Motivation: Understanding the molecular mechanisms of thermal stability is a challenge in protein biology. Indeed, knowing the temperature at which proteins are stable has important theoretical implications, which are intimately linked with properties of the native fold, and a wide range of potential applications from drug design to the optimization of enzyme activity. Results: Here, we present a novel graph-theoretical framework to assess thermal stability based on the structure without any a priori information. In this approach we describe proteins as energy-weighted graphs and compare them using ensembles of interaction networks. Investigating the position of specific interactions within the 3D native structure, we developed a parameter-free network descriptor that permits to distinguish thermostable and mesostable proteins with an accuracy of 76% and area under the receiver operating characteristic curve of 78%. Availability and implementation: Code is available upon request to edoardo.milanetti@uniroma1.it. Supplementary information: Supplementary data are available at Bioinformatics online.
Insights on protein thermal stability: a graph representation of molecular interactions / Miotto, Mattia; Olimpieri, PIER PAOLO; DI RIENZO, Lorenzo; Ambrosetti, Francesco; Corsi, Pietro; Lepore, Rosalba; Tartaglia, Gian Gaetano; Milanetti, Edoardo. - In: BIOINFORMATICS. - ISSN 1367-4803. - 35:15(2019), pp. 1-9. [10.1093/bioinformatics/bty1011]
Insights on protein thermal stability: a graph representation of molecular interactions
MIOTTO, MATTIA;OLIMPIERI, PIER PAOLO;DI RIENZO, LORENZO;AMBROSETTI, FRANCESCO;Lepore, Rosalba;Tartaglia, Gian Gaetano
;Milanetti, Edoardo
2019
Abstract
Motivation: Understanding the molecular mechanisms of thermal stability is a challenge in protein biology. Indeed, knowing the temperature at which proteins are stable has important theoretical implications, which are intimately linked with properties of the native fold, and a wide range of potential applications from drug design to the optimization of enzyme activity. Results: Here, we present a novel graph-theoretical framework to assess thermal stability based on the structure without any a priori information. In this approach we describe proteins as energy-weighted graphs and compare them using ensembles of interaction networks. Investigating the position of specific interactions within the 3D native structure, we developed a parameter-free network descriptor that permits to distinguish thermostable and mesostable proteins with an accuracy of 76% and area under the receiver operating characteristic curve of 78%. Availability and implementation: Code is available upon request to edoardo.milanetti@uniroma1.it. Supplementary information: Supplementary data are available at Bioinformatics online.File | Dimensione | Formato | |
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