Workshop

New Frontiers of AI for Drug Discovery and Development

Animashree Anandkumar · Ilija Bogunovic · Ti-chiun Chang · Quanquan Gu · Jure Leskovec · Michelle Li · Chong Liu · Nataša Tagasovska · Mengdi Wang · Wei Wang

Project Page

Abstract

We will facilitate interdisciplinary discussions to identify gaps and opportunities for AI in the drug discovery and development pipeline.

Video

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Schedule

Timezone: America/Los_Angeles

6:15 AM

Opening Remarks

Chong Liu

Video

6:25 AM

Roundtable Discussion

Video

7:05 AM

Invited Talk 1 - Wengong Jin (MIT) - DSMBind: SE(3) denoising score matching for unsupervised binding energy prediction and nanobody design

Video

7:40 AM

2 Oral Presentations

Video

8:00 AM

Coffee Break

8:30 AM

Invited Talk 2 - Marinka Zitnik (Harvard) - Foundation Models for Molecular Drug Design and Clinical Drug Development

Video

9:05 AM

2 Oral Presentations

Video

9:25 AM

Invited Talk 3 - Haoda Fu (Eli Lilly) - LLM Is Not All You Need. Generative AI on Smooth Manifolds

Video

10:00 AM

Lunch Break

11:20 AM

Poster Session

12:25 PM

Invited Talk 4 - Michael Bronstein (Oxford) - Harnessing geometry for molecular design

Michael Bronstein

Video

1:00 PM

Coffee Break

1:30 PM

Invited Talk 5 - Jian Tang (MILA) - Diffusion Models for Molecular Structure Prediction

Video

2:05 PM

Invited Talk 6 - Iya Khalil (Merck) - Decoding Biology with AI and High-Throughput Biology

Video

2:40 PM

Award Ceremony

Lucian Chan · Denis Tarasov

Video

3:10 PM

Concluding Remarks

Chong Liu

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Removing Biases from Molecular Representations via Information Maximization

Chenyu Wang · Sharut Gupta · Caroline Uhler · Tommi Jaakkola

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MolSiam: Simple Siamese Self-supervised Representation Learning for Small Molecules

Joshua Yao-Yu Lin

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Multitask-Guided Self-Supervised Tabular Learning for Patient-Specific Survival Prediction

You Wu · Omid Bazgir · Yongju Lee · Tommaso Biancalani · James Lu · Ehsan Hajiramezanali

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Do chemical language models provide a better compound representation?

Mirko Torrisi · Saeid Asadollahi · Antonio De la Vega de Leon · Kai Wang · Wilbert Copeland

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Generalist Equivariant Transformer Towards 3D Molecular Interaction Learning

Xiangzhe Kong · Wenbing Huang · Yang Liu

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Inpainting Protein Sequence and Structure with ProtFill

Elizaveta Kozlova · Arthur Valentin · Daniel Nakhaee-Zadeh Gutierrez

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$\textit{In vitro}$ validated antibody design against multiple therapeutic antigens using generative inverse folding

Amir Shanehsazzadeh

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TopoPool: An Adaptive Graph Pooling Layer for Extracting Molecular and Protein Substructures

Mattson Thieme · Majdi Hassan · Chetan Rupakheti · Kedar Thiagarajan · Abhishek Pandey · Han Liu

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Offline RL for generative design of protein binders

Denis Tarasov · Ulrich Armel Mbou Sob · Miguel Arbesú · Nima Siboni · Sebastien Boyer · Andries Smit · Oliver Bent · Arnu Pretorius · Marcin Skwark

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Online Learning of Optimal Prescriptions under Bandit Feedback with Unknown Contexts

Hongju Park · Mohamad Kazem Shirani Faradonbeh

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Hit Expansion Driven By Machine Learning

Jin Xu · Steven Kearnes · JW Feng

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A framework for conditional diffusion modelling with applications in motif scaffolding for protein design

Kieran Didi · Francisco Vargas · Simon Mathis · Vincent Dutordoir · Emile Mathieu · Urszula Julia Komorowska · Pietro Lió

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Automating reward function configuration for drug design

Temitope Ajileye · Paul Gainer · Marius Urbonas · Douglas Pires

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DGFN: Double Generative Flow Networks

Elaine Lau · Nikhil Murali Vemgal · Doina Precup · Emmanuel Bengio

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Target Conditioned GFlowNet for Drug Design

Tony Shen · Mohit Pandey · Martin Ester

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Towards a more inductive world for drug repurposing approaches

Jesus de la Fuente Cedeño · Guillermo Serrano · Uxia Veleiro · Mikel Casals · Laura Vera · Marija Pizurica · Antonio Pineda-Lucena · Idoia Ochoa · Silve Vicent · Olivier Gevaert · Mikel Hernaez

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Sample-efficient Antibody Design through Protein Language Model for Risk-aware Batch Bayesian Optimization

Yanzheng Wang · Tianyu Shi

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De novo design of antibody heavy chains with SE(3) diffusion

Frédéric Dreyer · Daniel Cutting · David Errington · Charlotte Deane

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Identifying regularization schemes that make the feature attributions faithful

Julius Adebayo · Samuel Stanton · Simon Kelow · Michael Maser · Richard Bonneau · Vladimir Gligorijevic · Kyunghyun Cho · Stephen Ra · Nathan Frey

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ChatPathway: Conversational Large Language Models for Biology Pathway Detection

Yanjing Li · Hannan Xu · Haiteng Zhao · Hongyu Guo · Shengchao Liu

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Leap: molecular synthesisability scoring with intermediates

Antonia Calvi · Théophile Gaudin · Dominik Miketa · Dominique Sydow · Liam Wilbraham

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PharmacoNet: Accelerating Large-Scale Virtual Screening by Deep Pharmacophore Modeling

Seonghwan Seo · Woo Youn Kim

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Model-free selective inference and its applications to drug discovery

Ying Jin · Emmanuel Candes

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AlphaFold Meets Flow Matching for Generating Protein Ensembles

Bowen Jing · Bonnie Berger · Tommi Jaakkola

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RetroBridge: Modeling Retrosynthesis with Markov Bridges

Ilia Igashov · Arne Schneuing · Marwin Segler · Michael Bronstein · Bruno Correia

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Ab-DeepGA: A generative modeling framework leveraging deep learning for antibody affinity tuning

BoRam Lee · Yara Seif · Kevin Teng · Xiao Xiao · Isha Verma · Ming-Tang Chen · Alan Cheng

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ExPT: Scaling Foundation Models for Experimental Design via Synthetic Pretraining

Tung Nguyen · Sudhanshu Agrawal · Aditya Grover

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On Modelability and Generalizability: Are Machine Learning Models for Drug Synergy Exploiting Artefacts and Biases in Available Data?

Arushi Gandhi

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Machine Learning Guided AQFEP: A Fast & Efficient Absolute Free Energy Perturbation Solution for Virtual Screening

Jordan Crivelli-Decker · Zane Beckwith · Gary Tom · Ly Le · Sheenam Khuttan · Romelia Salomon-Ferrer · Jackson Beall · Andrea Bortolato

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Data-Efficient Molecular Generation with Hierarchical Textual Inversion

Seojin Kim · Jaehyun Nam · Sihyun Yu · Younghoon Shin · Jinwoo Shin

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PiNUI: A Dataset of Protein-Protein Interactions for Machine Learning

Geoffroy Dubourg-Felonneau · Eyal Akiva · Daniel Wesego · Ranjani Varadan

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Protein Language Model-Powered 3-Dimensional Ligand Binding Site Prediction from Protein Sequence

Shuo Zhang · Lei Xie

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All You Need is LOVE: Large Optimized Vector Embeddings Network for Drug Repurposing

Sina Akbarian · Sepehr Asgarian · Jouhyun Jeon

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PoseCheck: Generative Models for 3D Structure-based Drug Design Produce Unrealistic Poses

Charles Harris · Kieran Didi · Arian Jamasb · Chaitanya K. Joshi · Simon Mathis · Pietro Lió · Tom Blundell

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Neurosymbolic AI Reveals Biases and Limitations in ML-Driven Drug Discovery

Lauren Nicole DeLong · Yojana Gadiya · Jacques Fleuriot · Daniel Domingo-Fernández

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Leveraging expert feedback to align proxy and ground truth rewards in goal-oriented molecular generation

Julien Martinelli · Yasmine Nahal · Duong Lê · Ola Engkvist · Samuel Kaski

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CryoSTAR: Cryo-EM Heterogeneous Reconstruction of Atomic Models with Structural Regularization

Yi Zhou · Yilai Li · Jing Yuan · Fei YE · Quanquan Gu

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TrustAffinity: accurate, reliable and scalable out-of-distribution protein-ligand binding affinity prediction using trustworthy deep learning

Amitesh Badkul · Li Xie · Shuo Zhang · Lei Xie

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Scalable Normalizing Flows Enable Boltzmann Generators for Macromolecules

Joseph Kim · David Bloore · Karan Kapoor · Jun Feng · Ming-Hong Hao · Mengdi Wang

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Evaluating Zero-Shot Scoring for In Vitro Antibody Binding Prediction with Experimental Validation

Divya Nori · Simon Mathis · Amir Shanehsazzadeh

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CongFu: Conditional Graph Fusion for Drug Synergy Prediction

Oleksii Tsepa · Bohdan Naida · Anna Goldenberg · Bo Wang

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The neural scaling laws for phenotypic drug discovery

Drew Linsley · John Griffin · Jason Brown · Adam Roose · Steven Finkbeiner · Peter Linsley · Jeremy Linsley

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VN-EGNN: Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification

Florian Sestak · Lisa Schneckenreiter · Sepp Hochreiter · Andreas Mayr · Günter Klambauer

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SALSA: Semantically-Aware Latent Space Autoencoder

Kathryn E. Kirchoff · Travis Maxfield · Alexander Tropsha · Shawn Gomez

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Gotta be SAFE: A New Framework for Molecular Design

Emmanuel Noutahi · Cristian Gabellini · Michael Craig · Jonathan Siu Chi Lim · Prudencio Tossou

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MoleculeGPT: Instruction Following Large Language Models for Molecular Property Prediction

Weitong ZHANG · Xiaoyun Wang · Weili Nie · Joe Eaton · Brad Rees · Quanquan Gu

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Embracing assay heterogeneity with neural processes for markedly improved bioactivity predictions

Lucian Chan · Marcel Verdonk · Carl Poelking

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FragXsiteDTI: an interpretable transformer-based model for drug-target interaction prediction

Ali Khodabandeh Yalabadi · Mehdi Yazdani-Jahromi · Niloofar Yousefi · Aida Tayebi · Sina Abdidizaji · OZLEM GARIBAY

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Tree Search-Based Evolutionary Bandits for Protein Sequence Optimization

Jiahao Qiu · Hui Yuan · Jinghong Zhang · Wentao Chen · Huazheng Wang · Mengdi Wang

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GraphPrint: Extracting Features from 3D Protein Structure for Drug Target Affinity Prediction

Amritpal Singh

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Large-scale Pretraining Improves Sample Efficiency of Active Learning based Molecule Virtual Screening

Zhonglin Cao · Simone Sciabola · Ye Wang

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Role of Structural and Conformational Diversity for Machine Learning Potentials

Nikhil Shenoy · Prudencio Tossou · Emmanuel Noutahi · Hadrien Mary · Dominique Beaini · Jiarui Ding

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DrugImprover: Utilizing Reinforcement Learning for Multi-Objective Alignment in Drug Optimization

Xuefeng Liu · Songhao Jiang · Archit Vasan · Alexander Brace · Ozan Gokdemir · Thomas Brettin · Fangfang Xia · Ian Foster · Rick Stevens

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AbLEF: Antibody Language Ensemble Fusion for thermodynamically empowered property predictions

Zachary Rollins · Talal Widatalla · Andrew Waight · Alan Cheng · Essam Metwally

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DiffDock-Pocket: Diffusion for Pocket-Level Docking with Sidechain Flexibility

Michael Plainer · Marcella Toth · Simon Dobers · Hannes Stärk · Gabriele Corso · Céline Marquet · Regina Barzilay

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PDB-Struct: A Comprehensive Benchmark for Structure-based Protein Design

Chuanrui Wang · Bozitao Zhong · Zuobai Zhang · Narendra Chaudhary · Sanchit Misra · Jian Tang

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Protein Language Models Enable Accurate Cryptic Ligand Binding Pocket Prediction

David Bloore · Joseph Kim · Karan Kapoor · Eric Chen · Kaifu Gao · Mengdi Wang · Ming-Hong Hao

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Explaining Drug Repositioning: A Case-Based Reasoning Graph Neural Network Approach

Adriana Carolina Gonzalez Cavazos

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Graph Neural Bayesian Optimization for Virtual Screening

Miles Wang-Henderson · Bartu Soyuer · Parnian Kassraie · Andreas Krause · Ilija Bogunovic

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Synthon Embeddings for Modeling DNA Encoded Libraries

Benson Chen · Mohammad Sultan · Theofanis Karaletsos

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Learning Scalar Fields for Molecular Docking with Fast Fourier Transforms

Bowen Jing · Tommi Jaakkola · Bonnie Berger

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$\textit{In vitro}$ validated antibody design against multiple therapeutic antigens using generative inverse folding

Amir Shanehsazzadeh

Link

Offline RL for generative design of protein binders

Denis Tarasov · Ulrich Armel Mbou Sob · Miguel Arbesú · Nima Siboni · Sebastien Boyer · Andries Smit · Oliver Bent · Arnu Pretorius · Marcin Skwark

Video

Link

A framework for conditional diffusion modelling with applications in motif scaffolding for protein design

Kieran Didi · Francisco Vargas · Simon Mathis · Vincent Dutordoir · Emile Mathieu · Urszula Julia Komorowska · Pietro Lió

Link

Towards a more inductive world for drug repurposing approaches

Link

Embracing assay heterogeneity with neural processes for markedly improved bioactivity predictions

Lucian Chan · Marcel Verdonk · Carl Poelking

Video

Link

DrugImprover: Utilizing Reinforcement Learning for Multi-Objective Alignment in Drug Optimization

Xuefeng Liu · Songhao Jiang · Archit Vasan · Alexander Brace · Ozan Gokdemir · Thomas Brettin · Fangfang Xia · Ian Foster · Rick Stevens

Video

Link