SSBONDPredict

A machine learning method for disulfide bond engineering site prediction based on structures

Introduction

SSBONDPredict is a project use a computational method based on neural network to predict residue pairs that can form disulfide bonds after cysteine mutations.The neural network was trained with atomic structures curated from the Protein Data Bank. The webserver are available at PredDisufideBond and you can get the detail source code and usage in PreDisulfideBond folder.Beside predicting the residue pairs which can form disulfide bonds after mutations,it also can calculate the change of entropy and energy due to mutations. The predicted result will show you this:

CYSA4-ARGA10 0.997 -24.4450 -1.8942

from left to right, the columes are:

• Residue pairs that are predicted to form disulfide bonds after mutations.
• The probability for this residue pairs to form disulfide bonds after mutations.
• The change of entropy after mutations
• The change of energy after mutations

Detailed Documentation

see the README in the Source code pages.

Copyright

SSBONDPredict is created by liulab of Beijing Compulational Science Research Center.