# HPRNA: Predicting synergistic drug combinations for angina pectoris based on human pathway relationship network algorithm

## TL;DR

This paper introduces a new algorithm called HPRNA to predict effective drug combinations for angina pectoris using human pathway networks.

## Contribution

The novel Human Pathway Relationship Network Algorithm (HPRNA) improves prediction of synergistic drug combinations for angina pectoris.

## Key findings

- HPRNA outperforms previous algorithms in predicting synergistic drug combinations for angina pectoris.
- The algorithm uses drug targets and pathway information to calculate drug pair scores effectively.

## Abstract

Over the years, synergistic drug combinations therapies have attracted widespread attention due to its advantages of overcoming drug resistance, increasing treatment efficacy and decreasing toxicity. Compared to lengthy medical drugs experimental screening, mathematical models and algorithms show great potential in synergistic drug combinations prediction. In this paper, we introduce a novel mathematical algorithm, the Human Pathway Relationship Network Algorithm (HPRNA), which is designed to predict synergistic drug combinations for angina pectoris. We first reconstruct a novel angina pectoris drug dataset, which include drug name, drug metabolism, chemical formula, targets and pathways, then construct a comprehensive human pathway network based on the genetic similarity of the pathways which contain information about the targets. Finally, we introduce a novel indicator to calculate drug pair scores which measure the likelihood of forming synergistic drug combination. Experimental results on angina pectoris drug datasets convincingly demonstrate that the HPRNA makes efficient use of target and pathway information and is superior to previous algorithms.