Gaining insights into the physicochemical properties and sequence space of blood–brain barrier penetrating peptides

Gaining insights into the physicochemical properties and sequence space of blood–brain barrier penetrating peptides

The blood–brain barrier (BBB) poses a significant obstacle to the administration of drugs to the brain for the development of therapies of central nervous system (CNS) disorders. Blood-brain barrier penetrating peptides (BBBPps) are a group of peptides that can traverse the BBB by different processe...

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Bibliographic Details
Main Authors: Abhigyan Nath, Sneha Pandey, Kottakkaran Sooppy Nisar, Anoop Kumar Tiwari
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Egyptian Informatics Journal
Subjects:
Blood brain barrier penetrating peptides
Sequence properties
Physicochemical space
Gradient boosting machines
XGboost
Model agnostic interpretation methods
Online Access:http://www.sciencedirect.com/science/article/pii/S1110866524001208
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Summary:The blood–brain barrier (BBB) poses a significant obstacle to the administration of drugs to the brain for the development of therapies of central nervous system (CNS) disorders. Blood-brain barrier penetrating peptides (BBBPps) are a group of peptides that can traverse the BBB by different processes without causing harm to the BBB. These peptides show promise as potential drugs for CNS ailments. Nevertheless, the process of identifying BBBPps using experimental approaches is both time-consuming and labour-intensive. To discover additional BBBPps as potential treatments for CNS diseases, it is critical to develop insilico methods that can distinguish BBBPps from non- BBBPps rapidly and precisely. In the current work, machine learning aided models are developed for accurate prediction of BBBPps using physicochemical and evolutionary information. The best model achieved an accuracy of 84.8 % by using 5-fold cross-validation and 79.8 % based on the holdout testing set on a reduced set of features. Further an extensive analysis is carried out for the black box models using model agnostic interpretation approaches to infer the physicochemical and sequence space of BBBPps. Basic amino acids and conservation of Arginine and Lysine are found to be more favoured in BBBPps. Further, basic amino acid property group and its interactions with other features are found to be prominent important interactions.
ISSN:1110-8665

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