Our results suggest that the DYT1 gene might have a limited role in causation of dystonia in the Indian population.

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Graphic abstract The Coronavirus disease 2019 (COVID-19), caused by the novel coronavirus, SARS-CoV-2, has recently emerged as a pandemic. Here, an attempt has been made through in-silico high throughput screening to explore the antiviral compounds from traditionally used plants for antiviral treatments in India namely, Tea, Neem and Turmeric, as potential inhibitors of two widely studied viral proteases, main protease (Mpro) and papain-like protease (PLpro) of the SARS-CoV-2. Molecular docking study using BIOVIA Discovery Studio 2018 revealed, (−)-epicatechin-3-O-gallate (ECG), a tea polyphenol has a binding affinity toward both the selected receptors, with the lowest CDocker energy − 46.22 kcal mol −1 for SARS-CoV-2 Mpro and CDocker energy − 44.72 kcal mol −1 for SARS-CoV-2 PLpro, respectively. The SARS-CoV-2 Mpro complexed with (−)-epicatechin-3-O-gallate, which had shown the best binding affinity was subjected to molecular dynamics simulations to validate its binding affinity, during which, the root-mean-square-deviation values of SARS-CoV-2 Mpro–Co-crystal ligand (N3) and SARS-CoV-2 Mpro- (−)-epicatechin-3-O-gallate systems were found to be more stable than SARS-CoV-2 Mpro system. Further, (−)-epicatechin-3-O-gallate was subjected to QSAR analysis which predicted IC 50 of 0.3281 nM against SARS-CoV-2 Mpro. Overall, (−)-epicatechin-3-O-gallate showed a potential binding affinity with SARS-CoV-2 Mpro and could be proposed as a potential natural compound for COVID-19 treatment. Supplementary Information The online version contains supplementary material available at 10.1007/s11030-021-10211-9.

Parkinson's disease (PD) is a neurodegenerative disease with the absence of markers for diagnosis. Several studies on PD reported the elements imbalance in biofluids as biomarkers. However, their results remained inconclusive. This study integrates metallomics, multivariate and artificial neural network (ANN) to understand element variations in CSF and serum of PD patients from the largest cohort of Indian population to solve the inconsistent results of previous studies. Also, this study is aimed to (1) ascertain a common element signature between CSF and serum. (2) Assess cross sectional element variation with clinical symptoms. (3) Develop ANN models for rapid diagnosis. A metallomic profile of 110 CSF and 530 serum samples showed significant variations in 10 elements of CSF and six in serum of patients compared to controls. Consistent variations in elements pattern were noticed for Calcium, Magnesium and Iron in both the fluids of PD, which provides feasible diagnosis from serum. Furthermore, implementing multivariate analyses showed clear classification between normal and PD in both the fluids. Also, ANN provides 99% accuracy in detection of disease from CSF and serum. Overall, our analyses demonstrate that elements profile in biofluids of PD will be useful in development of diagnostic markers for PD.

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