Prediction of deleterious non-synonymous SNPs of TMPRSS2 protein combined with Molecular Dynamics Simulations and free energy analysis to identify the potential peptide substrates against SARS-CoV-2

Balajee Ramachandrana Structural and Computational Biology Lab, Department of Bioinformatics, Alagappa University, Science Block, Karaikudi, Tamil Nadu, India;b Department of Pharmacology, Physiology and Biophysics, Boston University School of Medicine, Boston, MA, USAView further author information

Ahmed Nadeemc Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi ArabiaView further author information

Aruchamy Mohanprasanthd AMR & Nanotherapeutics Lab, Department of Pharmacology, Saveetha Dental College, Saveetha Institute of Medical and Technical, Sciences (SIMATS), Chennai, Tamil Nadu, IndiaView further author information

Muthupandian Saravanand AMR & Nanotherapeutics Lab, Department of Pharmacology, Saveetha Dental College, Saveetha Institute of Medical and Technical, Sciences (SIMATS), Chennai, Tamil Nadu, IndiaCorrespondence[email protected]
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Prediction of deleterious non-synonymous SNPs of TMPRSS2 protein combined with Molecular Dynamics Simulations and free energy analysis to identify the potential peptide substrates against SARS-CoV-2

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Prediction of deleterious non-synonymous SNPs of TMPRSS2 protein combined with Molecular Dynamics Simulations and free energy analysis to identify the potential peptide substrates against SARS-CoV-2

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