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Updated: Sep 9, 2025
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Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach
Published on: December 1, 2011
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Outbreak dates of virus could be predicted by their protein sequence
Peijun Zuo1, Longlong Zuo2, Zhihong Li3
1School of Public Health, Shantou University, Guangdong, China. peijunzuo@hotmail.com.
Journal of Translational Medicine
|September 2, 2025
Summary
Mathematical models predict viral outbreak timing using one-dimension protein sequences. This method analyzes monkeypox, smallpox, and coronavirus strains to forecast future outbreaks based on antigenic properties.
Area of Science:
- Virology
- Computational Biology
- Epidemiology
Background:
- Viral outbreaks including monkeypox, smallpox, and coronavirus have occurred globally for over 50 years.
- Predicting outbreak timing is crucial for public health preparedness and response.
- The relationship between pathogen genetic sequences and outbreak dynamics requires further investigation.
Purpose of the Study:
- To establish a mathematical model correlating one-dimension protein sequences with viral outbreak dates.
- To investigate the predictive power of antigenic properties derived from protein sequences for outbreak timing.
- To analyze the predictability of outbreak intervals for monkeypox, smallpox, and coronavirus.
Main Methods:
- Collected outbreak dates for monkeypox, smallpox, and coronavirus strains.
- Determined outbreak time intervals relative to SARS-CoV-2 D614.
- Analyzed one-dimension antigenic amino acid sequences to identify super-antigens and calculated antigen precision (x) and tryptophan content (y).
Main Results:
- A regression equation (z = 13.762x² - 109.376x - 63.290y + 221.197) was established, correlating outbreak time interval (z) with antigen precision (x) and tryptophan content (y).
- The model achieved a perfect correlation coefficient (R = 1.0000000).
- Statistical testing indicated a low probability of class I errors (P = 0.008).
Conclusions:
- The developed mathematical model effectively predicts viral outbreak dates using one-dimension protein sequence data.
- This approach is applicable to various viruses, including monkeypox, smallpox, and coronavirus.
- Protein sequence analysis offers a promising tool for forecasting viral emergence and spread.
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