Timothy Jenkins

Head of Data Science and Assistant Prof at DTU Bioengineering with a keen interest in antibody discovery, de-novo protein design, ML, and next-gen therapeutics.

[Timothy Jenkins @TimothyPJenkins]

🧪🐍 AI vs venom!
Our Nature paper with David Baker shows AI-designed proteins can block deadly snake toxins. Now featured by Reuters! 🎥
✅ 80–100% survival in mice
💸 Cheap, fast, scalable
🌍 A step toward better antivenoms

📄 https://t.co/DsEkTQ3QGR
🎬 https://t.co/KGupUmBi1W

[Dr Singularity @Dr_Singularity]

Another Huge, insane cancer Breakthrough

A new AI based method can produce specially designed proteins in just a few weeks that can arm the T cells in the body's immune system to attack and kill cancer cells

Researchers from the Technical University of Denmark and the Scripps Research Institute have developed an advanced AI platform that rapidly designs protein based therapies to arm a patient's immune system against cancer, a major leap in precision medicine.

Published in Science, the study shows for the first time that it’s possible to design proteins entirely in a computer to redirect T cells toward cancer cells via pMHC molecules, reducing the discovery timeline from YEARS! to just 4–6 weeks.

Using this method, the team created “IMPAC-T” cells, engineered T cells that successfully killed cancer cells in lab tests.

One key example was a protein targeting NY-ESO-1, a marker found in many cancers. The platform also proved effective in designing custom treatments for a melanoma patient, demonstrating its potential for personalized therapies.

The innovation includes a virtual safety screening, allowing scientists to predict and eliminate dangerous side effects before lab testing.

[Biology+AI Daily @BiologyAIDaily]

De Novo-Designed pMHC Binders Facilitate T Cell–Mediated Cytotoxicity Toward Cancer Cells @ScienceMagazine

1. A groundbreaking study presents a rapid de novo design platform for minibinders (miBds) targeting cancer-associated peptide-bound major histocompatibility complex (pMHC) using advanced generative models, achieving high-affinity binding and T cell-mediated cytotoxicity against cancer cells.

2. The platform leverages in silico cross-panning and molecular dynamics simulations to enhance specificity and predictability of miBds, significantly improving the success rate of identifying binders compared to traditional methods.

3. A high-affinity binder targeting the NY-ESO-1 antigen was identified and validated through cryo-electron microscopy, demonstrating its potential for precision immunotherapy when incorporated into chimeric antigen receptors (CARs).

4. The study also successfully designed and validated binders for a neoantigen pMHC complex with an unknown structure, showcasing the platform's applicability to personalized cancer therapy.

5. The computational pipeline, including RFdiffusion, ProteinMPNN, and AlphaFold2, enables efficient and accurate design of miBds, with a success rate of 10% for ultrahigh target affinity binders, highlighting the potential for rapid therapeutic discovery.

6. The findings suggest that this approach could be transformative for targeting viral antigens and autoimmune diseases, in addition to cancer, by providing a versatile and precise method for pMHC targeting.

@TimothyPJenkins
📜Paper: https://t.co/HfgsMHYA0L
#ProteinDesign #CancerTherapy #Immunotherapy #ComputationalBiology #PersonalizedMedicine

[Timothy Jenkins @TimothyPJenkins]

@BiologyAIDaily @ScienceMagazine Thanks for sharing our work! Hopefully a lot more cool things building on this PoC to come🎉

[Kristoffer H. J. @KrisHaurum]

Thrilled to share our new paper in @ScienceMagazine! 💥
We developed a computational platform to design tiny 'minibinders' from scratch that can guide T cells to kill cancer cells. This is proof-of-concept for targeting intracellular cancer antigens with a new modality! 🎯

[Timothy Jenkins @TimothyPJenkins]

We believe this approach can accelerate the development of safer, more effective immunotherapies for patients.
And a special thank you to the talented @moonii1020 & @Joe_r_loeffler for the stunning graphic! 🎨
#CancerResearch #Immunotherapy #AI

[Timothy Jenkins @TimothyPJenkins]

Thrilled to announce our paper, "De novo-designed pMHC binders facilitate T cell-mediated cytotoxicity toward cancer cells," is officially out in @ScienceMagazine!

We used generative AI to build a 'GPS' for immune cells to hunt cancer.

Read it here: https://t.co/T7rfR8uK8M

[Timothy Jenkins @TimothyPJenkins]

This was a monumental team effort bringing together immunology, computational biology, and structural biology.
A huge congratulations to the incredible teams at @DTU_HealthTech, @DTUbioengineer, & @scrippsresearch and to all my brilliant co-authors, especially @KrisHaurum.

[Timothy Jenkins @TimothyPJenkins]

While I’m bouncing between emails and desperately waiting for my holiday, it’s good to know at least something in the lab is holding it together

Thermal stability might not be glamorous, but it’s underrated

Designerbodies: even when things get heated, still doing their job ;)

[AffinityAI @affinityaibio]

Whether you're on holiday 🏖️ or still in the lab 🧪 trying to keep cool, at least one thing isn't melting: our DesignerBodies.

Generatively designed. Thermally stable ❄️ Reliable reagents that don’t need a break 💪

#ProteinDesign #AI #Biotech

[Timothy Jenkins @TimothyPJenkins]

@affinityaibio Built for heat. Unlike me ;)

[InstaDeep @instadeepai]

🧬 In March, we published our research for InstaNovo and InstaNovo+ in @NatMachIntell, our diffusion-powered ‘de novo’ peptide sequencing models built to uncover the secrets of the human proteome.

https://t.co/oWnzl646Kr

[InstaDeep @instadeepai]

📆 Six months, four publications, one cover.

We’re halfway through the year and InstaDeep research is powering ahead with multiple boundary-pushing papers published in the @NaturePortfolio!

Catch up on the highlights below 🔽

[Timothy Jenkins @TimothyPJenkins]

@affinityaibio Designing binders instead of screening for months? Can’t wait to disappoint reviewers in new and innovative ways.

[Timothy Jenkins @TimothyPJenkins]

At @affinityaibio we’re moving from “finders keepers” to “designers binders”, one generative model at a time.

If you could have a binder to anything, what would it be?

(Proteins, obscure signalling pathways, that one reviewer who never gets back to you…;)

[AffinityAI @affinityaibio]

We’re rethinking what a binding reagent can be.

Most antibodies weren’t designed, they were discovered. At AffinityAI, we’re flipping that logic: we build binders from first principles, guided by generative AI.

What targets would you be interested in having a binder to?

[AffinityAI @affinityaibio]

At AffinityAI, we combine Danish design sensibilities with precision molecular engineering. Elegant. Efficient. Engineered to bind.

🧬 Discover how we’re reshaping molecular function:

https://t.co/gOwxHE4A9e

[Timothy Jenkins @TimothyPJenkins]

Huge thanks to Anders Høeg Nissen for the great conversation and to the brilliant team behind InstaNovo, especially @InstaDeepAI and @DTUBioengineering.

#AI #ProteinDesign #MassSpectrometry #deNovoSequencing #MachineLearning #NatureMI #InstaNovo #DTU #DigitalBiotechLab

[Timothy Jenkins @TimothyPJenkins]

We focus on our new Nature Machine Intelligence paper introducing InstaNovo, a transformer model for de novo peptide sequencing from mass spectrometry. No reference database needed.
📄 https://t.co/0QlDVAA83m

[Timothy Jenkins @TimothyPJenkins]

💡 Curious about:
– How generative AI is transforming protein research?
– Why mass spec is such a rich (but messy) playground for AI?
– What it takes to go from spectrum to sequence to structure?
Give it a listen 🎧👇

[Timothy Jenkins @TimothyPJenkins]

🎧 Had the pleasure of joining Anders Høeg Nissen on the AI Denmark Podcast to talk about how we’re using AI to crack the protein code 🧬

Catch my segment from 9:30 (and yes — it’s in English 😉)
🎙️ https://t.co/msbjJGD8bX