Normal modes for predicting protein motions: a comprehensive database assessment and associated Web tool

Reused Protein Segments Linked to Functional Dynamics

Protein space is characterized by extensive recurrence, or "reuse," of parts, suggesting that new proteins and domains can evolve by mixing-and-matching of existing segments. From an evolutionary perspective, for a given combination to persist, the protein segments should presumably not only match geometrically but also dynamically communicate with each other to allow concerted motions that are key to function. Evidence from protein space supports the premise that domains indeed combine in this manner; we explore whether a similar phenomenon can be observed at the sub-domain level. To this end, we use Gaussian Network Models (GNMs) to calculate the so-called soft modes, or low-frequency modes of motion for a dataset of 150 protein domains. Modes of motion can be used to decompose a domain into segments of consecutive amino acids that we call "dynamic elements", each of which belongs to one of two parts that move in opposite senses. We find that, in many cases, the dynamic elements, detected based on GNM analysis, correspond to established "themes": Sub-domain-level segments that have been shown to recur in protein space, and which were detected in previous research using sequence similarity alone (i.e. completely independently of the GNM analysis). This statistically significant correlation hints at the importance of dynamics in evolution. Overall, the results are consistent with an evolutionary scenario where proteins have emerged from themes that need to match each other both geometrically and dynamically, e.g. to facilitate allosteric regulation.

AlphaFold2 Reveals Structural Patterns of Seasonal Haplotype Diversification in SARS-CoV-2 Nucleocapsid Protein Variants

The COVID-19 pandemic saw the emergence of various Variants of Concern (VOCs) that took the world by storm, often replacing the ones that preceded them. The characteristic mutant constellations of these VOCs increased viral transmissibility and infectivity. Their origin and evolution remain puzzling. With the help of data mining efforts and the GISAID database, a chronology of 22 haplotypes described viral evolution up until 23 July 2023. Since the three-dimensional atomic structures of proteins corresponding to the identified haplotypes are not available, ab initio methods were here utilized. Regions of intrinsic disorder proved to be important for viral evolution, as evidenced by the targeted change to the nucleocapsid (N) protein at the sequence, structure, and biochemical levels. The linker region of the N-protein, which binds to the RNA genome and self-oligomerizes for efficient genome packaging, was greatly impacted by mutations throughout the pandemic, followed by changes in structure and intrinsic disorder. Remarkably, VOC constellations acted co-operatively to balance the more extreme effects of individual haplotypes. Our strategy of mapping the dynamic evolutionary landscape of genetically linked mutations to the N-protein structure demonstrates the utility of ab initio modeling and deep learning tools for therapeutic intervention.

Mutations in Glycosyltransferases and Glycosidases: Implications for Associated Diseases

Glycosylation, a crucial and the most common post-translational modification, coordinates a multitude of biological functions through the attachment of glycans to proteins and lipids. This process, predominantly governed by glycosyltransferases (GTs) and glycoside hydrolases (GHs), decides not only biomolecular functionality but also protein stability and solubility. Mutations in these enzymes have been implicated in a spectrum of diseases, prompting critical research into the structural and functional consequences of such genetic variations. This study compiles an extensive dataset from ClinVar and UniProt, providing a nuanced analysis of 2603 variants within 343 GT and GH genes. We conduct thorough MTR score analyses for the proteins with the most documented variants using MTR3D-AF2 via AlphaFold2 (AlphaFold v2.2.4) predicted protein structure, with the analyses indicating that pathogenic mutations frequently correlate with Beta Bridge secondary structures. Further, the calculation of the solvent accessibility score and variant visualisation show that pathogenic mutations exhibit reduced solvent accessibility, suggesting the mutated residues are likely buried and their localisation is within protein cores. We also find that pathogenic variants are often found proximal to active and binding sites, which may interfere with substrate interactions. We also incorporate computational predictions to assess the impact of these mutations on protein function, utilising tools such as mCSM to predict the destabilisation effect of variants. By identifying these critical regions that are prone to disease-associated mutations, our study opens avenues for designing small molecules or biologics that can modulate enzyme function or compensate for the loss of stability due to these mutations.

Conformational dynamics of complement protease C1r inhibitor proteins from Lyme disease- and relapsing fever-causing spirochetes

Borrelial pathogens are vector-borne etiological agents known to cause Lyme disease, relapsing fever, and Borrelia miyamotoi disease. These spirochetes each encode several surface-localized lipoproteins that bind components of the human complement system to evade host immunity. One borrelial lipoprotein, BBK32, protects the Lyme disease spirochete from complement-mediated attack via an alpha helical C-terminal domain that interacts directly with the initiating protease of the classical complement pathway, C1r. In addition, the B. miyamotoi BBK32 orthologs FbpA and FbpB also inhibit C1r, albeit via distinct recognition mechanisms. The C1r-inhibitory activities of a third ortholog termed FbpC, which is found exclusively in relapsing fever-causing spirochetes, remains unknown. Here, we report the crystal structure of the C-terminal domain of Borrelia hermsii FbpC to a limiting resolution of 1.5 Å. We used surface plasmon resonance and assays of complement function to demonstrate that FbpC retains potent BBK32-like anticomplement activities. Based on the structure of FbpC, we hypothesized that conformational dynamics of the complement inhibitory domains of borrelial C1r inhibitors may differ. To test this, we utilized the crystal structures of the C-terminal domains of BBK32, FbpA, FbpB, and FbpC to carry out molecular dynamics simulations, which revealed borrelial C1r inhibitors adopt energetically favored open and closed states defined by two functionally critical regions. Taken together, these results advance our understanding of how protein dynamics contribute to the function of bacterial immune evasion proteins and reveal a surprising plasticity in the structures of borrelial C1r inhibitors.

In silico designing of a novel polyvalent multi-subunit peptide vaccine leveraging cross-immunity against human visceral and cutaneous leishmaniasis: an immunoinformatics-based approach

CONTEXT

Leishmaniasis is a group of vector-borne infectious diseases caused by over 20 pathogenic Leishmania species that are endemic in many tropical and subtropical countries. The emergence of drug-resistant strains, the adverse side effects of anti-Leishmania drugs, and the absence of a preventative vaccination strategy threaten the sensitive population. Recently, many groups of researchers have exploited the field of reverse vaccinology to develop vaccines, focusing chiefly on inducing immunity against either visceral or cutaneous leishmaniasis.

METHODS

This present work involves retrieving twelve experimentally validated leishmanial antigenic protein sequences from the UniProt database, followed by their antigenicity profiling employing ANTIGENpro and Vaxijen 2.0 servers. MHC-binding epitopes for the same were predicted using both NetCTL 1.2 and SYFPEITHI servers, while epitopes for B cell were computed using ABCpred and BepiPred 2.0 servers. The screened epitopes with significantly higher scores were utilized for designing the vaccine construct with appropriate linkers and natural adjuvant. The secondary and tertiary structures of the synthetic peptide were determined by conditional random fields, shallow neural networks, and profile-profile threading alignment with iterative structure assembly simulations, respectively. The 3-D vaccine model was validated through CASP10-tested refinement and the MolProbity web server. Molecular docking and multi-scale normal mode analysis simulation were performed to analyze the best vaccine-TLR complex. Finally, computational immune simulation findings revealed promising cellular and humoral immune responses, suggesting that the engineered chimeric peptide is a potential broad-spectrum vaccine against visceral and cutaneous leishmaniasis.

"Conformational dynamics of C1r inhibitor proteins from Lyme disease and relapsing fever spirochetes"

Borrelial pathogens are vector-borne etiological agents of Lyme disease, relapsing fever, and Borrelia miyamotoi disease. These spirochetes each encode several surface-localized lipoproteins that bind to components of the human complement system. BBK32 is an example of a borrelial lipoprotein that protects the Lyme disease spirochete from complement-mediated attack. The complement inhibitory activity of BBK32 arises from an alpha helical C-terminal domain that interacts directly with the initiating protease of the classical pathway, C1r. Borrelia miyamotoi spirochetes encode BBK32 orthologs termed FbpA and FbpB, and these proteins also inhibit C1r, albeit via distinct recognition mechanisms. The C1r-inhibitory activities of a third ortholog termed FbpC, which is found exclusively in relapsing fever spirochetes, remains unknown. Here we report the crystal structure of the C-terminal domain of B. hermsii FbpC to a limiting resolution of 1.5 Å. Surface plasmon resonance studies and assays of complement function demonstrate that FbpC retains potent BBK32-like anti-complement activities. Based on the structure of FbpC, we hypothesized that conformational dynamics of the complement inhibitory domains of borrelial C1r inhibitors may differ. To test this, we utilized the crystal structures of the C-terminal domains of BBK32, FbpA, FbpB, and FbpC to carry out 1 µs molecular dynamics simulations, which revealed borrelial C1r inhibitors adopt energetically favored open and closed states defined by two functionally critical regions. This study advances our understanding of how protein dynamics contribute to the function of bacterial immune evasion proteins and reveals a surprising plasticity in the structures of borrelial C1r inhibitors.

Evolutionary conservation of protein dynamics: insights from all-atom molecular dynamics simulations of 'peptidase' domain of Spt16

Protein function is encoded in its sequence, manifested in its three-dimensional structure, and facilitated by its dynamics. Studies have suggested that protein structures with higher sequence similarity could have more similar patterns of dynamics. However, such studies of protein dynamics within and across protein families typically rely on coarse-grained models, or approximate metrics like crystallographic B-factors. This study uses µs scale molecular dynamics (MD) simulations to explore the conservation of dynamics among homologs of ∼50 kDa N-terminal module of Spt16 (Spt16N). Spt16N from Saccharomyces cerevisiae (Sc-Spt16N) and three of its homologs with 30-40% sequence identities were available in the PDB. To make our data-set more comprehensive, the crystal structure of an additional homolog (62% sequence identity with Sc-Spt16N) was solved at 1.7 Å resolution. Cumulative MD simulations of 6 µs were carried out on these Spt16N structures and on two additional protein structures with varying degrees of similarity to it. The simulations revealed that correlation in patterns of backbone fluctuations vary linearly with sequence identity. This trend could not be inferred using crystallographic B-factors. Further, normal mode analysis suggested a similar pattern of inter-domain (inter-lobe) motions not only among Spt16N homologs, but also in the M24 peptidase structure. On the other hand, MD simulation results highlighted conserved motions that were found unique for Spt16N protein, this along with electrostatics trends shed light on functional aspects of Spt16N.Communicated by Ramaswamy H. Sarma.

The "violin model": Looking at community networks for dynamic allostery

Allosteric regulation of proteins continues to be an engaging research topic for the scientific community. Models describing allosteric communication have evolved from focusing on conformation-based descriptors of protein structural changes to appreciating the role of internal protein dynamics as a mediator of allostery. Here, we explain a "violin model" for allostery as a contemporary method for approaching the Cooper-Dryden model based on redistribution of protein thermal fluctuations. Based on graph theory, the violin model makes use of community network analysis to functionally cluster correlated protein motions obtained from molecular dynamics simulations. This Review provides the theory and workflow of the methodology and explains the application of violin model to unravel the workings of protein kinase A.

Human VH-based chimeric antigen receptor T cells targeting glypican 3 eliminate tumors in preclinical models of HCC

BACKGROUND AND AIMS

Efficacy of chimeric antigen receptor (CAR) T cells for treating solid tumors, including HCC, remains a challenge. Nanobodies are emerging building blocks of CAR T cells due to their small size and high expression. Membrane proximal sites have been shown as attractive epitopes of CAR T cells. However, current CAR formats are not tailored toward nanobodies or targeting membrane distal epitopes.

APPROACH AND RESULTS

Using hYP7 Fv (membrane proximal) and HN3 VH nanobody (membrane distal) as GPC3 targeting elements, we sought to determine how hinges and transmembrane portions of varying structures and sizes affect CAR T-cell function. We generated multiple permutations of CAR T cells containing CD8, CD28, IgG4, and Fc domains. We show that engineered HN3 CAR T cells can be improved by 2 independent, synergistic changes in the hinge and transmembrane domains. The T cells expressing the HN3 CAR which contains the hinge region of IgG4 and the CD28 transmembrane domain (HN3-IgG4H-CD28TM) exhibited high cytotoxic activity and caused complete HCC tumor eradication in immunodeficient mice. HN3-IgG4H-CD28TM CAR T cells were enriched for cytotoxic-memory CD8+ T cells and NFAT signals, and reduced β catenin levels in HCC cells.

CONCLUSION

Our findings indicate that altering the hinge and transmembrane domains of a nanobody-based CAR targeting a distal GPC3 epitope, in contrast to a membrane proximal epitope, lead to robust T-cell signaling and induce swift and durable eradication of HCC tumors.

Molecular simulation unravels the amyloidogenic misfolding of nascent ApoA1 protein, driven by deleterious point mutations occurring in between 170-178 hotspot region

Protein ApoA1 is extensively studied for its role in lipid metabolism. Its seedy dark side of amyloid formulation remains relatively understudied yet. Due to genetic mutations, the protein pathologically misshapes into its amyloid form that gets accumulated in various organs, including the heart. To contrive effective therapeutics against this debilitating congenital disorder, it is imperative to comprehend the structural ramifications induced by mutations in APoA1's dynamic conformation. Till now, several point mutations have been implicated in ApoA1's amyloidosis, although only a handful has been examined considerably. Especially, the single nucleotide polymorphisms (SNPs) that occur in-between 170-178 mutation hotspot site of APoA1 needs to be investigated, since most of them are culpable of amyloid deposition in the heart. To that effect, in the present study, we have computationally quantified and studied the ApoA1's biomolecular modifications fostered by SNPs in the 170-178 mutation hotspot. Findings from discrete molecular dynamics simulation studies indicate that the SNPs have noticeably steered the ApoA1's behaviour from its native structural dynamics. Analysis of protein's secondary structural changes exhibits a considerable change upon mutations. Further, subjecting the protein structures to simulated thermal denaturation shows increased resistance to denaturation among mutants when compared to native. Further, normal mode analysis of protein's dynamic motion also shows discrepancy in its dynamic structural change upon SNP. These structural digressions induced by SNPs can very well be the biomolecular incendiary that drives ApoA1 into its amyloidogenesis. And, understanding these structural modifications initiates a better understanding of SNP's amyloidogenic pathology on APoA1.Communicated by Ramaswamy H. Sarma.

Molecular mechanism of ATP and RNA binding to Zika virus NS3 helicase and identification of repurposed drugs using molecular dynamics simulations

Congenital Zika virus syndrome has caused a public health emergency of international concern. So far, there are no drugs available to prevent or treat the infection caused by Zika virus. The Zika virus NS3 helicase is a potential protein target for drug discovery due to its vital role in viral genome replication. NS3 helicase unwinds the viral RNA to enable the reproduction of the viral genome by the NS5 protein. NS3 helicase has two crucial binding sites; the ATP binding site and the RNA binding site. We used molecular docking and molecular dynamics (MD) simulations to study the structural behavior of Zika virus NS3 helicase in its apo form and in the presence of ATP, single-stranded RNA, and both ATP-RNA to understand their potential implications in NS3 helicase activity. Further, we have carried out virtual screening of FDA approved drugs, followed by molecular docking to identify the ATP-competitive hit molecules as probable Zika virus NS3 helicase inhibitors. The MD simulations trajectories were analyzed using normal mode analysis and principal component analysis that reveals fluctuations in the R-loop. These findings aid in understanding the molecular mechanisms of the simultaneous binding of ATP and RNA, and guide the design and discovery of new inhibitors of the Zika virus NS3 helicase as a promising drug target to treat the Zika virus infection. Communicated by Ramaswamy H. Sarma.

Computational methods for the analysis of solution small-angle X-ray scattering of biomolecules: ATSAS

The ATSAS software suite provides a comprehensive set of programs for the processing, analysis and modeling of small-angle scattering data, tailored for but not limited to data acquired on biological macromolecules. In this review the major components and developments in the ATSAS package are described, with a focus on user driven application. Data reduction, analysis and modeling approaches and strategies will be introduced and discussed. At the time of writing the latest package, ATSAS 3.1, is freely available for academic users at: https://www.embl-hamburg.de/biosaxs/software.html.

Computational studies on the design of NCI natural products as inhibitors to SARS-CoV-2 main protease

The pandemic coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in more than 5 million deaths globally. Currently there are no effective drugs available to treat COVID-19. The viral protease replication can be blocked by the inhibition of main protease that is encoded in polyprotein 1a and is therefore a potential protein target for drug discovery. We have carried out virtual screening of NCI natural compounds followed by molecular docking in order to identify hit molecules as probable SARS-CoV-2 main protease inhibitors. The molecular dynamics (MD) simulations of apo form in complex with N3, α-ketoamide and NCI natural products was used to validate the screened compounds. The MD simulations trajectories were analyzed using normal mode analysis and principal component analysis revealing dynamical nature of the protein. These findings aid in understanding the binding of natural products and molecular mechanisms of SARS-CoV-2 main protease inhibition.Communicated by Ramaswamy H. Sarma.

An integrated in silico based subtractive genomics and reverse vaccinology approach for the identification of novel vaccine candidate and chimeric vaccine against XDR Salmonella typhi H58

Salmonella typhi is notorious for causing enteric fever which is also known as typhoid fever. It emerged as an extreme drug resistant strain that requires urgent attention to prevent its global spread. Statistically, about 11-17 million typhoid illnesses are reported worldwide annually. The only alternative approach for the control of this illness is proper vaccination. However, available typhoid vaccine has certain limitations such as poor long-term efficacy, and non-recommendation for below 6 years children, which opens the avenues for designing new vaccines to overcome such limitations. Computational-based reverse vaccinology along with subtractive genomics analysis is one of the robust approaches used for the prioritization of vaccine candidates through direct screening of genome sequence assemblies. In the current study, we have successfully designed a peptide-based novel antigen chimeric vaccine candidate against the XDR strain of S. typhi H58. The pipeline revealed four peptides from WP_001176621.1 i.e., peptidoglycan-associated lipoprotein Pal and two peptides from WP_000747548.1 i.e., OmpA family lipoprotein as promising target for the induction of immune response against S. typhi. The six epitopes from both proteins were found as immunogenic, antigenic, virulent, highly conserved, nontoxic, and non-allergenic among whole Salmonella H58 proteome. Furthermore, the binding interaction between a chimeric vaccine and human population alleles was unveiled through structure-based studies. So far, these proteins have never been characterized as vaccine targets against S. typhi. The current study proposed that construct V2 could be a significant vaccine candidate against S. typhi H58. However, to ascertain this, future experimental holistic studies are recommended as follow-up.

Dynamics-Evolution Correspondence in Protein Structures

The genotype-phenotype mapping of proteins is a fundamental question in structural biology. In this Letter, with the analysis of a large dataset of proteins from hundreds of protein families, we quantitatively demonstrate the correlations between the noise-induced protein dynamics and mutation-induced variations of native structures, indicating the dynamics-evolution correspondence of proteins. Based on the investigations of the linear responses of native proteins, the origin of such a correspondence is elucidated. It is essential that the noise- and mutation-induced deformations of the proteins are restricted on a common low-dimensional subspace, as confirmed from the data. These results suggest an evolutionary mechanism of the proteins gaining both dynamical flexibility and evolutionary structural variability.

ATSAS 3.0: expanded functionality and new tools for small-angle scattering data analysis

The ATSAS software suite encompasses a number of programs for the processing, visualization, analysis and modelling of small-angle scattering data, with a focus on the data measured from biological macromolecules. Here, new developments in the ATSAS 3.0 package are described. They include IMSIM, for simulating isotropic 2D scattering patterns; IMOP, to perform operations on 2D images and masks; DATRESAMPLE, a method for variance estimation of structural invariants through parametric resampling; DATFT, which computes the pair distance distribution function by a direct Fourier transform of the scattering data; PDDFFIT, to compute the scattering data from a pair distance distribution function, allowing comparison with the experimental data; a new module in DATMW for Bayesian consensus-based concentration-independent molecular weight estimation; DATMIF, an ab initio shape analysis method that optimizes the search model directly against the scattering data; DAMEMB, an application to set up the initial search volume for multiphase modelling of membrane proteins; ELLLIP, to perform quasi-atomistic modelling of liposomes with elliptical shapes; NMATOR, which models conformational changes in nucleic acid structures through normal mode analysis in torsion angle space; DAMMIX, which reconstructs the shape of an unknown intermediate in an evolving system; and LIPMIX and BILMIX, for modelling multilamellar and asymmetric lipid vesicles, respectively. In addition, technical updates were deployed to facilitate maintainability of the package, which include porting the PRIMUS graphical interface to Qt5, updating SASpy - a PyMOL plugin to run a subset of ATSAS tools - to be both Python 2 and 3 compatible, and adding utilities to facilitate mmCIF compatibility in future ATSAS releases. All these features are implemented in ATSAS 3.0, freely available for academic users at https://www.embl-hamburg.de/biosaxs/software.html.

Dynamic plasticity of the lipid antigen-binding site of CD1d is crucially favoured by acidic pH and helper proteins

CD1 molecules present lipid antigens for recognition by T-cell receptors (TCRs). Although a reasonably detailed picture of the CD1-lipid-TCR interaction exists, the initial steps regarding lipid loading onto and exchange between CD1 proteins remain elusive. The hydrophobic nature of lipids and the fact that CD1 molecules are unable to extract lipids from membranes raise the need for the assistance of helper proteins in lipid trafficking. However, the experimental study of this traffic in the endosomal compartments at which it occurs is so challenging that computational studies can help provide mechanistic insight into the associated processes. Here we present a multifaceted computational approach to obtain dynamic structural data on the human CD1d isotype. Conformational dynamics analysis shows an intrinsic flexibility associated with the protein architecture. Electrostatic properties together with molecular dynamics results for CD1d complexes with several lipids and helper proteins unravel the high dynamic plasticity of the antigen-binding site that is crucially favoured by acidic pH and the presence of helper proteins.

Identification of a Pivotal Residue for Determining the Block Structure-Forming Properties of Alginate C-5 Epimerases

Alginate is a linear copolymer composed of 1→4 linked β-d-mannuronic acid (M) and its epimer α-l-guluronic acid (G). The polysaccharide is first produced as homopolymeric mannuronan and subsequently, at the polymer level, C-5 epimerases convert M residues to G residues. The bacterium Azotobacter vinelandii encodes a family of seven secreted and calcium ion-dependent mannuronan C-5 epimerases (AlgE1-AlgE7). These epimerases consist of two types of structural modules: the A-modules, which contain the catalytic site, and the R-modules, which influence activity through substrate and calcium binding. In this study, we rationally designed new hybrid mannuronan C-5 epimerases constituting the A-module from AlgE6 and the R-module from AlgE4. This led to a better understanding of the molecular mechanism determining differences in MG- and GG-block-forming properties of the enzymes. A long loop with either tyrosine or phenylalanine extruding from the β-helix of the enzyme proved essential in defining the final alginate block structure, probably by affecting substrate binding. Normal mode analysis of the A-module from AlgE6 supports the results.

Long-range correlation in protein dynamics: Confirmation by structural data and normal mode analysis

Proteins in cellular environments are highly susceptible. Local perturbations to any residue can be sensed by other spatially distal residues in the protein molecule, showing long-range correlations in the native dynamics of proteins. The long-range correlations of proteins contribute to many biological processes such as allostery, catalysis, and transportation. Revealing the structural origin of such long-range correlations is of great significance in understanding the design principle of biologically functional proteins. In this work, based on a large set of globular proteins determined by X-ray crystallography, by conducting normal mode analysis with the elastic network models, we demonstrate that such long-range correlations are encoded in the native topology of the proteins. To understand how native topology defines the structure and the dynamics of the proteins, we conduct scaling analysis on the size dependence of the slowest vibration mode, average path length, and modularity. Our results quantitatively describe how native proteins balance between order and disorder, showing both dense packing and fractal topology. It is suggested that the balance between stability and flexibility acts as an evolutionary constraint for proteins at different sizes. Overall, our result not only gives a new perspective bridging the protein structure and its dynamics but also reveals a universal principle in the evolution of proteins at all different sizes.

The long-range correlated fluctuations are closely related to many biological processes of the proteins, such as catalysis, ligand binding, biomolecular recognition, and transportation. In this paper, we elucidate the structural origin of the long-range correlation and describe how native contact topology defines the slow-mode dynamics of the native proteins. Our result suggests an evolutionary constraint for proteins at different sizes, which may shed light on solving many biophysical problems such as structure prediction, multi-scale molecular simulations, and the design of molecular machines. Moreover, in statistical physics, as the long-range correlations are notable signs of the critical point, unveiling the origin of such criticality can extend our understanding of the organizing principle of a large variety of complex systems.

LARMD: integration of bioinformatic resources to profile ligand-driven protein dynamics with a case on the activation of estrogen receptor

Protein dynamics is central to all biological processes, including signal transduction, cellular regulation and biological catalysis. Among them, in-depth exploration of ligand-driven protein dynamics contributes to an optimal understanding of protein function, which is particularly relevant to drug discovery. Hence, a wide range of computational tools have been designed to investigate the important dynamic information in proteins. However, performing and analyzing protein dynamics is still challenging due to the complicated operation steps, giving rise to great difficulty, especially for nonexperts. Moreover, there is a lack of web protocol to provide online facility to investigate and visualize ligand-driven protein dynamics. To this end, in this study, we integrated several bioinformatic tools to develop a protocol, named Ligand and Receptor Molecular Dynamics (LARMD, http://chemyang.ccnu.edu.cn/ccb/server/LARMD/ and http://agroda.gzu.edu.cn:9999/ccb/server/LARMD/), for profiling ligand-driven protein dynamics. To be specific, estrogen receptor (ER) was used as a case to reveal ERβ-selective mechanism, which plays a vital role in the treatment of inflammatory diseases and many types of cancers in clinical practice. Two different residues (Ile373/Met421 and Met336/Leu384) in the pocket of ERβ/ERα were the significant determinants for selectivity, especially Met336 of ERβ. The helix H8, helix H11 and H7-H8 loop influenced the migration of selective agonist (WAY-244). These computational results were consistent with the experimental results. Therefore, LARMD provides a user-friendly online protocol to study the dynamic property of protein and to design new ligand or site-directed mutagenesis.

Substrate recognition by the Pseudomonas aeruginosa EF-Tu-modifying methyltransferase EftM

The opportunistic bacterial pathogen Pseudomonas aeruginosa is a leading cause of serious infections in individuals with cystic fibrosis, compromised immune systems, or severe burns. P. aeruginosa adhesion to host epithelial cells is enhanced by surface-exposed translation elongation factor EF-Tu carrying a Lys-5 trimethylation, incorporated by the methyltransferase EftM. Thus, the EF-Tu modification by EftM may represent a target to prevent P. aeruginosa infections in vulnerable individuals. Here, we extend our understanding of EftM activity by defining the molecular mechanism by which it recognizes EF-Tu. Acting on the observation that EftM can bind to EF-Tu lacking its N-terminal peptide (encompassing the Lys-5 target site), we generated an EftM homology model and used it in protein/protein docking studies to predict EftM/EF-Tu interactions. Using site-directed mutagenesis of residues in both proteins, coupled with binding and methyltransferase activity assays, we experimentally validated the predicted protein/protein interface. We also show that EftM cannot methylate the isolated N-terminal EF-Tu peptide and that binding-induced conformational changes in EftM are likely needed to enable placement of the first 5-6 amino acids of EF-Tu into a conserved peptide-binding channel in EftM. In this channel, a group of residues that are highly conserved in EftM proteins position the N-terminal sequence to facilitate Lys-5 modification. Our findings reveal that EftM employs molecular strategies for substrate recognition common among both class I (Rossmann fold) and class II (SET domain) methyltransferases and pave the way for studies seeking a deeper understanding of EftM's mechanism of action on EF-Tu.

Negative Thermophoretic Force in the Strong Coupling Regime

Negative thermophoresis (a particle moving up the temperature gradient) is a somewhat counterintuitive phenomenon which has thus far eluded a simple thermostatistical description. The purpose of this Letter is to show that a thermodynamic framework based on the formulation of a Hamiltonian of mean force has the descriptive ability to capture this interesting and elusive phenomenon in an unusually elegant and straightforward fashion. We propose a mechanism that describes the advent of a thermophoretic force acting from cold to hot on systems that are strongly coupled to a nonisothermal heat bath. When a system is strongly coupled to the heat bath, the system's eigenenergies E_{j} become effectively temperature dependent. This adjustment of the energy levels allows the system to take heat from the environment, +d⟨E_{j}⟩, and return it as work, -d⟨TdE_{j}/dT⟩. This effect can make the temperature dependence of the effective energy profile nonmonotonic. As a result, particles may experience a force in either direction depending on the temperature.

Effects of Lid 1 Mutagenesis on Lid Displacement, Catalytic Performances and Thermostability of Cold-active Pseudomonas AMS8 Lipase in Toluene

Pseudomonas fluorescens AMS8 lipase lid 1 structure is rigid and holds unclear roles due to the absence of solvent-interactions. Lid 1 region was stabilized by 17 hydrogen bond linkages and displayed lower mean hydrophobicity (0.596) compared to MIS38 lipase. Mutating lid 1 residues, Thr-52 and Gly-55 to aromatic hydrophobic-polar tyrosine would churned more side-chain interactions between lid 1 and water or toluene. This study revealed that T52Y leads G55Y and its recombinant towards achieving higher solvent-accessible surface area and longer half-life at 25 to 37 °C in 0.5% (v/v) toluene. T52Y also exhibited better substrate affinity with long-chain carbon substrate in aqueous media. The affinity for pNP palmitate, laurate and caprylate increased in 0.5% (v/v) toluene in recombinant AMS8, but the affinity in similar substrates was substantially declined in lid 1 mutated lipases. Regarding enzyme efficiency, the recombinant AMS8 lipase displayed highest value of k_cat/K_m in 0.5% (v/v) toluene, mainly with pNPC. In both hydrolysis reactions with 0% and 0.5% (v/v) toluene, the enzyme efficiency of G55Y was found higher than T52Y for pNPL and pNPP. At 0.5% (v/v) toluene, both mutants showed reductions in activation energy and enthalpy values as temperature increased from 25 to 35 °C, displaying better catalytic functions. Only T52Y exhibited increase in entropy values at 0.5% (v/v) toluene indicating structure stability. As a conclusion, Thr-52 and Gly-55 are important residues for lid 1 stability as their existence helps to retain the geometrical structure of alpha-helix and connecting hinge.

Progress in Allosteric Database

An allosteric mechanism refers to the biological regulation process wherein macromolecules propagate the effect of ligand binding at one site to a spatially distant orthosteric locus, thus affecting activity. The theory has remained a trending topic in biology research for over 50 years, since the understanding of allostery is fundamental for gleaning numerous biological processes and developing new drug therapies. In the past two decades, the allosteric paradigm has evolved into more descriptive models, with ever-expanding amounts of experimental data pertaining to newly identified allosteric molecules. The AlloSteric Database (ASD, accessible at http://mdl.shsmu.edu.cn/ASD ), which is a comprehensive knowledge repository, has provided the public with integrated information encompassing allosteric proteins, modulators, sites, pathways, and networks to investigate allostery since 2009. In this chapter, we introduce the history and usage of the ASD and give attention to specific applications that have benefited from the ASD.

Why the Energy Landscape of Barnase Is Hierarchical

We have used NMR and computational methods to characterize the dynamics of the ribonuclease barnase over a wide range of timescales in free and inhibitor-bound states. Using temperature- and denaturant-dependent measurements of chemical shift, we show that barnase undergoes frequent and highly populated hinge bending. Using relaxation dispersion, we characterize a slower and less populated motion with a rate of 750 ± 200 s⁻¹, involving residues around the lip of the active site, which occurs in both free and bound states and therefore suggests conformational selection. Normal mode calculations characterize correlated hinge bending motions on a very rapid timescale. These three measurements are combined with previous measurements and molecular dynamics calculations on barnase to characterize its dynamic landscape on timescales from picoseconds to milliseconds and length scales from 0.1 to 2.5 nm. We show that barnase has two different large-scale fluctuations: one on a timescale of 10⁻⁹−10⁻⁶ s that has no free energy barrier and is a hinge bending that is determined by the architecture of the protein; and one on a timescale of milliseconds (i.e., 750 s⁻¹) that has a significant free energy barrier and starts from a partially hinge-bent conformation. These two motions can be described as hierarchical, in that the more highly populated faster motion provides a platform for the slower (less probable) motion. The implications are discussed. The use of temperature and denaturant is suggested as a simple and general way to characterize motions on the intermediate ns-μs timescale.

Flexible Peptide Linkers Enhance the Antimicrobial Activity of Surface-Immobilized Bacteriolytic Enzymes

Chemical linkers are frequently used in enzyme immobilization to improve enzyme flexibility and activity, whereas peptide linkers, although ubiquitous in protein engineering, are much less explored in enzyme immobilization. Here, we report peptide-linker-assisted noncovalent immobilization of the bacteriolytic enzyme lysostaphin (Lst) to generate anti- Staphylococcus aureus surfaces. Lst was immobilized through affinity tags onto a silica surface (glass slides) and nickel nitrilotriacetic acid (NiNTA) agarose beads via silica-binding peptides (SiBPs) or a hexahistidine tag (His-tag) fused at the C-terminus of Lst, respectively. By inserting specific peptide linkers upstream of the SiBP or His-tag, the immobilized enzymes killed >99.5% of S. aureus ATCC 6538 cells (10⁸ CFU/mL) within 3 h in buffer and could be reused multiple times without significant loss of activity. In contrast, immobilized Lst without a peptide linker was less active/stable. Molecular modeling of Lst-linker-affinity tag constructs illustrated that the presence of the peptide linkers enhanced the molecular flexibility of the proximal Lst binding domain, which interacts with the bacterial substrate, and such increased flexibility correlated with increased antimicrobial activity. We further show that Lst immobilized onto NiNTA beads retained the ability to kill ∼99% of a 10⁸ CFU/mL microbial challenge even in the presence of 1% of a commercial anionic surfactant, C12-14 alcohol EO 3:1 sodium sulfate, when the Lst construct contained a decapeptide linker containing glycine, serine, and alanine residues. This linker-assisted immobilization strategy could be extended to an unrelated lytic enzyme, the endolysin PlyPH, to target Bacillus anthracis Sterne cells either in buffer or in the presence of anionic surfactants. Our approach, therefore, provides a facile route to the use of antimicrobial enzymes on surfaces.

Molecular Modeling Applied to Nucleic Acid-Based Molecule Development

Molecular modeling by means of docking and molecular dynamics (MD) has become an integral part of early drug discovery projects, enabling the screening and enrichment of large libraries of small molecules. In the past decades, special emphasis was drawn to nucleic acid (NA)-based molecules in the fields of therapy, diagnosis, and drug delivery. Research has increased dramatically with the advent of the SELEX (systematic evolution of ligands by exponential enrichment) technique, which results in single-stranded DNA or RNA sequences that bind with high affinity and specificity to their targets. Herein, we discuss the role and contribution of docking and MD to the development and optimization of new nucleic acid-based molecules. This review focuses on the different approaches currently available for molecular modeling applied to NA interaction with proteins. We discuss topics ranging from structure prediction to docking and MD, highlighting their main advantages and limitations and the influence of flexibility on their calculations.

PLA2-like proteins myotoxic mechanism: a dynamic model description

Phospholipase A₂-like (PLA₂-like) proteins contribute to the development of muscle necrosis in Viperidae snake bites and are not efficiently neutralized by current antivenom treatments. The toxic mechanisms of PLA₂-like proteins are devoid of catalytic activity and not yet fully understood, although structural and functional experiments suggest a dimeric assembly and that the C-terminal residues are essential to myotoxicity. Herein, we characterized the functional mechanism of bothropic PLA₂-like structures related to global and local measurements using the available models in the Protein Data Bank and normal mode molecular dynamics (NM-MD). Those measurements include: (i) new geometric descriptions between their monomers, based on Euler angles; (ii) characterizations of canonical and non-canonical conformations of the C-terminal residues; (iii) accessibility of the hydrophobic channel; (iv) inspection of ligands; and (v) distance of clustered residues to toxin interface of interaction. Thus, we described the allosteric activation of PLA₂-like proteins and hypothesized that the natural movement between monomers, calculated from NM-MD, is related to their membrane disruption mechanism, which is important for future studies of the inhibition process. These methods and strategies can be applied to other proteins to help understand their mechanisms of action.

Normal mode analysis as a method to derive protein dynamics information from the Protein Data Bank

Normal mode analysis (NMA) can facilitate quick and systematic investigation of protein dynamics using data from the Protein Data Bank (PDB). We developed an elastic network model-based NMA program using dihedral angles as independent variables. Compared to the NMA programs that use Cartesian coordinates as independent variables, key attributes of the proposed program are as follows: (1) chain connectivity related to the folding pattern of a polypeptide chain is naturally embedded in the model; (2) the full-atom system is acceptable, and owing to a considerably smaller number of independent variables, the PDB data can be used without further manipulation; (3) the number of variables can be easily reduced by some of the rotatable dihedral angles; (4) the PDB data for any molecule besides proteins can be considered without coarse-graining; and (5) individual motions of constituent subunits and ligand molecules can be easily decomposed into external and internal motions to examine their mutual and intrinsic motions. Its performance is illustrated with an example of a DNA-binding allosteric protein, a catabolite activator protein. In particular, the focus is on the conformational change upon cAMP and DNA binding, and on the communication between their binding sites remotely located from each other. In this illustration, NMA creates a vivid picture of the protein dynamics at various levels of the structures, i.e., atoms, residues, secondary structures, domains, subunits, and the complete system, including DNA and cAMP. Comparative studies of the specific protein in different states, e.g., apo- and holo-conformations, and free and complexed configurations, provide useful information for studying structurally and functionally important aspects of the protein.

Structural analyses of the Haemophilus influenzae peptidoglycan synthase activator LpoA suggest multiple conformations in solution

In many Gram-negative bacteria, the peptidoglycan synthase PBP1A requires the outer membrane lipoprotein LpoA for constructing a functional peptidoglycan required for bacterial viability. Previously, we have shown that the C-terminal domain of Haemophilus influenzae LpoA (HiLpoA) has a highly conserved, putative substrate-binding cleft between two α/β lobes. Here, we report a 2.0 Å resolution crystal structure of the HiLpoA N-terminal domain. Two subdomains contain tetratricopeptide-like motifs that form a concave groove, but their relative orientation differs by ∼45° from that observed in an NMR structure of the Escherichia coli LpoA N domain. We also determined three 2.0-2.8 Å resolution crystal structures containing four independent full-length HiLpoA molecules. In contrast to an elongated model previously suggested for E. coli LpoA, each HiLpoA formed a U-shaped structure with a different C-domain orientation. This resulted from both N-domain twisting and rotation of the C domain (up to 30°) at the end of the relatively immobile interdomain linker. Moreover, a previously predicted hinge between the lobes of the LpoA C domain exhibited variations of up to 12°. Small-angle X-ray scattering data revealed excellent agreement with a model calculated by normal mode analysis from one of the full-length HiLpoA molecules but even better agreement with an ensemble of this molecule and two of the partially extended normal mode analysis-predicted models. The different LpoA structures helped explain how an outer membrane-anchored LpoA can either withdraw from or extend toward the inner membrane-bound PBP1A through peptidoglycan gaps and hence regulate the synthesis of peptidoglycan necessary for bacterial viability.

Deciphering conformational transitions of proteins by small angle X-ray scattering and normal mode analysis

Structural flexibility and conformational rearrangements are often related to important functions of biological macromolecules, but the experimental characterization of such transitions with high-resolution techniques is challenging. At a lower resolution, small angle X-ray scattering (SAXS) can be used to obtain information on biomolecular shapes and transitions in solution. Here, we present SREFLEX, a hybrid modeling approach that uses normal mode analysis (NMA) to explore the conformational space of high-resolution models and refine the structure guided by the agreement with the experimental SAXS data. The method starts from a given conformation of the protein (which does not agree with the SAXS data). The structure is partitioned into pseudo-domains either using structural classification databases or automatically from the protein dynamics as predicted by the NMA. The algorithm proceeds hierarchically employing NMA to first probe large rearrangements and progresses into smaller and more localized movements. At the large rearrangements stage the pseudo-domains stay as rigid bodies allowing one to avoid structural disruptions inherent to the earlier NMA-based algorithms. To validate the approach, we compiled a representative benchmark set of 88 conformational states known experimentally at high resolution. The performance of the algorithm is demonstrated in the simulated data on the benchmark set and also in a number of experimental examples. SREFLEX is included into the ATSAS program package freely available to the academic users, both for download and in the on-line mode.

Applications of Normal Mode Analysis Methods in Computational Protein Design

Recent advances in coarse-grained normal mode analysis methods make possible the large-scale prediction of the effect of mutations on protein stability and dynamics as well as the generation of biologically relevant conformational ensembles. Given the interplay between flexibility and enzymatic activity, the combined analysis of stability and dynamics using the Elastic Network Contact Model (ENCoM) method has ample applications in protein engineering in industrial and medical applications such as in computational antibody design. Here, we present a detailed tutorial on how to perform such calculations using ENCoM.

Theory of Acoustic Raman Modes in Proteins

We present a theoretical analysis that associates the resonances of extraordinary acoustic Raman (EAR) spectroscopy [Wheaton et al., Nat. Photonics 9, 68 (2015)] with the collective modes of proteins. The theory uses the anisotropic elastic network model to find the protein acoustic modes, and calculates Raman intensity by treating the protein as a polarizable ellipsoid. Reasonable agreement is found between EAR spectra and our theory. Protein acoustic modes have been extensively studied theoretically to assess the role they play in protein function; this result suggests EAR spectroscopy as a new experimental tool for studies of protein acoustic modes.

Regulatory network of the allosteric ATP inhibition of E. coli phosphofructokinase-2 studied by hybrid dimers

We have proposed an allosteric ATP inhibition mechanism of Pfk-2 determining the structure of different forms of the enzyme together with a kinetic enzyme analysis. Here we complement the mechanism by using hybrid oligomers of the homodimeric enzyme to get insights about the allosteric communication pathways between the same sites or different ones located in different subunits. Kinetic analysis of the hybrid enzymes indicate that homotropic interactions between allosteric sites for ATP or between substrate sites for fructose-6-P have a minor effect on the enzymatic inhibition induced by ATP. In fact, the sigmoid response for fructose-6-P observed at elevated ATP concentrations can be eliminated even though the enzymatic inhibition is still operative. Nevertheless, leverage coupling analysis supports heterotropic interactions between the allosteric ATP and fructose-6-P binding occurring between and within each subunit.

Characterization and Prediction of Protein Flexibility Based on Structural Alphabets

Motivation. To assist efforts in determining and exploring the functional properties of proteins, it is desirable to characterize and predict protein flexibilities. Results. In this study, the conformational entropy is used as an indicator of the protein flexibility. We first explore whether the conformational change can capture the protein flexibility. The well-defined decoy structures are converted into one-dimensional series of letters from a structural alphabet. Four different structure alphabets, including the secondary structure in 3-class and 8-class, the PB structure alphabet (16-letter), and the DW structure alphabet (28-letter), are investigated. The conformational entropy is then calculated from the structure alphabet letters. Some of the proteins show high correlation between the conformation entropy and the protein flexibility. We then predict the protein flexibility from basic amino acid sequence. The local structures are predicted by the dual-layer model and the conformational entropy of the predicted class distribution is then calculated. The results show that the conformational entropy is a good indicator of the protein flexibility, but false positives remain a problem. The DW structure alphabet performs the best, which means that more subtle local structures can be captured by large number of structure alphabet letters. Overall this study provides a simple and efficient method for the characterization and prediction of the protein flexibility.

Structural Plasticity of Cholesteryl Ester Transfer Protein Assists the Lipid Transfer Activity

Cholesteryl ester transfer protein (CETP) mediates the transfer of cholesteryl esters (CEs) and triglycerides between different lipoproteins. Recent studies have shown that blocking the function of CETP can increase the level of HDL cholesterol in blood plasma and suppress the risk of cardiovascular disease. Hence, understanding the structure, dynamics, and mechanism by which CETP transfers the neutral lipids has received tremendous attention in last decade. Although the recent crystal structure has provided direct evidence of the existence of strongly bound CEs in the CETP core, very little is known about the mechanism of CE/triglyceride transfer by CETP. In this study, we explore the large scale dynamics of CETP by means of multimicrosecond molecular dynamics simulations and normal mode analysis, which provided a wealth of detailed information about the lipid transfer mechanism of CETP. Results show that the bound CEs intraconvert between bent and linear conformations in the CETP core tunnel as a consequence of the high degree of conformational flexibility of the protein. During the conformational switching, there occurred a significant reduction in hydrophobic contacts between the CEs and CETP, and a continuous tunnel traversing across the CETP long axis appeared spontaneously. Thus, our results support the recently proposed "tunnel mechanism" of CETP from cryo-EM studies for the transfer of neutral lipids between different lipoproteins. The detailed understanding obtained here could help in devising methods to prevent CETP function as a cardiovascular disease therapeutic.

Bending-Twisting Motions and Main Interactions in Nucleoplasmin Nuclear Import

Alpha solenoid proteins play a key role in regulating the classical nuclear import pathway, recognizing a target protein and transporting it into the nucleus. Importin-α (Impα) is the solenoid responsible for cargo protein recognition, and it has been extensively studied by X-ray crystallography to understand the binding specificity. To comprehend the main motions of Impα and to extend the information about the critical interactions during carrier-cargo recognition, we surveyed different conformational states based on molecular dynamics (MD) and normal mode (NM) analyses. Our model of study was a crystallographic structure of Impα complexed with the classical nuclear localization sequence (cNLS) from nucleoplasmin (Npl), which was submitted to multiple 100 ns of MD simulations. Representative conformations were selected for calculating the 87 lowest frequencies NMs of vibration, and a displacement approach was applied along each NM. Based on geometric criteria, using the radius of curvature and inter-repeat angles as the reference metrics, the main motions of Impα were described. Moreover, we determined the salt bridges, hydrogen bonds and hydrophobic interactions in the Impα-NplNLS interface. Our results show the bending and twisting motions participating in the recognition of nuclear proteins, allowing the accommodation and adjustment of a classical bipartite NLS sequence. The essential contacts for the nuclear import were also described and were mostly in agreement with previous studies, suggesting that the residues in the cNLS linker region establish important contacts with Impα adjusting the cNLS backbone. The MD simulations combined with NM analysis can be applied to the Impα-NLS system to help understand interactions between Impα and cNLSs and the analysis of non-classic NLSs.

On the relationship between low-frequency normal modes and the large-scale conformational changes of proteins

Normal mode analysis is a computational technique that allows to study the dynamics of biological macromolecules. It was first applied to small protein cases, more than thirty years ago. The interest in this technique then raised when it was realized that it can provide insights about the large-scale conformational changes a protein can experience, for instance upon ligand binding. As it was also realized that studying highly simplified protein models can provide similar insights, meaning that this kind of analysis can be both quick and simple to handle, several applications were proposed, in the context of various structural biology techniques. This review focuses on these applications, as well as on how the functional relevance of the lowest-frequency modes of proteins was established.

Conformational selection in protein binding and function

Protein binding and function often involves conformational changes. Advanced nuclear magnetic resonance (NMR) experiments indicate that these conformational changes can occur in the absence of ligand molecules (or with bound ligands), and that the ligands may "select" protein conformations for binding (or unbinding). In this review, we argue that this conformational selection requires transition times for ligand binding and unbinding that are small compared to the dwell times of proteins in different conformations, which is plausible for small ligand molecules. Such a separation of timescales leads to a decoupling and temporal ordering of binding/unbinding events and conformational changes. We propose that conformational-selection and induced-change processes (such as induced fit) are two sides of the same coin, because the temporal ordering is reversed in binding and unbinding direction. Conformational-selection processes can be characterized by a conformational excitation that occurs prior to a binding or unbinding event, while induced-change processes exhibit a characteristic conformational relaxation that occurs after a binding or unbinding event. We discuss how the ordering of events can be determined from relaxation rates and effective on- and off-rates determined in mixing experiments, and from the conformational exchange rates measured in advanced NMR or single-molecule fluorescence resonance energy transfer experiments. For larger ligand molecules such as peptides, conformational changes and binding events can be intricately coupled and exhibit aspects of conformational-selection and induced-change processes in both binding and unbinding direction.

Identification of potential inhibitor targeting enoyl-acyl carrier protein reductase (InhA) in Mycobacterium tuberculosis: a computational approach

The explosive global spreading of multidrug resistant Mycobacterium tuberculosis (Mtb) has provoked an urgent need to discover novel anti-TB agents. Enoyl-acyl carrier protein reductase from Mtb is a well-known and thoroughly studied target for anti-tuberculosis therapy. In the present analysis, virtual screening techniques performed from Drug bank database by utilizing INH-NAD adduct as query for the discovery of potent anti-TB agents. About 100 molecules sharing similar scaffold with INH-NAD adduct were analyzed for their binding effectiveness. The initial screening based on number of rotatable bonds gave 42 hit molecules. Subsequently, physiochemical properties such as toxicity, solubility, drug-likeness and drug score were analyzed for the filtered set of compounds. Final data reduction was performed by means of molecular docking and normal mode docking analysis. The result indicates that DB04362, adenosine diphosphate 5-(beta-ethyl)-4-methyl-thiazole-2-carboxylic acid could be a promising lead compound and be effective in treating sensitive as well as drug-resistant strains of Mtb. We believe that this novel scaffolds might be the good starting point for lead compounds and certainly aid the experimental designing of anti-tuberculosis drug in a short time.

Identification of potential inhibitors of H5N1 influenza A virus neuraminidase by ligand-based virtual screening approach

The neuraminidase (NA) of the influenza virus is the target of antiviral drug, oseltamivir. Recently, cases were reported that influenza virus becoming resistant to oseltamivir, necessitating the development of new long-acting antiviral compounds. In this report, a novel class of lead molecule with potential NA inhibitory activity was identified using a combination of virtual screening (VS), molecular docking, and molecular dynamic approach. The PubChem database was used to perform the VS analysis by employing oseltamivir as query. Subsequently, the data reduction was carried out by employing molecular docking study. Furthermore, the screened lead molecules were analyzed with respect to the Lipinski rule of five, drug-likeness, toxicity profiles, and other physico-chemical properties of drugs by suitable software program. Final screening was carried out by normal mode analysis and molecular dynamic simulation approach. The result indicates that CID 25145634, deuterium-enriched oseltamivir, become a promising lead compound and be effective in treating oseltamivir sensitive as well as resistant influenza virus strains.

Modeling protein conformational transitions by a combination of coarse-grained normal mode analysis and robotics-inspired methods

BACKGROUND

Obtaining atomic-scale information about large-amplitude conformational transitions in proteins is a challenging problem for both experimental and computational methods. Such information is, however, important for understanding the mechanisms of interaction of many proteins.

METHODS

This paper presents a computationally efficient approach, combining methods originating from robotics and computational biophysics, to model protein conformational transitions. The ability of normal mode analysis to predict directions of collective, large-amplitude motions is applied to bias the conformational exploration performed by a motion planning algorithm. To reduce the dimension of the problem, normal modes are computed for a coarse-grained elastic network model built on short fragments of three residues. Nevertheless, the validity of intermediate conformations is checked using the all-atom model, which is accurately reconstructed from the coarse-grained one using closed-form inverse kinematics.

RESULTS

Tests on a set of ten proteins demonstrate the ability of the method to model conformational transitions of proteins within a few hours of computing time on a single processor. These results also show that the computing time scales linearly with the protein size, independently of the protein topology. Further experiments on adenylate kinase show that main features of the transition between the open and closed conformations of this protein are well captured in the computed path.

CONCLUSIONS

The proposed method enables the simulation of large-amplitude conformational transitions in proteins using very few computational resources. The resulting paths are a first approximation that can directly provide important information on the molecular mechanisms involved in the conformational transition. This approximation can be subsequently refined and analyzed using state-of-the-art energy models and molecular modeling methods.

Normal mode analysis based on an elastic network model for biomolecules in the Protein Data Bank, which uses dihedral angles as independent variables

We have developed a computer program, named PDBETA, that performs normal mode analysis (NMA) based on an elastic network model that uses dihedral angles as independent variables. Taking advantage of the relatively small number of degrees of freedom required to describe a molecular structure in dihedral angle space and a simple potential-energy function independent of atom types, we aimed to develop a program applicable to a full-atom system of any molecule in the Protein Data Bank (PDB). The algorithm for NMA used in PDBETA is the same as the computer program FEDER/2, developed previously. Therefore, the main challenge in developing PDBETA was to find a method that can automatically convert PDB data into molecular structure information in dihedral angle space. Here, we illustrate the performance of PDBETA with a protein-DNA complex, a protein-tRNA complex, and some non-protein small molecules, and show that the atomic fluctuations calculated by PDBETA reproduce the temperature factor data of these molecules in the PDB. A comparison was also made with elastic-network-model based NMA in a Cartesian-coordinate system.

In silico analysis of drug-resistant mutant of neuraminidase (N294S) against oseltamivir

The recent H1N1 influenza pandemic has attracted worldwide attention due to the high infection rate. Oseltamivir is a new class of anti-viral agent approved for the treatment and prevention of influenza infections. The principal target for this drug is a virus surface glycoprotein, neuraminidase (NA), which facilitates the release of nascent virus and thus spreads infection. Until recently, only a low prevalence of neuraminidase inhibitor (NAI) resistance (<1 %) had been detected in circulating viruses. However, there have been reports of significant numbers of A (H1N1) influenza strains with a N294S neuraminidase mutation that was highly resistant to the NAI, oseltamivir. Hence, in the present study, we highlight the effect of point mutation-induced oseltamivir resistance in H1N1 subtype neuraminidases by molecular simulation approach. The docking analysis reveals that mutation (N294S) significantly affects the binding affinity of oseltamivir with mutant type NA. This is mainly due to the decrease in the flexibility of binding site residues and the difference in prevalence of hydrogen bonds in the wild and mutant structures. This study throws light on the possible effects of drug-resistant mutations on the large functionally important collective motions in biological systems.

PheVI:09 (Phe6.44) as a sliding microswitch in seven-transmembrane (7TM) G protein-coupled receptor activation

In seven-transmembrane (7TM), G protein-coupled receptors, highly conserved residues function as microswitches, which alternate between different conformations and interaction partners in an extended allosteric interface between the transmembrane segments performing the large scale conformational changes upon receptor activation. Computational analysis using x-ray structures of the β(2)-adrenergic receptor demonstrated that PheVI:09 (6.44), which in the inactive state is locked between the backbone and two hydrophobic residues in transmembrane (TM)-III, upon activation slides ∼2 Å toward TM-V into a tight pocket generated by five hydrophobic residues protruding from TM-III and TM-V. Of these, the residue in position III:16 (3.40) (often an Ile or Val) appears to function as a barrier or gate for the transition between inactive and active conformation. Mutational analysis showed that PheVI:09 is essential for the constitutive and/or agonist-induced signaling of the ghrelin receptor, GPR119, the β(2)-adrenergic receptor, and the neurokinin-1 receptor. Substitution of the residues constituting the hydrophobic pocket between TM-III and TM-V in the ghrelin receptor in four of five positions impaired receptor signaling. In GPR39, representing the 12% of 7TM receptors lacking an aromatic residue at position VI:09, unchanged agonist-induced signaling was observed upon Ala substitution of LeuVI:09 despite reduced cell surface expression of the mutant receptor. It is concluded that PheVI:09 constitutes an aromatic microswitch that stabilizes the active, outward tilted conformation of TM-VI relative to TM-III by sliding into a tight hydrophobic pocket between TM-III and TM-V and that the hydrophobic residue in position III:16 constitutes a gate for this transition.