Academic Appointments:

Associate Professor (Sept. 2020), Chemistry Department, Brooklyn College, The City University of New York
Doctoral Faculty, Chemistry PhD Program, The Graduate Center, The City University of New York
Doctoral Faculty, Biochemistry PhD Program, The Graduate Center, The City University of New York

Degree(s)

Ph.D. Chemical Physics (1996), Columbia University, New York, NY
M.Phil. Chemical Physics (1994), Columbia University, New York, NY
M.A. Chemistry (1992), Columbia University, New York, NY 

Research Focus:

My background is in statistical thermodynamic theory and computational modeling. My laboratory is primarily involved in the development and application of  molecular computational models of protein-drug binding and macromolecular molecular recognition phenomena.  The overall aim of the research is to deploy sophisticated molecular theories, efficient algorithms, and powerful computers to characterize fundamental chemical and biological mechanisms and work with colleagues to help address human health issues.  The specific application area we are currently targeting  is the computational screening of potential drugs against protein receptors using massive atomistic computer simulations and accurate free energy models. Computer models are nowadays an important and established component of modern and interdisciplinary structure-based drug discovery programs. The advanced molecular dynamics-based binding free energy methods that we target, in particular, are attractive because they can yield estimates of binding constants useful for ranking the inhibitory potency of drug candidates and for direct comparison to binding affinity measurements. Computational studies of this kind yield valuable information about the energetic, structural, and dynamical behavior of drug-receptor complexes to complement medicinal chemistry efforts. Our research is intrinsically collaborative and interdisciplinary. As illustrated by the published works below, we regularly partner with medicinal chemistry laboratories to increase the chance of success of drug discovery programs against viral infections, cancer, and drug addiction among others.

Selected Recent Publications

1. Rajat K. Pal and Emilio Gallicchio. Perturbation Potentials to Overcome Order/Disorder Transitions in Alchemical Binding Free Energy Calculations. Chem. Phys. 151, 124116 (2019).
2. Rajat K. Pal, Steve Ramsey, Satishkumar Gadhiya, Pierpaolo Cordone, Lauren Wickstrom, Wayne W Harding, Tom Kurtzman, Emilio Gallicchio. Inclusion of Enclosed Hydration Effects in the Binding Free Energy Estimation of Dopamine D3 Receptor Complexes. PLoS ONE 14(9): e0222902 (2019).
3. Denise Kilburg and Emilio Gallicchio. Assessment of a Single Decoupling Alchemical Approach for the Calculation of the Absolute Binding Free Energies of Protein-Peptide Complexes. Frontiers Molecular Biosciences: Molecular Recognition 5, 22 (2018).
4. Baofeng Zhang, Denise Kilburg, Peter Eastman, Vijay S. Pande, Emilio Gallicchio. Efficient Gaussian Density Formulation of Volume and Surface Areas of Macromolecules on Graphical Processing Units. Comp. Chem. (2017).
5. Baofeng Zhang, Michael P. D’Erasmo, Ryan P. Murelli, Emilio Gallicchio. Free Energy-Based Virtual Screening and Optimization of RNase H Inhibitors of HIV-1 Reverse Transcriptase. ACS Omega. 1, 435-447 (2016).

Grants over the last 5 years

Emilio Gallicchio, PI
NSF CAREER
1750511
Theory, Models and Computer Simulation of Molecular Recognition Processes
9/1/2018-8/31/2023