Protein Engineering Design & Selection

Papers
(The median citation count of Protein Engineering Design & Selection is 2. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-05-01 to 2025-05-01.)
ArticleCitations
Enhancing the Thermostability and solubility of a single-domain catalytic antibody37
Improving plastic degrading enzymes via directed evolution27
Yeast surface display-based identification of ACE2 mutations that modulate SARS-CoV-2 spike binding across multiple mammalian species23
Comprehensive mapping of SARS-CoV-2 peptide epitopes for development of a highly sensitive serological test for total and neutralizing antibodies20
Cyan fluorescent proteins derived from mNeonGreen18
Yeast biopanning against site-specific phosphorylations in tau11
Enzyme design pioneer Steve Mayo: I was trying to capture the fundamental physics of the problem as a way to elucidate mechanisms11
Design of functional intrinsically disordered proteins10
Engineering enzyme activity using an expanded amino acid alphabet9
Engineering of a lysosomal-targeted GAA enzyme8
Sequence-developability mapping of affibody and fibronectin paratopes via library-scale variant characterization7
Antibody-mediated delivery of CRISPR-Cas9 ribonucleoproteins in human cells7
Modifying pH-sensitive PCSK9/LDLR interactions as a strategy to enhance hepatic cell uptake of low-density lipoprotein cholesterol (LDL-C)6
abYpap: improvements to the prediction of antibody VH/VL packing using gradient boosted regression6
Correction to: Protease-stable DARPins as promising oral therapeutics6
Analysis of conformational stability of interacting residues in protein binding interfaces6
Engineering of a phosphotriesterase with improved stability and enhanced activity for detoxification of the pesticide metabolite malaoxon5
Physics-based approach to extend a de novo TIM barrel with rationally designed helix-loop-helix motifs5
An easy-to-use high-throughput selection system for the discovery of recombinant protein binders from alternative scaffold libraries5
Effect of alanine versus serine at position 88 of human transthyretin mutants on the protein stability5
Structure-based engineering of minimal proline dehydrogenase domains for inhibitor discovery4
Stabilization of the SARS-CoV-2 receptor binding domain by protein core redesign and deep mutational scanning4
An engineered NKp46 antibody for construction of multi-specific NK cell engagers4
Strategies for enriching and characterizing proteins with inhibitory properties on the yeast surface4
Sequence-activity mapping via depletion reveals striking mutational tolerance and elucidates functional motifs in Tur1a antimicrobial peptide4
A protein engineering approach toward understanding FKBP51 conformational dynamics and mechanisms of ligand binding4
CDRxAbs: antibody small-molecule conjugates with computationally designed target-binding synergy4
Tuning ProteinMPNN to reduce protein visibility via MHC Class I through direct preference optimization3
Optimized single-cell gates for yeast display screening3
Enhancing the activity of a monomeric alcohol dehydrogenase for site-specific applications by site-directed mutagenesis3
Growing ecosystem of deep learning methods for modeling protein–protein interactions3
Contributions from ClpS surface residues in modulating N-terminal peptide binding and their implications for NAAB development3
Reducing substrate inhibition of malate dehydrogenase from Geobacillus stearothermophilus by C-terminal truncation3
Data-driven enzyme engineering to identify function-enhancing enzymes2
A multivalent antibody assembled from different building blocks using tag/catcher systems: a case study2
Engineered FHA domains can bind to a variety of Phosphothreonine-containing peptides2
Benchmarking TriadAb using targets from the second antibody modeling assessment2
Supercharged Phosphotriesterase for improved Paraoxon activity2
TIMED-Design: flexible and accessible protein sequence design with convolutional neural networks2
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