Peptriever: a Bi-Encoder approach for large-scale protein-peptide binding search.
Bioinformatics
; 40(5)2024 05 02.
Article
en En
| MEDLINE
| ID: mdl-38710496
ABSTRACT
MOTIVATION Peptide therapeutics hinge on the precise interaction between a tailored peptide and its designated receptor while mitigating interactions with alternate receptors is equally indispensable. Existing methods primarily estimate the binding score between protein and peptide pairs. However, for a specific peptide without a corresponding protein, it is challenging to identify the proteins it could bind due to the sheer number of potential candidates. RESULTS:
We propose a transformers-based protein embedding scheme in this study that can quickly identify and rank millions of interacting proteins. Furthermore, the proposed approach outperforms existing sequence- and structure-based methods, with a mean AUC-ROC and AUC-PR of 0.73. AVAILABILITY AND IMPLEMENTATION Training data, scripts, and fine-tuned parameters are available at https//github.com/RoniGurvich/Peptriever. The proposed method is linked with a web application available for customized prediction at https//peptriever.app/.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Péptidos
/
Unión Proteica
/
Programas Informáticos
/
Proteínas
Idioma:
En
Revista:
Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2024
Tipo del documento:
Article
País de afiliación:
Israel
Pais de publicación:
Reino Unido