Barry Bunin, PhD
Founder & CEO
Collaborative Drug Discovery
Researchers Whose Work Led to the Development of Wegovy and Ozempic Share How They Should be Used. Jens Juul Holst, a Danish biomedical scientist who worked on the initial delivery mechanism for glucagon-like peptide 1 (GLP-1), the hormone mimicked by semaglutide—sold as Ozempic, Wegovy, and Rybelsu—has an interesting take on the impact these weight-losing drugs may have on people. Some people lose up to 15% of their body weight in about a year…and as with all drugs, one needs to look at the benefit to risk ratio. In an interview with Wired, University of Copenhagen Professor Holst said: “We found that not only did GLP-1 stimulate insulin secretion, it also inhibited glucagon secretion. This was interesting, because people with diabetes have too much glucagon and that glucagon causes high blood sugar. So by stimulating insulin and inhibiting glucagon, you could have a double mechanism on the blood glucose. And now it was beginning to look like something interesting, and we were beginning to think of diabetes…” At first people getting full was seen as a side effect, as it complicated their testing protocol which required a full meal. As a medical doctor, he primarily looks at it from a health perspective (diabetes, obesity, etc), and yet treatment is related to quality of life, which of course may impact long-term revenues: “…what happens is that you lose your appetite and also the pleasure of eating, and so I think there’s a price to be paid when you do that. If you like food, then that pleasure is gone. The craving for food for some people is taken away when they take GLP-1 drugs. Once you’ve been on this for a year or two, life is so miserably boring that you can’t stand it any longer and you have to go back to your old life."
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An Improved Vaccine Technology? Derek Lowe, in his blog for Science, points to an interesting paper from CalTech and Acuitas, and commentary on the vaccine development. Here is how it basically works: it combines the mRNA aspect (to get in a cell) plus encoding a self-assembled eVLP (eveloped virus-like particle) which then “buds” from cells for the immunological response. The paper combines the traditional approach of injecting viral protein, with mRNA technology for a hybrid vaccine that self assembles and could provide broader protection – in mice. The preview states “…both mRNA-based delivery of genes encoding antigens as well as nanoparticle-based vaccines have shown great promise in tackling challenging pathogens. In this issue of Cell, Hoffmann et al. combine these two approaches, harnessing the same cellular pathway hijacked by many viruses to boost immune responses to SARS-CoV-2 vaccination.” The authors demonstrated they could make an mRNA vaccine with the coronavirus Spike (S) protein sequence + the “ESCRT and ALIX binding region” (EABR) protein sequence. “This EABR vaccine, when compared in mice to the ‘classic’ mRNA Spike protein vaccine technology, produces higher antibody titers and what’s more, ones with a wider polyclonal range as well,” Lowe writes. “So in theory you end up with the speed and flexibility of the mRNA approach (and all its endogenous-protein-production advantages), and the higher immunogenicity of the particle approaches. If this really does work out that way, it could be a big advance in vaccine technology in general.”
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AI Helps Researchers Identify Three Anti-Aging & Anti-Cancer Compounds. Researchers at Scotland’s University of Edinburgh have published a paper in Nature Communications detailing how they used an AI algorithm to comb through 4,300 chemical compounds to find three that could prompt cell senescence. An article in the UK’s Daily Mail explains researchers were searching for ways to eliminate cells related to aging which stop multiplying, but do not die off as they should, and continue to release chemicals that can trigger inflammation. The AI algorithm initially identified 21 candidates, which the researchers narrowed down to three common compounds (ginkgetin, oleandrin, and periplocin) which were able to remove defective cells without harming healthy ones when tested on human cells. The article notes “Cellular senescence occurs in a wide range of health conditions associated with getting older, including vision decline, osteoarthritis, a chronic lung disease known as Idiopathic pulmonary fibrosis, certain cancers, Alzheimer's disease, and atherosclerosis.” The mainstream newspaper quotes Dr. Diego Oyarzún, a co-author of the study, as saying: “This study demonstrates that AI can be incredibly effective in helping us identify new drug candidates, particularly at early stages of drug discovery and for diseases with complex biology or few known molecular targets.”
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Bambu: A New Long-Read RNA Sequencing Tool. Scientists from the Agency for Science, Technology and Research (A*STAR) of the Genome Institute of Singapore report they have developed a new tool, named Bambu (after the plant bamboo), which uses artificial intelligence to identify and characterize new genes, enabling an adaptable analysis across various species and samples. The team’s study is published in Nature Methods. The investigators write: “Most approaches to transcript quantification rely on fixed reference annotations; however, the transcriptome is dynamic and depending on the context, such static annotations contain inactive isoforms for some genes, whereas they are incomplete for others. Here we present Bambu, a method that performs machine-learning-based transcript discovery to enable quantification specific to the context of interest using long-read RNA-sequencing.” Jonathan Göke, PhD, group leader of the laboratory of computational transcriptomics at A*STAR, and the corresponding author of the study, is quoted in Genetic Engineering & Biotechnology News saying: “It is fascinating to see that scientists are still discovering new genes even in genomes that have been studied for many years, such as the human or mouse genome. However, the key question is if these transcripts are relevant, or if they could be artifacts. To address this, Bambu quantifies the probability that a transcript is real, making transcript and gene discovery much more reliable.”
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Barry A. Bunin, PhD, is the Founder & CEO of Collaborative Drug Discovery, which provides a modern approach to drug discovery research informatics trusted globally by thousands of leading researchers. The CDD Vault is a hosted biological and chemical database that securely manages your private and external data.
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