Probing polymorph binding preference of CaCO3 biomineralization peptides through machine learning
Andre Leopold S Nidoy,
Jose Isagani B Janairo
Abstract:An exploratory machine learning (ML) classification model that seeks to examine CaCO3 polymorph selection is presented. The ML model can distinguish if a given peptide sequence binds with calcite or aragonite, polymorphs of CaCO3. The classifier, which was created using SVM and amino acid chemical composition as the input descriptors, yielded satisfactory performance in the classification task, as characterized by AUC = 0.736 and F1 = 0.800 in the test set. Model optimization revealed that tiny, aliphatic, aro… Show more
A key factor in biomineralization is the use of organic molecules to direct the formation of inorganic materials. However, identification of molecules that can selectively produce the calcium carbonate polymorphs...
A key factor in biomineralization is the use of organic molecules to direct the formation of inorganic materials. However, identification of molecules that can selectively produce the calcium carbonate polymorphs...
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