Key papers

• AI-Driven Drug Discovery: A Comprehensive Review (2026)
  Garima Sharma
  17.91
• Antiviral drug discovery and development: challenges and future directions (2026)
  Shaoqing Du et al.
  11.12
• The Open Molecules 2025 (OMol25) Dataset, Evaluations, and Models (2025)
  Daniel S. Levine et al.
  11.05
• InternAgent-1.5: A Unified Agentic Framework for Long-Horizon Autonomous Scientific Discovery (2026)
  Shiyang Feng et al.
  11.03
• Towards an AI co-scientist (2025)
  Juraj Gottweis et al.
  10.78
• BixBench: a Comprehensive Benchmark for LLM-based Agents in Computational Biology (2025)
  Ludovico Mitchener et al.
  10.60
• Digital materials ecosystem: from databases to AI agents for autonomous discovery (2026)
  Di Zhang et al.
  10.48
• DrugGen 2: A disease-aware language model for enhancing drug discovery (2026)
  Ali Motahharynia et al.
  10.47
• UMA: A Family of Universal Models for Atoms (2025)
  Brandon M. Wood et al.
  10.14
• BERT Learns (and Teaches) Chemistry (2020)
  Josh Payne et al.
  10.07
• MACE-OFF: Transferable Short Range Machine Learning Force Fields for Organic Molecules (2023)
  D\'avid P\'eter Kov\'acs et al.
  10.02
• Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets (2022)
  Xingang Peng et al.
  10.00
• MassSpecGym: A benchmark for the discovery and identification of molecules (2024)
  Roman Bushuiev et al.
  9.94
• SmileyLlama: Modifying Large Language Models for Directed Chemical Space Exploration (2024)
  Joseph M. Cavanagh et al.
  9.86
• DeepScientist: Advancing Frontier-Pushing Scientific Findings Progressively (2025)
  Yixuan Weng et al.
  9.44
• Accurate RNA 3D structure prediction using a language model-based deep learning approach (2022)
  Tao Shen et al.
  9.35
• Machine Learning for De Novo Molecular Generation: A Comprehensive Review. (2026)
  Yingjun Chen et al.
  9.05
• Artificial Intelligence in Drug Discovery: Integrative Advances From Data to Therapeutic Innovation (2026)
  M. Mehran et al.
  9.05
• Self-Assembled Monolayers in p-i-n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning-Accelerated Material Discovery. (2026)
  Asmat Ullah et al.
  9.05
• Enhanced Sampling in the Age of Machine Learning: Algorithms and Applications (2025)
  Kai Zhu et al.
  8.98
• Large Language Models to Accelerate Organic Chemistry Synthesis (2025)
  Yu Zhang et al.
  8.79
• The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search (2025)
  Yutaro Yamada et al.
  8.70
• Materials Informatics: Emergence to Autonomous Discovery in the Age of AI. (2026)
  T. Lookman et al.
  8.66
• Artificial Intelligence for Natural Products Drug Discovery in Neurodegenerative Therapies: A Review (2026)
  F. Fontanella et al.
  8.66
• Graph Neural Networks in Modern AI-aided Drug Discovery (2025)
  Odin Zhang et al.
  8.64
• Equivariant Neural Diffusion for Molecule Generation (2025)
  Fran\c{c}ois Cornet and Grigory Bartosh and Mikkel N. Schmidt and Christian A. Naesseth
  8.64
• A Computational Community Blind Challenge on Pan-Coronavirus Drug Discovery Data (2026)
  Hugo MacDermott-Opeskin et al.
  8.23
• Unified modeling of 3D molecular generation via atomic interactions with PocketXMol. (2026)
  Xingang Peng et al.
  8.23
• Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design (2025)
  Tong Chen et al.
  8.18
• Machine Learning - Driven Materials Discovery: Unlocking Next-Generation Functional Materials - A review (2025)
  Dilshod Nematov and Mirabbos Hojamberdiev
  8.17
• SE(3)-Equivariant Ternary Complex Prediction Towards Target Protein Degradation (2025)
  Fanglei Xue et al.
  8.12
• Learning-Order Autoregressive Models with Application to Molecular Graph Generation (2025)
  Zhe Wang et al.
  8.07
• MACE-POLAR-1: A Polarisable Electrostatic Foundation Model for Molecular Chemistry (2026)
  Ilyes Batatia et al.
  8.00
• OmniScience: A Domain-Specialized LLM for Scientific Reasoning and Discovery (2025)
  Vignesh Prabhakar et al.
  7.96
• PharmAgents: Building a Virtual Pharma with Large Language Model Agents (2025)
  Bowen Gao et al.
  7.96
• Multi-domain Distribution Learning for De Novo Drug Design (2025)
  Arne Schneuing et al.
  7.86
• Democratising real-world drug discovery through agentic AI. (2026)
  Jiazhen He et al.
  7.73
• Benchmarking Pretrained Molecular Embedding Models For Molecular Representation Learning (2025)
  Mateusz Praski et al.
  7.72
• AI-Powered Prediction of Nanoparticle Pharmacokinetics: A Multi-View Learning Approach (2025)
  Amirhossein Khakpour et al.
  7.71
• RiNALMo: General-Purpose RNA Language Models Can Generalize Well on Structure Prediction Tasks (2024)
  Rafael Josip Peni\'c et al.
  7.62
• FlowMol3: Flow Matching for 3D De Novo Small-Molecule Generation (2025)
  Ian Dunn et al.
  7.57
• System of Agentic AI for the Discovery of Metal-Organic Frameworks (2025)
  Theo Jaffrelot Inizan et al.
  7.50
• Physics-Informed Neural Network-Based Discovery of Hyperelastic Constitutive Models from Extremely Scarce Data (2025)
  Hyeonbin Moon et al.
  7.50
• Challenging reaction prediction models to generalize to novel chemistry (2025)
  John Bradshaw et al.
  7.47
• Amortized Sampling with Transferable Normalizing Flows (2025)
  Charlie B. Tan et al.
  7.41
• Kosmos: An AI Scientist for Autonomous Discovery (2025)
  Ludovico Mitchener et al.
  7.41
• MDCrow: Automating Molecular Dynamics Workflows with Large Language Models (2025)
  Quintina Campbell et al.
  7.39
• drGT: Attention-Guided Gene Assessment of Drug Response Utilizing a Drug-Cell-Gene Heterogeneous Network (2024)
  Yoshitaka Inoue et al.
  7.38
• Computing solvation free energies of small molecules with experimental accuracy (2024)
  J. Harry Moore et al.
  7.38
• AlphaEvolve: A coding agent for scientific and algorithmic discovery (2025)
  Alexander Novikov et al.
  7.35
• A Text-guided Protein Design Framework (2023)
  Shengchao Liu et al.
  7.32
• Advancing Molecular Machine Learning Representations with Stereoelectronics-Infused Molecular Graphs (2024)
  Daniil A. Boiko et al.
  7.30
• Collaborative Expert LLMs Guided Multi-Objective Molecular Optimization (2025)
  Jiajun Yu et al.
  7.29
• Multi-view biomedical foundation models for molecule-target and property prediction (2024)
  Parthasarathy Suryanarayanan et al.
  7.23
• AgenticSciML: Collaborative Multi-Agent Systems for Emergent Discovery in Scientific Machine Learning (2025)
  Qile Jiang et al.
  7.22
• ChemDFM-R: A Chemical Reasoning LLM Enhanced with Atomized Chemical Knowledge (2025)
  Zihan Zhao et al.
  7.19
• Gumbel-Softmax Flow Matching with Straight-Through Guidance for Controllable Biological Sequence Generation (2025)
  Sophia Tang et al.
  7.13
• Long-Term Potentiation and Closed-Loop Learning in Paired Brain Organoids for CNS Drug Discovery (2026)
  Corey Rountree et al.
  7.13
• IMPACT Framework: Establishing Global Standards for Artificial Intelligence Implementation, Methodology, and Translation in Drug Discovery (2026)
  Amit Gangwal et al.
  7.13
• Artificial Intelligence in Accelerating Materials Discovery: Opportunities and Challenges (2026)
  Avadhesh Kumar Yadav
  7.13