| 1 | Porphyromonas gingivalis in Alzheimer's disease brains: Evidence for disease causation and treatment… | メディシナルケミストリー | 2019年1月 | ✅ |
| 2 | kUPS: a molecular simulation engine for the AI era | 計算化学 | 2026年4月 | ✅ |
| 3 | Landscape-scale navigation unlocks antibody CDR structural logic for AI-guided rescue and therapeuti… | 機械学習・AI | 2026年4月 | ✅ |
| 4 | Structure-guided molecular design with contrastive 3D protein-ligand learning | 機械学習・AI | 2026年4月 | ✅ |
| 5 | Robust Inference-Time Steering of Protein Diffusion Models via Embedding Optimization | 機械学習・AI | 2026年2月 | ✅ |
| 6 | Regression with Large Language Models for Materials and Molecular Property Prediction | 機械学習・AI | 2024年(arXiv プレプリント) | ✅ |
| 7 | Mol-Debate: Multi-Agent Debate Improves Structural Reasoning in Molecular Design | 機械学習・AI | 2026年4月22日(arXiv プレプリント) | ✅ |
| 8 | Multimodal Graph Fusion with Statistically Guided Parsimonious Descriptor Selection for Molecular Pr… | 機械学習・AI | 2026年(Journal of Cheminformatics, 18:18) | ✅ |
| 9 | Advancing Reproducibility and Open Data in Theoretical and Computational Chemistry | 計算化学 | 2026年(J. Chem. Theory Comput. / J. Chem. Inf. Model. 連名エディトリアル) | ✅ |
| 10 | Ensemble Analyzer: An Open-Source Python Framework for Automated Conformer Ensemble Refinement | 計算化学 | 2026年4月 | ✅ |
| 11 | A Transformer for Reaction-Aware Compound Explorations with GFlowNet in QSAR-Guided Molecular Design | 機械学習・AI | 2026年4月(J. Chem. Inf. Model.、ASAP) | ✅ |
| 12 | Combined All-Atom Simulations and Biophysical Assays Uncover Loop-Driven Stabilization in the HRAS i… | 計算化学 | 2026年3月(J. Chem. Inf. Model. 2026, 66, 3276–3287) | ✅ |
| 13 | Rise of AI Technologies in Virtual Screening | 機械学習・AI | 2026年4月(J. Chem. Inf. Model., Letter) | ✅ |
| 14 | Drug Discovery and Computational Chemistry: A State-of-the-Art Review | 計算化学 | 2026年4月(ChemistrySelect、Accepted 2026-04-13) | ✅ |
| 15 | Revisiting Target-Aware de novo Molecular Generation with TarPass: Between Rational Design and Texas… | 計算化学 | 2026年4月(Advanced Science、Received 2026-03-12 / Accepted 2026-04-13) | ✅ |
| 16 | Identification of KKL-35 as a novel carnosine dipeptidase 2 (CNDP2) inhibitor by in silico screening | 計算化学 | 2025年9月(bioRxiv プレプリント) | ✅ |
| 17 | Supporting Medicinal Chemists in Iterative Hypothesis Generation for Drug Target Identification | 機械学習・AI | 2025年12月 | ✅ |
| 18 | DynaRepo: the repository of macromolecular conformational dynamics | 計算化学 | 2025年10月(Nucleic Acids Research、Database issue) | ✅ |
| 19 | MolAI: A Deep Learning Framework for Data-Driven Molecular Descriptor Generation and Advanced Drug D… | 機械学習・AI | 2025年9月(J. Chem. Inf. Model. 2025, 65, 9892–9909) | ✅ |
| 20 | SHARP: Generating Synthesizable Molecules via Fragment-Based Hierarchical Action-Space Reinforcement… | 機械学習・AI | 2025年10月(J. Chem. Inf. Model. 2025, 65, 11601–11619) | ✅ |
| 21 | VeGA: A Versatile Generative Architecture for Bioactive Molecules across Multiple Therapeutic Target… | 機械学習・AI | 2025年10月(J. Chem. Inf. Model. 2025, 65, 10918–10931) | ✅ |
| 22 | Combining GCN Structural Learning with LLM Chemical Knowledge for Enhanced Virtual Screening | 機械学習・AI | 2025年10月(J. Chem. Inf. Model. 2025, 65, 11510–11520) | ✅ |
| 23 | ChemFM as a scaling law guided foundation model pre-trained on informative chemicals | 機械学習・AI | 2025年11月(Communications Chemistry, Article in Press) | ✅ |
| 24 | LLMize: A Framework for Large Language Model-Based Numerical Optimization | 機械学習・AI | 2025年12月(arXiv プレプリント) | ✅ |
| 25 | HELM-BERT: A Transformer for Medium-Sized Peptide Property Prediction | 機械学習・AI | 2025年12月(arXiv プレプリント) | ✅ |
| 26 | aiXiv: A Next-Generation Open Access Ecosystem for Scientific Discovery Generated by AI Scientists | 機械学習・AI | 2025年8月(arXiv プレプリント、v2: 2025年12月更新) | ✅ |
| 27 | AI-Driven Molecular Design: Synergizing Deep Generative Models with Evolutionary Optimization | 機械学習・AI | 2025年11月(IConTES 2025, Antalya/Türkiye) | ✅ |
| 28 | LAMMPS-ANI: Large Scale Molecular Dynamics Simulations with ANI Neural Network Potential | 機械学習・AI | 2025年(ChemRxiv プレプリント) | ✅ |
| 29 | BindFlow: a free, user-friendly pipeline for absolute binding free energy calculations using free en… | 計算化学 | 2025年9月(bioRxiv preprint) | ✅ |
| 30 | Unified all-atom molecule generation with neural fields | 機械学習・AI | 2025年11月 | ✅ |
| 31 | Uncertainty-Aware Multi-Objective Reinforcement Learning-Guided Diffusion Models for 3D De Novo Mole… | 機械学習・AI | 2025年10月 | ✅ |
| 32 | Lost in Tokenization: Context as the Key to Unlocking Biomolecular Understanding in Scientific LLMs | 機械学習・AI | 2025年10月 | ✅ |
| 33 | Physics–Preference Aligned Tool-Using Policies for Molecular Design with Gemma-3 270M | 機械学習・AI | 2025年(NeurIPS 2025 ML4PS Workshop) | ✅ |
| 34 | Joint Design of Protein Surface and Structure Using a Diffusion Bridge Model | 機械学習・AI | 2025年11月(NeurIPS 2025) | ✅ |
| 35 | Improving protein-ligand complex generation with force field guidance | 機械学習・AI | 2025年(NeurIPS 2025 Workshop SimBioChem) | ✅ |
| 36 | Trillion Ligands per Day: Performance-Portable Virtual Screening via Compound Database Optimization … | 計算化学 | 2025年11月(SC '25, St Louis, MO, USA) | ✅ |
| 37 | Integrated In Silico Pipeline for Validating AI-Generated Ligands: From Docking Consensus to Molecul… | 計算化学 | 2026年(IWBBIO 2025 proceedings, LNBI 16050) | ✅ |
| 38 | Protocol for an automated virtual screening pipeline including library generation and docking evalua… | 計算化学 | 2025年12月 | ✅ |
| 39 | PLNet: Persistent Laplacian Neural Network for Protein–Protein Binding Free Energy Prediction | 機械学習・AI | 2025年12月 | ✅ |
| 40 | Modeling Protein–Small Molecule Conformational Ensembles with PLACER | 機械学習・AI | 2025年11月 | ✅ |
| 41 | Resolving Data Bias Improves Generalization in Binding Affinity Prediction | 機械学習・AI | 2025年 | ✅ |
| 42 | Navigating Structure-Based Drug Discovery with Emerging Innovations in Physics- and Knowledge-Based … | 計算化学 | 2025年 | ✅ |
| 43 | Sampling Challenges of MM/PBSA Binding Energy Calculations | 計算化学 | 2025年10月 | ✅ |
| 44 | MicroCycle: An Integrated and Automated Platform to Accelerate Drug Discovery | メディシナルケミストリー | 2024年1月25日(J. Med. Chem. 2024, 67, 2118–2128) | ✅ |
| 45 | Evaluating Ligand Docking Methods for Drugging Protein–Protein Interfaces: Insights from AlphaFold2 … | 計算化学 | 2025年(J. Cheminformatics 17:144) | ✅ |
| 46 | Computation of Protein-Ligand Binding Free Energies with a Quantum Mechanics-Based Mining Minima Alg… | 計算化学 | 2025年3月(Accepted: March 3, 2025) | ✅ |
| 47 | REINFORCE-ING Chemical Language Models for Drug Discovery | 機械学習・AI | 2025年11月(Accepted: November 7, 2025) | ✅ |
| 48 | SynKit: A Graph-Based Python Framework for Rule-Based Reaction Modeling and Analysis | 計算化学 | 2025年11月(Accepted: November 19, 2025) | ✅ |
| 49 | Boosting Drug Discovery: Expanding the Applicability of Fragment Dissolved Molecular Dynamics to Acc… | 計算化学 | 2025年(JCIM ASAP) | ✅ |
| 50 | RLMolLM: Reinforcement Learning-Enhanced Language Model Framework for Inverse Molecular Design | 機械学習・AI | 2025年11月 | ✅ |
| 51 | SiteMatcher: A Web Server for Structure-Based Drug Design Using Protein-Ligand Interaction Patterns | 計算化学 | 2025年11月 | ✅ |
| 52 | Combining AlphaFold with Focused Virtual Library Design in the Development of Novel CCR2 and CCR5 An… | メディシナルケミストリー | 2025年(JCIM ASAP) | ✅ |
| 53 | MAPCliff-WMGR: Exploring Activity Cliffs in Molecular Activity Prediction Enhanced by Weighted Molec… | 機械学習・AI | 2025年11月 | ✅ |
| 54 | Ultra-large Library Screening with an Evolutionary Algorithm in Rosetta (REvoLd) | 計算化学 | 2025年 | ✅ |
| 55 | A Quantitative Model of Structure-Based Virtual Screening Performance | 計算化学 | 2025年 | ✅ |
| 56 | FEP Ω: The End of Parameter Tuning | 計算化学 | 2025年 | ✅ |
| 57 | Benchmarking Active Learning Virtual Screening across Vina, Glide, and SILCS-based Docking at a Tran… | 計算化学 | 2025年 | ✅ |
| 58 | Rethinking Ligand Efficiency: Normalization Pitfalls, Uncertainty, and State-Invariant Metrics | メディシナルケミストリー | 2025年11月 | ✅ |
| 59 | PEGASUS: Unlocking Polarity in Cell-Permeable Cyclic Peptides Using AI Models Built on Massively Par… | 機械学習・AI | November 2025 | ✅ |
| 60 | EDWARD: E(3)-Equivariant Dual-Way Attentive Reduction for Peptide-to-Small-Molecule Design | 機械学習・AI | December 2025 | ✅ |
| 61 | A QM-AI Approach for the Acceleration of Accurate Assessments of Halogen-π Interactions by Training … | 計算化学 | December 2025 | ✅ |
| 62 | Improved ADME Prediction by Multitask Pretraining on Predicted Data: Insights from the ASAP-Polaris-… | 機械学習・AI | 2025年(J. Chem. Inf. Model.、掲載確定) | ✅ |
| 63 | Descriptor-First Approach for ADMET Prediction in the PolarisHub Antiviral Challenge | 機械学習・AI | 2026年1月(J. Chem. Inf. Model. 2026, 66, 406–412) | ✅ |
| 64 | BioChemAIgent: An AI-driven Protein Modeling and Docking Framework for Structure-Based Drug Discover… | 機械学習・AI | 2025年12月 | ✅ |
| 65 | A unified language model bridging de novo and fragment-based 3D molecule design delivers potent CBL-… | 機械学習・AI | 2025年11月 | ✅ |
| 66 | BENTO: Benchmarking Classical and AI Docking on Drug Design-Relevant Data | 計算化学 | 2025年12月 | ✅ |
| 67 | The Influence of Ligands on AlphaFold3 Prediction of Cryptic Pockets | 機械学習・AI | 2026年1月 | ✅ |
| 68 | FlashAffinity: Bridging the Accuracy-Speed Gap in Protein-Ligand Binding Affinity Prediction | 機械学習・AI | 2025年12月 | ✅ |
| 69 | Explaining how mutations affect AlphaFold predictions | 機械学習・AI | 2026年1月 | ✅ |
| 70 | SeedFold: Scaling Biomolecular Structure Prediction | 機械学習・AI | 2025年12月 | ✅ |
| 71 | Apo2Mol: 3D Molecule Generation via Dynamic Pocket-Aware Diffusion Models | 機械学習・AI | 2025年11月 | ✅ |
| 72 | SculptDrug: A Spatial Condition-Aware Bayesian Flow Model for Structure-based Drug Design | 機械学習・AI | 2025年11月 | ✅ |
| 73 | ReACT-Drug: Reaction-Template Guided Reinforcement Learning for de novo Drug Design | 機械学習・AI | 2025年12月 | ✅ |
| 74 | MolGuidance: Advanced Guidance Strategies for Conditional Molecular Generation with Flow Matching | 機械学習・AI | 2025年12月 | ✅ |
| 75 | Peptide2Mol: A Diffusion Model for Generating Small Molecules as Peptide Mimics for Targeted Protein… | 機械学習・AI | 2025年11月 | ✅ |
| 76 | Diffusion Models are Molecular Dynamics Simulators | 機械学習・AI | 2025年11月 | ✅ |
| 77 | MolSculpt: Sculpting 3D Molecular Geometries from Chemical Syntax | 機械学習・AI | 2025年12月 | ✅ |
| 78 | RxnBench: A Multimodal Benchmark for Evaluating Large Language Models on Chemical Reaction Understan… | 機械学習・AI | 2025年12月 | ✅ |
| 79 | MDAgent2: Large Language Model for Code Generation and Knowledge Q&A in Molecular Dynamics | 機械学習・AI | 2026年1月 | ✅ |
| 80 | MolAct: An Agentic RL Framework for Molecular Editing and Property Optimization | 機械学習・AI | 2025年12月 | ✅ |
| 81 | HalluMat: Detecting Hallucinations in LLM-Generated Materials Science Content Through Multi-Stage Ve… | 機械学習・AI | 2025年12月 | ✅ |
| 82 | FRAGMENTA: End-to-end Fragmentation-based Generative Model with Agentic Tuning for Drug Lead Optimiz… | 機械学習・AI | 2025年11月 | ✅ |
| 83 | AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.Org | 機械学習・AI | 2025年12月 | ✅ |
| 84 | SCP: Accelerating Discovery with a Global Web of Autonomous Scientific Agents | 機械学習・AI | 2025年12月 | ✅ |
| 85 | Understanding Structural Representation in Foundation Models for Polymers | 機械学習・AI | 2025年12月 | ✅ |
| 86 | Learning to Make Decisions for Autonomous Drug Design | 機械学習・AI | 2025年(Chalmers 工科大学 + ヨーテボリ大学 博士論文) | ✅ |
| 87 | Deep contrastive learning enables genome-wide virtual screening | 機械学習・AI | 2026年1月8日 | ✅ |
| 88 | Computational and experimental investigation for new transition metal selenides and sulfides: The im… | 計算化学 | 2016年7月 | ✅ |
| 89 | Assessing the potential of deep learning for protein–ligand docking | 機械学習・AI | 2025年(受理: 2025年11月) | ✅ |
| 90 | Monovalent pseudo-natural products supercharge degradation of IDO1 by its native E3 KLHDC3 | メディシナルケミストリー | 2026年(受理: 2025年11月) | ✅ |
| 91 | Quantum-machine-assisted drug discovery | 機械学習・AI | 2026年(npj Drug Discovery, 2026, 3:1) | ✅ |
| 92 | Extrapolating Foundation Generative Models with Physics: A Case Study of Exploring Peptide Conformat… | 機械学習・AI | 2025年12月(J. Phys. Chem. Lett. 受理) | ✅ |
| 93 | Discovery of MT-7117 (Dersimelagon Phosphoric Acid): A Novel, Potent, Selective, and Nonpeptidic Ora… | メディシナルケミストリー | 2024年12月(J. Med. Chem. 2024, 67, 21729–21748) | ✅ |
| 94 | Highlights of Medicinal Chemistry Optimization Strategies in Peptidomimetic Antimalarial Drug Discov… | メディシナルケミストリー | 2025年12月(J. Med. Chem. 受理) | ✅ |
| 95 | A New Fragment-Based Pharmacophore Virtual Screening Workflow Identifies Potent Inhibitors of SARS-C… | 計算化学 | 2025年(J. Comput. Chem. 2025; 46:e70201) | ✅ |
| 96 | ALCHEMD: Bridging Accessibility and Accuracy in Automated Relative Binding Free Energy Workflows | 計算化学 | 2025年12月(J. Chem. Theory Comput. オンライン先行公開) | ✅ |
| 97 | Automated Machine Learning Pipeline: Large Language Models-Assisted Automated Data set Generation fo… | 機械学習・AI | 2025年12月(J. Chem. Theory Comput. オンライン先行公開) | ✅ |
| 98 | DiffDec: Structure-Aware Scaffold Decoration with an End-to-End Diffusion Model | 機械学習・AI | 2023年10月(bioRxiv preprint); J. Chem. Inf. Model. 2024掲載 | ✅ |
| 99 | AlphaFold-RandomWalk and AlphaFold-Ensemble: Sampling Alternative Protein Conformations with Perturb… | 機械学習・AI | 2025年12月(オンライン先行公開) | ✅ |
| 100 | Meeko: Molecule Parametrization and Software Interoperability for Docking and Beyond | 計算化学 | 2025年12月 | ✅ |
| 101 | Improving the Reliability of Molecular String Representations for Generative Chemistry | 機械学習・AI | 2025年 | ✅ |
| 102 | Contact Parallel Cascade Selection Molecular Dynamics (cPaCS-MD) for Accurate In Silico Prediction o… | 計算化学 | 2026年1月(受理: 2025年12月16日) | ✅ |
| 103 | Novel GPU Engines for Virtual Screening of Giga-Sized Libraries Identify Inhibitors of Challenging T… | 計算化学 | 2025年9月 | ✅ |
| 104 | TorchANI 2.0: An Extensible, High-Performance Library for the Design, Training, and Use of NN-IPs | 機械学習・AI | 2025年10月 | ✅ |
| 105 | ADvisor: An Open-Source Tool for Applicability Domain Definition and Optimization in Molecular Predi… | 機械学習・AI | 2025年10月 | ✅ |
| 106 | Navigating Ultralarge Virtual Chemical Spaces with Product-of-Experts Chemical Language Models | 機械学習・AI | 2024年10月 | ✅ |
| 107 | ProfhEX: Empowering Early Drug Discovery with Machine Learning-Based Target Profiling and Liability … | 機械学習・AI | 2025年(受理: 2025年10月15日) | ✅ |
| 108 | gSelformer-MV: Multiview, Subgraph-Augmented Group SELFIES Transformer for Molecular Property Predic… | 機械学習・AI | 2025年(受理: 2025年12月) | ✅ |
| 109 | Can AI-Predicted Complexes Teach Machine Learning to Compute Drug Binding Affinity? | 機械学習・AI | 2025年(受理: 2025年12月) | ✅ |
| 110 | Chemprop v2: An Efficient, Modular Machine Learning Package for Chemical Property Prediction | 機械学習・AI | 2025年(受理: 2025年12月) | ✅ |
| 111 | TEMPL: A Template-Based Protein–Ligand Pose Prediction Baseline | 計算化学 | 2025年10月 | ✅ |
| 112 | Toward Generalizable Data-Driven Pharmacokinetics with Interpretable Neural ODEs | 機械学習・AI | 2026-02 (J. Chem. Inf. Model. 2026, 66, 2640−2650) | ✅ |
| 113 | ROSHAMBO2: Accelerating Molecular Alignment for Large Chemical Libraries with GPU Optimization and A… | 計算化学 | 2025-09 (J. Chem. Inf. Model. 65, 9842−9849) | ✅ |
| 114 | The growing role of open source software in molecular modeling | 計算化学 | 2026(ChemRxiv preprint, CC BY 4.0) | ✅ |
| 115 | SynFrag: Synthetic Accessibility Predictor based on Fragment Assembly Generation in Drug Discovery | 機械学習・AI | 2025(ChemRxiv preprint, CC BY 4.0) | ✅ |
| 116 | Practically Significant Method Comparison Protocols for Machine Learning in Small Molecule Drug Disc… | 機械学習・AI | 2025年9月 | ✅ |
| 117 | eRMSF: A Python Package for Ensemble-Based RMSF Analysis of Biomolecular Systems | 計算化学 | 2025年11月 | ✅ |
| 118 | From Obstacle to Design Advantage: Activity Cliff Aware Modeling for Small-Molecule Drug Discovery | 機械学習・AI | 2025年12月(Drug Discovery Today) | ✅ |
| 119 | Computational Approaches Enhance the Design of Molecular Glue Degraders for Undruggable Proteins | 計算化学 | 2025年12月(Drug Discovery Today Vol.31 No.1 Jan 2026) | ✅ |
| 120 | Deep Learning and Molecular Dynamics Reveal Promising EZH2 Inhibitors for Epigenetic Cancer Targetin… | 計算化学 | 2025年11月 | ✅ |
| 121 | graphpancake: A Python package for representing organic molecules as molecular graphs utilizing elec… | 機械学習・AI | 2025(ChemRxiv preprint, MIT license) | ✅ |
| 122 | A Foundation Model for Accurate Atomistic Simulations in Drug Design | 機械学習・AI | 2025年(ChemRxiv preprint) | ✅ |
| 123 | A Systematic Review of Drug-Related Interactions Utilizing Deep Learning and LLMs for Prediction and… | 機械学習・AI | 2025年12月 | ✅ |
| 124 | A Foundation Model for Accurate Atomistic Simulations in Drug Design | 機械学習・AI | 2025(ChemRxiv preprint) | ✅ |
| 125 | ChemTSv3: Generalizing Molecular Design via Flexible Search Space Control | 機械学習・AI | 2025(ChemRxiv preprint) | ✅ |
| 126 | Hybrid ChemBERTa and DFT Machine Learning Framework for Predicting Enantioselectivity in Organosilan… | 機械学習・AI | 2025(ChemRxiv preprint) | ✅ |
| 127 | Modular Assembly of Allosteric MEK Inhibitor Structural Elements Unravels Potency and Feedback-Modul… | メディシナルケミストリー | December 2015 | ✅ |
| 128 | Decoding of Inconsistent Biological Data: A Critical Step toward Enhanced AI Predictivity in Drug Di… | 機械学習・AI | 2025 (online ahead of print) | ✅ |
| 129 | Discovery of Potent and Efficacious Influenza PB2 Inhibitors | メディシナルケミストリー | December 2025 (online), January 2026 (issue) | ✅ |
| 130 | Active Learning FEP Using 3D-QSAR for Prioritizing Bioisosteres in Medicinal Chemistry | 計算化学 | April 2025 | ✅ |
| 131 | Application of Free Energy Perturbation (FEP) Methodology for Predicting the Binding Affinity of Mac… | 計算化学 | May 2025 | ✅ |
| 132 | MSFold: Multi-State Protein Structure Prediction via Parallel Tempering in Discrete Token Space | 機械学習・AI | March 2026 | ✅ |
| 133 | Protenix-v1: A Fully Open-Source Structure Prediction Model Surpassing AlphaFold3 | 機械学習・AI | February 2026 | ✅ |
| 134 | Structural Consequences of Introducing Multiple Ionizable Residues in a Protein with a Highly Charge… | 計算化学 | March 2026 | ✅ |
| 135 | G-screen: Scalable Receptor-Aware Virtual Screening through Flexible Ligand Alignment | 計算化学 | March 2026 | ✅ |
| 136 | Integrating BioEmu Ensemble Sampling with Molecular Dynamics and Markov State Models for Protein Con… | 計算化学 | January 2026 | ✅ |
| 137 | Beyond Bioisosteres: sp3-Rich Bicyclic Scaffolds for Improved ADME Properties in Lead Optimization | メディシナルケミストリー | 2026 | ✅ |
| 138 | Beyond SMILES: Evaluating Agentic AI Systems for Chemistry | 機械学習・AI | February 2026 | ✅ |
| 139 | DESRO: Scientific Reasoning from Outcomes via Large Language Models | 機械学習・AI | 2026 | ✅ |
| 140 | SpaceGFN: Programmable Chemical Space Exploration via GFlowNet | 機械学習・AI | 2026 | ✅ |
| 141 | Evaluating Boltz-2 for Protein-Ligand Binding Prediction: A Large-Scale Computational Study | 計算化学 | March 2026 | ✅ |
| 142 | SciDesignBench: A Benchmark for Scientific Design Reasoning with Reinforcement Learning from Scienti… | 機械学習・AI | March 2026 | ✅ |
| 143 | Beyond Affinity: A Comprehensive Benchmark for Structure-Based Drug Design Methods | 機械学習・AI | January 2026 | ✅ |
| 144 | TerraBind: Coarse-Grained Molecular Representations for Efficient Protein-Ligand Binding Affinity Pr… | 機械学習・AI | February 2026 | ✅ |
| 145 | DrugR: Optimizing Molecular Drugs through LLM-Based Explicit Reasoning | 機械学習・AI | 2026年2月(プレプリント) | ✅ |
| 146 | Reinforcement Learning with LLM-Guided Action Spaces for Synthesizable Lead Optimization | 機械学習・AI | 2026年4月(プレプリント) | ✅ |
| 147 | Reference-Guided Policy Optimization for Molecular Optimization via LLM Reasoning | 機械学習・AI | 2026年(ICLR 2026 採択) | ✅ |
| 148 | MolEvolve: LLM-Guided Evolutionary Search for Interpretable Molecular Optimization | 機械学習・AI | 2026年3月(プレプリント) | ✅ |
| 149 | MolecularIQ: Characterizing Chemical Reasoning Capabilities Through Symbolic Verification on Molecul… | 機械学習・AI | 2026年1月(プレプリント) | ✅ |
| 150 | Ontology-to-Tools Compilation for Executable Semantic Constraint Enforcement in LLM Agents | 機械学習・AI | 2026年2月(Cambridge Centre for Computational Chemical Engineering プレプリント) | ✅ |
| 151 | Accurate Predictions of Novel Biomolecular Interactions with IsoDDE | 機械学習・AI | 2026年2月(Isomorphic Labs テクニカルレポート) | ✅ |
| 152 | Epsilon: An Autonomous Research Engine with Epistemic Integrity for Scientific Discovery | 機械学習・AI | 2026年2月(独立プレプリント) | ✅ |
| 153 | A Unified Language Model Bridging De Novo and Fragment-Based 3D Molecule Design | 機械学習・AI | 2026年2月(Research Square プレプリント) | ✅ |
| 154 | Breaking the Barriers of Molecular Dynamics With Deep-Learning: Opportunities, Pitfalls, and How to … | 機械学習・AI | 2026年(WIREs Computational Molecular Science) | ✅ |
| 155 | Fast Sampling of Protein Conformational Dynamics | 計算化学 | 2026年(Science Advances) | ✅ |
| 156 | Physics Beats Diffusion: Agentic AI-Driven Virtual Screening Benchmark on a GPCR Target | 計算化学 | 2026年3月(Research Square プレプリント) | ✅ |
| 157 | PROTAC Approaches against Drug-Resistant EGFR C797S/L858R/T790M Mutants: Biological Evaluation and S… | メディシナルケミストリー | 2026年(RSC Medicinal Chemistry) | ✅ |
| 158 | DeepDegradome: A Structure-Aware Deep Learning Framework for PROTAC and Ligand Generation Against Pr… | 機械学習・AI | 2026年(PNAS) | ✅ |
| 159 | An LLM Chatbot to Facilitate Primary-to-Specialist Care Transitions: A Randomized Controlled Trial | 機械学習・AI | 2026年(Nature Medicine) | ✅ |
| 160 | Molecular Representation Matters: Comparative Evaluation of Fingerprints, RDKit Descriptors, and Has… | 機械学習・AI | 2026年(J. Phys. Chem. Lett.) | ✅ |
| 161 | In-Pocket 3D Graphs Enhance Ligand-Target Generative Small-Molecule Creation: A Dopamine D2 Receptor… | 機械学習・AI | 2026年(J. Phys. Chem. B) | ✅ |
| 162 | Large Library Docking for Polypharmacology: Simultaneous Discovery of Ligands for Multiple GPCR Targ… | 計算化学 | 2026年(J. Med. Chem.) | ✅ |
| 163 | What Happens in Successful Optimizations? A Survey of 2018–2024 Literature | メディシナルケミストリー | 2026年(J. Med. Chem.) | ✅ |
| 164 | Tokenization for Molecular Foundation Models: A Comprehensive Evaluation | 機械学習・AI | 2026年(J. Chem. Inf. Model.) | ✅ |
| 165 | ArtiDock: Accurate Machine Learning Approach to Protein-Ligand Docking for High-Throughput Virtual S… | 計算化学 | 2026年(Journal of Chemical Information and Modeling) | ✅ |
| 166 | A Relative Binding Free Energy Framework for Structurally Dissimilar Molecules (CBFE) | 計算化学 | 2026年(Journal of Chemical Information and Modeling, 66, 1626-1636) | ✅ |
| 167 | QUICK and Robust ESP and RESP Charges for Computational Biochemistry | 計算化学 | 2026年(Journal of Chemical Information and Modeling, 66, 3173-3187) | ✅ |
| 168 | CHARMM-GUI Hybrid ML/MM Builder for Hybrid Machine Learning and Molecular Mechanical Simulations | 計算化学 | 2026年(Journal of Chemical Information and Modeling, 66, 2960-2966) | ✅ |
| 169 | CHARMM-GUI Ligand Docker for Molecular Docking with Various Docking Programs | 計算化学 | 2026年(Journal of Chemical Information and Modeling) | ✅ |
| 170 | GlueFinder: A Data-Driven Framework for the Rational Discovery of Molecular Glues | 計算化学 | 2026年(Journal of Chemical Information and Modeling) | ✅ |
| 171 | DIVINE: Deterministic Top-Down Clustering Framework for Molecular Dynamics Trajectories | 計算化学 | 2026年(Journal of Chemical Information and Modeling) | ✅ |
| 172 | Improving Fidelity and Diversity in Chemical Language Transformers for Inverse Molecular Design | 機械学習・AI | 2026年(Journal of Chemical Information and Modeling, 66, 3059-3073) | ✅ |
| 173 | UCBbind: More Accurate Binding Affinity Prediction via Protein Homology and Ligand-Based Transfer Le… | 機械学習・AI | 2026年(Journal of Chemical Information and Modeling, 66, 2006-2016) | ✅ |
| 174 | BOLD-GPCRs: A Transformer-Powered App for Predicting Ligand Bioactivity across Class A GPCRs | 機械学習・AI | 2026年(Journal of Chemical Information and Modeling, 66, 855-866) | ✅ |
| 175 | MolOrgGPT: De Novo Generation via Large Language Models and Reinforcement Learning | 機械学習・AI | 2026年(Journal of Chemical Information and Modeling) | ✅ |
| 176 | Large Language Model Agent for Modular Task Execution in Drug Discovery | 機械学習・AI | 2026年(Journal of Chemical Information and Modeling) | ✅ |
| 177 | UniDock-Pro: Unified GPU-Accelerated Platform for High-Throughput Virtual Screening | 計算化学 | 2026年(Journal of Chemical Information and Modeling, 66, 2735-2752) | ✅ |
| 178 | A Computational Community Blind Challenge on Pan-Coronavirus Drug Discovery Data | 計算化学 | 2026年(Journal of Chemical Information and Modeling, 66, 3129-3149) | ✅ |
| 179 | Symmetry-Sensitive Analysis of Molecular Graph Neural Network Models | 機械学習・AI | 2026年(Journal of Chemical Information and Modeling, 66, 2610-2615) | ✅ |
| 180 | CoDrug: A Text-Driven Molecular Virtual Screening and Multiproperty Optimization Framework | 機械学習・AI | 2026年(Journal of Chemical Information and Modeling) | ✅ |
| 181 | Topology-Aware Generation and Activity-Based Filtering for Data-Scarce QAC Discovery | 機械学習・AI | 2026年(Journal of Chemical Information and Modeling) | ✅ |
| 182 | Assessing Boltz-2 Performance for the Binding Classification of Docking Hits | 機械学習・AI | 2026年(Journal of Chemical Information and Modeling, 66, 1511-1521) | ✅ |
| 183 | DualBind: Dual-Module Protein-Ligand Binding Affinity Prediction with Adaptive GNN and Structure-Awa… | 機械学習・AI | 2026年(Expert Systems With Applications, Vol. 309) | ✅ |
| 184 | Discovery of Covalent Ligands with AlphaFold3 | 計算化学 | 2026年(JACS) | ✅ |
| 185 | Advances in Computational Methods for PROTAC Drug Discovery | 機械学習・AI | March 2026 (Drug Discovery Today, Vol. 31, No. 2) | ✅ |
| 186 | Reward Function Design for Reinforcement Learning-Based Molecular Generation: Additive vs. Multiplic… | 機械学習・AI | 2025年(ChemRxiv プレプリント、Galvin/Elix) | ✅ |
| 187 | Independent Benchmarking of Boltzmann-Based Structure Prediction (Boltz-2) on ChEMBL-Derived Protein… | 機械学習・AI | 2026年(Chem-Bio Informatics Journal, Vol. 26) | ✅ |
| 188 | Hit Identification in Ultra Large Virtual Screening: An Integrative Review and Future Challenges | 機械学習・AI | 2026年1月(Drug Discovery Today) | ✅ |
| 189 | Machine Learning, Docking, or Physics for Structure Prediction of Ligand-induced Ternary Complexes | 機械学習・AI | 2026年1月(Current Opinion in Structural Biology 97:103217) | ✅ |
| 190 | NextTopDocker: The Largest-to-Date Docking Power Benchmark Reveals That Deep Learning Performs Gener… | 計算化学 | 2026年2月(ChemRxiv プレプリント) | ✅ |
| 191 | Generative Virtual Screening: From Search to Generate and Back | 機械学習・AI | 2026年2月(ChemRxiv プレプリント) | ✅ |
| 192 | ChemSpace Copilot: Agentic AI for Interactive Visualization and Exploration of Chemical Space | 機械学習・AI | 2026年3月(ChemRxiv プレプリント) | ✅ |
| 193 | Transparent Acceleration of Large Library Docking with ChemSTEP | 計算化学 | 2026年3月(ChemRxiv プレプリント) | ✅ |
| 194 | FragBERTa: Exploring Fragment-based Molecular Representation Learning with SAFE | 機械学習・AI | 2026年2月(ChemRxiv プレプリント) | ✅ |
| 195 | A Comparative Study of SMILES, SELFIES, and ECFP4 Representations for Molecular Similarity Search | 機械学習・AI | 2026年2月(ChemRxiv プレプリント) | ✅ |
| 196 | PyMolGen: Database-Driven Molecular Generation of Drug-Like Compounds | 機械学習・AI | 2026年3月(ChemRxiv プレプリント) | ✅ |
| 197 | A Reinforcement Learning-guided Genetic Algorithm Integrating Medicinal Chemistry-inspired Molecular… | 機械学習・AI | 2026年2月(ChemRxiv プレプリント) | ✅ |
| 198 | Docking of Millions: Accelerating a Million-Scale Virtual Screening Using Deep Learning | 機械学習・AI | 2026年3月(Briefings in Bioinformatics 27, bbag128) | ✅ |
| 199 | BBB-Permeable PROTACs: Where Do We Stand? | メディシナルケミストリー | 2026年(ACS Medicinal Chemistry Letters) | ✅ |
| 200 | Machine Learning for De Novo Molecular Generation: A Comprehensive Review | 機械学習・AI | 2026年(ACS Chemical Neuroscience 17, 666-680) | ✅ |
| 201 | From Prompt to Drug: Toward Pharmaceutical Superintelligence | 機械学習・AI | 2026年(ACS Central Science) | ✅ |
| 202 | PROTACs in Targeted Protein Degradation: Advances in Development and AI-Enhanced Drug Discovery | 機械学習・AI | 2026年3月(European Journal of Medicinal Chemistry Reports) | ✅ |
| 203 | AI-aided Drug Development for Protein Degraders: Design, Lead Identification, and Optimization | 機械学習・AI | 2025年(Annual Reports in Medicinal Chemistry 65) | ✅ |
| 204 | The Statistical Software Revolution in Pharmaceutical Development: Challenges and Opportunities in O… | 機械学習・AI | 2026年1月(Drug Discovery Today) | ✅ |
| 205 | New Approach Methodologies for Drug Discovery | 機械学習・AI | 2026年4月(Cell 189) | ✅ |
| 206 | Steering Semi-Flexible Molecular Diffusion Model for Structure-Based Drug Design with Reinforcement … | 機械学習・AI | 2026年4月(Science Advances 12, eady9955) | ✅ |
| 207 | Construction of a Multi-label Odor Prediction Model Based on Molecular Structures and Olfactory Rece… | 機械学習・AI | 2026年(Analytical Sciences) | ✅ |
| 208 | KIMMDY: A Biomolecular Reaction Emulator | 計算化学 | 2026年(Nature Communications 17:3500) | ✅ |
| 209 | Structural Optimization of Drug Molecules with Incrementally Trained Language Models | 機械学習・AI | 2026年(Nature Communications 17:3456) | ✅ |
| 210 | Harnessing AI to Build Virtual Cells | 機械学習・AI | 2026年4月(bioRxiv) | ✅ |
| 211 | UBio-MolFM: A Universal Molecular Foundation Model for Bio-Systems | 機械学習・AI | 2026年4月(preprint) | ✅ |
| 212 | MolMem: Memory-Augmented Agentic Reinforcement Learning for Sample-Efficient Molecular Optimization | 機械学習・AI | 2026年4月(preprint) | ✅ |
| 213 | MarS-FM: Generative Modeling of Molecular Dynamics via Markov State Models | 機械学習・AI | 2026年(preprint) | ✅ |
| 214 | Tabular Foundation Models for In-Context Prediction of Molecular Properties | 機械学習・AI | 2026年4月(preprint) | ✅ |
| 215 | How Creative Are Large Language Models in Generating Molecules? | 機械学習・AI | 2026年4月(preprint) | ✅ |
| 216 | Target Identification and Assessment in the Era of AI | 機械学習・AI | 2026年(Nat. Rev. Drug Discov. 2026) | ✅ |
| 217 | Chemical Space Navigation of Nitidine Leads to the Discovery of a Novel PD-L1 Degradation Agent by T… | メディシナルケミストリー | 2026年(J. Med. Chem. 2026, 69, 8237-8254) | ✅ |
| 218 | Scaffold-Hopping Strategy on a Series of Proteasome Inhibitors Led to a Preclinical Candidate for th… | メディシナルケミストリー | 2021年(J. Med. Chem. 2021, 64, 5905-5930) | ✅ |
| 219 | Automated Molecular Design in BRADSHAW, Applied to the Optimization of ERAP1 Inhibitors | メディシナルケミストリー | 2026年(J. Med. Chem. 2026, 69, 8869-8896) | ✅ |
| 220 | Discovery of YYSW001: A Highly Selective, Orally Bioavailable JAK1 Inhibitor Achieving Efficacy unde… | メディシナルケミストリー | 2026年(J. Med. Chem. 2026, 69, 7869-7903) | ✅ |
| 221 | How to Use Quantum Computers for Biomolecular Free Energies | 計算化学 | 2026年(J. Chem. Theory Comput. 2026, in press) | ✅ |
| 222 | Multiscale Hypergraph Masked Autoencoder with Δ-Property Alignment for Novel Molecular Representatio… | 機械学習・AI | 2026年(J. Chem. Inf. Model. 2026, 66, 3858-3877) | ✅ |
| 223 | ProtCross: Bridging the PDB-AlphaFold Gap for Binding Site Prediction with Protein Point Clouds | 機械学習・AI | 2026年(J. Chem. Inf. Model. 2026, 66, 3688-3701) | ✅ |
| 224 | DeepMIF: A Multiview Interactive Fusion-Based Deep Learning Method for RNA-Small Molecule Binding Af… | 機械学習・AI | 2026年(J. Chem. Inf. Model. 2026, 66, 3575-3589) | ✅ |
| 225 | Chat-Driven Computational (Bio)chemistry: Using LLM Agents to Accelerate Bio- and Chemoinformatics | 機械学習・AI | 2026年(J. Chem. Inf. Model. 2026, 66, 3397-3401) | ✅ |
| 226 | StereoMolGraph: Stereochemistry-Aware Molecular and Reaction Graphs | 計算化学 | 2026年(J. Chem. Inf. Model. 2026, 66, 3830-3839) | ✅ |
| 227 | LigandExplorer: An Automated Tool for Ligand Extraction from PDB Structures | 計算化学 | 2026年(J. Chem. Inf. Model. 2026, 66, 3026-3035) | ✅ |
| 228 | Unveiling the Activation Mechanism of Glucagon-Like Peptide-1 Receptor by an Ago-Allosteric Modulato… | 計算化学 | 2026年(J. Chem. Inf. Model.) | ✅ |
| 229 | Efficient Binding Affinity Estimation for Fragment-Based Compounds Using a Separated Topologies Appr… | 計算化学 | 2026年(J. Chem. Inf. Model.) | ✅ |
| 230 | Automated Force Field Developer and Optimizer Platform: Torsion Reparameterization | 計算化学 | 2026年(J. Chem. Inf. Model. 2026, 66, 3206-3219) | ✅ |
| 231 | AI-MedCraft: A Strategy-Driven AI Platform for Multi-Objective Molecular Design | 機械学習・AI | 2026年(J. Chem. Inf. Model. 2026, 66, 3424-3431) | ✅ |
| 232 | Doing More with Less: Accurate and Scalable Ligand Free Energy Calculations by Focusing on the Bindi… | 計算化学 | 2026年(J. Chem. Inf. Model.) | ✅ |
| 233 | Improving Stereochemical Limitations in Protein-Ligand Complex Structure Prediction | 計算化学 | 2025年(ACS Omega 2025, 10, 56075-56084) | ✅ |
| 234 | Evaluating the Progression of Large Language Model Capabilities for Small-Molecule Drug Design | 機械学習・AI | 2026年4月(preprint) | ✅ |
| 235 | Polyformer: a generative framework for thermodynamic modeling of polymeric molecules | 機械学習・AI | 2026年4月(preprint) | ✅ |
| 236 | The HTC-Claw: Automating Discovery through High-Throughput Computational Campaigns | 機械学習・AI | 2025年4月(preprint) | ✅ |
| 237 | UniSim: A Unified Simulator for Time-Coarsened Dynamics of Biomolecules | 機械学習・AI | 2025年(ICML 2025) | ✅ |
| 238 | LinkLlama: Enabling Large Language Model for Chemically Reasonable Linker Design | 機械学習・AI | 2026年4月(bioRxiv preprint) | ✅ |
| 239 | AlphaFast: High-throughput AlphaFold 3 via GPU-accelerated MSA construction | 計算化学 | 2026年2月(bioRxiv preprint) | ✅ |
| 240 | How to write an impactful review article? | メディシナルケミストリー | 2026年5月(Drug Discovery Today Vol.31 No.3) | ✅ |
| 241 | Large language models for molecular design: bridging the gap between chemical syntax and biological … | 機械学習・AI | 2026年3月(Drug Discovery Today Vol.31 No.2) | ✅ |
| 242 | Toward generalizable predictive models for DNA-encoded libraries | 機械学習・AI | 2026年3月(Drug Discovery Today Vol.31 No.2) | ✅ |
| 243 | Closing the loop: Experimentally validated methods in artificial intelligence–driven protein design | 機械学習・AI | 2026年(Current Opinion in Structural Biology Vol.98) | ✅ |
| 244 | A Scaffold-Hopping Strategy on a Series of Proteasome Inhibitors Which Led to a Preclinical Candidat… | メディシナルケミストリー | 2021年頃(J. Med. Chem. 掲載、著者 Thomas/Gilbert ら) | ✅ |
| 245 | Quantification of Hydrogen Bond Donating Ability of Biologically Relevant Compounds | メディシナルケミストリー | April 2024 | ✅ |
| 246 | The Role of Allylic Strain for Conformational Control in Medicinal Chemistry | メディシナルケミストリー | 2023 | ✅ |
| 247 | Discovery and Characterization of the Potent and Selective P2X4 Inhibitor BAY-1797 | メディシナルケミストリー | December 2019 | ✅ |
| 248 | Eyes on Topical Ocular Disposition: Design of a Lead JAK Inhibitor with Azetidin-3-Amino Bridging Sc… | メディシナルケミストリー | June 2023 | ✅ |
| 249 | 2025 In Review: Trends in Pharmaceutical Innovation | メディシナルケミストリー | March 2026 | ✅ |
| 250 | Design, Quality and Validation of the EU-OPENSCREEN Fragment Library Poised to a High-Throughput Scr… | メディシナルケミストリー | April 2024 | ✅ |
| 251 | Discovery of Novel and Potent Prolyl Hydroxylase Domain-Containing Protein (PHD) Inhibitors for the … | メディシナルケミストリー | January 2024 | ✅ |
| 252 | Discovery of Tetrahydropyrazolopyrazine Derivatives as Potent and Selective MYT1 Inhibitors for the … | メディシナルケミストリー | January 2024 | ✅ |
| 253 | Escaping from Flatland: Multiparameter Optimization Leads to the Discovery of Novel Tetrahydropyrido… | メディシナルケミストリー | May 2023 | ✅ |
| 254 | Geminal Diheteroatomic Motifs: Some Applications of Acetals, Ketals, and Their Sulfur and Nitrogen H… | メディシナルケミストリー | 2021 | ✅ |
| 255 | Synthetic Opportunities and Challenges for Macrocyclic Kinase Inhibitors | メディシナルケミストリー | May 2021 | ✅ |
| 256 | Validation of a New Methodology to Create Oral Drugs beyond the Rule of 5 for Intracellular Tough Ta… | メディシナルケミストリー | November 2023 | ✅ |
| 257 | Structure-Based Design and Evaluation of Reversible KRAS G13D Inhibitors | メディシナルケミストリー | December 2023 | ✅ |
| 258 | Rapid Traversal of Ultralarge Chemical Space using Machine Learning Guided Docking Screens | 計算化学 | 2023年(プレプリント)/ J. Chem. Inf. Model. 2024 | ✅ |
| 259 | FragGrow: A Web Server for Structure-Based Drug Design by Fragment Growing within Constraints | 計算化学 | 2024年 | ✅ |
| 260 | AlphaFold2-RAVE: From Sequence to Boltzmann Ranking | 計算化学 | 2023年 | ✅ |
| 261 | Conservation of Hot Spots and Ligand Binding Sites in Protein Models by AlphaFold2 | 計算化学 | 2024年 | ✅ |
| 262 | Comparative Assessment of Free Energy Computational Methods for Revealing the Interactions Driving P… | 計算化学 | 2026年4月(受付 2026年1月) | ✅ |
| 263 | MAIP: An Open-Source Tool to Enrich High-Throughput Screening Output and Identify Novel, Druglike Mo… | 機械学習・AI | 2023年 | ✅ |
| 264 | Accelerated Chemical Reaction Optimization Using Multi-Task Learning | 機械学習・AI | 2023年 | ✅ |
| 265 | Systematic Evaluation of Local and Global Machine Learning Models for the Prediction of ADME Propert… | 機械学習・AI | 2023年 | ✅ |
| 266 | Molecular Deep Learning at the Edge of Chemical Space | 機械学習・AI | 2026年3月(オンライン先行公開) | ✅ |
| 267 | A Multi-Grained Symmetric Differential Equation Model for Learning Protein-Ligand Binding Dynamics | 計算化学 | 2025年12月(Nature Communications in Press) | ✅ |
| 268 | NNP/MM: Fast Molecular Dynamics Simulations with Machine Learning Potentials and Molecular Mechanics | 計算化学 | 2022年1月(arXiv: 2201.08110),2023年(J. Chem. Inf. Model. 掲載) | ✅ |
| 269 | Scalable Spatio-Temporal SE(3) Diffusion for Long-Horizon Protein Dynamics | 計算化学 | 2026年2月 | ✅ |
| 270 | Artificial Intelligence for Direct Prediction of Molecular Dynamics Across Chemical Space | 計算化学 | 2025年5月(arXiv),2025年〜2026年(JCTC 掲載) | ✅ |
| 271 | Ultra-Large Virtual Screening Identifies PARP-1 and FSP1 Inhibitors via Adaptive Targeting | 計算化学 | 2023年4月(bioRxiv) | ✅ |
| 272 | ATMOS: Autoregressive Trajectory Model for Open-ended Simulation | 機械学習・AI | 2026年3月(arXiv) | ✅ |
| 273 | Exploring the Capabilities of Machine-Learned Potentials for Biomolecular Simulations | 計算化学 | 2022年1月(arXiv) | ✅ |
| 274 | Accelerating Protein Molecular Dynamics Simulation with DeepJump | 計算化学 | 2025年9月16日(arXiv) | ✅ |
| 275 | Artificial Intelligence for Direct Prediction of Molecular Dynamics Across Chemical Space | 計算化学 | 2026年(arXiv) | ✅ |
| 276 | BioMD: All-atom Generative Model for Biomolecular Dynamics Simulation | 機械学習・AI | 2025年9月2日(arXiv) | ✅ |
| 277 | Scalable Spatio-Temporal SE(3) Diffusion for Long-Horizon Protein Dynamics | 機械学習・AI | 2026年2月11日(arXiv) | ✅ |
| 278 | Guidelines for the analysis of free energy calculations | 計算化学 | 2015年5月(J. Comput. Aided Mol. Des. 29(5): 397–411) | ✅ |
| 279 | BIOPTIC B1 Ultra-High-Throughput Virtual Screening System Discovers LRRK2 Ligands in Vast Chemical S… | 機械学習・AI | 2025年(J. Chem. Inf. Model., accepted 2025) | ✅ |
| 280 | A bottom-up approach to find lead compounds in expansive chemical spaces | 計算化学 | 2025年(Communications Chemistry) | ✅ |
| 281 | Synthon-Based Strategies Exploiting Molecular Similarity and Protein-Ligand Interactions for Efficie… | 計算化学 | 2025年(J. Chem. Inf. Model., accepted April 2025) | ✅ |
| 282 | ANI Neural Networks Meet Electrostatics: A ML/MM Implementation in Amber | 計算化学 | 2024年 | ✅ |
| 283 | Hit Identification Driven by Combining Artificial Intelligence and Computational Chemistry Methods: … | メディシナルケミストリー | 2023年8月 | ✅ |
| 284 | When Macrocyclic Peptides Meet the Crystal Structure of a Melanocortin Receptor | メディシナルケミストリー | 2021年(受理 2020年12月) | ✅ |
| 285 | Autonomous Diffractometry Enabled by Visual Reinforcement Learning | 計算化学 | 2026年4月 | ✅ |
| 286 | Consensus docking aid to model the activity of an inhibitor of DNA methyltransferase 1 inspired by d… | 計算化学 | 2023年12月 | ✅ |