 axis are the bottlenecks for the discovery of small-molecule antagonists to perturb this interaction interface significantly. Understanding the process of this protein-protein interaction (PPI) is of fundamental biological interest in structure-based drug designing. Food and Drug Administration (FDA)-approved anti-PD-1 monoclonal antibodies (mAbs) are the first-in-class with distinct binding modes to access this axis clinically; however, their mechanistic aspects remain elusive. Here, we have unveiled the interactive interfaces with PD-L1 and mAbs to investigate the native plasticity of PD-1 at global (structural and dynamical) and local (residue side-chain orientations) levels. We found that the structural stability and coordinated C_α movements are increased in the presence of PD-1's binding partners. The rigorous analysis of these PPIs using computational biophysical approaches revealed PD-1's intrinsic plasticity, its concerted loops' movement (BC, FG, and CC'), distal side-chain motions, and the thermodynamic landscape, which are perturbed remarkably from its unbound to bound states. Based on intra-/inter-residues' contact networks and energetics, the hot-spots have been identified that were found to be essential to arrest the dynamical motions of PD-1 significantly for the rational design of therapeutic agents by mimicking the mAbs mechanism.

Distinguishing Enzymes and Non-enzymes Based on Structural Information with an Alignment Free Approach

Background:

Knowledge of protein functions is very crucial for the understanding of biological processes. Experimental methods for protein function prediction are powerless to treat the growing amount of protein sequence and structure data.

Objective:

To develop some computational techniques for the protein function prediction.

Method:

Based on the residue interaction network features and the motion mode information, an SVM model was constructed and used as the predictor. The role of these features was analyzed and some interesting results were obtained.

Results:

An alignment-free method for the classification of enzyme and non-enzyme is developed in this work. There is not any single feature that occupies a dominant position in the prediction process. The topological and the information-theoretic residue interaction network features have a better performance. The combination of the fast mode and the slow mode can get a better explanation for the classification result.

Conclusion:

The method proposed in this paper can act as a classifier for the enzymes and nonenzymes.

Network Re-Wiring During Allostery and Protein-Protein Interactions: A Graph Spectral Approach

The process of allostery is often guided by subtle changes in the non-covalent interactions between residues of a protein. These changes may be brought about by minor perturbations by natural processes like binding of a ligand or protein-protein interaction. The challenge lies in capturing minute changes at the residue interaction level and following their propagation at local as well as global distances. While macromolecular effects of the phenomenon of allostery are inferred from experiments, a computational microscope can elucidate atomistic-level details leading to such macromolecular effects. Network formalism has served as an attractive means to follow this path and has been pursued further for the past couple of decades. In this chapter some concepts and methods are summarized, and recent advances are discussed. Specifically, the changes in strength of interactions (edge weight) and their repercussion on the overall protein organization (residue clustering) are highlighted. In this review, we adopt a graph spectral method to probe these subtle changes in a quantitative manner. Further, the power of this method is demonstrated for capturing re-ordering of side-chain interactions in response to ligand binding, which culminates into formation of a protein-protein complex in β₂-adrenergic receptors.

An allosteric hot spot in the tandem-SH2 domain of ZAP-70 regulates T-cell signaling

T-cell receptor (TCR) signaling is initiated by recruiting ZAP-70 to the cytosolic part of TCR. ZAP-70, a non-receptor tyrosine kinase, is composed of an N-terminal tandem SH2 (tSH2) domain connected to the C-terminal kinase domain. The ZAP-70 is recruited to the membrane through binding of tSH2 domain and the doubly phosphorylated ITAM motifs of CD3 chains in the TCR complex. Our results show that the tSH2 domain undergoes a biphasic structural transition while binding to the doubly phosphorylated ITAM-ζ1 peptide. The C-terminal SH2 domain binds first to the phosphotyrosine residue of ITAM peptide to form an encounter complex leading to subsequent binding of second phosphotyrosine residue to the N-SH2 domain. We decipher a network of noncovalent interactions that allosterically couple the two SH2 domains during binding to doubly phosphorylated ITAMs. Mutation in the allosteric network residues, for example, W165C, uncouples the formation of encounter complex to the subsequent ITAM binding thus explaining the altered recruitment of ZAP-70 to the plasma membrane causing autoimmune arthritis in mice. The proposed mechanism of allosteric coupling is unique to ZAP-70, which is fundamentally different from Syk, a close homolog of ZAP-70 expressed in B-cells.

webPSN v2.0: a webserver to infer fingerprints of structural communication in biomacromolecules

A mixed Protein Structure Network (PSN) and Elastic Network Model-Normal Mode Analysis (ENM-NMA)-based strategy (i.e. PSN-ENM) was developed to investigate structural communication in bio-macromolecules. Protein Structure Graphs (PSGs) are computed on a single structure, whereas information on system dynamics is supplied by ENM-NMA. The approach was implemented in a webserver (webPSN), which was significantly updated herein. The webserver now handles both proteins and nucleic acids and relies on an internal upgradable database of network parameters for ions and small molecules in all PDB structures. Apart from the radical restyle of the server and some changes in the calculation setup, other major novelties concern the possibility to: a) compute the differences in nodes, links, and communication pathways between two structures (i.e. network difference) and b) infer links, hubs, communities, and metapaths from consensus networks computed on a number of structures. These new features are useful to identify commonalties and differences between two different functional states of the same system or structural-communication signatures in homologous or analogous systems. The output analysis relies on 3D-representations, interactive tables and graphs, also available for download. Speed and accuracy make this server suitable to comparatively investigate structural communication in large sets of bio-macromolecular systems. URL: http://webpsn.hpc.unimore.it.

Acylation and deacylation mechanism and kinetics of penicillin G reaction with Streptomyces R61 DD-peptidase

Two quantum mechanical (QM)-cluster models are built for studying the acylation and deacylation mechanism and kinetics of Streptomyces R61 DD-peptidase with the penicillin G at atomic level detail. DD-peptidases are bacterial enzymes involved in the cross-linking of peptidoglycan to form the cell wall, necessary for bacterial survival. The cross-linking can be inhibited by antibiotic beta-lactam derivatives through acylation, preventing the acyl-enzyme complex from undergoing further deacylation. The deacylation step was predicted to be rate-limiting. Transition state and intermediate structures are found using density functional theory in this study, and thermodynamic and kinetic properties of the proposed mechanism are evaluated. The acyl-enzyme complex is found lying in a deep thermodynamic sink, and deacylation is indeed the severely rate-limiting step, leading to suicide inhibition of the peptidoglycan cross-linking. The usage of QM-cluster models is a promising technique to understand, improve, and design antibiotics to disrupt function of the Streptomyces R61 DD-peptidase.

Identification of Selective Novel Hits against Plasmodium falciparum Prolyl tRNA Synthetase Active Site and a Predicted Allosteric Site Using in silico Approaches

Recently, there has been increased interest in aminoacyl tRNA synthetases (aaRSs) as potential malarial drug targets. These enzymes play a key role in protein translation by the addition of amino acids to their cognate tRNA. The aaRSs are present in all Plasmodium life cycle stages, and thus present an attractive malarial drug target. Prolyl tRNA synthetase is a class II aaRS that functions in charging tRNA with proline. Various inhibitors against Plasmodium falciparum ProRS (PfProRS) active site have been designed. However, none have gone through clinical trials as they have been found to be highly toxic to human cells. Recently, a possible allosteric site was reported in PfProRS with two possible allosteric modulators: glyburide and TCMDC-124506. In this study, we sought to identify novel selective inhibitors targeting PfProRS active site and possible novel allosteric modulators of this enzyme. To achieve this, virtual screening of South African natural compounds against PfProRS and the human homologue was carried out using AutoDock Vina. The modulation of protein motions by ligand binding was studied by molecular dynamics (MD) using the GROningen MAchine for Chemical Simulations (GROMACS) tool. To further analyse the protein global motions and energetic changes upon ligand binding, principal component analysis (PCA), and free energy landscape (FEL) calculations were performed. Further, to understand the effect of ligand binding on the protein communication, dynamic residue network (DRN) analysis of the MD trajectories was carried out using the MD-TASK tool. A total of ten potential natural hit compounds were identified with strong binding energy scores. Binding of ligands to the protein caused observable global and residue level changes. Dynamic residue network calculations showed increase in betweenness centrality (BC) metric of residues at the allosteric site implying these residues are important in protein communication. A loop region at the catalytic domain between residues 300 and 350 and the anticodon binding domain showed significant contributions to both PC1 and PC2. Large motions were observed at a loop in the Z-domain between residues 697 and 710 which was also in agreement with RMSF calculations that showed increase in flexibility of residues in this region. Residues in this loop region are implicated in ATP binding and thus a change in dynamics may affect ATP binding affinity. Free energy landscape (FEL) calculations showed that the holo protein (protein-ADN complex) and PfProRS-SANC184 complexes were stable, as shown by the low energy with very few intermediates and hardly distinguishable low energy barriers. In addition, FEL results agreed with backbone RMSD distribution plots where stable complexes showed a normal RMSD distribution while unstable complexes had multimodal RMSD distribution. The betweenness centrality metric showed a loss of functional importance of key ATP binding site residues upon allosteric ligand binding. The deep basins in average L observed at the allosteric region imply that there is high accessibility of residues at this region. To further analyse BC and average L metrics data, we calculated the ΔBC and ΔL values by taking each value in the holo protein BC or L matrix less the corresponding value in the ligand-bound complex BC or L matrix. Interestingly, in allosteric complexes, residues located in a loop region implicated in ATP binding had negative ΔL values while in orthosteric complexes these residues had positive ΔL values. An increase in contact frequency between residues Ser263, Thr267, Tyr285, and Leu707 at the allosteric site and residues Thr397, Pro398, Thr402, and Gln395 at the ATP binding TXE loop was observed. In summary, this study identified five potential orthosteric inhibitors and five allosteric modulators against PfProRS. Allosteric modulators changed ATP binding site dynamics, as shown by RMSF, PCA, and DRN calculations. Changes in dynamics of the ATP binding site and increased contact frequency between residues at the proposed allosteric site and the ATP binding site may explain how allosteric modulators distort the ATP binding site and thus might inhibit PfProRS. The scaffolds of the identified hits in the study can be used as a starting point for antimalarial inhibitor development with low human cytotoxicity.

Regulation of MIF Enzymatic Activity by an Allosteric Site at the Central Solvent Channel

In proteins with multiple functions, such as macrophage migration inhibitory factor (MIF), the study of its intramolecular dynamic network can offer a unique opportunity to understand how a single protein is able to carry out several nonoverlapping functions. A dynamic mechanism that controls the MIF-induced activation of CD74 was recently discovered. In this study, the regulation of tautomerase activity was explored. The catalytic base Pro1 is found to form dynamic communications with the same allosteric node that regulates CD74 activation. Signal transmission between the allosteric and catalytic sites take place through intramolecular aromatic interactions and a hydrogen bond network that involves residues and water molecules of the MIF solvent channel. Once thought to be a consequence of trimerization, a regulatory function for the solvent channel is now defined. These results provide mechanistic insights into the regulation of catalytic activity and the role of solvent channel water molecules in MIF catalysis.

NAPS update: network analysis of molecular dynamics data and protein-nucleic acid complexes

Network theory is now a method of choice to gain insights in understanding protein structure, folding and function. In combination with molecular dynamics (MD) simulations, it is an invaluable tool with widespread applications such as analyzing subtle conformational changes and flexibility regions in proteins, dynamic correlation analysis across distant regions for allosteric communications, in drug design to reveal alternative binding pockets for drugs, etc. Updated version of NAPS now facilitates network analysis of the complete repertoire of these biomolecules, i.e., proteins, protein–protein/nucleic acid complexes, MD trajectories, and RNA. Various options provided for analysis of MD trajectories include individual network construction and analysis of intermediate time-steps, comparative analysis of these networks, construction and analysis of average network of the ensemble of trajectories and dynamic cross-correlations. For protein–nucleic acid complexes, networks of the whole complex as well as that of the interface can be constructed and analyzed. For analysis of proteins, protein–protein complexes and MD trajectories, network construction based on inter-residue interaction energies with realistic edge-weights obtained from standard force fields is provided to capture the atomistic details. Updated version of NAPS also provides improved visualization features, interactive plots and bulk execution. URL: http://bioinf.iiit.ac.in/NAPS/

Dynamics and structural communication in the ternary complex of fully phosphorylated V2 vasopressin receptor, vasopressin, and β-arrestin 1

G protein-coupled receptors (GPCRs) are critically regulated by arrestins, which not only desensitize G-protein signaling but also initiate a G protein-independent wave of signaling. The information from structure determination was herein exploited to build a structural model of the ternary complex, comprising fully phosphorylated V2 vasopressin receptor (V2R), the agonist arginine vasopressin (AVP), and β-arrestin 1 (β-arr1). Molecular simulations served to explore dynamics and structural communication in the ternary complex. Flexibility and mechanical profiles reflect fold of V2R and β-arr1. Highly conserved amino acids tend to behave as hubs in the structure network and contribute the most to the mechanical rigidity of V2R seven-helix bundle and of β-arr1. Two structurally and dynamically distinct receptor-arrestin interfaces assist the twist of the N- and C-terminal domains (ND and CD, respectively) of β-arr1 with respect to each other, which is linked to arrestin activation. While motion of the ND is essentially assisted by the fully phosphorylated C-tail of V2R (V2RCt), that of CD is assisted by the second and third intracellular loops and the cytosolic extensions of helices 5 and 6. In the presence of the receptor, the β-arr1 inter-domain twist angle correlates with the modes describing the essential subspace of the ternary complex. β-arr1 motions are also influenced by the anchoring to the membrane of the C-edge-loops in the β-arr1-CD. Overall fluctuations reveal a coupling between motions of the agonist binding site and of β-arr1-ND, which are in allosteric communication between each other. Mechanical rigidity points, often acting as hubs in the structure network and distributed along the main axis of the receptor helix bundle, contribute to establish a preferential communication pathway between agonist ligand and the ND of arrestin. Such communication, mediated by highly conserved amino acids, involves also the first amino acid in the arrestin C-tail, which is highly dynamic and is involved in clathrin-mediated GPCR internalization.

Structure and dynamics of ionic liquid tolerant hyperthermophilic endoglucanase Cel12A from Rhodothermus marinus

Economic deconstruction of lignocellulose remains a challenge due to the complex architecture of cellulose, hemicellulose, and lignin. Advancements in pretreatment processes have introduced ionic liquids (ILs) as promising non-derivatizing solvents for reducing biomass recalcitrance and for promoting enzymatic hydrolysis. However, available commercial cellulases are destabilized or inactivated even in low concentration of residual ILs. Thus, a molecular understanding of IL-enzyme interactions is crucial for developing IL-tolerant enzymes with high catalytic activity. In this study, molecular insight behind the IL tolerance of hyperthermophilic endoglucanase Cel12A from Rhodothermus marinus (RmCel12A) has been investigated in 20%, 40%, and 60% 1-ethyl-3-methylimidazolium acetate (EmimAc) through molecular dynamic simulations at 368 K. Though the enzyme retained its stability in all EmimAc concentrations, the activity was affected due to the loss of essential dynamic motions. A protein structure network was constructed using the snapshots of protein structures from the simulation trajectories and the hub properties of residues R20, Y59, W68, W197, E203, and F220 were found to be lost in 60% EmimAc. Emim cations were observed to intrude the active site tunnel and interact with more number of catalytic residues with higher cumulative fractional occupancy in 60% EmimAc than in 20% or 40% EmimAc. Some non-catalytic residues have also been identified at the active site, which can be probable mutation targets for improving the IL tolerance. Our findings reveal the molecular understanding behind the origin of activity loss of RmCel12A and proposed insights for the further improvement of IL sensitivity.

Understanding the behavior of ionic liquid tolerant hyperthermophilic endoglucanase Cel12A from Rhodothermus marinus in different concentrations of EmimAc.

Probing the Druggablility on the Interface of the Protein-Protein Interaction and Its Allosteric Regulation Mechanism on the Drug Screening for the CXCR4 Homodimer

Modulating protein–protein interactions (PPIs) with small drug-like molecules targeting it exhibits great promise in modern drug discovery. G protein-coupled receptors (GPCRs) are the largest family of targeted proteins and could form dimers in living biological cells through PPIs. However, compared to drug development of the orthosteric site, there has been lack of investigations on the druggability of the PPI interface for GPCRs and its functional implication on experiments. Thus, in order to address these issues, we constructed a novel computational strategy, which involved in molecular dynamics simulation, virtual screening and protein structure network (PSN), to study one representative GPCR homodimer (CXCR4). One druggable pocket was identified in the PPI interface and one small molecule targeting it was screened, which could strengthen PPI mainly through hydrophobic interaction between the benzene rings of the PPI molecule and TM4 of the receptor. The PSN results further reveals that the PPI molecule could increase the number of the allosteric regulation pathways between the druggable pocket of the dimer interface to the orthostatic site for the subunit A but only play minor role for the other subunit B, leading to the asymmetric change in the volume of the binding pockets for the two subunits (increase for the subunit A and minor change for the subunit B). Consequently, the screening performance of the subunit A to the antagonists is enhanced while the subunit B is unchanged nearly, implying that the PPI molecule may be beneficial to enhance the drug efficacies of the antagonists. In addition, one main regulation pathway with the highest frequency was identified for the subunit A, which consists of Trp195^5.34–Tyr190^ECL2–Val196^5.35–Gln200^5.39–Asp262^6.58–Cys28^N-term, revealing their importance in the allosteric regulation from the PPI molecule. The observations from the work could provide valuable information for the development of the PPI drug-like molecule for GPCRs.

Effects of Membrane and Biological Target on the Structural and Allosteric Properties of Recoverin: A Computational Approach

Recoverin (Rec) is a prototypical calcium sensor protein primarily expressed in the vertebrate retina. The binding of two Ca²⁺ ions to the functional EF-hand motifs induces the extrusion of a myristoyl group that increases the affinity of Rec for the membrane and leads to the formation of a complex with rhodopsin kinase (GRK1). Here, unbiased all-atom molecular dynamics simulations were performed to monitor the spontaneous insertion of the myristoyl group into a model multicomponent biological membrane for both isolated Rec and for its complex with a peptide from the GRK1 target. It was found that the functional membrane anchoring of the myristoyl group is triggered by persistent electrostatic protein-membrane interactions. In particular, salt bridges between Arg43, Arg46 and polar heads of phosphatidylserine lipids are necessary to enhance the myristoyl hydrophobic packing in the Rec-GRK1 assembly. The long-distance communication between Ca²⁺-binding EF-hands and residues at the interface with GRK1 is significantly influenced by the presence of the membrane, which leads to dramatic changes in the connectivity of amino acids mediating the highest number of persistent interactions (hubs). In conclusion, specific membrane composition and allosteric interactions are both necessary for the correct assembly and dynamics of functional Rec-GRK1 complex.

Interconnecting Flexibility, Structural Communication, and Function in RhoGEF Oncoproteins

Dbl family Rho guanine nucleotide exchange factors (RhoGEFs) play a central role in cell biology by catalyzing the exchange of guanosine 5'-triphosphate for guanosine 5'-diphosphate (GDP) on RhoA. Insights into the oncogenic constitutive activity of the Lbc RhoGEF were gained by analyzing the structure and dynamics of the protein in different functional states and in comparison with a close homologue, leukemia-associated RhoGEF. Higher intrinsic flexibility, less dense and extended structure network, and less stable allosteric communication pathways in Lbc, compared to the nonconstitutively active homologue, emerged as major determinants of the constitutive activity. Independent of the state, the essential dynamics of the two RhoGEFs is contributed by the last 10 amino acids of Dbl homology (DH) and the whole pleckstrin homology (PH) domains and tends to be equalized by the presence of RhoA. The catalytic activity of the RhoGEF relies on the scaffolding action of the DH domain that primarily turns the switch I (SWI) of RhoA on itself through highly conserved amino acids participating in the stability core and essential for function. Changes in the conformation of SWI and disorganization of the RhoA regions deputed to nucleotide binding are among the major RhoGEF effects leading to GDP release. Binding of RhoA reorganizes the allosteric communication on RhoGEF, strengthening the communication among the canonical RhoA binding site on DH, a secondary RhoA binding site on PH, and the binding site for heterotrimeric G proteins, suggesting dual roles for RhoA as a catalysis substrate and as a regulatory protein. The structure network-based analysis tool employed in this study proved to be useful for predicting potentially druggable regulatory sites in protein structures.

Molecular Dynamics Simulations Study on the Resistant Mechanism of Insects to Imidacloprid due to Y151-S and R81T Mutations in nAChRs

Imidacloprid (IMI) is the first widely used neonicotinoid insecticide due to its high insecticidal activity and low toxicity. However, as its extensive use in crop protection, many insects are resistant to IMI. One of the main resistance mechanisms of insects to IMI is Y151-S and R81T mutations in nicotinic acetylcholine receptor (nAChR). However, how these two mutations affect the interaction of IMI with nAChR is unknown. Here, to uncover the resistant mechanism of nAChR to IMI due to Y151-S and R81T mutations, molecular dynamics simulations and molecular mechanics/generalized Born surface area (MM-GBSA) calculation, residue interaction network (RIN) analysis were performed. Due that the structure of nAChR is still unkonwn, the crystal structure of lymnaea stagnalis acetylcholine binding protein (Ls-AChBP) was used here to simulate nAChR. Y151 and R81 in nAChR correspond to H145 and Q55 in Ls-AChBP, respectively. The calculated binding free energy indicated that two mutations reduced the binding ability of IMI with Ls-AChBP. Q55T mutation reduced the contribution of several key residues, such as W53, T55, Y113, T144 and C187. As for H145-S mutation, the contribution of W53, Q55 and Y113 residues also decreased. RIN analysis showed that two mutants changed the binding pocket by changing the conformation of residues that interact directly with the mutated residues. The obtained resistance mechanism of IMI will be helpful for the design of potent insecticides.

Conformational Dynamics and Allosteric Regulation Landscapes of Germline PTEN Mutations Associated with Autism Compared to Those Associated with Cancer

Individuals with germline PTEN tumor-suppressor variants have PTEN hamartoma tumor syndrome (PHTS). Clinically, PHTS has variable presentations; there are distinct subsets of PHTS-affected individuals, such as those diagnosed with autism spectrum disorder (ASD) or cancer. It remains unclear why mutations in one gene can lead to such seemingly disparate phenotypes. Therefore, we sought to determine whether it is possible to predict a given PHTS-affected individual's a priori risk of ASD, cancer, or the co-occurrence of both phenotypes. By integrating network proximity analysis performed on the human interactome, molecular simulations, and residue-interaction networks, we demonstrate the role of conformational dynamics in the structural communication and long-range allosteric regulation of germline PTEN variants associated with ASD or cancer. We show that the PTEN interactome shares significant overlap with the ASD and cancer interactomes, providing network-based evidence that PTEN is a crucial player in the biology of both disorders. Importantly, this finding suggests that a germline PTEN variant might perturb the ASD or cancer networks differently, thus favoring one disease outcome at any one time. Furthermore, protein-dynamic structural-network analysis reveals small-world structural communication mediated by highly conserved functional residues and potential allosteric regulation of PTEN. We identified a salient structural-communication pathway that extends across the inter-domain interface for cancer-only mutations. In contrast, the structural-communication pathway is predominantly restricted to the phosphatase domain for ASD-only mutations. Our integrative approach supports the prediction and potential modulation of the relevant conformational states that influence structural communication and long-range perturbations associated with mutational effects that lead to PTEN-ASD or PTEN-cancer phenotypes.