RFGR: Repeat Finder for Complete and Assembled Whole Genomes and NGS Reads.

Repetitive DNA sequences cause genomic instability and are important genetic markers. Identification of repeats is a critical step in genome annotation and analysis. On the other hand, repeats also pose a technical challenge for genome assembly and alignment programs using NGS data. RFGR is a comprehensive tool that can find exact repetitive sequences in complete genomes and assembled genomes, as well as NGS reads of prokaryotes. For complete genomes, RFGR uses a suffix trees to find seed repeats of repetitive sequences of fixed length with indels. For assembled genomes, RFGR uses a modified Bowtie aligner to find seed repeats of exact repetitive sequences in the contigs/ scaffolds, which are then extended to maximal repeats. The repeats are classified and for repeats near a gene, RFGR reports the gene as well. For the control dataset of E. coli UTI89 and E. coli K12, RFGR reports 35,141 and 49,352 repeats, respectively. For NGS reads, RFGR uses the frequency of the repetitive k-mers to determine FASTQ reads containing repetitive sequences and removes them from the dataset. An E. coli K12 NGS dataset pre-processed using RFGR, on comparison with the original dataset, gives an improved assembly. The N50 value improves by 22.86% with a decrease in size of the assembly graph by nearly 50%. Thus, with RFGR, we achieve a better assembly with reduced computation. RFGR can be improved in terms of the length of the minimum repeat found, extending to find approximate repeats and to be applicable to Eukaryotes as well.

Complete chloroplast genome of the medicinal plant Evolvulus alsinoides: comparative analysis, identification of mutational hotspots and evolutionary dynamics with species of Solanales.

Evolvulus alsinoides, belonging to the family Convolvulaceae, is an important medicinal plant widely used as a nootropic in the Indian traditional medicine system. In the genus Evolvulus, no research on the chloroplast genome has been published. Hence, the present study focuses on annotation, characterization, identification of mutational hotspots, and phylogenetic analysis in the complete chloroplast genome (cp) of E. alsinoides. Genome comparison and evolutionary dynamics were performed with the species of Solanales. The cp genome has 114 genes (80 protein-coding genes, 30 transfer RNA, and 4 ribosomal RNA genes) that were unique with total genome size of 157,015 bp. The cp genome possesses 69 RNA editing sites and 44 simple sequence repeats (SSRs). Predicted SSRs were randomly selected and validated experimentally. Six divergent hotspots such as trnQ-UUG, trnF-GAA, psaI, clpP, ndhF, and ycf1 were discovered from the cp genome. These microsatellites and divergent hot spot sequences of the Taxa 'Evolvulus' could be employed as molecular markers for species identification and genetic divergence investigations. The LSC area was found to be more conserved than the SSC and IR region in genome comparison. The IR contraction and expansion studies show that nine genes rpl2, rpl23, ycf1, ycf2, ycf1, ndhF, ndhA, matK, and psbK were present in the IR-LSC and IR-SSC boundaries of the cp genome. Fifty-four protein-coding genes in the cp genome were under negative selection pressure, indicating that they were well conserved and were undergoing purifying selection. The phylogenetic analysis reveals that E. alsinoides is closely related to the genus Cressa with some divergence from the genus Ipomoea. This is the first time the chloroplast genome of the genus Evolvulus has been published. The findings of the present study and chloroplast genome data could be a valuable resource for future studies in population genetics, genetic diversity, and evolutionary relationship of the family Convolvulaceae. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-021-01051-w.

Making novel proteins from pseudogenes.

MOTIVATION: Recently, we made synthetic proteins from non-coding DNA of Escherichia coli. Encouraged by this, we asked: can we artificially express pseudogenes into novel and functional proteins? What kind of structures would be generated? Would these proteins be stable? How would the organism respond to the artificial reactivation of pseudogenes? RESULTS: To answer these questions, we studied 16 full-length protein equivalents of pseudogenes. The sequence-based predictions indicated interesting molecular and cellular functional roles for pseudogene-derived proteins. Most of the proteins were predicted to be involved in the amino acid biosynthesis, energy metabolism, purines and pyrimidine biosynthesis, central intermediary metabolism, transport and binding. Interestingly, many of the pseudogene-derived proteins were predicted to be enzymes. Furthermore, proteins showed strong evidence of stable tertiary structures. The prediction scores for structure, function and stability were found to be favorable in most of the cases. IMPACT: To our best knowledge, this is the first such report that predicts the possibility of making functional and stable proteins from pseudogenes. In future, it would be interesting to experimentally synthesize and validate these predictions.

Ethnic and region-specific genetic risk variants of stroke and its comorbid conditions can define the variations in the burden of stroke and its phenotypic traits.

Burden of stroke differs by region, which could be attributed to differences in comorbid conditions and ethnicity. Genomewide variation acts as a proxy marker for ethnicity, and comorbid conditions. We present an integrated approach to understand this variation by considering prevalence and mortality rates of stroke and its comorbid risk for 204 countries from 2009 to 2019, and Genome-wide association studies (GWAS) risk variant for all these conditions. Global and regional trend analysis of rates using linear regression, correlation, and proportion analysis, signifies ethnogeographic differences. Interestingly, the comorbid conditions that act as risk drivers for stroke differed by regions, with more of metabolic risk in America and Europe, in contrast to high systolic blood pressure in Asian and African regions. GWAS risk loci of stroke and its comorbid conditions indicate distinct population stratification for each of these conditions, signifying for population-specific risk. Unique and shared genetic risk variants for stroke, and its comorbid and followed up with ethnic-specific variation can help in determining regional risk drivers for stroke. Unique ethnic-specific risk variants and their distinct patterns of linkage disequilibrium further uncover the drivers for phenotypic variation. Therefore, identifying population- and comorbidity-specific risk variants might help in defining the threshold for risk, and aid in developing population-specific prevention strategies for stroke.

Interaction analysis of SARS-CoV-2 omicron BA1 and BA2 of RBD with fifty monoclonal antibodies: Molecular dynamics approach.

This report provides detailed insights into the interaction of fifty monoclonal antibodies with two recent Omicron variants, BA1 and BA2. It has been observed that numerous mutations in the receptor binding domain (RBD) result in significant structural changes in Omicron, enhancing its ability to mediate viral infections compared to other variants of concern. The following antibodies, namely JX3S304, 7KMG, 7CH4, 7BELCOVOX45, 7CDJ, 7C01, 7JX3S2H14, 6XCA, 7CDI, 7JMO, 7B3O, 6ZER, 6XC7CR3022, JX3S309, 6XC7CC123, 7CM4, 7KMI, 7L7EAZD8895, exhibit a superior binding affinity towards the Spike when compared to the reference CR3022. Four best-docked systems were subjected to further testing through molecular dynamics (MD) simulations. The MM/GBSA free energy for the top-scored complexes of BA1 variant are BA1_JX3S3O4, BA1_7KMI, BA1_7CH4, and BA1_7KMG, with respective values of -56.120 kcal/mol, -41.30 kcal/mol, -17.546 kcal/mol, and -8.527 kcal/mol; and of BA2 variant are BA2_JX3S3O4, BA2_7CM4, BA2_KMG, and BA2_7CH4, with respective values of -40.903 kcal/mol, -23.416 kcal/mol, -17.350 kcal/mol, and -5.460 kcal/mol. Detailed structural/energetic parameters, principal component analysis, and free energy landscape (FEL) studies reveal a significant decrease in antibody resistance due to the disappearance of numerous hydrogen bond interactions and various metastable states. We believe that these crucial mechanistic insights will contribute to breakthroughs in SARS-CoV-2 research.

Molecular dynamics and docking studies on potentially active natural phytochemicals for targeting SARS-CoV-2 main protease.

In the present study, we screened eighty seven novel phytochemical compounds from four popular herbs, such as, Aegle Marmelos, Coleus Amboinicus, Aerva Lanata and Biophytum Sensitivum and identified the best three for targeting the main protease (Mpro) receptor of SARS-CoV-2. After categorizing all the phytochemicals based upon LibDock scores and hydrogen bonding interactions, the top ranked 26 compounds were further subjected for detailed Molecular dynamics (MD) study. From these screening we identified that Aegelinosides B leads the list with a high LibDock value of 142.50 (binding energy: -8.54 kcal/mol), which is better than several popular reference compounds namely, Tipranavir (LibDock score, 141.50), Saquinavir (125.34), Zopicole (122.9), Pirenepine (122.70), (115.37), Metixene (109.18), Oxiconazole Pimozide (138.00) and Rimonabant (91.88). Detailed analysis for structural stability (RMSD), Cα fluctuations (RMSF), intermolecular hydrogen bond interactions, effect of solvent accessibility (SASA) and compactness (Rg) factors were performed for the best six compounds and it is found that they are very stable and exhibit folding behavior. Apart from the docking and MD tests, through further drug-likeness and toxicity tests, three compounds, such as, Aegelinosides B, Epicatechin, and Feruloyltyramine (LibDock scores, respectively, 142.50, 124.33 and 129.06) can be suggested for fighting SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Insights on the interaction of SARS-CoV-2 variant B.1.617.2 with antibody CR3022 and analysis of antibody resistance.

BACKGROUND: The existence of mutated Delta (B.1.617.2) variants of SARS-CoV-2 causes rapid transmissibility, increase in virulence, and decrease in the effectiveness of public health. Majority of mutations are seen in the surface spike, and they are considered as antigenicity and immunogenicity of the virus. Hence, finding suitable cross antibody or natural antibody and understanding its biomolecular recognition for neutralizing surface spike are crucial for developing many clinically approved COVID-19 vaccines. Here, we aim to design SARS-CoV-2 variant and hence, to understand its mechanism, binding affinity and neutralization potential with several antibodies. RESULTS: In this study, we modelled six feasible spike protein (S1) configurations for Delta SARS-CoV-2 (B.1.617.2) and identified the best structure to interact with human antibodies. Initially, the impact of mutations at the receptor-binding domain (RBD) of B.1.617.2 was tested, and it is found that all mutations increase the stability of proteins (ΔΔG) and decrease the entropies. An exceptional case is noted for the mutation of G614D variant for which the vibration entropy change is found to be within the range of 0.133-0.004 kcal/mol/K. Temperature-dependent free energy change values (ΔG) for wild type is found to be - 0.1 kcal/mol, whereas all other cases exhibit values within the range of - 5.1 to - 5.5 kcal/mol. Mutation on spike increases the interaction with the glycoprotein antibody CR3022 and the binding affinity (CLUSpro energy = - 99.7 kcal/mol). The docked Delta variant with the following antibodies, etesevimab, bebtelovimab, BD-368-2, imdevimab, bamlanivimab, and casirivimab, exhibit a substantially decreased docking score (- 61.7 to - 112.0 kcal/mol) and the disappearance of several hydrogen bond interactions. CONCLUSION: Characterization of antibody resistance for Delta variant with respect to the wild type gives understanding regarding why Delta variant endures the resistance boosted through several trademark vaccines. Several interactions with CR3022 have appeared compared to Wild for Delta variant, and hence, it is suggested that modification on the CR3022 antibody could further improve for the prevention of viral spread. Antibody resistance decreased significantly due to numerous hydrogen bond interactions which clearly indicate that these marketed/launched vaccines (etesevimab) will be effective for Delta variants.

Identification and molecular modeling of novel endogenous activator proteins of Sirt-1: an in silico study.

Sirt-1 is one of the most extensively studied mammalian Sirtuins that deacetylates histones and several non-histone proteins critical to cellular homeostasis. As a key sensor of cellular metabolism, it is regulated at multiple levels including transcriptional and post translational levels. As an allosteric enzyme, its activity is also modulated by ligands and certain endogenous proteins. The present study is an in silico approach to identify novel Sirt-1 binding proteins. Bioinformatic search for similarity in sequence, structure, and topology of binding region to Lamin-A, a known activator of Sirt-1, identified three proteins viz. Epididymis secretory sperm binding protein (ESSBP), xylosyltransferase 1 (XT-1), and Adenylyl cyclase 9 (ADCY-9). Molecular docking studies revealed binding of ESSBP and ADCY-9 to the N-terminal region of Sirt-1 while XT-1 docks at both N-terminal and C-terminal region of Sirt-1 with Z-Dock score better than Lamin-A; XT-1 and ADCY-9 showed better Z-Rank score as well. MD simulation studies for extended time followed by MM-PBSA analysis showed that the Sirt-1-protein complexes were stable with favourable binding energy and minimal change in RMSD relating to backbone structure and RMSF relating to residue fluctuations. Further, H-bond analysis showed only minimal changes in H bonding interactions. Docking of these proteins to Sirt-1 through interaction with several residues particularly to its N-terminal region spanning 1-243 residues, in a manner similar to the docking of the activator Lamin-A and different from the inhibitor DLBC-1 binding site, suggests that these proteins may also positively modulate Sirt-1 activity. Further experimental data would be required to validate the computational prediction and to understand its physiological role.Communicated by Ramaswamy H. Sarma.

Diterpenoid and C20 diterpenoid alkaloid as a potent inhibitor of SARS-CoV-2 main protease (Mpro): from Piper barberi Gamble, an endemic and endangered species of Southern Western Ghats.

The present study investigated the phytochemicals and in silico anti-nCoV properties of Piper barberi, an endangered and endemic species of Southern Western Ghats. Using conventional soxhlet extraction method, the leaf and stem were extracted separately with methanol (PBLM and PBSM). The bioactive compounds from the extracts were identified using HR-LCMS/MS-qTOF analysis. These compounds were subjected to various in silico analyses to identify potential drug candidates against nCoV. The HR LCMS/MS analysis of PBLM and PBSM revealed the presence of phenols, flavonoids, alkaloids, and terpenoids in it and this is the first report of the phytoconstituents present in the species P. barberi. All the identified bioactive compounds were subjected to predict ADMET. Out of 49 identified compounds, only 31 passed drug-likeness properties and toxicity tests. Molecular interaction studies were conducted using the AutoDockTools 4.2.6., which showed that only 13 compounds exhibited acceptable binding affinity with the nCoV target Mpro. Structural stability and binding free energy analyses of the five compounds with the higher binding affinity indicated that the bioactive compounds Hetisine and Ajaconine are stable with both hydrogen bonds and hydrophobic interactions. Hetisine shows stable binding among these two compounds with two hydrogen bond interactions with the crucial catalytic dyad residue (His41). Thus, this study concludes that these compounds might potentially be used as an alternative drug candidate for managing nCoV. However, further experimental validation, including in vitro and in vivo assays, is required to substantiate the results.Communicated by Ramaswamy H. Sarma.

Discovery of a new Daboia russelli viper venom PLA2 inhibitor using virtual screening of pharmacophoric features of co-crystallized compound.

Snake venom PLA2, a member of the group of hydrolase enzymes, has been recognized as a promising drug target for snake envenomation. In the present study, an attempt was made to identify potential inhibitors of snake venom PLA2 by employing a pharmacophore-based virtual screening, docking, and dynamics approach. A receptor-based pharmacophore model was generated based on the features of the established and bound co-crystal ligand (2-carbamoylmethyl-5-propyl-octahydro-indol-7-yl)-acetic acid in the PLA2 complex. The best pharmacophore model (ADDH) derived, consisted of four features, namely one hydrogen bond acceptor, two hydrogen bond donors, and one hydrophobic region. This common pharmacophore was then used to perform virtual screening against a drug-like diverse database, with due consideration to the Lipinski 'rule of five', so as to obtain a pool of lead molecules. The short-listed lead molecules were then subjected to docking analysis with that of the Daboia russelli viper venom PLA2 followed by a molecular simulation study for a duration of 100 ns. CAP04815700 was chosen as the best compound based on the simulation parameters, which were then taken for MM/PBSA calculation, and it was revealed that it has a similar effective inhibitory potential as that of the crystal ligand. Further, the cluster analysis also revealed the structural significance of the backbone protein after the interaction with CAP04815700. This study will continue to explore its bioactivity in vitro and in vivo.Communicated by Ramaswamy H. Sarma.

In silico screening and epitope mapping of leptospiral outer membrane protein-Lsa46.

Leptospirosis is one of the neglected diseases caused by the spirochete, Leptospira interrogans. Leptospiral surface adhesion (Lsa) proteins are surface exposed outer membrane proteins present in the pathogen. It acts as laminin and plasminogen binding proteins which enable them to infect host cells. The major target for the development of vaccine in the current era focuses on surface exposed outer membrane proteins, as they can induce strong and fast immune response in hosts. Therefore, the present study mapped the potential epitopes of the Leptospiral outer membrane proteins, mainly the surface adhesion proteins. Protein sequence analysis of Lsa proteins was done by in silico methods. The primary protein sequence analysis revealed Lsa46 as a suitable target which can be a potent Leptospiral vaccine candidate. Its structure was modelled by threading based method in I-TASSER server and validated by Ramachandran plot. The predicted epitope's interactions with human IgG, IgM(Fab) and T-cell receptor TCR(αß) were performed by molecular docking studies using Biovia Discovery studio 2018. One of the predicted B-cell epitopes and the IgG showed desirable binding interactions, while four of the predicted B-cell epitopes and T-cell epitopes showed desirable binding interactions with IgM and TCR respectively. The molecular dynamic simulation studies carried out with the molecular docked complexes gave minimized energies indicating stable interactions. The structural analysis of the entire simulated complex showed a stable nature except for one of the Epitope-IgM complex. Further the binding free energy calculation of eight receptor-ligand complex predicted them energetically stable. The results of the study help in elucidating the structural and functional characterization of Lsa46 for epitope-based vaccine design.Communicated by Ramaswamy H. Sarma.

Chrysin inhibits adipogenesis by modulating PPARγ: in silico and in vitro studies.

Adipose tissue is the major storage site of lipids and plays a vital role in energy homeostasis. Adipogenesis is a well-regulated process wherein preadipocytes differentiate into adipocytes. It requires the sequential activation of numerous transcription factors, including peroxisome proliferator activated receptor-γ (PPAR-γ). Phytochemicals have been reported to regulate adipogenesis and flavonoids represent the most researched groups of phytochemicals with regard to their effect on adipogenesis. Chrysin is a naturally occurring flavone and is reported to have anti-inflammatory effects in obese conditions. The present study was aimed to examine the effect of chrysin on adipogenesis. In silico Molecular docking, dynamic simulation studies and in vitro cell-based assays showed that chrysin inhibited adipogenesis by modulating key adipogenic transcription factor PPARγ. Enhanced adipogenesis leads to obesity and targeting adipogenesis is potential in regulating adipose tissue development. So, these investigations may provide important information for designing therapeutic interventions to control adiposity.Communicated by Ramaswamy H. Sarma.

In silico screening of the phytochemicals present in Clitoria ternatea L. as the inhibitors of snake venom phospholipase A2 (PLA2).

Millions of people suffer from snake bite envenomation, and its management is a challenge, even today. Medicinal plants have attracted the researcher's attention for their outstanding advantages in treating many diseases, including snake venom poisoning. Clitoria ternatea L, is a plant popularly known for its various pharmacological effects especially, anti-snake venom property. However, the molecular mechanism behind this is poorly understood. It is reported that snake venom PLA2 is an extensively studied toxic factor. This study is meant to screen the compound's capability to act as inhibitors of the Daboia russelli snake venom PLA2 through molecular docking and dynamics studies. Our results show that among the 27 compounds taken for the study, only Kaempferol showed good interaction profile with the conserved catalytic active site residues, His48 and Asp49. The pharmacophore features of the compound also demonstrate its exact fitting at the binding pocket. Further RMSD, RMSF, Rg, and hydrogen bond analysis confirmed the stable binding of Kaempferol with PLA2 through molecular dynamic simulations for 100 ns. In addition, the MM/PBSA binding free energy calculation of the complex was also affirming the docking results. The binding free energy (BFE) of Kaempferolis better than the reference compound. ADME and Lipinski's rule of five reveals its drug like properties.Communicated by Ramaswamy H. Sarma.

Molecular docking and dynamics studies for the identification of Nipah virus glycoprotein inhibitors from Indian medicinal plants.

The infection by Nipah Virus (NiV), a zoonotic paramyxovirus, is fatal and several outbreaks have been reported in humans in various countries. No effective vaccines or drugs are developed till date to control this infection. The NiV-Glycoprotein (NiV-G) is one of the essential proteins for viral entry by binding to the Ephrin-B receptors. The present study screens the potential phytocompounds that can target NiV-G and thereby inhibit the viral entry to human. Computer-aided virtual screening of 1426 phytocompounds from various medicinal plants was carried out to investigate their efficacy as potential therapeutics. Ribavirin, the currently used drug, was also docked to compare the docking score and intermolecular interactions between ligand and target protein. Further, molecular dynamics simulations and MM-PBSA binding free energy calculations were performed to understand the stability of the docked complexes. Radius of gyrations and Solvent Accessible Surface Area were also performed to evaluate the compactness and solvent behaviour of ligand-receptor complexes during the 100 ns simulation. Our analysis revealed that the alkaloid, Serpentinine, has the highest potency to block NiV-G with favourable binding.Communicated by Ramaswamy H. Sarma.

SARS-CoV-2 variants infectivity prediction and therapeutic peptide design using computational approaches.

The outbreak of severe acute respiratory coronavirus 2 (SARS-CoV-2) has created a public health emergency globally. SARS-CoV-2 enters the human cell through the binding of the spike protein to human angiotensin converting enzyme 2 (ACE2) receptor. Significant changes have been reported in the mutational landscape of SARS-CoV-2 in the receptor binding domain (RBD) of S protein, subsequent to evolution of the pandemic. The present study examines the correlation between the binding affinity of mutated S-proteins and the rate of viral infectivity. For this, the binding affinity of SARS-CoV and variants of SARS-CoV-2 towards ACE2 was computationally determined. Subsequently, the RBD mutations were classified on the basis of the number of strains identified with respect to each mutation and the resulting variation in the binding affinity was computationally examined. The molecular docking studies indicated a significant correlation between the Z-Rank score of mutated S proteins and the rate of infectivity, suitable for predicting SARS-CoV-2 infectivity. Accordingly, a 30-mer peptide was designed and the inhibitory properties were computationally analyzed. Single amino acid-wise mutation was performed subsequently to identify the peptide with the highest binding affinity. Molecular dynamics and free energy calculations were then performed to examine the stability of the peptide-protein complexes. Additionally, selected peptides were synthesized and screened using a colorimetric assay. Together, this study developed a model to predict the rate of infectivity of SARS-CoV-2 variants and propose a potential peptide that can be used as an inhibitor for the viral entry to human.Communicated by Ramaswamy H. Sarma.

The elusive short gene--an ensemble method for recognition for prokaryotic genome.

Accurate prediction of short protein coding DNA from genome sequence information remains an unsolved problem in DNA sequence analysis. Popular gene finding tools show drastic reduction in accuracy while attempting to predict genes of length less than 400 nt, a length we define as short. This study performs a quantitative evaluation of a set of selected coding measures in terms of their discriminative power in recognizing short genes in prokaryotic genomes. By performing Fast Correlation Based Feature Selection (FCBF) technique, we identified a subset of coding measures with high discriminative power. Using the measures identified thus, we present a novel approach for short genes recognition. A short-gene predictor employing AdaBoost.M1 in conjunction with random forests as the base classifier gives 92.74% accuracy, 94.77% sensitivity and 90.06% specificity on short genes.

Looking for a sequence based allostery definition: a statistical journey at different resolution scales.

The aim of this work was to detect allosteric hotspots signatures characterizing protein regions acting as the 'key drivers' of global allosteric conformational change. We computationally estimated the relative strength of intra-molecular interaction in allosteric proteins between two putative allostery-susceptible sites using a co-evolution model based upon the optimization of the cross-correlation in terms of free-energy-transfer hydrophobicity scale (Tanford scale) distribution along the chain. Cross-Recurrence Quantification Analysis (Cross-RQA) applied on the sequences of allostery susceptible sites showed evidence of strong interaction amongst allosteric susceptible sites. This could be due to transient weak molecular bonds between allostery susceptible patches enabling regions far-apart to come together. Further, using a large protein dataset, by comparing allosteric protein set with a randomly generated sequence population as well as a generic protein set, we reconfirmed our earlier findings that hydrophobicity patterning (as formalized by Recurrence Quantification Analysis (RQA) descriptors) may serve as determinant of allostery and its relevance in the transmission of allosteric conformational change. We applied RQA to free-energy-transfer hydrophobicity-transformed amino acid sequences of the allostery dataset to extract allostery specific global sequence features. These free-energy-transfer hydrophobicity-based RQA markers proved to be representative of allosteric signatures and not related to the differences between randomly generated and real proteins. These free-energy-transfer hydrophobicity-based RQA markers when evaluated by pattern recognition tools could distinguish allosteric proteins with 92% accuracy.

Identification and analysis of novel microRNAs from fragile sites of human cervical cancer: computational and experimental approach.

Accurate identification of mature miRNAs is an important requirement for exploring the post-transcriptional regulatory mechanism of organisms. In this work we present a novel computational tool 'Mpred' which first identifies pre-miRNAs and then predicts its mature miRNAs. We first use our method to learn with high accuracy characteristic features of human miRNA precursors from miRbase registry and then apply to sequences from fragile site regions related to cervical cancer in search of novel miRNA genes. The study identified 13 putative miRNA-like sequences and most of them were not related to each other and do not share homology with annotated sequences. Finally, four of the top scoring predictions were verified experimentally using quantitative RT-PCR validation. Expression profile studies revealed that four novel miRs were present in cervical tissues and these data compiled here provide a regulatory framework of miRNA genes that may have roles in tumorigenesis.

Bioinformatics screening of ETV4 transcription factor oncogenes and identifying small-molecular anticancer drugs.

This bioinformatics study aimed to identify ETV4 transcription factor oncogenes and outline anticancer drugs for these genes. First, we collected known 61 ETV4 cancer targets that were framed as two classes of queries to screen against the multiomics resources in GeneMANIA. This method accessed and added functionally similar 20 genes to each set. These data were interpreted by hub genes, network clustering, gene ontology, and pathway analyses, and the results confirmed that all resultant genes were cancer promoters. The ETS-binding motifs were identified from the promoter regions of these genes. Thus, 23 ETV4 targets were figured and those involved in oncogenesis were filtered as the following 16 putative nodes: MMP8, MMP14, KDR, BRIP1, CXCR1, GRB14, SHC2, SHC4, SH2B1, SH2B2, INPPL1, PTPN3, GNG12, SEMA4D, RHOA, and SPSB2. The transcriptional regulation of these oncogenes was coordinated by an extensive miRNA network that found to deregulate many cancer pathways. Using DgIb database, the high quality 6 oncogene-drug combinations (MMP8-CHEMBL1231240, MMP8-Aminomethylamide, CXCR1-Reparixin, SEMA4D-Pepinemab, RHOA-Clausine E, and SPSB2-CHEMBL175296) were proposed. These findings may advance our understanding of novel neoplastic gene nexus of ETV4 and design treatment strategies for its modulation.

Identification of potential lead compounds against BACE1 through in-silico screening of phytochemicals of Medhya rasayana plants for Alzheimer's disease management.

Alzheimer's disease is a progressive and irreversible neurodegenerative disease that accounts for 70-80% of dementia in the elderly. According to recent clinical data, the incidence of the disease is exponentially increasing with age. Beta-site amyloid precursor protein cleaving enzyme1 (BACE1) is an important molecule involved in the pathogenesis of Alzheimer's disease due to its early role in the amyloid cascade. Cleavage of amyloid precursor protein by BACE1 is the rate-limiting step leading to the production and aggregation of amyloid-beta plaques. A number of natural products are being identified as non-competitive BACE1 inhibitors. In Ayurveda, Medhya rasayana is a group of medicinal herbs, specifically used for managing neurological disorders and is known to be effective in improving cognitivity and intellect. This study aimed to analyze the pharmacological activity of bio-active compounds in Medhya rasayana plants against BACE1, employing structure-based docking approach. 11 compounds out of 876 were identified as potential hits, based on docking scores, binding energies, and interactions with the critical residues of BACE1. Possible neurological activities of these compounds were predicted using PASS server. Out of the 11 compounds screened, two compounds, 'Convolidine' from the plant Convolvulus pleuricaulis Choisy and 'N-(4-hydroxybutyl) phthalimide' from Glycyrrhiza glabra satisfied the pharmacological parameters of Lipinski rule of filtering and ADMET prediction. The binding stability of these compounds against BACE1 was confirmed by molecular dynamic simulation and post dynamic MM/GBSA calculations. Detailed analysis of the interaction with the critical amino acids in the active site revealed the possible inhibitory potential of these compounds of medicinal plant origin against BACE1.