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A desirability-based multi objective approach for the virtual screening discovery of broad-spectrum anti-gastric
Yunierkis Perez-Castillo1, Aminael Sánchez-Rodríguez2, Eduardo Tejera3
1Escuela de Ciencias Físicas y Matemáticas, Universidad de Las Américas, Quito, Ecuador.
Abstract:
Gastric cancer is the third leading cause of cancer-related mortality worldwide and despite advances in prevention, diagnosis and therapy, it is still regarded as a global health concern. The efficacy of the therapies for gastric cancer is limited by a poor response to currently available therapeutic regimens. One of the reasons that may explain these poor clinical outcomes is the highly heterogeneous nature of this disease. In this sense, it is essential to discover new molecular agents capable of targeting various gastric cancer subtypes simultaneously. Here, we present a multi-objective approach for the ligand-based virtual screening discovery of chemical compounds simultaneously active against the gastric cancer cell lines AGS, NCI-N87 and SNU-1. The proposed approach relays in a novel methodology based on the development of ensemble models for the bioactivity prediction against each individual gastric cancer cell line. The methodology includes the aggregation of one ensemble per cell line using a desirability-based algorithm into virtual screening protocols. Our research leads to the proposal of a multi-targeted virtual screening protocol able to achieve high enrichment of known chemicals with anti-gastric cancer activity. Specifically, our results indicate that, using the proposed protocol, it is possible to retrieve almost 20 more times multi-targeted compounds in the first 1% of the ranked list than what is expected from a uniform distribution of the active ones in the virtual screening database. More importantly, the proposed protocol attains an outstanding initial enrichment of known multi-targeted anti-gastric cancer agents.
Insights
This study introduces a novel virtual screening method to discover multi-targeted anti-gastric cancer compounds. The approach effectively identifies chemical agents active against diverse gastric cancer cell lines, improving therapeutic discovery.
Area of Science:
- Oncology
- Computational Chemistry
- Drug Discovery
Background:
- Gastric cancer remains a leading cause of cancer mortality globally.
- Therapeutic efficacy is limited by the disease's heterogeneity and poor drug response.
- There is a critical need for novel agents targeting multiple gastric cancer subtypes.
Purpose of the Study:
- To develop a multi-objective virtual screening approach for identifying compounds active against multiple gastric cancer cell lines (AGS, NCI-N87, SNU-1).
- To create ensemble models for predicting bioactivity against individual cell lines and aggregate them for screening.
Main Methods:
- Ligand-based virtual screening.
- Development of ensemble models for bioactivity prediction.
- Aggregation of ensemble models using a desirability-based algorithm.
- Multi-targeted virtual screening protocol design.
Main Results:
- The proposed protocol significantly enriches known multi-targeted anti-gastric cancer compounds.
- Achieved nearly 20-fold enrichment of multi-targeted compounds in the top 1% of the screened list compared to uniform distribution.
- Demonstrated outstanding initial enrichment of known multi-targeted agents.
Conclusions:
- The developed multi-targeted virtual screening protocol is effective in discovering novel anti-gastric cancer agents.
- This approach addresses the challenge of gastric cancer heterogeneity by identifying compounds with multi-subtype activity.
- The methodology offers a promising strategy for advancing gastric cancer drug discovery.
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