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Martin Shkreli Is Back With a Web3 Drug Discovery Platform

The platform, still in the early development phase, is called Druglike, according to a press release that circulated on July 25. Its goals are ostensibly lofty, but the details are extremely sketchy, and Shkreli’s intentions have already drawn skepticism. It’s also unclear whether the enterprise will run Shkreli afoul of his lifetime ban from the pharmaceutical industry, which stemmed from the abrupt and callous 4,000 percent price hike of a life-saving drug that made him infamous.

Shkreli, who is named as a cofounder of Druglike, says the platform aims to make early-stage drug discovery more affordable and accessible. “Druglike will remove barriers to early-stage drug discovery, increase innovation and allow a broader group of contributors to share the rewards,” Shkreli said in the press release. “Underserved and underfunded communities, such as those focused on rare diseases or in developing markets, will also benefit from access to these tools.”

Generally, early-stage drug development can sometimes involve virtual screens to identify potential drug candidates. In these cases, pharmaceutical scientists first identify a “target”—a specific compound or protein that plays a critical role in developing a disease or condition. Then researchers look for compounds or small molecules that could interfere with that target, sometimes binding or “docking” directly to the target in a way that keeps it from functioning. This can be done in physical labs using massive libraries of compounds in high-throughput chemical screens. But it can also be done virtually, using specialized software and a lot of computing power, which can be resource-intensive.

DeepMind’s protein-folding AI cracks biology’s biggest problem

DeepMind has predicted the structure of almost every protein so far catalogued by science, cracking one of the grand challenges of biology in just 18 months thanks to an artificial intelligence called AlphaFold. Researchers say that the work has already led to advances in combating malaria, antibiotic resistance and plastic waste, and could speed up the discovery of new drugs.

Determining the crumpled shapes of proteins based on their sequences of constituent amino acids has been a persistent problem for decades in biology. Some of these amino acids are attracted to others, some are repelled by water, and the chains form intricate shapes that are hard to accurately determine.

Thinking long-term to save the world Martin Rees at New Scientist Live this October.

New vaccine could save thousands of lives

Academics have created a vaccine which has the potential to protect humans from the infection melioidosis, also called Whitmore’s disease.

The vaccine is the result of two decades of research, and is the most protective tested to date.

Melioidosis is caused by the bacterium Burkholderia pseudomallei. It is thought to be spread in soil and dust, but experts do not yet know why it only affects people and animals in tropical regions. Occasionally people from the UK have contracted melioidosis while on holiday abroad.

The Virus Zoo: A Quick Primer on Molecular Virology

The Virus Zoo is my latest educational blog post! I’ve written up ~1 page ‘cheat sheets’ on the molecular biology of specific viruses. I cover genome, structure, and life cycle. So far, my zoo includes adeno-associated virus (AAV), adenovirus, and herpes simplex virus 1 (HSV-1). However, I plan to add more viruses as time goes on! Some others I would like to incorporate later are coronavirus, HIV, anellovirus, lentivirus, ebolavirus, and MS2 bacteriophage. Feel free to suggest other interesting viruses in the comments! All images were created by me. #virology #molecularbiology #biotechnology #genetherapy #virus #biochemistry #genetics


Genome and Structure:

AAV genomes are about 4.7 kb in length and are composed of ssDNA. Inverted terminal repeats (ITRs) form hairpin structures at ends of the genome. These ITR structures are important for AAV genomic packaging and replication. Rep genes (encoded via overlapping reading frames) include Rep78, Rep68, Rep52, Rep40.1 These proteins facilitate replication of the viral genome. As a Dependoparvovirus, additional helper functions from adenovirus (or certain other viruses) are needed for AAVs to replicate.

AAV capsids are about 25 nm in diameter. Cap genes include VP1, VP2, VP3 and are transcribed from overlapping reading frames.2 The VP3 protein is the smallest capsid protein. The VP2 protein is the same as VP3 except that it includes an N-terminal extension with a nuclear localization sequence. The VP1 protein is the same as VP2 except that it includes a further N-terminal extension encoding a phospholipase A2 (PLA2) that facilitates endosomal escape during infection. In the AAV capsid, VP1, VP2, and VP3 are present at a ratio of roughly 1:1:10. It should be noted that this ratio is actually the average of a distribution, not a fixed number.

MIT system can fix your software bugs on its own (by borrowing from other software)

Circa 2015


New software being developed at MIT is proving able to autonomously repair software bugs by borrowing from other programs and across different programming languages, without requiring access to the source code. This could save developers thousands of hours of programming time and lead to much more stable software.

Bugs are the bane of the software developer’s life. The changes that must be made to fix them are often trivial, typically involving changing only a few lines of code, but the process of identifying exactly which lines need to be fixed can be a very time-consuming and often very frustrating process, particularly in larger projects.

But now, new software from MIT could take care of this, and more. The system, dubbed CodePhage, can fix bugs which have to do with variable checks, and could soon be expanded to fix many more types of mistakes. Remarkably, according to MIT researcher Stelios Sidiroglou-Douskos, the software can do this kind of dynamic code translation and transplant (dubbed “horizontal code transplant,” from the analogous process in genetics) without needing access to the source code and across different programming languages, by analyzing the executable file directly.

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