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DeepKa Web Server: High-Throughput Protein p K a Prediction.

Zhitao CaiHao PengShuo SunJiahao HeFangfang LuoYandong Huang
Published in: Journal of chemical information and modeling (2024)
DeepKa is a deep-learning-based protein p K a predictor proposed in our previous work. In this study, a web server was developed that enables online protein p K a prediction driven by DeepKa. The web server provides a user-friendly interface where a single step of entering a valid PDB code or uploading a PDB format file is required to submit a job. Two case studies have been attached in order to explain how p K a 's calculated by the web server could be utilized by users. Finally, combining the web server with post processing as described in case studies, this work suggests a quick workflow of investigating the relationship between protein structure and function that are pH dependent. The web server of DeepKa is freely available at http://www.computbiophys.com/DeepKa/main.
Keyphrases
  • protein protein
  • small molecule
  • high throughput
  • deep learning
  • binding protein
  • artificial intelligence
  • health information
  • convolutional neural network