FIBOS: R and python packages for analyzing protein packing and structure.

Herson H M Soares, João P R Romanelli, Patrick J Fleming, Carlos H da Silveira

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Article in Bioinformatics (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Herson H M SoaresInstitute of Technological Sciences, Federal University of Itajubá, Itabira, 35903-087, Brazil.

João P R RomanelliInstitute of Applied and Pure Sciences, Federal University of Itajubá, Itabira, 35903-087, Brazil.

Patrick J FlemingThomas C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD 21218, United States.

Carlos H da SilveiraInstitute of Technological Sciences, Federal University of Itajubá, Itabira, 35903-087, Brazil.ORCID 0000-0001-6979-8469

Funding

FAPEMIG 11839

6 · The paper itself

Abstract

motivationAdvances in the prediction of the 3D structures of most known proteins through machine learning have achieved unprecedented accuracies. However, although these computed models are remarkably good, they still challenge accuracy at the atomic level. The Occluded Surface (OS) algorithm is widely used for atomic packing analysis. But it lacks implementations in high-level languages.

resultsWe introduce FIBOS, an R and Python package incorporating the OS methodology with enhancements. We show how FIBOS can be used to atomically compare experimental structures and AlphaFold predictions. Although the average packing was similar, AlphaFold models exhibited slightly greater variability, revealing a specific pattern of outliers. AVAILABILITY AND IMPLEMENTATION: FIBOS can be installed locally as a PyPi Python or CRAN R package, and it is also available at https://github.com/insilico-unifei/fibos-R and https://github.com/insilico-unifei/fibos-py.

Indexed as

ProteinsSoftwareAlgorithmsComputational BiologyMachine LearningModels, MolecularProtein ConformationProteins

Identifiers

PMID40758457

DOI10.1093/bioinformatics/btaf434

PMCPMC12449057

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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.