Lifeboat Foundation

The entirety of the known universe is teeming with an infinite number of molecules. But what fraction of these molecules have potential drug-like traits that can be used to develop life-saving drug treatments? Millions? Billions? Trillions? The answer: novemdecillion, or 10⁶⁰. This gargantuan number prolongs the drug development process for fast-spreading diseases like COVID-19 because it is far beyond what existing drug design models can compute. To put it into perspective, the Milky Way has about 100 thousand million, or 10⁸, stars.

In a paper that will be presented at the International Conference on Machine Learning (ICML), MIT researchers developed a geometric deep-learning model called EquiBind that is 1,200 times faster than one of the fastest existing computational molecular docking models, QuickVina2-W, in successfully binding drug-like molecules to proteins. EquiBind is based on its predecessor, EquiDock, which specializes in binding two proteins using a technique developed by the late Octavian-Eugen Ganea, a recent MIT Computer Science and Artificial Intelligence Laboratory and Abdul Latif Jameel Clinic for Machine Learning in Health (Jameel Clinic) postdoc, who also co-authored the EquiBind paper.

Before drug development can even take place, drug researchers must find promising drug-like molecules that can bind or “dock” properly onto certain protein targets in a process known as drug discovery. After successfully docking to the protein, the binding drug, also known as the ligand, can stop a protein from functioning. If this happens to an essential protein of a bacterium, it can kill the bacterium, conferring protection to the human body.

Yes, it is true, cats are known to possess certain math skills in their own feline manner. Although it is obvious, they don’t have the knowledge of trigonometry or geometry as we do, but they sure understand the concept of ‘more and less’.

Every cat owner knows they get notified by their cat if the food dish is getting empty or the water is relatively less in the bowl. Furthermore, as they grow, cats can adeptly tell the difference between heights.

Albeit, this is still an ongoing study and researchers have found similarities between the thinking process of fish and that of cats. Fish swim in schools, and that’s how they learn to count. Likewise, adult cats or rather mother cats can identify if one of the kittens is missing.

While many artificial materials have advanced properties, they have a long way to go to combine the versatility and functionality of living materials that can adapt to their situation. For example, in the human body bone and muscle continuously reorganise their structure and composition to better sustain changing weight and level of activity.

Now, researchers from Imperial College London and University College London have demonstrated the first spontaneously self-organising laser device, which can reconfigure when conditions change.

The innovation, reported in Nature Physics (“Self-organized Lasers of Reconfigurable Colloidal Assemblies”), will help enable the development of smart photonic materials capable of better mimicking properties of biological matter, such as responsiveness, adaptation, self-healing, and collective behaviour.

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Gene editing with CRISPR can cause off-target mutations, but this seems to happen less often with an enzyme that cuts one of the strands of DNA instead of both.

The potential of quantum computing can in no way be undermined today as it solves some of the most obstinate challenges from bringing down global warming to dramatically bringing down drug discovery time and much more. And with this, several companies are in a spree to bring up quantum computing capabilities.

Nvidia has announced a unified computing platform that will bring in an open environment across quantum processors and classical computers. The company said that the platform aims at speeding enhanced quantum research and development across Artificial Intelligence (AI), High Performance Computing (HPC), health, finance and other disciplines.

The company claims that Nvidia Quantum Optimized Device Architecture or QODA is a first-of-its-kind platform for hybrid quantum-classical computers and aims to make quantum computing more accessible by creating a comprehensive hybrid quantum-classical programming model.