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Home / SmartTech / Coronavirus takes crowdsourcing molecular science from Folding @ Home to an exaflop level – TechCrunch

Coronavirus takes crowdsourcing molecular science from Folding @ Home to an exaflop level – TechCrunch



The long-standing Folding @ Home program to accomplish the enormously complex task of solving molecular interactions has reached an important milestone as thousands of new users log in to get their computers up and running. The network now includes an “exaflop” of computing power: 1,000,000,000,000,000,000 operations per second.

Folding @ Home was launched about 20 years ago as a novel way at that time, which was done by SETI @ Home, which is now at rest, as pioneering work to break up the calculation – serious problems and distribute them to individuals for execution. It is a crude supercomputer that is spread across the globe, and although it is not as effective at jumping through calculations as a "real" supercomputer, it can solve complex problems in a short amount of time.

The problem in question is addressed by this tool (managed by a group at Washington University in St. Louis) is protein folding. Proteins are one of the many chemical structures that make our biology work, and they range from small, relatively well-understood molecules to really huge molecules.

The thing with proteins is that they change shape depending on the conditions ̵

1; temperature, pH, the presence or absence of other molecules. This shape change often makes them useful – for example, a kinesin protein changes shape like a pair of legs that takes steps to carry a payload through a cell. Another protein, such as an ion channel, opens to allow charged atoms to pass through only when there is another protein that fits like a key in a lock.

Picture credits: Voelz et al.

Some such changes, or coils, are well documented, but most are far from being completely unknown. However, by robustly simulating the molecules and their environment, we can discover new information about proteins that can lead to important discoveries. For example, what if you could show that another protein, once this ion channel is open, could block or close it this way longer than usual? Finding this type of opportunity is what this type of molecular science is all about.

Unfortunately, it is also extremely computationally intensive. These inter- and intramolecular interactions can endlessly grind supercomputers to cover all possibilities. Supercomputers were much rarer 20 years ago than they are today, so Folding @ Home started to cope with this kind of heavy workload without buying a $ 500 million cray setup.

The program chugged all the time. and probably got a boost when SETI @ Home recommended it as an alternative to its many users. But the corona virus crisis has made the idea of ​​using its resources for a larger cause very attractive, and as such, the number of users has increased enormously – so much that the servers have trouble solving problems on all computers. [19659009] Examples of COVID-19-related proteins as visualized by Folding @ Home.

The milestone it celebrates is reaching an exaflop of processing power, which in my opinion means one sextillion (one billion billion) operations per second. An operation is a logical operation like AND or NOR, and several of them together form mathematical expressions that ultimately add up to useful things like the statement: “At temperatures above 38 degrees Celsius, this protein deforms so that a drug can bind to it can and disable it. “

Exascale computing is the next target of supercomputers. Intel and Cray are building Exascale computers for National Laboratories, which are expected to go online in the next few years. However, the fastest supercomputers available today operate on a scale of hundreds of petaflops, or about one-half to one-third the speed of an exaflop.

Of course, these two things are not directly comparable – Folding @ Home compiles the computing power of an exaflop, but does not work as a single unit that works on a single problem, since the exascale systems are designed for this. The Exa label is intended to give an impression of scalability.

Will this type of analysis lead to coronavirus treatments? Maybe later, but almost certainly not in the near future. Proteomics is "basic research" in that it is essentially about understanding the world around us (and in us) better.

COVID-19 (like Parkinson's, Alzheimer's, ALS, and others) is not a single problem, but a large, poorly limited amount of unknowns; The proteome and the associated interactions are part of this set. The point is not to come across a miracle cure, but to create a basis for understanding so that when evaluating potential solutions we can choose the right one percent faster, because we know that this molecule in This situation behaves like so .

As the project stated in a blog post announcing the publication of work related to coronaviruses:

This first wave of projects focuses on a better understanding of how these coronaviruses interact with the human ACE2 receptor, the is required for viral entry into human host cells and how researchers may disrupt them through the design of new therapeutic antibodies or small molecules that could disrupt their interaction.

If you'd like to help, you can download the Folding @ Home client and donate your spare CPU and GPU cycles to the cause.


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