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
@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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RT @OxfordJournals: We are recruiting: @ProtEngDesSel is looking for an Editor-in-Chief to lead the journal into the future! If you’re a le….
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Congratulations to @NobelPrize winner David Baker for his groundbreaking contributions to protein design! Learn more about his research in the webinar linked below:
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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10/.Bruce Donald and coworkers (@dukecompsci) introduce DexDesign, an extension of their OSPREY #ProteinDesign software that enables the creation of D-peptide inhibitors.
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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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9/.@GuillemCasaF and @silviaosu from @CompBioLab_IQCC (@IQCCUdG) present a web server for the computation of shortest path maps for any enzyme of interest.
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Abstract. SPMweb is the online webserver of the Shortest Path Map (SPM) tool for identifying the key conformationally-relevant positions of a given enzyme
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8/.@ProteinMagnus and coworkers (@MolBiolAU) review the design of functional intrinsically disordered proteins (IDPs).
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Abstract. Many proteins do not fold into a fixed three-dimensional structure, but rather function in a highly disordered state. These intrinsically disorde
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7/.@ChrisWellsWood and colleagues (@SBSatEd) report the Three-dimensional Inference Method for Efficient Design (TIMED), a convolutional #NeuralNetwork-based algorithm for #InverseFolding.
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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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6/.Haiyan Liu and colleagues describe recent advances in #DeepLearning for sequence design on a given protein backbone, also known as #InverseFolding.
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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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5/.@JuliaRuRogers, Gergő Nikolényi and @MoAlQuraishi (@ColumbiaSysBio) review the growing ecosystem of deep learning methods for modelling protein–protein interactions.
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Abstract. Numerous cellular functions rely on protein–protein interactions. Efforts to comprehensively characterize them remain challenged however by the d
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4/.Opuu and Simonson (@Polytechnique) review the application of computational design methods to noncanonical amino acids for #GeneticCodeExpansion.
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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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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:.
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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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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.
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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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@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.
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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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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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Computational methods for protein design
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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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RT @ProtEngDesSel: New article alert!. @CarlDenard et al. present a series of YESS plasmids that provide a robust platform to observe and q….
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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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RT @IQCCUdG: Check our latest work about shortest path method (SPM) webserver for computational enzyme design by @GuillemCasaF J Casadevall….
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Abstract. SPMweb is the online webserver of the Shortest Path Map (SPM) tool for identifying the key conformationally-relevant positions of a given enzyme
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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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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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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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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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