Research Projects

ChatGPT is a language model developed by OpenAI. It is a machine learning model that has been trained on a large dataset of human language, allowing it to generate human-like text. It can be used for a variety of natural language processing tasks such as language translation, text summarization, and question answering. In the current work we have discussed the application of ChatGPT in drug discovery

This study explored the substrate promiscuity of glycerophosphodiesterase (GpdQ) through the hydrolysis of different types of phosphoesters. They compared different mechanisms and found that GpdQ prefers diester substrates, followed by tri- and monoesters. The findings align with experimental data and provide insights for designing optimized catalysts.

Using molecular dynamics simulations, the study examined how the MLN-4760 inhibitor affects ACE2 and its interaction with the SARS-CoV-2 spike protein. 

The study explored the interactions between glycerophosphodiesterase (GpdQ) and various substrates using molecular dynamics simulations. It revealed the roles of metal ions, amino acid residues, and coordination flexibility in the enzyme-substrate complexes. The substrate's chemical nature influenced binding, electrostatic potential, and active site reorganization. 

The study found that a chemical compound called [Re(CO)3(dppz)(Py)]+ can bind to Alzheimer's-related Aβ fibrils. When exposed to light, the compound undergoes changes and oxidizes the fibril. Computer simulations predict binding in a hydrophobic crevice between Val18 and Phe20. Oxidation occurs at Met35.

We used structure-activity relationships to identify new compounds that inhibit the SARS-CoV-2 main protease. Four rules for designing effective inhibitors have been proposed, guiding medicinal chemists in the search for potential treatments. A potential lead compound, GB111-NH2, has been identified based on these rules.