AI for Tuberculosis Research

Machine Learning Enzymes
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About

Jinich Lab Photo

Our Humble Beginnings

In September 2023, we opened our doors at UC San Diego as a mixed computational and experimental group. Our mission is to bring cutting-edge AI for tuberculosis research — from predicting essential protein interactions to designing protein-based inhibitors. At the same time, we pursue foundational problems in biochemistry, with a focus on protein language models and the enzyme-to-substrate mapping challenge.

The Computational Lab

Our lab uses powerful computers to apply machine learning tools to the protein-small molecule (e.g. enzyme-substrate) mapping problem. We have our own GPU workstations and access to supercomputers at the San Diego Supercomputer Center (SDSC).

Computer Xochipilli
The Wet Lab

The Wet Lab

Our wet lab focuses on enzyme biochemistry, where among other things, we:

  • Validate computational predictions of enzyme function
  • Generate new data to train our machine learning models
  • Perform enzyme activity assays

We collaborate with world-class LC-MS experts at UCSD to precisely measure enzyme activities and metabolites.

Our values

We strive for excellence in all we do. Our main goal is to nurture scientists and humans; high-quality research and publications naturally follow from this focus. We encourage the use of resources like Materials for Nurturing Scientists from Uri Alon's group to support this mission. We value community engagement through outreach activities and embrace diversity in all its forms. To enhance our scientific productivity and empower our trainees, we actively integrate AI tools, including large language models, into our work.

Jinich Lab Group

Team

The members of the Jinich Lab

Adrian Jinich Head

Adrian Jinich

Principal Investigator

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Erika Garay

Erika Garay

Staff Scientist

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Pedro Gutierrez Tamayo

Pedro Gutierrez Tamayo

Post-Doctoral Researcher

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Melina Shamshoum

Melina Shamshoum

Post-Doctoral Researcher

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Ricardo Almada Monter

Ricardo Almada Monter

Graduate (PhD) Student, Chemistry

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Adriana Siordia

Adriana Siordia

Graduate (PhD) Student, Biochemistry

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Sarah Marta Veskimägi

Sarah Marta Veskimägi

Graduate (PhD) Student, Biochemistry

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Nathaniel Roethler

Nathaniel Roethler

Graduate (PhD) Student, Biochemistry

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Sarah Johnson

Sarah Johnson

Graduate (PhD) Student, Biochemistry

Coadvised with Prof. Neville Bethel

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Woojung Kim

Woojung Kim

Graduate (PhD) Student, Chemistry

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Zinnia Ma

Zinnia Ma

Rotation Graduate (PhD) Student, Biochemistry

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Javier Espinoza Herrera

Javier Espinoza Herrera

Graduate (MS) Student, Biochemistry

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Amnada Spencer

Amanda Spencer

Graduate (MS) Student, Biochemistry

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Param Chordiya

Param Chordiya

Graduate (MS) Student, Electrical and Computer Engineering

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Maeve OConnor

Maeve O'Connor

Undergraduate Student, Biochemistry

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Karry Shi

Karry Shi

Undergraduate Student, Biochemistry

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Chloe Keggen

Chloe Keggen

Undergraduate Student, Bioinformatics

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Ivan Guzman

Ivan Guzmán

Undergraduate Student, Biochemistry

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Dyllan Mead

Dyllan Mead

Undergraduate Student, Biotechnology/ Biochemistry

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Eri Ishii

Eri Ishii

Undergraduate Student, Human Biology

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Abhijit Nambiar

Abhijit Nambiar

Undergraduate Student, Biology-Bioinformatics

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Publications

Click in the Picture to know more about each paper

A full list of publications can be found here.

Sequence similarity with PLMs
The Protein Language Visualizer: Sequence Similarity Networks for the Era of Language Models
Javier Espinoza-Herrera, María F. Manríquez-García, Sofía Medina-Bermejo, Ailyn López-Jasso, Karry Shi, Dyllan Mead, Sarah M. Veskimägi, Maeve O’Connor, Adriana Siordia, Nathaniel Roethler, Adrian Jinich
genome-wide co-essentiality analysis in Mycobacterium
Genome-wide co-essentiality analysis in Mycobacterium tuberculosis reveals an itaconate defense enzyme module
Adrian Jinich, Sakila Z. Nazia, Andrea V. Tellez, Amy M. Wu, Ricardo Almada-Monter, Clare M. Smith, Kyu Rhee
Annotation-ree prediction
Candidate transmission survival genome of Mycobacterium tuberculosis
Saurabh Mishra, Prabhat Ranjan Singh, Xiaoyi Hu, Landys Lopez-Quezada, Adrian Jinich, Robin Jahn, Luc Geurts, Naijian Shen, Michael A. DeJesus, Travis Hartman, Kyu Rhee, Matthew Zimmerman, Veronique Dartois, Richard M. Jones, Xiuju Jiang, Ricardo Almada-Monter, Lydia Bourouiba, Carl Nathan
Genome-wide screen identifies host loci
Genome-wide screen identifies host loci that modulate Mycobacterium tuberculosis fitness in immunodivergent mice
Rachel K Meade, Jarukit E Long, Adrian Jinich, Kyu Y Rhee, David G Ashbrook, Robert W Williams, Christopher M Sassetti, Clare M Smith
Enzyme Subtrate Prediction from Three-Dimensional
Enzyme Substrate Prediction from Three-Dimensional Feature Representations Using Space-Filling Curves
Dmitrij Rappoport, Adrian Jinich
Enzyme Subtrate with Protein Languague Models
Predicting enzyme substrate chemical structure with protein language models
Adrian Jinich, Sakila Z Nazia, Andrea V Tellez, Dmitrij Rappoport, Mohammed AlQuraishi, Kyu Rhee

Pictures

We like working with the broader community!

Members of the Jinich lab are strongly encouraged to actively participate in outreach activities, such as the Clubes de Ciencia Mexico program.

Club de Ciencias

Clubes de Ciencias México

The Clubes de Ciencia program was created in Guanajuato, Mexico in 2014, and has rapidly expanded to 9 cities and 8 Ibero-American countries. The mission of CdeCMx is to expand access to the highest quality scientific education for young people from all socio-economic backgrounds in high school and higher education levels and to inspire the next generation of Mexican scientists, technologists, and innovators through international education networks. Our volunteer instructors are scientists who are experts in their respective research fields.

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Teaching at UCSD

We teach Chem 169/269: Applied Machine Learning and AI for Biochemistry, a hands-on course focused on applying modern AI to real biological data. Students work in teams to analyze protein language model embeddings, predict enzyme function, and explore tools like AlphaFold, UMAP, and contrastive learning — all in the context of cutting-edge biochemical problems.

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Enlace Program

Contact Us

University of California, San Diego

Skaggs School of Pharmacy and Pharmaceutical Sciences

9255 Pharmacy Ln, La Jolla, California, CA, 92093

ajinich@health.ucsd.edu