Area of research
Molecular Biology · Computational Theory and Mathematics
Research interest
Research interests include Computational Drug Discovery Methods, Protein Structure and Dynamics, RNA and protein synthesis mechanisms, and Machine Learning in Materials Science.
The chaperone PrsA2 regulates the secretion, stability, and folding of listeriolysin O during <i>Listeria monocytogenes</i> infection
Mesoscale All-Atom Influenza Virus Simulations Suggest New Substrate Binding Mechanism
Emerging Computational Methods for the Rational Discovery of Allosteric Drugs
POVME 2.0: An Enhanced Tool for Determining Pocket Shape and Volume Characteristics
Weighted Implementation of Suboptimal Paths (WISP): An Optimized Algorithm and Tool for Dynamical Network Analysis
Computational approaches to mapping allosteric pathways
LipidWrapper: An Algorithm for Generating Large-Scale Membrane Models of Arbitrary Geometry
Machine‐Learning Techniques Applied to Antibacterial Drug Discovery
Celastrol inhibits Plasmodium falciparum enoyl-acyl carrier protein reductase
AutoGrow 3.0: An improved algorithm for chemically tractable, semi-automated protein inhibitor design
Comparing Neural-Network Scoring Functions and the State of the Art: Applications to Common Library Screening
AutoClickChem: Click Chemistry in Silico
Novel Cruzain Inhibitors for the Treatment of Chagas’ Disease
LigMerge: A Fast Algorithm to Generate Models of Novel Potential Ligands from Sets of Known Binders
The Molecular Dynamics of <i>Trypanosoma brucei</i> UDP‐Galactose 4′‐Epimerase: A Drug Target for African Sleeping Sickness