Garza Lab

Pomona College

Department of Chemistry

Claremont, California

Leveraging computational chemistry to study protein dynamics and design novel therapeutics for complex biological targets.

Front cover articles

Natural Sciences · 2025

Copper(II) Inhibition of the SARS-CoV-2 Main Protease

Biophysical Journal · 2026

Multivalent Binding Mechanism of LRP1-Fibrinogen Interaction

The Garzanians

The “Garzanian” name was born from Dr. Kendall Houk’s visit to Pomona College as the 2026 Robbins Lecturer. Houk, a founding father in the field of computational organic chemistry, recognized that Dr. Garza was doing more than just teaching: he was building a unique, high-energy culture of scientific excellence. During his visit, Houk dubbed the research group as the "Garzanians." The name stuck immediately, serving as a way to distinguish the contributions made towards computational chemistry from the Garza Lab.

Research

The Garza Lab pursues a fundamental question at the intersection of computational biophysics and structure-based drug design: how are proteins regulated dynamically by ligand binding, post-translational modifications, and their molecular environment, and how can this knowledge be harnessed to develop better therapeutics?

We utilize advanced molecular modeling and physics-based simulations to visualize protein motions at atomic resolution that are invisible to traditional experimental methods.

By combining the rigorous "Garzanian" approach with state-of-the-art computational tools, we seek to accelerate the development of life-saving treatments for diseases on all fronts. We welcome collaborations with researchers interested in atomic‑level characterization of biological processes and drug discovery.

Intrinsically Disordered Proteins

Intrinsically disordered proteins lack a single fixed structure, instead existing as an ensemble of rapidly interconverting conformations. Because they present no stable binding pocket, they remain largely undruggable by conventional structure-based drug design methods. We use molecular dynamics and enhanced sampling simulations to reveal conformations at the atomic level inaccessible by experiment. Recent work in our group has characterized a previously unidentified intrinsically disordered region of the HPV-16E6 oncoprotein.

Selected work

Liam Kwak, Roberto A Garza-López, "Conformational Dynamics and Disorder of HPV-16 E6," J. Phys. Chem. B (2026), 10.1021/acs.jpcb.6c04908.

Allosteric Modulation

Allosteric sites sit away from a protein’s primary binding pocket, yet ligands that occupy them can tune activity rather than switch it off, and because these sites are less conserved they offer selectivity that orthosteric drugs rarely achieve. The effect is kinetic as much as structural: an allosteric modulator can reshape how long an orthosteric ligand stays bound. We use unbinding kinetics simulations, which drive ligand release under an applied bias to recover residence times far longer than conventional MD can reach, together with pathway analysis to identify the residues that gate exit. Recent work in our group uncovered the molecular basis of μ-opioid receptor allosteric modulators using unbinding kinetics simulations.

Selected work

Liam Kwak, Roberto A Garza-López, "Mechanistic Basis of μ-Opioid Receptor Allosteric Modulation from Molecular Simulations", Preprint: ChemRxiv (2026), 10.26434/chemrxiv.15010296/v1.

Protein-Protein Interactions

Protein-protein interactions organize nearly every cellular process, and the interfaces they form are often large, shallow and transient rather than pocket-like, which makes both their mechanism and their inhibition difficult to resolve experimentally. Identifying the specific residue contacts that hold an interface together is a prerequisite for disrupting or stabilizing it with a drug. We use physics-based molecular docking together with MD simulations to obtain time-series interaction data at atomic resolution, working with experimental collaborators to give mechanistic insight into binding. Recent work in our group has resolved the multivalent binding mechanism of the LRP1-fibrinogen interaction alongside QCM-D measurements.

Selected work

Liam Kwak, Kevin Ye, Ananya Vinay, Gabby Lewis, Alyssa Yao, Daniel L Gao, Roberto A Garza-López, Malkiat S Johal, "Multivalent Binding Mechanism of LRP1-Fibrinogen Interaction Revealed by QCM-D and Molecular Dynamics", Biophys. J. 125, 1059-1069, 10.1016/j.bpj.2026.01.008.

Enzyme Catalysis

Enzymes accelerate reactions by many orders of magnitude, and that catalytic power rests on precise arrangements of active-site residues, cofactors and metal centers that reorganize as substrate binds. Resolving how those contacts form, and how a small molecule can compete with them, is the basis for designing selective inhibitors. We combine induced-fit docking which allows the active site to relax around a candidate ligand, with QM/MM simulations to characterize binding modes and their energetics. Recent work in our group has resolved a Cu(II) dependent binding mechanism of flavonoids to human tyrosinase using induced-fit docking and QCM-D.

Selected work

Ita Junhee Lee, Ian Tam, Ryan M Mooney, Tenley Overdeck, Liam Kwak, Roberto A Garza-López, Malkiat S Johal, "Quantitative Analysis of Flavonoid Binding to Tyrosinase by Quartz Crystal Microbalance and Molecular Dynamics," Langmuir (2026), 10.1021/acs.langmuir.6c04466.

Computer-Aided Drug Design

In-silico prediction of drug potency has emerged as a cost-efficient yet effective method during the early stages of drug design. We use computer-aided drug design (CADD) techniques such as physics-based high-throughput virtual screening (HTVS) to filter large databases of molecules for lead compounds and scaffolds. We use MD simulations and free energy calculations of lead compounds to inform future stages of drug development. Furthermore, we employ quantitative structure-activity relationship (QSAR) models to more efficiently process large datasets.

Selected work

Ian Tam, Andrew Chung, Liam Kwak, Roberto A Garza-López, "Structure-Based Virtual Screening for Small-Molecule Inhibitors of HPV-16 E6", Preprint: ChemRxiv (2026), 10.26434/chemrxiv-2026-64n5z.

Organometallic Inhibitors

Small-molecule organometallic compounds can serve as potent inhibitors. We assess the viability of organometallic compounds synthesized by collaborators as potential therapeutics. In earlier work, we have shown the viability of copper (II)-chelated small molecules in inhibiting the SARS-CoV-2 main protease.

Selected work

Roberto A Garza-López, Liam Kwak, Andrew Chung, Gabriel L Ancajas, John J Kozak, Harry B Gray, "Copper(II) Inhibition of the SARS-CoV-2 Main Protease," Nat. Sci. 5, e70012 (2025), 10.1002/ntls.70012.

Random Walks and Diffusion

Diffusion-controlled processes such as electron transfer and exciton trapping on lattice structures are near-Markovian in nature. Modeling these processes as random walks can provide analytic formulas for properties such as mean-first passage time. We have developed random walk models for multi-layered two-dimensional and fractal lattices and applied them to a multitude of physically relevant systems.

Selected works

Roberto A Garza-López, Lawrence Chen, John J Kozak, "Markovian Model for Photoinduced Charge Separation in Dendritic Molecules," Chem. Phys. Lett.: X 737, 100009 (2019), 10.1016/j.cpletx.2019.100009.

John J Kozak, Roberto A Garza-López, Enrique Abad, "Lattice Statistical Theory of Random Walks on a Fractal-Like Geometry," Phys. Rev. E 89 (2016), 10.1103/PhysRevE.89.032147.

Team

Roberto A. Garza-López, PhD

Professor of Chemistry, Pomona College

rgarza@pomona.edu ResearchGate

Roberto earned his B.S. in chemical engineering at Texas A&M University, an M.S. in chemistry at the University of Texas at El Paso, and his Ph.D. in chemistry at the University of Georgia in 1991, where he stayed on as a postdoctoral associate.

He joined Pomona College in 1992 and is now a full professor of theoretical and computational physical chemistry, with more than thirty peer-reviewed articles in statistical thermodynamics, stochastic processes, molecular mechanics, and random walks and diffusion-controlled reactions on fractal and Euclidean surfaces. He was the first Cambridge-Pomona exchange professor, and held sabbaticals in the laboratories of Richard Zare at Stanford and Nobel laureate Ahmed Zewail at Caltech — whose autobiography he translated into Spanish as Viaje a Través del Tiempo: senderos hacia el Premio Nobel.

His current work, in long-standing collaboration with Harry Gray and John J. Kozak, spans protein folding and visualization, energy transfer in dendrimers, and computational drug design. He has taught in the Pomona Academy for Youth Success (PAYS) program since its inception, bringing high-school students into research with open-source computational tools.

Liam Kwak

Postbaccalaureate Fellow, Class of '26

liam.kwak@pomona.edu ORCID

Liam obtained a B.S. in Chemistry from Pomona College in 2026. During his time at Pomona College he joined the group of Dr. Roberto Garza where he completed a senior thesis with distinction for studying mu-opioid receptor allosteric modulation. Upon completing his undergraduate studies in 2026, he returned to the Garza Lab as a postbaccalaureate fellow. Currently, he is investigating how small molecules bind to intrinsically disordered proteins using molecular dynamics simulations in connection to experimental NMR methods.

Ian Tam

Research Assistant, Class of '27

iwtp2023@mymail.pomona.edu

Ian is studying chemistry and applied math at Pomona College with a minor in music. In the lab of Dr. Roberto Garza, he has studied the binding mechanisms of flavonoid compounds to tyrosinase. He is currently investigating force fields for more accurate molecular dynamics (MD) simulations of intrinsically disordered proteins (IDPs). Ian is a clarinetist in the Pomona College Orchestra and plays in a clarinet-violin-piano trio.

Andrew Chung

Research Assistant, Class of '28

acck2024@mymail.pomona.edu

Andrew is studying chemistry at Pomona College. In Dr. Roberto Garza's lab, his research uses molecular dynamics simulations to probe the mechanisms of RORγt inverse agonists as potential modulators of Th17-driven autoimmunity. His work bridges computational biophysics with wet-lab immunology experience, and he is working toward a career as a physician-scientist in this space.

Jonathan Cong

Research Assistant, Class of '28

jcid2024@mymail.pomona.edu

Jonathan is studying psychology at Pomona College. He conducts computational chemistry research in Dr. Roberto Garza's lab, where he has evaluated novel corticosteroid candidates for Duchenne muscular dystrophy through virtual screening and molecular modeling of the glucocorticoid receptor. His current research focuses on identifying small-molecule inhibitors of Streptococcus mutans glucansucrases for their potential use in preventing dental caries. Outside the lab, Jonathan competes on the Pomona-Pitzer Men's Swim and Dive team.

Bra'sen Phillips-Bates

Research Assistant, Class of '28

bcpd2024@mymail.pomona.edu

Bra'sen is a junior at Pomona College majoring in Chemistry. His current project focuses on identifying novel, AAK1-selective small-molecule inhibitors as a potential dystrophin-independent therapeutic strategy for Duchenne Muscular Dystrophy (DMD).