Monash University

About: Monash University is a education organization based out in Melbourne, Victoria, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 35920 authors who have published 100681 publications receiving 3027002 citations.

The homozygosity test of neutrality

Abstract: An earlier paper showed that the homozygosity (of a population or sample) was a good statistic for testing departures from selective neutrality in the direction of heterozygote advantage or disadvantage. It is here shown that homozygosity is also influenced by the presence of deleterious alleles and by other departures from neutrality, but at a lower order of magnitude of effect if the selection coefficients are of the same small order of magnitude. Tables are provided for the significance points and moments of the homozygosity, under the null hypothesis of neutrality.

Antiretroviral Drugs for Treatment and Prevention of HIV Infection in Adults: 2016 Recommendations of the International Antiviral Society–USA Panel

Abstract: Importance New data and therapeutic options warrant updated recommendations for the use of antiretroviral drugs (ARVs) to treat or to prevent HIV infection in adults. Objective To provide updated recommendations for the use of antiretroviral therapy in adults (aged ≥18 years) with established HIV infection, including when to start treatment, initial regimens, and changing regimens, along with recommendations for using ARVs for preventing HIV among those at risk, including preexposure and postexposure prophylaxis. Evidence Review A panel of experts in HIV research and patient care convened by the International Antiviral Society–USA reviewed data published in peer-reviewed journals, presented by regulatory agencies, or presented as conference abstracts at peer-reviewed scientific conferences since the 2014 report, for new data or evidence that would change previous recommendations or their ratings. Comprehensive literature searches were conducted in the PubMed and EMBASE databases through April 2016. Recommendations were by consensus, and each recommendation was rated by strength and quality of the evidence. Findings Newer data support the widely accepted recommendation that antiretroviral therapy should be started in all individuals with HIV infection with detectable viremia regardless of CD4 cell count. Recommended optimal initial regimens for most patients are 2 nucleoside reverse transcriptase inhibitors (NRTIs) plus an integrase strand transfer inhibitor (InSTI). Other effective regimens include nonnucleoside reverse transcriptase inhibitors or boosted protease inhibitors with 2 NRTIs. Recommendations for special populations and in the settings of opportunistic infections and concomitant conditions are provided. Reasons for switching therapy include convenience, tolerability, simplification, anticipation of potential new drug interactions, pregnancy or plans for pregnancy, elimination of food restrictions, virologic failure, or drug toxicities. Laboratory assessments are recommended before treatment, and monitoring during treatment is recommended to assess response, adverse effects, and adherence. Approaches are recommended to improve linkage to and retention in care are provided. Daily tenofovir disoproxil fumarate/emtricitabine is recommended for use as preexposure prophylaxis to prevent HIV infection in persons at high risk. When indicated, postexposure prophylaxis should be started as soon as possible after exposure. Conclusions and Relevance Antiretroviral agents remain the cornerstone of HIV treatment and prevention. All HIV-infected individuals with detectable plasma virus should receive treatment with recommended initial regimens consisting of an InSTI plus 2 NRTIs. Preexposure prophylaxis should be considered as part of an HIV prevention strategy for at-risk individuals. When used effectively, currently available ARVs can sustain HIV suppression and can prevent new HIV infection. With these treatment regimens, survival rates among HIV-infected adults who are retained in care can approach those of uninfected adults.

Signalling bias in new drug discovery: detection, quantification and therapeutic impact

Abstract: Agonists of seven-transmembrane receptors, also known as G protein-coupled receptors (GPCRs), do not uniformly activate all cellular signalling pathways linked to a given seven-transmembrane receptor (a phenomenon termed ligand or agonist bias); this discovery has changed how high-throughput screens are designed and how lead compounds are optimized for therapeutic activity. The ability to experimentally detect ligand bias has necessitated the development of methods for quantifying agonist bias in a way that can be used to guide structure-activity studies and the selection of drug candidates. Here, we provide a viewpoint on which methods are appropriate for quantifying bias, based on knowledge of how cellular and intracellular signalling proteins control the conformation of seven-transmembrane receptors. We also discuss possible predictions of how biased molecules may perform in vivo, and what potential therapeutic advantages they may provide.

MUSTANG: a multiple structural alignment algorithm.

Abstract: Multiple structural alignment is a fundamental problem in structural genomics. In this article, we define a reliable and robust algorithm, MUSTANG (MUltiple STructural AligNment AlGorithm), for the alignment of multiple protein structures. Given a set of protein structures, the program constructs a multiple alignment using the spatial information of the C(alpha) atoms in the set. Broadly based on the progressive pairwise heuristic, this algorithm gains accuracy through novel and effective refinement phases. MUSTANG reports the multiple sequence alignment and the corresponding superposition of structures. Alignments generated by MUSTANG are compared with several handcurated alignments in the literature as well as with the benchmark alignments of 1033 alignment families from the HOMSTRAD database. The performance of MUSTANG was compared with DALI at a pairwise level, and with other multiple structural alignment tools such as POSA, CE-MC, MALECON, and MultiProt. MUSTANG performs comparably to popular pairwise and multiple structural alignment tools for closely related proteins, and performs more reliably than other multiple structural alignment methods on hard data sets containing distantly related proteins or proteins that show conformational changes.