ArticleProteomics. Clinical applications2025
Classification of Acid and Alkaline Enzymes Based on Normalized Van der Waals Volume Features.
Article in Proteomics. Clinical applications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveAcidic and alkaline enzymes play crucial roles in the food industry and environmental management. This study aims to develop a computational method for accurately distinguishing between acidic and alkaline enzymes to enhance their stability in varying pH environments.
methodsWe employed AutoProp for feature extraction and the MRMD3.0 algorithm for feature selection. The most discriminative feature, the normalized Van der Waals volume (nFeat43), was identified and used for classification.
resultsThe selected feature (nFeat43) achieved a classification accuracy of 76.2% in distinguishing acidic from alkaline enzymes. Further analysis was conducted to interpret the physicochemical significance of this feature in enzyme discrimination.
conclusionsOur findings demonstrate that nFeat43 is a key determinant in differentiating acidic and alkaline enzymes. This method provides a rapid and reliable computational approach for enzyme characterization, which could aid in industrial and environmental applications.
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