Multi-Branch-CNN: Classification of ion channel interacting peptides using multi-branch convolutional neural network

Jielu YAN, Bob ZHANG*, Mingliang ZHOU, Hang Fai KWOK, Shirley W.I. SIU*

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

12 Citations (Scopus)

Abstract

Ligand peptides that have high affinity for ion channels are critical for regulating ion flux across the plasma membrane. These peptides are now being considered as potential drug candidates for many diseases, such as cardiovascular disease and cancers. In this work, we developed Multi-Branch-CNN, a CNN method with multiple input branches for identifying three types of ion channel peptide binders (sodium, potassium, and calcium) from intra- and inter-feature types. As for its real-world applications, prediction models that are able to recognize novel sequences having high or low similarities to training sequences are required. To this end, we tested our models on two test sets: a general test set including sequences spanning different similarity levels to those of the training set, and a novel-test set consisting of only sequences that bear little resemblance to sequences from the training set. Our experiments showed that the Multi-Branch-CNN method performs better than thirteen traditional ML algorithms (TML13), yielding an improvement in accuracy of 3.2%, 1.2%, and 2.3% on the test sets as well as 8.8%, 14.3%, and 14.6% on the novel-test sets for sodium, potassium, and calcium ion channels, respectively. We confirmed the effectiveness of Multi-Branch-CNN by comparing it to the standard CNN method with one input branch (Single-Branch-CNN) and an ensemble method (TML13-Stack). The data sets, script files to reproduce the experiments, and the final predictive models are freely available at https://github.com/jieluyan/Multi-Branch-CNN.

Original languageEnglish
Article number105717
JournalComputers in Biology and Medicine
Volume147
Early online date8 Jun 2022
DOIs
Publication statusPublished - Aug 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022 Elsevier Ltd

Keywords

  • Classification
  • Deep learning
  • Drug discovery
  • Ion channel
  • Multi-Branch-CNN
  • Peptides

Fingerprint

Dive into the research topics of 'Multi-Branch-CNN: Classification of ion channel interacting peptides using multi-branch convolutional neural network'. Together they form a unique fingerprint.

Cite this