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Updated: Sep 23, 2025
Characterization of Sickling During Controlled Automated Deoxygenation with Oxygen Gradient Ektacytometry
Published on: November 5, 2019
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.
Insights
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.
Abstract:
Sickle cell disease (SCD), an autosomal recessive genetic disorder, has been recognized by the World Health Organization (WHO) as a major public health problem as it affects 300 000 individuals worldwide. Complications arising from SCD include anemia, microvascular occlusion, severe pain, stokes, renal dysfunction and infections. A lucrative therapeutic strategy is to employ anti-sickling agents that can disrupt the formation of the HbS polymer. This study therefore employed cheminformatic approaches, encompassing classification structure-activity relationship (CSAR) modeling, to deduce the privileged substructures giving rise to the anti-sickling activity of an investigated set of 115 compounds, followed by substructure analysis. Briefly, the compiled compounds were described by fingerprint descriptors and used in the construction of CSAR models via several machine learning algorithms. The modelability of the data set, as exemplified by the MODI index, was determined to be in the range of 0.70-0.84. The predictive performance was deduced by the accuracy, sensitivity, specificity and Matthews correlation coefficient, which was found to be statistically robust, whereby the former three parameters afforded values in excess of 0.7 while the latter statistical parameter provided a value greater than 0.5. An analysis of the top 20 important substructure descriptors for anti-sickling activity revealed that 10 important features were significant in the differentiation of actives from inactives, as illustrated by aromaticity/conjugation (e.g. SubFPC287, SubFPC171 and SubFPC5), carbonyl groups (e.g. SubFPC137, SubFPC139, SubFPC49 and SubFPC135) and miscellaneous groups (e.g. SubFPC303, SubFPC302 and SubFPC275). Furthermore, an analysis of the structure-activity relationship revealed that the length of alkyl chains, choice of functional moiety and position of substitution on the benzene ring may affect the anti-sickling activity of these compounds. Thus, this knowledge is anticipated to be useful for guiding the design of robust compounds against the gelling activity of HbS, as preliminarily demonstrated in the data-driven compound design presented herein.
