A5100755257- Computational Drug Discovery Methods
- Bioinformatics and Genomic Networks
- Metabolomics and Mass Spectrometry Studies
- Machine Learning in Bioinformatics
- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Advanced Proteomics Techniques and Applications
- Receptor Mechanisms and Signaling
- Gene expression and cancer classification
- 3D Printing in Biomedical Research
- Genetic Associations and Epidemiology
- Pharmacogenetics and Drug Metabolism
- RNA modifications and cancer
- Chemical Synthesis and Analysis
- Cancer-related molecular mechanisms research
- Analytical Chemistry and Chromatography
- Zebrafish Biomedical Research Applications
- RNA Research and Splicing
- Click Chemistry and Applications
- Microbial Natural Products and Biosynthesis
- Histone Deacetylase Inhibitors Research
- Cancer therapeutics and mechanisms
- Genetics and Neurodevelopmental Disorders
- MicroRNA in disease regulation
- Drug Transport and Resistance Mechanisms
Zhejiang University
2016-2025
Artificial Intelligence in Medicine (Canada)
2024-2025
Chongqing University
2014-2025
Alibaba Group (China)
2021-2025
Second Affiliated Hospital of Zhejiang University
2022-2025
Zhejiang Lab
2020-2024
First Affiliated Hospital of Xi'an Jiaotong University
2013-2024
Children's Hospital of Zhejiang University
2024
Hubei Provincial Hospital of Traditional Chinese Medicine
2024
National Clinical Research
2024
Knowledge of therapeutic targets and early drug candidates is useful for improved discovery. In particular, information about target regulators the patented agents facilitates research regarding druggability, systems pharmacology, new trends, molecular landscapes, development discovery tools. To complement other databases, we constructed Therapeutic Target Database (TTD) with expanded (i) target-regulating microRNAs transcription factors, (ii) target-interacting proteins, (iii) their...
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...
Drug discovery relies on the knowledge of not only drugs and targets, but also comparative agents targets. These include poor binders non-binders for developing tools, prodrugs improved therapeutics, co-targets therapeutic targets multi-target strategies off-target investigations, collective structure-activity drug-likeness landscapes enhanced drug feature. However, such valuable data are inadequately covered by available databases. In this study, a major update Therapeutic Target Database,...
Extensive efforts have been directed at the discovery, investigation and clinical monitoring of targeted therapeutics. These may be facilitated by convenient access genetic, proteomic, interactive other aspects therapeutic targets. Here, we describe an update Therapeutic target database (TTD) previously featured in NAR. This includes: (i) 2000 drug resistance mutations 83 targets 104 target/drug regulatory genes, which are resistant to 228 drugs targeting 63 diseases (49 61 with patient...
Knowledge and investigation of therapeutic targets (responsible for drug efficacy) the targeted drugs facilitate target discovery validation. Therapeutic Target Database (TTD, http://bidd.nus.edu.sg/group/ttd/ttd.asp) has been developed to provide comprehensive information about efficacy corresponding approved, clinical trial investigative drugs. Since its last update, major improvements updates have made TTD. In addition significant increase data content (from 1894 5028 2025 17 816 drugs),...
Sequence-derived structural and physicochemical features have been extensively used for analyzing predicting structural, functional, expression interaction profiles of proteins peptides. PROFEAT has developed as a web server computing commonly peptides from amino acid sequence. To facilitate more extensive studies protein peptides, numerous improvements updates made to PROFEAT. We added new functions descriptors protein-protein protein-small molecule interactions, segment local properties...
Diverse forms of unwanted signal variations in mass spectrometry-based metabolomics data adversely affect the accuracies metabolic profiling. A variety normalization methods have been developed for addressing this problem. However, their performances vary greatly and depend heavily on nature studied data. Moreover, given complexity actual data, it is not feasible to assess performance by single criterion. We therefore NOREVA enable evaluation various from multiple perspectives. integrated...
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...
Extensive drug discovery efforts have yielded many approved and candidate drugs targeting various targets in different biological pathways. Several freely accessible databases provide the drug, target drug-targeted pathway information for facilitating efforts, but there is an insufficient coverage of clinical trial Here, we describe update Therapeutic Target Database (TTD) previously featured NAR. The updated contents include: (i) significantly increased (1.6 2.3 times previous release,...
Increasing numbers of proteins, nucleic acids and other molecular entities have been explored as therapeutic targets, hundreds which are targets approved clinical trial drugs. Knowledge these corresponding drugs, particularly those in uses trials, is highly useful for facilitating drug discovery. Therapeutic Target Database (TTD) has developed to provide information about In order accommodate increasing demand comprehensive knowledge the primary approved, experimental numerous improvements...
Dual inhibition of serotonin and norepinephrine transporters (hSERT hNET) gives greatly improved efficacy tolerability for treating major depressive disorder (MDD) compared with selective reuptake inhibitors. Pioneer studies provided valuable information on structure, function, pharmacology drugs targeting both hSERT hNET (serotonin–norepinephrine inhibitors, SNRIs), the differential binding mechanism between SNRIs inhibitors 5-HT (SSRIs) or NE (sNRIs) to their corresponding targets was...
Many drugs are nature derived. Low drug productivity has renewed interest in natural products as drug-discovery sources. Nature-derived composed of dozens molecular scaffolds generated by specific secondary-metabolite gene clusters selected species. It can be hypothesized that drug-like structures probably distributed selective groups We compared the species origins 939 approved and 369 clinical-trial with those 119 preclinical 19,721 bioactive products. In contrast to scattered distribution...
Target discovery is one of the essential steps in modern drug development, and identification promising targets fundamental for developing first-in-class drug. A variety methods have emerged target assessment based on druggability analysis, which refers to likelihood a being effectively modulated by drug-like agents. In therapeutic database (TTD), nine categories established characteristics were thus collected 426 successful, 1014 clinical trial, 212 preclinical/patented, 1479...
The etiology of schizophrenia (SCZ) is regarded as one the most fundamental puzzles in current medical research, and its diagnosis limited by lack objective molecular criteria. Although plenty studies were conducted, SCZ gene signatures identified these independent are found highly inconsistent. As important factors contributing to this inconsistency, feature selection methods used currently do not fully consider reproducibility among discovered from different datasets. Therefore, it crucial...
Abstract Biological processes (like microbial growth & physiological response) are usually dynamic and require the monitoring of metabolic variation at different time-points. Moreover, there is clear shift from case-control (N=2) study to multi-class (N>2) problem in current metabolomics, which crucial for revealing mechanisms underlying certain process, disease metastasis, etc. These time-course metabolomics have attracted great attention, data normalization essential removing...
Label-free quantification (LFQ) with a specific and sequentially integrated workflow of acquisition technique, tool processing method has emerged as the popular technique employed in metaproteomic research to provide comprehensive landscape adaptive response microbes external stimuli their interactions other organisms or host cells. The performance LFQ is highly dependent on studied data. Hence, it essential discover most appropriate one for data set. However, challenging perform such...
Human serotine transporter (hSERT) is one of the most influential drug targets, and its allosteric modulators (e.g., escitalopram) have emerged to be next-generation medication for psychiatric disorders. However, molecular mechanism underlying modulation hSERT still elusive. Here, simulation strategies conventional (cMD) steered (SMD) dynamics were applied investigate this from distinct perspectives. First, cMD simulations revealed that escitalopram's binding hSERT's site simultaneously...
Abstract The efficacy and safety of drugs are widely known to be determined by their interactions with multiple molecules pharmacological importance, it is therefore essential systematically depict the molecular atlas pharma-information studied drugs. However, our understanding such information neither comprehensive nor precise, which necessitates construction a new database providing network containing large number interacting molecules. Here, describing (DrugMAP) was constructed. It...
Drug discovery and development affects various aspects of human health dramatically impacts the pharmaceutical market. However, investments in a new drug often go unrewarded due to long complex process research (R&D). With advancement experimental technology computer hardware, artificial intelligence (AI) has recently emerged as leading tool analyzing abundant high-dimensional data. Explosive growth size biomedical data provides advantages applying AI all stages R&D. Driven by big...