Article

Human immunode_ciency virus reverse transcriptase and protease sequence database.

Division of Infectious Diseases, Department of Medicine, Stanford University, Stanford, CA 94305, USA.
Nucleic Acids Research (Impact Factor: 9.11). 02/2003; 31(1):298-303.
Source: PubMed

ABSTRACT

The HIV reverse transcriptase and protease sequence database is an on-line relational database that catalogues evolutionary and drug-related sequence variation in the human immunodeficiency virus (HIV) reverse transcriptase (RT) and protease enzymes, the molecular targets of antiretroviral therapy (http://hivdb.stanford.edu). The database contains a compilation of nearly all published HIV RT and protease sequences, including submissions to GenBank, sequences published in journal articles and sequences of HIV isolates from persons participating in clinical trials. Sequences are linked to data about the source of the sequence, the antiretroviral drug treatment history of the person from whom the sequence was obtained and the results of in vitro drug susceptibility testing. Sequence data on two new molecular targets of HIV drug therapy--gp41 (cell fusion) and integrase--will be added to the database in 2003.

  • Source
    • "In all four patients, progressively lower viral rebounds were observed with a vigorous development of T CD8+ cells and an initial decrease in the response of T-helper cells, followed by a subsequent increase. In a second study, using a standard genotyping analysis and the HIVdb[12], the sequences codifying for the protease and reverse transcriptase were analyzed in samples corresponding to the viral rebounds of the STI program, finding no resistance to any of the PI or reversetranscriptase inhibitors commercially available[6]. Despite the limitations of the number of patients analyzed, the results of that previous work suggested that STI, in the context evaluated, could be safe; however, before suggesting new research in different populations of children, it is necessary to consider the genetic heterogeneity of the viral subpopulations during HIV infection and to assess the presence or absence of mutations associated with antiretroviral resistance even in minority viral populations infecting a patient. "

    Full-text · Dataset · Jan 2016
  • Source
    • "PDR was assessed by the presence of any of the mutations included in the list for HIV TDR surveillance defined and periodically updated by the WHO[16]. Additionally, PDR and ADR analyses were carried out with the Stanford HIV Drug Resistance Database algorithm (v7.0)[17,18], using the HIVdb programme available on line[19,20]. To define the presence of ARV drug resistance, a total drug penalty score of 15 or higher to any ARV drug (at least low-level resistance) was considered. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Introduction We assessed HIV drug resistance (DR) in individuals failing ART (acquired DR, ADR) and in ART-naïve individuals (pre-ART DR, PDR) in Honduras, after 10 years of widespread availability of ART. Methods 365 HIV-infected, ART-naïve, and 381 ART-experienced Honduran individuals were enrolled in 5 reference centres in Tegucigalpa, San Pedro Sula, La Ceiba, and Choluteca between April 2013 and April 2015. Plasma HIV protease-RT sequences were obtained. HIVDR was assessed using the WHO HIVDR mutation list and the Stanford algorithm. Recently infected (RI) individuals were identified using a multi-assay algorithm. Results PDR to any ARV drug was 11.5% (95% CI 8.4–15.2%). NNRTI PDR prevalence (8.2%) was higher than NRTI (2.2%) and PI (1.9%, p<0.0001). No significant trends in time were observed when comparing 2013 and 2014, when using a moving average approach along the study period or when comparing individuals with >500 vs. <350 CD4+ T cells/μL. PDR in recently infected individuals was 13.6%, showing no significant difference with PDR in individuals with longstanding infection (10.7%). The most prevalent PDR mutations were M46IL (1.4%), T215 revertants (0.5%), and K103NS (5.5%). The overall ADR prevalence in individuals with <48 months on ART was 87.8% and for the ≥48 months on ART group 81.3%. ADR to three drug families increased in individuals with longer time on ART (p = 0.0343). M184V and K103N were the most frequent ADR mutations. PDR mutation frequency correlated with ADR mutation frequency for PI and NNRTI (p<0.01), but not for NRTI. Clusters of viruses were observed suggesting transmission of HIVDR both from ART-experienced to ART-naïve individuals and between ART-naïve individuals. Conclusions The global PDR prevalence in Honduras remains at the intermediate level, after 10 years of widespread availability of ART. Evidence of ADR influencing the presence of PDR was observed by phylogenetic analyses and ADR/PDR mutation frequency correlations.
    Full-text · Article · Nov 2015 · PLoS ONE
  • Source
    • "The design of novel or rewired signaling and metabolic networks [78], for instance, inevitably invokes complex tradeoffs between different molecules and their properties, and these can also be encoded within the framework presented here. Recent advances in the application of deep sequencing to libraries of natural protein variants [79] [80] and of in vitro mutational repertoires selected for complex combinations of physical features, including stability , binding, and specificity profiles [34,36,81–83] are generating datasets comprising thousands of mutants that relate sequence changes to function at unprecedented resolution and coverage [84]. The fuzzy-logic design framework described here can be used to test hypotheses relating sequence, structure , and energetics to function, as well as in turn to fitness. "
    [Show abstract] [Hide abstract]
    ABSTRACT: To carry out their activities biological macromolecules balance different physical traits, such as stability, interaction affinity, and selectivity. How such often-opposing traits are encoded in a macromolecular system is critical to our understanding of evolutionary processes and ability to design new molecules with desired functions. We present a framework for constraining design simulations to balance different physical characteristics. Each trait is represented by the equilibrium fractional occupancy of the desired state relative to its alternatives, ranging from none to full occupancy, and the different traits are combined using Boolean operators to effect a ‘fuzzy’-logic language for encoding any combination of traits. In another paper, we presented a new combinatorial-backbone design algorithm AbDesign where the fuzzy-logic framework was used to optimize protein backbones and sequences for both stability and binding affinity in antibody-design simulation. We now extend this framework and find that fuzzy-logic design simulations reproduce sequence and structure design principles seen in nature to underlie exquisite specificity on the one hand, and multispecificity on the other. The fuzzy-logic language is broadly applicable and could help define the space of tolerated and beneficial mutations in natural biomolecular systems and design artificial molecules that encode complex characteristics.
    Full-text · Article · Oct 2014 · Journal of Molecular Biology
Show more