Relevant papers
Concilio, S., Di Martino, M., Nardiello, A. M., Panunzi, B., Sessa, L., Miele, Y., . . . Piotto, S. (2020). A flavone-based solvatochromic probe with a low expected perturbation impact on the membrane physical state. Molecules, 25(15). doi:10.3390/molecules25153458
Di Martino, M., Sessa, L., Panunzi, B., Diana, R., Piotto, S., & Concilio, S. (2024). Cationic Azobenzenes as Light-Responsive Crosslinkers for Alginate-Based Supramolecular Hydrogels. Polymers, 16(9). doi:10.3390/polym16091233
Diana, R., Sessa, L., Concilio, S., Piotto, S., Di Costanzo, L., Carella, A., & Panunzi, B. (2024). Experimental and Theoretical Insights into a Novel Lightfast Thiophene Azo Dye. Crystals, 14(1). doi:10.3390/cryst14010031
Piotto, S., Di Biasi, L., Sessa, L., & Concilio, S. (2018). Transmembrane peptides as sensors of the membrane physical state. Frontiers in Physics, 6(MAY). doi:10.3389/fphy.2018.00048
Sarkar, A., Concilio, S., Sessa, L., Marrafino, F., & Piotto, S. (2024). Advancements and novel approaches in modified AutoDock Vina algorithms for enhanced molecular docking. Results in Chemistry, 7. doi:10.1016/j.rechem.2024.101319
Sarkar, A., Santoro, J., Biasi, L. D., Marrafino, F., & Piotto, S. (2022). YAMACS: a graphical interface for GROMACS. Bioinformatics, 38(19), 4645-4646. doi:10.1093/bioinformatics/btac573
Sarkar, A., Sessa, L., Marrafino, F., & Piotto, S. (2023). GUIDE: A GUI for automated quantum chemistry calculations. Journal of Computational Chemistry, 44(25), 2030-2036. doi:10.1002/jcc.27177
Sessa, L., Concilio, S., Di Martino, M., Nardiello, A. M., Miele, Y., Rossi, F., . . . Piotto, S. (2021). A selective Nile Red based solvatochromic probe: A study of fluorescence in LUVs and GUVs model membranes. Dyes and Pigments, 196. doi:10.1016/j.dyepig.2021.109759
Sessa, L., Nardiello, A. M., Santoro, J., Concilio, S., & Piotto, S. (2021). Hydroxylated fatty acids: The role of the sphingomyelin synthase and the origin of selectivity. Membranes, 11(10). doi:10.3390/membranes11100787
Projects
The aim of the NEWROAD project is to develop an EU-wide capability for Systematic Drug Repurposing (SDR). To achieve this NEWROAD will develop an open, collaborative in silico platform for the repurposing of drugs in oncology based on Augmented Intelligence (AuI) architecture layered on top of Artificial Intelligence (AI) algorithms, initially targeted at rare and paediatric cancer research
The MIND (Molecules Inhibiting Neurological Diseases) project we are working on involves the application of SoftMining Artificial Intelligence-based platform for the design, synthesis and preclinical characterization of molecules for neurological diseases.