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PEDS: Protein Engineering, Design & Selection Profile
PEDS: Protein Engineering, Design & Selection

@ProtEngDesSel

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PEDS is an Oxford University Press journal publishing the latest research in #proteinengineering, #proteindesign and #proteinscience.

Joined January 2020
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@ProtEngDesSel
PEDS: Protein Engineering, Design & Selection
1 year
@ProtEngDesSel is excited to share its latest article collection on "Computational Methods for #ProteinDesign". Free to read until Sept. 30, 2024:
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Protein Engineering, Design and Selection is pleased to publish a special collection of articles on computational methods for protein design. Computational
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@OxfordJournals
Oxford Journals
1 year
We are recruiting: @ProtEngDesSel is looking for an Editor-in-Chief to lead the journal into the future! If you’re a leader in protein engineering with a strong vision for the field, we want to hear from you. View more details and apply: https://t.co/wqYwxOvFhQ #JournalEditor
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@ProtEngDesSel
PEDS: Protein Engineering, Design & Selection
1 year
Congratulations to @NobelPrize winner David Baker for his groundbreaking contributions to protein design! Learn more about his research in the webinar linked below: https://t.co/jzoixybvZB.
@NobelPrize
The Nobel Prize
1 year
BREAKING NEWS The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Chemistry with one half to David Baker “for computational protein design” and the other half jointly to Demis Hassabis and John M. Jumper “for protein structure prediction.”
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@ProtEngDesSel
PEDS: Protein Engineering, Design & Selection
1 year
10/ Bruce Donald and coworkers (@dukecompsci) introduce DexDesign, an extension of their OSPREY #ProteinDesign software that enables the creation of D-peptide inhibitors. https://t.co/hYSCfDKNRh
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Abstract. With over 270 unique occurrences in the human genome, peptide-recognizing PDZ domains play a central role in modulating polarization, signaling,
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@ProtEngDesSel
PEDS: Protein Engineering, Design & Selection
1 year
7/ @ChrisWellsWood and colleagues (@SBSatEd) report the Three-dimensional Inference Method for Efficient Design (TIMED), a convolutional #NeuralNetwork-based algorithm for #InverseFolding. https://t.co/asXOftjlll
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Abstract. Sequence design is a crucial step in the process of designing or engineering proteins. Traditionally, physics-based methods have been used to sol
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@ProtEngDesSel
PEDS: Protein Engineering, Design & Selection
1 year
6/ Haiyan Liu and colleagues describe recent advances in #DeepLearning for sequence design on a given protein backbone, also known as #InverseFolding. https://t.co/ftK2XBaAi3
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Abstract. Deep learning methods for protein sequence design focus on modeling and sampling the many- dimensional distribution of amino acid sequences condi
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@ProtEngDesSel
PEDS: Protein Engineering, Design & Selection
1 year
5/ @JuliaRuRogers, Gergő Nikolényi and @MoAlQuraishi (@ColumbiaSysBio) review the growing ecosystem of deep learning methods for modelling protein–protein interactions. https://t.co/gX8atRQY2p
academic.oup.com
Abstract. Numerous cellular functions rely on protein–protein interactions. Efforts to comprehensively characterize them remain challenged however by the d
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@ProtEngDesSel
PEDS: Protein Engineering, Design & Selection
1 year
4/ Opuu and Simonson (@Polytechnique) review the application of computational design methods to noncanonical amino acids for #GeneticCodeExpansion. https://t.co/THIFZqd16a
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Abstract. Enzyme design is an important application of computational protein design (CPD). It can benefit enormously from the additional chemistries provid
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@ProtEngDesSel
PEDS: Protein Engineering, Design & Selection
1 year
3/ @KevinKaichuang and colleagues (@MSFTResearch) explore a multimodal approach for inverse folding by training a masked inverse folding protein language model parameterised as a structured graph neural network: https://t.co/RF7ExpaBSQ
academic.oup.com
Abstract. Self-supervised pretraining on protein sequences has led to state-of-the art performance on protein function and fitness prediction. However, seq
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@ProtEngDesSel
PEDS: Protein Engineering, Design & Selection
1 year
2/ Lee et al. (@protabit) present the Triad Antibody Homology Modelling (TriadAb) package, which predicts the structure of heavy and light chain sequences of an #antibody Fv domain using template-based modelling. https://t.co/YT1xBjhs6g
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Abstract. Computational modeling and design of antibodies has become an integral part of today’s research and development in antibody therapeutics. Here we
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@ProtEngDesSel
PEDS: Protein Engineering, Design & Selection
1 year
@ferruz_noelia @_amelie_rocks 1/ @BirteHoecker et al. use a physics-based approach to insert structural elements on a de-novo-designed TIM barrel: Physics-based approach to extend a de novo TIM barrel with rationally designed helix-loop-helix motifs https://t.co/tiGpsPqklH
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Abstract. Computational protein design promises the ability to build tailor-made proteins de novo. While a range of de novo proteins have been constructed
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@ProtEngDesSel
PEDS: Protein Engineering, Design & Selection
1 year
This collection provides a broad view of the current diversity and progress within the field of #ProteinDesign, spanning classic modelling approaches and newer machine learning methods. Check out the editorial by @ferruz_noelia and @_amelie_rocks:
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Computational protein design (CPD) aims to create proteins with novel functions or properties not found in nature. While CPD has a long history (Dahiyat an
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@ProtEngDesSel
PEDS: Protein Engineering, Design & Selection
2 years
New article alert! @CarlDenard et al. present a series of YESS plasmids that provide a robust platform to observe and quantify PTM-enzyme activity in yeast. Modular and integrative activity reporters enhance biochemical studies in the yeast ER
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Abstract. The yeast endoplasmic reticulum sequestration and screening (YESS) system is a broadly applicable platform to perform high-throughput biochemical
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@ProtEngDesSel
PEDS: Protein Engineering, Design & Selection
2 years
New article alert! @CarlDenard et al. present a series of YESS plasmids that provide a robust platform to observe and quantify PTM-enzyme activity in yeast. Modular and integrative activity reporters enhance biochemical studies in the yeast ER
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academic.oup.com
Abstract. The yeast endoplasmic reticulum sequestration and screening (YESS) system is a broadly applicable platform to perform high-throughput biochemical
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@ProtEngDesSel
PEDS: Protein Engineering, Design & Selection
2 years
New article alert! In this review, @Jackson_Lab identify knowledge gaps and current challenges, and highlight recent studies related to the directed evolution of plastic-degrading enzymes. Improving plastic degrading enzymes via directed evolution
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Abstract. Plastic degrading enzymes have immense potential for use in industrial applications. Protein engineering efforts over the last decade have result
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@ProtEngDesSel
PEDS: Protein Engineering, Design & Selection
2 years
New article from our "Computational methods for protein design" special collection! DexDesign: an OSPREY-based algorithm for designing de novo D-peptide inhibitors
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academic.oup.com
Abstract. With over 270 unique occurrences in the human genome, peptide-recognizing PDZ domains play a central role in modulating polarization, signaling,
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