Lab-Mori: Computations & Biophysics in Medicinal Chemistry 

Lab-Mori is a medicinal chemistry research group at the Department of Biotechnology, Chemistry and Pharmacy of the University of Siena.

Research Activity. We aim to develop and apply computational modeling approaches in the interrogation of biomolecular recognition/binding and in supporting the discovery and optimization of bioactive small molecules. By extracting mechanistic insights from structural models, we analyze and interpret inter- and intra-molecular interactions, conformational dynamics, and physicochemical determinants relevant to structural features and intermolecular binding. From a drug design perspective, this leads to the prioritization and optimization of small molecules up to preclinical/drug candidates. The research areas mainly concern antimicrobial resistance (AMR) and cancer.

Antimicrobial Resistance. We investigate three complementary target classes: (i) membranes, to understand interaction and perturbation patterns relevant to antimicrobial agents such as polymyxins; (ii) nucleic acids, with a strong emphasis on G-quadruplex structures as non-canonical motifs of functional relevance; and (iii) proteins, including metallo-beta-lactamases that are involved in bacterial resistance to beta-lactam antibiotics (e.g., penicillins, cephalosporins, monobactams, and carbapenems).

Anticancer Discovery. We study cancer-related enzymes and pathways, including aldehyde dehydrogenases (ALDH), carbonic anhydrases, and the Hedgehog signaling pathway, with the goal of identifying and optimizing small molecule modulators of pharmacologic relevance by rationally assess ligand binding modes and structure–activity relationships.

Methods and Facilities. Our workflow includes chemioinformatics, virtual screening, molecular docking, MD simulations, and QM/MM approaches. Computational results are integrated with measurements from our biophysical laboratory, leveraging CD and UV–Vis spectroscopy to assist in structural characterization and to support experimental validation.