PMTPred: machine-learning-based prediction of protein methyltransferases using the composition of k-spaced amino acid pairs.

Protein methyltransferases (PMTs) are a group of enzymes that help catalyze the transfer of a methyl group to its substrates. These enzymes play an important role in epigenetic regulation and can methylate various substrates with DNA, RNA, protein, and small-molecule secondary metabolites. Dysregulation of methyltransferases is implicated in various human cancers. However, in light of the well-recognized significance of PMTs, reliable and efficient identification methods are essential. In the present work, we propose a machine-learning-based method for the identification of PMTs. Various sequence-based features were calculated, and prediction models were trained using various machine-learning algorithms using a tenfold cross-validation technique. After evaluating each model on the dataset, the SVM-based CKSAAP model achieved the highest prediction accuracy with balanced sensitivity and specificity. Also, this SVM model outperformed deep-learning algorithms for the prediction of PMTs. In addition, cross-database validation was performed to ensure the robustness of the model. Feature importance was assessed using shapley additive explanations (SHAP) values, providing insights into the contributions of different features to the model's predictions. Finally, the SVM-based CKSAAP model was implemented in a standalone tool, PMTPred, due to its consistent performance during independent testing and cross-database evaluation. We believe that PMTPred will be a useful and efficient tool for the identification of PMTs. The PMTPred is freely available for download at https://github.com/ArvindYadav7/PMTPred and http://www.bioinfoindia.org/PMTPred/home.html for research and academic use.

Quercetin ameliorates chronic unpredicted stress-mediated memory dysfunction in male Swiss albino mice by attenuating insulin resistance and elevating hippocampal GLUT4 levels independent of insulin receptor expression.

Chronic stress is associated with impaired neuronal functioning, altered insulin signaling, and behavioral dysfunction. Quercetin has shown neuroprotective and antidiabetic effects, besides modulating cognition and insulin signaling. Therefore, in the present study, we explored whether or not quercetin ameliorates stress-mediated cognitive dysfunction and explored the underlying mechanism. Swiss albino male mice were subjected to an array of unpredicted stressors for 21days, during which 30mg/kg quercetin treatment was given orally. The effect of chronic unpredicted stress (CUS) and quercetin treatment on cognition were evaluated using novel object recognition (NOR) and Morris water maze (MWM) tests. Hippocampal neuronal integrity was observed by histopathological examination. Blood glucose, serum corticosterone, and insulin levels were measured by commercial kits and insulin resistance was evaluated in terms of HOMA-IR index. Hippocampal insulin signaling was determined by immunofluorescence staining. CUS induced significant cognitive dysfunction (NOR and MWM) and severely damaged hippocampal neurons, especially in the CA3 region. Quercetin treatment alleviated memory dysfunction and rescued neurons from CUS-mediated damage. Fasting blood glucose, serum corticosterone, and serum insulin were significantly elevated in stressed animals, besides, having significantly higher HOMA-IR index, suggesting the development of insulin resistance. Quercetin treatment alleviated insulin resistance and attenuated altered biochemical parameters. CUS markedly down-regulated insulin signaling in CA3 region and quercetin treatment improved neuronal GLUT4 expression, which seemed to be independent of insulin and insulin receptor levels. These results suggest that intact insulin functioning in the hippocampus is essential for cognitive functions and quercetin improves CUS-mediated cognitive dysfunction by modulating hippocampal insulin signaling.

Mining NGS transcriptomes for miRNAs and dissecting their role in regulating growth, development, and secondary metabolites production in different organs of a medicinal herb, Picrorhiza kurroa.

MAIN CONCLUSION: This study is the first endeavor on mining of miRNAs and analyzing their involvement in development and secondary metabolism of an endangered medicinal herb Picrorhiza kurroa (P. kurroa ). miRNAs are ubiquitous non-coding RNA species that target complementary sequences of mRNA and result in either translational repression or target degradation in eukaryotes. The role of miRNAs has not been investigated in P. kurroa which is a medicinal herb of industrial value due to the presence of secondary metabolites, picroside-I and picroside-II. Computational identification of miRNAs was done in 6 transcriptomes of P. kurroa generated from root, shoot, and stolon organs varying for growth, development, and culture conditions. All available plant miRNA entries were retrieved from miRBase and used as backend datasets to computationally identify conserved miRNAs in transcriptome data sets. Total 18 conserved miRNAs were detected in P. kurroa followed by target prediction and functional annotation which suggested their possible role in controlling various biological processes. Validation of miRNA and expression analysis by qRT-PCR and 5' RACE revealed that miRNA-4995 has a regulatory role in terpenoid biosynthesis ultimately affecting the production of picroside-I. miR-5532 and miR-5368 had negligible expression in field-grown samples as compared to in vitro-cultured samples suggesting their role in regulating P. kurroa growth in culture conditions. The study has thus identified novel functions for existing miRNAs which can be further validated for their potential regulatory role.

A computational study on structural and functional consequences of nsSNPs in human dopa decarboxylase.

The Dopa Decarboxylase (DDC) gene plays an important role in the synthesis of biogenic amines such as dopamine, serotonin, and histamine. Non-synonymous single nucleotide polymorphisms (nsSNPs) in the DDC gene have been linked with various neurodegenerative disorders. In this study, a comprehensive in silico analysis of nsSNPs in the DDC gene was conducted to assess their potential functional consequences and associations with disease outcomes. Using publicly available databases, a complete list of nsSNPs in the DDC gene was obtained. 29 computational tools and algorithms were used to characterise the effects of these nsSNPs on protein structure, function, and stability. In addition, the population-based association studies were performed to investigate possible associations between specific nsSNPs and arthritis. Our research identified four novel DDC gene nsSNPs that have a major impact on the structure and function of proteins. Through molecular dynamics simulations (MDS), we observed changes in the stability of the DDC protein induced by specific nsSNPs. Furthermore, population-based association studies have revealed potential associations between certain DDC nsSNPs and various neurological disorders, including Parkinson's disease and dementia. The in silico approach used in this study offers insightful information about the functional effects of nsSNPs in the DDC gene. These discoveries provide insight into the cellular processes that underlie cognitive disorders. Furthermore, the detection of disease-associated nsSNPs in the DDC gene may facilitate the development of tailored and targeted therapy approaches.Communicated by Ramaswamy H. Sarma.

Computational studies on Alzheimer's disease associated pathways and regulatory patterns using microarray gene expression and network data: revealed association with aging and other diseases.

Alzheimer's disease (AD), which is one of the most common age-associated neurodegenerative disorders, affects millions of people worldwide. Due to its polygenic nature, AD is believed to be caused not by defects in single genes, but by variations in a large number of genes and their complex interactions, which ultimately contribute to the broad spectrum of disease phenotypes. Extraction of insights and knowledge from microarray and network data will lead to a better understanding of complex diseases. The present study aimed to identify genes with differential topology and their further association with other biological processes that regulate causative factors for AD, ageing (AG) and other diseases. Our analysis revealed a common sharing of important biological processes and putative candidate genes among AD and AG. Some significant novel genes and other variants for various biological processes have been reported as being associated with AD, AG, and other diseases, and these could be implicated in biochemical events leading to AD from AG through pathways, interactions, and associations. Novel information for network motifs such as BiFan, MIM (multiple input module), and SIM (single input module) and their close variants has also been discovered and this implicit information will help to improve research into AD and AG. Ten major classes for TFs (transcription factors) have been identified in our data, where hundreds of TFBS patterns are being found associated with AD, and other disease. Structural and physico-chemical properties analysis for these TFBS classes revealed association of biological processes involved with other severe human disease. Nucleosomes and linkers positional information could provide insights into key cellular processes. Unique miRNA (micro RNA) targets were identified as another regulatory process for AD. The association of novel genes and variants of existing genes have also been explored for their interaction and association with other diseases that are either directly or indirectly implicated through AG and AD.

Computational approach for assessing the involvement of SMYD2 protein in human cancers using TCGA data.

BACKGROUND: SMYD2 is a protein of the SET and MYND domain-containing family SMYD. It can methylate the lysine residue of various histone and nonhistone cancer-related proteins and plays a critical role in tumorigenesis. Although emerging evidence supports the association of SMYD2 in the progression of cancers, but its definitive effect is not yet clear. Therefore, further study of the gene in relation with cancer progression needs to be conducted. In the current study, investigators used TCGA data to determine the potential carcinogenic effect of SMYD2 in 11 cancer types. The transcriptional expression, survival rate, mutations, enriched pathways, and Gene Ontology of the SMYD2 were explored using different bioinformatics tools and servers. In addition, we also examined the correlation between SMYD2 gene expression and immunocyte infiltration in multiple cancer types. RESULTS: Findings revealed that higher expression of SMYD2 was significantly correlated with cancer incidents. In CESC and KIRC, the mRNA expression of SMYD2 was significantly correlated with overall survival (OS). In BRCA, KIRC, COAD, and HNSC, the mRNA expression of SMYD2 was significantly correlated with disease-free survival (DFS). We detected 15 missense, 4 truncating, 4 fusions, and 1 splice type of mutation. The expression of SMYD2 was significantly correlated with tumor purity and immunocyte infiltration in six cancer types. The gene GNPAT was highly associated with SMYD2. Significant pathways and Gene Ontology (GO) terms for co-expressed genes were associated to various processes linked with cancer formation. CONCLUSION: Collectively, our data-driven results may provide reasonably comprehensive insights for understanding the carcinogenic effect of SMYD2. It suggests that SMYD2 might be used as a significant target for identifying new biomarkers for various human tumors.

Computational screening of pathogenic missense nsSNPs in heme oxygenase 1 (HMOX1) gene and their structural and functional consequences.

Heme Oxygenase 1 (HMOX1) is a cytoprotective enzyme, exhibiting the highest activity in the spleen, catalyzing the heme ring breakdown into products of biological significance- biliverdin, CO, and Fe2+. In vascular cells, HMOX1 possesses strong anti-apoptotic, antioxidant, anti-proliferative, anti-inflammatory, and immunomodulatory actions. The majority of these activities are crucial for the prevention of atherogenesis. Single amino acid substitutions in proteins generated by missense non-synonymous single nucleotide polymorphism (nsSNPs) in the protein-encoding regions of genes are potent enough to cause significant medical challenges due to the alteration of protein structure and function. The current study aimed at characterizing and analyzing high-risk nsSNPs associated with the human HMOX1 gene. Preliminary screening of the total available 288 missense SNPs was performed through the lens of deleteriousness and stability prediction tools. Finally, a total of seven nsSNPs (Y58D, A131T, Y134H, F166S, F167S, R183S and M186V) were found to be most deleterious by all tools that are present at highly conserved positions. Molecular dynamics simulations (MDS) analysis explained the mutational effects on the dynamic action of the wild-type and mutant proteins. In a nutshell, R183S (rs749644285) was identified as a highly detrimental mutation that could significantly render the enzymatic activity of HMOX1. The finding of this computational analysis might help subject the experimental confirmatory analysis to characterize the role of nsSNPs in HMOX1.Communicated by Ramaswamy H. Sarma.

Repurposing of drugs against methyltransferase as potential Zika virus therapies.

In recent years, the outbreak of infectious disease caused by Zika Virus (ZIKV) has posed a major threat to global public health, calling for the development of therapeutics to treat ZIKV disease. Several possible druggable targets involved in virus replication have been identified. In search of additional potential inhibitors, we screened 2895 FDA-approved compounds using Non-Structural Protein 5 (NS5) as a target utilizing virtual screening of in-silco methods. The top 28 compounds with the threshold of binding energy -7.2 kcal/mol value were selected and were cross-docked on the three-dimensional structure of NS5 using AutoDock Tools. Of the 2895 compounds screened, five compounds (Ceforanide, Squanavir, Amcinonide, Cefpiramide, and Olmesartan_Medoxomil) ranked highest based on filtering of having the least negative interactions with the NS5 and were selected for Molecular Dynamic Simulations (MDS) studies. Various parameters such as RMSD, RMSF, Rg, SASA, PCA and binding free energy were calculated to validate the binding of compounds to the target, ZIKV-NS5. The binding free energy was found to be -114.53, -182.01, -168.19, -91.16, -122.56, and -150.65 kJ mol-1 for NS5-SFG, NS5-Ceforanide, NS5-Squanavir, NS5-Amcinonide, NS5-Cefpiramide, and NS5-Ol_Me complexes respectively. The binding energy calculations suggested Cefpiramide and Olmesartan_Medoxomil (Ol_Me) as the most stable compounds for binding to NS5, indicating a strong rationale for their use as lead compounds for development of ZIKV inhibitors. As these drugs have been evaluated on pharmacokinetics and pharmacodynamics parameters only, in vitro and in vivo testing and their impact on Zika viral cell culture may suggest their clinical trials on ZIKV patients.

Comprehensive analysis of non-synonymous missense SNPs of human galactose mutarotase (GALM) gene: an integrated computational approach.

Missense Non-synonymous single nucleotide polymorphisms (nsSNPs) of Galactose Mutarotase (GALM) are associated with the Novel type of Galactosemia (Galactosemia type 4) together with symptoms such as high blood galactose levels and eye cataracts. The objective of the present study was to identify deleterious nsSNPs of GALM recorded on the dbSNP database through comprehensive insilico analysis. Among the 319 missense nsSNPs reported, various insilco tools predicted R78S, R82G, A163E, P210S, Y281C, E307G and F339C as the most deleterious mutations. Structural analysis, PTM analysis and molecular dynamics simulations (MDS) were carried out to understand the effect of these mutations on the structural and physicochemical properties of the GALM protein. The residues R82G and E307G were found to be part of the binding site that resulted in decreased surface accessibility. Replacing the charged wild-type residue with a neutral mutant type affected its substrate binding. All 7 mutations were found to increase the rigidity of the protein structure, which is unfavorable during ligand binding. The mutation F339E made the protein structure more rigid than all the other mutations. Y281 is a phosphorylated site, and therefore, less significant structural changes were observed when compared to other mutations; however, it may have significant differences in the usual functioning of the protein. In summary, the structural and functional analysis of missense SNPs of GALM is important to reduce the number of potential mutations to be evaluated in vitro to understand the association with some genetic diseases.Communicated by Ramaswamy H. Sarma.

Comprehensive bioinformatics analysis of structural and functional consequences of deleterious missense mutations in the human QDPR gene.

Quinonoid dihydropteridine reductase (QDPR) is an enzyme that regulates tetrahydrobiopterin (BH4), a cofactor for enzymes involved in neurotransmitter synthesis and blood pressure regulation. Reduced QDPR activity can cause dihydrobiopterin (BH2) accumulation and BH4 depletion, leading to impaired neurotransmitter synthesis, oxidative stress, and increased risk of Parkinson's disease. A total of 10,236 SNPs were identified in the QDPR gene, with 217 being missense SNPs. Over 18 different sequence-based and structure-based tools were employed to assess the protein's biological activity, with several computational tools identifying deleterious SNPs. Additionally, the article provides detailed information about the QDPR gene and protein structure and conservation analysis. The results showed that 10 mutations were harmful and linked to brain and central nervous system disorders, and were predicted to be oncogenic by Dr. Cancer and CScape. Following conservation analysis, the HOPE server was used to analyse the effect of six selected mutations (L14P, V15G, G23S, V54G, M107K, G151S) on the protein structure. Overall, the study provides insights into the biological and functional impact of nsSNPs on QDPR activity and the potential induced pathogenicity and oncogenicity. In the future, research can be conducted to systematically evaluate QDPR gene variation through clinical studies, investigate mutation prevalence across different geographical regions, and validate computational results with conclusive experiments.Communicated by Ramaswamy H. Sarma.

Curative anti-typhoid effect of Detarium microcarpum Guill. & Perr. (Leguminosae) hydroethanolic extract root bark based-on in vivo and molecular docking analyses.

ETHNOPHARMACOLOGICAL RELEVANCE: Detarium microcarpum is used to treat typhoid fever, a major public health problem, by indigenous population in Africa. Though its preventive activities have been documented, the curative effect is still to be confirmed. AIM OF THE STUDY: This study aimed at evaluating the curative effects of the hydroethanolic extract of Detarium microcarpum root bark on Salmonella typhimurium-induced typhoid in rat and exploring the in-silico inhibition of some bacterial key enzymes. STUDY DESIGN: In vitro antioxydant, in vivo antisalmonella of the extract and in silico molecular docking assay on the isolated compounds were carried out to explore the anti-salmonella effects of Detarium microcarpum. MATERIAL AND METHODS: The in vitro antioxidant properties of the extract were evaluated using DPPH, ABTS and FRAP tests. The anti-salmonella activity of the extract was assessed through feacal sample from Salmonella typhimurium-infected rat cultured in Salmonella-Shigella agar (SS agar) medium. The affinity of isolated compounds (Rhinocerotinoic acid and Microcarposide) from the extract were performed on four key enzymes (Adenylosuccinate lyase, Acetyl coenzyme A synthetase, Thymidine phosphorylase and LuxS-Quorum sensor) using molecular docking simulation to elucidate the molecular level inhibition mechanism. RESULTS: Crude extract of D. microcarpum root bark showed variable activities on DPPH (RSa50: 6.09 ± 1.04 µg/mL), ABTS (RSa50: 24.46 ± 0.27), and FRAP (RSa50: 23.30 ± 0.23). The extract at all the doses exhibited significant healing effect of infected rats, with the complete clearance. The extract restored hematological, biochemical and histological parameters closed to the normal control. The molecular docking results indicates that rhinocerotinoic acid and microcarposide present more affinity to the LuxS-Quorum sensor and Acetyl coenzyme A synthetase protein as compared to the others. CONCLUSION: These results demonstrate potent anti-typhoid activities of the hydroethanolic of Detarium microcarpum root bark extract through antioxidant properties and high inhibitory affinity of its compounds on some bacterial key enzymes that justify its use as traditional medicine to typhoid fever.

Identification of small molecules against cyclin dependent kinase-5 using chemoinformatics approach for Alzheimer's disease and other tauopathies.

Alzheimer's disease (AD) is a multifactorial complex and wide spreading global disease. It is a chronic neurodegenerative disorder characterized by amyloid beta (Aß) and neurofibrillary tangles (NFTs). Several enzymes are involved in which CDK5 is a major tau phosphorylation enzyme. We have screened (n = 5,36,801) compounds against CDK5 and 392 compounds were selected for pharmacokinetics analysis. In the pharmacokinetics analysis, various descriptors were used for filtering the compounds. After that 16 compounds with the control compound Z3R were employed for the redocking using Autodock Vina and Autodock. Lastly, four compounds were selected and employed for 100 ns MDS studies. On the basis of various MD analysis like RMSD, RMSF, Rg, SASA, Number of hydrogen bonds, Principal component analysis and binding free energy (CDK5-ZINC6261568: -129.50 kJ.mol-1 and CDK5-ZINC14168360: -191.16 kJ.mol-1), we have found that ZINC6261568 and ZINC14168360 can act as a lead compound against the CDK5.Communicated by Ramaswamy H. Sarma.

Physicochemical characterization of paclitaxel prodrugs with cytochrome 3A4 to correlate solubility and bioavailability implementing molecular docking and simulation studies.

Prodrugs are biologically inactive drug molecules that may be developed through rational drug design with an objective to improve a drug's pharmaceutical and pharmacokinetic properties. Paclitaxel, a highly potent anticancer drug, is directed against many cancers like breast cancer, ovarian cancer, lung cancer, head and neck tumors, non-small cell lung cancer, and Kaposi's sarcoma, etc. Along with its excellent antitumor activity the drug had a major limitation of low water solubility. To overcome this limitation of this nanomolar active drug many prodrugs were formed in the past. Though increase in the solubility of the drug was obtained but that may or may not account for its increase in bioavailability. CYP3A4 liver enzymes are responsible for the metabolism of fifty percent of the drugs and are major metabolizing enzyme for paclitaxel. Phosphate prodrugs are well known to account the insolubility of many drugs and thus increasing their bioavailability also. In this study, we calculated the ADMET properties of a dataset of twenty phosphate prodrugs of paclitaxel. On the basis of reflection of three favourable properties, ten prodrugs were chosen for further docking studies against CYP3A4. Finally, three prodrugs showing unfavourable binding affinities were selected for Molecular Dynamics Simulations and from this in-silico study we identified that all the three selected prodrugs were unstable as compared to the paclitaxel. The instability of these prodrugs showed their lesser interaction with the CYP3A4 and hence contributing more towards its bioavailability. Thus the three suggested prodrugs those were studied in-silico for oral bioavailability can be further validated for gastrointestinal cancer.Communicated by Ramaswamy H. Sarma.

Disruption of DYRK1A-induced hyperphosphorylation of amyloid-beta and tau protein in Alzheimer's disease: An integrative molecular modeling approach.

Alzheimer's disease (AD) is a neurological disorder caused by the abnormal accumulation of hyperphosphorylated proteins. Dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) is a dual phosphorylation enzyme which phosphorylates the amyloid-ß (Aß) and neurofibrillary tangles (NFTs). A high throughput virtual screening approach was applied to screen a library of 98,071 compounds against DYRK1A using different programs including AutoDock Vina, Smina, and idock. Based on the binding affinities, we selected 330 compounds for absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis. Various pharmacokinetics parameters were predicted using the admetSAR server, and based on the pharmacokinetics results, 14 compounds were selected for cross-docking analysis using AutoDock. Cross-docking analysis revealed four compounds, namely, ZINC3843365 (-11.07 kcal/mol-1), ZINC2123081 (-10.93 kcal/mol-1), ZINC5220992 (-10.63 kcal/mol-1), and ZINC68569602 (-10.35 kcal/mol-1), which had the highest negative affinity scores compared to the 10 other molecules analyzed. Density functional theory (DFT) analysis was conducted for all the four top-ranked compounds. The molecular interaction stability of these four compounds with DYRK1A has been evaluated using molecular dynamics (MD) simulations on 100 nanoseconds followed by principal component analysis (PCA) and binding free energy calculations. The Gibbs free energy landscape analysis suggested the metastable state and folding pattern of selected docking complexes. Based on the present study outcome, we propose four antagonists, viz., ZINC3843365, ZINC2123081, ZINC5220992, and ZINC68569602 as potential inhibitors against DYRK1A and to reduce the amyloid-ß and neurofibrillary tangle burden. These screened molecules can be further investigated using a number of in vitro and in vivo experiments.

A bioinformatics approach to the identification of novel deleterious mutations of human TPMT through validated screening and molecular dynamics.

Polymorphisms of Thiopurine S-methyltransferase (TPMT) are known to be associated with leukemia, inflammatory bowel diseases, and more. The objective of the present study was to identify novel deleterious missense SNPs of TPMT through a comprehensive in silico protocol. The initial SNP screening protocol used to identify deleterious SNPs from the pool of all TPMT SNPs in the dbSNP database yielded an accuracy of 83.33% in identifying extremely dangerous variants. Five novel deleterious missense SNPs (W33G, W78R, V89E, W150G, and L182P) of TPMT were identified through the aforementioned screening protocol. These 5 SNPs were then subjected to conservation analysis, interaction analysis, oncogenic and phenotypic analysis, structural analysis, PTM analysis, and molecular dynamics simulations (MDS) analysis to further assess and analyze their deleterious nature. Oncogenic analysis revealed that all five SNPs are oncogenic. MDS analysis revealed that all SNPs are deleterious due to the alterations they cause in the binding energy of the wild-type protein. Plasticity-induced instability caused by most of the mutations as indicated by the MDS results has been hypothesized to be the reason for this alteration. While in vivo or in vitro protocols are more conclusive, they are often more challenging and expensive. Hence, future research endeavors targeted at TPMT polymorphisms and/or their consequences in relevant disease progressions or treatments, through in vitro or in vivo means can give a higher priority to these SNPs rather than considering the massive pool of all SNPs of TPMT.

High-throughput screening of natural compounds and inhibition of a major therapeutic target HsGSK-3ß for Alzheimer's disease using computational approaches.

BACKGROUND: Alzheimer's disease is a leading neurodegenerative disease worldwide and is the 6th leading cause of death in the USA. AD is a very complex disease and the drugs available in the market cannot fully cure it. The glycogen synthase kinase 3 beta plays a major role in the hyperphosphorylation of tau protein which forms the neurofibrillary tangles which is a major hallmark of AD. In this study, we have used a series of computational approaches to find novel inhibitors against GSK-3ß to reduce the TAU hyperphosphorylation. RESULTS: We have retrieved a set of compounds (n=167,741) and screened against GSK-3ß in four sequential steps. The resulting analysis of virtual screening suggested that 404 compounds show good binding affinity and can be employed for pharmacokinetic analysis. From here, we have selected 20 compounds those were good in terms of pharmacokinetic parameters. All these compounds were re-docked by using Autodock Vina followed by Autodock. Four best compounds were employed for MDS and here predicted RMSD, RMSF, Rg, hydrogen bonds, SASA, PCA, and binding-free energy. From all these analyses, we have concluded that out of 167,741 compounds, the ZINC15968620, ZINC15968622, and ZINC70707119 can act as lead compounds against HsGSK-3ß to reduce the hyperphosphorylation. CONCLUSION: The study suggested three compounds (ZINC15968620, ZINC15968622, and ZINC70707119) have great potential to be a drug candidate and can be tested using in vitro and in vivo experiments for further characterization and applications.

Structural and functional analysis of disease-associated mutations in GOT1 gene: An in silico study.

Disease-associated single nucleotide polymorphisms (SNPs) alter the natural functioning and the structure of proteins. Glutamic-oxaloacetic transaminase 1 (GOT1) is a gene associated with multiple cancers and neurodegenerative diseases which codes for aspartate aminotransferase. The present study involved a comprehensive in-silico analysis of the disease-associated SNPs of human GOT1. Four highly deleterious nsSNPs (L36R, Y159C, W162C and L345P) were identified through SNP screening using several sequence-based and structure-based tools. Conservation analysis and oncogenic analysis showed that most of the nsSNPs are at highly conserved residues, oncogenic in nature and cancer drivers. Molecular dynamics simulations (MDS) analysis was performed to understand the dynamic behaviour of native and mutant proteins. PTM analysis revealed that the nsSNP Y159C is at a PTM site and will mostly affect phosphorylation at that site. Based on the overall analyses carried out in this study, L36R is the most deleterious mutation amongst the aforementioned deleterious mutations of GOT1.

Virtual screening, pharmacokinetics, molecular dynamics and binding free energy analysis for small natural molecules against cyclin-dependent kinase 5 for Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder and characterized by brain cell death, memory loss and is the most common form of dementia. Although AD has devastating effects, however, drugs which can treat the AD remain limited. The cyclin-dependent kinase 5 (CDK5) has been recognized as being involved in the pathological hyperphosphorylation of tau protein, which leads to the formation of neurofibrillary tangles (NFTs). We utilized the structure-based virtual screening (SBVS) approach to find the potential inhibitors against HsCDK5. The natural compound subset from the ZINC database (n = 167,741) was retrieved and screened by using SBVS method. From here, we have predicted 297 potent inhibitors. These 297 compounds were evaluated through their pharmacokinetic properties by ADMET (absorption, distribution, metabolism, elimination/excretion and toxicity) descriptors. Finally, 17 compounds were selected and used for re-docking. After the refinement by molecular docking and by using drug-likeness analysis, we have identified four potential inhibitors (ZINC85877721, ZINC96114862, ZINC96115616 and ZINC96116231). All these four ligands were employed for 100 ns MDS study. From the root mean square deviation (RMSD), root mean square fluctuation (RMSF), Rg, number of hydrogen bonds, solvent accessible surface area (SASA), principal component analysis (PCA) and binding free energy analysis we have found that out of four inhibitors ZINC85877721 and ZINC96116231 showed good binding free energy of -198.84 and -159.32 kJ.mol-1, respectively, and also good in other structural analyses. Both compounds displayed excellent pharmacological and structural properties to be the drug candidates. Collectively, these findings recommend that two compounds have great potential to be a promising agent against AD to reduce the CDK5 induced hyperphosphorylation and could be considered as therapeutic agents for the AD.Communicated by Ramaswamy H. Sarma.

Tunicate mitogenomics and phylogenetics: peculiarities of the Herdmania momus mitochondrial genome and support for the new chordate phylogeny.

BACKGROUND: Tunicates represent a key metazoan group as the sister-group of vertebrates within chordates. The six complete mitochondrial genomes available so far for tunicates have revealed distinctive features. Extensive gene rearrangements and particularly high evolutionary rates have been evidenced with regard to other chordates. This peculiar evolutionary dynamics has hampered the reconstruction of tunicate phylogenetic relationships within chordates based on mitogenomic data. RESULTS: In order to further understand the atypical evolutionary dynamics of the mitochondrial genome of tunicates, we determined the complete sequence of the solitary ascidian Herdmania momus. This genome from a stolidobranch ascidian presents the typical tunicate gene content with 13 protein-coding genes, 2 rRNAs and 24 tRNAs which are all encoded on the same strand. However, it also presents a novel gene arrangement, highlighting the extreme plasticity of gene order observed in tunicate mitochondrial genomes. Probabilistic phylogenetic inferences were conducted on the concatenation of the 13 mitochondrial protein-coding genes from representatives of major metazoan phyla. We show that whereas standard homogeneous amino acid models support an artefactual sister position of tunicates relative to all other bilaterians, the CAT and CAT+BP site- and time-heterogeneous mixture models place tunicates as the sister-group of vertebrates within monophyletic chordates. Moreover, the reference phylogeny indicates that tunicate mitochondrial genomes have experienced a drastic acceleration in their evolutionary rate that equally affects protein-coding and ribosomal-RNA genes. CONCLUSION: This is the first mitogenomic study supporting the new chordate phylogeny revealed by recent phylogenomic analyses. It illustrates the beneficial effects of an increased taxon sampling coupled with the use of more realistic amino acid substitution models for the reconstruction of animal phylogeny.