Dr Alessandro Pandini
Senior Lecturer in Computer Science
My research activity focuses on the development and application of computational methods to study protein dynamics and its role in protein-ligand binding, protein-protein interactions, and protein design.
I obtained my PhD in Computational Chemistry at the University of Milan-Bicocca under the supervision of Prof. Laura Bonati. As part of her research group I contributed to the unveil the molecular mechanism of toxic response mediated by binding of dioxins to the Aryl hydrocarbon Receptor. In 2008 I was awarded a Marie Curie Inter European Fellowship to work at the MRC National Institute for Medical Research (NIMR) under the supervision of Dr. Willie R. Taylor and Dr. Jens Kleinjung. From 2011 to 2014 he was a BBSRC-funded postdoctoral research assistant in the group of Prof. Franca Fraternali at King’s College London working on methods to investigate allosteric regulation, and to analyse protein-protein interaction interfaces and networks.
During my career I developed and applied novel approaches combining structural bioinformatics and molecular simulation to address challenging biological questions, especially in relation to protein function, allosteric regulation and drug design. I introduced novel points of view in the definition of the limits and potential of molecular docking on theoretical models and in the use of molecular dynamics for drug design and medicinal chemistry. In particular, I developed an innovative computational method to detect local functional motions and to describe allosteric transmission in protein structures.
Most recently, in collaboration with Dr. Arianna Fornili (QMUL), I contributed to the development of a novel strategy for biasing the sampling of local states to drive the global conformational transitions in proteins. In collaboration with Dr. Shahid Khan (LBNL – Berkeley Lab) and Dr. Willie Taylor, I have contributed to explain the relationships between residue coevolution and molecular dynamics in two bacterial ring assemblies.
Newest selected publications
Li, T., Motta, S., Stevens, AO., Song, S., Hendrix, E., Pandini, A. and (2022) 'Recognizing the Binding Pattern and Dissociation Pathways of the p300 Taz2-p53 TAD2 Complex'. JACS Au, 0 (in press). pp. 1935 - 1945. ISSN: 2691-3704 Open Access Linket al.
Motta, S., Callea, L., Bonati, L. and Pandini, A. (2022) 'PathDetect-SOM: A Neural Network Approach for the Identification of Pathways in Ligand Binding Simulations'. Journal of Chemical Theory and Computation, 18 (3). pp. 1957 - 1968. ISSN: 1549-9618 Open Access Link
Marchetti, F., Moroni, E., Pandini, A. and Colombo, G. (2021) 'Machine Learning Prediction of Allosteric Drug Activity from Molecular Dynamics'. The Journal of Physical Chemistry Letters, 12 (15). pp. 3724 - 3732. ISSN: 1948-7185 Open Access Link
Motta, S., Pandini, A., Fornili, A. and Bonati, L. (2021) 'Reconstruction of ARNT PAS-B Unfolding Pathways by Steered Molecular Dynamics and Artificial Neural Networks'. Journal of chemical theory and computation, 17 (4). pp. 2080 - 2089. ISSN: 1549-9618 Open Access Link
Meli, M., Pandini, A. and Morra, G. (2021) 'Editorial: Computational Drug Discovery for Targeting of Protein-Protein Interfaces'. Frontiers in Chemistry, 9. pp. 1 - 2. ISSN: 2296-2646 Open Access Link