Generative AI and Proteins

 Always an interest of mine, often mentioned here, approach should be interesting

Generative AI is dreaming up new proteins      by Laura Howes  in Cen.acs.org

April 10, 2023 | A version of this story appeared in Volume 101, Issue 12

In the past year, phrases like learned language models, diffusion, and hallucination have gained new meanings in popular culture as artificial intelligence has started taking over mundane tasks. Today, users can log on to an AI-powered chatbot and ask it to draft texts based on simple prompts. They can then use text-to-image services to create illustrations and new images to accompany the dreamed-up words.

But beyond these consumer applications, algorithmic approaches are helping researchers create a whole world of new proteins—proteins that could become vaccines, biologic therapies, materials, or tools for bioremediation.

A few years ago, C&EN chatted with David Baker of the University of Washington about a host of topics, including de novo protein design, which is designing new proteins from scratch rather than adjusting existing ones. Back then, he said he tried not to look too far into the future. Too much could change; too much was uncertain. That has never been truer.

De novo protein design has reached an inflection point, researchers say. AI-powered protein design is becoming very real and very usable, thanks to technological advances in the development of algorithms and the hardware that runs them.

Protein science itself was uniquely positioned to take advantage of these advances because of the enormous amounts of work carried out over the past 50 years to curate and annotate biological data.

“Every time there is a new method in computer vision or natural language processing, we are in a race to try to transfer it to biology,” says protein designer Noelia Ferruz at the Institute of Molecular Biology of Barcelona. “I guess it’s the perfect moment, because we’re seeing an AI revolution in every field.”

THE PROTEIN DESIGN PUZZLE

Proteins are hugely variable and incredibly specialized. They can form large, complicated complexes that mediate biological functions, or they can exist as small peptides that merely send signals from place to place. Proteins move and interact. They bind to and modify one another. They form part of the complex molecular dance we call life.

But proteins are also just molecules. They are composed of amino acid building blocks stuck together using amide linkages to create polymer chains. These polymers can curl up to build various shapes, chemical environments, forms, and functions, depending on where they sit and the interactions between the side chains in the molecules. For example, a hydrophobic portion might be found curled up inside the protein it’s part of or buried in a fatty membrane.  ... ' 

Re a Further Look at BioPhysics

How does life and physics fit together?    Just received in an Alumni mailing discussing,

THE PHYSICS OF Us

Physicists are studying how living matter works, and find that it breaks the standard rules and produces fascinating new phenomena.

Monday, December 5, 2022, By Susan Ahlborn. Illustrations by Marina Muun,   UPenn Omnia 

The James Webb telescope is showing us our universe in vibrant new detail. Some physicists, though, are looking in another direction: at us and other living matter here on Earth, from the cilia in lungs to the vasculature in leaves to the neurons in brains. What they’re finding is equally marvelous, and it’s challenging some of the current understanding of physics. 

Ultimately, they’re working to discover the rules that govern how matter lives and evolves, and their research may lead to better medicine, robotics based on biology, and an expanded understanding of the physical and biological world. 

How can an intelligent system arise from the collective dynamics of its basic components?

“We’re using physics principles to understand life and living matter,” says Eleni Katifori, Associate Professor of Physics and Astronomy, who studies vasculature in plants and animals. “But we are also using living matter as an inspiration to discover new physics, for asking the right questions or new questions.”

“Biology has already invented a lot of things. Living matter, from bacteria to leaves to humans, works in ways that physicists don’t understand, much less can duplicate,” adds Arnold Mathijssen, Assistant Professor of Physics and Astronomy. His goal is to unravel the physics of pathogens, design biomedical materials, and understand the collective functionality of living systems out of equilibrium. “It’s fundamental research. For example, how can an intelligent system arise from the collective dynamics of its basic components? It’s also directly relevant to our society, as in, what is the probability of SARS-CoV-2 transmission within a food supply chain?”

Leading the Way

The study of biophysics is not new; Luigi and Lucia Galvani were already investigating animal electricity in the late 1700s. In the last 20 years, though, technological advances have allowed researchers to see microscopic phenomena in living tissue with unprecedented detail, record simultaneously from thousands of neurons, and even track the large-scale behavior of ecosystems. All of these new methods produce vast amounts of quantitative data from which we can infer the laws of living matter. But it wasn’t until 2022 that the National Academies of Science, Engineering, and Medicine recognized biological physics as a separate field. 

Penn Arts & Sciences physicists have been studying living matter for decades, bringing Penn to the front of this area. Philip Nelson, Professor of Physics and Astronomy, wrote key books in the field, starting with Biological Physics: Energy, Information, Life in 2014. He’s been honored with the Emily Gray Award of the Biophysical Society for his “far-reaching and significant contributions.” Arjun Yodh, James M. Skinner Professor of Science, has received the Michael S. Feld Biophotonics Award of the Optical Society of America for his pioneering work in demonstrating and clinically translating biomedical optics. A.T. Charlie Johnson, Rebecca W. Bushnell Professor of Physics and Astronomy, is using biological molecules as chemical recognition elements in disease diagnosis, security, and environmental monitoring. Marija Drndic, Fay R. and Eugene L. Langberg Professor of Physics, explores mesoscopic and nanoscale structures, including the detection and analysis of DNA and microRNA.

In 2021, Penn Arts & Sciences and Penn Engineering made a unique investment in this interdisciplinary study with the new Center for Soft and Living Matter. Led by Director Andrea J. Liu, Hepburn Professor of Physics, and Associate Director Douglas J. Durian, Mary Amanda Wood Professor of Physics and Astronomy, the center brings together more than 60 faculty from the two schools. And Penn’s Computational Neuroscience Initiative, cofounded by Vijay Balasubramanian, Cathy and Marc Lasry Professor of Physics and Astronomy, involves researchers from Arts & Sciences, the Perelman School of Medicine, and Engineering. 

“If you look at a different scale or regime, new phenomena always pop up,” says Balasubramanian, a theoretical physicist who also holds a secondary appointment in neuroscience in the Perelman School of Medicine. “It’s the interactions between the components of living systems that make them so interesting, unlike, for example simple gases in a room. The brain contains a hundred billion interacting neurons. Molecules can talk to the whole organism, pheromones can change the behavior of entire colonies of organisms, stress can change gene expression. So, living systems interact across scales of organization unlike most physical systems that we are used to.”  .... ' 

Understanding of Cellular Metabolism

Home/News/Better Understanding of Cellular Metabolism With AI/Full Text

ACM TECHNEWS

Better Understanding of Cellular Metabolism With AI   By EPFL

October 6, 2022  Scientists at EPFL, the Swiss Federal Institute of Technology, Lausanne, have developed REKINDLE, a deep learning-based computational framework that replicates dynamic metabolism in cells.

"REKINDLE will allow the research community to reduce computational efforts in generating kinetic models by several orders of magnitude," says EPFL's Ljubisa Miskovic. "It will also help in postulating new hypotheses by integrating biochemical data in these models, elucidating experimental observations, and steering new therapeutic discoveries and biotechnology designs."

Researchers envision the framework optimizing the metabolic network of microbes to generate industrial-scale chemical compounds, as well as unifying the use of kinetic modeling in the scientific community. To that end, EPFL's Subham Choudhury said REKINDLE uses popular Python libraries to promote accessibility and ease of use. ... 

An EPFL framework that leverages deep learning paves the way for the efficient and accurate modeling of metabolic processes. ... 

full Article

Most Proteins Mapped with Deepmind

 New Digital Biology Advances with Deepmind

DeepMind found the structure of nearly every protein known to science

They’ll all be freely available

By Nicole Wetsman  Jul 28, 2022,

DeepMind is releasing a free expanded database with its predictions of the structure of nearly every protein known to science, the company, a subsidiary of Google parent Alphabet, announced today.

DeepMind transformed science in 2020 with its AlphaFold AI software, which produces highly accurate predictions of the structures of proteins — information that can help scientists understand how they work, which can help treat diseases and develop medications. It first started publicly releasing AlphaFold’s predictions last summer through a database built in collaboration with the European Molecular Biology Laboratory (EMBL). That initial set included 98 percent of all human proteins.

Now, the database is expanding to over 200 million structures, “covering almost every organism on Earth that has had its genome sequenced,” DeepMind said in a statement.

“You can think of it as covering the entire protein universe,” Demis Hassabis, CEO of DeepMind, said during a press briefing. “We’re at the beginning of a new era now in digital biology.”  ... '

Simulating 3D cells

 Simulating cell behavior with Nvidia GPUs

Researchers Simulate Behavior of Living 'Minimal Cell' in Three Dimensions

University of Illinois News Bureau, Diana Yates, January 20, 2022

Scientists at the University of Illinois Urbana-Champaign (UIUC) and California non-profit J. Craig Venter Institute (JCVI) have assembled a living "minimal cell" and a three-dimensional (3D) computer simulation that replicates its behavior. UIUC's Zaida Luthey-Schulten said minimal cells feature genomes stripped of nonessential genes, containing mainly those required to perform most life-defining functions. The model maps out the location and chemical properties of thousands of cellular elements in atomic-level 3D space. The JCVI team built the minimal cell the model was based on, then the UIUC researchers used Nvidia graphics processing units to run the simulation. Said Luthey-Schulten, "Our model opens a window on the inner workings of the cell, showing us how all of the components interact and change in response to internal and external cues."  .... ' 

DeepMind Releases Accurate Picture of Human Proteome

Was briefly involved in a discussion of protein folding structure prediction, so have an appreciation of the complexity the  Have been told this is a very big deal, and also future direction.  Good thing to watch, as I do.

DeepMind Releases Accurate Picture of the Human Proteome   By SciTechDaily,  July 23, 2021

DeepMind today announced its partnership with the European Molecular Biology Laboratory (EMBL), Europe's flagship laboratory for the life sciences, to make the most complete and accurate database yet of predicted protein structure models for the human proteome. This will cover all ~20,000 proteins expressed by the human genome, and the data will be freely and openly available to the scientific community. The database and artificial intelligence system provide structural biologists with powerful new tools for examining a protein's three-dimensional structure, and offer a treasure trove of data that could unlock future advances and herald a new era for AI-enabled biology.

AlphaFold's recognition in December 2020 by the organizers of the Critical Assessment of protein Structure Prediction (CASP) benchmark as a solution to the 50-year-old grand challenge of protein structure prediction was a stunning breakthrough for the field. The AlphaFold Protein Structure Database builds on this innovation and the discoveries of generations of scientists, from the early pioneers of protein imaging and crystallography, to the thousands of prediction specialists and structural biologists who've spent years experimenting with proteins since. The database dramatically expands the accumulated knowledge of protein structures, more than doubling the number of high-accuracy human protein structures available to researchers. Advancing the understanding of these building blocks of life, which underpin every biological process in every living thing, will help enable researchers across a huge variety of fields to accelerate their work.... 

The ability to predict a proteins shape computationally from its amino acid sequence is already helping scientists to achieve in months what previously took years. .... 

"...  The proteome is the entire set of proteins that is, or can be, expressed by a genome, cell, tissue, or organism at a certain time. It is the set of expressed proteins in a given type of cell or organism, at a given time, under defined conditions. Proteomics is the study of the proteome. ... "  WKP

From SciTechDaily

See further in ScienceMag: 

Protein structures. Public Database of AI-Predicted Protein Structures Could Transform Biology

By Robert F. Service

Pollination Robotics

An example I had not seen before.

Buzz Off, Bees. Pollination Robots Are Here.

By The Wall Street Journal, July 13, 2021

Farmers have long relied on insects, wind and even human workers to help pollinate their crops. Now, advances in artificial intelligence are helping some startups develop another way to pollinate plants: robots.

Across the globe, startups are testing robots to pollinate everything from blueberries to almonds. And in Australia, one company is so confident in robots' abilities that it will soon deploy a fleet of them to pollinate tomatoes in its greenhouses.

Pollination robots could give future farmers a significant advantage, increasing yield compared with using insects, such as bees, and the human workers who are sometimes needed to help with certain crops. Scientists are also concerned that insect populations are declining because of habitat loss, pesticide use, climate change and other factors, which would make pollination robots even more important.

From MIT News in WSJ

Smartphone Camera Can Illuminate Bacteria Causing Acne, Dental Plaque

Diagnosis Application.

Smartphone Camera Can Illuminate Bacteria Causing Acne, Dental Plaque

By University of Washington News, June 17, 2021

Researchers at the University of Washington have developed a technique to identify potentially harmful bacteria on skin and in the mouth using images taken by conventional smartphone cameras.

Their cost-effective approach — which could become the basis for home-based methods to assess basic skin and oral health — combines a smartphone-case modification with image-processing methods.

The researchers attached a three-dimensional printed ring featuring 10 LED black lights around the smartphone case's camera opening, which researcher Qinghua He said serve to "'excite' a class of bacteria-derived molecules called porphyrins, causing them to emit a red fluorescent signal that the smartphone camera can then pick up."

Researcher Ruikang Wang explained, "If you have bacteria producing a different byproduct that you want to detect, you can use the same image to look for it — something you can't do today with conventional imaging systems."

From University of Washington News ... 

Worlds Smallest Computer at Work

An unusual example of embedding computing using sensors.

Snails Carrying World's Smallest Computer Help Solve Mass Extinction Survivor Mystery

University of Michigan News Service

By Katherine McAlpine; Catharine June  University of Michigan,  June 15, 2021

University of Michigan (U-M) biologists and engineers used the world's smallest computer to learn how the South Pacific Society Islands tree snail Partula hyalina survived a mass extinction. Former U-M researcher Inhee Lee adapted the Michigan Micro Mote (M3) sensor to test the theory that P. hyalina survived the deliberate introduction of the predatory rosy wolf snail to its environment as attributable to its light-reflecting white shell. The researchers deployed 50 M3s in Tahiti, gluing some to rosy wolf snails while others were stuck on leaves harboring the P. hyalina, which rests in daytime. Lee wirelessly downloaded data from each M3 at the end of the day. Based on that data, the researchers suspect P. hyalina avoids predation because the rosy wolf snail will not venture far into its sunlight-heavy habitat.

Identifying Birds from Behind

Not banned for bias yet.   So at least we can continue to fine tune accuracy as needed and apply it to studies to help the avian world.

Birdwatching AI can recognise individual birds from behind
in NewScientist   By Michael Le Page

Artificial intelligence has been trained to recognise individual birds, which is more than we humans are capable of. The system is being developed for biologists studying wild animals, but could be adapted so that people can identify individual birds in their surroundings.

André Ferreira at the Center for Functional and Evolutionary Ecology in Montpellier, France, started the project while studying how individual sociable weavers contribute to their colonies. This is normally done by putting coloured tags on their legs and sitting by nests to watch them, which is very time-consuming. Ferreira tried filming the colonies instead, but often the coloured tags weren’t visible in the footage, so he and his colleagues turned to AI. ... "  

AI and Spatial Biology

A term I had not hear before,  though the work on protein folding might be included?   Also sounds somewhat like process mapping, applied to genes and protein activity.   With visual hints to bring in the human researchers to new discoveries?   The thought is intriguing. 

AI Tools Will Help Us Make the Most of Spatial Biology  in AITrends

In spatial biology, we can anticipate that applying AI to cell-by-cell maps of gene or protein activity will pave the way for significant discoveries. (David W. Craig, Ph.D.)
Contributed Commentary by David W. Craig, Ph.D. and Brooke Hjelm, Ph.D.

We have heard a lot about cellular and tissue spatial biology lately, and for good reason. Tissues are heterogeneous mixtures of cells; this is particularly important in disease. Cells are also the foundational unit of life, and they are shaped by those cells proximal to them. Not surprisingly, the research field sought to survey cellular and tissue heterogeneity. The last decade saw massive adoption of single-cell sequencing RNA. This approach requires that we disaggregate cells, leading to accounting and characterization of cell populations, but at the same time losing their spatial context such as their proximity to other cells or where they fit with traditional approaches such as histopathology.    .... "