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Biomolecules
Special Issues
Harnessing Protein Design and Engineering for Therapeutic Applications
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Harnessing Protein Design and Engineering for Therapeutic Applications

A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Molecular Biophysics: Structure, Dynamics, and Function".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 10630

Special Issue Editors

Dr. Julia Shifman

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Guest Editor
Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
Interests: protein design and evolution; protein-protein interactions
Dr. Norman Metanis

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Guest Editor
Institute of Chemistry, Casali Center for Applied Chemistry, The Center for Nanoscience and Nanotechnology, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
Interests: chemical protein synthesis; peptide chemistry; selenoproteins; posttranslational protein modification
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Protein engineering, a cornerstone of molecular biology and biotechnology, plays a crucial role in tailoring proteins for diverse applications, particularly in therapeutics. This Special Issue explores the latest advancements in protein engineering methodologies aimed at optimizing protein properties for therapeutic interventions. This Special Issue presents studies that engineer therapeutic proteins and improve therapeutic protein stability, affinity, specificity, and pharmacokinetics. The contributions of this Special Issue highlight the multifaceted approaches employed, including rational design and directed evolution methods, augmented by computational techniques such as artificial intelligence. In addition, the field of chemical protein synthesis has reached a level in which large proteins, with different posttranslational modifications are now accessible, opening new horizons in chemical biology and medicinal chemistry. We welcome original manuscripts and reviews that shed light on protein engineering, protein synthesis, and design and its implications for therapeutic innovation.

Dr. Julia Shifman
Dr. Norman Metanis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomolecules is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • therapeutic peptides and proteins
  • protein design and engineering
  • chemical protein synthesis
  • chemoselective protein modification
  • posttranslational protein modification

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Published Papers (5 papers)

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Research

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18 pages, 7768 KiB  
Article
Rational Introduction of Electrostatic Interactions at Crystal Contacts to Enhance Protein Crystallization of an Ene Reductase
by Brigitte Walla, Anna Maslakova, Daniel Bischoff, Robert Janowski, Dierk Niessing and Dirk Weuster-Botz
Biomolecules 2025, 15(4), 467; https://doi.org/10.3390/biom15040467 - 22 Mar 2025
Viewed by 418
Abstract
Protein crystallization is an alternative to well-established but cost-intensive and time-consuming chromatography in biotechnological processes, with protein crystallization defined as an essential unit operation for isolating proteins, e.g., active pharmaceutical ingredients. Crystalline therapeutic proteins attract interest in formulation and delivery processes of biopharmaceuticals [...] Read more.
Protein crystallization is an alternative to well-established but cost-intensive and time-consuming chromatography in biotechnological processes, with protein crystallization defined as an essential unit operation for isolating proteins, e.g., active pharmaceutical ingredients. Crystalline therapeutic proteins attract interest in formulation and delivery processes of biopharmaceuticals due to the high purity, concentration, and stability of the crystalline state. Although improving protein crystallization is mainly achieved by high-throughput screening of crystallization conditions, recent studies have established a rational protein engineering approach to enhance crystallization for two homologous alcohol dehydrogenases from Lactobacillus brevis (LbADH) and Lactobacillus kefiri (LkADH). As generalizing crystallization processes across a wide range of target proteins remains challenging, this study takes a further step by applying the successful crystal contact engineering strategies for LbADH/LkADH to a non-homologous protein, an NADH-binding derivative of the Nostoc sp. PCC 1720 ene reductase (NspER1-L1,5). Here, the focus lies on introducing electrostatic interactions at crystal contacts, specifically between lysine and glutamic acid. Out of the nine tested NspER1-L1,5 mutants produced in E. coli, six crystallized, while four mutants revealed an increased propensity to crystallize in static µL-batch crystallization compared to the wild type: Q204K, Q350K, D352K, and T354K. The best-performing mutant Q204K was selected for upscaling, crystallizing faster than the wild type in a stirred batch crystallizer. Even when spiked with E. coli cell lysate, the mutant maintained increased crystallizability compared to the wild type. The results of this study highlight the potential of crystal contact engineering as a reliable tool for improving protein crystallization as an alternative to chromatography, paving the way for more efficient biotechnological downstream processing. Full article
(This article belongs to the Special Issue Harnessing Protein Design and Engineering for Therapeutic Applications)
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15 pages, 1665 KiB  
Article
Improving Circulation Half-Life of Therapeutic Candidate N-TIMP2 by Unfolded Peptide Extension
by Jason Shirian, Alexandra Hockla, Justyna J. Gleba, Matt Coban, Naama Rotenberg, Laura M. Strik, Aylin Alasonyalilar Demirer, Matt L. Pawlush, John A. Copland, Evette S. Radisky and Julia M. Shifman
Biomolecules 2024, 14(9), 1187; https://doi.org/10.3390/biom14091187 - 20 Sep 2024
Cited by 2 | Viewed by 1476
Abstract
Matrix metalloproteinases (MMPs) are significant drivers of many diseases, including cancer, and are established targets for drug development. Tissue inhibitors of metalloproteinases (TIMPs) are endogenous MMP inhibitors and are being pursued for the development of anti-MMP therapeutics. TIMPs possess many attractive properties for [...] Read more.
Matrix metalloproteinases (MMPs) are significant drivers of many diseases, including cancer, and are established targets for drug development. Tissue inhibitors of metalloproteinases (TIMPs) are endogenous MMP inhibitors and are being pursued for the development of anti-MMP therapeutics. TIMPs possess many attractive properties for drug candidates, such as complete MMP inhibition, low toxicity, low immunogenicity, and high tissue permeability. However, a major challenge with TIMPs is their rapid clearance from the bloodstream due to their small size. This study explores a method for extending the plasma half-life of the N-terminal domain of TIMP2 (N-TIMP2) by appending it with a long, intrinsically unfolded tail containing Pro, Ala, and Thr (PATylation). We designed and produced two PATylated N-TIMP2 constructs with tail lengths of 100 and 200 amino acids (N-TIMP2-PAT100 and N-TIMP2-PAT200). Both constructs demonstrated higher apparent molecular weights and retained high inhibitory activity against MMP-9. N-TIMP2-PAT200 significantly increased plasma half-life in mice compared to the non-PATylated variant, enhancing its therapeutic potential. PATylation offers distinct advantages for half-life extension, such as fully genetic encoding, monodispersion, and biodegradability. It can be easily applied to N-TIMP2 variants engineered for high affinity and selectivity toward individual MMPs, creating promising candidates for drug development against MMP-related diseases. Full article
(This article belongs to the Special Issue Harnessing Protein Design and Engineering for Therapeutic Applications)
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12 pages, 1886 KiB  
Article
Sequence-Based Viscosity Prediction for Rapid Antibody Engineering
by Bram Estes, Mani Jain, Lei Jia, John Whoriskey, Brian Bennett and Hailing Hsu
Biomolecules 2024, 14(6), 617; https://doi.org/10.3390/biom14060617 - 23 May 2024
Viewed by 2244
Abstract
Through machine learning, identifying correlations between amino acid sequences of antibodies and their observed characteristics, we developed an internal viscosity prediction model to empower the rapid engineering of therapeutic antibody candidates. For a highly viscous anti-IL-13 monoclonal antibody, we used a structure-based rational [...] Read more.
Through machine learning, identifying correlations between amino acid sequences of antibodies and their observed characteristics, we developed an internal viscosity prediction model to empower the rapid engineering of therapeutic antibody candidates. For a highly viscous anti-IL-13 monoclonal antibody, we used a structure-based rational design strategy to generate a list of variants that were hypothesized to mitigate viscosity. Our viscosity prediction tool was then used as a screen to cull virtually engineered variants with a probability of high viscosity while advancing those with a probability of low viscosity to production and testing. By combining the rational design engineering strategy with the in silico viscosity prediction screening step, we were able to efficiently improve the highly viscous anti-IL-13 candidate, successfully decreasing the viscosity at 150 mg/mL from 34 cP to 13 cP in a panel of 16 variants. Full article
(This article belongs to the Special Issue Harnessing Protein Design and Engineering for Therapeutic Applications)
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Review

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23 pages, 5499 KiB  
Review
Integrating Computational Design and Experimental Approaches for Next-Generation Biologics
by Ahrum Son, Jongham Park, Woojin Kim, Wonseok Lee, Yoonki Yoon, Jaeho Ji and Hyunsoo Kim
Biomolecules 2024, 14(9), 1073; https://doi.org/10.3390/biom14091073 - 27 Aug 2024
Cited by 3 | Viewed by 2943
Abstract
Therapeutic protein engineering has revolutionized medicine by enabling the development of highly specific and potent treatments for a wide range of diseases. This review examines recent advances in computational and experimental approaches for engineering improved protein therapeutics. Key areas of focus include antibody [...] Read more.
Therapeutic protein engineering has revolutionized medicine by enabling the development of highly specific and potent treatments for a wide range of diseases. This review examines recent advances in computational and experimental approaches for engineering improved protein therapeutics. Key areas of focus include antibody engineering, enzyme replacement therapies, and cytokine-based drugs. Computational methods like structure-based design, machine learning integration, and protein language models have dramatically enhanced our ability to predict protein properties and guide engineering efforts. Experimental techniques such as directed evolution and rational design approaches continue to evolve, with high-throughput methods accelerating the discovery process. Applications of these methods have led to breakthroughs in affinity maturation, bispecific antibodies, enzyme stability enhancement, and the development of conditionally active cytokines. Emerging approaches like intracellular protein delivery, stimulus-responsive proteins, and de novo designed therapeutic proteins offer exciting new possibilities. However, challenges remain in predicting in vivo behavior, scalable manufacturing, immunogenicity mitigation, and targeted delivery. Addressing these challenges will require continued integration of computational and experimental methods, as well as a deeper understanding of protein behavior in complex physiological environments. As the field advances, we can anticipate increasingly sophisticated and effective protein therapeutics for treating human diseases. Full article
(This article belongs to the Special Issue Harnessing Protein Design and Engineering for Therapeutic Applications)
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14 pages, 2435 KiB  
Review
Computational Methods to Predict Conformational B-Cell Epitopes
by M. Carroll, E. Rosenbaum and R. Viswanathan
Biomolecules 2024, 14(8), 983; https://doi.org/10.3390/biom14080983 - 10 Aug 2024
Cited by 1 | Viewed by 2649
Abstract
Accurate computational prediction of B-cell epitopes can greatly enhance biomedical research and rapidly advance efforts to develop therapeutics, monoclonal antibodies, vaccines, and immunodiagnostic reagents. Previous research efforts have primarily focused on the development of computational methods to predict linear epitopes rather than conformational [...] Read more.
Accurate computational prediction of B-cell epitopes can greatly enhance biomedical research and rapidly advance efforts to develop therapeutics, monoclonal antibodies, vaccines, and immunodiagnostic reagents. Previous research efforts have primarily focused on the development of computational methods to predict linear epitopes rather than conformational epitopes; however, the latter is much more biologically predominant. Several conformational B-cell epitope prediction methods have recently been published, but their predictive performances are weak. Here, we present a review of the latest computational methods and assess their performances on a diverse test set of 29 non-redundant unbound antigen structures. Our results demonstrate that ISPIPab performs better than most methods and compares favorably with other recent antigen-specific methods. Finally, we suggest new strategies and opportunities to improve computational predictions of conformational B-cell epitopes. Full article
(This article belongs to the Special Issue Harnessing Protein Design and Engineering for Therapeutic Applications)
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