PIGSpro is a significant upgrade of the popular PIGS server for the prediction of the structure of immunoglobulins. The software has been completely rewritten in python following a similar pipeline as in the original method, but including, at various steps, relevant modifications found to improve its prediction accuracy, as demonstrated here. The steps of the pipeline include the selection of the appropriate framework for predicting the conserved regions of the molecule by homology; the target template alignment for this portion of the molecule; the selection of the main chain conformation of the hypervariable loops according to the canonical structure model, the prediction of the third loop of the heavy chain (H3) for which complete canonical structures are not available and the packing of the light and heavy chain if derived from different templates. Each of these steps has been improved including updated methods developed along the years. Last but not least, the user interface has been completely redesigned and an automatic monthly update of the underlying database has been implemented. The method is available as a web server at http://biocomputing.it/pigspro.

PIGSPro: prediction of immunoGlobulin structures v2 / Lepore, Rosalba; Olimpieri, Pier P; Messih, Mario A; Tramontano, Anna. - In: NUCLEIC ACIDS RESEARCH. - ISSN 0305-1048. - 45:W1(2017), pp. 17-23. [10.1093/nar/gkx334]

PIGSPro: prediction of immunoGlobulin structures v2

Lepore, Rosalba
Primo
;
Olimpieri, Pier P;Tramontano, Anna
2017

Abstract

PIGSpro is a significant upgrade of the popular PIGS server for the prediction of the structure of immunoglobulins. The software has been completely rewritten in python following a similar pipeline as in the original method, but including, at various steps, relevant modifications found to improve its prediction accuracy, as demonstrated here. The steps of the pipeline include the selection of the appropriate framework for predicting the conserved regions of the molecule by homology; the target template alignment for this portion of the molecule; the selection of the main chain conformation of the hypervariable loops according to the canonical structure model, the prediction of the third loop of the heavy chain (H3) for which complete canonical structures are not available and the packing of the light and heavy chain if derived from different templates. Each of these steps has been improved including updated methods developed along the years. Last but not least, the user interface has been completely redesigned and an automatic monthly update of the underlying database has been implemented. The method is available as a web server at http://biocomputing.it/pigspro.
2017
Antibody Modelling, Antibody structure, Machine Learning, Molecular Interactions, Structure-Function Relationship, Antibody Analysis
01 Pubblicazione su rivista::01a Articolo in rivista
PIGSPro: prediction of immunoGlobulin structures v2 / Lepore, Rosalba; Olimpieri, Pier P; Messih, Mario A; Tramontano, Anna. - In: NUCLEIC ACIDS RESEARCH. - ISSN 0305-1048. - 45:W1(2017), pp. 17-23. [10.1093/nar/gkx334]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1680139
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