# Therapeutic Targeting a Non-Hodgkin Lymphoma Driver Using AI

> **NIH NIH R01** · BAYLOR COLLEGE OF MEDICINE · 2024 · $623,283

## Abstract

Therapeutic Targeting a Non-Hodgkin Lymphoma Driver using AI
PROJECT SUMMARY
Baylor College of Medicine (BCM) and Atomwise Incorporation have partnered to discover, optimize, and test
inhibitors to undruggable oncoproteins using artificial intelligence (AI). Both Hodgkin lymphoma and non-
Hodgkin lymphoma (NHL) are cancers that start in lymphocytes, which are part of the body’s immune system.
The main difference between Hodgkin lymphoma and NHL is in the specific lymphocyte each involves: in the
presence of abnormal cells called Reed-Sternberg cells, the lymphoma is classified as Hodgkin’s; otherwise, it
is classified as NHL. NHL is the most common blood cancer and causes over 20,000 deaths every year in the
United States. There are about 90 types of NHL, which usually develop when mutations occur within a
lymphocyte. The gene MYD88 encodes myeloid differentiation primary response 88 protein, a critical universal
adapter with essential functions in inflammation and immunity. Following stimulation of toll-like receptors,
MYD88 transduces the signal to activate genes responsible for innate and adaptive immune responses.
MYD88 is a driver oncogene that is frequently mutated in B-cell NHLs. The most frequent missense
mutation is L265P, which changes leucine at position 265 to proline and accounts for ~90% of all MYD88
mutations. MYD88 L265P is found in ~90% of Waldenström macroglobulinemia (WM, a rare NHL), >50% of
primary extranodal lymphomas, and ~29% of activated B-cell diffuse large B-cell lymphomas (DLBCL). WM is
considered incurable. DLBCL can be cured in about 40% of the patients, but those with MYD88 L265P have
poorer survival than those without. BCM collaborates with Atomwise, the inventor of the first deep learning AI
technology based on neural networks and a leader in AI-assisted drug discovery, to virtually screen 2.7 million
compounds. We identified scores of AI-selected compounds targeting a binding site near L265P in MYD88. We
validated these hits by evaluating their inhibition of MYD88 L265P ubiquitination and xenograft tumorigenesis.
One compound attenuated lymphoma growth from NHL cells with MYD88 L265P, but not that with WT MYD88.
We hypothesize that adaptor oncoproteins such as MYD88 L265P can be targeted by AI. In this
application, we propose two specific aims to develop drug candidates that target MYD88 L265P for NHL
therapy. In Aim 1, we will use AI to virtually screen billions of compounds to discover novel drug candidates
targeting a binding site near L265P in MYD88. In Aim 2, we will optimize validated hit compounds targeting
MYD88 L265P. Data generated from this partnership will provide a solid scientific platform for therapeutic
development targeting the oncogenic MYD88 L265P while sparing WT MYD88, which is critical for both innate
and adaptive immunity. This work addresses the unmet clinical need to target MYD88 L265P directly and
advances drug development against mutation-specific drivers.

## Key facts

- **NIH application ID:** 10755367
- **Project number:** 5R01CA271546-02
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** Yong Li
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $623,283
- **Award type:** 5
- **Project period:** 2022-12-16 → 2027-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10755367

## Citation

> US National Institutes of Health, RePORTER application 10755367, Therapeutic Targeting a Non-Hodgkin Lymphoma Driver Using AI (5R01CA271546-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10755367. Licensed CC0.

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