Cutting-Edge Perspectives on Protein and Enzyme Engineering

A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Biomacromolecules: Proteins, Nucleic Acids and Carbohydrates".

Deadline for manuscript submissions: 31 May 2026 | Viewed by 3748

Special Issue Editors


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Guest Editor
1. Department of Biochemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
2. Key Laboratory of Systems Bioengineering of the Ministry of Education, Tianjin University, Tianjin 300072, China
Interests: protein materials; industrial enzyme; cell factories; protein production

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Guest Editor
Institute of Bioengineering, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China
Interests: enzyme evolution; machine learning; protein design; unnatural amino acids

Special Issue Information

Dear Colleagues,

Protein and enzyme engineering is the process of developing useful or valuable proteins such as protein materials, industrial enzymes, and therapy proteins. It includes technologies for engineering protein, producing protein, and purifying protein. Directed evolution has emerged as a powerful strategy to engineer various protein properties. In addition, machine learning and deep learning have developed rapidly and have been applied in protein engineering such as in protein function prediction, enzymes directed evolution, and so forth. Additionally, synthetic biology provides more maneuverability for protein design and synthesis. In the process of protein engineering, unnatural amino acids may be also included, via newer methods, such as expanded genetic code, which allows for encoding novel amino acids in genetic code. For protein production and purification, the construction of efficient cell factories, development of specific chassis cells, and separation tags are current research hotspots. This Special Issue is aimed at providing an overview of the most recent advances in the field of protein and enzyme engineering.

The journal will be accepting contributions covering potential topics including, but not limited to, the following:

  • protein material;
  • protein expression system;
  • protein separation and purification;
  • enzymes directed evolution;
  • therapy proteins engineering;
  • protein computational design;
  • machine learning used for protein engineering;
  • molecular dynamics simulations of proteins;
  • unnatural amino acids incorporation;
  • protein post-translation modification;
  • protein structures and mechanisms;

Dr. Haishan Qi
Dr. Haoran Yu
Guest Editors

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Keywords

  • protein engineering
  • protein material
  • enzyme evolution
  • therapy protein
  • protein expression
  • machine learning
  • unnatural amino acids

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Published Papers (2 papers)

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Research

16 pages, 3153 KB  
Article
Comparative Analysis of Lysis Buffers for Enhanced Proteomic and Glycoproteomic Profiling
by Tiantian Chu, Bo Meng, Xinyu Ji, Jinze Huang, Huanyue Liao, Rui Zhai, Xuping Shentu, Xiang Fang and Yang Zhao
Biomolecules 2026, 16(2), 288; https://doi.org/10.3390/biom16020288 - 11 Feb 2026
Viewed by 976
Abstract
Efficient and reproducible protein extraction is a critical prerequisite for high-quality proteomic and glycoproteomic analyses. In this study, four commonly used lysis buffers, sodium dodecyl sulfate (SDS), guanidine hydrochloride (GuHCl), urea (UA), and mammalian protein extraction reagent (MPER), were systematically evaluated within an [...] Read more.
Efficient and reproducible protein extraction is a critical prerequisite for high-quality proteomic and glycoproteomic analyses. In this study, four commonly used lysis buffers, sodium dodecyl sulfate (SDS), guanidine hydrochloride (GuHCl), urea (UA), and mammalian protein extraction reagent (MPER), were systematically evaluated within an integrated proteomic and N-glycoproteomic workflow. Using HeLa and HEK293T cells as model systems, we assessed buffer performance in terms of protein and intact N-glycopeptide identification depth, quantitative reproducibility, subcellular coverage, and glycan type distribution. Across both cell lines, SDS consistently achieved the deepest proteome and N-glycoproteome coverage, yielding the highest numbers of identified proteins, N-glycopeptides, glycoproteins, and glycosylation sites. Quantitative analysis demonstrated that SDS provided superior reproducibility, with approximately 85% of quantified proteins exhibiting coefficients of variation below 5%. Subcellular localization analysis at the global proteome level showed that SDS enabled more comprehensive extraction of proteins from multiple cellular compartments, including the nucleus, cytoplasm, mitochondria, and plasma membrane, indicating reduced extraction bias toward specific subcellular regions. Consistently, subcellular localization analysis of identified glycoproteins revealed enhanced coverage of membrane-associated compartments, particularly the plasma membrane, endoplasmic reticulum, Golgi apparatus, and lysosome. In addition, the analysis of glycan type classification for intact N-glycopeptides revealed that the SDS lysis buffer demonstrated the most comprehensive identification capability for glycopeptides with multiple glycosylation modifications in both cell lines. MPER and UA showed a highly consistent distribution across various glycosylation types, whereas the guanidine hydrochloride method was comparatively least effective. Overall, these results establish SDS as a robust lysis buffer for comprehensive, reproducible, and quantitatively stable proteomic and N-glycoproteomic analyses, providing practical guidance for buffer selection in quantitative glycosylation-focused studies. Full article
(This article belongs to the Special Issue Cutting-Edge Perspectives on Protein and Enzyme Engineering)
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13 pages, 1868 KB  
Article
Efficient Incorporation of DOPA into Proteins Free from Competition with Endogenous Translation Termination Machinery
by Youhui Yang, Yingchen Wang, Zhaoguan Wang and Hao Qi
Biomolecules 2025, 15(3), 382; https://doi.org/10.3390/biom15030382 - 6 Mar 2025
Cited by 2 | Viewed by 2089
Abstract
3,4-Dihydroxy-L-phenylalanine (DOPA) is a promising noncanonical amino acid (ncAA) that introduces novel catechol chemical features into proteins, expanding their functional potential. However, the most common approach to incorporating ncAAs into proteins relies on stop codon suppression, which is often limited by the competition [...] Read more.
3,4-Dihydroxy-L-phenylalanine (DOPA) is a promising noncanonical amino acid (ncAA) that introduces novel catechol chemical features into proteins, expanding their functional potential. However, the most common approach to incorporating ncAAs into proteins relies on stop codon suppression, which is often limited by the competition of endogenous translational termination machinery. Here, we employed a special in vitro protein expression system that facilitates the efficiency of DOPA incorporation into proteins by removing essential Class I peptide release factors through targeted degradation. In the absence of both RF1 and RF2, we successfully demonstrated DOPA incorporation at all three stop codons (TAG, TAA, and TGA). By optimizing the concentration of engineered DOPA-specific aminoacyl-tRNA synthetase (DOPARS), DOPA, and DNA template, we achieved a synthesis yield of 2.24 µg of sfGFP with 100% DOPA incorporation in a 20 μL reaction system. DOPARS exhibited a dissociation constant (Kd) of 11.7 μM for DOPA but showed no detectable binding to its native counterpart, tyrosine. Additionally, DOPA was successfully incorporated into a reverse transcriptase, which interfered with its activity. This system demonstrates a fast and efficient approach for precise DOPA incorporation into proteins, paving the way for advanced protein engineering applications. Full article
(This article belongs to the Special Issue Cutting-Edge Perspectives on Protein and Enzyme Engineering)
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