Structure and energetics guide dynamic behaviour in a T = 3 icosahedral virus capsid.

Although virus capsids appear as rigid, symmetric particles in experimentally determined structures; biochemical studies suggest a significant degree of structural flexibility in the particles. We carried out all-atom simulations on the icosahedral capsid of an insect virus, Flock House Virus, which show intriguing differences in the degree of flexibility of quasi-equivalent capsid subunits consistent with previously described biological behaviour. The flexibility of all the ß and γ subunits of the protein and RNA fragments is analysed and compared. Both γA subunit and RNA fragment exhibit higher flexibility than the γB and γC subunits. The capsid shell is permeable to the bidirectional movement of water molecules, and the movement is heavily influenced by the geometry of the capsid shell along specific symmetry axes. In comparison to the symmetry axes along I5 and I3, the I2 axis exhibits a slightly higher water content. This enriched water environment along I2 could play a pivotal role in facilitating the structural transitions necessary for RNA release, shedding some light on the intricate and dynamic processes underlying the viral life cycle. Our study suggests that the physical characterization of whole virus capsids is the key to identifying biologically relevant transition states in the virus life cycle and understanding the basis of virus infectivity.

Molecular dynamics simulation-based trinucleotide and tetranucleotide level structural and energy characterization of the functional units of genomic DNA.

Genomes of most organisms on earth are written in a universal language of life, made up of four units - adenine (A), thymine (T), guanine (G), and cytosine (C), and understanding the way they are put together has been a great challenge to date. Multiple efforts have been made to annotate this wonderfully engineered string of DNA using different methods but they lack a universal character. In this article, we have investigated the structural and energetic profiles of both prokaryotes and eukaryotes by considering two essential genomic sites, viz., the transcription start sites (TSS) and exon-intron boundaries. We have characterized these sites by mapping the structural and energy features of DNA obtained from molecular dynamics simulations, which considers all possible trinucleotide and tetranucleotide steps. For DNA, these physicochemical properties show distinct signatures at the TSS and intron-exon boundaries. Our results firmly convey the idea that DNA uses the same dialect for prokaryotes and eukaryotes and that it is worth going beyond sequence-level analyses to physicochemical space to determine the functional destiny of DNA sequences.

Bicyclo-DNA mimics with enhanced protein binding affinities: insights from molecular dynamics simulations.

DNA-protein interactions occur at all levels of DNA expression and replication and are crucial determinants for the survival of a cell. Several modified nucleotides have been utilized to manipulate these interactions and have implications in drug discovery. In the present article, we evaluated the binding of bicyclo-nucleotides (generated by forming a methylene bridge between C1' and C5' in sugar, leading to a bicyclo system with C2' axis of symmetry at the nucleotide level) to proteins. We utilized four ssDNA-protein complexes with experimentally known binding free energies and investigated the binding of modified nucleotides to proteins via all-atom explicit solvent molecular dynamics (MD) simulations (200 ns), and compared the binding with control ssDNA-protein systems. The modified ssDNA displayed enhanced binding to proteins as compared to the control ssDNA, as seen by means of MD simulations followed by MM-PBSA calculations. Further, the Delphi-based electrostatic estimation revealed that the high binding of modified ssDNA to protein might be related to the enhanced electrostatic complementarity displayed by the modified ssDNA molecules in all the four systems considered for the study. The improved binding achieved with modified nucleotides can be utilized to design and develop anticancer/antisense molecules capable of targeting proteins or ssRNAs.Communicated by Ramaswamy H. Sarma.

BESFA: bioinformatics based evolutionary, structural & functional analysis of prostrate, Placenta, Ovary, Testis, and Embryo (POTE) paralogs.

The POTE family comprises 14 paralogues and is primarily expressed in Prostrate, Placenta, Ovary, Testis, Embryo (POTE), and cancerous cells. The prospective function of the POTE protein family under physiological conditions is less understood. We systematically analyzed their cellular localization and molecular docking analysis to elucidate POTE proteins' structure, function, and Adaptive Divergence. Our results suggest that group three POTE paralogs (POTEE, POTEF, POTEI, POTEJ, and POTEKP (a pseudogene)) exhibits significant variation among other members could be because of their Adaptive Divergence. Furthermore, our molecular docking studies on POTE protein revealed the highest binding affinity with NCI-approved anticancer compounds. Additionally, POTEE, POTEF, POTEI, and POTEJ were subject to an explicit molecular dynamic simulation for 50ns. MM-GBSA and other essential electrostatics were calculated that showcased that only POTEE and POTEF have absolute binding affinities with minimum energy exploitation. Thus, this study's outcomes are expected to drive cancer research to successful utilization of POTE genes family as a new biomarker, which could pave the way for the discovery of new therapies.

A small molecule targeting hepatitis B surface antigen inhibits clinically relevant drug-resistant hepatitis B virus.

BACKGROUND: Currently approved oral antivirals for chronic HBV infection target the reverse transcriptase (RT) domain of the HBV polymerase. Emergence of drug resistance has been reported in a small proportion of chronic HBV patients on prolonged treatment with antivirals. We recently reported ZINC20451377, a small molecule targeting hepatitis B surface antigen (HBsAg) that effectively inhibits both WT HBV and tenofovir-resistant HBV. Due to the partial overlap between the RT domain and HBsAg, drug-resistant mutants are associated with corresponding mutations in HBsAg. OBJECTIVES: To evaluate the efficacy of ZINC20451377 against nine clinically relevant drug-resistant HBV mutants that lead to simultaneous mutations in the overlapping HBsAg gene. METHODS: Huh7 cells were transfected with 1.2× HBV replicons corresponding to WT HBV or drug-resistant HBV mutants and treated with different concentrations of ZINC20451377. We assessed the IC50 values of ZINC20451377 for HBsAg levels in the culture supernatants using ELISAs. HBV secretion was measured by immunocapture of secreted virions followed by real-time PCR quantitation of virion-associated DNA. RESULTS: ZINC20451377 led to a dose-dependent inhibition of secreted HBsAg encoded by WT HBV and all nine drug-resistant mutants tested and the IC50 values were in the low micromolar range. ZINC20451377 inhibited HBV secretion from drug-resistant mutants except for mutants harbouring the rtL180M + rtM204V (MV) mutation. CONCLUSIONS: The small molecule ZINC20451377 inhibits HBsAg and virion secretion in some of the clinically relevant drug-resistant HBV mutants. ZINC20451377 has a modest overall effect, and it was not effective against the MV mutants (lamivudine- and entecavir-resistant mutants).

Seq2Enz: An application of mask BLAST methodology with a new chemical logic of amino acids for improved enzyme function prediction.

Seq2Enz method is a new way to identify whether a query protein sequence is an enzyme and to assign an enzyme class to the protein sequence. The method is based on mask BLAST fortified with some novel structural-chemical properties (NCL) of the building blocks of proteins. All available reviewed enyme sequences (267,276 in number) in Uniprot/SwissProt and most recent depositions (7062) not used for training in ECPred, a state of the art software for enzyme class prediction, are taken for assessment and the results are compared with those from conventional BLAST and ECPred respectively. Seq2Enz is seen to perform consistently better for all the enzyme classes to all the four levels. Seq2Enz methodology is converted into an easy to use web-server and made freely accessible at http://www.scfbio-iitd.res.in Seq2Enz/.

A novel piperazine derivative that targets hepatitis B surface antigen effectively inhibits tenofovir resistant hepatitis B virus.

Chronic hepatitis B virus (HBV) infection is a global problem. The loss of hepatitis B surface antigen (HBsAg) in serum is a therapeutic end point. Prolonged therapy with nucleoside/nucleotide analogues targeting the HBV-polymerase may lead to resistance and rarely results in the loss of HBsAg. Therefore, inhibitors targeting HBsAg may have potential therapeutic applications. Here, we used computational virtual screening, docking, and molecular dynamics simulations to identify potential small molecule inhibitors against HBsAg. After screening a million molecules from ZINC database, we identified small molecules with potential anti-HBV activity. Subsequently, cytotoxicity profiles and anti-HBV activities of these small molecules were tested using a widely used cell culture model for HBV. We identified a small molecule (ZINC20451377) which binds to HBsAg with high affinity, with a KD of 65.3 nM, as determined by Surface Plasmon Resonance spectroscopy. Notably, the small molecule inhibited HBsAg production and hepatitis B virion secretion (10 µM) at low micromolar concentrations and was also efficacious against a HBV quadruple mutant (CYEI mutant) resistant to tenofovir. We conclude that this small molecule exhibits strong anti-HBV properties and merits further testing.

Symmetric Nucleosides as Potent Purine Nucleoside Phosphorylase Inhibitors.

Nucleic acids are one of the most enigmatic biomolecules crucial to several biological processes. Nucleic acid-protein interactions are vital for the coordinated and controlled functioning of a cell, leading to the design of several nucleoside/nucleotide analogues capable of mimicking these interactions and hold paramount importance in the field of drug discovery. Purine nucleoside phosphorylase is a well-established drug target due to its association with numerous immunodeficiency diseases. Here, we study the binding of human purine nucleoside phosphorylase (PNP) to some bidirectional symmetric nucleosides, a class of nucleoside analogues that are more flexible due to the absence of sugar pucker restraints. We compared the binding energies of PNP-symmetric nucleosides to the binding energies of PNP-inosine/Imm-H (a transition-state analogue), by means of 200 ns long all-atom explicit-solvent Gaussian accelerated molecular dynamics simulations followed by energetics estimation using the MM-PBSA methodology. Quite interestingly, we observed that a few symmetric nucleosides, namely, ν3 and ν4, showed strong binding with PNP (-14.1 and -12.6 kcal/mol, respectively), higher than inosine (-6.3 kcal/mol) and Imm-H (-9.6 kcal/mol). This is rationalized by an enhanced hydrogen-bond network for symmetric nucleosides compared to inosine and Imm-H while maintaining similar van der Waals contacts. We note that the chemical structures of both ν3 and ν4, due to an additional unsaturation in them, resemble enzymatic transition states and fall in the category of transition-state analogues (TSAs), which are quite popular.

Intron exon boundary junctions in human genome have in-built unique structural and energetic signals.

Precise identification of correct exon-intron boundaries is a prerequisite to analyze the location and structure of genes. The existing framework for genomic signals, delineating exon and introns in a genomic segment, seems insufficient, predominantly due to poor sequence consensus as well as limitations of training on available experimental data sets. We present here a novel concept for characterizing exon-intron boundaries in genomic segments on the basis of structural and energetic properties. We analyzed boundary junctions on both sides of all the exons (3 28 368) of protein coding genes from human genome (GENCODE database) using 28 structural and three energy parameters. Study of sequence conservation at these sites shows very poor consensus. It is observed that DNA adopts a unique structural and energy state at the boundary junctions. Also, signals are somewhat different for housekeeping and tissue specific genes. Clustering of 31 parameters into four derived vectors gives some additional insights into the physical mechanisms involved in this biological process. Sites of structural and energy signals correlate well to the positions playing important roles in pre-mRNA splicing.

Allosterically Coupled Multisite Binding of Testosterone to Human Serum Albumin.

Human serum albumin (HSA) acts as a carrier for testosterone, other sex hormones, fatty acids, and drugs. However, the dynamics of testosterone's binding to HSA and the structure of its binding sites remain incompletely understood. Here, we characterize the dynamics of testosterone's binding to HSA and the stoichiometry and structural location of the binding sites using 2-dimensional nuclear magnetic resonance (2D NMR), fluorescence spectroscopy, 4,4'-dianilino-1,1'-binaphthyl-5,5'-disulfonic acid dipotassium salt partitioning, and equilibrium dialysis, complemented by molecular modeling. 2D NMR studies showed that testosterone competitively displaced 18-[13C]-oleic acid from at least 3 known fatty acid binding sites on HSA that also bind many drugs. Binding isotherms of testosterone's binding to HSA generated using fluorescence spectroscopy and equilibrium dialysis were nonlinear and the apparent dissociation constant varied with different concentrations of testosterone and HSA. The binding isotherms neither conformed to a linear binding model with 1:1 stoichiometry nor to 2 independent binding sites; the binding isotherms were most consistent with 2 or more allosterically coupled binding sites. Molecular dynamics studies revealed that testosterone's binding to fatty acid binding site 3 on HSA was associated with conformational changes at site 6, indicating that residues in in these 2 distinct binding sites are allosterically coupled. There are multiple, allosterically coupled binding sites for testosterone on HSA. Testosterone shares these binding sites on HSA with free fatty acids, which could displace testosterone from HSA under various physiological states or disease conditions, affecting its bioavailability.

Enhancing protein backbone angle prediction by using simpler models of deep neural networks.

Protein structure prediction is a grand challenge. Prediction of protein structures via the representations using backbone dihedral angles has recently achieved significant progress along with the on-going surge of deep neural network (DNN) research in general. However, we observe that in the protein backbone angle prediction research, there is an overall trend to employ more and more complex neural networks and then to throw more and more features to the neural networks. While more features might add more predictive power to the neural network, we argue that redundant features could rather clutter the scenario and more complex neural networks then just could counterbalance the noise. From artificial intelligence and machine learning perspectives, problem representations and solution approaches do mutually interact and thus affect performance. We also argue that comparatively simpler predictors can more easily be reconstructed than the more complex ones. With these arguments in mind, we present a deep learning method named Simpler Angle Predictor (SAP) to train simpler DNN models that enhance protein backbone angle prediction. We then empirically show that SAP can significantly outperform existing state-of-the-art methods on well-known benchmark datasets: for some types of angles, the differences are 6-8 in terms of mean absolute error (MAE). The SAP program along with its data is available from the website https://gitlab.com/mahnewton/sap .

PvP01-DB: computational structural and functional characterization of soluble proteome of PvP01 strain of Plasmodium vivax.

Despite Plasmodium vivax being the main offender in the majority of malarial infections, very little information is available about its adaptation and development in humans. Its capability for activating relapsing infections through its dormant liver stage and resistance to antimalarial drugs makes it as one of the major challenges in eradicating malaria. Noting the immediate necessity for the availability of a comprehensive and reliable structural and functional repository for P. vivax proteome, here we developed a web resource for the new reference genome, PvP01, furnishing information on sequence, structure, functions, active sites and metabolic pathways compiled and predicted using some of the state-of-the-art methods in respective fields. The PvP01 web resource comprises organized data on the soluble proteome consisting of 3664 proteins in blood and liver stages of malarial cycle. The current public resources represent only 163 proteins of soluble proteome of PvP01, with complete information about their molecular function, biological process and cellular components. Also, only 46 proteins of P. vivax have experimentally determined structures. In this milieu of extreme scarcity of structural and functional information, PvP01 web resource offers meticulously validated structures of 3664 soluble proteins. The sequence and structure-based functional characterization led to a quantum leap from 163 proteins available presently to whole soluble proteome offered through PvP01 web resource. We believe PvP01 web resource will serve the researchers in identifying novel protein drug targets and in accelerating the development of structure-based new drug candidates to combat malaria. Database Availability: http://www.scfbio-iitd.res.in/PvP01.

Improving the binding affinity estimations of protein-ligand complexes using machine-learning facilitated force field method.

Scoring functions are routinely deployed in structure-based drug design to quantify the potential for protein-ligand (PL) complex formation. Here, we present a new scoring function Bappl+ that is designed to predict the binding affinities of non-metallo and metallo PL complexes. Bappl+ outperforms other state-of-the-art scoring functions, achieving a high Pearson correlation coefficient of up to ~ 0.76 with low standard deviations. The biggest contributors to the increased performance are the use of a machine-learning model and the enlarged training dataset. We have also evaluated the performance of Bappl+ on target-specific proteins, which highlighted the limitations of our function and provides a way for further improvements. We believe that Bappl+ methodology could prove valuable in ranking candidate molecules against a target metallo or non-metallo protein by reliably predicting their binding affinities, thus helping in the drug discovery process.

A novel method SEProm for prokaryotic promoter prediction based on DNA structure and energetics.

MOTIVATION: Despite conservation in general architecture of promoters and protein-DNA interaction interface of RNA polymerases among various prokaryotes, identification of promoter regions in the whole genome sequences remains a daunting challenge. The available tools for promoter prediction do not seem to address the problem satisfactorily, apparently because the biochemical nature of promoter signals is yet to be understood fully. Using 28 structural and 3 energetic parameters, we found that prokaryotic promoter regions have a unique structural and energy state, quite distinct from that of coding regions and the information for this signature state is in-built in their sequences. We developed a novel promoter prediction tool from these 31 parameters using various statistical techniques. RESULTS: Here, we introduce SEProm, a novel tool that is developed by studying and utilizing the in-built structural and energy information of DNA sequences, which is applicable to all prokaryotes including archaea. Compared to five most recent, diverged and current best available tools, SEProm performs much better, predicting promoters with an 'F-value' of 82.04 and 'Precision' of 81.08. The next best 'F-value' was obtained with PromPredict (72.14) followed by BProm (68.37). On the basis of 'Precision' value, the next best 'Precision' was observed for Pepper (75.39) followed by PromPredict (72.01). SEProm maintained the lead even when comparison was done on two test organisms (not involved in training for SEProm). AVAILABILITY AND IMPLEMENTATION: The software is freely available with easy to follow instructions (www.scfbio-iitd.res.in/software/TSS_Predict.jsp). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

RASPD+: Fast Protein-Ligand Binding Free Energy Prediction Using Simplified Physicochemical Features.

The virtual screening of large numbers of compounds against target protein binding sites has become an integral component of drug discovery workflows. This screening is often done by computationally docking ligands into a protein binding site of interest, but this has the drawback of a large number of poses that must be evaluated to obtain accurate estimates of protein-ligand binding affinity. We here introduce a fast pre-filtering method for ligand prioritization that is based on a set of machine learning models and uses simple pose-invariant physicochemical descriptors of the ligands and the protein binding pocket. Our method, Rapid Screening with Physicochemical Descriptors + machine learning (RASPD+), is trained on PDBbind data and achieves a regression performance that is better than that of the original RASPD method and traditional scoring functions on a range of different test sets without the need for generating ligand poses. Additionally, we use RASPD+ to identify molecular features important for binding affinity and assess the ability of RASPD+ to enrich active molecules from decoys.

Symmetrization of the backbone of nucleic acids: a molecular dynamics study.

DNA displays directional asymmetry (5'→3'), a fundamental property associated with each strand of the nucleic acids and is crucial to several biological processes such as transcription and replication. We observe that this asymmetry can be altered by a number of ways leading to directionally symmetric nucleic acids. We report six such approaches for the creation of symmetric backbones, their insertion in a regular B-DNA structure followed by their characterization using molecular dynamics (MD) simulations on a microsecond timescale in explicit solvent. We compared the resultant MD structures of symmetric nucleic acids with that of regular B-DNA in terms of helicoidal parameters, dihedrals, groove geometry, and solvent/ions accessibility. We also compared the Watson-Crick hydrogen bond strength of these symmetric molecules to that of the control B-DNA system. It was found that the symmetric DNAs with a few substituents designed retained the double helical B-DNA type structure as seen by means of structural and energetic parameters. As an application of such symmetric molecules, we evaluated the binding free energies of single stranded symmetric nucleic acids with a short stretch of complementary RNA and found that a few molecules designed have comparable energies to that of control DNA-RNA hybrid system. As the chemical modifications in the oligonucleotides have been a remarkable tool for control over the nucleotide properties, mainly the nucleotide bending, binding to RNA targets, and stability to nucleases to design nucleoside drug analogs; the importance of the proposed symmetric molecules in these areas is foreseen.Communicated by Ramaswamy H. Sarma.

Appropriateness and pharmacoeconomics of surgical antimicrobial prophylaxis in open reduction internal fixation surgery practiced in a tertiary hospital compared to recommendations in the national center for disease control guidelines.

CONTEXT: Surgical site infections are frequently observed despite the availability of national guideline on surgical antimicrobial prophylaxis (SAP). These infections increase patient morbidity, mortality, and direct and indirect health-care costs. Open reduction internal fixation (ORIF) is a common orthopedic surgery for fracture. There is a paucity of Indian data on SAP in ORIF surgery. AIMS: The present study was taken up aiming at the evaluation of appropriateness and pharmacoeconomics of SAP in ORIF based on the national guidelines. SUBJECTS AND METHODS: One-year observational prospective cohort study was conducted among 412 participants, who underwent ORIF in the Department of Orthopedics in a Tertiary Care Hospital. Name, dose, route, timing, frequency, and duration of administration of prophylactic antimicrobials used were recorded. STATISTICAL ANALYSIS USED: Descriptive statistics were used wherever required. RESULTS: The mean age of participants was 39.24 years, majority (60.92%) were male, and 49.52% had fracture of lower-limb bones. The appropriateness of preoperative SAP in terms of indication in ORIF, timing, and route of administration was 100%. Selection and dose of preoperative and postoperative antimicrobials were appropriate in only 13% of cases. Omission of intraoperative dose was appropriate in all participants. Duration of postoperative Antimicrobial agent administration was inappropriately long in all participants. None of the cases received completely appropriate regimen. Cost analysis showed the mean cost of SAP practiced in our hospital was eleven times higher than that with recommended SAP. CONCLUSIONS: Considering the inappropriateness of SAP practiced, monitoring of guideline implementation and awareness among health-care professionals are necessary to prevent SSI and to decrease economic burden on the patients.

Active repurposing of drug candidates for melanoma based on GWAS, PheWAS and a wide range of omics data.

BACKGROUND: Drug repurposing is a swift, safe, and cheap drug discovery method. Melanoma disorders present low survival and high mortality rates and are challenging to diagnose and treat. Moreover, there is a high volume of worldwide investigations that are attempting to find melanoma-related genes of influence, which can be identified as responsive targets for reliable treatment. METHOD: In this study, we used a wide range of data analyses to analyze over 1100 genes and proteins of influence with respect to cutaneous malignant melanoma. Our analysis included various investigational results from genome- and phenome-wide association studies (GWAS and PheWAS, respectively), biomedical, transcriptomic, and metabolomic datasets. We then researched the DrugBank for potential melanoma targets from the selected list. We excluded known melanoma targets to obtain a list of druggable proteins. We performed a precise analysis of the drugs' pathogenesis and checked the expression profiles of the selected drugs having high associations with known anti-melanoma drugs. RESULT: We found 35 drugs that interacted with 20 unique targets. These drugs appear to have high melanoma treatment potentials. We confirmed our results with previous studies and found supporting references for 30 of these drugs. In conclusion, this investigation can be applied to various diseases for the efficient and economical repurposing of various drug compounds. For further validation, the results may be applicable for in vivo tests and clinical trials.

C5' omitted DNA enhances bendability and protein binding.

Protein-DNA interactions are of great biological importance. The specificity and strength of these intimate contacts are crucial in the proper functioning of a cell, wherein the role of DNA dynamic bendability has been a matter of discussion. We relate DNA bendability to protein binding by introducing some simple modifications in the DNA structure. We removed C5' carbon in first modified structure and the second has an additional carbon between C3' and 3'-OH, hereby pronounced as C(-) and C(+) nucleic acids respectively. We observed that C(+) nucleic acid retains B-DNA duplex as seen by means of 500 ns long molecular dynamics (MD) simulations, structural and energetic calculations, while C(-) nucleic acid attains a highly bend structure. We transferred these observations to a protein-DNA system in order to monitor as to what extent the bendability enhances the protein binding. The energetics of binding is explored by performing 100 ns long MD simulations on control and modified DNA-protein complexes followed by running MM-PBSA/GBSA calculations on the resultant structures. It is observed that C(+) nucleic acid has protein binding in close correspondence to the control system (∼-14 kcal/mol) due to their relatable structure, while the C(-) nucleic acid displayed high binding to the protein (∼-18 kcal/mol). DelPhi based calculations reveal that the high binding could be the result of enhanced electrostatic interactions caused by exposed bases in the bend structure for protein recognition. Such modified oligonucleotides, due to their improved binding to protein and resistance to nuclease degradation, have a great therapeutic value.