Dissertations, Theses, and Capstone Projects

Date of Degree


Document Type


Degree Name





Emilio Gallicchio

Committee Members

Richard Magliozzo

Lauren Wickstrom

Sharon Loverde

Piero Procacci

Subject Categories

Computational Chemistry


Free Energy Perturbation, Binding Free Energy, Relative Binding Free Energy, Absolute Binding Free Energy, Alchemical Transfer Method


Molecular recognition plays a crucial role in various biological processes, such as enzymatic reactions, signal transduction, and genetic information processing. Investigating how proteins selectively bind to their partners is an active research area, but there is a lack of experimental details on protein structures and interactions in molecular complexes. Computational techniques based on macromolecular structures offer a way to predict protein-ligand interactions and explore their recognition mechanisms. Estimating binding affinities, particularly through alchemical binding free energy calculations, has become valuable in supporting drug discovery. This work introduces new methodologies, utilizing the Alchemical Transfer Method, to address issues like poor convergence and conformational bias in binding free energy calculations. The primary undertaking in this thesis aims to enhance accuracy by assessing statistical fluctuations, calculating ligand reorganization energy, and employing enhanced sampling techniques to eliminate conformational bias and improve system variance. Together, these approaches enhance the precision of binding free energy calculations and reduce mis-predictions caused by limited conformational sampling.