Changes in the Plasticity of HIV-1 Nef RNA during the Evolution of the North American Epidemic

G-Quadruplexes in the Regulation of Viral Gene Expressions and Their Impacts on Controlling Infection

G-quadruplexes (G4s) are noncanonical nucleic acid structures that play significant roles in regulating various biological processes, including replication, transcription, translation, and recombination. Recent studies have identified G4s in the genomes of several viruses, such as herpes viruses, hepatitis viruses, and human coronaviruses. These structures are implicated in regulating viral transcription, replication, and virion production, influencing viral infectivity and pathogenesis. G4-stabilizing ligands, like TMPyP4, PhenDC3, and BRACO19, show potential antiviral properties by targeting and stabilizing G4 structures, inhibiting essential viral life-cycle processes. This review delves into the existing literature on G4's involvement in viral regulation, emphasizing specific G4-stabilizing ligands. While progress has been made in understanding how these ligands regulate viruses, further research is needed to elucidate the mechanisms through which G4s impact viral processes. More research is necessary to develop G4-stabilizing ligands as novel antiviral agents. The increasing body of literature underscores the importance of G4s in viral biology and the development of innovative therapeutic strategies against viral infections. Despite some ligands' known regulatory effects on viruses, a deeper comprehension of the multifaceted impact of G4s on viral processes is essential. This review advocates for intensified research to unravel the intricate relationship between G4s and viral processes, paving the way for novel antiviral treatments.

Weighted lambda superstrings applied to vaccine design

We generalize the notion of λ-superstrings, presented in a previous paper, to the notion of weighted λ-superstrings. This generalization entails an important improvement in the applications to vaccine designs, as it allows epitopes to be weighted by their immunogenicities. Motivated by these potential applications of constructing short weighted λ-superstrings to vaccine design, we approach this problem in two ways. First, we formalize the problem as a combinatorial optimization problem (in fact, as two polynomially equivalent problems) and develop an integer programming (IP) formulation for solving it optimally. Second, we describe a model that also takes into account good pairwise alignments of the obtained superstring with the input strings, and present a genetic algorithm that solves the problem approximately. We apply both algorithms to a set of 169 strings corresponding to the Nef protein taken from patiens infected with HIV-1. In the IP-based algorithm, we take the epitopes and the estimation of the immunogenicities from databases of experimental epitopes. In the genetic algorithm we take as candidate epitopes all 9-mers present in the 169 strings and estimate their immunogenicities using a public bioinformatics tool. Finally, we used several bioinformatic tools to evaluate the properties of the candidates generated by our method, which indicated that we can score high immunogenic λ-superstrings that at the same time present similar conformations to the Nef virus proteins.