A5100407681- Computational Drug Discovery Methods
- Protein Structure and Dynamics
- Ubiquitin and proteasome pathways
- Bioinformatics and Genomic Networks
- Machine Learning in Materials Science
- Gene expression and cancer classification
- Epigenetics and DNA Methylation
- Protein Degradation and Inhibitors
- RNA and protein synthesis mechanisms
- Chemical Synthesis and Analysis
- Hepatitis B Virus Studies
- Hepatitis C virus research
- RNA Interference and Gene Delivery
- 14-3-3 protein interactions
- vaccines and immunoinformatics approaches
- RNA modifications and cancer
- Monoclonal and Polyclonal Antibodies Research
- HIV/AIDS drug development and treatment
- Nanomaterials for catalytic reactions
- Click Chemistry and Applications
- HIV Research and Treatment
- Machine Learning in Bioinformatics
- Immunotherapy and Immune Responses
- PI3K/AKT/mTOR signaling in cancer
- Catalytic Processes in Materials Science
Zhejiang University
2016-2025
Hangzhou Normal University
2024-2025
Shenyang Pharmaceutical University
2023-2025
Dalian University
2021-2025
Affiliated Zhongshan Hospital of Dalian University
2015-2025
Harbin Engineering University
2021-2025
State Key Laboratory on Integrated Optoelectronics
2024-2025
Stomatology Hospital
2018-2025
Jilin University
2024-2025
United Imaging Healthcare (China)
2020-2025
The antimicrobial peptide database (APD, http://aps.unmc.edu/AP/main.php) has been updated and expanded. It now hosts 1228 entries with 65 anticancer, 76 antiviral (53 anti-HIV), 327 antifungal 944 antibacterial peptides. second version of our (APD2) allows users to search families (e.g. bacteriocins, cyclotides, or defensins), sources fish, frogs chicken), post-translationally modified peptides amidation, oxidation, lipidation, glycosylation d-amino acids), binding targets membranes,...
We evaluated the capabilities of ten molecular docking programs to predict ligand binding poses (sampling power) and rank affinities (scoring power).
Abstract Protein–protein interactions (PPIs) play an important role in the different functions of cells, but accurate prediction three-dimensional structures for PPIs is still a notoriously difficult task. In this study, HawkDock, free and open accessed web server, was developed to predict analyze PPIs. HawkDock ATTRACT docking algorithm, HawkRank scoring function our group MM/GBSA energy decomposition analysis were seamlessly integrated into multi-functional platform. The predicted by...
Abstract Graph neural networks (GNN) has been considered as an attractive modelling method for molecular property prediction, and numerous studies have shown that GNN could yield more promising results than traditional descriptor-based methods. In this study, based on 11 public datasets covering various endpoints, the predictive capacity computational efficiency of prediction models developed by eight machine learning (ML) algorithms, including four (SVM, XGBoost, RF DNN) graph-based (GCN,...
Entropy effects play an important role in drug-target interactions, but the entropic contribution to ligand-binding affinity is often neglected by end-point binding free energy calculation methods, such as MM/GBSA and MM/PBSA, due expensive computational cost of normal mode analysis (NMA). Here, we systematically investigated entropy on prediction power MM/PBSA using >1500 protein-ligand systems six representative AMBER force fields. Two computationally efficient including NMA based...
Abstract Molecule docking has been regarded as a routine tool for drug discovery, but its accuracy highly depends on the reliability of scoring functions (SFs). With rapid development machine learning (ML) techniques, ML‐based SFs have gradually emerged promising alternative protein–ligand binding affinity prediction and virtual screening, most them shown significantly better performance than wide range classical SFs. Emergence more data‐hungry deep (DL) approaches in recent years further...
Predicting the native or near-native binding pose of a small molecule within protein pocket is an extremely important task in structure-based drug design, especially hit-to-lead and lead optimization phases. In this study, fastDRH, free open accessed web server, was developed to predict analyze protein-ligand complex structures. fastDRH AutoDock Vina AutoDock-GPU docking engines, structure-truncated MM/PB(GB)SA energy calculation procedures multiple poses based per-residue decomposition...
Abstract Decoupling the electronic and geometric effects has been a long cherished goal for heterogeneous catalysis due to their tangled relationship. Here, novel orthogonal decomposition method is firstly proposed settle this issue in p -chloronitrobenzene hydrogenation reaction on size- shape-controlled Pt nanoparticles (NPs) carried various supports. Results suggest Fermi levels of catalysts can be modulated by supports with varied work function ( W f ). And selectivity NPs similar size...
Regulated intramembrane proteolysis by members of the site-2 protease (S2P) family is an important signaling mechanism conserved from bacteria to humans. Here we report crystal structure transmembrane core domain S2P metalloprotease Methanocaldococcus jannaschii. The consists six segments, with catalytic zinc atom coordinated two histidine residues and one aspartate residue approximately 14 angstroms into lipid membrane surface. exhibits distinct conformations in crystals. In closed...
Abstract Although a wide variety of machine learning (ML) algorithms have been utilized to learn quantitative structure–activity relationships (QSARs), there is no agreed single best algorithm for QSAR learning. Therefore, comprehensive understanding the performance characteristics popular ML used in highly desirable. In this study, five linear [linear function Gaussian process regression (linear-GPR), support vector (linear-SVM), partial least squares (PLSR), multiple (MLR) and principal...
A large number of protein–protein interactions (PPIs) are mediated by the between proteins and peptide segments binding partners, therefore determination protein–peptide (PpIs) is quite crucial to elucidate important biological processes design peptides or peptidomimetic drugs that can modulate PPIs. Nowadays, as a powerful computation tool, molecular docking has been widely utilized predict structures complexes. However, although programs have available, systematic study on assessment their...
A significant number of protein-protein interactions (PPIs) are mediated through the between proteins and peptide segments, therefore determination protein-peptide (PpIs) is critical to gain an in-depth understanding PPI network even design peptides or small molecules capable modulating PPIs. Computational approaches, especially molecular docking, provide efficient way model PpIs, a reliable scoring function that can recognize correct binding conformations for complexes one most important...
Adverse effects induced by drug-drug interactions may result in early termination of drug development or even withdrawal drugs from the market, and many are caused inhibition cytochrome P450 (CYP450) enzymes. Therefore, accurate prediction capability a given compound against specific CYP450 isoform is highly desirable. In this study, three ensemble learning methods, including random forest, gradient boosting decision tree, eXtreme (XGBoost), two deep neural networks convolutional networks,...
Molecular docking provides a computationally efficient way to predict the atomic structural details of protein–RNA interactions (PRI), but accurate prediction three-dimensional structures and binding affinities for PRI is still notoriously difficult, partly due unreliability existing scoring functions PRI. MM/PBSA MM/GBSA are more theoretically rigorous than most docking, their performance systems remains unclear. Here, we systemically evaluated capability recognize near-native with...
Enhanced sampling has been extensively used to capture the conformational transitions in protein folding, but it attracts much less attention studies of protein-protein recognition. In this study, we evaluated impact enhanced methods and solute dielectric constants on overall accuracy molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) mechanics/generalized Born (MM/GBSA) approaches for binding free energy calculations. Here, two widely methods, including aMD GaMD, conventional...
Micelles are highly attractive nano-drug delivery systems for targeted cancer therapy. While they have been demonstrated to significantly alleviate the side-effects of their cargo drugs, therapy outcomes usually suboptimal partially due ineffective drug release and endosome entrapment. Stimulus-responsive nanoparticles allowed controlled in a smart fashion, we want use this concept design novel micelles. Herein, reported pH-sensitive paclitaxel (PTX)-loaded poly (ethylene...