Over the past few decades, the number of available structural bioinformatics pipelines, libraries, plugins, web resources and software has increased exponentially and become accessible to the broad realm of life scientists. This expansion has shaped the field as a tangled network of methods, algorithms and user interfaces. In recent years PyMOL, widely used software for biomolecules visualization and analysis, has started to play a key role in providing an open platform for the successful implementation of expert knowledge into an easy-to-use molecular graphics tool. This review outlines the plugins and features that make PyMOL an eligible environment for supporting structural bioinformatics analyses.

Boosting the Full Potential of PyMOL with Structural Biology Plugins / Rosignoli, Serena; Paiardini, Alessandro. - In: BIOMOLECULES. - ISSN 2218-273X. - 12:12(2022), p. 1764. [10.3390/biom12121764]

Boosting the Full Potential of PyMOL with Structural Biology Plugins

Serena Rosignoli
Primo
;
Alessandro Paiardini
Ultimo
2022

Abstract

Over the past few decades, the number of available structural bioinformatics pipelines, libraries, plugins, web resources and software has increased exponentially and become accessible to the broad realm of life scientists. This expansion has shaped the field as a tangled network of methods, algorithms and user interfaces. In recent years PyMOL, widely used software for biomolecules visualization and analysis, has started to play a key role in providing an open platform for the successful implementation of expert knowledge into an easy-to-use molecular graphics tool. This review outlines the plugins and features that make PyMOL an eligible environment for supporting structural bioinformatics analyses.
2022
PyMOL; bioinformatics; plugin; molecular viewer; structural biology; sequence analysis; molecular docking; molecular dynamics; structure-function analysis; protein structure prediction; virtual screening
01 Pubblicazione su rivista::01g Articolo di rassegna (Review)
Boosting the Full Potential of PyMOL with Structural Biology Plugins / Rosignoli, Serena; Paiardini, Alessandro. - In: BIOMOLECULES. - ISSN 2218-273X. - 12:12(2022), p. 1764. [10.3390/biom12121764]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1661534
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