Abstract

Heat shock proteins-47 (HSP47) is a collagen specific molecular chaperone, involved in the processing and/or secretion of procollagen. It seems to be regularly upregulated in various fibrotic or collagen disorders. Hence, this protein can be a potential target for the treatment of various fibrotic diseases including oral submucous fibrosis (OSF), which is a collagen metabolic disorder of oral cavity and whose etiopathogeneic mechanism and therapeutic protocols are still not well documented. The aim of this study is to identify the novel therapeutic agents using in-silico methods for the management of OSF. The objectives of this study are to identify the binding sites of HSP47 on the collagen molecule and to identify the lead compound with anti-HSP47 activity from the library of natural compounds, using in-silico methodology. The web-based and tool based in-silico analysis of the HSP47 and collagen molecules are used in this study. The crystal structure of collagen and HSP47 were retrieved from Protein Data Bank website. The binding site identification and the docking studies are done using Molegro Virtual Docker offline tool. Out of the 104 Natural compounds, six ligands are found to possess best binding affinity to the binding amino acid residues. Silymarin binds with the 4AU2A receptor and the energy value are found to be -178.193 with four Hbonds. The other best five natural compounds are hesperidin, ginkgolides, withanolides, resveratrol, and gingerol. Our findings provide the basis for the in-vitro validation of the above specified compounds, which can possibly act as "lead" molecules in designing the drugs for OSF. HSP47 can be a potential candidate to target, in order to control the production of abundance collagen in OSF. Hence, the binding sites of HSP47 with collagen are identified and some natural compounds with a potential to bind with these binding receptors are also recognized. These natural compounds might act as anti-HSP47 lead molecules in designing novel therapeutic agents for OSF, which are so far unavailable.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.