Evidence map›Paper›PMID 34778205›Full record

ArticleFrontiers in chemistry2021

Redesigning Vina@QNLM for Ultra-Large-Scale Molecular Docking and Screening on a Sunway Supercomputer.

Hao Lu, Zhiqiang Wei, Cunji Wang, Jingjing Guo, Yuandong Zhou, Zhuoya Wang, Hao Liu

Abstract read
In one paragraph

Article in Frontiers in chemistry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. DockOpt: A Tool for Automatic Optimization of Docking Models.Journal of chemical information and modeling · 2024
    Article
  3. Review
  4. Considerations Around Structure-Based Drug Discovery for KRAS Using DOCK.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  5. Metabolic Markers and Association of Biological Sex in Lupus Nephritis.International journal of molecular sciences · 2023
    Article
  6. Large-Scale Docking in the Cloud.Journal of chemical information and modeling · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Hao LuCollege of Computer Science and Technology, Ocean University of China, Qingdao, China.
Zhiqiang WeiCollege of Computer Science and Technology, Ocean University of China, Qingdao, China.
Cunji WangCollege of Computer Science and Technology, Ocean University of China, Qingdao, China.
Jingjing GuoCollege of Computer Science and Technology, Ocean University of China, Qingdao, China.
Yuandong ZhouCollege of Computer Science and Technology, Ocean University of China, Qingdao, China.
Zhuoya WangPilot National Laboratory for Marine Science and Technology, Qingdao, China.
Hao LiuCollege of Computer Science and Technology, Ocean University of China, Qingdao, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ultra-large-scale molecular docking can improve the accuracy of lead compounds in drug discovery. In this study, we developed a molecular docking piece of software, Vina@QNLM, which can use more than 4,80,000 parallel processes to search for potential lead compounds from hundreds of millions of compounds. We proposed a task scheduling mechanism for large-scale parallelism based on Vinardo and Sunway supercomputer architecture. Then, we readopted the core docking algorithm to incorporate the full advantage of the heterogeneous multicore processor architecture in intensive computing. We successfully expanded it to 10, 465, 065 cores (1,61,001 management process elements and 0, 465, 065 computing process elements), with a strong scalability of 55.92%. To the best of our knowledge, this is the first time that 10 million cores are used for molecular docking on Sunway. The introduction of the heterogeneous multicore processor architecture achieved the best speedup, which is 11x more than that of the management process element of Sunway. The performance of Vina@QNLM was comprehensively evaluated using the CASF-2013 and CASF-2016 protein-ligand benchmarks, and the screening power was the highest out of the 27 pieces of software tested in the CASF-2013 benchmark. In some existing applications, we used Vina@QNLM to dock more than 10 million molecules to nine rigid proteins related to SARS-CoV-2 within 8.5 h on 10 million cores. We also developed a platform for the general public to use the software.

Indexed as

drug discoverymolecular dockingparallel computingSunway supercomputervirtual screening

Identifiers

PMID34778205
PMCPMC8581564

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.