# Mathematical Analysis of the Probability of Spontaneous Mutations in HIV-1 Genome and Their Role in the Emergence of Resistance to Anti-Retroviral Therapy

## TL;DR

This paper presents a mathematical model analyzing the probability of spontaneous mutations across the HIV-1 genome, identifying genes with lower mutability that are promising vaccine targets and highlighting the robustness of protease inhibitors.

## Contribution

It introduces a linear mathematical model relating gene length to mutation probability and applies it to identify key genes with lower mutability in HIV-1.

## Key findings

- tat, vpr, vpu are least mutant genes in HIV-1
- Protease gene is least mutant within polymerases
- Protease inhibitors provide a high genetic barrier

## Abstract

$\textbf{Background:}$ High mutability of HIV is the driving force of antiretroviral drug resistance, which represents a medical care challenge. $\textbf{Method and Model Equation:}$ To detect the mutability of each gene in the HIV-1 genome; a mathematical analysis of HIV-1 genome is performed, depending on a linear relation wherein the probability of spontaneous mutations emergence is directly proportional to the ratio of the gene length to the whole genome length. \begin{equation*} {P_g}{S_i} =\frac{g}{G} \end{equation*} $\textbf{Results:}$ $\textbf{tat}$, $\textbf{vpr}$ and $\textbf{vpu}$ are the least mutant genes in HIV-1 genome. Protease $\textbf{PROT}$ gene is the least mutant gene component of the polymerases $\textbf{pol}$. $\textbf{Conclusion:}$ $\textbf{tat}$, $\textbf{vpr}$ and $\textbf{vpu}$ are the best candidates for HIV-1 recombinant subunit vaccines or as a part of $\textit{prime and boost}$ vaccine combinations. Also; the protease inhibitor-based regime represents a high genetic barrier for HIV to overcome.