Scoring predictive models using a reduced representation of proteins: model and energy definition |
| |
Authors: | Federico Fogolari Lidia Pieri Agostino Dovier Luca Bortolussi Gilberto Giugliarelli Alessandra Corazza Gennaro Esposito Paolo Viglino |
| |
Institution: | 1.Dipartimento di Scienze e Tecnologie Biomediche,Università di Udine,Udine,Italy;2.INAF – Astronomical Observatory of Padova Vicolo dell'Osservatorio 5,Padova,Italy;3.Dipartimento di Matematica e Informatica,Università di Udine,Udine,Italy;4.Dipartimento di Fisica,Università di Udine,Udine,Italy |
| |
Abstract: | Background Reduced representations of proteins have been playing a keyrole in the study of protein folding. Many such models are available,
with different representation detail. Although the usefulness of many such models for structural bioinformatics applications
has been demonstrated in recent years, there are few intermediate resolution models endowed with an energy model capable,
for instance, of detecting native or native-like structures among decoy sets. The aim of the present work is to provide a
discrete empirical potential for a reduced protein model termed here PC2CA, because it employs a PseudoCovalent structure
with only 2 Centers of interactions per Amino acid, suitable for protein model quality assessment. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|