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ADDZYME: A software to predict effect of additives on enzyme activity.

Authors :
Rayka, Milad
Latifi, Ali Mohammad
Mirzaei, Morteza
Farnoosh, Gholamreza
Khosravi, Zeinab
Source :
Journal of Chemical Sciences. Sep2024, Vol. 136 Issue 3, p1-9. 9p.
Publication Year :
2024

Abstract

Enzymes are biological catalysts that accelerate chemical reactions by reducing their activation energy. Enzymes specific environmental conditions to function optimally. Additive molecules and compounds, such as organic solvents, ionic liquids, and deep eutectic solvents, have crucial effects on enzyme behavior by changing activity and stability. However, finding and testing different additives is an expensive process that requires specialists, laboratory equipment, and chemical compounds. Machine learning, which has been present in all fields of science and technology in recent years, is one of the ways to find a suitable additive for our desired enzyme without doing a time-consuming experimental process. In this manuscript, we introduce ADDZYME, a machine learning-based software, to predict the effect of additives on enzyme activity. ADDZYME utilizes an ensemble of extremely randomized trees models alongside physicochemical descriptors to make a prediction. To ease usage, ADDZYME is accompanied by a graphical user interface. ADDZYME is freely available on www.github.com/miladrayka/addzyme for further experiments. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09743626
Volume :
136
Issue :
3
Database :
Academic Search Index
Journal :
Journal of Chemical Sciences
Publication Type :
Academic Journal
Accession number :
178527363
Full Text :
https://doi.org/10.1007/s12039-024-02272-8