Boltz: Towards a Unified Approach for Biomolecular Interaction Modeling

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Boston, Columbia, Costa Rica, Guatemala, Panama,  Peru and San Antonio  Chapters of the IEEE Computer Society, Boston IEEE Engineering in Medicine and Biology Society (EMBS), New Jersey Coast and North Florida Sections of IEEE and GBC/ACM

GabrieleCorso.jpgJeremyWohlwend.jpg7:00 PM, Tuesday, 24 June 2025

MIT Room 32-G449 (Kiva) and online via Zoom

Careers in Technology

Boltz: Towards a Unified Approach for Biomolecular Interaction Modeling

[With updates on new features in Boltz-2 including the ability to predict Binding Affinity]

Gabriele Corso and Jeremy Wohlwend

 

Please register in advance for this seminar even if you plan to attend in person at

<https://acm-org.zoom.us/webinar/register/5917463193812/WN_U1yhFblMQO-I4n1cBhkBFw>

After registering, you will receive a confirmation email containing information about joining the webinar.

Indicate on the registration form if you plan to attend in person. This will help us determine whether the room is close to reaching capacity. We plan to serve light refreshments (probably pizza) before the talk starting at around 6:30 pm. Letting us know you will come in person will help us determine how much pizza to order.

We may make some auxiliary material such as slides and access to the recording available after the seminar to people who have registered.

Abstract:

Accurately modeling biomolecular interactions is a central challenge in modern biology. While recent advances, such as AlphaFold3 and Boltz-1, have substantially improved our ability to predict biomolecular complex structures, these models still fall short in predicting binding affinity, a critical property underlying molecular function and therapeutic efficacy. In this talk, we present Boltz-2, a new structural biology foundation model that exhibits strong performance for both structure and affinity prediction. Boltz-2 introduces controllability features including experimental method conditioning, distance constraints, and multi-chain template integration for structure prediction, and is, to our knowledge, the first AI model to approach the performance of free-energy perturbation (FEP) methods in estimating small molecule--protein binding affinity. Crucially, it achieves strong correlation with experimental readouts on many benchmarks, while being at least 1000 times more computationally efficient than FEP.

For more information see boltz-2 info

Bio:

Jeremy Wohlwend and Gabriele Corso received PhDs this spring for work at the MIT Computer Science and Artificial Intelligence Laboratory where their research focuses on developing novel ML frameworks to tackle challenging problems in drug discovery and immunology.

Directions to 32-G449 - MIT Stata Center, 32 Vassar Street, Cambridge, MA: Please use the main entrance to the Stata Center at 32 Vassar Street (the entrance closest to Main street) as those doors will be unlocked. Upon entering, proceed to the elevators which will be on the right after passing a large set of stairs and a MITAC kiosk. Take the elevator to the 4th floor and turn right, following the hall to an open area; 32-G449 will be on the left. Location of Stata on campus map

 

 This joint meeting of the Boston (and other)Chapter(s) of the IEEE Computer and EMBS Societies and GBC/ACM will be hybrid (in person and online).


  Date and Time

  Location

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  • 32 Vassar St
  • Cambridge, Massachusetts
  • United States
  • Building: Stata Center, MIT building 32
  • Room Number: MIT Room 32-G449 (Kiva)
  • Contact Event Hosts
  • Co-sponsored by gbc/acm

  Speakers

Gabriele Corso of MIT

Topic:

Boltz: Towards a Unified Approach for Biomolecular Interaction Modeling

Understanding biomolecular interactions is fundamental to advancing fields like drug discovery and protein design. In this talk, we introduce Boltz-1, an open-source deep learning model incorporating innovations in model architecture, speed optimization, and data processing achieving AlphaFold3-level accuracy in predicting the 3D structures of biomolecular complexes. Boltz-1 demonstrates a performance on-par with state-of-the-art commercial models on a range of diverse benchmarks, setting a new benchmark for commercially accessible tools in structural biology. By releasing the training and inference code, model weights, datasets, and benchmarks under the MIT open license, we aim to foster global collaboration, accelerate discoveries, and provide a robust platform for advancing biomolecular modeling.

 

 

 

 

Biography:

Jeremy Wohlwend and Gabriele Corso are PhD students at the MIT Computer Science and Artificial Intelligence Laboratory where their research focuses on developing novel ML frameworks to tackle challenging problems in drug discovery and immunology.

 

 

 

 

Jeremy Wohlwend of MIT