Future drugs and therapeutic strategies will be designed to target gene regulation. However, understanding the molecular basis underlying gene editing and regulation remains a major challenge. In our lab, we use state-of-the-art computational methods, combining physics, chemistry and computational engineering, to unravel the function and improve application of key macromolecules responsible for gene editing and regulation. Our goal is to provide fundamental knowledge at the molecular level for the treatment of cancer and genetic diseases.
Mechanistic understanding and design of CRISPR-Cas9
The field of biology is experiencing a transformative phase, due to the recent discovery of a revolutionary genome editing technology, based on the CRISPR-Cas9 system. Our research aims at unravelling the mechanistic basis and at improving biological applications of this unique genome-editing machinery. This research is performed in collaboration with Profs. Martin Jinek (University of Zürich) and Jennifer A. Doudna (UC Berkeley).
Dissecting the mechanistic basis of non-coding RNA
RNA is a fundamental molecule that codes for protein and controls gene expression, playing a key regulation role in many cell responses and vital processes, such as human genetic heritance and diseases. We are interested in clarifying the molecular basis of non-coding RNA, which regulates gene expression via a variety of yet unknown mechanisms. We have suggested a mechanism for the splicing reaction in the bacterial groupII intron, and studied the functional dynamics of the human splicesome.
As originally revealed by Steitz & Steitz (PNAS 1993, 90), DNA/RNA endonucleases perform phosphodiester bond cleavage via a two-metal-ion aided mechanism. We are using computational methods to clarify the two-metal aided mechanism in several endonucleases. Our specific interest in understanding the role of metal ions and the functional differences in the catalysis of RNA & DNA.
Nucleosome dynamics and chromatin drug development
The constituents of chromatin, chromosomal DNA and histone proteins, are key molecular targets for anticancer drugs. By integrating molecular dynamics with X-ray crystallography and biochemical assays in collaboration with Profs. Paul J. Dyson (EPFL) and Curtis A. Davey (NTU-Singapore), we have characterized the mechanism of action of promising metal-based anticancer agents at the level of the nucleosome core particle, the fundamental unit of chromatin. This integrated research deciphered the corresponding relationships to cytotoxicity and impact on cancer cell function.
The Fatty Acid Amide Hydrolase is a key membrane protein involved in the control of pain, cancer and immune diseases. By using molecular dynamics techniques, including free energy methods and ab-initio MD, flanked by estensive analyses using Bayesian statistics and Machine Learning, I have clarified the mechanisms of lipid selection and degradation in the enzyme, with significant insights for the discovery of targeting drugs.
Density Functional Theory for Solar Cells technology
Solar cells are the energy revolution of the 21th century, converting solar energy in electricity. By using Density Functional Theory (DFT), I have characterised the atomistic and electronic structure nature of hybrid organic-inorganic perovskites, novel materials for solar cells technology. Our outcomes have been integrated with the experiments of the lab of Prof. M, Graetzel for developing more efficient solar cells technologies.
A duel with pain: multi-target drug discovery
Multi-target drug discovery is promising for the development of innovative drugs. By applying molecular simulations and free energy methods, I have clarified the mechanism of action of ARN2508, a novel anti-inflammatory agent that inhibits both the Fatty Acid Amide Hydrolase (FAAH) and the cyclooxygenase (COX) enzymes. With this research, we provide the basis of dual inhibition for anti-inflammatory treatments.
Read more: ChemMedChem 2016, 11, pp 1252 –1258
My initial work has been focused on the development of methods for the prediction – based on the Karplus and Altona models – of NMR coupling constants (3JC-H), which are of key importance for the structural elucidation of bioorganic and pharmaceutically relevant compounds. Based on Density Functional Theory (DFT), I have formally derived a general 3JC-H prediction equation, which is used as a support to NMR experiments for the structural elucidation of organic compounds.
Read more: J. Org. Chem., 2010, 75, pp 1982–1991