Key papers

• Machine Learning for De Novo Molecular Generation: A Comprehensive Review. (2026)
  Yingjun Chen et al.
  9.10
• Machine learning, docking, or physics for structure prediction of ligand-induced ternary complexes. (2026)
  Riccardo Solazzo et al.
  7.19
• AbBiBench: A Benchmark for Antibody Binding Affinity Maturation and Design (2025)
  Xinyan Zhao et al.
  6.80
• Protein Language Models and Structure-Based Machine Learning for Prediction of Allosteric Binding Sites in Protein Kinases: An Explainable AI Framework Grounded in Energy Landscape-Encoded Frustration (2026)
  Kamila Riedlová et al.
  5.52
• Water-Guided Docking Improves Prediction of Protein-Glycan Complexes. (2026)
  J. O. Lannot et al.
  5.52
• Differentiable Folding for Nearest Neighbor Model Optimization (2025)
  Ryan K. Krueger et al.
  5.24
• IgCraft: A versatile sequence generation framework for antibody discovery and engineering (2025)
  Matthew Greenig et al.
  5.24
• Zero-shot protein stability prediction by inverse folding models: a free energy interpretation (2025)
  Jes Frellsen et al.
  4.98
• Structure-Based Experimental Datasets for Benchmarking Protein Simulation Force Fields (2023)
  Chapin E. Cavender et al.
  4.48
• Two-dimensional geometric template diffusion for boosting single-sequence protein structure prediction (2026)
  Xudong Wang et al.
  4.20
• Harnessing angular geometry in deep learning for protein-ligand binding affinity prediction (2026)
  Julia Rahman et al.
  4.20
• Extending Conformational Ensemble Prediction to Multidomain Proteins and Protein Complex (2026)
  Junjie Zhu et al.
  4.20
• Constant pH Simulation with FMM Electrostatics in GROMACS. (A) Design and Applications (2024)
  Eliane Briand et al.
  4.08
• CellFlux: Simulating Cellular Morphology Changes via Flow Matching (2025)
  Yuhui Zhang et al.
  3.59
• RNACG: A Universal RNA Sequence Conditional Generation model based on Flow-Matching (2024)
  Letian Gao et al.
  3.25
• QuantumDNA: A Python Package for Analyzing Quantum Charge Dynamics in DNA and Exploring Its Biological Relevance (2025)
  Dennis Herb et al.
  2.65
• Aligning Large Language Models and Geometric Deep Models for Protein Representation (2024)
  Dong Shu et al.
  2.54
• Persistent Manifold Learning of Protein Properties (2026)
  Xingjian Xu et al.
  2.00
• AMPBench-MT: A Homology-Controlled Benchmark for Antimicrobial Peptide Potency, Spectrum, and Safety Prediction (2026)
  Ziheng Zhou et al.
  2.00
• Bayesian-Steered Structure Prediction of Mechanical Biomolecules Using Twisted Diffusion (2026)
  Colin Klaus et al.
  1.94
• Hyaline: Geometric Deep Learning for Accurate Prediction of G Protein-Coupled Receptor Activation States from Structure (2026)
  A. Khaleq et al.
  1.94
• Computational discovery of SARS-CoV-2 viral entry inhibitory peptides from Androctonus mauretanicus scorpion venom: molecular docking and molecular dynamics simulations targeting the spike protein (2026)
  Reda Chahir et al.
  1.94
• DualBind: Dual-module protein-ligand binding affinity prediction with adaptive GNN and structure-aware transformer (2026)
  Xuan Lin et al.
  1.94
• Visual-like 2D Geometric Template Diffusion for Boosting Single-Sequence Protein Structure Prediction (2026)
  Xudong Wang et al.
  1.94
• RIMGOGraph: integrating AlphaFold-derived residue interaction graphs and protein language embeddings for structure-informed protein function prediction (2026)
  Tong Chang et al.
  1.94
• SimpleFold-Turbo: Adaptive Inference Caching Yields 14-fold Acceleration of Flow-matching Protein Structure Prediction (2026)
  Geoffrey J. Taghon
  1.94
• HAGGNN: Hydration-Aware Geometric Graph Neural Network for Protein Thermal Stability Prediction. (2026)
  Yingying Jiang et al.
  1.94
• Structure-Aware Protein Language Model with Multi-Branch Ensemble for Nanobody–Antigen Interaction Prediction (2026)
  Fangli Ying et al.
  1.94
• Benchmarking MSA pairing for protein-protein complex structure prediction reveals a depth-over-pairing principle (2026)
  Yuxian Luo et al.
  1.94
• Hybrid BiLSTM machine learning with RNAfold-based thermodynamic modeling for RNA secondary structure prediction (2026)
  Jophy Lin
  1.94
• AI-Driven De Novo Binder Design: From Structure Prediction to Closed-Loop Optimization (2026)
  Xinhao Li et al.
  1.94
• Hybrid deep learning model (E2BNet) combining ESM2 and BiLSTM for 8-state protein secondary structure prediction (2026)
  Diganta Das Droba et al.
  1.94
• KASSPer: Kinase Active Site Structure Prediction using Protein and Ligand Language Models and Its Application to Virtual Screening (2026)
  Wonkyeong Jang et al.
  1.94
• From Atoms to Cells: AI-Based Structure Prediction Fueling Molecular Dynamics Simulations in Computational Structural Biology. (2026)
  Rafael C. Bernardi et al.
  1.94
• ME-pKa: A Deep Learning Method with Multimodal Learning for Protein pKa Prediction. (2026)
  Shanshan Shi et al.
  1.94
• An Overview of Molecular Docking (2026)
  Deepa. R et al.
  1.94
• Comparative benchmarking of template-based, evolutionary-diffusion, and generative language models for ispetase structure prediction (2026)
  Berkay Orcun Yener et al.
  1.94
• Stoic: Fast and accurate protein stoichiometry prediction (2026)
  Daniil Litvinov et al.
  1.94
• StrEAMM-Thioether: Efficient Structure Prediction for Thioether-Linked Cyclic Peptides. (2026)
  Minh Ngoc Ho et al.
  1.94
• Towards protein folding pathways by reconstructing protein residue networks with a policy-driven model (2026)
  Susan Khor
  1.83
• BConformeR: A Conformer Based on Mutual Sampling for Unified Prediction of Continuous and Discontinuous Antibody Binding Sites (2025)
  Zhangyu You et al.
  1.39
• Guided Generation for Developable Antibodies (2025)
  Siqi Zhao et al.
  1.33
• MDRefine: a Python package for refining Molecular Dynamics trajectories with experimental data (2024)
  Ivan Gilardoni et al.
  0.94
• A unified cross-attention model for predicting antigen binding specificity to both HLA and TCR molecules (2024)
  Chenpeng Yu et al.
  0.61
• The allosteric lever: towards a principle of specific allosteric response (2023)
  Maximilian Vossel et al.
  0.28
• SAMPL9 blind predictions using nonequilibrium alchemical approaches (2022)
  Piero Procacci et al.
  —
• DPST: De Novo Peptide Sequencing with Amino-Acid-Aware Transformers (2022)
  Yan Yang and Zakir Hossain and Khandaker Asif and Liyuan Pan and Shafin Rahman and Eric Stone
  —
• Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design (2022)
  J\"org K. H. Franke et al.
  —
• Antibody-Antigen Docking and Design via Hierarchical Equivariant Refinement (2022)
  Wengong Jin et al.
  —
• Heterogeneous reconstruction of deformable atomic models in Cryo-EM (2022)
  Youssef Nashed et al.
  —
• Hairygami: Analysis of DNA Nanostructures' Conformational Change Driven by Functionalizable Overhangs (2023)
  Matthew Sample et al.
  —
• AbODE: Ab Initio Antibody Design using Conjoined ODEs (2023)
  Yogesh Verma et al.
  —
• Sifting through the Noise: A Survey of Diffusion Probabilistic Models and Their Applications to Biomolecules (2024)
  Trevor Norton and Debswapna Bhattacharya
  —
• Characterizing RNA oligomers using Stochastic Titration Constant-pH Metadynamics simulations (2024)
  Tomas F.D. Silva and Giovanni Bussi
  —
• A Heterogeneous Network-based Contrastive Learning Approach for Predicting Drug-Target Interaction (2024)
  Junwei Hu et al.
  —