Seq-InSite: sequence supersedes structure for protein interaction site prediction.
Bioinformatics
; 40(1)2024 01 02.
Article
en En
| MEDLINE
| ID: mdl-38212995
ABSTRACT
MOTIVATION Proteins accomplish cellular functions by interacting with each other, which makes the prediction of interaction sites a fundamental problem. As experimental methods are expensive and time consuming, computational prediction of the interaction sites has been studied extensively. Structure-based programs are the most accurate, while the sequence-based ones are much more widely applicable, as the sequences available outnumber the structures by two orders of magnitude. Ideally, we would like a tool that has the quality of the former and the applicability of the latter. RESULTS:
We provide here the first solution that achieves these two goals. Our new sequence-based program, Seq-InSite, greatly surpasses the performance of sequence-based models, matching the quality of state-of-the-art structure-based predictors, thus effectively superseding the need for models requiring structure. The predictive power of Seq-InSite is illustrated using an analysis of evolutionary conservation for four protein sequences. AVAILABILITY AND IMPLEMENTATION Seq-InSite is freely available as a web server at http//seq-insite.csd.uwo.ca/ and as free source code, including trained models and all datasets used for training and testing, at https//github.com/lucian-ilie/Seq-InSite.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Programas Informáticos
/
Proteínas
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2024
Tipo del documento:
Article
País de afiliación:
Canadá