Drug Discovery

MolCRAFT: Structure-Based Drug Design in Continuous Parameter Space

Yanru Qu, Keyue Qiu, Yuxuan Song et al.

BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Yusuf Roohani, Andrew Lee, Qian Huang et al.

Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation

Tuan Le, Julian Cremer, Frank Noe et al.

MOOSE-Chem: Large Language Models for Rediscovering Unseen Chemistry Scientific Hypotheses

Zonglin Yang, Wanhao Liu, Ben Gao et al.

A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?

Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta et al.

Conversational Drug Editing Using Retrieval and Domain Feedback

Shengchao Liu, Jiongxiao Wang, Yijin Yang et al.

Efficient Evolutionary Search Over Chemical Space with Large Language Models

Haorui Wang, Marta Skreta, Cher-Tian Ser et al.

PepTune: De Novo Generation of Therapeutic Peptides with Multi-Objective-Guided Discrete Diffusion

Sophia Tang, Yinuo Zhang, Pranam Chatterjee, PhD

Domain-Agnostic Molecular Generation with Chemical Feedback

Yin Fang, Ningyu Zhang, Zhuo Chen et al.

GenMol: A Drug Discovery Generalist with Discrete Diffusion

Seul Lee, Karsten Kreis, Srimukh Veccham et al.

DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization

Xiangxin Zhou, Xiwei Cheng, Yuwei Yang et al.

Projecting Molecules into Synthesizable Chemical Spaces

Shitong Luo, Wenhao Gao, Zuofan Wu et al.

Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning

Gang Liu, Michael Sun, Wojciech Matusik et al.

Searching for High-Value Molecules Using Reinforcement Learning and Transformers

Raj Ghugare, Santiago Miret, Adriana Hugessen et al.

NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation

Zhiyuan Liu, Yanchen Luo, Han Huang et al.

Drug Discovery with Dynamic Goal-aware Fragments

Seul Lee, Seanie Lee, Kenji Kawaguchi et al.

Generating Novel Leads for Drug Discovery Using LLMs with Logical Feedback

Shreyas Bhat Brahmavar, Ashwin Srinivasan, Tirtharaj Dash et al.

CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph

Haitao Lin, Guojiang Zhao, Odin Zhang et al.

MolTailor: Tailoring Chemical Molecular Representation to Specific Tasks via Text Prompts

Haoqiang Guo, Sendong Zhao, Haochun Wang et al.

Binding-Adaptive Diffusion Models for Structure-Based Drug Design

Mol-LLaMA: Towards General Understanding of Molecules in Large Molecular Language Model

Dongki Kim, Wonbin Lee, Sung Ju Hwang

Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models

Cong Fu, Xiner Li, Blake Olson et al.

Multi-domain Distribution Learning for De Novo Drug Design

Arne Schneuing, Ilia Igashov, Adrian Dobbelstein et al.

Removing Biases from Molecular Representations via Information Maximization

Chenyu Wang, Sharut Gupta, Caroline Uhler et al.

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

Keir Adams, Kento Abeywardane, Jenna Fromer et al.

Knowledge Enhanced Representation Learning for Drug Discovery

Thanh Lam Hoang, Marco Luca Sbodio, Marcos Martinez et al.

BOOM: Benchmarking Out-Of-distribution Molecular Property Predictions of Machine Learning Models

Evan Antoniuk, Shehtab Zaman, Tal Ben-Nun et al.

UniMoMo: Unified Generative Modeling of 3D Molecules for De Novo Binder Design

Xiangzhe Kong, Zishen Zhang, Ziting Zhang et al.

Procedural Synthesis of Synthesizable Molecules

Michael Sun, Alston Lo, Minghao Guo et al.

LLM-Augmented Chemical Synthesis and Design Decision Programs

Haorui Wang, Jeff Guo, Lingkai Kong et al.

Representing Molecules as Random Walks Over Interpretable Grammars

Michael Sun, Minghao Guo, Weize Yuan et al.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery

Xiuyuan Hu, Guoqing Liu, Can Chen et al.

Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models

Songtao Liu, Hanjun Dai, Yue Zhao et al.

Molecular Optimization Model with Patentability Constraint

Sally Turutov, Kira Radinsky

CL-MFAP: A Contrastive Learning-Based Multimodal Foundation Model for Molecular Property Prediction and Antibiotic Screening

Gen Zhou, Sugitha Janarthanan, Yutong Lu et al.

Piloting Structure-Based Drug Design via Modality-Specific Optimal Schedule

Keyue Qiu, Yuxuan Song, Zhehuan Fan et al.

MAGNet: Motif-Agnostic Generation of Molecules from Scaffolds

Leon Hetzel, Johanna Sommer, Bastian Rieck et al.

Integrating Protein Dynamics into Structure-Based Drug Design via Full-Atom Stochastic Flows

Xiangxin Zhou, Yi Xiao, Haowei Lin et al.

Template-Guided 3D Molecular Pose Generation via Flow Matching and Differentiable Optimization

Noémie Bergues, Arthur Carré, Paul Join-Lambert et al.

Multi-modal Contrastive Learning with Negative Sampling Calibration for Phenotypic Drug Discovery

Jiahua Rao, Hanjing Lin, Leyu Chen et al.

DMol: A Highly Efficient and Chemical Motif-Preserving Molecule Generation Platform

Peizhi Niu, Yu-Hsiang Wang, Vishal Rana et al.

A Dataset for Distilling Knowledge Priors from Literature for Therapeutic Design

Haydn Jones, Natalie Maus, Josh magnus Ludan et al.

ModuLM: Enabling Modular and Multimodal Molecular Relational Learning with Large Language Models

Zhuo Chen, YIZHEN ZHENG, Huan Yee Koh et al.

Uncertainty-Aware Multi-Objective Reinforcement Learning-Guided Diffusion Models for 3D De Novo Molecular Design

Lianghong Chen, Dongkyu Kim, Mike Domaratzki et al.

Prior-Guided Flow Matching for Target-Aware Molecule Design with Learnable Atom Number

Jingyuan Zhou, Hao Qian, Shikui Tu et al.

Controllable 3D Molecular Generation for Structure-Based Drug Design Through Bayesian Flow Networks and Gradient Integration

Seungyeon Choi, Hwanhee Kim, Chihyun Park et al.

Offline Model-based Optimization for Real-World Molecular Discovery

Dong-Hee Shin, Young-Han Son, Hyun Jung Lee et al.

MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning

Peter Eckmann, Dongxia Wu, Germano Heinzelmann et al.

Reframing Structure-Based Drug Design Model Evaluation via Metrics Correlated to Practical Needs

Bowen Gao, Haichuan Tan, Yanwen Huang et al.

Interaction-based Retrieval-augmented Diffusion Models for Protein-specific 3D Molecule Generation

Zhilin Huang, Ling Yang, Xiangxin Zhou et al.

Empower Structure-Based Molecule Optimization with Gradient Guided Bayesian Flow Networks

Keyue Qiu, Yuxuan Song, Jie Yu et al.

BounDr.E: Predicting Drug-likeness via Biomedical Knowledge Alignment and EM-like One-Class Boundary Optimization

Dongmin Bang, Inyoung Sung, Yinhua Piao et al.

Enhancing Ligand Validity and Affinity in Structure-Based Drug Design with Multi-Reward Optimization

Seungbeom Lee, Munsun Jo, Jungseul Ok et al.

CombiMOTS: Combinatorial Multi-Objective Tree Search for Dual-Target Molecule Generation

Thibaud Southiratn, Bonil Koo, Yijingxiu Lu et al.

DynaPhArM: Adaptive and Physics-Constrained Modeling for Target-Drug Complexes with Drug-Specific Adaptations

Diya Zhang, Mengwei Sun, Xingdan Wang et al.

CIDD: Collaborative Intelligence for Structure-Based Drug Design Empowered by LLMs

Bowen Gao, Yanwen Huang, Yiqiao Liu et al.

R-DTI: Drug Target Interaction Prediction Based on Second-Order Relevance Exploration

Yang Hua, Tianyang Xu, Xiaoning Song et al.

Latent Retrieval Augmented Generation of Cross-Domain Protein Binders

Zishen Zhang, Xiangzhe Kong, Wenbing Huang et al.

M²N: A Progressive Macro-to-Micro 3D Modeling Scheme for Unveiling Drug-Target Affinity

Tianxu Lv, Jie Zhu, Jinyi Liu et al.

Self-supervised Blending Structural Context of Visual Molecules for Robust Drug Interaction Prediction

Tengfei Ma, Kun Chen, Yongsheng Zang et al.

Automatic Auxiliary Task Selection and Adaptive Weighting Boost Molecular Property Prediction

Zhiqiang Zhong, Davide Mottin

Integrating Drug Substructures and Longitudinal Electronic Health Records for Personalized Drug Recommendation

Wenjie Du, Xuqiang Li, Jinke Feng et al.

OligoGym: Curated Datasets and Benchmarks for Oligonucleotide Drug Discovery

Rachapun Rotrattanadumrong, Carlo De Donno

Training-free Multi-objective Diffusion Model for 3D Molecule Generation

XU HAN, Caihua Shan, Yifei Shen et al.

Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models

Zhilin Huang, Ling Yang, Xiangxin Zhou et al.