Research

Systems and network pharmacology

We integrate biological data across various levels of organization, such as genomics, proteomics, and metabolomics. By doing so, we gain a better understanding of the intricate interactions between drugs and biological pathways in the body. This knowledge strengthens our ability to design drugs that target multiple targets/pathways simultaneously, achieving better and more comprehensive therapeutic outcomes. Our approach offers a promising direction toward developing more effective treatments for a range of complex diseases.

Structural bioinformatics

We use of computational methods such as molecular dynamics simulations, to predict and analyze the structure of protein-ligand complexes, which can be used to identify potential therapeutic targets and design new drugs. Furthermore, we validate our findings through experimental testing to ensure their accuracy and reliability. Our approach in structural bioinformatics offers a promising avenue for discovering novel treatments for a range of diseases.

Multitarget drug design aimed at complex diseases

We employed machine learning and artificial intelligence to analyze large datasets and identify novel targets. We then designed new molecules using this information to create multitarget-directed ligands. The designed molecules are tested and optimized through medicinal chemistry campaigns.