Tag Archives: Francisco J. Martin-Martinez

Sonifying proteins to make music and brand new proteins

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Markus Buehler at the Massachusetts Institute of Technology (MIT) has been working with music and science for a number of years. My December 9, 2011 posting, Music, math, and spiderwebs, was the first one here featuring his work. My November 28, 2012 posting, Producing stronger silk musically, was a followup to Buehler’s previous work.

A June 28, 2019 news item on Azonano provides a recent update,

Composers string notes of different pitch and duration together to create music. Similarly, cells join amino acids with different characteristics together to make proteins.

Now, researchers have bridged these two seemingly disparate processes by translating protein sequences into musical compositions and then using artificial intelligence to convert the sounds into brand-new proteins. …

Caption: Researchers at MIT have developed a system for converting the molecular structures of proteins, the basic building blocks of all living beings, into audible sound that resembles musical passages. Then, reversing the process, they can introduce some variations into the music and convert it back into new proteins never before seen in nature. Credit: Zhao Qin and Francisco Martin-Martinez

A June 26, 2019 American Chemical Society (ACS) news release, which originated the news item, provides more detail and a video,

To make proteins, cellular structures called ribosomes add one of 20 different amino acids to a growing chain in combinations specified by the genetic blueprint. The properties of the amino acids and the complex shapes into which the resulting proteins fold determine how the molecule will work in the body. To better understand a protein’s architecture, and possibly design new ones with desired features, Markus Buehler and colleagues wanted to find a way to translate a protein’s amino acid sequence into music.

The researchers transposed the unique natural vibrational frequencies of each amino acid into sound frequencies that humans can hear. In this way, they generated a scale consisting of 20 unique tones. Unlike musical notes, however, each amino acid tone consisted of the overlay of many different frequencies –– similar to a chord. Buehler and colleagues then translated several proteins into audio compositions, with the duration of each tone specified by the different 3D structures that make up the molecule. Finally, the researchers used artificial intelligence to recognize specific musical patterns that corresponded to certain protein architectures. The computer then generated scores and translated them into new-to-nature proteins. In addition to being a tool for protein design and for investigating disease mutations, the method could be helpful for explaining protein structure to broad audiences, the researchers say. They even developed an Android app [Amino Acid Synthesizer] to allow people to create their own bio-based musical compositions.

Here’s the ACS video,

A June 26, 2019 MIT news release (also on EurekAlert) provides some specifics and the MIT news release includes two embedded audio files,

Want to create a brand new type of protein that might have useful properties? No problem. Just hum a few bars.

In a surprising marriage of science and art, researchers at MIT have developed a system for converting the molecular structures of proteins, the basic building blocks of all living beings, into audible sound that resembles musical passages. Then, reversing the process, they can introduce some variations into the music and convert it back into new proteins never before seen in nature.

Although it’s not quite as simple as humming a new protein into existence, the new system comes close. It provides a systematic way of translating a protein’s sequence of amino acids into a musical sequence, using the physical properties of the molecules to determine the sounds. Although the sounds are transposed in order to bring them within the audible range for humans, the tones and their relationships are based on the actual vibrational frequencies of each amino acid molecule itself, computed using theories from quantum chemistry.

The system was developed by Markus Buehler, the McAfee Professor of Engineering and head of the Department of Civil and Environmental Engineering at MIT, along with postdoc Chi Hua Yu and two others. As described in the journal ACS Nano, the system translates the 20 types of amino acids, the building blocks that join together in chains to form all proteins, into a 20-tone scale. Any protein’s long sequence of amino acids then becomes a sequence of notes.

While such a scale sounds unfamiliar to people accustomed to Western musical traditions, listeners can readily recognize the relationships and differences after familiarizing themselves with the sounds. Buehler says that after listening to the resulting melodies, he is now able to distinguish certain amino acid sequences that correspond to proteins with specific structural functions. “That’s a beta sheet,” he might say, or “that’s an alpha helix.”

Learning the language of proteins

The whole concept, Buehler explains, is to get a better handle on understanding proteins and their vast array of variations. Proteins make up the structural material of skin, bone, and muscle, but are also enzymes, signaling chemicals, molecular switches, and a host of other functional materials that make up the machinery of all living things. But their structures, including the way they fold themselves into the shapes that often determine their functions, are exceedingly complicated. “They have their own language, and we don’t know how it works,” he says. “We don’t know what makes a silk protein a silk protein or what patterns reflect the functions found in an enzyme. We don’t know the code.”

By translating that language into a different form that humans are particularly well-attuned to, and that allows different aspects of the information to be encoded in different dimensions — pitch, volume, and duration — Buehler and his team hope to glean new insights into the relationships and differences between different families of proteins and their variations, and use this as a way of exploring the many possible tweaks and modifications of their structure and function. As with music, the structure of proteins is hierarchical, with different levels of structure at different scales of length or time.

The team then used an artificial intelligence system to study the catalog of melodies produced by a wide variety of different proteins. They had the AI system introduce slight changes in the musical sequence or create completely new sequences, and then translated the sounds back into proteins that correspond to the modified or newly designed versions. With this process they were able to create variations of existing proteins — for example of one found in spider silk, one of nature’s strongest materials — thus making new proteins unlike any produced by evolution.

Although the researchers themselves may not know the underlying rules, “the AI has learned the language of how proteins are designed,” and it can encode it to create variations of existing versions, or completely new protein designs, Buehler says. Given that there are “trillions and trillions” of potential combinations, he says, when it comes to creating new proteins “you wouldn’t be able to do it from scratch, but that’s what the AI can do.”

“Composing” new proteins

By using such a system, he says training the AI system with a set of data for a particular class of proteins might take a few days, but it can then produce a design for a new variant within microseconds. “No other method comes close,” he says. “The shortcoming is the model doesn’t tell us what’s really going on inside. We just know it works.

This way of encoding structure into music does reflect a deeper reality. “When you look at a molecule in a textbook, it’s static,” Buehler says. “But it’s not static at all. It’s moving and vibrating. Every bit of matter is a set of vibrations. And we can use this concept as a way of describing matter.”

The method does not yet allow for any kind of directed modifications — any changes in properties such as mechanical strength, elasticity, or chemical reactivity will be essentially random. “You still need to do the experiment,” he says. When a new protein variant is produced, “there’s no way to predict what it will do.”

The team also created musical compositions developed from the sounds of amino acids, which define this new 20-tone musical scale. The art pieces they constructed consist entirely of the sounds generated from amino acids. “There are no synthetic or natural instruments used, showing how this new source of sounds can be utilized as a creative platform,” Buehler says. Musical motifs derived from both naturally existing proteins and AI-generated proteins are used throughout the examples, and all the sounds, including some that resemble bass or snare drums, are also generated from the sounds of amino acids.

The researchers have created a free Android smartphone app, called Amino Acid Synthesizer, to play the sounds of amino acids and record protein sequences as musical compositions.

Here’s a link to and a citation for the paper,

A Self-Consistent Sonification Method to Translate Amino Acid Sequences into Musical Compositions and Application in Protein Design Using Artificial Intelligence by Chi-Hua Yu, Zhao Qin, Francisco J. Martin-Martinez, Markus J. Buehler. ACS Nano 2019 XXXXXXXXXX-XXX DOI: https://doi.org/10.1021/acsnano.9b02180 Publication Date:June 26, 2019 Copyright © 2019 American Chemical Society

This paper is behind a paywall.

ETA October 23, 2019 1000 hours: Ooops! I almost forgot the link to the Aminot Acid Synthesizer.

Worm-inspired gel material and soft robots

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The Nereis virens worm inspired new research out of the MIT Laboratory for Atomistic and Molecular Mechanics. Its jaw is made of soft organic material, but is as strong as harder materials such as human dentin. Photo: Alexander Semenov/Wikimedia Commons

What an amazing worm! Here’s more about robots inspired by the Nereis virens worm in a March 20, 2017 news item on Nanowerk,

A new material that naturally adapts to changing environments was inspired by the strength, stability, and mechanical performance of the jaw of a marine worm. The protein material, which was designed and modeled by researchers from the Laboratory for Atomistic and Molecular Mechanics (LAMM) in the Department of Civil and Environmental Engineering (CEE) [at the Massachusetts Institute of Technology {MIT}], and synthesized in collaboration with the Air Force Research Lab (AFRL) at Wright-Patterson Air Force Base, Ohio, expands and contracts based on changing pH levels and ion concentrations. It was developed by studying how the jaw of Nereis virens, a sand worm, forms and adapts in different environments.

The resulting pH- and ion-sensitive material is able to respond and react to its environment. Understanding this naturally-occurring process can be particularly helpful for active control of the motion or deformation of actuators for soft robotics and sensors without using external power supply or complex electronic controlling devices. It could also be used to build autonomous structures.

A March 20, 2017 MIT news release, which originated the news item, provides more detail,

“The ability of dramatically altering the material properties, by changing its hierarchical structure starting at the chemical level, offers exciting new opportunities to tune the material, and to build upon the natural material design towards new engineering applications,” wrote Markus J. Buehler, the McAfee Professor of Engineering, head of CEE, and senior author of the paper.

The research, recently published in ACS Nano, shows that depending on the ions and pH levels in the environment, the protein material expands and contracts into different geometric patterns. When the conditions change again, the material reverts back to its original shape. This makes it particularly useful for smart composite materials with tunable mechanics and self-powered roboticists that use pH value and ion condition to change the material stiffness or generate functional deformations.

Finding inspiration in the strong, stable jaw of a marine worm

In order to create bio-inspired materials that can be used for soft robotics, sensors, and other uses — such as that inspired by the Nereis — engineers and scientists at LAMM and AFRL needed to first understand how these materials form in the Nereis worm, and how they ultimately behave in various environments. This understanding involved the development of a model that encompasses all different length scales from the atomic level, and is able to predict the material behavior. This model helps to fully understand the Nereis worm and its exceptional strength.

“Working with AFRL gave us the opportunity to pair our atomistic simulations with experiments,” said CEE research scientist Francisco Martin-Martinez. AFRL experimentally synthesized a hydrogel, a gel-like material made mostly of water, which is composed of recombinant Nvjp-1 protein responsible for the structural stability and impressive mechanical performance of the Nereis jaw. The hydrogel was used to test how the protein shrinks and changes behavior based on pH and ions in the environment.

The Nereis jaw is mostly made of organic matter, meaning it is a soft protein material with a consistency similar to gelatin. In spite of this, its strength, which has been reported to have a hardness ranging between 0.4 and 0.8 gigapascals (GPa), is similar to that of harder materials like human dentin. “It’s quite remarkable that this soft protein material, with a consistency akin to Jell-O, can be as strong as calcified minerals that are found in human dentin and harder materials such as bones,” Buehler said.

At MIT, the researchers looked at the makeup of the Nereis jaw on a molecular scale to see what makes the jaw so strong and adaptive. At this scale, the metal-coordinated crosslinks, the presence of metal in its molecular structure, provide a molecular network that makes the material stronger and at the same time make the molecular bond more dynamic, and ultimately able to respond to changing conditions. At the macroscopic scale, these dynamic metal-protein bonds result in an expansion/contraction behavior.

Combining the protein structural studies from AFRL with the molecular understanding from LAMM, Buehler, Martin-Martinez, CEE Research Scientist Zhao Qin, and former PhD student Chia-Ching Chou ’15, created a multiscale model that is able to predict the mechanical behavior of materials that contain this protein in various environments. “These atomistic simulations help us to visualize the atomic arrangements and molecular conformations that underlay the mechanical performance of these materials,” Martin-Martinez said.

Specifically, using this model the research team was able to design, test, and visualize how different molecular networks change and adapt to various pH levels, taking into account the biological and mechanical properties.

By looking at the molecular and biological makeup of a the Nereis virens and using the predictive model of the mechanical behavior of the resulting protein material, the LAMM researchers were able to more fully understand the protein material at different scales and provide a comprehensive understanding of how such protein materials form and behave in differing pH settings. This understanding guides new material designs for soft robots and sensors.

Identifying the link between environmental properties and movement in the material

The predictive model explained how the pH sensitive materials change shape and behavior, which the researchers used for designing new PH-changing geometric structures. Depending on the original geometric shape tested in the protein material and the properties surrounding it, the LAMM researchers found that the material either spirals or takes a Cypraea shell-like shape when the pH levels are changed. These are only some examples of the potential that this new material could have for developing soft robots, sensors, and autonomous structures.

Using the predictive model, the research team found that the material not only changes form, but it also reverts back to its original shape when the pH levels change. At the molecular level, histidine amino acids present in the protein bind strongly to the ions in the environment. This very local chemical reaction between amino acids and metal ions has an effect in the overall conformation of the protein at a larger scale. When environmental conditions change, the histidine-metal interactions change accordingly, which affect the protein conformation and in turn the material response.

“Changing the pH or changing the ions is like flipping a switch. You switch it on or off, depending on what environment you select, and the hydrogel expands or contracts” said Martin-Martinez.

LAMM found that at the molecular level, the structure of the protein material is strengthened when the environment contains zinc ions and certain pH levels. This creates more stable metal-coordinated crosslinks in the material’s molecular structure, which makes the molecules more dynamic and flexible.

This insight into the material’s design and its flexibility is extremely useful for environments with changing pH levels. Its response of changing its figure to changing acidity levels could be used for soft robotics. “Most soft robotics require power supply to drive the motion and to be controlled by complex electronic devices. Our work toward designing of multifunctional material may provide another pathway to directly control the material property and deformation without electronic devices,” said Qin.

By studying and modeling the molecular makeup and the behavior of the primary protein responsible for the mechanical properties ideal for Nereis jaw performance, the LAMM researchers are able to link environmental properties to movement in the material and have a more comprehensive understanding of the strength of the Nereis jaw.

Here’s link to and a citation for the paper,

Ion Effect and Metal-Coordinated Cross-Linking for Multiscale Design of Nereis Jaw Inspired Mechanomutable Materials by Chia-Ching Chou, Francisco J. Martin-Martinez, Zhao Qin, Patrick B. Dennis, Maneesh K. Gupta, Rajesh R. Naik, and Markus J. Buehler. ACS Nano, 2017, 11 (2), pp 1858–1868 DOI: 10.1021/acsnano.6b07878 Publication Date (Web): February 6, 2017

Copyright © 2017 American Chemical Society

This paper is behind a paywall.