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Privileged substructures for anti-sickling activity via cheminformatic analysis.
Chuleeporn Phanus-Umporn1, Watshara Shoombuatong1, Veda Prachayasittikul1
1Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University Bangkok 10700 Thailand chanin.nan@mahidol.edu.
RSC Advances
|May 11, 2022
Summary
This study used cheminformatics to identify key molecular structures that inhibit sickle cell disease (SCD) formation. These findings will guide the development of new anti-sickling agents to combat this global health issue.
Area of Science:
- Medicinal Chemistry
- Computational Chemistry
- Genetics
Background:
- Sickle Cell Disease (SCD) is a major global health problem affecting over 300,000 individuals.
- SCD complications include anemia, pain, stroke, and organ damage, necessitating effective therapeutic strategies.
- Anti-sickling agents that prevent HbS polymerization are a promising treatment avenue.
Purpose of the Study:
- To identify privileged substructures responsible for the anti-sickling activity of chemical compounds.
- To develop robust Classification Structure-Activity Relationship (CSAR) models for predicting anti-sickling potential.
- To guide the rational design of novel anti-sickling agents.
Main Methods:
- Employed cheminformatic approaches, including fingerprint descriptors and CSAR modeling with machine learning algorithms.
- Assessed dataset modelability using the MODI index (0.70-0.84).
- Evaluated predictive performance using accuracy, sensitivity, specificity, and Matthews correlation coefficient.
Main Results:
- Developed statistically robust CSAR models with high predictive performance (accuracy, sensitivity, specificity > 0.7; MCC > 0.5).
- Identified key substructures associated with anti-sickling activity, including aromatic/conjugation, carbonyl, and miscellaneous groups.
- Determined that alkyl chain length, functional moiety, and substitution position influence anti-sickling activity.
Conclusions:
- The study successfully identified critical molecular features for anti-sickling activity.
- The developed CSAR models provide a data-driven approach for designing effective anti-sickling compounds.
- These findings offer valuable insights for developing new therapeutics against HbS gelling and SCD.
