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Papers of the Week


Papers: 26 Mar 2022 - 1 Apr 2022


Pharmacology/Drug Development


2022 Mar 26


Comput Biol Med


145

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

Authors

Herrera-Bravo J, Farías JG, Contreras F P, Herrera-Belén L, Beltrán JF
Comput Biol Med. 2022 Mar 26; 145:105414.
PMID: 35358751.

Abstract

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-PRED for the highly specific prediction of voltage-gated Na channel blocking peptides. PEP-PRED 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-PRED tool could be very useful in accelerating and reducing the costs of the discovery of new voltage-gated Na channel blocking peptides with therapeutic potential.