We found 267 results for your search.

Evolutionary protein design

from the unnatural-selection dept.
vik points out an item about researchers at the Massachusetts General Hospital in Boston who have been developing proteins with specific binding affinity by pseudo-evolutionary processes, which appeared on Natureís Science Update site. Researchers Anthony Keefe and Jack Szostak have developed a method to indetify proteins to do a predetermined job from a vast number of random genes. The article makes an explicit connection to the potential of protein design as a pathway toward nanotechnology:
"It's 20 years since Eric Drexler, one of the prophets of nanotechnology, suggested that proteins could be engineered, and that molecular machines could be used in computing or medicine. But protein design has proved damnably difficult, because of our inability to predict how a linear sequence of amino acids will fold up into a three-dimensional protein. An evolutionary approach might sidestep this problem."

Drexler's 1981 paper in the Proceedings of the National Academy of Sciences USA, which first proposed the protein engineering pathway, is cited.

vik writes: "An evolutionary approach to protein design may be more fruitful than protein-folding predictions in producing either protein-based machinery or using custom proteins as templates for the catalysis of nanoscale components."

Alexis Courbet | Computational Design of Self Assembling Protein Nanomachines @ MSD Workshop 2023

Presenter Alexis Courbet, Baker Lab The conversion of chemical energy into mechanical work can be regarded as the most technologically transformative advances of modern science. Yet, even decades after Feynmanā€™s insights on molecular machines, the capability to perform useful work remains limited to the macroscale. The realization that natural molecular motors generate mechanical forces at… Continue reading Alexis Courbet | Computational Design of Self Assembling Protein Nanomachines @ MSD Workshop 2023

Simon DĆ¼rr | Designing stable Metalloproteins using Deep Learning

Presenter Simon DĆ¼rr, Ecole Polytechnique Federale der Lausanne (EPFL) Simon DĆ¼rr is a PhD student at Ecole Polytechnique Federale der Lausanne (EPFL) in Switzerland. He works on methods to improve protein engineering of metalloproteins using deep learning and molecular modeling. He is also known for his work improving accessibility of machine learning models via easy… Continue reading Simon DĆ¼rr | Designing stable Metalloproteins using Deep Learning

Xinru Wang, postdoc at University of Washington | Design of Receptor Binding Proteins

Presenter Xinru Wang, postdoc at University of Washington Iā€™m a highly motivated protein chemist specialized in structural biology. Summary: Xinru Wang, postdoc at University of Washington, stepped in for her colleage to describe the process of designing proteins that bind to receptors. She uses insulin as an example – one of the most useful and… Continue reading Xinru Wang, postdoc at University of Washington | Design of Receptor Binding Proteins

Linna An, postdoc at University of Washington | De Novo Design of Small Molecule Binding Proteins

Presenter Linna An, postdoc at University of Washington I design protein binders for small molecules and peptide binders for protein complexes. Summary: Linna An, postdoc at University of Washington, describes the process of designing small molecules that bind to proteins. The canonical method involved generating scaffolds, designing the ligand docking, designing docks, designing filters, then… Continue reading Linna An, postdoc at University of Washington | De Novo Design of Small Molecule Binding Proteins

Designing novel protein backbones through digital evolution

Computational recombination of small elements of structure from known protein structures generates a vast library of designs that balance protein stability with the potential for new functions and novel interactions.

Rational design of protein architectures not found in nature

Computational design of proteins satisfying predetermined geometric constraints produced stable proteins with the designed structure that are not found in nature.

Large, open protein cages designed and built

Design principles have been developed and tested to construct novel synthetic protein monomers that can self-assemble into large, open protein cages for potential use in vaccines and drug delivery.

Computational design of protein-small molecule interactions

A major advance in the computational design of proteins that bind tightly to specific small molecules will facilitate several technologies, possibly including the development of atomically precise manufacturing.

Nanotechnology milestone: general method for designing stable proteins

Five proteins were designed from scratch and found to fold into stable proteins as designed, proving the ability to provide ideal, robust building blocks for artificial protein structures.

0
    0
    Your Cart
    Your cart is emptyReturn to Shop