ArgosMol: A Web Tool for Protein Structure Prediction and Visualization

E. Sejje Condori, J. Soncco Lupa, S. Barrios Cornejo, V. Machaca Arceda

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

ArgosMol is a 3D molecular visualization tool designed to predict and visualize protein structures. ArgosMol allows loading molecular structure files in.pdb format and amino acid sequence files in Fasta and/or a3m format to generate a permanent link with the representation of the structure that the user can then manipulate. ArgosMol has several intuitive options for the visualization of the structure, such as different visualization forms, tags, a variety of colour schemes, amino acid search engine, and chain management. For the prediction of the protein structure, HH-Suite tool and the Profold architecture were integrated. Finally, we compared the functionalities of ArgosMol with other visualization tools.

Original languageEnglish
Title of host publicationAdvances in Information and Communication - Proceedings of the 2022 Future of Information and Communication Conference, FICC
EditorsKohei Arai
PublisherSpringer Science and Business Media Deutschland GmbH
Pages604-616
Number of pages13
ISBN (Print)9783030980115
DOIs
StatePublished - 2022
Externally publishedYes
EventFuture of Information and Communication Conference, FICC 2022 - Virtual, Online
Duration: 3 Mar 20224 Mar 2022

Publication series

NameLecture Notes in Networks and Systems
Volume438 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

ConferenceFuture of Information and Communication Conference, FICC 2022
CityVirtual, Online
Period3/03/224/03/22

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • Neural networks
  • Prediction
  • Protein structure
  • Visualization

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