Carlos Bueno

Scientific Software Developer and Computational Biophysicist

About

As a Postdoctoral Associate at the Rice Center for Theoretical Biological Physics (CTBP) and a Molecular Sciences Software Institute (MolSSI) Fellow, I develop physics-based molecular models to investigate biological phenomena. I am a lead developer of several open-source force fields, including OpenAWSEM for protein dynamics, Open3SPN2 for DNA, and OpenActin for actin cytoskeletal networks. These models, written in Python and built on top of the OpenMM molecular dynamics framework, are designed following best practices in scientific software development with modular architecture, continuous integration workflows, and documentation accessible to beginners, advanced users, and developers alike. My current research focuses on optimizing force field parameters using machine learning, in direct collaboration with experimental laboratories to ensure that each model addresses well-defined questions in structural and cellular biology. I also actively support the training of the next generation of scientists through initiatives such as Science Clubs Peru, iGEM, and Frontiers in Science, where I guide students in interdisciplinary projects focused on biophysical model development. My goal is to create open-source, modular, reproducible, and sustainable computational tools that not only accelerate scientific discovery but also help build the infrastructure needed by the scientific community.

Education

• PhD, Systems, Synthetic and Physical Biology, Rice University, Houston, TX (Dec 2022)
  Dissertation: Mesoscale Models for the Study of Emergent Behaviors Arising from Protein Interactions
• BSc. Chemistry. BSc. Pharmacy and Biochemistry, Cayetano Heredia University, Lima, Peru (May 2013)
  

Experience

• Software Fellow, Molecular Sciences Software Institute (MolSSI), Remote (Jul. 2024 - Present)
  Participated in the Software Best Practices Boot Camp at MolSSI HQ.
  Developed infrastructure tools for computational molecular sciences.
  Collaborated with Software Scientists in specialized training on maintainable and extensible code design.
• Postdoctoral Scientist, Center for Theoretical Biological Physics, Rice University, Houston, TX (Jan. 2023 - Present)
  Developed Python packages for structure and sequence analysis using Pandas, NumPy, Scipy, PyTorch, Numba, Simpy.
  Authored 3 peer-reviewed publications and presented research in 2 international conferences.
  Mentored undergraduate and graduate students across interdisciplinary teams.
• Research Assistant, Center for Theoretical Biological Physics, Rice University, Houston, TX (Jan. 2016 - Dec. 2022)
  Developed Python packages to model and analyze protein interactions.
  Led a team of 4 developers on C++ scientific software.
  Applied statistical modeling and machine learning to simulations.
  Built a mathematical model of protein network connectivity.
  Authored 10 publications, presented in 6 conferences, and delivered internal research updates.
• Bioinformatics Scientist, Bioinformatics Unit, FARVET, Ica, Peru (Mar. 2013 - Dec. 2014)
  Created software tools for vaccine development using public bioinformatics databases.
  Contributed to veterinary vaccine development projects.
  Presented progress reports to executives and interdisciplinary departments.
• Research Assistant, Bioinformatics Lab, Cayetano Heredia University, Lima, Peru (Jan. 2012 - Jul. 2015)
  Built and used bioinformatics software for scientific research.
  Curated and analyzed large-scale biological datasets with Python.
  Managed GPU cluster server deployment and networking.
  Taught classes and workshops on simulation, visualization, and scientific programming.

Projects

• 2024
  • AWESOME: Implementing modular python code for potentials in openMM, analysis tools in Python and machine learning optimization with PyTorch of the AWSEM forcefield by retraining it using high-throughput ΔΔG data.
  • OpenFit: Developed a molecular density fitting method that optimizes the correlation between experimental and simulated density maps. Implemented efficient algorithms for computing density maps and calculating derivatives for integration with MD simulations. Optimized code performance using Numba for high-speed parallel computations.
• 2023
  • OpenActin: Developed a novel mesoscale open-source coarse-grained force-field to simulate actin network aggregation using openMM.
  • DCA-frustratometer: Co-led the development of a Python package to parameterize energy models from protein sequence data using Direct Coupling Analysis (DCA). The open-source code includes documentation, tutorials, unit testing, and CI with GitHub Actions.
• 2021
  • Percolation of actin networks: Designed a mathematical model of percolation in actin networks based on connectivity and percolation of graphs.
• 2020
  • Open3SPN2: Developed an open-source coarse-grained force-fields for DNA simulations in collaboration with Juan J. de Pablo group. Included version-control, documentation, tutorials, parameterized unit testing, continuous integration using github actions, and distribution through pip and anaconda including conda-forge, with force classes using inheritance from openMM forces. Forcefield was adapted from previous C++ versions from the code for LAMMPS and compared them using jupyter notebooks.
  • OpenAWSEM: Co-developed an open-source coarse-grained force-fields for protein simulations based on previous LAMMPS C++ code. Included version-control, documentation, tutorials, and distribution through pip and anaconda including conda-forge.
• 2019
  • Multivalent linker model in MEDYAN: Designed, coded, and implemented a C++ plugin for a mechanochemical model of actin networks. Led a technical team of 2 graduate students and a computer scientist in collaboration with Gareg Papoian.
• 2018
  • Prediction of folding free energy based on sequence: Applied Bayesian inference methods to predict folding free energy changes from sequence data.
• 2017
  • Acute myeloid leukemia outcome predictor: Explored predictive models in Python to assess AML prognosis, utilizing random forests and evolutionary algorithms.

Publications

• 2024
  • Galpern EA, Jaafari H, Bueno C, Wolynes PG, Ferreiro DU. Reassessing the exon–foldon correspondence using frustration analysis. PNAS 121:e2400151121.
  • Jaafari H, Bueno C, Schafer NP, Martin J, Morcos F, Wolynes PG. The physical and evolutionary energy landscapes of devolved protein sequences corresponding to pseudogenes. PNAS 121:e2322428121.
• 2023
  • Chen X, Jin S, Chen M, Bueno C, Wolynes PG. The marionette mechanism of domain-domain communication in the antagonist, agonist, and coactivator responses of the estrogen receptor. PNAS 120:1–9.
• 2022
  • Gu X, Schafer NP, Bueno C, Lu W, Wolynes PG. A structural dynamics model for how CPEB3 binding to SUMO2 can regulate translational control in dendritic spines. PLoS Comp. Bio. 18:e1010657.
  • Jin S, Bueno C, Lu W, Wang Q, Chen M, Chen X, Wolynes PG, Gao Y. Computationally exploring the mechanism of bacteriophage T7 gp4 helicase translocating along ssDNA. PNAS 119:1–10.
  • Bueno C, Liman J, Schafer NP, Cheung MS, Wolynes PG. A generalized Flory-Stockmayer kinetic theory of connectivity percolation and rigidity percolation of cytoskeletal networks. PLoS Comp. Bio. 18:e1010105.
• 2021
  • Lu W, Bueno C, Schafer NP, Moller J, Jin S, Chen X, Chen M, Gu X, Davtyan A, de Pablo JJ, Wolynes PG. OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations. PLoS Comp. Bio. 17:1–21.
  • Thadani NN, Zhou Q, Gamas KR, Butler S, Bueno C, Schafer NP, Morcos F, Wolynes PG, Suh J. Frustration and Direct-Coupling Analyses to Predict Formation and Function of Adeno-Associated Virus. Biophys J. 120:489–503.
• 2020
  • Liman J, Bueno C, Eliaz Y, Schafer NP, Waxham MN, Wolynes PG, Levine H, Cheung MS. The Role of the Arp2/3 Complex in Shaping the Dynamics and Structures of Branched Actomyosin Networks. PNAS 117:10825–31.
  • Shikai J, Contessoto VG, Chen M, Schafer NP, Lu W, Chen X, Bueno C, Hajitaheri A, Sirovetz BJ, Davtyan A, Papoian GA, Tsai MY, Wolynes PG. AWSEM-Suite: A Protein Structure Prediction Server Based on Template-Guided, Coevolutionary-Enhanced Optimized Folding Landscapes. Nucleic Acids Res. 48:W25–W30.
• 2019
  • Wang Q, Chen M, Schafer NP, Bueno C, Song SS, Hudmon A, Wolynes PG, Waxham MN, Cheung MS. Assemblies of calcium/calmodulin-dependent kinase II with actin and their dynamic regulation by calmodulin in dendritic spines. PNAS 116:18937–18942.
• 2017
  • Potoyan DA, Bueno C, Zheng W, Komives EA, Wolynes PG. Resolving the NFκB hetero-dimer binding paradox: Strain and frustration guide the binding of dimeric transcription factors. J. Am. Chem. Soc. 2017:jacs.7b08741.
• 2016
  • Tataje-Lavanda L, Montalván Á, Bueno C, Requena D, Fernández-Díaz M. First evidence of detection of Asia/South America II (A/SAII) infectious bronchitis virus in a commercial broiler flock in Peru. Veterinary Record Case Reports 4:e000292.
• 2014
  • Rueda D, Sheen P, Gilman RH, Bueno C, Santos M, Pando-Robles V, Batista CV, Zimic M. Nicotinamidase/pyrazinamidase of Mycobacterium tuberculosis forms homo-dimers stabilized by disulfide bonds. Tuberculosis (Edinb) 2014:Pii: S1472-9792(14)20554-3.

Awards

• 2024: MolSSI Software Fellow

Mentoring

• 2023: Mentor, Frontiers in Science program
• 2021: Instructor, Design your micro-world: Build computational theoretical models for protein simulations
• 2020: Mentor, Frontiers in Science program
• 2015-2019: Mentor, Serendipity mentorship program

Skills

• Python
• Git
• Linux (Advanced)
• MATLAB
• C++ (Intermediate)
• Javascript
• R
• SQL (Basic)

Contact