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DeepKa Web Server: High-Throughput Protein pKa Prediction.
Cai, Zhitao; Peng, Hao; Sun, Shuo; He, Jiahao; Luo, Fangfang; Huang, Yandong.
Affiliation
  • Cai Z; College of Computer Engineering, Jimei University, Xiamen 361021, China.
  • Peng H; National Pilot School of Software, Yunnan University, Kunming 650504, China.
  • Sun S; College of Computer Engineering, Jimei University, Xiamen 361021, China.
  • He J; College of Computer Engineering, Jimei University, Xiamen 361021, China.
  • Luo F; College of Computer Engineering, Jimei University, Xiamen 361021, China.
  • Huang Y; College of Computer Engineering, Jimei University, Xiamen 361021, China.
J Chem Inf Model ; 64(8): 2933-2940, 2024 04 22.
Article in En | MEDLINE | ID: mdl-38530291
ABSTRACT
DeepKa is a deep-learning-based protein pKa predictor proposed in our previous work. In this study, a web server was developed that enables online protein pKa 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 pKa'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.
Subject(s)

Full text: 1 Database: MEDLINE Main subject: Software / Internet Language: En Journal: J Chem Inf Model Journal subject: INFORMATICA MEDICA / QUIMICA Year: 2024 Type: Article Affiliation country: China

Full text: 1 Database: MEDLINE Main subject: Software / Internet Language: En Journal: J Chem Inf Model Journal subject: INFORMATICA MEDICA / QUIMICA Year: 2024 Type: Article Affiliation country: China