PEP-PREDNa+: A web server for prediction of highly specific peptides targeting voltage-gated Na+ channels using machine learning techniques

Primer Autor
Beltran, Jorge F.
Co-autores
Herrera-Bravo, Jesus
Farias, Jorge G.
Contreras, Fernanda Parraguez
Herrera-Belen, Lisandra
Título
PEP-PREDNa+: A web server for prediction of highly specific peptides targeting voltage-gated Na+ channels using machine learning techniques
Editorial
PERGAMON-ELSEVIER SCIENCE LTD
Revista
COMPUTERS IN BIOLOGY AND MEDICINE
Lenguaje
en
Resumen
Voltage-gated sodium channel activity has long been associated with several diseases including epilepsy, chronic pain, cardiovascular diseases, cancers, immune system, neuromuscular and respiratory disorders. The strong participation of these channels in the development of diseases makes them excellent promising therapeutic targets. Voltage-gated Na+ channel blocking peptides come from a wide source of organisms such as venoms. However, the in vitro and in vivo identification and validation of these peptides are time-consuming and resource intensive. In this work, we developed a bioinformatics tool called PEP-PREDNa+ for the highly specific prediction of voltage-gated Na+ channel blocking peptides. PEP-PREDNa+ is based on the random forest algorithm, which presented excellent performance measures during the cross-validation (sensitivity = 0.81, accuracy = 0.83, precision = 0.85, F-score = 0.83, specificity = 0.86, and Matthew's correlation coefficient = 0.67) and testing (sensitivity = 0.88, accuracy = 0.92, precision = 0.96, F-score = 0.91, specificity = 0.96, and Matthew's correlation coefficient = 0.84) phases. The PEP-PREDNa+ tool could be very useful in accelerating and reducing the costs of the of new Na+ channel with therapeutic potential.
Tipo de Recurso
artículo original
doi
10.1016/j.compbiomed.2022.105414
Formato Recurso
PDF
Palabras Claves
Machine learning
Peptide
Toxin
Channel
Sodium
Server
SODIUM-CHANNELS
TOOLS
Ubicación del archivo
http://dx.doi.org/10.1016/j.compbiomed.2022.105414
Categoría OCDE
Biología
Ciencias de la Computación
Aplicaciones Interdisciplinarias
Ingeniería Biomédica
Biología Matemática y Computacional
Materias
Aprendizaje automático
Péptido
Toxina
Canal
Sodio
Servidor
CANALES DE SODIO
HERRAMIENTAS
Disciplinas de la OCDE
Ciencias de la Información y Bioinformática
Biotecnología Relacionada con la Salud
Farmacología y Farmacia
Título de la cita (Recomendado-único)
PEP-PREDNa+: A web server for prediction of highly specific peptides targeting voltage-gated Na+ channels using machine learning techniques
Identificador del recurso (Mandatado-único)
artículo original
Versión del recurso (Recomendado-único)
version publicada
Condición de la licencia (Recomendado-repetible)
0
Derechos de acceso
metadata
Access Rights
metadata
Id de Web of Science
WOS:000821011100001
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