Recommendable! Good news! Protein 3D analysis and design is taking off!
The possibilities are almost endless!
"... Yet in late 2020 ... Google’s company DeepMind and several university research teams had improved artificial intelligence (AI)-based structure prediction methods to the point where they had become highly accurate. ... Now, within less than six months and without any prior expertise in wood-degrading enzymes, [scientists] managed to design, produce and analyze stable variants of three versatile peroxidases whose original versions could not, in the past, have been produced in the lab. The scientists used AI-based 3D models as their starting point. They applied to these models an algorithm created in Fleishman’s lab called the Protein Repair One Stop Shop, or PROSS, which designs an altered protein on the computer to improve its properties on demand. ... This combined approach opens an enormous range of opportunities. “Millions of potentially valuable proteins that once could not have been accessed biochemically are now within reach for research and for use in biomedicine and chemistry,” ... the fact that 3D structures have been solved experimentally for less than 0.05 percent of the millions of natural proteins whose DNA sequence is known, and that about half of all proteins in nature cannot be effectively expressed and tested in the lab. ... Drug design is one area that could immediately benefit from this advance. For example, antibodies created in lab animals must be adapted to humans before they can be used in a clinical setting – a laborious process that involves crystallization and altering numerous regions of the animal molecule. The new advance is expected to make this and other antibody engineering processes much more efficient and effective. ...
Wood-degrading enzymes could, for example, be adapted for recycling tough agricultural waste. Instead of burning such waste or dissolving it with polluting chemicals, as is often done today, it may be possible to break it down, using versatile peroxidases, into sugars that can be fermented into biofuel. Farmers would then be able to perform recycling in small bioreactors. ...
The enzymes could also be designed to degrade environmental pollutants. In fact, [a scientist] has already shown that her improved enzymes can attack a particularly stubborn polluting dye. ..."
Wood-degrading enzymes could, for example, be adapted for recycling tough agricultural waste. Instead of burning such waste or dissolving it with polluting chemicals, as is often done today, it may be possible to break it down, using versatile peroxidases, into sugars that can be fermented into biofuel. Farmers would then be able to perform recycling in small bioreactors. ...
The enzymes could also be designed to degrade environmental pollutants. In fact, [a scientist] has already shown that her improved enzymes can attack a particularly stubborn polluting dye. ..."
From the abstract:
"White-rot fungi secrete a repertoire of high-redox potential oxidoreductases to efficiently decompose lignin. Of these enzymes, versatile peroxidases (VPs) are the most promiscuous biocatalysts. VPs are attractive enzymes for research and industrial use but their recombinant production is extremely challenging. To date, only a single VP has been structurally characterized and optimized for recombinant functional expression, stability, and activity. Computational enzyme optimization methods can be applied to many enzymes in parallel but they require accurate structures. Here, we demonstrate that model structures computed by deep-learning-based ab initio structure prediction methods are reliable starting points for one-shot PROSS [Protein Repair One Stop Shop] stability-design calculations. Four designed VPs encoding as many as 43 mutations relative to the wildtype enzymes are functionally expressed in yeast, whereas their wildtype parents are not. Three of these designs exhibit substantial and useful diversity in their reactivity profiles and tolerance to environmental conditions. The reliability of the new generation of structure predictors and design methods increases the scale and scope of computational enzyme optimization, enabling efficient discovery and exploitation of the functional diversity in natural enzyme families directly from genomic databases."
Stable and Functionally Diverse Versatile Peroxidases Designed Directly from Sequences (open access)
3D structural model of a versatile peroxidase enzyme generated by an AI-based structure predictor. Yellow dots are the sites of mutations suggested by PROSS for improving the enzyme’s stability
