We-Kcr: a new protein crotonylation site prediction method based on sequence feature and neural network

Lysine crotonylation (Kcr) is a form of post-translational modification that can be widely found in both histones and non-histone proteins. Precise detection of Kcr is essential for a better understanding of their functional mechanisms and drug development studies. Computational algorithms can predict Kcr and provide reliable data support for experimental methods. In this study, an effective new neural network-based computational framework for Kcr prediction (We-Kcr) was designed on a large amount of protein sequence data. After validation assessment and method comparison, the results showed that the prediction model exhibits higher accuracy in predicting Kcr sites. The research in this work provides biologists to explore the functional and biological mechanisms of protein modification. The materials can be downloaded from the following website: https://github.com/lihh225/We-Kcr.