Machine Learning in Structural Biology

Workshop at the 38th Conference on Neural Information Processing Systems

15th December 2024

About

Structural biology, the study of the 3D structure or shape of proteins and other biomolecules, has been transformed by breakthroughs from machine learning algorithms. Machine learning models are now routinely used by experimentalists to predict structures to aid in hypothesis generation and experimental design, accelerate the experimental process of structure determination (e.g. computer vision algorithms for cryo-electron microscopy), and have become a new industry standard for bioengineering new protein therapeutics (e.g. large language models for protein design). Despite all of this progress, there are still many active and open challenges for the field, such as modeling protein dynamics, predicting the structure of other classes of biomolecules such as RNA, learning and generalizing the underlying physics driving protein folding, and relating the structure of isolated proteins to the in vivo and contextual nature of their underlying function. These challenges are diverse and interdisciplinary, motivating new kinds of machine learning methods and requiring the development and maturation of standard benchmarks and datasets.

Machine Learning in Structural Biology (MLSB), seeks to bring together field experts, practitioners, and students from across academia, industry research groups, and pharmaceutical companies to focus on these new challenges and opportunities. This year, MLSB aims to bridge the theoretical and practical by addressing the outstanding computational and experimental problems at the forefront of our field. The intersection of artificial intelligence and structural biology promises to unlock new scientific discoveries and develop powerful design tools.

MLSB will be an in-person NeurIPS workshop on 15th December 2024 in MTG Rooms 11 & 12 at the Vancouver Convention Center.

Please contact the organizers at workshopmlsb@gmail.com with any questions.

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Invited Speakers


Schedule (Pacific Standard Time)

08:30 Opening Remarks
08:35 Invited Speaker - Noelia Ferruz

Tailored protein design with conditional language models

08:40
08:45
08:50
08:55
09:00 Contributed Talk

The OMG dataset: An Open MetaGenomic corpus for mixed-modality genomic language modeling
Yunha Hwang · Andre Cornman · Jacob West-Roberts · Martin Beracochea · Sergey Ovchinnikov · Simon Roux · Antonio Camargo · Milot Mirdita

09:05
09:10
09:15 Invited Speaker - Josh Abramson, AlphaFold3 Team

Biomolecular Structure Prediction with AlphaFold3

09:20
09:25
09:30
09:35
09:40 Break
09:45
09:50
09:55 Invited Speaker - Erika Alden DeBenedictis

How do we make the next PDB? Introducing Align’s Data Platform

10:00
10:05
10:10
10:15
10:20 Contributed Talk

Controllable All-Atom Generation of Protein Sequence and Structure from Sequence-Only Inputs
Amy Lu · Wilson Yan · Kevin Yang · Vladimir Gligorijevic · Kyunghyun Cho · Richard Bonneau · Pieter Abbeel · Nathan Frey

10:25
10:30
10:35 Contributed Talk

Protein Language Model Fitness is a Matter of Preference
Cade Gordon · Amy Lu · Pieter Abbeel

10:40
10:45
10:50 Invited Speaker - Gabe Rocklin

Learning the determinants of protein folding energy landscapes from large-scale experiments

10:55
11:00
11:05
11:10
11:15 Word from Sponsors
11:20 Poster Session/Lunch
11:25
11:30
11:35
11:40
11:45
11:50
11:55
12:00
12:05
12:10
12:15
12:20 Invited Speaker - Jennifer Listgarten

Protein-Protein Interactions in Synthetic Co-Evolution & Other Stories

12:25
12:30
12:35
12:40
12:45 Contributed Talk

Generative modeling of protein ensembles guided by crystallographic electron densities
Sai Advaith Maddipatla · Nadav Sellam · Sanketh Vedula · Ailie Marx · Alex Bronstein

12:50
12:55
01:00 Contributed Talk

Improving Ab-Initio Cryo-EM Reconstruction with Semi-Amortized Pose Inference
Shayan Shekarforoush · David Lindell · Marcus Brubaker · David Fleet

01:05
01:10
01:15 Break
01:20
01:25
01:30 Invited Speaker - Milot Mirdita

Challenges to metagenomic annotation with Foldseek and protein language models

01:35
01:40
01:45
01:50
01:55 Invited Speaker - Jeremy Wohlwend, Boltz-1

Boltz-1: Democratizing Biomolecular Interaction Modeling

02:00
02:05
02:10
02:15
02:20 Contributed Talk

FlowPacker: protein side-chain packing with torsional flow matching
Jin Sub Lee · Philip Kim

02:25
02:30
02:35 Contributed Talk

HelixFlow, SE(3)–equivariant Full-atom Design of Peptides With Flow-matching Models
Xuezhi Xie · Pedro A Valiente · Jisun Kim · Jin Sub Lee · Philip Kim

02:40
02:45
02:50 Break
02:55
03:00 Word from PLINDER / PINDER competition
03:05 PLINDER / PINDER competition talks
03:10
03:15 Panel Session
03:20
03:25
03:30
03:35
03:40
03:45
03:50
03:55 Closing Remarks
04:00 Poster Session / Happy Hour
04:05
04:10
04:15
04:20
04:25
04:30
04:35
04:40
04:45
04:50
04:55
05:00

Accepted Papers

Organizers