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Updated: Sep 19, 2025
Determination of the Gas-phase Acidities of Oligopeptides
Published on: June 24, 2013
Classification of Acid and Alkaline Enzymes Based on Normalized Van der Waals Volume Features
Hao Wan1, Quan Zou2, Yanan Zhang1
1Institute of Advanced Cross-Field Science, College of Life Science, Qingdao University, Qingdao, China.
Objective:
Acidic 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.
Methods:
We 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.
Results:
The 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.
Conclusions:
Our 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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