Demo Data from EDBT 2026 / reviewers in the wild / expert
Liang Rao
dblp:262/6214
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › molecular informatics › molecular modeling › molecular docking
protein-ligand docking |
0.6 | 1 | 2022 | ATPdock: a template-based method for ATP-specific protein-ligand docking · Bioinform. 2022 |
Bioinformatics and computational biology › molecular informatics › molecular modeling › molecular docking
template-based docking |
0.6 | 1 | 2022 | ATPdock: a template-based method for ATP-specific protein-ligand docking · Bioinform. 2022 |
Bioinformatics and computational biology › gene regulation
binding site prediction |
0.2 | 1 | 2022 | ATPdock: a template-based method for ATP-specific protein-ligand docking · Bioinform. 2022 |
Bioinformatics and computational biology
protein structure prediction |
0.2 | 1 | 2022 | ATPdock: a template-based method for ATP-specific protein-ligand docking · Bioinform. 2022 |
Methods — techniques the papers use, named apart from their topics
structural alignment · 0.6monte carlo simulation · 0.6energy function · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | ATPdock: a template-based method for ATP-specific protein-ligand dockingabstractMOTIVATION: Accurately identifying protein-ATP binding poses is significantly valuable for both basic structure biology and drug discovery. Although many docking methods have been designed, most of them require a user-defined binding site and are difficult to achieve a high-quality protein-ATP docking result. It is critical to develop a protein-ATP-specific blind docking method without user-defined binding sites. RESULTS: Here, we present ATPdock, a template-based method for docking ATP into protein. For each query protein, if no pocket site is given, ATPdock first identifies its most potential pocket using ATPbind, an ATP-binding site predictor; then, the template pocket, which is most similar to the given or identified pocket, is searched from the database of pocket-ligand structures using APoc, a pocket structural alignment tool; thirdly, the rough docking pose of ATP (rdATP) is generated using LS-align, a ligand structural alignment tool, to align the initial ATP pose to the template ligand corresponding to template pocket; finally, the Metropolis Monte Carlo simulation is used to fine-tune the rdATP under the guidance of AutoDock Vina energy function. Benchmark tests show that ATPdock significantly outperforms other state-of-the-art methods in docking accuracy. AVAILABILITY AND IMPLEMENTATION: https://jun-csbio.github.io/atpdock/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Liang Rao, Ning-Xin Jia, Jun Hu 0010, Dongjun Yu, Guijun Zhang |
Bioinform. | 1 |