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Cited by 267

The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.

Caver Web 1.0: identification of tunnels and channels in proteins and analysis of ligand transport

Open access
Stourac, Jan, Vavra, Ondrej, Kokkonen, Piia, Filipovic, Jiri, Pinto, Gaspar, Brezovsky, Jan, Damborsky, Jiri, Bednar, David·2019·Nucleic Acids Research
DOI 10.1093/nar/gkz378
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Abstract

Caver Web 1.0 is a web server for comprehensive analysis of protein tunnels and channels, and study of the ligands’ transport through these transport pathways. Caver Web is the first interactive tool allowing both the analyses within a single graphical user interface. The server is built on top of the abundantly used tunnel detection tool Caver 3.02 and CaverDock 1.0 enabling the study of the ligand transport. The program is easy-to-use as the only required inputs are a protein structure for a tunnel identification and a list of ligands for the transport analysis. The automated guidance procedures assist the users to set up the calculation in a way to obtain biologically relevant results. The identified tunnels, their properties, energy profiles and trajectories for ligands’ passages can be calculated and visualized. The tool is very fast (2–20 min per job) and is applicable even for virtual screening purposes. Its simple setup and comprehensive graphical user interface make the tool accessible for a broad scientific community. The server is freely available at https://loschmidt.chemi.muni.cz/caverweb.

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Metadata

Authors
Stourac, J., Vavra, O., Kokkonen, P., Filipovic, J., Pinto, G., Brezovsky, J., Damborsky, J., & Bednar, D.
Venue
Nucleic Acids Research
Publisher
Oxford University Press (OUP)
Published
2019-05-22
Volume
47
Issue
W1
Pages
W414-W422
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
DOI
10.1093/nar/gkz378
OpenAlex
W2944930475
Cited by
267
References
48
FWCI
13.91
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Caver Web 1.0: identification of tunnels and channels in proteins and analysis of ligand transport. https://app.cochat.ai/papers/10.1093/nar/gkz378
The paper
Stourac, J., Vavra, O., Kokkonen, P., Filipovic, J., Pinto, G., Brezovsky, J., Damborsky, J., & Bednar, D. (2019). Caver Web 1.0: identification of tunnels and channels in proteins and analysis of ligand transport. Nucleic Acids Research. https://doi.org/10.1093/nar/gkz378

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.