Prediction of lysine formylation sites using the composition of k-spaced amino acid pairs via Chou's 5-steps rule and general pseudo components

• Published in: Genomics (San Diego, Calif.) Vol. 112; no. 1; pp. 859 - 866
• Main Authors: Ju, Zhe, Wang, Shi-Yun
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.01.2020
• Subjects: bioinformatics; chromatin; DNA; epigenetics; Feature extraction; Formylation; histones; lysine; Post-translational modification; prediction; Support vector machine; support vector machines; Post-translational modification; Feature extraction; Formylation; Support vector machine
• ISSN: 0888-7543; 1089-8646; 1089-8646
• DOI: 10.1016/j.ygeno.2019.05.027

Lysine formylation is a newly discovered post-translational modification in histones, which plays a crucial role in epigenetics of chromatin function and DNA binding. In this study, a novel bioinformatics tool named CKSAAP_FormSite is proposed to predict lysine formylation sites. An effective feature extraction method, the composition of k-spaced amino acid pairs, is employed to encode formylation sites. Moreover, a biased support vector machine algorithm is proposed to solve the class imbalance problem in the prediction of formylation sites. As illustrated by 10-fold cross-validation, CKSAAP_FormSite achieves an satisfactory performance with an AUC of 0.8234. Therefore, CKSAAP_FormSite can be a useful bioinformatics tool for the prediction of formylation sites. Feature analysis shows that some amino acid pairs, such as ‘KA’, ‘SxxxxK’ and ‘SxxxA’ around formylation sites may play an important role in the prediction. The results of analysis and prediction could offer useful information for elucidating the molecular mechanisms of formylation. •A novel predictor is develop to predict formylation sites.•The CKSAAP encoding is used to predict and analyze formylation sites.•The biased SVM is adopted as classifier.•A free online service is available for prediction.