CV for Diego del Alamo, PhD

I’m a computational biologist and structural bioinformatician with fifteen years of research experience, including ten years in the wet lab. Currently I engineer and design biotherapeutics and protein reagents at GSK using a combination of classical modeling and machine learning tools. My background is in experimental and computational biophysics of membrane proteins (transporters), and I am personally interested in protein dynamics and evolution.

Cell: +1 (617) 869 2425

Email, Github, LinkedIn, Google Scholar, Bluesky

Skills and expertise

Computational structural biology

  • Experience with generative AI methods for sequence- and structure-based design of proteins and antibodies (RF-diffusion, ProGen, inverse folding methods such as ProteinMPNN, ESM-IF, etc)
  • Extensive experience with Rosetta, AlphaFold2, and ESMFold, including introducing source code modifications for protein and antibody design
  • Some experience with small molecule modeling (MOE), MD simulations (Amber, GROMACS, and Desmond), and free energy perturbation (Schrödinger Maestro)

Bioinformatics and deep learning

  • Proficient in sequence and structural search (BLAST, Hmmer, Foldseek), alignment (Clustal, MUSCLE, TM-Align), and clustering (MMSeqs, CPPTraj)
  • Some experience with training, fine-tuning, and transfer learning of protein language models (ESM, Progen) and inverse folding models (ProteinMPNN) for predictive modeling of stability, fitness, and other properties

DevOps, cloud computing, and pipelining

  • Some experience building containerization (Docker, Singularity/Apptainer) and Nextflow pipelines
  • Some experience with Heroku and GCP

Programming skills

  • Comfortable with Python (NumPy, PyTorch, Pandas, SciKit-Learn, BioPython), R (ggplot2), Bash and the Unix command line
  • Previous experience with C++11

Experimental skills

  • Previous experience with membrane protein purification, bacterial cell culture, proteoliposome and nanodisc reconstitution, pulse and continuous-wave electron paramagnetic resonance spectroscopy, radioligand transport assays

Miscellaneous skills

  • Experience making high-quality publication-ready figures with Inkscape, GIMP, PyMOL. Comfortable with LaTeX

Work and Research Experience

GSK (Baar, ZG, Switzerland)

Investigator - Protein Design & Informatics (May 2022 - Present)

My primary responsibilities involve the rational design and multi-parameter optimization of antibodies and other proteins using a combination of sequence- and structure-based modeling tools. As part of this role I interface with experimental groups to build upon previous-round datasets under both data-poor and data-rich conditions

  • Antibody engineering: applying a combination of physics-based methods (Schrödinger FEP, Rosetta), fine-tuned predictive models (developed using PyTorch and SciKit-Learn), and AI/ML tools (such as ESM, ProteinMPNN, ProGen, and others) for various engineering challenges such as de-risking of immunogenicity, solubility, specificity, thermostability, expression, and patent infringement
  • Enzyme engineering: identifying starting points for directed evolution campaigns using bioinformatics search tools (MMSeqs), structural modeling (ESMFold, AlphaFold, Rosetta), and ligand-binding pocket featurization (MOE)
  • Writing and distributing Python scripts across GSK R&D for molecular modeling and analysis, including rapid retrieval from public databases of millions of protein models, in silico linker screening and ranking, and modeling of alternate conformational states of diverse proteins such as viral fusion proteins
  • Developed and deployed reproducible pipelines with Singularity and Nextflow
  • Preparing manuscripts for publication, and presenting findings at scientific conferences

Vanderbilt University (Nashville, TN, USA)

Postdoctoral Researcher (Aug 2021 - Apr 2022)

  • Initiated and led a multi-departmental project focused on designing and testing transformer- and CNN-based AI/ML methods (developed in PyTorch and Jax) for processing electron paramagnetic resonance spectroscopy data
  • Identified, developed, and published methods to model conformational changes in membrane proteins, such as transporters and G-protein coupled receptors, using AlphaFold2 and Rosetta
  • Concluded my PhD research work (see below)

Graduate Student/Research Assistant (Aug 2015 - Aug 2021)

My PhD research work focused on the experimental and computational characterization of the membrane transporter GadC. This interdisciplinary project involved a combination of spectroscopy measurements, activity assays, and integrative modeling using experimental data as geometric restraints

  • Supervised and mentored one undergraduate, one Master’s student, one research assistant, and two Ph.D. rotation students
  • Taught and co-hosted twelve interactive in-person and remote workshops and courses
  • Coauthored ten peer-reviewed publications and presented research at four international conferences

Karyopharm Therapeutics (Newton, MA, USA)

Senior Research Associate (Jan 2014 - May 2015)

  • Tested small molecule inhibitors of XPO1 using cell-based assays and identified the future clinical candidate Eltanexor
  • Maintained cell culture stocks of human and mammalian cells

Research Associate (Jul 2012 - Dec 2013)

  • Designed, implemented, and managed data trackers to monitor blood and plasma samples collected during Phase I and II clinical trials
  • Wrote preclinical dosing schedules and interfaced with academic partners and contract research organizations
  • Proofread patents for small molecules, verified that reported values and structures matched internal data

Education

Ph.D. - Vanderbilt University (Nashville, TN, USA)

Chemical and Physical Biology Program (Aug 2015 - Aug 2021)

Dissertation title: Integrative modeling of secondary active transporters

B.S. - University of New Hampshire (Durham, NH, USA)

Major: Biochemistry, Molecular Biology and Cell Biology (Aug 2008 - May 2012)

Minor: Genetics

Preprints and Publications

2024

2023

2022

2021

2020

Before 2020

Presentations and Invited Talks

2024

2023

  • “Integrative modeling of the secondary active transporter GadC” Invited talk at the KTH Royal Institute of Technology in Stockholm, Sweden, 9 March 2023

2022

  • “Modeling alternative conformations with AlphaFold2” Oral presentation at the “Applications of AlphaFold” industry conference hosted by the European Molecular Biology Laboratory in Hinxton, UK, 8 November 2022

Before 2022

  • “Making the most of sparse data: modeling a bacterial transporter using double electron-electron resonance spectroscopy data” Invited talk at Leipzig University in Leipzig, DE, 22 September 2020
  • “Protein fold prediction using simulated double electron-electron resonance distance distributions and decay traces” Oral presentation at RosettaCon in Ft. Leavenworth, WA, USA, 7 August 2019

Side projects

  • PubMedBERT literature fetcher: A cloud-based app that emails me papers I might find interesting on a daily basis. It is hosted on Heroku and 1) scrapes biorxiv, arxiv, and PubMED for new submissions each morning, 2) embeds their abstracts using large language models (via the OpenAI API), and 3) calculates relevance using a custom-trained regression model (SciKit-Learn). I receive an e-mail every weekday morning at 5AM GMT with the results.

  • Protein structural modelling and design Zettelkasten: A wiki I run that sorts and summarizes information from over 500 recent protein design and modelling papers.