A cystatin C similar protein from Musa acuminata that inhibits cathepsin B involved in rheumatoid arthritis using in silico approach and in vitro cathepsin B inhibition by protein extract.

Rheumatoid arthritis (RA) is an auto-immune disease that affects the synovial lining of the joints, causes synovitis and culminates to joint destruction. Cathepsin B is responsible for digesting unwanted proteins in extracellular matrix but its hyper expression could implicate in pathological diseases like RA. Available treatments for RA are classified into non-steroidal anti-inflammatory drugs (NSAIDs), disease-modifying anti-rheumatic drugs (DMARDs), and steroids, but the severe side effects associated with these drugs is one of concerns and cannot be ignored. Thus, any alternative therapy with minimum or no side effects would be a cornerstone. In our in silico studies a cystatin C similar protein (CCSP) has been identified from Musa acuminata that could effectively inhibit the cathepsin B activity. In silico and molecular dynamics studies showed that the identified CCSP and cathepsin B complex has binding energy -66.89 kcal/mol as compared to cystatin C - cathepsin B complex with binding energy of -23.38 kcal/mol. These results indicate that CCSP from Musa acuminata has better affinity towards cathepsin B as compared to its natural inhibitor cystatin C. Hence, CCSP may be suggested as an alternative therapeutic in combating RA by inhibiting its one of the key proteases cathepsin B. Further, in vitro experiments with fractionated protein extracts from Musa sp. peel inhibited cathepsin B to 98.30% at 300 µg protein concentration and its IC50 was found to be 45.92 µg indicating the presence of cathepsin B inhibitor(s) in protein extract of peel which was further confirmed by reverse zymography.Communicated by Ramaswamy H. Sarma.

In-silico screening and in-vitro assay show the antiviral effect of Indomethacin against SARS-CoV-2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the worldwide spread of coronavirus disease 19 (COVID-19), and till now, it has caused death to more than 6.2 million people. Although various vaccines and drug candidates are being tested globally with limited to moderate success, a comprehensive therapeutic cure is yet to be achieved. In this study, we applied computational drug repurposing methods complemented with the analyses of the already existing gene expression data to find better therapeutics in treatment and recovery. Primarily, we identified the most crucial proteins of SARS-CoV-2 and host human cells responsible for viral infection and host response. An in-silico screening of the existing drugs was performed against the crucial proteins for SARS-CoV-2 infection, and a few existing drugs were shortlisted. Further, we analyzed the gene expression data of SARS-CoV-2 in human lung epithelial cells and investigated the molecules that can reverse the cellular mRNA expression profiles in the diseased state. LINCS L1000 and Comparative Toxicogenomics Database (CTD) were utilized to obtain two sets of compounds that can be used to counter SARS-CoV-2 infection from the gene expression perspective. Indomethacin, a nonsteroidal anti-inflammatory drug (NSAID), and Vitamin-A were found in two sets of compounds, and in the in-silico screening of existing drugs to treat SARS-CoV-2. Our in-silico findings on Indomethacin were further successfully validated by in-vitro testing in Vero CCL-81 cells with an IC50 of 12 µM. Along with these findings, we briefly discuss the possible roles of Indomethacin and Vitamin-A to counter the SARS-CoV-2 infection in humans.

Polymorphisms at site 469 of B-RAF protein associated with skin melanoma may be correlated with dabrafenib resistance: An in silico study.

Melanoma is a type of skin cancer. Numerous genes and their proteins are strongly associated with melanoma susceptibility. This study aims to use an in silico method to identify genetic variants in the melanoma susceptibility gene. The COSMIC database was queried for genes and cross-referenced with three environment-gene interaction databases (EGP, SeattleSNPs and CTD) to identify shared genes. The majority of approved skin melanoma drugs were found to act on the protein serine/threonine-protein kinase (B-RAF) encoded by the BRAF gene, which was also present in all three referenced databases. Comprehensive computational analysis was performed to predict deleterious genetic variants associated with skin melanoma, and the nsSNPs G469V and G469E were prioritized based on their predicted deleterious effects. Molecular dynamic simulation analysis of the B-RAF protein mutants G469V and G469E reveals that variations in the amino acid conformation at the drug binding site result in inconsistency in drug interaction. Additionally, this analysis showed that the G469V and G469E mutants have lower binding energy for dabrafenib than the wild type. The population with the highest frequency of each deleterious and pathogenic variant has been determined. The study's findings would support the development of more effective treatment strategies for skin melanoma. Communicated by Ramaswamy H. Sarma.

Coronary arterial abnormalities detected in children over 10 years following initial Kawasaki disease using cardiac computed tomography.

OBJECTIVE: To evaluate whether Kawasaki disease predisposes to premature atherosclerosis and to assess status of coronary artery abnormalities at least 10 years after diagnosis. MATERIAL AND METHODS: A prospective study was carried out on 21 patients who were diagnosed with Kawasaki disease at least 10 years back and are on regular follow-up. The study was conducted on 128 Slice Dual Source computed tomography scanner with electrocardiography-triggered radiation optimised protocols for assessment of coronary artery abnormalities and calcifications. RESULTS: Study cohort had 21 subjects - 15 males and 6 females (age range: 11-23 years; mean: 15.76 + 3.72 years). Mean age at time of diagnosis was 3.21 + 2.48 years. Mean time interval from diagnosis of Kawasaki disease to computed tomography coronary angiography was 12.59 + 2.89 years. Four children had evidence of coronary artery abnormalities on transthoracic echocardiography at time of diagnosis. Of these, two had persistent abnormalities on computed tomography coronary angiography. One subject (4.76%) had coronary calcification that was localised to abnormal coronary artery segment. Four coronary artery abnormalities (one saccular; three fusiform aneurysms) were noted in two subjects. CONCLUSION: Prevalence of coronary artery calcification is low and, if present, is localised to abnormal segments. This calcification is likely dystrophic rather than atherosclerotic. It appears that coronary artery abnormalities can persist for several years after acute episode of Kawasaki disease. Periodic follow-up by computed tomography coronary angiography is now a feasible non-invasive imaging modality for long term surveillance of patients with Kawasaki disease who had coronary artery abnormalities at time of diagnosis.

Predicting MicroRNA Sequence Using CNN and LSTM Stacked in Seq2Seq Architecture.

CNN and LSTM have proven their ability in feature extraction and natural language processing, respectively. So, we tried to use their ability to process the language of RNAs, i.e., predicting sequence of microRNAs using the sequence of mRNA. The idea is to extract the features from sequence of mRNA using CNN and use LSTM network for prediction of miRNA. The model has learned the basic features such as seed match at first 2-8 nucleotides starting at the 5' end and counting toward the 3' end. Also, it was able to predict G-U wobble base pair in seed region. While validating on experimentally validated data, the model was able to predict on average 72 percent of miRNAs for specific mRNA and shows highest positive expression fold change of predicted targets on a microarray data generated using anti 25 miRNAs compare to other predicted tools. Codes are available at https://github.com/rajkumar1501/sequence-prediction-using-CNN-and-LSTMs.

In silico analysis of nsSNPs in ABCB1 gene affecting breast cancer associated protein P-glycoprotein (P-gp).

Breast cancer is one of the most common cancers among women and increased expression of some polymorphic genes, which is rare within families, enhances the risk of breast cancer incidence. The correct identification of the functional SNPs of such genes is important for characterizing the functional aspect of these SNPs which can be assessed by evaluating their significant influence on the structure and function of proteins. Since the presence of SNPs in these genes affects the quality of life of a breast cancer patient, thus, the associated diagnostic markers have a reliable potential for assessing the prognosis of breast cancer. ATP-binding cassette (ABC) genes have been shown to obstruct the treatment of breast cancer by providing resistance to malignant cells from anti-cancer drugs. Some allelic variants of ABCG2 and ABCB1 are also associated with occurrence of skin toxicity during the treatment of breast cancer with anti-cancer drugs. The present study has incorporated comprehensive bioinformatics analysis to explore the possible disease-associated mutations of ABCB1 gene, a gene that resulted from gene-environment interaction study, and understand their consequential effect on the structural and functional behavior of P-glycoprotein. Two gene variants (R538S and M701R) of P-glycoprotein were selected as potentially detrimental point mutations, and these variants were modeled. Molecular dynamic simulation (MDS) studies unraveled the atomic interactions and motion trajectories of the native as well as the two mutant (R538S and M701R) structures and were predicted to have a deleterious effect on breast cancer associated P-gp. Thus, the present study may broaden the way to design novel potent drugs for overcoming the problems associated with multidrug resistance (MDR) resulting from a change in protein conformation due to a mutation in ABCB1 gene.