Drug Discovery
ML for drug and molecule design
Top Papers
Learning Smooth and Expressive Interatomic Potentials for Physical Property Prediction
Xiang Fu, Brandon Wood, Luis Barroso-Luque et al.
Towards 3D Molecule-Text Interpretation in Language Models
Sihang Li, Zhiyuan Liu, Yanchen Luo et al.
BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments
Yusuf Roohani, Andrew Lee, Qian Huang et al.
MOOSE-Chem: Large Language Models for Rediscovering Unseen Chemistry Scientific Hypotheses
Zonglin Yang, Wanhao Liu, Ben Gao 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
Learning to design protein-protein interactions with enhanced generalization
Anton Bushuiev, Roman Bushuiev, Petr Kouba et al.
A Multi-Modal Contrastive Diffusion Model for Therapeutic Peptide Generation
Yongkang Wang, Xuan Liu, Feng Huang et al.
ClinicalLab: Aligning Agents for Multi-Departmental Clinical Diagnostics in the Real World
Weixiang Yan, Haitian Liu, Tengxiao Wu et al.
MOFDiff: Coarse-grained Diffusion for Metal-Organic Framework Design
Xiang Fu, Tian Xie, Andrew Rosen et al.
Towards Fast, Specialized Machine Learning Force Fields: Distilling Foundation Models via Energy Hessians
Ishan Amin, Sanjeev Raja, Aditi Krishnapriyan
Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning
Gang Liu, Michael Sun, Wojciech Matusik et al.
Generating Novel Leads for Drug Discovery Using LLMs with Logical Feedback
Shreyas Bhat Brahmavar, Ashwin Srinivasan, Tirtharaj Dash et al.
SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints
Miruna Cretu, Charles Harris, Ilia Igashov et al.
CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph
Haitao Lin, Guojiang Zhao, Odin Zhang et al.
Generative Flows on Synthetic Pathway for Drug Design
Seonghwan Seo, Minsu Kim, Tony Shen et al.
IgGM: A Generative Model for Functional Antibody and Nanobody Design
Rubo Wang, Fandi Wu, Xingyu Gao et al.
Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models
Cong Fu, Xiner Li, Blake Olson et al.
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks
Yanqiao Zhu, Jeehyun Hwang, Keir Adams et al.
MolParser: End-to-end Visual Recognition of Molecule Structures in the Wild
Xi Fang, Jiankun Wang, Xiaochen Cai et al.
Mol-LLaMA: Towards General Understanding of Molecules in Large Molecular Language Model
Dongki Kim, Wonbin Lee, Sung Ju Hwang
Beam Enumeration: Probabilistic Explainability For Sample Efficient Self-conditioned Molecular Design
Jeff Guo, Philippe Schwaller
Knowledge Enhanced Representation Learning for Drug Discovery
Thanh Lam Hoang, Marco Luca Sbodio, Marcos Martinez et al.
FlashMD: long-stride, universal prediction of molecular dynamics
Filippo Bigi, Sanggyu Chong, Agustinus Kristiadi et al.
ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design
Keir Adams, Kento Abeywardane, Jenna Fromer et al.
LLM-Augmented Chemical Synthesis and Design Decision Programs
Haorui Wang, Jeff Guo, Lingkai Kong et al.
MOL-Mamba: Enhancing Molecular Representation with Structural & Electronic Insights
Jingjing Hu, Dan Guo, Zhan Si et al.
GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning
Minghao Xu, Yunteng Geng, Yihang Zhang et al.
OSDA Agent: Leveraging Large Language Models for De Novo Design of Organic Structure Directing Agents
Zhaolin Hu, Yixiao Zhou, Zhongan Wang et al.
Hierarchical Graph Tokenization for Molecule-Language Alignment
Yongqiang Chen, QUANMING YAO, Juzheng Zhang et al.
Bi-level Contrastive Learning for Knowledge-Enhanced Molecule Representations
Pengcheng Jiang, Cao Xiao, Tianfan Fu et al.
EBMDock: Neural Probabilistic Protein-Protein Docking via a Differentiable Energy Model
Huaijin Wu, Wei Liu, Yatao Bian et al.
GDiffRetro: Retrosynthesis Prediction with Dual Graph Enhanced Molecular Representation and Diffusion Generation
Shengyin Sun, Wenhao Yu, Yuxiang Ren et al.
CFP-Gen: Combinatorial Functional Protein Generation via Diffusion Language Models
Junbo Yin, Chao Zha, Wenjia He et al.
Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph Languages
Michael Sun, Weize Yuan, Gang Liu et al.
ChemAgent: Self-updating Memories in Large Language Models Improves Chemical Reasoning
Xiangru Tang, Tianyu Hu, Muyang Ye et al.
MarkushGrapher: Joint Visual and Textual Recognition of Markush Structures
Lucas Morin, Valery Weber, Ahmed Nassar et al.
JAMUN: Bridging Smoothed Molecular Dynamics and Score-Based Learning for Conformational Ensemble Generation
Ameya Daigavane, Bodhi Vani, Darcy Davidson et al.
Relation-Aware Equivariant Graph Networks for Epitope-Unknown Antibody Design and Specificity Optimization
Lirong Wu, Haitao Lin, Yufei Huang et al.
MAGNet: Motif-Agnostic Generation of Molecules from Scaffolds
Leon Hetzel, Johanna Sommer, Bastian Rieck et al.
REBIND: Enhancing Ground-state Molecular Conformation Prediction via Force-Based Graph Rewiring
Taewon Kim, Hyunjin Seo, Sungsoo Ahn et al.
Towards Human-Understandable Multi-Dimensional Concept Discovery
Arne GrobrΓΌgge, Niklas KΓΌhl, Gerhard Satzger et al.
DMol: A Highly Efficient and Chemical Motif-Preserving Molecule Generation Platform
Peizhi Niu, Yu-Hsiang Wang, Vishal Rana et al.
ModuLM: Enabling Modular and Multimodal Molecular Relational Learning with Large Language Models
Zhuo Chen, YIZHEN ZHENG, Huan Yee Koh et al.
Template-Guided 3D Molecular Pose Generation via Flow Matching and Differentiable Optimization
NoΓ©mie Bergues, Arthur CarrΓ©, Paul Join-Lambert et al.
Atomic Diffusion Models for Small Molecule Structure Elucidation from NMR Spectra
Ziyu Xiong, Yichi Zhang, Foyez Alauddin et al.
RETRO SYNFLOW: Discrete Flow-Matching for Accurate and Diverse Single-Step Retrosynthesis
Robin Yadav, Qi Yan, Guy Wolf et al.
Multi-modal Contrastive Learning with Negative Sampling Calibration for Phenotypic Drug Discovery
Jiahua Rao, Hanjing Lin, Leyu Chen et al.
UniSim: A Unified Simulator for Time-Coarsened Dynamics of Biomolecules
Ziyang Yu, Wenbing Huang, Yang Liu
InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization
Yifan Niu, Ziqi Gao, Tingyang Xu et al.
Blend the Separated: Mixture of Synergistic Experts for Data-Scarcity Drug-Target Interaction Prediction
Xinlong Zhai, Chunchen Wang, Ruijia Wang et al.
Fast and Accurate Blind Flexible Docking
Zizhuo Zhang, Lijun Wu, Kaiyuan Gao et al.
Data Distillation for extrapolative protein design through exact preference optimization
Mostafa Karimi, Sharmi Banerjee, Tommi Jaakkola et al.
Integrating Protein Dynamics into Structure-Based Drug Design via Full-Atom Stochastic Flows
Xiangxin Zhou, Yi Xiao, Haowei Lin et al.
DesignX: Human-Competitive Algorithm Designer for Black-Box Optimization
Hongshu Guo, Zeyuan Ma, Yining Ma 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.
MACS: Multi-Agent Reinforcement Learning for Optimization of Crystal Structures
Elena Zamaraeva, Christopher Collins, George Darling et al.
Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models
Songtao Liu, Hanjun Dai, Yue Zhao et al.
3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery
Xiuyuan Hu, Guoqing Liu, Can Chen et al.
Drug Discovery with Dynamic Goal-aware Fragments
Seul Lee, Seanie Lee, Kenji Kawaguchi et al.
Interaction-based Retrieval-augmented Diffusion Models for Protein-specific 3D Molecule Generation
Zhilin Huang, Ling Yang, Xiangxin Zhou et al.
MolCRAFT: Structure-Based Drug Design in Continuous Parameter Space
Yanru Qu, Keyue Qiu, Yuxuan Song et al.
Reframing Structure-Based Drug Design Model Evaluation via Metrics Correlated to Practical Needs
Bowen Gao, Haichuan Tan, Yanwen Huang 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.
NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation
Zhiyuan Liu, Yanchen Luo, Han Huang et al.
UniMoMo: Unified Generative Modeling of 3D Molecules for De Novo Binder Design
Xiangzhe Kong, Zishen Zhang, Ziting Zhang et al.
CombiMOTS: Combinatorial Multi-Objective Tree Search for Dual-Target Molecule Generation
Thibaud Southiratn, Bonil Koo, Yijingxiu Lu et al.
Latent Retrieval Augmented Generation of Cross-Domain Protein Binders
Zishen Zhang, Xiangzhe Kong, Wenbing Huang et al.
A Dataset for Distilling Knowledge Priors from Literature for Therapeutic Design
Haydn Jones, Natalie Maus, Josh magnus Ludan et al.
Empower Structure-Based Molecule Optimization with Gradient Guided Bayesian Flow Networks
Keyue Qiu, Yuxuan Song, Jie Yu et al.
GenMol: A Drug Discovery Generalist with Discrete Diffusion
Seul Lee, Karsten Kreis, Srimukh Veccham et al.
Piloting Structure-Based Drug Design via Modality-Specific Optimal Schedule
Keyue Qiu, Yuxuan Song, Zhehuan Fan et al.
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning
Peter Eckmann, Dongxia Wu, Germano Heinzelmann et al.
NeuralPLexer3: Accurate Biomolecular Complex Structure Prediction with Flow Models
Jarren Zhuoran Qiao, Feizhi Ding, Thomas Dresselhaus et al.
Offline Model-based Optimization for Real-World Molecular Discovery
Dong-Hee Shin, Young-Han Son, Hyun Jung Lee et al.
3D Interaction Geometric Pre-training for Molecular Relational Learning
Namkyeong Lee, Yunhak Oh, Heewoong Noh et al.
AANet: Virtual Screening under Structural Uncertainty via Alignment and Aggregation
Wenyu Zhu, Jianhui Wang, Bowen Gao et al.
Enhancing Ligand Validity and Affinity in Structure-Based Drug Design with Multi-Reward Optimization
Seungbeom Lee, Munsun Jo, Jungseul Ok et al.
Training-free Multi-objective Diffusion Model for 3D Molecule Generation
XU HAN, Caihua Shan, Yifei Shen et al.
Self-supervised Blending Structural Context of Visual Molecules for Robust Drug Interaction Prediction
Tengfei Ma, Kun Chen, Yongsheng Zang et al.
DynaPhArM: Adaptive and Physics-Constrained Modeling for Target-Drug Complexes with Drug-Specific Adaptations
Diya Zhang, Mengwei Sun, Xingdan Wang et al.
Searching for High-Value Molecules Using Reinforcement Learning and Transformers
Raj Ghugare, Santiago Miret, Adriana Hugessen et al.
Scalable and Cost-Efficient de Novo Template-Based Molecular Generation
Piotr GaiΕski, Oussama Boussif, Andrei Rekesh 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.
Aligning Transformers with Continuous Feedback via Energy Rank Alignment
Shriram Chennakesavalu, Frank Hu, Sebastian Ibarraran et al.
Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models
Zhilin Huang, Ling Yang, Xiangxin Zhou et al.
Reaction Prediction via Interaction Modeling of Symmetric Difference Shingle Sets
Runhan Shi, Letian Chen, Gufeng Yu et al.
Protein Design with Dynamic Protein Vocabulary
Nuowei Liu, Jiahao Kuang, Yanting Liu et al.
DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization
Xiangxin Zhou, Xiwei Cheng, Yuwei Yang et al.
Omni-Mol: Multitask Molecular Model for Any-to-any Modalities
Chengxin Hu, Hao Li, Yihe Yuan et al.
CL-MFAP: A Contrastive Learning-Based Multimodal Foundation Model for Molecular Property Prediction and Antibiotic Screening
Gen Zhou, Sugitha Janarthanan, Yutong Lu et al.
ForceFM: Enhancing Protein-Ligand Predictions through Force-Guided Flow Matching
HUANLEI GUO, Song LIU, Bingyi Jing
Unlocking hidden biomolecular conformational landscapes in diffusion models at inference time
Daniel D. Richman, Jessica Karaguesian, Carl-Mikael Suomivuori et al.
Flexible MOF Generation with Torsion-Aware Flow Matching
Nayoung Kim, Seongsu Kim, Sungsoo Ahn
Conversational Drug Editing Using Retrieval and Domain Feedback
Shengchao Liu, Jiongxiao Wang, Yijin Yang et al.
Reinforced Active Learning for Large-Scale Virtual Screening with Learnable Policy Model
Yicong Chen, Jiahua Rao, Jiancong Xie et al.
Bridging the Gap Between Cross-Domain Theory and Practical Application: A Case Study on Molecular Dissolution
Sihan Wang, Wenjie Du, Qing Zhu et al.
KnowMol: Advancing Molecular Large Language Models with Multi-Level Chemical Knowledge
Zaifei Yang, Hong Chang, RuiBing Hou et al.
Removing Biases from Molecular Representations via Information Maximization
Chenyu Wang, Sharut Gupta, Caroline Uhler et al.
Fine-grained List-wise Alignment for Generative Medication Recommendation
Chenxiao Fan, Chongming Gao, Wentao Shi et al.