Boltz: Towards a Unified Approach for Biomolecular Interaction Modeling
Boston, Costa Rica, Guatemala, Panama, and Peru 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
7:00 PM, Tuesday, 24 June 2025
MIT Room 32-G449 (Kiva) and online via Zoom
Boltz: Towards a Unified Approach for Biomolecular Interaction Modeling
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: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.
Bio:
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.
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 Chapter of the IEEE Computer and EMBS Societies and GBC/ACM will be hybrid (in person and online).
Date and Time
Location
Hosts
Registration
- Date: 24 Jun 2025
- Time: 11:00 PM UTC to 12:30 AM UTC
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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
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