Diego Barreto Gomes, PhD, College of Sciences and Mathematics Faculty and Staff

Professional Experience

• Research Scientist and Lead Developer of VMD 2.0 — Auburn University, Department of Physics, Auburn, AL, USA | 07/2021–Present. Leads VMD 2.0 development (C++, C, Tcl/Tk, Python, CUDA and OpenGL), including the molfile reader suite, WaterCompress trajectory codec, accelerated molecular-surface generation, secondary-structure assignment and glycan rendering, validated on NVIDIA Grace Hopper and Blackwell. Built nodeskit (DARPA Nodes) for OLCF Frontier, targeting more than 10,000 one-microsecond simulations; serves as a core contributor to the NSF-funded CyberShuttle cyberinfrastructure (PEARC ’23); and administers the group’s NVIDIA DGX GPU cluster (Slurm/PBS).
• Visiting Professor — Federal University of Juiz de Fora, Department of Computer Sciences, Brazil | 03/2019–03/2021. Designed and taught two 60-hour graduate courses, Molecular Modelling and Bioinformatics for Computational Scientists, and supervised machine-learning research on host–guest binding free-energy prediction.
• Postdoctoral Researcher — University of Strasbourg, Chemistry Department, France | 12/2016–03/2019. Designed and developed ChemFlow (J. Chem. Inf. Model. 2023); led the campaign that identified five Smooth Muscle Myosin 2 inhibitors for hypertrophic cardiomyopathy research; performed charge parametrization for the French National Chemical Library; and co-authored GRALL (Bioinformatics 2020).
• Principal Investigator, Computational Biology Laboratory — INMETRO (National Institute of Standards), Duque de Caxias, RJ, Brazil | 11/2011–12/2018. Founded and managed the laboratory as a CRO-style platform; served as PI on CNPq PROMETRO (2012–2015) and co-PI on CAPES Computational Biology (2015–2019).
• Assistant Professor (Substitute Contract, 20 hours per week) — Federal University of Rio de Janeiro, Brazil | 03/2012–03/2014. Designed and taught five undergraduate courses totaling 345 contact hours in structural biology, drug discovery, bioinformatics and molecular modeling.
• Postdoctoral Researcher — ENS Cachan (now ENS Paris-Saclay), France | 08/2010–07/2011. Developed a genetic algorithm for fully flexible protein–protein docking with normal-mode analysis and an HPC pipeline integrating computational chemistry tools with automated reporting.

Innovation

My research sits at the interface of computation and the life sciences: I develop the software and high-performance computing infrastructure that make large-scale biomolecular simulation possible and apply those tools to open problems in mechanobiology. Current research areas include:

1. VMD 2.0 — Next-generation visualization and analysis for very large biomolecular systems, including high-performance file input and output and trajectory compression.
2. Mechanobiology of bacterial adhesins — Steered molecular dynamics and in silico single-molecule force spectroscopy explaining how staphylococcal adhesins achieve ultrastrong, force-activated binding (“dock, lock and latch”). This work recently identified calcium as a key regulator of adhesion to human skin (Science Advances, 2025).
3. Mechanical anisotropy of nanobodies and affibodies — Dynamic network analysis combined with AI-based epitope prediction to guide the design of mechanically stable therapeutic complexes (JACS, 2024; ACS Nano, 2024).
4. AI and machine learning for molecular science — AlphaFold integration in VMD and machine-learning models for binding free-energy prediction.

Research interests: high-performance computing for research; computational biophysics and computational chemistry applied to biofuels, nanosensors, proteins in nanomaterials and nonaqueous solvents; protein structure and drug design; virtual screening; and protein–protein docking.