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D3AI-Spike: A deep learning platform for predicting binding affinity between SARS-CoV-2 spike receptor binding domain with multiple amino acid mutations and human angiotensin-converting enzyme 2.
Han, Jiaxin; Liu, Tingting; Zhang, Xinben; Yang, Yanqing; Shi, Yulong; Li, Jintian; Ma, Minfei; Zhu, Weiliang; Gong, Likun; Xu, Zhijian.
  • Han J; School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing, 210046, China; Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China.
  • Liu T; Center for Drug Safety Evaluation and Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China.
  • Zhang X; Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China.
  • Yang Y; Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; School of Pharmacy, University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing, 100049, China.
  • Shi Y; Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; School of Pharmacy, University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing, 100049, China.
  • Li J; Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; School of Pharmacy, University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing, 100049, China.
  • Ma M; Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; School of Pharmacy, University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing, 100049, China.
  • Zhu W; School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing, 210046, China; Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; School of Pharmacy, University of Chinese Academy of Sciences, No.19A Yuquan
  • Gong L; Center for Drug Safety Evaluation and Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China. Electronic address: lkgong@cdser.simm.ac.cn.
  • Xu Z; Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; School of Pharmacy, University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing, 100049, China. Electronic address: zjxu@simm.ac.cn.
Comput Biol Med ; 151(Pt A): 106212, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2086096
ABSTRACT
The number of SARS-CoV-2 spike Receptor Binding Domain (RBD) with multiple amino acid mutations is huge due to random mutations and combinatorial explosions, making it almost impossible to experimentally determine their binding affinities to human angiotensin-converting enzyme 2 (hACE2). Although computational prediction is an alternative way, there is still no online platform to predict the mutation effect of RBD on the hACE2 binding affinity until now. In this study, we developed a free online platform based on deep learning models, namely D3AI-Spike, for quickly predicting binding affinity between spike RBD mutants and hACE2. The models based on CNN and CNN-RNN methods have the concordance index of around 0.8. Overall, the test results of the models are in agreement with the experimental data. To further evaluate the prediction power of D3AI-Spike, we predicted and experimentally determined the binding affinity of a VUM (variants under monitoring) variant IHU (B.1.640.2), which has fourteen amino acid substitutions, including N501Y and E484K, and 9 deletions located in the spike protein. The predicted average affinity score for wild-type RBD and IHU to hACE2 are 0.483 and 0.438, while the determined Kaff values are 5.39 ± 0.38 × 107 L/mol and 1.02 ± 0.47 × 107 L/mol, respectively, demonstrating the strong predictive power of D3AI-Spike. We think D3AI-Spike will be helpful to the viral transmission prediction for the new emerging SARS-CoV-2 variants. D3AI-Spike is now available free of charge at https//www.d3pharma.com/D3Targets-2019-nCoV/D3AI-Spike/index.php.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Deep Learning / COVID-19 Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Topics: Variants Limits: Humans Language: English Journal: Comput Biol Med Year: 2022 Document Type: Article Affiliation country: J.compbiomed.2022.106212

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Deep Learning / COVID-19 Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Topics: Variants Limits: Humans Language: English Journal: Comput Biol Med Year: 2022 Document Type: Article Affiliation country: J.compbiomed.2022.106212