gRINN: a tool for calculation of residue interaction energies and protein energy network analysis of molecular dynamics simulations

Multi-omics integration analysis: Tools and applications in environmental toxicology

Nowadays, traditional single-omics study is not enough to explain the causality between molecular alterations and toxicity endpoints for environmental pollutants. With the development of high-throughput sequencing technology and high-resolution mass spectrometry technology, the integrative analysis of multi-omics has become an efficient strategy to understand holistic biological mechanisms and to uncover the regulation network in specific biological processes. This review summarized sample preparation methods, integration analysis tools and the application of multi-omics integration analyses in environmental toxicology field. Currently, omics methods have been widely applied being as the sensitivity of early biological response, especially for low-dose and long-term exposure to environmental pollutants. Integrative omics can reveal the overall changes of genes, proteins, and/or metabolites in the cells, tissues or organisms, which provide new insights into revealing the overall toxicity effects, screening the toxic targets, and exploring the underlying molecular mechanism of pollutants.

Effect of Direct and Water-Mediated Interactions on the Identification of Hotspots in Biomolecular Complexes with Multiple Subsystems

Identification of important residues in biochemical complexes is often a crucial step for many problems in molecular biology and biochemistry. A method is proposed to identify hotspots in biomolecular complexes based on a new metric, derived from networks representing molecular subunits (residues, bridging solvent molecules, ligands etc.) connected by interactions. A singular value decomposition of the weighted adjacency matrix is used to construct a scalar rank for each subunit that reflects its importance in the residue interaction network. This metric is called the singular value centrality. In addition, a new formalism is proposed to account for water-mediated interactions in the ranking of residues. Interactions for a residue network can be provided by various computational methods. In this work interactions are obtained from full quantum-mechanical calculations of protein-protein complexes using the fragment molecular orbital method. The ranking results are shown to be in good agreement with earlier computational and experimental studies. The developed method can be used to gain a deeper insight into the role of subunits in complex biomolecular systems.

Networks of ion-pairs are responsible for the large differences in the thermal stability of two structurally similar aminopeptidases

Aminopeptidases are an important class of enzymes for protein metabolism. Leucyl aminopeptidase (PepL) preferably removes leucine from the N-terminus of small peptides. PepL of Lacticaseibacillus casei was observed to be thermally unstable, while a structurally similar aminopeptidase T (AmpT) of Thermus thermophilus is highly stable. To understand the molecular interaction responsible for the large difference in their stability, molecular dynamics simulations were carried out to study the thermal stability of PepL and AmpT at 300 K to 450 K temperature range over 100 ns. PepL sampled a larger conformational space with a rugged free-energy landscape, while AmpT navigated a smoother energy landscape to reach the global minimum. The RMSD, RMSF, radius of gyration and principal component analysis suggested large movements in PepL than in AmpT with an increase in temperature. Analysis of residue-interaction network revealed AmpT possessing a greater number of low, medium and high energy contacts in comparison to PepL. AmpT showed a higher abundance of ion-pair clusters and ionic residues per cluster compared to PepL. Moreover, AmpT retained a greater number of high-energy contacts at elevated temperatures. These findings showed that the inherently lower stability of PepL originates from a comparatively smaller number of contacts and can be pivotal in engineering PepL for higher stability.

Using residue interaction networks to understand protein function and evolution and to engineer new proteins

Residue interaction networks (RINs) provide graph-based representations of interaction networks within proteins, providing important insight into the factors driving protein structure, function, and stability relationships. There exists a wide range of tools with which to perform RIN analysis, taking into account different types of interactions, input (crystal structures, simulation trajectories, single proteins, or comparative analysis across proteins), as well as formats, including standalone software, web server, and a web application programming interface (API). In particular, the ability to perform comparative RIN analysis across protein families using "metaRINs" provides a valuable tool with which to dissect protein evolution. This, in turn, highlights hotspots to avoid (or target) for in vitro evolutionary studies, providing a powerful framework that can be exploited to engineer new proteins.

Characterization of Mycobacterium smegmatis Glutaminase-Free Asparaginase (MSMEG_3173)

l-asparaginase is an enzyme catalyzing the hydrolysis of l-asparagine into l-aspartate and ammonia, which is of great therapeutic importance in tumor treatment. However, commercially available enzymes are associated with adverse effects, and searching for a new l-asparaginase with better pharmaceutical properties was the aim of this work. The coding sequence for Mycobacterium smegmatisl-asparaginase (MsA) was cloned and expressed. The recombinant protein showed high activity toward l-asparagine, whereas none was detected for l-glutamine. The enzymatic properties (K m = 1.403 ± 0.24 mM and k cat = 708.1 ± 25.05 s-1) indicate that the enzyme would be functional within the expected blood l-asparagine concentration, with good activity, as shown by k cat. The pH and temperature profiles suggest its use as a biopharmaceutical in humans. Molecular dynamics analysis of the MsA model reveals the formation of a hydrogen bond network involving catalytic residues with l-asparagine. However, the same is not observed with l-glutamine, mainly due to steric hindrance. Additionally, the structural feature of residue 119 being a serine rather than a proline has significant implications. These findings help explain the low glutaminase activity observed in MsA, like what is described for the Wolinella succinogenes enzyme. This establishes mycobacterial asparaginases as key scaffolds to develop biopharmaceuticals against acute lymphocytic leukemia.

NMR tools to detect protein allostery

Allostery is a fundamental mechanism of cellular homeostasis by intra-protein communication between distinct functional sites. It is an internal process of proteins to steer interactions not only with each other but also with other biomolecules such as ligands, lipids, and nucleic acids. In addition, allosteric regulation is particularly important in enzymatic activities. A major challenge in structural and molecular biology today is unraveling allosteric sites in proteins, to elucidate the detailed mechanism of allostery and the development of allosteric drugs. Here we summarize the recently developed tools and approaches which enable the elucidation of regulatory hotspots and correlated motion in biomolecules, focusing primarily on solution-state nuclear magnetic resonance spectroscopy (NMR). These tools open an avenue towards a rational understanding of the mechanism of allostery and provide essential information for the design of allosteric drugs.

Protein O-Fucosyltransferase Is Required for the Efficient Invasion of Hepatocytes by Plasmodium berghei Sporozoites

The O-fucosylation of the thrombospondin type I repeat (TSR) domain is important for TSR-containing proteins' optimal folding and stability. However, the importance of Plasmodium O-fucosyltransferase 2 (POFut2) remains unclear due to two different reports. Here, we disrupted the POFut2 gene in Plasmodium berghei and demonstrated that POFut2 KO parasites develop normally in blood and mosquito stages but show reduced infectivity in mice. We found that the reduced infectivity of POFut2 KO sporozoites was due to a diminished level of TRAP that affected the parasite gliding motility and hepatocyte infectivity. Using all-atom MD simulation, we also hypothesize that O-fucosylation impacts the TSR domain's stability more than its heparin binding capacity.

PACAP key interactions with PAC1, VPAC1, and VPAC2 identified by molecular dynamics simulations

The neuropeptide pituitary adenylate cyclase-activating polypeptide (PACAP) belongs to the glucagon/secretin family. PACAP interacts with the pituitary adenylate cyclase-activating polypeptide receptor type 1 (PAC1) and vasoactive intestinal peptide receptors 1 and 2 (VPAC1 and VPAC2), exhibiting functions in the immune, endocrine, and nervous systems. This peptide is upregulated in numerous instances of brain injury, acting as a neuroprotective agent. It can also suppress HIV-1 and SARS-CoV-2 viral replication in vitro. This work aimed to identify, in each peptide-receptor system, the most relevant residues for complex stability and interaction energy communication via Molecular Dynamics (MD), Free Energy calculations, and Protein-energy networks, thus revealing in detail the underlying mechanisms of activation of these receptors. Hydrogen bond formation, interaction energies, and computational alanine scanning between PACAP and its receptors showed that His1, Asp3, Arg12, Arg14, and Lys15 are crucial to the peptide's stability. Furthermore, several PACAP interactions with structurally conserved positions deemed necessary in GPCR B1 activation, including Arg2.60, Lys2.67, and Glu7.42, were significant for the peptide's stability within the receptors. According to the protein-energy network, the connection between Asp3 of PACAP and the receptors' conserved Arg2.60 represents a critical energy communication hub in all complexes. Additionally, the ECDs of the receptors were also found to function as energy communication hubs for PACAP. Although the overall binding mode of PACAP in the three receptors was found to be highly conserved, Arg12 and Tyr13 of PACAP were more prominent in complex with PAC1, while Ser2 of PACAP was with VPAC2. The detailed analyses performed in this work pave the way for using PACAP and its receptors as therapeutic targets.Communicated by Ramaswamy H. Sarma.

State-dependent dynamics of extramembrane domains in the β2 -adrenergic receptor

G protein-coupled receptors (GPCRs) are membrane-bound signaling proteins that play an essential role in cellular signaling processes. Due to their intrinsic function of transmitting internal signals in response to external cues, these receptors are adapted to be highly dynamic in nature. The β2 -adrenergic receptor (β2 AR) is a representative member of the family that has been extensively analyzed in terms of its structure and activation. Although the structure of the transmembrane domain has been characterized in the different functional states of the receptor, the conformational dynamics of the extramembrane domains, especially the intrinsically disordered regions are still emerging. In this study, we analyze the state-dependent dynamics of extramembrane domains of β2 AR using atomistic molecular dynamics simulations. We introduce a parameter, the residue excess dynamics that allows us to better quantify receptor dynamics. Using this measure, we show that the dynamics of the extramembrane domains are sensitive to the receptor state. Interestingly, the ligand-bound intermediateR ' state shows the maximal dynamics compared to either the active R*G or inactive R states. Ligand binding appears to be correlated with high residue excess dynamics that are dampened upon G protein coupling. The intracellular loop-3 (ICL3) domain has a tendency to flip towards the membrane upon ligand binding, which could contribute to receptor "priming." We highlight an important ICL1-helix-8 interplay that is broken in the ligand-bound state but is retained in the active state. Overall, our study highlights the importance of characterizing the functional dynamics of the GPCR loop domains.

Ebola virus VP35 interacts non-covalently with ubiquitin chains to promote viral replication

Ebolavirus (EBOV) belongs to a family of highly pathogenic viruses that cause severe hemorrhagic fever in humans. EBOV replication requires the activity of the viral polymerase complex, which includes the cofactor and Interferon antagonist VP35. We previously showed that the covalent ubiquitination of VP35 promotes virus replication by regulating interactions with the polymerase complex. In addition, VP35 can also interact non-covalently with ubiquitin (Ub); however, the function of this interaction is unknown. Here, we report that VP35 interacts with free (unanchored) K63-linked polyUb chains. Ectopic expression of Isopeptidase T (USP5), which is known to degrade unanchored polyUb chains, reduced VP35 association with Ub and correlated with diminished polymerase activity in a minigenome assay. Using computational methods, we modeled the VP35-Ub non-covalent interacting complex, identified the VP35-Ub interacting surface, and tested mutations to validate the interface. Docking simulations identified chemical compounds that can block VP35-Ub interactions leading to reduced viral polymerase activity. Treatment with the compounds reduced replication of infectious EBOV in cells and in vivo in a mouse model. In conclusion, we identified a novel role of unanchored polyUb in regulating Ebola virus polymerase function and discovered compounds that have promising anti-Ebola virus activity.

Elucidation of bezlotoxumab binding specificity to toxin B in Clostridioides difficile

C. difficile or Clostridioides difficile infection (CDI) is currently one of the major causes of epidemics worldwide. Toxin B from Clostridioides difficile toxin B (TcdB) infection is the main target protein inhibiting CDI recurrence. Clinical research suggested that bezlotoxumab's (Bez) efficiency is significantly reduced in neutralizing the B2 strain compared to the B1 strain. The monoclonal antibody (mAb) functions by binding to the epitope 1 and 2 regions in the combined repetitive oligopeptide (CROP) domain. Some binding residues are distinctively different between B1 and B2 strains. In this work, we aimed to elucidate and compare insights into the interaction of toxins B1 and B2 in complex with Bez by using all-atom molecular dynamics (MD) simulations and binding free energy calculations. The predicted ΔGbinding values suggested that the antibody (Ab) could bind to toxin B1 significantly better than B2, supported by higher salt bridge and hydrogen bonding (H-bonding) interactions, as well as the number of contact residues between the two focused proteins. The toxin B1 residues important for binding with Bez were E1878, T1901, E1902, F1905, N1941, V1946, N2031, T2032, E2033, V2076, V2077, and E2092. The lower susceptibility of Bez towards toxin B2 was primarily due to a change of residue E2033 from glutamate to alanine (A2033) and the loss of E1878 and E1902 contributions, as determined by the intermolecular interaction changes from the dynamic residue interaction network (dRIN) analysis. The obtained data strengthen our understanding of Bez/toxin B binding.

Contribution of Signaling Partner Association to Strigolactone Receptor Selectivity

The parasitic plant witchweed, Striga hermonthica, results in agricultural losses of billions of dollars per year. It perceives its host via plant hormones called strigolactones, which act as germination stimulants for witchweed. Strigolactone signaling involves substrate binding to the strigolactone receptor, followed by substrate hydrolysis and a conformational change from an inactive, or open state, to an active, or closed state. In the active state, the receptor associates with a signaling partner, MAX2. Recently, it was shown that this MAX2 association process acts as a strong contributor to the uniquely high signaling activity observed in ShHTL7; however, it is unknown why ShHTL7 has enhanced MAX2 association affinity. Using an umbrella sampling molecular dynamics approach, we characterized the association processes of AtD14, ShHTL7, a mutant of ShHTL7, and ShHTL6 with MAX2 homologue OsD3. From these results, we show that ShHTL7 has an enhanced standard binding free energy of OsD3 compared to those of the other receptors. Additionally, our results suggest that the overall topology of the T2/T3 helix region is likely an important modulator of MAX2 binding. Thus, differences in MAX2 association, modulated by differences in the T2/T3 helix region, are a contributor to differences in signaling activity between different strigolactone receptors.

Surfaces: a software to quantify and visualize interactions within and between proteins and ligands

SUMMARY

Computational methods for the quantification and visualization of the relative contribution of molecular interactions to the stability of biomolecular structures and complexes are fundamental to understand, modulate and engineer biological processes. Here, we present Surfaces, an easy to use, fast and customizable software for quantification and visualization of molecular interactions based on the calculation of surface areas in contact. Surfaces calculations shows equivalent or better correlations with experimental data as computationally expensive methods based on molecular dynamics.

AVAILABILITY AND IMPLEMENTATION

All scripts are available at https://github.com/NRGLab/Surfaces. Surface's documentation is available at https://surfaces-tutorial.readthedocs.io/en/latest/index.html.

Connected Component Analysis of Dynamical Perturbation Contact Networks

Describing protein dynamical networks through amino acid contacts is a powerful way to analyze complex biomolecular systems. However, due to the size of the systems, identifying the relevant features of protein-weighted graphs can be a difficult task. To address this issue, we present the connected component analysis (CCA) approach that allows for fast, robust, and unbiased analysis of dynamical perturbation contact networks (DPCNs). We first illustrate the CCA method as applied to a prototypical allosteric enzyme, the imidazoleglycerol phosphate synthase (IGPS) enzyme from Thermotoga maritima bacteria. This approach was shown to outperform the clustering methods applied to DPCNs, which could not capture the propagation of the allosteric signal within the protein graph. On the other hand, CCA reduced the DPCN size, providing connected components that nicely describe the allosteric propagation of the signal from the effector to the active sites of the protein. By applying the CCA to the IGPS enzyme in different conditions, i.e., at high temperature and from another organism (yeast IGPS), and to a different enzyme, i.e., a protein kinase, we demonstrated how CCA of DPCNs is an effective and transferable tool that facilitates the analysis of protein-weighted networks.

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

G-protein coupled receptors (GPCRs) present specific activation pathways and signaling among receptor subtypes. Hence, an extensive knowledge of the structural dynamics of the receptor is critical for the development of therapeutics. Here, we target the adenosine A1 receptor (A1R), for which a negligible number of drugs have been approved. We combine molecular dynamics simulations, enhanced sampling techniques, network theory and pocket detection to decipher the activation pathway of A1R, decode the allosteric networks and identify transient pockets. The A1R activation pathway reveal hidden intermediate and pre-active states together with the inactive and fully-active states observed experimentally. The protein energy networks computed throughout these conformational states successfully unravel the extra and intracellular allosteric centers and the communication pathways that couples them. We observe that the allosteric networks are dynamic, being increased along activation and fine-tuned in presence of the trimeric G-proteins. Overlap of transient pockets and energy networks uncover how the allosteric coupling between pockets and distinct functional regions of the receptor is altered along activation. By an in-depth analysis of the bridge between activation pathway, energy networks and transient pockets, we provide a further understanding of A1R. This information can be useful to ease the design of allosteric modulators for A1R.

Characterizing interactions in E-cadherin assemblages

Cadherin intermolecular interactions are critical for cell-cell adhesion and play essential roles in tissue formation and the maintenance of tissue structures. In this study, we focus on E-cadherin, a classical cadherin that connects epithelial cells, to understand how they interact in cis and trans conformations when attached to the same cell or opposing cells. We employ coevolutionary sequence analysis and molecular dynamics simulations to confirm previously known interaction sites as well as to identify new interaction sites. The sequence coevolutionary results yield a surprising result indicating that there are no strongly favored intermolecular interaction sites, which is unusual and suggests that many interaction sites may be possible, with none being strongly preferred over others. By using molecular dynamics, we test the persistence of these interactions and how they facilitate adhesion. We build several types of cadherin assemblages, with different numbers and combinations of cis and trans interfaces to understand how these conformations act to facilitate adhesion. Our results suggest that, in addition to the established interaction sites on the EC1 and EC2 domains, an additional plausible cis interface at the EC3-EC5 domain exists. Furthermore, we identify specific mutations at cis/trans binding sites that impair adhesion within E-cadherin assemblages.

PyInteraph2 and PyInKnife2 to Analyze Networks in Protein Structural Ensembles

Due to the complex nature of noncovalent interactions and their long-range effects, analyzing protein conformations using network theory can be enlightening. Protein Structure Networks (PSNs) provide a convenient formalism to study protein structures in relation to essential properties such as key residues for structural stability, allosteric communication, and the effects of modifications of the protein. PSNs can be defined according to very different principles, and the available tools have limitations in input formats, supported models, and version control. Other outstanding problems are related to the definition of network cutoffs and the assessment of the stability of the network properties. The protein science community could benefit from a common framework to carry out these analyses and make them easier to reproduce, reuse, and evaluate. We here provide two open-source software packages, PyInteraph2 and PyInKnife2, to implement and analyze PSNs in a reproducible and documented manner. PyInteraph2 interfaces with multiple formats for protein ensembles and incorporates different network models with the possibility of integrating them into a macronetwork and performing various downstream analyses, including hubs, connected components, and several other centrality measures, and visualizes the networks or further analyzes them thanks to compatibility with Cytoscape.PyInKnife2 that supports the network models implemented in PyInteraph2. It employs a jackknife resampling approach to estimate the convergence of network properties and streamline the selection of distance cutoffs. We foresee that the modular structure of the code and the supported version control system will promote the transition to a community-driven effort, boost reproducibility, and establish common protocols in the PSN field. As developers, we will guarantee the introduction of new functionalities and maintenance, assistance, and training of new contributors.

Ebola Virus VP35 Interacts Non-Covalently with Ubiquitin Chains to Promote Viral Replication Creating New Therapeutic Opportunities

Ebolavirus (EBOV) belongs to a family of highly pathogenic viruses that cause severe hemorrhagic fever in humans. EBOV replication requires the activity of the viral polymerase complex, which includes the co-factor and Interferon antagonist VP35. We previously showed that the covalent ubiquitination of VP35 promotes virus replication by regulating interactions with the polymerase complex. In addition, VP35 can also interact non-covalently with ubiquitin (Ub); however, the function of this interaction is unknown. Here, we report that VP35 interacts with free (unanchored) K63-linked polyUb chains. Ectopic expression of Isopeptidase T (USP5), which is known to degrade unanchored polyUb chains, reduced VP35 association with Ub and correlated with diminished polymerase activity in a minigenome assay. Using computational methods, we modeled the VP35-Ub non-covalent interacting complex, identified the VP35-Ub interacting surface and tested mutations to validate the interface. Docking simulations identified chemical compounds that can block VP35-Ub interactions leading to reduced viral polymerase activity that correlated with reduced replication of infectious EBOV. In conclusion, we identified a novel role of unanchored polyUb in regulating Ebola virus polymerase function and discovered compounds that have promising anti-Ebola virus activity.

Purification and identification of xanthine oxidase inhibitory peptides from enzymatic hydrolysate of α-lactalbumin and bovine colostrum casein

The development of food-derived Xanthine Oxidase (XO) inhibitors is critical to the treatment of hyperuricemia and oxidative stress-related disease. Few studies report on milk protein hydrolysates' XO inhibitory activity, with the mechanism of their interaction remaining elusive. Here, different commercial enzymes were used to hydrolyze α-lactalbumin and bovine colostrum casein. The two proteins hydrolyzed by alkaline protease exhibited the most potent XO inhibitory activity (bovine casein: IC₅₀ = 0.13 mg mL^-1; α-lactalbumin: IC₅₀ = 0.28 mg mL^-1). Eight potential XO inhibitory peptides including VYPFPGPI, GPVRGPFPIIV, VYPFPGPIPN, VYPFPGPIHN, QLKRFSFRSFIWR, LVYPFPGPIHN, AVFPSIVGR, and GFININSLR (IC₅₀ of 4.67-8.02 mM) were purified and identified from alkaline protease hydrolysates by using gel filtration, LC-MS/MS and PeptideRanker. The most important role of inhibiting activity of peptides is linked to hydrophobic interactions and hydrogen bonding based on the results of molecular docking and molecular dynamics simulation. The enzymatic hydrolysate of α-lactalbumin and bovine colostrum casein could be a competitive candidates for hyperuricemia-resisting functional food.

Structural Model for Factor X Inhibition of IgM and Complement-Mediated Neutralization of Adenovirus

Adenovirus has strong therapeutic potential as an oncolytic virus and gene therapy vector. However, injecting human species C serotype 5 adenovirus, HAdv-C5, into the bloodstream leads to numerous interactions with plasma proteins that affect viral tropism and biodistribution, and can lead to potent immune responses and viral neutralization. The HAdv/factor X (FX) interaction facilitates highly efficient liver transduction and protects virus particles from complement-mediated neutralization after intravenous delivery. Ablating the FX interaction site on the HAdv-C5 capsid leaves the virus susceptible to neutralization by natural IgM followed by activation of the complement cascade and covalent binding of complement components C4b and C3b to the viral capsid. Here we present structural models for IgM and complement components C1, C4b, and C3b in complex with HAdv-C5. Molecular dynamics simulations indicate that when C3b binds near the vertex, multiple stabilizing interactions can be formed between C3b, penton base, and fiber. These interactions may stabilize the vertex region of the capsid and prevent release of the virally encoded membrane lytic factor, protein VI, which is packaged inside of the viral capsid, thus effectively neutralizing the virus. In a situation where FX and IgM are competing for binding to the capsid, IgM may not be able to form a bent conformation in which most of its Fab arms interact with the capsid. Our structural modeling of the competitive interaction of FX and IgM with HAdv-C5 allows us to propose a mechanistic model for FX inhibition of IgM-mediated virus neutralization. According to this model, although IgM may bind to the capsid, in the presence of FX it will likely retain a planar conformation and thus be unable to promote activation of the complement cascade at the virus surface.

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

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

Swing-out opening of stromal interaction molecule 1

Stromal interaction molecule 1 (STIM1) resides in the endoplasmic reticulum (ER) membrane and senses luminal calcium (Ca2+ ) concentration. STIM1 activation involves a large-scale conformational transition that exposes a STIM1 domain termed "CAD/SOAR", - which is required for activation of the calcium channel Orai. Under resting cell conditions, STIM1 assumes a quiescent state where CAD/SOAR is suspended in an intramolecular clamp formed by the coiled-coil 1 domain (CC1) and CAD/SOAR. Here, we present a structural model of the cytosolic part of the STIM1 resting state using molecular docking simulations that take into account previously reported interaction sites between the CC1α1 and CAD/SOAR domains. We corroborate and refine previously reported interdomain coiled-coil contacts. Based on our model, we provide a detailed analysis of the CC1-CAD/SOAR binding interface using molecular dynamics simulations. We find a very similar binding interface for a proposed domain-swapped configuration of STIM1, where the CAD/SOAR domain of one monomer interacts with the CC1α1 domain of another monomer of STIM1. The rich structural and dynamical information obtained from our simulations reveals novel interaction sites such as M244, I409, or E370, which are crucial for STIM1 quiescent state stability. We tested our predictions by electrophysiological and Förster resonance energy transfer experiments on corresponding single-point mutants. These experiments provide compelling support for the structural model of the STIM1 quiescent state reported here. Based on transitions observed in enhanced-sampling simulations paired with an analysis of the quiescent STIM1 conformational dynamics, our work offers a first atomistic model for CC1α1-CAD/SOAR detachment.

A single amino acid deletion in the ER Ca2+ sensor STIM1 reverses the in vitro and in vivo effects of the Stormorken syndrome-causing R304W mutation

Stormorken syndrome is a multiorgan hereditary disease caused by dysfunction of the endoplasmic reticulum (ER) Ca2+ sensor protein STIM1, which forms the Ca2+ release-activated Ca2+ (CRAC) channel together with the plasma membrane channel Orai1. ER Ca2+ store depletion activates STIM1 by releasing the intramolecular "clamp" formed between the coiled coil 1 (CC1) and CC3 domains of the protein, enabling the C terminus to extend and interact with Orai1. The most frequently occurring mutation in patients with Stormorken syndrome is R304W, which destabilizes and extends the STIM1 C terminus independently of ER Ca2+ store depletion, causing constitutive binding to Orai1 and CRAC channel activation. We found that in cis deletion of one amino acid residue, Glu296 (which we called E296del) reversed the pathological effects of R304W. Homozygous Stim1 E296del+R304W mice were viable and phenotypically indistinguishable from wild-type mice. NMR spectroscopy, molecular dynamics simulations, and cellular experiments revealed that although the R304W mutation prevented CC1 from interacting with CC3, the additional deletion of Glu296 opposed this effect by enabling CC1-CC3 binding and restoring the CC domain interactions within STIM1 that are critical for proper CRAC channel function. Our results provide insight into the activation mechanism of STIM1 by clarifying the molecular basis of mutation-elicited protein dysfunction and pathophysiology.

A new approach for extracting information from protein dynamics

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

Targeted pharmacokinetics and bioinformatics screening strategy reveals JAK2 as the main target for Xin-Ji-Er-Kang in treatment of MIR injury

BACKGROUND AND PURPOSE

Xin-Ji-Er-Kang (XJEK) is traditional Chinese formula presented excellent protective effects on several heart diseases, but the potential components and targets are still unclear. The aim of this study is to elucidate the effective components of XJEK and reveal its potential mechanism of cardioprotective effect in myocardial ischemia-reperfusion (MIR) injury.

EXPERIMENTAL APPROACH

Firstly, the key compounds in XJEK, plasma and heart tissue were analyzed by high resolution mass spectrometry. Bioinformatics studies were also involved to disclose the potential targets and the binding sites for the key compounds. Secondly, to study the protective effect of XJEK on MIR injury and related mechanism, mice subjected to MIR surgery and gavage administered with XJEK for 6 weeks. Cardiac function parameters and apoptosis level of cardiac tissue were assessed. The potential mechanism was further verified by knock down of target protein in vitro.

RESULTS

Pharmacokinetics studies showed that Sophora flavescens alkaloids, primarily composed with matrine, are the key component of XJEK. And, through bioinformatic analysis, we speculated JAK2 could be the potential target for XJEK, and could form stable hydrogen bonds with matrine. Administration of XJEK and matrine significantly improved heart function and reduced apoptosis of cardiomyocytes by increasing the phosphorylation of JAK2 and STAT3. The anti-apoptosis effect of XJEK and matrine was also observed on AC16 cells, and could be reversed by co-treatment with JAK2 inhibitor AG490 or knock-down of JAK2.

CONCLUSION

XJEK exerts cardioprotective effect on MIR injury, which may be associated with the activation of JAK2/STAT3 signaling pathway.

In-silico structural inhibition of ACE-2 binding site of SARS-CoV-2 and SARS-CoV-2 Omicron spike protein by lectin antiviral dyad system to treat COVID-19

Spike glycoprotein of SARS-CoV-2 binds ACE-2 receptors via its receptor-binding-domain (RBD) and mediates virus-to-host cell fusion. Recently emerged omicron variant of SARS-CoV-2 possess around 30 mutations in spike protein where N501Y tremendously increases viral infectivity and transmission. Lectins interact with glycoproteins and mediate innate immunity displaying antiviral, antibacterial and anticarcinogenic properties. In this study, we analysed the potential of lectin, and lectin-antibody (spike-specific) complex to inhibit the ACE-2 binding site of wild and N501Y mutated spike protein by utilizing in-silico molecular docking and simulation approach. Docking of lectin at reported ACE-2 binding spike-RBD residues displayed the ZDock scores of 1907 for wild and 1750 for N501Y mutated spike-RBD. Binding of lectin with antibody to form proposed dyad complex gave ZDock score of 1174 revealing stable binding. Docking of dyad complex with wild and N501Y mutated spike-RBD, at lectin and antibody individually, showed high efficiency binding hence, effective structural inhibition of spike-RBD. MD simulation of 100ns of each complex proved high stability of complexes with RMSD values ranging from 0.2 -1.5nm. Consistent interactions of lead ACE-2 binding spike residues with lectin during simulation disclosed efficient structural inhibition by lectin against formation of spike RBD-ACE-2 complex.Hence, lectins along with their ability to induce innate immunity against spike glycoprotein can structurally inhibit the spike-RBD when given as lectin-antibody dyad system and thus can be developed into a dual effect treatment against COVID-19. Moreover, the high binding specificity of this system with spike-RBD can be exploited for development of diagnostic and drug-delivery systems.

In silico evaluation of Philippine Natural Products against SARS-CoV-2 Main Protease

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, is a novel strain of coronavirus first reported in December 2019 which rapidly spread throughout the world and was subsequently declared a pandemic by the World Health Organization (WHO) in March 2020. Although vaccines, as well as treatments, have been rapidly developed and deployed, these are still spread thin, especially in the developing world. There is also a continuing threat of the emergence of mutated variants which may not be as responsive to available vaccines and drugs. Accessible and affordable sources of antiviral drugs against SARS-CoV-2 offer wider options for the clinical treatment of populations at risk for severe COVID-19. Using in silico methods, this study identified potential inhibitors against the SARS-CoV-2 main protease (Mpro), the protease directly responsible for the activation of the viral replication enzyme, from a consolidated database of 1516 Philippine natural products. Molecular docking experiments, along with in silico ADME predictions, determined top ligands from this database with the highest potential inhibitory effects against Mpro. Molecular dynamic trajectories of the apo and diosmetin-7-O-b-D-glucopyranoside (DG) in complex with the protein predicted potential mechanisms of action for the ligand-by separating the Cys145-His41 catalytic dyad and by influencing the protein network through key intra-signaling residues within the Mpro binding site. These findings show the inhibitory potential of DG against the SARS-CoV-2 Mpro, and further validation is recommended through in vitro or in vivo experimentation.

Expanding the Accessible Chemical Space of SIRT2 Inhibitors through Exploration of Binding Pocket Dynamics

Considerations of binding pocket dynamics are one of the crucial aspects of the rational design of binders. Identification of alternative conformational states or cryptic subpockets could lead to the discovery of completely novel groups of the ligands. However, experimental characterization of pocket dynamics, besides being expensive, may not be able to elucidate all of the conformational states relevant for drug discovery projects. In this study, we propose the protocol for computational simulations of sirtuin 2 (SIRT2) binding pocket dynamics and its integration into the structure-based virtual screening (SBVS) pipeline. Initially, unbiased molecular dynamics simulations of SIRT2:inhibitor complexes were performed using optimized force field parameters of SIRT2 inhibitors. Time-lagged independent component analysis (tICA) was used to design pocket-related collective variables (CVs) for enhanced sampling of SIRT2 pocket dynamics. Metadynamics simulations in the tICA eigenvector space revealed alternative conformational states of the SIRT2 binding pocket and the existence of a cryptic subpocket. Newly identified SIRT2 conformational states outperformed experimentally resolved states in retrospective SBVS validation. After performing prospective SBVS, compounds from the under-represented portions of the SIRT2 inhibitor chemical space were selected for in vitro evaluation. Two compounds, NDJ18 and NDJ85, were identified as potent and selective SIRT2 inhibitors, which validated the in silico protocol and opened up the possibility for generalization and broadening of its application. The anticancer effects of the most potent compound NDJ18 were examined on the triple-negative breast cancer cell line. Results indicated that NDJ18 represents a promising structure suitable for further evaluation.

Molecular Modeling is an Enabling Approach to Complement and Enhance Channelopathy Research

Hundreds of human membrane proteins form channels that transport necessary ions and compounds, including drugs and metabolites, yet details of their normal function or how function is altered by genetic variants to cause diseases are often unknown. Without this knowledge, researchers are less equipped to develop approaches to diagnose and treat channelopathies. High-resolution computational approaches such as molecular modeling enable researchers to investigate channelopathy protein function, facilitate detailed hypothesis generation, and produce data that is difficult to gather experimentally. Molecular modeling can be tailored to each physiologic context that a protein may act within, some of which may currently be difficult or impossible to assay experimentally. Because many genomic variants are observed in channelopathy proteins from high-throughput sequencing studies, methods with mechanistic value are needed to interpret their effects. The eminent field of structural bioinformatics integrates techniques from multiple disciplines including molecular modeling, computational chemistry, biophysics, and biochemistry, to develop mechanistic hypotheses and enhance the information available for understanding function. Molecular modeling and simulation access 3D and time-dependent information, not currently predictable from sequence. Thus, molecular modeling is valuable for increasing the resolution with which the natural function of protein channels can be investigated, and for interpreting how genomic variants alter them to produce physiologic changes that manifest as channelopathies. © 2022 American Physiological Society. Compr Physiol 12:3141-3166, 2022.

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.

SenseNet, a tool for analysis of protein structure networks obtained from molecular dynamics simulations

Computational methods play a key role for investigating allosteric mechanisms in proteins, with the potential of generating valuable insights for innovative drug design. Here we present the SenseNet (“Structure ENSEmble NETworks”) framework for analysis of protein structure networks, which differs from established network models by focusing on interaction timelines obtained by molecular dynamics simulations. This approach is evaluated by predicting allosteric residues reported by NMR experiments in the PDZ2 domain of hPTP1e, a reference system for which previous computational predictions have shown considerable variance. We applied two models based on the mutual information between interaction timelines to estimate the conformational influence of each residue on its local environment. In terms of accuracy our prediction model is comparable to the top performing model published for this system, but by contrast benefits from its independence from NMR structures. Our results are complementary to experimental data and the consensus of previous predictions, demonstrating the potential of our new analysis tool SenseNet. Biochemical interpretation of our model suggests that allosteric residues in the PDZ2 domain form two distinct clusters of contiguous sidechain surfaces. SenseNet is provided as a plugin for the network analysis software Cytoscape, allowing for ease of future application and contributing to a system of compatible tools bridging the fields of system and structural biology.

A new approach for extracting information from protein dynamics

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

Modeling the Dynamics of Protein-Protein Interfaces, How and Why?

Protein-protein assemblies act as a key component in numerous cellular processes. Their accurate modeling at the atomic level remains a challenge for structural biology. To address this challenge, several docking and a handful of deep learning methodologies focus on modeling protein-protein interfaces. Although the outcome of these methods has been assessed using static reference structures, more and more data point to the fact that the interaction stability and specificity is encoded in the dynamics of these interfaces. Therefore, this dynamics information must be taken into account when modeling and assessing protein interactions at the atomistic scale. Expanding on this, our review initially focuses on the recent computational strategies aiming at investigating protein-protein interfaces in a dynamic fashion using enhanced sampling, multi-scale modeling, and experimental data integration. Then, we discuss how interface dynamics report on the function of protein assemblies in globular complexes, in fuzzy complexes containing intrinsically disordered proteins, as well as in active complexes, where chemical reactions take place across the protein-protein interface.

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.

Conformational exploration of RbgA using molecular dynamics: Possible implications in ribosome maturation and GTPase activity in different nucleotide bound states

Ribosome biogenesis GTPase A (RbgA) is involved in the late steps of the 50S ribosomal subunit maturation by binding into the 45S pre-ribosomal subunit. The association of RbgA to the 45S intermediate subunit depends on its bound nucleotide (GTP/GDP), probably because of the conformational shifts that occur between the GTP and GDP bound states. However, the available crystal structures of Staphylococcus aureus RbgA (SaRbgA) do not show any significant variations between different nucleotide bound states. Therefore, conformational exploration of SaRbgA in different nucleotide bound states was carried out using all-atom molecular dynamics (MD) simulations. Exploration of conformational distribution using cluster analysis and principal component analysis (PCA) revealed that GDP and pppGpp bound systems exhibit a larger distribution. This is majorly due to the fluctuations of the C-terminal tail (C-tail) as a result of the unwinding of α-helical secondary conformations into loop conformations which are observed from RMSF and DSSP analyses. Further investigation of the network of interactions revealed that the GTP and GMPPNP bound systems hold the C-tail in an α-helical form through stronger interactions between the active-site and C-tail. We also find that the presence of Mg²⁺ positions Sw-I loop away from the bound nucleotide and stabilizes the active-site water molecules. This seems to assist SaRbgA GTPase activity. In addition, mutations at the C-terminal and Sw-II conserved residues exhibit a larger conformational distribution majorly due to the C-tail fluctuations suggesting that the C-tail of SaRbgA probably interacts with the rRNA or rprotein in the process of ribosome biogenesis.

Simulated Drug Efflux for the AbgT Family of Membrane Transporters

Drug extrusion through molecular efflux pumps is an important mechanism for the survival of many pathogenic bacteria by removing drugs, providing multidrug resistance (MDR). Understanding molecular mechanisms for drug extrusion in multidrug efflux pumps is important for the development of new antiresistance drugs. The AbgT family of transporters involved in the folic acid biosynthesis pathway represents one such important efflux pump system. In addition to the transport of the folic acid precursor p-amino benzoic acid (PABA), members of this family are involved in the efflux of several sulfa drugs, conferring drug resistance to the bacteria. With the availability of structures for two members of this family (YdaH and MtrF), we investigate molecular pathways for transport of PABA and a sulfa drug (sulfamethazine) particularly for the YdaH transporter using steered molecular dynamics. Our analyses reveal the probable ligand migration pathways through the transporter, which also identifies key residues along the transport pathway. In addition, simulations using both PABA and sulfamethazine show how the protein is able to transport ligands of different shapes and sizes out of the pathogen. Our observations confirm previously reported functional residues for transport along the pathways by which YdaH transporters achieve antibiotic resistance to shuttle drugs out of the cells.

Defects in the STIM1 SOARα2 domain affect multiple steps in the CRAC channel activation cascade

The calcium release-activated calcium (CRAC) channel consists of STIM1, a Ca2+ sensor in the endoplasmic reticulum (ER), and Orai1, the Ca2+ ion channel in the plasma membrane. Ca2+ store depletion triggers conformational changes and oligomerization of STIM1 proteins and their direct interaction with Orai1. Structural alterations include the transition of STIM1 C-terminus from a folded to an extended conformation thereby exposing CAD (CRAC activation domain)/SOAR (STIM1-Orai1 activation region) for coupling to Orai1. In this study, we discovered that different point mutations of F394 in the small alpha helical segment (STIM1 α2) within the CAD/SOAR apex entail a rich plethora of effects on diverse STIM1 activation steps. An alanine substitution (STIM1 F394A) destabilized the STIM1 quiescent state, as evident from its constitutive activity. Single point mutation to hydrophilic, charged amino acids (STIM1 F394D, STIM1 F394K) impaired STIM1 homomerization and subsequent Orai1 activation. MD simulations suggest that their loss of homomerization may arise from altered formation of the CC1α1-SOAR/CAD interface and potential electrostatic interactions with lipid headgroups in the ER membrane. Consistent with these findings, we provide experimental evidence that the perturbing effects of F394D depend on the distance of the apex from the ER membrane. Taken together, our results suggest that the CAD/SOAR apex is in the immediate vicinity of the ER membrane in the STIM1 quiescent state and that different mutations therein can impact the STIM1/Orai1 activation cascade in various manners. Legend: Upon intracellular Ca2+ store depletion of the endoplasmic reticulum (ER), Ca2+ dissociates from STIM1. As a result, STIM1 adopts an elongated conformation and elicits Ca2+ influx from the extracellular matrix (EM) into the cell due to binding to and activation of Ca2+-selective Orai1 channels (left). The effects of three point mutations within the SOARα2 domain highlight the manifold roles of this region in the STIM1/Orai1 activation cascade: STIM1 F394A is active irrespective of the intracellular ER Ca2+ store level, but activates Orai1 channels to a reduced extent (middle). On the other hand, STIM1 F394D/K cannot adopt an elongated conformation upon Ca2+ store-depletion due to altered formation of the CC1α1-SOAR/CAD interface and/or electrostatic interaction of the respective side-chain charge with corresponding opposite charges on lipid headgroups in the ER membrane (right).

pyProGA-A PyMOL plugin for protein residue network analysis

The field of protein residue network (PRN) research has brought several useful methods and techniques for structural analysis of proteins and protein complexes. Many of these are ripe and ready to be used by the proteomics community outside of the PRN specialists. In this paper we present software which collects an ensemble of (network) methods tailored towards the analysis of protein-protein interactions (PPI) and/or interactions of proteins with ligands of other type, e.g. nucleic acids, oligosaccharides etc. In parallel, we propose the use of the network differential analysis as a method to identify residues mediating key interactions between proteins. We use a model system, to show that in combination with other, already published methods, also included in pyProGA, it can be used to make such predictions. Such extended repertoire of methods allows to cross-check predictions with other methods as well, as we show here. In addition, the possibility to construct PRN models from various kinds of input is so far a unique asset of our code. One can use structural data as defined in PDB files and/or from data on residue pair interaction energies, either from force-field parameters or fragment molecular orbital (FMO) calculations. pyProGA is a free open-source software available from https://gitlab.com/Vlado_S/pyproga.

Transient Tertiary Structures of Disordered Dynein Intermediate Chain Regulate its Interactions with Multiple Partners

The N-terminal domain of dynein intermediate chain (N-IC) is central to the cytoplasmic dynein 'cargo attachment subcomplex' and regulation of motor activity. It is a prototypical intrinsically disordered protein (IDP), serving as a primarily disordered polybivalent molecular scaffold for numerous binding partners, including three dimeric dynein light chains and coiled coil domains of dynein partners dynactin p150^Glued and NudE. At the very N-terminus, a 40 amino acid single alpha helix (SAH) forms the major binding site for both p150^Glued and NudE, while a shorter nascent helix (H2) separated from SAH by a disordered linker, is necessary for tight binding to dynactin p150^Glued but not to NudE. Here we demonstrate that transient tertiary interactions in this highly dynamic protein underlie the differences in its interactions with p150^Glued and NudE. NMR paramagnetic relaxation enhancement experiments and restrained molecular dynamics simulations identify interactions between the two non-contiguous SAH and H2 helical regions, the extent of which correlates with the length and stability of H2, showing clearly that tertiary and secondary structure formation are coupled in IDPs. These interactions are significantly attenuated when N-IC is bound to NudE, suggesting that NudE binding shifts the conformational ensemble to one that is more extended and with less structure in H2. While the intrinsic disorder and flexibility in N-IC modulate its ability to serve as a binding platform for numerous partners, deviations of this protein from random-coil behavior provide a process for regulating these binding interactions and potentially the dynein motor.

Evolutionary selectivity of amino acid is inspired from the enhanced structural stability and flexibility of the folded protein

AIM

The present study attempts to decipher the site-specific amino acid alterations at certain positions experiencing preferential selectivity and their effect on proteins' stability and flexibility. The study examines the selection preferences by considering pair-wise non-bonded interaction energies of adjacent and interacting amino acids present at the interacting site, along with their evolutionary history.

MATERIALS AND METHODS

For the study, variations in the interacting residues of spike protein (S-Protein) receptor-binding domain (RBD) of different coronaviruses were examined. The MD simulation trajectory analysis revealed that, though all the variants studied were structurally stable at their native and bound confirmations, the RBD of 2019-nCoV/SARS-CoV-2 was found to be more flexible and more dynamic. Furthermore, a noticeable change observed in the non-bonded interaction energies of the amino acids interacting with the receptor corroborated their selection at respective positions.

KEY FINDINGS

The conformational changes exerted by the altered amino acids could be the reason for a broader range of interacting receptors among the selected proteins.

SIGNIFICANCE

The results envisage a strong indication that the residue selection at certain positions is governed by a well-orchestrated feedback mechanism, which follows increased stability and flexibility in the folded structure compared to its evolutionary predecessor.

Dynamic residue interaction network analysis of the oseltamivir binding site of N1 neuraminidase and its H274Y mutation site conferring drug resistance in influenza A virus

Background

Oseltamivir (OTV)-resistant influenza virus exhibits His-to-Tyr mutation at residue 274 (H274Y) in N1 neuraminidase (NA). However, the molecular mechanisms by which the H274Y mutation in NA reduces its binding affinity to OTV have not been fully elucidated.

Methods

In this study, we used dynamic residue interaction network (dRIN) analysis based on molecular dynamics simulation to investigate the correlation between the OTV binding site of NA and its H274Y mutation site.

Results

dRIN analysis revealed that the OTV binding site and H274Y mutation site of NA interact via the three interface residues connecting them. H274Y mutation significantly enhanced the interaction between residue 274 and the three interface residues in NA, thereby significantly decreasing the interaction between OTV and its surrounding loop 150 residues. Thus, we concluded that such changes in residue interactions could reduce the binding affinity of OTV to NA, resulting in drug resistant influenza viruses. Using dRIN analysis, we succeeded in understanding the characteristic changes in residue interactions due to H274Y mutation, which can elucidate the molecular mechanism of reduction in OTV binding affinity to influenza NA. Finally, the dRIN analysis used in this study can be widely applied to various systems such as individual proteins, protein-ligand complexes, and protein-protein complexes, to characterize the dynamic aspects of the interactions.

Unraveling the Allosteric Communication Mechanisms in T-Cell Receptor-Peptide-Loaded Major Histocompatibility Complex Dynamics Using Molecular Dynamics Simulations: An Approach Based on Dynamic Cross Correlation Maps and Residue Interaction Energy Calculations

Antigen presentation by major histocompatibility complex (MHC) proteins to T-cell receptors (TCRs) plays a crucial role in triggering the adaptive immune response. Most of our knowledge on TCR-peptide-loaded major histocompatibility complex (pMHC) interaction stemmed from experiments yielding static structures, yet the dynamic aspects of this molecular interaction are equally important to understand the underlying molecular mechanisms and to develop treatment strategies against diseases such as cancer and autoimmune diseases. To this end, computational biophysics studies including all-atom molecular dynamics simulations have provided useful insights; however, we still lack a basic understanding of an overall allosteric mechanism that results in conformational changes in the TCR and subsequent T-cell activation. Previous hydrogen-deuterium exchange and nuclear magnetic resonance studies provided clues regarding these molecular mechanisms, including global rigidification and allosteric effects on the constant domain of TCRs away from the pMHC interaction site. Here, we show that molecular dynamics simulations can be used to identify how this overall rigidification may be related to the allosteric communication within TCRs upon pMHC interaction via essential dynamics and nonbonded residue-residue interaction energy analyses. The residues taking part in the rigidification effect are highlighted with an intricate analysis on residue interaction changes, which lead to a detailed outline of the complex formation event. Our results indicate that residues of the Cβ domain of TCRs show significant differences in their nonbonded interactions upon complex formation. Moreover, the dynamic cross correlations between these residues are also increased, in line with their nonbonded interaction energy changes. Altogether, our approach may be valuable for elucidating intramolecular allosteric changes in the TCR structure upon pMHC interaction in molecular dynamics simulations.

In silico and in vitro assessment of androgen receptor antagonists

There is a growing concern for male reproductive health as studies suggest that there is a sharp increase in prostate cancer and other fertility related problems. Apart from lifestyle, pollutants are also known to negatively affect the reproductive system. In addition to many other compounds that have been shown to alter androgen signaling, several environmental pollutants are known to disrupt androgen signaling via binding to androgen receptor (AR) or indirectly affecting the androgen synthesis. We analyzed here the molecular mechanism of the interaction between the human AR Ligand Binding Domain (hAR-LBD) and two environmental pollutants, linuron (a herbicide) and procymidone (a pesticide), and compared with the steroid agonist dihydrotestosterone (DHT) and well-known hAR antagonists bicalutamide and enzalutamide. Using molecular docking and dynamics simulations, we showed that the co-activator interaction site of the hAR-LBD is disrupted in different ways by different ligands. Binding free energies of the ligands were also ordered in increasing order as follows: linuron, procymidone, DHT, bicalutamide, and enzalutamide. These data were confirmed by in vitro assays. Reporter assay with MDA-kb2 cells showed that linuron, procymidone, bicalutamide and enzalutamide can inhibit androgen mediated activation of luciferase activity. Gene expression analysis further showed that these compounds can inhibit the expression of prostate specific antigen (PSA) and microseminoprotein beta (MSMB) in prostate cell line LNCaP. Comparative analysis showed that procymidone is more potent than linuron in inhibiting AR activity. Furthermore, procymidone at 10 μM dose showed equivalent and higher activity to AR inhibitor enzalutamide and bicalutamide respectively.

FMODB: The World's First Database of Quantum Mechanical Calculations for Biomacromolecules Based on the Fragment Molecular Orbital Method

We developed the world's first web-based public database for the storage, management, and sharing of fragment molecular orbital (FMO) calculation data sets describing the complex interactions between biomacromolecules, named FMO Database (https://drugdesign.riken.jp/FMODB/). Each entry in the database contains relevant background information on how the data was compiled as well as the total energy of each molecular system and interfragment interaction energy (IFIE) and pair interaction energy decomposition analysis (PIEDA) values. Currently, the database contains more than 13 600 FMO calculation data sets, and a comprehensive search function implemented at the front-end. The procedure for selecting target proteins, preprocessing the experimental structures, construction of the database, and details of the database front-end were described. Then, we demonstrated a use of the FMODB by comparing IFIE value distributions of hydrogen bond, ion-pair, and XH/π interactions obtained by FMO method to those by molecular mechanics approach. From the comparison, the statistical analysis of the data provided standard reference values for the three types of interactions that will be useful for determining whether each interaction in a given system is relatively strong or weak compared to the interactions contained within the data in the FMODB. In the final part, we demonstrate the use of the database to examine the contribution of halogen atoms to the binding affinity between human cathepsin L and its inhibitors. We found that the electrostatic term derived by PIEDA greatly correlated with the binding affinities of the halogen containing cathepsin L inhibitors, indicating the importance of QM calculation for quantitative analysis of halogen interactions. Thus, the FMO calculation data in FMODB will be useful for conducting statistical analyses to drug discovery, for conducting molecular recognition studies in structural biology, and for other studies involving quantum mechanics-based interactions.

Shared Binding Mode of Perrottetinene and Tetrahydrocannabinol Diastereomers inside the CB1 Receptor May Incentivize Novel Medicinal Drug Design: Findings from an in Silico Assay

In recent years, therapeutic compounds derived from phytocannabinoids have brought renewed attention to the benefits they offer to ameliorate chronic disease symptoms. Among cannabinoids, tetrahydrocannabinol (THC) is a well-known component of the Cannabis plant, whose active principles have been studied through the years. Another psychoactive phytocannabinoid, derived from liverworts Radula, perrottetinene (PET), has created interest, especially as a pharmaceutical product and for its legal recreational use. Unfortunately, so far, the interaction mode of these compounds at the type 1 cannabinoid receptors (CB1R) binding site remains unknown, and no experimental three-dimensional structure in complex with THC or PET is available in the Protein Data Bank. Today, many computational methodologies can assist in this crusade and help unveil how these molecules bind, based on the already known pose of a structurally similar compound. In this work, we aim to elucidate the binding mode of THC and PET molecules in both cis and trans conformers, using a combination of several computational methodologies, including molecular docking, molecular dynamics, free energy calculations, and protein-energy network studies. We found that THC and PET interact similarly with the CB1R, in a different conformation depending on the considered diastereomer. We have observed that cis ligands adopted a half-chair conformation of the cycle ring containing the dimethyl group, assuming an axial or equatorial conformation producing a different induced fitting of the surrounding residues compared with trans ligands, with higher interaction energy than the trans conformer. For PET, we have seen that Trp-279 and Trp-356 have a marked influence on the binding. After binding, Trp-279 accommodates its side chain to better interact with the PET's terminal phenyl group, disturbing CB1R residues communication. The interaction with Trp-356 might impair the activation of CB1R and can influence the binding of PET as a partial agonist. Understanding the PET association with CB1R from a molecular perspective can offer a glimpse of preventing potential toxicological or recreational effects since it is an attractive lead for drug development with fewer side effects than trans-THC.

Simulations on the dual effects of flavonoids as suppressors of Aβ42 fibrillogenesis and destabilizers of mature fibrils

Structural studies of the aggregation inhibition of the amyloid-β peptide (Aβ) by different natural compounds are of the utmost importance due to their great potential as neuroprotective and therapeutic agents for Alzheimer’s disease. We provided the simulation of molecular dynamics for two different states of Aβ42, including “monomeric aggregation-prone state (APS)” and “U-shaped pentamers of amyloidogenic protofilament intermediates” in the absence and presence of polyphenolic flavonoids (Flvs, myricetin and morin) in order to verify the possible mechanism of Flvs fibrillogenesis suppression. Data showed that Flvs directly bind into Aβ42 species in both states of “monomeric APS β-sheets” and “pentameric amyloidogenic intermediates”. Binding of Flvs with amyloidogenic protofilament intermediates caused the attenuation of some inter-chains H-bonds, salt bridges, van der Waals and interpeptide interaction energies without interfering with their secondary β-sheets. Therefore, Flvs redirect oligomeric amyloidogenic intermediates into unstructured aggregates by significant disruption of the "steric zipper" motif of fibrils—pairs of self-complementary β-sheets—without changing the amount of β-sheets. It is while Flvs completely destruct the disadvantageous secondary β-sheets of monomeric APS conformers by converting them into coil/helix structures. It means that Flvs suppress the fibrillogenesis process of the monomeric APS structures by converting their β-sheets into proper soluble coil/helices structures. The different actions of Flvs in contact with two different states of Aβ conformers are related to high interaction tendency of Flvs with additional H-bonds for monomeric APS β-sheet, rather than oligomeric protofilaments. Linear interaction energy (LIE) analysis confirmed the strong binding of monomeric Aβ-Flvs with more negative ∆G_binding, rather than oligomeric Aβ-Flvs system. Therefore, atomic scale computational evaluation of Flvs actions demonstrated different dual functions of Flvs, concluded from the application of two different monomeric and pentameric Aβ42 systems. The distinct dual functions of Flvs are proposed as suppressing the aggregation by converting β-sheets of monomeric APS to proper soluble structures and disrupting the "steric zipper" fibril motifs of oligomeric intermediate by converting on-pathway into off-pathway. Taken together, our data propose that Flvs exert dual and more effective functions against monomeric APS (fibrillogenesis suppression) and remodel the Aβ aggregation pathway (fibril destabilization).

DSS1 allosterically regulates the conformation of the tower domain of BRCA2 that has dsDNA binding specificity for homologous recombination

DSS1 is an evolutionary conserved, small intrinsically disordered protein that regulates various cellular functions. Although several studies have elucidated the role of DSS1 in stabilizing BRCA2 and its importance in homologous recombination repair (HRR), yet the structural mechanism behind the stability and HRR remains elusive. In this study, using molecular dynamics simulation we show that DSS1 stabilizes linearly arranged DNA/DSS1 binding domains of BRCA2 with many native contacts. These contacts are absent in the complexes with two missense DSS1 mutants associated with germline breast cancer and somatic mouth carcinoma. Most importantly, our protein energy-based network models show DSS1 allosterically regulates the conformation of the distant tower domain of BRCA2 that has dsDNA binding specificity for HRR. We further postulate that the unique conformation of the tower domain with kinked-helices might be responsible for DNA strand invasion and initiation of HRR. Induced conformation of the tower domain by the kinked-helices is absent in the unbound BRCA2, as well as in the two mutant DSS1-BRCA2 complexes. This suggests that DSS1 allosterically regulates the tower domain conformations of BRCA2 that affects dsDNA binding, essential for HRR. Our results add a new dimension to the function of DSS1 and its role in regulating HRR.