Yu Kang

Genetic Algorithm-Based Receptor Ligand: A Genetic Algorithm-Guided Generative Model to Boost the Novelty and Drug-Likeness of Molecules in a Sampling Chemical Space.

[BibT_eX]

[DOI]

Mingyang Wang

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J. Chem. Inf. Model., February, 2024

Comprehensive Evaluation of 10 Docking Programs on a Diverse Set of Protein-Cyclic Peptide Complexes.

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J. Chem. Inf. Model., 2024

DrugFlow: An AI-Driven One-Stop Platform for Innovative Drug Discovery.

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J. Chem. Inf. Model., 2024

TransfIGN: A Structure-Based Deep Learning Method for Modeling the Interaction between HLA-A*02:01 and Antigen Peptides.

[BibT_eX]

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J. Chem. Inf. Model., 2024

Evaluation of AlphaFold2 Structures for Hit Identification across Multiple Scenarios.

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J. Chem. Inf. Model., 2024

Token-Mol 1.0: Tokenized drug design with large language model.

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[DOI]

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CoRR, 2024

Deep Geometry Handling and Fragment-wise Molecular 3D Graph Generation.

[BibT_eX]

[DOI]

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CoRR, 2024

AttABseq: an attention-based deep learning prediction method for antigen-antibody binding affinity changes based on protein sequences.

[BibT_eX]

[DOI]

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Briefings Bioinform., 2024

TB-IECS: an accurate machine learning-based scoring function for virtual screening.

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J. Cheminformatics, December, 2023

Small-Molecule Conformer Generators: Evaluation of Traditional Methods and AI Models on High-Quality Data Sets.

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J. Chem. Inf. Model., November, 2023

ResGen is a pocket-aware 3D molecular generation model based on parallel multiscale modelling.

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[DOI]

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Nat. Mac. Intell., September, 2023

ML-PLIC: a web platform for characterizing protein-ligand interactions and developing machine learning-based scoring functions.

[BibT_eX]

[DOI]

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Briefings Bioinform., September, 2023

On the Dynamic Mechanism of Long-Flexible Fatty Acid Binding to Fatty Acid Binding Protein: Resolving the Long-Standing Debate.

[BibT_eX]

[DOI]

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J. Chem. Inf. Model., August, 2023

Deep Generation Model Guided by the Docking Score for Active Molecular Design.

[BibT_eX]

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J. Chem. Inf. Model., May, 2023

Can molecular dynamics simulations improve predictions of protein-ligand binding affinity with machine learning?

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[DOI]

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Briefings Bioinform., March, 2023

Quasiclassical Trajectory Simulation as a Protocol to Build Locally Accurate Machine Learning Potentials.

[BibT_eX]

[DOI]

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J. Chem. Inf. Model., February, 2023

Efficient and accurate large library ligand docking with KarmaDock.

[BibT_eX]

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Nat. Comput. Sci., 2023

Learning on topological surface and geometric structure for 3D molecular generation.

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Nat. Comput. Sci., 2023

Organic Compound Synthetic Accessibility Prediction Based on the Graph Attention Mechanism.

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J. Chem. Inf. Model., 2022

Exploring Low-Toxicity Chemical Space with Deep Learning for Molecular Generation.

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J. Chem. Inf. Model., 2022

ALipSol: An Attention-Driven Mixture-of-Experts Model for Lipophilicity and Solubility Prediction.

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J. Chem. Inf. Model., 2022

Molecular View on the Dissociation Pathways and Transactivation Regulation Mechanism of Nonsteroidal GR Ligands.

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J. Chem. Inf. Model., 2022

ReMODE: a deep learning-based web server for target-specific drug design.

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J. Cheminformatics, 2022

fastDRH: a webserver to predict and analyze protein-ligand complexes based on molecular docking and MM/PB(GB)SA computation.

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Briefings Bioinform., 2022

CovalentInDB: a comprehensive database facilitating the discovery of covalent inhibitors.

[BibT_eX]

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Nucleic Acids Res., 2021

The impact of cross-docked poses on performance of machine learning classifier for protein-ligand binding pose prediction.

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J. Cheminformatics, 2021

Do we need different machine learning algorithms for QSAR modeling? A comprehensive assessment of 16 machine learning algorithms on 14 QSAR data sets.

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Briefings Bioinform., 2021

Development and Evaluation of MM/GBSA Based on a Variable Dielectric GB Model for Predicting Protein-Ligand Binding Affinities.

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J. Chem. Inf. Model., 2020

farPPI: a webserver for accurate prediction of protein-ligand binding structures for small-molecule PPI inhibitors by MM/PB(GB)SA methods.

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Bioinform., 2019

Cheminformatic Insight into the Differences between Terrestrial and Marine Originated Natural Products.

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J. Chem. Inf. Model., 2018

Characterizing Drug-Target Residence Time with Metadynamics: How To Achieve Dissociation Rate Efficiently without Losing Accuracy against Time-Consuming Approaches.

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