Browsing by Subject "Drug discovery"

The protein kinase C (PKC) enzyme is a type of peripheral membrane protein that is classified as a member of the Ser/Thr kinases superfamily. Its function is to add phosphate groups to serine or threonine residues in other proteins. The multitude of functions that PKC performs, and consequently its involvement in a diverse array of diseases, is attributed to the complicated nature of the enzyme: it consists of 12 distinct isoforms, each exhibiting minor variations in catalytic activity. Out of them, eight have therapeutic potential and utilize diacylglycerol (DAG) as a secondary signalling molecule. The research in this thesis is to perform computational modelling that assists an experimental research program searching for selective activators for PKC. The particular project involves combining molecular modelling with insight from structural biology. In concrete terms, three pieces of scientific work are involved: 1) The investigation of the behaviour in the membrane of drug candidate molecules that emerge as new scaffolds is developed by the experimental medicinal chemistry team. 2) Predicting the structure of PKCα, PKCδ, and PKCϵ using AlphaFold2 and evaluating their stability using molecular dynamic simulation. 3) Combining the predicted structures with DAG-containing membranes to examine predicted protein binding to the membrane. According to the results, 15 candidates out of 21 exhibited comparable behaviour to the positive control in terms of their angle of penetration into the membrane leaflets. Turning to regulatory domain prediction, all three proteins’ C1 and C2 domains were predicted with high confidence scores. All predicted structures showed root mean square deviation (RMSD) and root mean square fluctuation (RMSF) within the normal range, and most of their secondary structures were stable during simulation. When combined with the membrane, the C2 domains showed stable interactions with the membrane, and C2 binding to the membrane completely triggers C1 to bind to the membrane; however, there were some instabilities between the C1 domain binding and the membrane. This study highlights promising PKC activators, demonstrating the utility of computational modelling for identifying potential therapeutic agents.