1

CAMP: Combinatorial Engineering of Proteins

Manvitha Ponnapati, Brian Lynch, Sapna Sinha, Joseph Jacobson

MIT, Independent

2

An Intrinsic Framework for Riemannian Diffusion Models

Hyunwoo Park, Sungwoo Park

Carnegie Mellon University, LG AI Research

3

RNA-FRAMEFLOW: Flow Matching for de novo 3D RNA Backbone Design

Rishabh Anand, Chaitanya K. Joshi, Alex Morehead, Arian R. Jamasb, Charles C. Harris, Simon V. Mathis, Kieran Didi, Bryan Hooi, Pietro Liò

Yale University, University of Cambridge, University of Missouri, Prescient Design (Genentech), National University of Singapore

4

PharmacoForge: Generating Pharmacophores with Diffusion Models

Emma L. Flynn, Riya Shah, Rishal Aggarwal, Ian Dunn, David Ryan Koes

University of Pittsburgh

5

Known Unknowns: Out-of-Distribution Property Prediction in Molecules and Materials

Nofit Segal, Aviv Netanyahu, Kevin Greenman, Rafael Gomez-Bombarelli, Pulkit Agrawal

MIT, Catholic Institute of Technology

6

LOL-EVE: Predicting Promoter Variant Effects from Evolutionary Sequences

Courtney A. Shearer, Felix Teufel, Rose Orenbuch, Daniel Ritter, Aviv Spinner, Erik Xie, Jonathan Frazer, Mafalda Dias, Pascal Notin, Debora S. Marks

Harvard Medical School, Novo Nordisk A/S, University of Copenhagen, Cornell University, MIT, Centre for Genomic Regulation Universitat Pompeu Fabra, University of Oxford, Broad Institute

7

REACTION-CONDITIONED DE NOVO ENZYME DESIGN WITH ALPHAENZYME

Chenqing Hua

McGill University, Mila-Quebec AI Institute

8

Bio2Token: All-atom tokenization of any biomolecular structure with Mamba

Andrew Li-Yang Liu, Axel Elaldi, Nathan Russell, Olivia Viessmann

Flagship Pioneering

9

VaxSeer: Selecting influenza vaccine strains through evolutionary and antigenicity models

Wenxian Shi, Jeremy Wohlwend, Menghua Wu, Regina Barzilay

MIT

10

FINE-TUNING DISCRETE DIFFUSION MODELS VIA REWARD OPTIMIZATION WITH APPLICATIONS TO DNA AND PROTEIN DESIGN

Chenyu Wang, Masatoshi Uehara, Yichun He, Amy Wang, Tommaso Biancalani, Avantika Lal, Tommi Jaakkola, Sergey Levine, Hanchen Wang, Aviv Regev

MIT, Genentech, Harvard University, Genentech, UC Berkeley, Stanford University

11

De Novo Generation of Heavy Metal-Binding Peptides with Classifier-Guided Diffusion Sampling

Yinuo Zhang, Pranam Chatterjee

Duke University

12

Retraining ProteinMPNN with Family-Specific Proteins for Enhanced Thermostability and Enzymatic Activity of Lysozyme at Elevated Temperatures

Yehlin Cho, Lirong Zhou, Banghao Wu, Hannes Stärk, Bingxin Zhou, Jason Yim, Jin Huang, Daniella Pretorius, Liang Hong, Sergey Ovchinnikov

MIT, Shanghai Jiao Tong University, Imperial College London

13

PREDICTING PERTURBATION TARGETS WITH CAUSAL DIFFERENTIAL NETWORKS

Menghua Wu, Umesh Padia, Sean H Murphy, Regina Barzilay, Tommi Jaakkola

MIT

14

ProtDiff: Function-Conditioned Masked Diffusion Models for Robust Directed Protein Generation

Vishrut Thoutam, Yair Schiff, Sergey Ovchinnikov, Pranam Chatterjee

High Technology High School, Cornell University, MIT, Duke University

15

MeMDLM: De Novo Membrane Protein Design with Masked Discrete Diffusion Protein Language Models

Shrey Goel, Vishrut Thoutam, Edgar Mariano Marroquin, Aaron Gokaslan, Arash Firouzbakht, Sophia Vincoff, Volodymyr Kuleshov, Huong T. Kratochvil, Pranam Chatterjee

Duke University, Cornell University, University of North Carolina

16

moPPIt: De Novo Generation of Motif-Specific Binders with Protein Language Models

Tong Chen, Yinuo Zhang, Pranam Chatterjee

Duke University

17

Functionally Shrinking Proteins with Guided Diffusion Models

Zhangzhi Peng, Chentong Wang, Alex Tong, Pranam Chatterjee

Duke University, Westlake University, Mila-Quebec AI Institute

18

Quantum Positional Encodings for Graph Neural Networks

Slimane Thabet, Mehdi Djellabi, Igor O. Sokolov, Sachin Kasture, Louis-Paul Henry, Loïc Henriet

Pasqal

19

Quantum-Enhanced Neural Exchange-Correlation Functionals

Igor O. Sokolov, Gert-Jan Both, Art D. Bochevarov, Pavel A. Dub, Daniel S. Levine, Christopher T. Brown, Shaheen Acheche, Panagiotis Kl. Barkoutsos, Vincent E. Elfving

PASQAL, Schrödinger

20

CLIPZyme: Reaction-Conditioned Virtual Screening of Enzymes

Peter G. Mikhael, Itamar Chinn, Regina Barzilay

MIT

21

DPAC: Prediction and Design of Protein-DNA Interactions via Sequence-Based Contrastive Learning

Tianlai Chen, Pranay Vure, Rishab Pulugurta, Pranam Chatterjee

Duke University

22

Efficient Generation of Molecular Clusters with Dual-Scale Equivariant Flow Matching

Akshay Subramanian, Shuhui Qu, Cheol Woo Park, Sulin Liu, Janghwan Lee, Rafael Gomez-Bombarelli

MIT, Samsung Display America Lab

23

ProtSCAPE: Mapping the landscape of protein conformations in molecular dynamics

Siddharth Viswanath, Dhananjay Bhaskar, David R. Johnson, João Felipe Rocha, Egbert Castro, Jackson D. Grady, Alex T. Grigas, Michael A. Perlmutter, Corey S. O'Hern, Smita Krishnaswamy

Yale University, Boise State University

24

JAMUN: Transferable Molecular Conformational Ensemble Generation with Walk-Jump Sampling

Ameya Daigavane, Bodhi P. Vani, Joseph Kleinhenz, Joshua Rackers, Saeed Saremi

Prescient Design (Genentech)

25

Learning Collective Variables with Synthetic Data Augmentation through Physics-Inspired Geodesic Interpolation

Soojung Yang, Juno Nam, Johannes C. B. Dietschreit, Rafael Gomez-Bombarelli

MIT, University of Vienna

26

FLOW MATCHING FOR ACCELERATED SIMULATION OF ATOMIC TRANSPORT IN MATERIALS

Juno Nam, Sulin Liu, Gavin Winter, KyuJung Jun, Soojung Yang, Rafael Gomez-Bombarelli

MIT

27

MDmis: A biophysical machine learning approach for missense variants in disordered protein regions

Aziz Zafar, Chao Hou, Yufeng Shen

Columbia University

28

Enhancing Molecular Design through Graph-based Topological Reinforcement Learning

Xiangyu Zhang

Johns Hopkins University

29

Semiparametric conformal prediction for molecular property prediction

Ji Won Park, Kyunghyun Cho

Prescient Design (Genentech), NYU

30

Molphenix: A Multimodal Foundation Model for PhenoMolecular Retrieval

Philip Fradkin, Puria Azadi Moghadam, Karush Suri, Frederik Wenkel, Maciej Sypetkowski, Dominique Beaini

Valence Labs, University of Toronto, University of British Columbia, Université de Montréal, Mila-Quebec AI Institute

31

Enhancing ultra-large library virtual screening with SPRINT

Andrew T. McNutt, Abhinav K. Adduri, Caleb N. Ellington, Monica T. Dayao, Eric P. Xing, Hosein Mohimani, David R. Koes

University of Pittsburgh, Carnegie Mellon University, Mohamed bin Zayed University of Artificial Intelligence, Petuum Inc.

32

SHAPBALS: Improving Molecular Mapping and Interpretability of Machine Learning for Property Prediction

Christopher Kottke, Michael-Rock Goldsmith, Maximilian Ebert

Congruence Therapeutics

33

ImmunoStruct: Integration of protein structure, sequence, and biochemical properties for immunogenicity prediction and interpretation

Kevin B. Givechian, Joao Felipe Rocha, Edward Yang, Chen Liu, Rex Ying, Akiko Iwasaki, Smita Krishnaswamy

Yale University, Howard Hughes Medical Institute - Chevy Chase

34

Exploring Pre-training Objectives for Foundation Models for Mass Spectrometry Data

Ling Min Serena Khoo, Regina Barzilay

MIT

35

Generative artificial intelligence for navigating synthesizable chemical space

Wenhao Gao, Shitong Luo, Connor W. Coley

MIT

36

FusOn-pLM: A Fusion Oncoprotein-Specific Language Model via Focused Probabilistic Masking

Sophia Vincoff, Shrey Goel, Kseniia Kholina, Rishab Pulugurta, Pranay Vure, Pranam Chatterjee

Duke University

37

ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design

Keir Adams, Kento Abeywardane, Jenna Fromer, Connor Coley

MIT

38

Navigating Chemical Space with Latent Flows

Guanghao Wei, Yining Huang, Chenru Duan, Yue Song, Yuanqi Du

Cornell University, Harvard University, MIT, Caltech

39

Scaffold Hopping with Generative Reinforcement Learning

Luke Rossen, Finton Sirockin, Nadine Schneider, Francesca Grisoni

Eindhoven University of Technology, Novartis BioMedical Research

40

Organic Solubility Prediction at the Limit of Aleatoric Uncertainty

Lucas Attia, Jackson Burns, Patrick S. Doyle, William H. Green

MIT

41

PropEn: Optimizing Proteins with Implicit Guidance

Nataša Tagasovska, Vladimir Gligorijević, Kyunghyun Cho, Andreas Loukas

Genentech|Roche, NYU

42

Benchmarking Deep Learning Models for Protein-Ligand Interactions Beyond Public Datasets

Hao Yu, Dave Barkan, Jian Fang, Lingling Shen, Peter Kutchukian

Novartis Institutes for BioMedical Research

43

Ab initio Reconstruction of Protein Structures Inside Cells

Rishwanth Raghu, Axel Levy, Ryan Feathers, Ellen D. Zhong

Princeton University, Stanford University

44

Structural Elucidation with Forward Mass Spectrometry Neural Networks

Runzhong Wang, Mrunali Manjrekar, Joules Provenzano, Samuel Goldman, Connor W. Coley

MIT

45

Phospho-Tune: Enhanced Structural Modeling of Phosphorylated Protein Interactions

Ernest Glukhov, Veranika Averkava, Sergei Kotelnikov, Sofya A. Gaydukova, Darya Stepanenko, Thu Nguyen, Julie C. Mitchell, Carlos Simmerling, Sandor Vajda, Andrew Emili, Dzmitry Padhorny, Dima Kozakov

Stony Brook University, Boston University, Oak Ridge National Laboratory, OHSU Knight Cancer Institute

46

COMPOSING UNBALANCED FLOWS FOR FLEXIBLE DOCKING AND RELAXATION

Gabriele Corso, Vignesh Ram Somnath, Noah Getz, Regina Barzilay, Tommi Jaakkola, Andreas Krause

MIT, ETH

47

Manufacturing-Aware Generative Model Architectures Enable Biological Sequence Design and Synthesis at Petascale

Eli N. Weinstein, Mattia G. Gollub, Andrei Slabodkin, Cameron L. Gardner, Kerry Dobbs, Xiao-Bing Cui, Alan N. Amin, George M. Church, Elizabeth B. Wood

Columbia University, Jura Bio, NYU, Harvard University, Jura Bio

48

PiFold+: Inverse Folding of Protein Binders with Additional Target Side Chain Context

Venkata Srikar Kavirayuni, Ryan Brand, Amir Shanehsazzadeh

Absci Corporation