Luhua Lai
Orcid: 0000-0002-8343-7587
According to our database1,
Luhua Lai
authored at least 45 papers
between 1996 and 2022.
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Bibliography
2022
J. Chem. Inf. Model., 2022
Uncovering the Dominant Motion Modes of Allosteric Regulation Improves Allosteric Site Prediction.
J. Chem. Inf. Model., 2022
Advances and Challenges in De Novo Drug Design Using Three-Dimensional Deep Generative Models.
J. Chem. Inf. Model., 2022
BMC Bioinform., 2022
2021
ePharmer: An integrated and graphical software for pharmacophore-based virtual screening.
J. Comput. Chem., 2021
Learning to design drug-like molecules in three-dimensional space using deep generative models.
CoRR, 2021
A transferable deep learning approach to fast screen potential antiviral drugs against SARS-CoV-2.
Briefings Bioinform., 2021
2020
Discovery of Targeted Covalent Natural Products against PLK1 by Herb-Based Screening.
J. Chem. Inf. Model., 2020
2018
Analysis of protein features and machine learning algorithms for prediction of druggable proteins.
Quant. Biol., 2018
CavityPlus: a web server for protein cavity detection with pharmacophore modelling, allosteric site identification and covalent ligand binding ability prediction.
Nucleic Acids Res., 2018
Fine-Tuning Accuracy Using Conditional Probability of the Bottom Sign-Bit in Fixed-Width Modified Booth Multiplier.
Circuits Syst. Signal Process., 2018
2017
Deep Learning Based Regression and Multiclass Models for Acute Oral Toxicity Prediction with Automatic Chemical Feature Extraction.
J. Chem. Inf. Model., November, 2017
J. Chem. Inf. Model., June, 2017
PharmMapper 2017 update: a web server for potential drug target identification with a comprehensive target pharmacophore database.
Nucleic Acids Res., 2017
Molecular Graph Encoding Convolutional Neural Networks for Automatic Chemical Feature Extraction.
CoRR, 2017
Sequence-based prediction of protein protein interaction using a deep-learning algorithm.
BMC Bioinform., 2017
2016
Motions of Allosteric and Orthosteric Ligand-Binding Sites in Proteins are Highly Correlated.
J. Chem. Inf. Model., 2016
2015
2014
<i>De Novo</i> Design of Multitarget Ligands with an Iterative Fragment-Growing Strategy.
J. Chem. Inf. Model., 2014
J. Cheminformatics, 2014
2013
Ligand Clouds around Protein Clouds: A Scenario of Ligand Binding with Intrinsically Disordered Proteins.
PLoS Comput. Biol., 2013
2011
J. Chem. Inf. Model., 2011
Correction to Identification of Small-Molecule Inhibitors against Human Leukocyte Antigen-Death Receptor 4 (HLA-DR4) Through a Comprehensive Strategy.
J. Chem. Inf. Model., 2011
Identification of Small-Molecule Inhibitors against Human Leukocyte Antigen-Death Receptor 4 (HLA-DR4) Through a Comprehensive Strategy.
J. Chem. Inf. Model., 2011
Molecular Docking and Competitive Binding Study Discovered Different Binding Modes of Microsomal Prostaglandin E Synthase-1 Inhibitors.
J. Chem. Inf. Model., 2011
SDOCK: A global protein-protein docking program using stepwise force-field potentials.
J. Comput. Chem., 2011
2010
Binding Energy Landscape Analysis Helps to Discriminate True Hits from High-Scoring Decoys in Virtual Screening.
J. Chem. Inf. Model., 2010
2009
2007
PLoS Comput. Biol., 2007
A Large Descriptor Set and a Probabilistic Kernel-Based Classifier Significantly Improve Druglikeness Classification.
J. Chem. Inf. Model., 2007
Computation of Octanol-Water Partition Coefficients by Guiding an Additive Model with Knowledge.
J. Chem. Inf. Model., 2007
BMC Bioinform., 2007
Identification of amyloid fibril-forming segments based on structure and residue-based statistical potential.
Bioinform., 2007
2006
J. Chem. Inf. Model., 2006
2005
J. Chem. Inf. Model., 2005
J. Chem. Inf. Model., 2005
2002
Further development and validation of empirical scoring functions for structure-based binding affinity prediction.
J. Comput. Aided Mol. Des., 2002
2001
J. Comput. Aided Mol. Des., 2001
1999
J. Chem. Inf. Comput. Sci., 1999
1997
J. Chem. Inf. Comput. Sci., 1997
1996
J. Chem. Inf. Comput. Sci., 1996