02677nas a2200313   4500000000100000008004100001260001200042653004100054653002000095653002900115653001400144653002500158653002200183100001400205700001500219700001300234700001200247700003300259700001200292700001500304700001300319700001500332245011700347856007000464300001400534490000700548520179400555022001402349       2020                            d  c01/202010aComputational saturation mutagenesis10aDrug resistance10aInteratomic interactions10aMutations10aMycobacterium leprae10aProtein stability1 aVedithi S1 aMalhotra S1 aSkwark M1 aMunir A1 aAcebrón-García-de-Eulate M1 aWaman V1 aAlsulami A1 aAscher D1 aBlundell T00aHARP: a database of structural impacts of systematic missense mutations in drug targets of Mycobacterium leprae.  uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7711215/pdf/main.pdf  a3692-37040 v183 a<p>Computational Saturation Mutagenesis is an  approach that employs systematic mutagenesis of each amino acid residue in the protein to all other amino acid types, and predicts changes in thermodynamic stability and affinity to the other subunits/protein counterparts, ligands and nucleic acid molecules. The data thus generated are useful in understanding the functional consequences of mutations in antimicrobial resistance phenotypes. In this study, we applied computational saturation mutagenesis to three important drug-targets in  for the drugs dapsone, rifampin and ofloxacin namely Dihydropteroate Synthase (DHPS), RNA Polymerase (RNAP) and DNA Gyrase (GYR), respectively.  causes leprosy and is an obligate intracellular bacillus with limited protein structural information associating mutations with phenotypic resistance outcomes in leprosy. Experimentally solved structures of DHPS, RNAP and GYR of  are not available in the Protein Data Bank, therefore, we modelled the structures of these proteins using template-based comparative modelling and introduced systematic mutations in each model generating 80,902 mutations and mutant structures for all the three proteins. Impacts of mutations on stability and protein-subunit, protein-ligand and protein-nucleic acid affinities were computed using various in-house developed and other published protein stability and affinity prediction software. A consensus impact was estimated for each mutation using qualitative scoring metrics for physicochemical properties and by a categorical grouping of stability and affinity predictions. We developed a web database named HARP (a database of ansen's Disease ntimicrobial esistance rofiles), which is accessible at the URL -  and provides the details to each of these predictions.</p>  a2001-0370