Multiquery Similarity Searching Models: An Alternative Approach for Predicting Hemolytic Activity from Peptide Sequence

Journal
Chemical Research in Toxicology
ISSN
0893-228X
1520-5010
Publisher
American Chemical Society
Date Issued
2024
Author(s)
Castillo-Mendieta, Kevin
Agüero-Chapin, Guillermin
Marquez, Edgar
Perez-Castillo, Yunierkis
Barigye, Stephen J.
Pérez-Cárdenas, Mariela
Peréz-Giménez, Facundo
Type
text::journal::journal article
DOI
URL
Abstract
The desirable pharmacological properties and a broad number of therapeutic activities have made peptides promising drugs over small organic molecules and antibody drugs. Nevertheless, toxic effects, such as hemolysis, have hampered the development of such promising drugs. Hence, a reliable computational tool to predict peptide hemolytic toxicity is enormously useful before synthesis and experimental evaluation. Currently, four web servers that predict hemolytic activity using machine learning (ML) algorithms are available; however, they exhibit some limitations, such as the need for a reliable negative set and limited application domain. Hence, we developed a robust model based on a novel theoretical approach that combines network science and a multiquery similarity searching (MQSS) method. A total of 1152 initial models were constructed from 144 scaffolds generated in a previous report. These were evaluated on external data sets, and the best models were fused and improved. Our best MQSS model I1 outperformed all state-of-the-art ML-based models and was used to characterize the prevalence of hemolytic toxicity on therapeutic peptides. Based on our model’s estimation, the number of hemolytic peptides might be 3.9-fold higher than the reported.© 2024 American Chemical Society
License
Acceso Restringido
How to cite
Castillo-Mendieta, K., Agüero-Chapin, G., Marquez, E., Perez-Castillo, Y., Barigye, S. J., Pérez-Cárdenas, M., Peréz-Giménez, F., & Marrero-Ponce, Y. (2024). Multiquery Similarity Searching Models: An Alternative Approach for Predicting Hemolytic Activity from Peptide Sequence. In Chemical Research in Toxicology. American Chemical Society (ACS). https://doi.org/10.1021/acs.chemrestox.3c00408