Lifeboat Foundation

An algorithm that already predicts how proteins fold might also shed light on the physical principles that dictate this folding.

Proteins control every cell-level aspect of life, from immunity to brain activity. They are encoded by long sequences of compounds called amino acids that fold into large, complex 3D structures. Computational algorithms can model the physical amino-acid interactions that drive this folding [1]. But determining the resulting protein structures has remained challenging. In a recent breakthrough, a machine-learning model called AlphaFold [2] predicted the 3D structure of proteins from their amino-acid sequences. Now James Roney and Sergey Ovchinnikov of Harvard University have shown that AlphaFold has learned how to predict protein folding in a way that reflects the underlying physical amino-acid interactions [3]. This finding suggests that machine learning could guide the understanding of physical processes too complex to be accurately modeled from first principles.

Predicting the 3D structure of a specific protein is difficult because of the sheer number of ways in which the amino-acid sequence could fold. AlphaFold can start its computational search for the likely structure from a template (a known structure for similar proteins). Alternatively, and more commonly, AlphaFold can use information about the biological evolution of amino-acid sequences in the same protein family (proteins with similar functions that likely have comparable folds). This information is helpful because consistent correlated evolutionary changes in pairs of amino acids can indicate that these amino acids directly interact, even though they may be far in sequence from each other [4, 5]. Such information can be extracted from the multiple sequence alignments (MSAs) of protein families, determined from, for example, evolutionary variations of sequences across different biological species.

Kathryn Tunyasuvunakool grew up surrounded by scientific activities carried out at home by her mother—who went to university a few years after Tunyasuvunakool was born. One day a pendulum hung from a ceiling in her family’s home, Tunyasuvunakool’s mother standing next to it, timing the swings for a science assignment. Another day, fossil samples littered the dining table, her mother scrutinizing their patterns for a report. This early exposure to science imbued Tunyasuvunakool with the idea that science was fun and that having a career in science was an attainable goal. “From early on I was desperate to go to university and be a scientist,” she says.

Tunyasuvunakool fulfilled that ambition, studying math as an undergraduate, and computational biology as a graduate student. During her PhD work she helped create a model that captured various elements of the development of a soil-inhabiting roundworm called Caenorhabditis elegans, a popular organism for both biologists and physicists to study. She also developed a love for programming, which, she says, lent itself naturally to a jump into software engineering. Today Tunyasuvunakool is part of the team behind DeepMind’s AlphaFold—a protein-structure-prediction tool. Physics Magazine spoke to her to find out more about this software, which recently won two of its makers a Breakthrough Prize, and about why she’s excited for the potential discoveries it could enable.

All interviews are edited for brevity and clarity.

UCLA researchers and their colleagues have discovered a new physics principle governing how heat transfers through materials, and the finding contradicts the conventional wisdom that heat always moves faster as pressure increases.

Up until now, the common belief has held true in recorded observations and scientific experiments involving different materials such as gases, liquids and solids.

The researchers detailed their discovery in a study published last week by Nature. They have found that boron arsenide, which has already been viewed as a highly promising material for heat management and advanced electronics, also has a unique property. After reaching an extremely high pressure that is hundreds of times greater than the pressure found at the bottom of the ocean, boron arsenide’s thermal conductivity actually begins to decrease.

Work, conducted at Lawrence Livermore National Laboratory and featured in Nature Physics, shows that ions behave differently in fusion reactions than previously expected. Credit: John Jett and Jake Long/LLNL

Ions behave differently in fusion reactions than previously expected, according to new findings by scientists at Lawrence Livermore National Laboratory (LLNL). This discovery provides crucial insights for the future design of a laser–fusion energy source.

The findings, entitled “Evidence for suprathermal ion distribution in burning plasmas,” were featured in a new paper published in the November 14 issue of Nature Physics.

Someone else posted about this, but this is from LLNL. I love what they do, and Twitter reminded me of the many Photonics shares I have. This is cool, and Ill post more links.

November 7, 2022

A record high-laser-energy NIF target shot on Sept. 19 produced about 1.2 million joules of fusion energy yield. Compared with the groundbreaking 1.35-megajoule (MJ) experiment of Aug. 8, 2021, this experiment used higher laser energy and a modified experimental design.

Continue reading “High-Laser-Energy Shot Puts NIF Back on Track Toward Ignition” »

The merging of two neutron stars emits both light and gravitational waves at the same time, so if gravity and light have the same speed, they should be detected on Earth at the same time. Given the distance of the galaxy that housed these two neutron stars, we know that the two types of waves had traveled for about 130 million years and arrived within two seconds of one another.

So, that’s the answer. Gravity and light travel at the same speed, determined by a precise measurement. It validates Einstein once again, and it hints at something profound about the nature of space. Scientists hope one day to fully understand why these two very different phenomena have identical speeds.

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Continue reading “The REAL Possibility of Mapping Alien Planets!” »

Workshop supported by the Imperial College Physics of Life Network of Excellence.

https://www.imperial.ac.uk/physics-of-life.

Continue reading “Physics of Emergent Behaviour III: from origin of life to multicellularity, 2nd July 2021 (part 1)” »

If wormholes in space exist, they look a lot like black holes from a particular angle, physicists claim, raising the possibility we’ve seen examples of this long-sought phenomenon without knowing it.