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Isnan Mulia
Bogor Agricultural University
Computer Science & IT

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Algorithm for Predicting Compound Protein Interaction Using Tanimoto Similarity and Klekota-roth Fingerprint Isnan Mulia; Wisnu Ananta Kusuma; Farit Mochamad Afendi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 4: August 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i4.5916

Abstract

This research aimed to develop a method for predicting interaction between chemical compounds contained in herbs and proteins related to particular disease. The algorithm of this method is based on binary local models algorithm, with protein similarity section is omitted. Klekota-Roth fingerprint is used for the compound's representation. In the development process of the method, three similarity functions are compared: Tanimoto, Cosine, and Dice. Youden’s index is used to evaluate optimum threshold value. The result showed that Tanimoto similarity function yielded higher similarity values and higher AUC value than those of the other two functions. Moreover, the optimum threshold value obtained is 0.65. Therefore, Tanimoto similarity function and threshold value 0.65 are selected to be used on the prediction method. The average evaluation accuracy of the developed algorithm is only about 50%. The low accuracy value is allegedly caused by the only use of compound similarity on the prediction method, without including the protein similarity.
Co-Authors Farit Mochamad Afendi Wisnu Ananta Kusuma