1
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Tripp A, Braun M, Wieser F, Oberdorfer G, Lechner H. Click, Compute, Create: A Review of Web-based Tools for Enzyme Engineering. Chembiochem 2024:e202400092. [PMID: 38634409 DOI: 10.1002/cbic.202400092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 04/14/2024] [Accepted: 04/15/2024] [Indexed: 04/19/2024]
Abstract
Enzyme engineering, though pivotal across various biotechnological domains, is often plagued by its time-consuming and labor-intensive nature. This review aims to offer an overview of supportive in silico methodologies for this demanding endeavor. Starting from methods to predict protein structures, to classification of their activity and even the discovery of new enzymes we continue with describing tools used to increase thermostability and production yields of selected targets. Subsequently, we discuss computational methods to modulate both, the activity as well as selectivity of enzymes. Last, we present recent approaches based on cutting-edge machine learning methods to redesign enzymes. With exception of the last chapter, there is a strong focus on methods easily accessible via web-interfaces or simple Python-scripts, therefore readily useable for a diverse and broad community.
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Affiliation(s)
- Adrian Tripp
- Institute of Biochemistry, Graz University of Technology, Petersgasse 12/2, 8010, Graz, Austria
| | - Markus Braun
- Institute of Biochemistry, Graz University of Technology, Petersgasse 12/2, 8010, Graz, Austria
| | - Florian Wieser
- Institute of Biochemistry, Graz University of Technology, Petersgasse 12/2, 8010, Graz, Austria
| | - Gustav Oberdorfer
- Institute of Biochemistry, Graz University of Technology, Petersgasse 12/2, 8010, Graz, Austria
- BioTechMed, Graz, Austria
| | - Horst Lechner
- Institute of Biochemistry, Graz University of Technology, Petersgasse 12/2, 8010, Graz, Austria
- BioTechMed, Graz, Austria
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2
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Badaczewska-Dawid AE, Kuriata A, Pintado-Grima C, Garcia-Pardo J, Burdukiewicz M, Iglesias V, Kmiecik S, Ventura S. A3D Model Organism Database (A3D-MODB): a database for proteome aggregation predictions in model organisms. Nucleic Acids Res 2024; 52:D360-D367. [PMID: 37897355 PMCID: PMC10767922 DOI: 10.1093/nar/gkad942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 09/27/2023] [Accepted: 10/11/2023] [Indexed: 10/30/2023] Open
Abstract
Protein aggregation has been associated with aging and different pathologies and represents a bottleneck in the industrial production of biotherapeutics. Numerous past studies performed in Escherichia coli and other model organisms have allowed to dissect the biophysical principles underlying this process. This knowledge fuelled the development of computational tools, such as Aggrescan 3D (A3D) to forecast and re-design protein aggregation. Here, we present the A3D Model Organism Database (A3D-MODB) http://biocomp.chem.uw.edu.pl/A3D2/MODB, a comprehensive resource for the study of structural protein aggregation in the proteomes of 12 key model species spanning distant biological clades. In addition to A3D predictions, this resource incorporates information useful for contextualizing protein aggregation, including membrane protein topology and structural model confidence, as an indirect reporter of protein disorder. The database is openly accessible without any need for registration. We foresee A3D-MOBD evolving into a central hub for conducting comprehensive, multi-species analyses of protein aggregation, fostering the development of protein-based solutions for medical, biotechnological, agricultural and industrial applications.
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Affiliation(s)
| | - Aleksander Kuriata
- Biological and Chemical Research Center, Faculty of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
| | - Carlos Pintado-Grima
- Institut de Biotecnologia i de Biomedicina (IBB) and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain
| | - Javier Garcia-Pardo
- Institut de Biotecnologia i de Biomedicina (IBB) and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain
| | - Michał Burdukiewicz
- Institut de Biotecnologia i de Biomedicina (IBB) and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain
- Clinical Research Centre, Medical University of Białystok, Kilińskiego 1, 15-369, Białystok, Poland
| | - Valentín Iglesias
- Institut de Biotecnologia i de Biomedicina (IBB) and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain
| | - Sebastian Kmiecik
- Biological and Chemical Research Center, Faculty of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
| | - Salvador Ventura
- Institut de Biotecnologia i de Biomedicina (IBB) and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain
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3
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Garfagnini T, Bemporad F, Harries D, Chiti F, Friedler A. Amyloid Aggregation Is Potently Slowed Down by Osmolytes Due to Compaction of Partially Folded State. J Mol Biol 2023; 435:168281. [PMID: 37734431 DOI: 10.1016/j.jmb.2023.168281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Revised: 07/30/2023] [Accepted: 09/11/2023] [Indexed: 09/23/2023]
Abstract
Amyloid aggregation is a key process in amyloidoses and neurodegenerative diseases. Hydrophobicity is one of the major driving forces for this type of aggregation, as an increase in hydrophobicity generally correlates with aggregation susceptibility and rate. However, most experimental systems in vitro and prediction tools in silico neglect the contribution of protective osmolytes present in the cellular environment. Here, we assessed the role of hydrophobic mutations in amyloid aggregation in the presence of osmolytes. To achieve this goal, we used the model protein human muscle acylphosphatase (mAcP) and mutations to leucine that increased its hydrophobicity without affecting its thermodynamic stability. Osmolytes significantly slowed down the aggregation kinetics of the hydrophobic mutants, with an effect larger than that observed on the wild-type protein. The effect increased as the mutation site was closer to the middle of the protein sequence. We propose that the preferential exclusion of osmolytes from mutation-introduced hydrophobic side-chains quenches the aggregation potential of the ensemble of partially unfolded states of the protein by inducing its compaction and inhibiting its self-assembly with other proteins. Our results suggest that including the effect of the cellular environment in experimental setups and predictive softwares, for both mechanistic studies and drug design, is essential in order to obtain a more complete combination of the driving forces of amyloid aggregation.
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Affiliation(s)
- Tommaso Garfagnini
- Institute of Chemistry, The Hebrew University of Jerusalem, Edmond J. Safra Campus at Givat Ram, Jerusalem 9190401, Israel
| | - Francesco Bemporad
- Department of Experimental and Clinical Biomedical Sciences, University of Florence, Florence 50134, Italy
| | - Daniel Harries
- Institute of Chemistry, The Hebrew University of Jerusalem, Edmond J. Safra Campus at Givat Ram, Jerusalem 9190401, Israel; The Fritz Haber Research Center, The Hebrew University of Jerusalem, Edmond J. Safra Campus at Givat Ram, Jerusalem 9190401, Israel
| | - Fabrizio Chiti
- Department of Experimental and Clinical Biomedical Sciences, University of Florence, Florence 50134, Italy
| | - Assaf Friedler
- Institute of Chemistry, The Hebrew University of Jerusalem, Edmond J. Safra Campus at Givat Ram, Jerusalem 9190401, Israel.
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4
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Ejaz S, Paracha RZ, Ejaz S, Jamal Z. Antibody designing against IIIabc junction (JIIIabc) of HCV IRES through affinity maturation; RNA-Antibody docking and interaction analysis. PLoS One 2023; 18:e0291213. [PMID: 37682810 PMCID: PMC10490861 DOI: 10.1371/journal.pone.0291213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 08/24/2023] [Indexed: 09/10/2023] Open
Abstract
Hepatitis C virus is a single-stranded RNA based virus which can cause chronic HCV and hepatocellular carcinoma. HCV genotype 3a has relatively higher rate of fibrosis progression, prevalence of steatosis and incidence of HCC. Despite HCVs variation in genomic sequence, the 5' untranslated region containing internal ribosome entry site (IRES) is highly conserved among all genotypes. It is responsible for translation and initiation of the viral protein. In present study, IRES was targeted by designing variants of reported antigen binding fragment (Fab) through affinity maturation approach. Affinity maturation strategy allowed the rational antibody designing with better biophysical properties and antibody-antigen binding interactions. Complementarity determining regions of reported Fab (wild type) were assessed and docked with IRES. Best generated model of Fab was selected and subjected to alanine scanning Three sets of insilico mutations for variants (V) designing were selected; single (1-71), double (a-j) and triple (I-X). Redocking of IRES-Fab variants consequently enabled the discovery of three variants exhibiting better docking score as compared to the wild type Fab. V1, V39 and V4 exhibited docking scores of -446.51, -446.52 and-446.29 kcal/mol respectively which is better as compared to the wild type Fab that exhibited the docking score of -351.23 kcal/mol. Variants exhibiting better docking score were screened for aggregation propensity by assessing the aggregation prone regions in Fab structure. Total A3D scores of wild type Fab, V1, V4 and V39 were predicted as -315.325, -312.727, -316.967 and -317.545 respectively. It is manifested that solubility of V4 and V39 is comparable to wild type Fab. In future, development and invitro assessment of these promising Fab HCV3 variants is aimed.
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Affiliation(s)
- Saima Ejaz
- School of Interdisciplinary Engineering & Sciences (SINES), National University of Sciences and Technology, Islamabad, Pakistan
| | - Rehan Zafar Paracha
- School of Interdisciplinary Engineering & Sciences (SINES), National University of Sciences and Technology, Islamabad, Pakistan
| | - Sadaf Ejaz
- Department of Biosciences, COMSATS University Islamabad, Pakistan
| | - Zunera Jamal
- Department of Virology, National Institutes of Health, Islamabad, Pakistan
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5
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Bauer J, Rajagopal N, Gupta P, Gupta P, Nixon AE, Kumar S. How can we discover developable antibody-based biotherapeutics? Front Mol Biosci 2023; 10:1221626. [PMID: 37609373 PMCID: PMC10441133 DOI: 10.3389/fmolb.2023.1221626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 07/10/2023] [Indexed: 08/24/2023] Open
Abstract
Antibody-based biotherapeutics have emerged as a successful class of pharmaceuticals despite significant challenges and risks to their discovery and development. This review discusses the most frequently encountered hurdles in the research and development (R&D) of antibody-based biotherapeutics and proposes a conceptual framework called biopharmaceutical informatics. Our vision advocates for the syncretic use of computation and experimentation at every stage of biologic drug discovery, considering developability (manufacturability, safety, efficacy, and pharmacology) of potential drug candidates from the earliest stages of the drug discovery phase. The computational advances in recent years allow for more precise formulation of disease concepts, rapid identification, and validation of targets suitable for therapeutic intervention and discovery of potential biotherapeutics that can agonize or antagonize them. Furthermore, computational methods for de novo and epitope-specific antibody design are increasingly being developed, opening novel computationally driven opportunities for biologic drug discovery. Here, we review the opportunities and limitations of emerging computational approaches for optimizing antigens to generate robust immune responses, in silico generation of antibody sequences, discovery of potential antibody binders through virtual screening, assessment of hits, identification of lead drug candidates and their affinity maturation, and optimization for developability. The adoption of biopharmaceutical informatics across all aspects of drug discovery and development cycles should help bring affordable and effective biotherapeutics to patients more quickly.
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Affiliation(s)
- Joschka Bauer
- Early Stage Pharmaceutical Development Biologicals, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach/Riss, Germany
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
| | - Nandhini Rajagopal
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| | - Priyanka Gupta
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| | - Pankaj Gupta
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| | - Andrew E. Nixon
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| | - Sandeep Kumar
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
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6
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Rosace A, Bennett A, Oeller M, Mortensen MM, Sakhnini L, Lorenzen N, Poulsen C, Sormanni P. Automated optimisation of solubility and conformational stability of antibodies and proteins. Nat Commun 2023; 14:1937. [PMID: 37024501 PMCID: PMC10079162 DOI: 10.1038/s41467-023-37668-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Accepted: 03/24/2023] [Indexed: 04/08/2023] Open
Abstract
Biologics, such as antibodies and enzymes, are crucial in research, biotechnology, diagnostics, and therapeutics. Often, biologics with suitable functionality are discovered, but their development is impeded by developability issues. Stability and solubility are key biophysical traits underpinning developability potential, as they determine aggregation, correlate with production yield and poly-specificity, and are essential to access parenteral and oral delivery. While advances for the optimisation of individual traits have been made, the co-optimization of multiple traits remains highly problematic and time-consuming, as mutations that improve one property often negatively impact others. In this work, we introduce a fully automated computational strategy for the simultaneous optimisation of conformational stability and solubility, which we experimentally validate on six antibodies, including two approved therapeutics. Our results on 42 designs demonstrate that the computational procedure is highly effective at improving developability potential, while not affecting antigen-binding. We make the method available as a webserver at www-cohsoftware.ch.cam.ac.uk.
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Affiliation(s)
- Angelo Rosace
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK
- Master in Bioinformatics for Health Sciences, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain
- Institute for Research in Biomedicine (IRB), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain
| | - Anja Bennett
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK
- Department of Mammalian Expression, Global Research Technologies, Novo Nordisk A/S, Novo Nordisk Park 1, 2760, Måløv, Denmark
- BRIC, Faculty of Health and Medical Sciences, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Marc Oeller
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK
| | - Mie M Mortensen
- Department of Purification Technologies, Global Research Technologies, Novo Nordisk A/S, Novo Nordisk Park 1, 2760, Måløv, Denmark
- Faculty of Engineering and Science, Department of Biotechnology, Chemistry and Environmental Engineering, University of Aalborg, Fredrik Bajers Vej 7H, 9220, Aalborg, Denmark
| | - Laila Sakhnini
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK
- Department of Biophysics and Injectable Formulation 2, Global Research Technologies, Novo Nordisk A/S, Måløv, 2760, Denmark
| | - Nikolai Lorenzen
- Department of Biophysics and Injectable Formulation 2, Global Research Technologies, Novo Nordisk A/S, Måløv, 2760, Denmark
| | - Christian Poulsen
- Department of Mammalian Expression, Global Research Technologies, Novo Nordisk A/S, Novo Nordisk Park 1, 2760, Måløv, Denmark
| | - Pietro Sormanni
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK.
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7
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Shin J, Raissi S, Phelan P, Bullock PA. Rational design of a Nivolumab-based ANTI-PD-1 single chain variable fragment that blocks the interaction between PD-1 expressed on T-CELLS and PD-L1 ON CHO cells. Protein Expr Purif 2023; 202:106196. [PMID: 36280166 DOI: 10.1016/j.pep.2022.106196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 10/13/2022] [Accepted: 10/16/2022] [Indexed: 11/05/2022]
Abstract
Antibodies that block the interaction between PD-1 expressing T-cells and cancer cells expressing PD-L1 play a central role in contemporary immunotherapy regimes [1-3]. We previously reported the isolation of a single chain variable fragment (scFv) of the monoclonal anti-PD-1 antibody Nivolumab, that binds to purified PD-1 and blocked its interaction with PD-L1 [4]. This anti-PD-1 scFv did not, however, function in a cell-based assay designed to detect the disruption of the PD-1/PD-L1 interaction, a result likely due to its poor solubility in tissue culture media. Herein we report that following a series of structure-based rational design analyses, including Aggreescan3D, we have isolated a variant of the anti-PD-1 scFv having significantly improved solubility in tissue culture medium. Moreover, this soluble anti-PD-1 scFv variant disrupted the interaction between PD-1 expressed on Jurkat Cells and PD-L1 expressed on CHO cells. These findings are discussed in terms of the related observation that the residues mutated to form the anti-PD-1 variant are conserved in many other scFvs; thus, the properties of a range of scFvs will likely be enhanced by similar mutations of the conserved residues.
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Affiliation(s)
- Jong Shin
- Department of Pathology, New York University Grossman School of Medicine, 550 First Avenue, New York, NY, 10016, USA
| | - Siavash Raissi
- Department of Developmental, Molecular and Chemical Biology Tufts University School of Medicine, 136 Harrison Avenue, Boston, MA, 02111, USA
| | - Paul Phelan
- Joinn Biologics, 2600 Hilltop Drive, Building L, Richmond, CA, 94806, USA
| | - Peter A Bullock
- Department of Developmental, Molecular and Chemical Biology Tufts University School of Medicine, 136 Harrison Avenue, Boston, MA, 02111, USA.
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8
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Svilenov HL, Arosio P, Menzen T, Tessier P, Sormanni P. Approaches to expand the conventional toolbox for discovery and selection of antibodies with drug-like physicochemical properties. MAbs 2023; 15:2164459. [PMID: 36629855 PMCID: PMC9839375 DOI: 10.1080/19420862.2022.2164459] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 12/22/2022] [Accepted: 12/29/2022] [Indexed: 01/12/2023] Open
Abstract
Antibody drugs should exhibit not only high-binding affinity for their target antigens but also favorable physicochemical drug-like properties. Such drug-like biophysical properties are essential for the successful development of antibody drug products. The traditional approaches used in antibody drug development require significant experimentation to produce, optimize, and characterize many candidates. Therefore, it is attractive to integrate new methods that can optimize the process of selecting antibodies with both desired target-binding and drug-like biophysical properties. Here, we summarize a selection of techniques that can complement the conventional toolbox used to de-risk antibody drug development. These techniques can be integrated at different stages of the antibody development process to reduce the frequency of physicochemical liabilities in antibody libraries during initial discovery and to co-optimize multiple antibody features during early-stage antibody engineering and affinity maturation. Moreover, we highlight biophysical and computational approaches that can be used to predict physical degradation pathways relevant for long-term storage and in-use stability to reduce the need for extensive experimentation.
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Affiliation(s)
- Hristo L. Svilenov
- Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, Gent, Belgium
| | - Paolo Arosio
- Department of Chemistry and Applied Biosciences, ETH Zürich, Zürich, Switzerland
| | - Tim Menzen
- Coriolis Pharma Research GmbH, Martinsried, 82152, Germany
| | - Peter Tessier
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Pietro Sormanni
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK
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9
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Qing R, Hao S, Smorodina E, Jin D, Zalevsky A, Zhang S. Protein Design: From the Aspect of Water Solubility and Stability. Chem Rev 2022; 122:14085-14179. [PMID: 35921495 PMCID: PMC9523718 DOI: 10.1021/acs.chemrev.1c00757] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Indexed: 12/13/2022]
Abstract
Water solubility and structural stability are key merits for proteins defined by the primary sequence and 3D-conformation. Their manipulation represents important aspects of the protein design field that relies on the accurate placement of amino acids and molecular interactions, guided by underlying physiochemical principles. Emulated designer proteins with well-defined properties both fuel the knowledge-base for more precise computational design models and are used in various biomedical and nanotechnological applications. The continuous developments in protein science, increasing computing power, new algorithms, and characterization techniques provide sophisticated toolkits for solubility design beyond guess work. In this review, we summarize recent advances in the protein design field with respect to water solubility and structural stability. After introducing fundamental design rules, we discuss the transmembrane protein solubilization and de novo transmembrane protein design. Traditional strategies to enhance protein solubility and structural stability are introduced. The designs of stable protein complexes and high-order assemblies are covered. Computational methodologies behind these endeavors, including structure prediction programs, machine learning algorithms, and specialty software dedicated to the evaluation of protein solubility and aggregation, are discussed. The findings and opportunities for Cryo-EM are presented. This review provides an overview of significant progress and prospects in accurate protein design for solubility and stability.
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Affiliation(s)
- Rui Qing
- State
Key Laboratory of Microbial Metabolism, School of Life Sciences and
Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
- Media
Lab, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
- The
David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
| | - Shilei Hao
- Media
Lab, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
- Key
Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing 400030, China
| | - Eva Smorodina
- Department
of Immunology, University of Oslo and Oslo
University Hospital, Oslo 0424, Norway
| | - David Jin
- Avalon GloboCare
Corp., Freehold, New Jersey 07728, United States
| | - Arthur Zalevsky
- Laboratory
of Bioinformatics Approaches in Combinatorial Chemistry and Biology, Shemyakin−Ovchinnikov Institute of Bioorganic
Chemistry RAS, Moscow 117997, Russia
| | - Shuguang Zhang
- Media
Lab, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
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10
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Badaczewska-Dawid AE, Garcia-Pardo J, Kuriata A, Pujols J, Ventura S, Kmiecik S. A3D database: structure-based predictions of protein aggregation for the human proteome. Bioinformatics 2022; 38:3121-3123. [PMID: 35445695 PMCID: PMC9746890 DOI: 10.1093/bioinformatics/btac215] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 03/10/2022] [Accepted: 04/19/2022] [Indexed: 12/16/2022] Open
Abstract
SUMMARY Protein aggregation is associated with many human disorders and constitutes a major bottleneck for producing therapeutic proteins. Our knowledge of the human protein structures repertoire has dramatically increased with the recent development of the AlphaFold (AF) deep-learning method. This structural information can be used to understand better protein aggregation properties and the rational design of protein solubility. This article uses the Aggrescan3D (A3D) tool to compute the structure-based aggregation predictions for the human proteome and make the predictions available in a database form. In the A3D database, we analyze the AF-predicted human protein structures (for over 20.5 thousand unique Uniprot IDs) in terms of their aggregation properties using the A3D tool. Each entry of the A3D database provides a detailed analysis of the structure-based aggregation propensity computed with A3D. The A3D database implements simple but useful graphical tools for visualizing and interpreting protein structure datasets. It also enables testing the influence of user-selected mutations on protein solubility and stability, all integrated into a user-friendly interface. AVAILABILITY AND IMPLEMENTATION A3D database is freely available at: http://biocomp.chem.uw.edu.pl/A3D2/hproteome. The data underlying this article are available in the article and in its online supplementary material. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | - Javier Garcia-Pardo
- Institut de Biotecnologia i de Biomedicina (IBB) and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
| | - Aleksander Kuriata
- Biological and Chemical Research Center, Faculty of Chemistry, University of Warsaw, Warsaw 02-093, Poland
| | - Jordi Pujols
- Institut de Biotecnologia i de Biomedicina (IBB) and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
| | - Salvador Ventura
- Institut de Biotecnologia i de Biomedicina (IBB) and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain,To whom correspondence should be addressed. and
| | - Sebastian Kmiecik
- Biological and Chemical Research Center, Faculty of Chemistry, University of Warsaw, Warsaw 02-093, Poland,To whom correspondence should be addressed. and
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11
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MPEPE, a predictive approach to improve protein expression in E. coli based on deep learning. Comput Struct Biotechnol J 2022; 20:1142-1153. [PMID: 35317239 PMCID: PMC8913310 DOI: 10.1016/j.csbj.2022.02.030] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 02/27/2022] [Accepted: 02/28/2022] [Indexed: 12/20/2022] Open
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12
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Computational methods to predict protein aggregation. Curr Opin Struct Biol 2022; 73:102343. [PMID: 35240456 DOI: 10.1016/j.sbi.2022.102343] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 12/20/2021] [Accepted: 01/17/2022] [Indexed: 01/13/2023]
Abstract
In most cases, protein aggregation stems from the establishment of non-native intermolecular contacts. The formation of insoluble protein aggregates is associated with many human diseases and is a major bottleneck for the industrial production of protein-based therapeutics. Strikingly, fibrillar aggregates are naturally exploited for structural scaffolding or to generate molecular switches and can be artificially engineered to build up multi-functional nanomaterials. Thus, there is a high interest in rationalizing and forecasting protein aggregation. Here, we review the available computational toolbox to predict protein aggregation propensities, identify sequential or structural aggregation-prone regions, evaluate the impact of mutations on aggregation or recognize prion-like domains. We discuss the strengths and limitations of these algorithms and how they can evolve in the next future.
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13
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Khetan R, Curtis R, Deane CM, Hadsund JT, Kar U, Krawczyk K, Kuroda D, Robinson SA, Sormanni P, Tsumoto K, Warwicker J, Martin ACR. Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics. MAbs 2022; 14:2020082. [PMID: 35104168 PMCID: PMC8812776 DOI: 10.1080/19420862.2021.2020082] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Therapeutic monoclonal antibodies and their derivatives are key components of clinical pipelines in the global biopharmaceutical industry. The availability of large datasets of antibody sequences, structures, and biophysical properties is increasingly enabling the development of predictive models and computational tools for the "developability assessment" of antibody drug candidates. Here, we provide an overview of the antibody informatics tools applicable to the prediction of developability issues such as stability, aggregation, immunogenicity, and chemical degradation. We further evaluate the opportunities and challenges of using biopharmaceutical informatics for drug discovery and optimization. Finally, we discuss the potential of developability guidelines based on in silico metrics that can be used for the assessment of antibody stability and manufacturability.
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Affiliation(s)
- Rahul Khetan
- Manchester Institute of Biotechnology, University of Manchester, Manchester, UK
| | - Robin Curtis
- Manchester Institute of Biotechnology, University of Manchester, Manchester, UK
| | | | | | - Uddipan Kar
- Department of Biological Engineering, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
| | | | - Daisuke Kuroda
- Department of Bioengineering, School of Engineering, The University of Tokyo, Tokyo, Japan.,Medical Device Development and Regulation Research Center, School of Engineering, The University of Tokyo, Tokyo, Japan.,Department of Chemistry and Biotechnology, School of Engineering, The University of Tokyo, Tokyo, Japan
| | | | - Pietro Sormanni
- Chemistry of Health, Yusuf Hamied Department of Chemistry, University of Cambridge
| | - Kouhei Tsumoto
- Department of Bioengineering, School of Engineering, The University of Tokyo, Tokyo, Japan.,Medical Device Development and Regulation Research Center, School of Engineering, The University of Tokyo, Tokyo, Japan.,Department of Chemistry and Biotechnology, School of Engineering, The University of Tokyo, Tokyo, Japan.,The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Jim Warwicker
- Manchester Institute of Biotechnology, University of Manchester, Manchester, UK
| | - Andrew C R Martin
- Institute of Structural and Molecular Biology, Division of Biosciences, University College London, London, UK
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14
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Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2022; 2313:57-113. [PMID: 34478132 DOI: 10.1007/978-1-0716-1450-1_4] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Although antibodies have become the fastest-growing class of therapeutics on the market, it is still challenging to develop them for therapeutic applications, which often require these molecules to withstand stresses that are not present in vivo. We define developability as the likelihood of an antibody candidate with suitable functionality to be developed into a manufacturable, stable, safe, and effective drug that can be formulated to high concentrations while retaining a long shelf life. The implementation of reliable developability assessments from the early stages of antibody discovery enables flagging and deselection of potentially problematic candidates, while focussing available resources on the development of the most promising ones. Currently, however, thorough developability assessment requires multiple in vitro assays, which makes it labor intensive and time consuming to implement at early stages. Furthermore, accurate in vitro analysis at the early stage is compromised by the high number of potential candidates that are often prepared at low quantities and purity. Recent improvements in the performance of computational predictors of developability potential are beginning to change this scenario. Many computational methods only require the knowledge of the amino acid sequences and can be used to identify possible developability issues or to rank available candidates according to a range of biophysical properties. Here, we describe how the implementation of in silico tools into antibody discovery pipelines is increasingly offering time- and cost-effective alternatives to in vitro experimental screening, thus streamlining the drug development process. We discuss in particular the biophysical and biochemical properties that underpin developability potential and their trade-offs, review various in vitro assays to measure such properties or parameters that are predictive of developability, and give an overview of the growing number of in silico tools available to predict properties important for antibody development, including the CamSol method developed in our laboratory.
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15
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Seyedhosseini Ghaheh H, Sajjadi S, Shafiee F, Barzegari E, Moazen F, Mir Mohammad Sadeghi H. Rational design of a new variant of Reteplase with optimized physicochemical profile and large-scale production in Escherichia coli. World J Microbiol Biotechnol 2022; 38:29. [PMID: 34989886 DOI: 10.1007/s11274-021-03204-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 12/06/2021] [Indexed: 10/19/2022]
Abstract
Structural engineering of the recombinant thrombolytic drug, Reteplase, and its cost-effective production are important goals in the pharmaceutical industry. In this study, a single-point mutant of the protein was rationally designed and evaluated in terms of physicochemical characteristics, enzymatic activity, as well as large-scale production settings. An accurate homology model of Reteplase was used as the input to appropriate tools to identify the aggregation-prone sites, while considering the structural stability. Selected variants underwent extensive molecular dynamic simulations (total 540 ns) to assess their solvation profile and their thermal stability. The Reteplase-fibrin interaction was investigated by docking. The best variant was expressed in E. coli, and Box-Behnken design was used through response surface methodology to optimize its expression conditions. M72R mutant demonstrated appropriate stability, enhanced enzymatic activity (p < 0.05), and strengthened binding to fibrin, compared to the wild type. The optimal conditions for the variant's production in a bioreactor was shown to be 37 ºC, induction with 0.5 mM IPTG, for 2 h of incubation. Under these conditions, the final amount of the produced enzyme was increased by about 23 mg/L compared to the wild type, with an increase in the enzymatic activity by about 2 IU/mL. This study thus offered a new Reteplase variant with nearly all favorable properties, except solubility. The impact of temperature and incubation time on its large-scale production were underlined as well.
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Affiliation(s)
- Hooria Seyedhosseini Ghaheh
- Department of Pharmaceutical Biotechnology, School of Pharmacy and Pharmaceutical Sciences, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Shabnam Sajjadi
- Faculty of Pharmacy, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | - Fatemeh Shafiee
- Department of Pharmaceutical Biotechnology, School of Pharmacy and Pharmaceutical Sciences, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Ebrahim Barzegari
- Medical Biology Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Fatemeh Moazen
- Department of Pharmaceutical Biotechnology, School of Pharmacy and Pharmaceutical Sciences, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Hamid Mir Mohammad Sadeghi
- Department of Pharmaceutical Biotechnology, School of Pharmacy and Pharmaceutical Sciences, Isfahan University of Medical Sciences, Isfahan, Iran.
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16
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Kuriata A, Badaczewska-Dawid AE, Pujols J, Ventura S, Kmiecik S. Protocols for Rational Design of Protein Solubility and Aggregation Properties Using Aggrescan3D Standalone. Methods Mol Biol 2022; 2340:17-40. [PMID: 35167068 DOI: 10.1007/978-1-0716-1546-1_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Protein aggregation is a major hurdle in the development and manufacturing of protein-based therapeutics. Development of aggregation-resistant and stable protein variants can be guided by rational redesign using computational tools. Here, we describe the architecture and functionalities of the Aggrescan3D (A3D) standalone package for the rational design of protein solubility and aggregation properties based on three-dimensional protein structures. We present the case studies of the three therapeutic proteins, including antibodies, exploring the practical use of the A3D standalone tool. The case studies demonstrate that protein solubility can be easily improved by the A3D prediction of non-destabilizing amino acid mutations at the protein surfaces.
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Affiliation(s)
- Aleksander Kuriata
- Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, Warsaw, Poland
| | | | - Jordi Pujols
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, Bellaterra, Spain
- Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Salvador Ventura
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, Bellaterra, Spain
- Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Sebastian Kmiecik
- Biological and Chemical Research Centre, University of Warsaw, Warsaw, Poland.
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17
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Pujols J, Iglesias V, Santos J, Kuriata A, Kmiecik S, Ventura S. A3D 2.0 Update for the Prediction and Optimization of Protein Solubility. Methods Mol Biol 2022; 2406:65-84. [PMID: 35089550 DOI: 10.1007/978-1-0716-1859-2_3] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Protein aggregation propensity is a property imprinted in protein sequences and structures, being associated with the onset of human diseases and limiting the implementation of protein-based biotherapies. Computational approaches stand as cost-effective alternatives for reducing protein aggregation and increasing protein solubility. AGGRESCAN 3D (A3D) is a structure-based predictor of aggregation that takes into account the conformational context of a protein, aiming to identify aggregation-prone regions exposed in protein surfaces. Here we inspect the updated 2.0 version of the algorithm, which extends the application of A3D to previously inaccessible proteins and incorporates new modules to assist protein redesign. Among these features, the new server includes stability calculations and the possibility to optimize protein solubility using an experimentally validated computational pipeline. Finally, we employ defined examples to navigate the A3D RESTful service, a routine to handle extensive protein collections. Altogether, this chapter is conceived to train and assist A3D non-experts in the study of aggregation-prone regions and protein solubility redesign.
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Affiliation(s)
- Jordi Pujols
- Institut de Biotecnologia i Biomedicina (IBB) and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barelona (UAB), Barcelona, Spain
| | - Valentín Iglesias
- Institut de Biotecnologia i Biomedicina (IBB) and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barelona (UAB), Barcelona, Spain
| | - Jaime Santos
- Institut de Biotecnologia i Biomedicina (IBB) and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barelona (UAB), Barcelona, Spain
| | - Aleksander Kuriata
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, Warsaw, Poland
| | - Sebastian Kmiecik
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, Warsaw, Poland
| | - Salvador Ventura
- Institut de Biotecnologia i Biomedicina (IBB) and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barelona (UAB), Barcelona, Spain.
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18
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Gil-Garcia M, Ventura S. Coiled-Coil Based Inclusion Bodies and Their Potential Applications. Front Bioeng Biotechnol 2021; 9:734068. [PMID: 34485264 PMCID: PMC8415879 DOI: 10.3389/fbioe.2021.734068] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 08/05/2021] [Indexed: 02/01/2023] Open
Abstract
The production of recombinant proteins using microbial cell factories is frequently associated with the formation of inclusion bodies (IBs). These proteinaceous entities can be sometimes a reservoir of stable and active protein, might display good biocompatibility, and are produced efficiently and cost-effectively. Thus, these submicrometric particles are increasingly exploited as functional biomaterials for biotechnological and biomedical purposes. The fusion of aggregation-prone sequences to the target protein is a successful strategy to sequester soluble recombinant polypeptides into IBs. Traditionally, the use of these IB-tags results in the formation of amyloid-like scaffolds where the protein of interest is trapped. This amyloid conformation might compromise the protein's activity and be potentially cytotoxic. One promising alternative to overcome these limitations exploits the coiled-coil fold, composed of two or more α-helices and widely used by nature to create supramolecular assemblies. In this review, we summarize the state-of-the-art of functional IBs technology, focusing on the coiled-coil-assembly strategy, describing its advantages and applications, delving into future developments and necessary improvements in the field.
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Affiliation(s)
- Marcos Gil-Garcia
- Institut de Biotecnologia i de Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Salvador Ventura
- Institut de Biotecnologia i de Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain
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19
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Abstract
A rapid-acting insulin lispro and long-acting insulin glargine are commonly used for the treatment of diabetes. Clinical cases have described the formation of injectable amyloidosis with these insulin analogues, but their amyloid core regions of fibrils were unknown. To reveal these regions, we have analysed the hydrolyzates of insulin fibrils and its analogues using high-performance liquid chromatography and mass spectrometry methods and found that insulin and its analogues have almost identical amyloid core regions that intersect with the predicted amyloidogenic regions. The obtained results can be used to create new insulin analogues with a low ability to form fibrils. Abbreviations a.a., amino acid residues; HPLC-MS, high-performance liquid chromatography/mass spectrometry; m/z, mass-to-charge ratio; TEM, transmission electron microscopy.
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Affiliation(s)
- Alexey K Surin
- Institute of Protein Research, Russian Academy of Sciences , Pushchino, Russian Federation.,State Research Center for Applied Microbiology and Biotechnology , Obolensk, Russian Federation.,The Branch of the Institute of Bioorganic Chemistry, Russian Academy of Sciences , Pushchino, Russian Federation
| | - Sergei Yu Grishin
- Institute of Protein Research, Russian Academy of Sciences , Pushchino, Russian Federation
| | - Oxana V Galzitskaya
- Institute of Protein Research, Russian Academy of Sciences , Pushchino, Russian Federation.,Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences , Pushchino, Russian Federation
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20
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Meric G, Naik S, Hunter AK, Robinson AS, Roberts CJ. Challenges for design of aggregation-resistant variants of granulocyte colony-stimulating factor. Biophys Chem 2021; 277:106630. [PMID: 34119805 DOI: 10.1016/j.bpc.2021.106630] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Revised: 05/14/2021] [Accepted: 05/31/2021] [Indexed: 01/15/2023]
Abstract
Non-native protein aggregation is a long-standing issue in pharmaceutical biotechnology. A rational design approach was used in order to identify variants of recombinant human granulocyte colony-stimulating factor (rhG-CSF) with lower aggregation propensity at solution conditions that are typical of commercial formulation. The approach used aggregation-prone-region (APR) predictors to select single amino acid substitutions that were predicted to decrease intrinsic aggregation propensity (IAP). The results of static light scattering temperature-ramps and chemical unfolding experiments demonstrated that none of the selected variants exhibited improved aggregation resistance, and the apparent conformational stability of each variant was lower than that of WT. Aggregation studies under partly denaturing conditions suggested that the IAP of at least one variant remained unaltered. Overall, this study highlights a general challenge in designing aggregation resistance for proteins, due to the need to accurately predict both APRs and conformational stability.
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Affiliation(s)
- Gulsum Meric
- Chemical & Biomolecular Engineering, University of Delaware, Newark, DE 19716, United States.
| | - Subhashchandra Naik
- Chemical & Biomolecular Engineering, University of Delaware, Newark, DE 19716, United States.
| | - Alan K Hunter
- Biopharmaceuticals Development, R&D, AstraZeneca, Gaithersburg, MD 20878, United States.
| | - Anne S Robinson
- Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, United States.
| | - Christopher J Roberts
- Chemical & Biomolecular Engineering, University of Delaware, Newark, DE 19716, United States.
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21
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Abstract
Protein aggregation is a widespread phenomenon with important implications in many scientific areas. Although amyloid formation is typically considered as detrimental, functional amyloids that perform physiological roles have been identified in all kingdoms of life. Despite their functional and pathological relevance, the structural details of the majority of molecular species involved in the amyloidogenic process remains elusive. Here, we explore the application of AlphaFold, a highly accurate protein structure predictor, in the field of protein aggregation. While we envision a straightforward application of AlphaFold in assisting the design of globular proteins with improved solubility for biomedical and industrial purposes, the use of this algorithm for predicting the structure of aggregated species seems far from trivial. First, in amyloid diseases, the presence of multiple amyloid polymorphs and the heterogeneity of aggregation intermediates challenges the "one sequence, one structure" paradigm, inherent to sequence-based predictions. Second, aberrant aggregation is not the subject of positive selective pressure, precluding the use of evolutionary-based approaches, which are the core of the AlphaFold pipeline. Instead, amyloid polymorphism seems to be constrained by the need for a defined structure-activity relationship in functional amyloids. They may thus provide a starting point for the application of AlphaFold in the amyloid landscape.
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22
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MED15 prion-like domain forms a coiled-coil responsible for its amyloid conversion and propagation. Commun Biol 2021; 4:414. [PMID: 33772081 PMCID: PMC7997880 DOI: 10.1038/s42003-021-01930-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 03/02/2021] [Indexed: 02/01/2023] Open
Abstract
A disordered to β-sheet transition was thought to drive the functional switch of Q/N-rich prions, similar to pathogenic amyloids. However, recent evidence indicates a critical role for coiled-coil (CC) regions within yeast prion domains in amyloid formation. We show that many human prion-like domains (PrLDs) contain CC regions that overlap with polyQ tracts. Most of the proteins bearing these domains are transcriptional coactivators, including the Mediator complex subunit 15 (MED15) involved in bridging enhancers and promoters. We demonstrate that the human MED15-PrLD forms homodimers in solution sustained by CC interactions and that it is this CC fold that mediates the transition towards a β-sheet amyloid state, its chemical or genetic disruption abolishing aggregation. As in functional yeast prions, a GFP globular domain adjacent to MED15-PrLD retains its structural integrity in the amyloid state. Expression of MED15-PrLD in human cells promotes the formation of cytoplasmic and perinuclear inclusions, kidnapping endogenous full-length MED15 to these aggregates in a prion-like manner. The prion-like properties of MED15 are conserved, suggesting novel mechanisms for the function and malfunction of this transcription coactivator.
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23
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Badaczewska-Dawid AE, Kolinski A, Kmiecik S. Protocols for Fast Simulations of Protein Structure Flexibility Using CABS-Flex and SURPASS. Methods Mol Biol 2021; 2165:337-353. [PMID: 32621235 DOI: 10.1007/978-1-0716-0708-4_20] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Conformational flexibility of protein structures can play an important role in protein function. The flexibility is often studied using computational methods since experimental characterization can be difficult. Depending on protein system size, computational tools may require large computational resources or significant simplifications in the modeled systems to speed up calculations. In this work, we present the protocols for efficient simulations of flexibility of folded protein structures that use coarse-grained simulation tools of different resolutions: medium, represented by CABS-flex, and low, represented by SUPRASS. We test the protocols using a set of 140 globular proteins and compare the results with structure fluctuations observed in MD simulations, ENM modeling, and NMR ensembles. As demonstrated, CABS-flex predictions show high correlation to experimental and MD simulation data, while SURPASS is less accurate but promising in terms of future developments.
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Affiliation(s)
- Aleksandra E Badaczewska-Dawid
- Faculty of Chemistry, Biological and Chemical Research Center, University of Warsaw, Warsaw, Poland.,Department of Chemistry, Iowa State University, Ames, IA, USA
| | - Andrzej Kolinski
- Faculty of Chemistry, Biological and Chemical Research Center, University of Warsaw, Warsaw, Poland
| | - Sebastian Kmiecik
- Faculty of Chemistry, Biological and Chemical Research Center, University of Warsaw, Warsaw, Poland.
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24
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Kollár É, Balázs B, Tari T, Siró I. Development challenges of high concentration monoclonal antibody formulations. DRUG DISCOVERY TODAY. TECHNOLOGIES 2020; 37:31-40. [PMID: 34895653 DOI: 10.1016/j.ddtec.2020.08.005] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 08/17/2020] [Accepted: 08/31/2020] [Indexed: 01/09/2023]
Abstract
High concentration monoclonal antibody drug products represent a special segment of biopharmaceuticals. In contrast to other monoclonal antibody products, high concentration monoclonal antibodies are injected subcutaneously helping increase patient compliance and reduce the number of hospital patient visits. It is important to note that a high protein concentration (≥50 mg/mL) poses a challenge from a product development perspective. Colloidal properties, physical and chemical protein stability should be considered during formulation, primary packaging and manufacturing process development as well as optimization of other dosage form-related parameters. The aim of such development work is to obtain a drug product capable of maintaining appropriate protein structure throughout its shelf-life and ensure proper and accurate dosage upon administration.
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Affiliation(s)
- Éva Kollár
- Department of Biotechnology Development, Gedeon Richter Plc., Gyömrői út 19-21, 1103 Budapest, Hungary.
| | - Boglárka Balázs
- Department of Biotechnology Development, Gedeon Richter Plc., Gyömrői út 19-21, 1103 Budapest, Hungary
| | - Tímea Tari
- Department of Biotechnology Development, Gedeon Richter Plc., Gyömrői út 19-21, 1103 Budapest, Hungary
| | - István Siró
- Department of Biotechnology Development, Gedeon Richter Plc., Gyömrői út 19-21, 1103 Budapest, Hungary
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25
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Computational prediction of protein aggregation: Advances in proteomics, conformation-specific algorithms and biotechnological applications. Comput Struct Biotechnol J 2020; 18:1403-1413. [PMID: 32637039 PMCID: PMC7322485 DOI: 10.1016/j.csbj.2020.05.026] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 05/26/2020] [Accepted: 05/28/2020] [Indexed: 12/16/2022] Open
Abstract
Protein aggregation is a widespread phenomenon that stems from the establishment of non-native intermolecular contacts resulting in protein precipitation. Despite its deleterious impact on fitness, protein aggregation is a generic property of polypeptide chains, indissociable from protein structure and function. Protein aggregation is behind the onset of neurodegenerative disorders and one of the serious obstacles in the production of protein-based therapeutics. The development of computational tools opened a new avenue to rationalize this phenomenon, enabling prediction of the aggregation propensity of individual proteins as well as proteome-wide analysis. These studies spotted aggregation as a major force driving protein evolution. Actual algorithms work on both protein sequences and structures, some of them accounting also for conformational fluctuations around the native state and the protein microenvironment. This toolbox allows to delineate conformation-specific routines to assist in the identification of aggregation-prone regions and to guide the optimization of more soluble and stable biotherapeutics. Here we review how the advent of predictive tools has change the way we think and address protein aggregation.
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26
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Kuriata A, Iglesias V, Kurcinski M, Ventura S, Kmiecik S. Aggrescan3D standalone package for structure-based prediction of protein aggregation properties. Bioinformatics 2020; 35:3834-3835. [PMID: 30825368 DOI: 10.1093/bioinformatics/btz143] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 02/12/2019] [Accepted: 02/27/2019] [Indexed: 11/13/2022] Open
Abstract
SUMMARY Aggrescan3D (A3D) standalone is a multiplatform Python package for structure-based prediction of protein aggregation properties and rational design of protein solubility. A3D allows the re-design of protein solubility by combining structural aggregation propensity and stability predictions, as demonstrated by a recent experimental study. It also enables predicting the impact of protein conformational fluctuations on the aggregation properties. The standalone A3D version is an upgrade of the original web server implementation-it introduces a number of customizable options, automated analysis of multiple mutations and offers a flexible computational framework for merging it with other computational tools. AVAILABILITY AND IMPLEMENTATION A3D standalone is distributed under the MIT license, which is free for academic and non-profit users. It is implemented in Python. The A3D standalone source code, wiki with documentation and examples of use, and installation instructions for Linux, macOS and Windows are available in the A3D standalone repository at https://bitbucket.org/lcbio/aggrescan3d.
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Affiliation(s)
- Aleksander Kuriata
- Biological and Chemical Research Centre, Department of Chemistry, University of Warsaw, Warsaw, Poland
| | - Valentin Iglesias
- Institut de Biotecnologia i de Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Mateusz Kurcinski
- Biological and Chemical Research Centre, Department of Chemistry, University of Warsaw, Warsaw, Poland
| | - Salvador Ventura
- Institut de Biotecnologia i de Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Sebastian Kmiecik
- Biological and Chemical Research Centre, Department of Chemistry, University of Warsaw, Warsaw, Poland
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27
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Pham NB, Meng WS. Protein aggregation and immunogenicity of biotherapeutics. Int J Pharm 2020; 585:119523. [PMID: 32531452 DOI: 10.1016/j.ijpharm.2020.119523] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 06/01/2020] [Accepted: 06/06/2020] [Indexed: 12/19/2022]
Abstract
Recombinant proteins are the mainstay of biopharmaceuticals. A key challenge in the manufacturing and formulation of protein biologic products is the tendency for the active pharmaceutical ingredients to aggregate, resulting in irreversible drug loss, and an increase in immunogenicity risk. While the molecular mechanisms of protein aggregation have been discussed extensively in the literature, knowledge gaps remain in connecting the phenomenon in the context of immunogenicity of biotherapeutics. In this review, we discussed factors that drive aggregation of pharmaceutical recombinant proteins, and highlighted methods of prediction and mitigation that can be deployed through the development stages, from formulation to bioproduction. The purpose is to stimulate new dialogs that would bridge the interface between physical characterizations of protein aggregates in biotherapeutics and the functional attributes of the immune system.
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Affiliation(s)
- Ngoc B Pham
- Graduate School of Pharmaceutical Sciences, School of Pharmacy, Duquesne University, Pittsburgh, PA 15282, United States
| | - Wilson S Meng
- Graduate School of Pharmaceutical Sciences, School of Pharmacy, Duquesne University, Pittsburgh, PA 15282, United States; McGowan Institute for Regenerative Medicine, University of Pittsburgh, PA 15219, United States.
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28
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Gil-Garcia M, Navarro S, Ventura S. Coiled-coil inspired functional inclusion bodies. Microb Cell Fact 2020; 19:117. [PMID: 32487230 PMCID: PMC7268670 DOI: 10.1186/s12934-020-01375-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 05/25/2020] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Recombinant protein expression in bacteria often leads to the formation of intracellular insoluble protein deposits, a major bottleneck for the production of soluble and active products. However, in recent years, these bacterial protein aggregates, commonly known as inclusion bodies (IBs), have been shown to be a source of stable and active protein for biotechnological and biomedical applications. The formation of these functional IBs is usually facilitated by the fusion of aggregation-prone peptides or proteins to the protein of interest, leading to the formation of amyloid-like nanostructures, where the functional protein is embedded. RESULTS In order to offer an alternative to the classical amyloid-like IBs, here we develop functional IBs exploiting the coiled-coil fold. An in silico analysis of coiled-coil and aggregation propensities, net charge, and hydropathicity of different potential tags identified the natural homo-dimeric and anti-parallel coiled-coil ZapB bacterial protein as an optimal candidate to form assemblies in which the native state of the fused protein is preserved. The protein itself forms supramolecular fibrillar networks exhibiting only α-helix secondary structure. This non-amyloid self-assembly propensity allows generating innocuous IBs in which the recombinant protein of interest remains folded and functional, as demonstrated using two different fluorescent proteins. CONCLUSIONS Here, we present a proof of concept for the use of a natural coiled-coil domain as a versatile tool for the production of functional IBs in bacteria. This α-helix-based strategy excludes any potential toxicity drawback that might arise from the amyloid nature of β-sheet-based IBs and renders highly active and homogeneous submicrometric particles.
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Affiliation(s)
- Marcos Gil-Garcia
- Institut de Biotecnologia i de Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193, Bellaterra, Barcelona, Spain
| | - Susanna Navarro
- Institut de Biotecnologia i de Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193, Bellaterra, Barcelona, Spain
| | - Salvador Ventura
- Institut de Biotecnologia i de Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, 08193, Bellaterra, Barcelona, Spain.
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Kuriata A, Iglesias V, Pujols J, Kurcinski M, Kmiecik S, Ventura S. Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility. Nucleic Acids Res 2020; 47:W300-W307. [PMID: 31049593 PMCID: PMC6602499 DOI: 10.1093/nar/gkz321] [Citation(s) in RCA: 75] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Revised: 03/29/2019] [Accepted: 04/20/2019] [Indexed: 12/11/2022] Open
Abstract
Protein aggregation is a hallmark of a growing number of human disorders and constitutes a major bottleneck in the manufacturing of therapeutic proteins. Therefore, there is a strong need of in-silico methods that can anticipate the aggregative properties of protein variants linked to disease and assist the engineering of soluble protein-based drugs. A few years ago, we developed a method for structure-based prediction of aggregation properties that takes into account the dynamic fluctuations of proteins. The method has been made available as the Aggrescan3D (A3D) web server and applied in numerous studies of protein structure-aggregation relationship. Here, we present a major update of the A3D web server to version 2.0. The new features include: extension of dynamic calculations to significantly larger and multimeric proteins, simultaneous prediction of changes in protein solubility and stability upon mutation, rapid screening for functional protein variants with improved solubility, a REST-ful service to incorporate A3D calculations in automatic pipelines, and a new, enhanced web server interface. A3D 2.0 is freely available at: http://biocomp.chem.uw.edu.pl/A3D2/
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Affiliation(s)
- Aleksander Kuriata
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, 02-089 Warsaw, Poland
| | - Valentin Iglesias
- Institut de Biotecnologia i Biomedicina and Departament de Bioquímica I Biologia Molecular Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Jordi Pujols
- Institut de Biotecnologia i Biomedicina and Departament de Bioquímica I Biologia Molecular Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Mateusz Kurcinski
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, 02-089 Warsaw, Poland
| | - Sebastian Kmiecik
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, 02-089 Warsaw, Poland
| | - Salvador Ventura
- Institut de Biotecnologia i Biomedicina and Departament de Bioquímica I Biologia Molecular Universitat Autònoma de Barcelona, Bellaterra, Spain
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30
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Willis LF, Kumar A, Jain T, Caffry I, Xu Y, Radford SE, Kapur N, Vásquez M, Brockwell DJ. The uniqueness of flow in probing the aggregation behavior of clinically relevant antibodies. ENGINEERING REPORTS : OPEN ACCESS 2020; 2:e12147. [PMID: 34901768 PMCID: PMC8638667 DOI: 10.1002/eng2.12147] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Revised: 02/18/2020] [Accepted: 02/19/2020] [Indexed: 06/10/2023]
Abstract
The development of therapeutic monoclonal antibodies (mAbs) can be hindered by their tendency to aggregate throughout their lifetime, which can illicit immunogenic responses and render mAb manufacturing unfeasible. Consequently, there is a need to identify mAbs with desirable thermodynamic stability, solubility, and lack of self-association. These behaviors are assessed using an array of in silico and in vitro assays, as no single assay can predict aggregation and developability. We have developed an extensional and shear flow device (EFD), which subjects proteins to defined hydrodynamic forces which mimic those experienced in bioprocessing. Here, we utilize the EFD to explore the aggregation propensity of 33 IgG1 mAbs, whose variable domains are derived from clinical antibodies. Using submilligram quantities of material per replicate, wide-ranging EFD-induced aggregation (9-81% protein in pellet) was observed for these mAbs, highlighting the EFD as a sensitive method to assess aggregation propensity. By comparing the EFD-induced aggregation data to those obtained previously from 12 other biophysical assays, we show that the EFD provides distinct information compared with current measures of adverse biophysical behavior. Assessing a candidate's liability to hydrodynamic force thus adds novel insight into the rational selection of developable mAbs that complements other assays.
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Affiliation(s)
- Leon F. Willis
- School of Molecular and Cellular Biology, Faculty of Biological SciencesUniversity of LeedsLeedsUK
- Astbury Centre for Structural Molecular BiologyUniversity of LeedsLeedsUK
| | - Amit Kumar
- School of Molecular and Cellular Biology, Faculty of Biological SciencesUniversity of LeedsLeedsUK
- Astbury Centre for Structural Molecular BiologyUniversity of LeedsLeedsUK
- Department of Life SciencesImperial College LondonLondonUK
| | | | - Isabelle Caffry
- Adimab LLCLebanonNew HampshireUSA
- Cornell Johnson Graduate School of ManagementIthacaNew YorkUSA
| | - Yingda Xu
- Adimab LLCLebanonNew HampshireUSA
- Biotheus Inc.ZhuhaiGuangdong ProvinceChina
| | - Sheena E. Radford
- School of Molecular and Cellular Biology, Faculty of Biological SciencesUniversity of LeedsLeedsUK
- Astbury Centre for Structural Molecular BiologyUniversity of LeedsLeedsUK
| | - Nikil Kapur
- School of Mechanical Engineering, Faculty of EngineeringUniversity of LeedsLeedsUK
| | | | - David J. Brockwell
- School of Molecular and Cellular Biology, Faculty of Biological SciencesUniversity of LeedsLeedsUK
- Astbury Centre for Structural Molecular BiologyUniversity of LeedsLeedsUK
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31
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Kumari A, Muthu SA, Prakash P, Ahmad B. Herbalome of Chandraprabha vati, a polyherbal formulation of Ayurveda prevents fibrillation of lysozyme by stabilizing aggregation-prone intermediate state. Int J Biol Macromol 2020; 148:102-109. [DOI: 10.1016/j.ijbiomac.2020.01.121] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 01/09/2020] [Accepted: 01/12/2020] [Indexed: 10/25/2022]
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32
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Computational prediction and redesign of aberrant protein oligomerization. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2020; 169:43-83. [DOI: 10.1016/bs.pmbts.2019.11.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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33
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Ferreira GM, Shahfar H, Sathish HA, Remmele RL, Roberts CJ. Identifying Key Residues That Drive Strong Electrostatic Attractions between Therapeutic Antibodies. J Phys Chem B 2019; 123:10642-10653. [PMID: 31739660 DOI: 10.1021/acs.jpcb.9b08355] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Attractive electrostatic protein-protein interactions (PPI) necessarily involve identifying oppositely charged regions of the protein surface that interact favorably. This cannot be done reliably if one only considers a single protein in isolation unless there are obvious charge "patches" that result in extreme molecular dipoles. Prior work [ J. Pharm. Sci. 2019 , 108 , 120 - 132 ] identified three monoclonal antibodies (MAbs) that displayed experimental behavior ranging from net repulsive to strongly attractive electrostatic interactions. The present work provides a systematic computational approach for identifying the origin of diverse PPI, in terms of which sets of amino acids or individual amino acids are most influential, and determining if there are different patterns of pairwise amino acid interaction "maps" that result in different behaviors. The charge was eliminated computationally, one by one, for each charged residue in the wild-type sequences, which resulted in predicted changes in the second osmotic virial coefficient. The results highlight interaction "maps" that correspond to cases with qualitatively different net electrostatic PPI for the different MAbs and solution conditions, as well as key sets of residues that contribute to strongly attractive PPI. A more computationally efficient method is also proposed to identify key amino acids based on Mayer-weighted interaction energies.
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Affiliation(s)
- Glenn M Ferreira
- Department of Chemical and Biomolecular Engineering , University of Delaware , Newark , Delaware 19716 , United States
| | - Hassan Shahfar
- Department of Chemical and Biomolecular Engineering , University of Delaware , Newark , Delaware 19716 , United States.,Department of Physics and Astronomy , University of Delaware , Newark , Delaware 19716 , United States
| | | | | | - Christopher J Roberts
- Department of Chemical and Biomolecular Engineering , University of Delaware , Newark , Delaware 19716 , United States
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Computational Assessment of Bacterial Protein Structures Indicates a Selection Against Aggregation. Cells 2019; 8:cells8080856. [PMID: 31398930 PMCID: PMC6721704 DOI: 10.3390/cells8080856] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Revised: 08/05/2019] [Accepted: 08/06/2019] [Indexed: 12/14/2022] Open
Abstract
The aggregation of proteins compromises cell fitness, either because it titrates functional proteins into non-productive inclusions or because it results in the formation of toxic assemblies. Accordingly, computational proteome-wide analyses suggest that prevention of aggregation upon misfolding plays a key role in sequence evolution. Most proteins spend their lifetimes in a folded state; therefore, it is conceivable that, in addition to sequences, protein structures would have also evolved to minimize the risk of aggregation in their natural environments. By exploiting the AGGRESCAN3D structure-based approach to predict the aggregation propensity of >600 Escherichia coli proteins, we show that the structural aggregation propensity of globular proteins is connected with their abundance, length, essentiality, subcellular location and quaternary structure. These data suggest that the avoidance of protein aggregation has contributed to shape the structural properties of proteins in bacterial cells.
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35
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Wang W, Ohtake S. Science and art of protein formulation development. Int J Pharm 2019; 568:118505. [PMID: 31306712 DOI: 10.1016/j.ijpharm.2019.118505] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2019] [Revised: 07/08/2019] [Accepted: 07/08/2019] [Indexed: 02/07/2023]
Abstract
Protein pharmaceuticals have become a significant class of marketed drug products and are expected to grow steadily over the next decade. Development of a commercial protein product is, however, a rather complex process. A critical step in this process is formulation development, enabling the final product configuration. A number of challenges still exist in the formulation development process. This review is intended to discuss these challenges, to illustrate the basic formulation development processes, and to compare the options and strategies in practical formulation development.
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Affiliation(s)
- Wei Wang
- Biological Development, Bayer USA, LLC, 800 Dwight Way, Berkeley, CA 94710, United States.
| | - Satoshi Ohtake
- Pharmaceutical Research and Development, Pfizer Biotherapeutics Pharmaceutical Sciences, Chesterfield, MO 63017, United States
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36
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Navarro S, Ventura S. Computational re-design of protein structures to improve solubility. Expert Opin Drug Discov 2019; 14:1077-1088. [DOI: 10.1080/17460441.2019.1637413] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Susanna Navarro
- Institut de Biotecnologia i de Biomedicina, Parc de Recerca UAB, Mòdul B, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Salvador Ventura
- Institut de Biotecnologia i de Biomedicina, Parc de Recerca UAB, Mòdul B, Universitat Autònoma de Barcelona, Barcelona, Spain
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37
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Sifniotis V, Cruz E, Eroglu B, Kayser V. Current Advancements in Addressing Key Challenges of Therapeutic Antibody Design, Manufacture, and Formulation. Antibodies (Basel) 2019; 8:E36. [PMID: 31544842 PMCID: PMC6640721 DOI: 10.3390/antib8020036] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 05/29/2019] [Accepted: 05/31/2019] [Indexed: 12/17/2022] Open
Abstract
Therapeutic antibody technology heavily dominates the biologics market and continues to present as a significant industrial interest in developing novel and improved antibody treatment strategies. Many noteworthy advancements in the last decades have propelled the success of antibody development; however, there are still opportunities for improvement. In considering such interest to develop antibody therapies, this review summarizes the array of challenges and considerations faced in the design, manufacture, and formulation of therapeutic antibodies, such as stability, bioavailability and immunological engagement. We discuss the advancement of technologies that address these challenges, highlighting key antibody engineered formats that have been adapted. Furthermore, we examine the implication of novel formulation technologies such as nanocarrier delivery systems for the potential to formulate for pulmonary delivery. Finally, we comprehensively discuss developments in computational approaches for the strategic design of antibodies with modulated functions.
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Affiliation(s)
- Vicki Sifniotis
- School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, Sydney 2006, Australia.
| | - Esteban Cruz
- School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, Sydney 2006, Australia.
| | - Barbaros Eroglu
- School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, Sydney 2006, Australia.
| | - Veysel Kayser
- School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, Sydney 2006, Australia.
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38
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Models for Antibody Behavior in Hydrophobic Interaction Chromatography and in Self-Association. J Pharm Sci 2019; 108:1434-1441. [DOI: 10.1016/j.xphs.2018.11.035] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Revised: 11/01/2018] [Accepted: 11/19/2018] [Indexed: 11/15/2022]
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