Integrated machine learning-based virtual screening and biological evaluation for identification of potential inhibitors against cathepsin K.

Cathepsin K is a type of cysteine proteinase that is primarily expressed in osteoclasts and has a key role in the breakdown of bone matrix protein during bone resorption. Many studies suggest that the deficiency of cathepsin K is concomitant with a suppression of osteoclast functioning, therefore rendering the resorptive properties of cathepsin K the most prominent target for osteoporosis. This innovative work has identified a novel anti-osteoporotic agent against Cathepsin K by using a comparison of machine learning and deep learning-based virtual screening followed by their biological evaluation.

Identification of novel TACE inhibitors using DNN based- virtual screening, molecular dynamics and biological evaluation.

Rheumatoid Arthritis (RA) is a well-known autoimmune inflammatory disease, distressing roughly 1% of the adult population throughout the globe. Many studies have suggested that overexpression of TNF-α, a pro-inflammatory cytokine, is responsible for the progression of RA. Furthermore, inhibition of the shedding rate of TNF-α is regulated by the TACE (TNF-α converting enzyme) protein and, hence is considered as an important therapeutic target for the prevention of progressive synovial joint destruction in rheumatoid arthritis.