Prevalence of and viral outcomes associated with primary HIV-1 drug resistance

Prevalence of primary drug resistance among newly diagnosed HIV-1 infected individuals in Hunan province, China

At present, research on the prevalence of primary drug resistance (PDR) in Hunan province is limited. Therefore, we explored the current status of HIV-1 PDR in Hunan to provide a basis for antiretroviral therapy (ART) and a theoretical foundation for the prevention and control of the HIV/AIDS epidemic.370 newly diagnosed HIV-1 infected individuals who had not received ART were enrolled in Hunan province, China. Plasma samples were collected, RNA was extracted, two rounds of gene amplification were carried out with the In-house method, and a subtype analysis and drug resistance analysis were carried out with the relevant software. We found that the most prevalent subtypes of HIV-1 in Hunan Province are CRF_01AE (126/359, 35.1%) and CRF07_BC (85/359, 23.7%). The PDR rate among newly diagnosed HIV/AIDS patients was 10.0% (36/359). Among them, the drug resistance rate of protease inhibitors (PIs), nucleotide reverse transcriptase inhibitors (NRTIs), non-nucleotide reverse transcriptase inhibitors (NNRTIs), and integrase inhibitors (INs) was 0.3% (1/359), 3.3% (12/359), 8.36% (30/359), and 0.6% (2/359), respectively. The distribution of HIV-1 subtypes in Hunan Province is diverse and complex, and the primary drug resistance rate has exceeded the low-level warning line set by the WHO (< 5%). Therefore, we should conduct pre-treatment drug resistance assays to determine the optimal primary ART, so that the patients can obtain better antiretroviral treatment outcomes, and the transmission of drug-resistant strains in the population can be blocked.

Increasing HIV-1 subtype diversity in seven states, United States, 2006-2013

PURPOSE

The aim of the analysis was to explore HIV-1 subtype diversity in the United States and understand differences in prevalence of non-B subtypes and circulating recombinant forms (CRFs) between demographic/risk groups and over time.

METHODS

We included HIV-1 polymerase sequences reported to the National HIV Surveillance System for HIV infections diagnosed during 2006-2013 in seven states. We assigned subtype or CRF using the automated subtyping tool COMET, assessed subtype/CRF prevalence by demographic characteristics and country of birth, and determined changes in subtype/CRF by HIV diagnosis year.

RESULTS

Of 32,968 sequences, 30,757 (93.3%) were subtype B. The most common non-B subtypes and CRFs were C (1.6%), CRF02_AG (1.4%), A (0.6%), CRF01_AE (0.5%), and G (0.3%). Elevated percentages of non-B infections occurred among persons aged <13 years at diagnosis (40.9%), Asians (32.1%), persons born outside the United States (22.6%), and persons with infection attributable to heterosexual contact (12.0%-15.0%). Prevalence of non-B infections increased from 5.9% in 2006 to 8.5% in 2013.

CONCLUSIONS

Subtype B continues to predominate in the United States. However, the percentage of non-B infections has grown in recent years, and numerous demographic subgroups have much higher prevalence. Subgroups and areas with high prevalence of non-B infections might represent sub-epidemics meriting further investigation.

New approach to develop ultra-high inhibitory drug using the power function of the stoichiometry of the targeted nanomachine or biocomplex

AIMS

To find methods for potent drug development by targeting to biocomplex with high copy number.

METHODS

Phi29 DNA packaging motor components with different stoichiometries were used as model to assay virion assembly with Yang Hui's Triangle [Formula: see text], where Z = stoichiometry, M = drugged subunits per biocomplex, p and q are the fraction of drugged and undrugged subunits in the population.

RESULTS

Inhibition efficiency follows a power function. When number of drugged subunits to block the function of the complex K = 1, the uninhibited biocomplex equals q(z), demonstrating the multiplicative effect of stoichiometry on inhibition with stoichiometry 1000 > 6 > 1. Complete inhibition of virus replication was found when Z = 6.

CONCLUSION

Drug inhibition potency depends on the stoichiometry of the targeted components of the biocomplex or nanomachine. The inhibition effect follows a power function of the stoichiometry of the target biocomplex.

Discovery of a new method for potent drug development using power function of stoichiometry of homomeric biocomplexes or biological nanomotors

INTRODUCTION

Multidrug resistance and the appearance of incurable diseases inspire the quest for potent therapeutics.

AREAS COVERED

We review a new methodology in designing potent drugs by targeting multi-subunit homomeric biological motors, machines or complexes with Z > 1 and K = 1, where Z is the stoichiometry of the target, and K is the number of drugged subunits required to block the function of the complex. The condition is similar to a series electrical circuit of Christmas decorations: failure of one light bulb causes the entire lighting system to lose power. In most multi-subunit, homomeric biological systems, a sequential coordination or cooperative action mechanism is utilized, thus K equals 1. Drug inhibition depends on the ratio of drugged to non-drugged complexes. When K = 1, and Z > 1, the inhibition effect follows a power law with respect to Z, leading to enhanced drug potency. The hypothesis that the potency of drug inhibition depends on the stoichiometry of the targeted biological complexes was recently quantified by Yang-Hui's Triangle (or binomial distribution), and proved using a highly sensitive in vitro phi29 viral DNA packaging system. Examples of targeting homomeric bio-complexes with high stoichiometry for potent drug discovery are discussed.

EXPERT OPINION

Biomotors with multiple subunits are widespread in viruses, bacteria and cells, making this approach generally applicable in the development of inhibition drugs with high efficiency.