Evidence map›Paper›PMID 30717654›Full record

ArticleBMC bioinformatics2019

Benchmarking of different molecular docking methods for protein-peptide docking.

Piyush Agrawal, Harinder Singh, Hemant Kumar Srivastava, Sandeep Singh, Gaurav Kishore, Gajendra P S Raghava

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed
16.2field-weighted citation impact, top 1% of its field
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

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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

70 citing papers in PubMed, 194 citations in OpenAlex.

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  18. Insight into Protein Engineering: FromCurrent pharmaceutical design · 2025
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10 more citing papers are in PubMed but not listed here.

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

6 authors at 2 institutions in 1 country.

Piyush AgrawalCenter for Computation Biology, Indraprastha Institute of Information Technology, Okhla Phase III, New Delhi, 110020, India.
Harinder SinghCSIR-Institute of Microbial Technology, Sector 39A, Chandigarh, India.
Hemant Kumar SrivastavaCSIR-Institute of Microbial Technology, Sector 39A, Chandigarh, India.
Sandeep SinghCSIR-Institute of Microbial Technology, Sector 39A, Chandigarh, India.
Gaurav KishoreCSIR-Institute of Microbial Technology, Sector 39A, Chandigarh, India.
Gajendra P S RaghavaCenter for Computation Biology, Indraprastha Institute of Information Technology, Okhla Phase III, New Delhi, 110020, India. raghava@iiitd.ac.in.ORCID http://orcid.org/0000-0002-8902-2876
Institute of Microbial Technology · INIndraprastha Institute of Information Technology Delhi · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMolecular docking studies on protein-peptide interactions are a challenging and time-consuming task because peptides are generally more flexible than proteins and tend to adopt numerous conformations. There are several benchmarking studies on protein-protein, protein-ligand and nucleic acid-ligand docking interactions. However, a series of docking methods is not rigorously validated for protein-peptide complexes in the literature. Considering the importance and wide application of peptide docking, we describe benchmarking of 6 docking methods on 133 protein-peptide complexes having peptide length between 9 to 15 residues. The performance of docking methods was evaluated using CAPRI parameters like FNAT, I-RMSD, L-RMSD.

resultFirstly, we performed blind docking and evaluate the performance of the top docking pose of each method. It was observed that FRODOCK performed better than other methods with average L-RMSD of 12.46 Å. The performance of all methods improved significantly for their best docking pose and achieved highest average L-RMSD of 3.72 Å in case of FRODOCK. Similarly, we performed re-docking and evaluated the performance of the top and best docking pose of each method. We achieved the best performance in case of ZDOCK with average L-RMSD 8.60 Å and 2.88 Å for the top and best docking pose respectively. Methods were also evaluated on 40 protein-peptide complexes used in the previous benchmarking study, where peptide have length up to 5 residues. In case of best docking pose, we achieved the highest average L-RMSD of 4.45 Å and 2.09 Å for the blind docking using FRODOCK and re-docking using AutoDock Vina respectively.

conclusionThe study shows that FRODOCK performed best in case of blind docking and ZDOCK in case of re-docking. There is a need to improve the ranking of docking pose generated by different methods, as the present ranking scheme is not satisfactory. To facilitate the scientific community for calculating CAPRI parameters between native and docked complexes, we developed a web-based service named PPDbench ( http://webs.iiitd.edu.in/raghava/ppdbench/ ).

Indexed as

BenchmarkingAlgorithmsBinding SitesDatabases, ProteinMolecular Docking SimulationPeptidesProtein BindingProteinsProtein Structure, SecondaryReproducibility of ResultsPeptidesProteinsATTRACTBenchmarkCAPRIFRODOCKHexPatchDockpepATTRACTProtein-peptide dockingZDOCK

Identifiers

PMID30717654
PMCPMC7394329
OpenAlexW2911741628

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LicenceCC BY
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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.