Application of PolyPRep tools on HIV protease polyproteins using molecular docking

Abstract In recent years, the development of high-throughput technologies for obtaining sequence data leveraged the possibility of analysis of protein data in silico. However, when it comes to viral polyprotein interaction studies, there is a gap in the representation of those proteins, given their...

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Main Authors: M. F. R. Dias, F. L. L. Oliveira, V. S. Pontes, M. L. Silva
Format: Article
Language:English
Published: Instituto Internacional de Ecologia 2021-12-01
Series:Brazilian Journal of Biology
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842024000100151&tlng=en
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author M. F. R. Dias
F. L. L. Oliveira
V. S. Pontes
M. L. Silva
author_facet M. F. R. Dias
F. L. L. Oliveira
V. S. Pontes
M. L. Silva
author_sort M. F. R. Dias
collection DOAJ
description Abstract In recent years, the development of high-throughput technologies for obtaining sequence data leveraged the possibility of analysis of protein data in silico. However, when it comes to viral polyprotein interaction studies, there is a gap in the representation of those proteins, given their size and length. The prepare for studies using state-of-the-art techniques such as Machine Learning, a good representation of such proteins is a must. We present an alternative to this problem, implementing a fragmentation and modeling protocol to prepare those polyproteins in the form of peptide fragments. Such procedure is made by several scripts, implemented together on the workflow we call PolyPRep, a tool written in Python script and available in GitHub. This software is freely available only for noncommercial users.
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spelling doaj.art-3edd16859bed4a2997745379f449caf62022-12-22T04:12:49ZengInstituto Internacional de EcologiaBrazilian Journal of Biology1678-43752021-12-018410.1590/1519-6984.245592Application of PolyPRep tools on HIV protease polyproteins using molecular dockingM. F. R. Diashttps://orcid.org/0000-0002-0069-3199F. L. L. Oliveirahttps://orcid.org/0000-0003-4646-9958V. S. Ponteshttps://orcid.org/0000-0001-7227-5407M. L. Silvahttps://orcid.org/0000-0003-4844-7138Abstract In recent years, the development of high-throughput technologies for obtaining sequence data leveraged the possibility of analysis of protein data in silico. However, when it comes to viral polyprotein interaction studies, there is a gap in the representation of those proteins, given their size and length. The prepare for studies using state-of-the-art techniques such as Machine Learning, a good representation of such proteins is a must. We present an alternative to this problem, implementing a fragmentation and modeling protocol to prepare those polyproteins in the form of peptide fragments. Such procedure is made by several scripts, implemented together on the workflow we call PolyPRep, a tool written in Python script and available in GitHub. This software is freely available only for noncommercial users.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842024000100151&tlng=enpolyproteinfragmentationmodelling3D structures
spellingShingle M. F. R. Dias
F. L. L. Oliveira
V. S. Pontes
M. L. Silva
Application of PolyPRep tools on HIV protease polyproteins using molecular docking
Brazilian Journal of Biology
polyprotein
fragmentation
modelling
3D structures
title Application of PolyPRep tools on HIV protease polyproteins using molecular docking
title_full Application of PolyPRep tools on HIV protease polyproteins using molecular docking
title_fullStr Application of PolyPRep tools on HIV protease polyproteins using molecular docking
title_full_unstemmed Application of PolyPRep tools on HIV protease polyproteins using molecular docking
title_short Application of PolyPRep tools on HIV protease polyproteins using molecular docking
title_sort application of polyprep tools on hiv protease polyproteins using molecular docking
topic polyprotein
fragmentation
modelling
3D structures
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842024000100151&tlng=en
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