Molecular Simulations and Machine Learning Methods for the Identification of Novel Aurora A Kinase Inhibitors Aurora kinase A (AAK) is a critical regulator of mitosis, the process of cell division. It plays essential roles in cell cycle regulation, centrosome maturation, spindle assembly, and chromosome segregation, all crucial for accurate daughter cell formation. Deregulation of AAK […]
Identification of Mycobacterium tuberculosis transcriptional repressor EthR inhibitors Tuberculosis (TB) has plagued humanity since prehistoric times, and the rise of drug-resistant strains has only made it harder to combat. Ethionamide (ETH), a second-line drug, targets mycolic acid synthesis in TB bacteria but requires activation by the EthR protein. Our research has focused on finding new […]
Machine learning assisted methods for the identification of low toxicity inhibitors of Enoyl-Acyl Carrier Protein Reductase (InhA) Tuberculosis, a deadly disease with ancient roots, continues to pose a global health threat. We have employed artificial intelligence and machine learning integrated approaches to identify potential new treatments by targeting the InhA protein in the tuberculosis-causing bacteria. […]