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DRDB: A Machine Learning Platform to Predict Chemical-Protein Interactions towards Diabetic Retinopathy
Yu Wei1, Ruili Zhang1, Xiaoqiang Li2
1State Key Laboratory of Medicinal Chemical Biology, Frontiers Science Center for Cell Responses, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Tianjin 300353, China.
Oxidative Medicine and Cellular Longevity
|August 1, 2022
Summary
This study developed a web server (DRDB) to predict drug targets for diabetic retinopathy (DR). It identified potential DR drug candidates and validated that key components of Danshen Dripping Pills target ICAM-1, a crucial DR protein.
Area of Science:
- Computational chemistry and bioinformatics
- Drug discovery and development
- Ophthalmology and diabetology
Background:
- Diabetic retinopathy (DR) affects 93 million globally, with current treatments showing limited efficacy and side effects due to complex pathogenesis involving multiple proteins.
- The need for novel therapeutic strategies is critical given the limitations of existing treatments for diabetic retinopathy.
- Identifying specific protein targets and effective drug candidates is essential for advancing DR treatment.
Purpose of the Study:
- To identify potential drugs and predict drug targets for diabetic retinopathy (DR) using in silico methods.
- To develop and validate a web server (DRDB) for predicting chemical-protein interactions (CPI) relevant to DR.
- To explore the therapeutic potential of Danshen Dripping Pills (CDDP) components against DR targets.
Main Methods:
- Developed 128 binary classifiers using Random Forest, KNN, SVM, and NN algorithms to predict CPI for 15 DR targets.
- Utilized MACCS, ECFP6 fingerprints, and protein descriptors for in silico prediction of chemical-protein interactions.
- Employed the developed DRDB web server to investigate potential CPIs of CDDP components in DR treatment and performed in vitro validation.
Main Results:
- Successfully developed 128 binary classifiers and a free web server (DRDB) for predicting CPI in DR.
- Investigated Danshen Dripping Pills (CDDP) using DRDB, revealing potential interactions with DR targets.
- In vitro experiments confirmed that cryptotanshinone and protocatechuic acid from CDDP target ICAM-1, a key DR protein.
Conclusions:
- The DRDB web server facilitates novel drug discovery and target identification for diabetic retinopathy.
- Key components of Danshen Dripping Pills show promise in targeting ICAM-1 for DR treatment.
- This research supports the development of more effective clinical strategies for managing diabetic retinopathy.
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