1
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Tithi AD, Song Y, Paskaleva E, Koffas M. Biosynthesis of animal-free recombinant chondroitin sulfate E using a functional chondroitin sulfotransferase in E. coli. Appl Microbiol Biotechnol 2024; 108:440. [PMID: 39145804 PMCID: PMC11327189 DOI: 10.1007/s00253-024-13275-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Revised: 07/22/2024] [Accepted: 08/02/2024] [Indexed: 08/16/2024]
Abstract
Chondroitin sulfate E (CS-E) is a vital sulfated glycosaminoglycan with diverse biological functions and therapeutic potential. This study marks a significant milestone by achieving the first successful microbial production of chondroitin 4-sulfate 6-O-sulfotransferase (GalNAc4S-6ST) in Escherichia coli, enabling recombinant CS-E biosynthesis. Initially, we identified sulfotransferases capable of converting chondroitin sulfate A (CS-A) to CS-E, but these enzymes were non-functional when expressed in E. coli. Moreover, there is no experimentally derived three-dimensional structure available for this specific sulfotransferase in the protein databases. To overcome this challenge, we developed a 3D model of GalNAc4S-6ST using AlphaFold2 and employed PROSS stability design to identify mutations that enhance enzyme solubility and stability with different N-terminal truncations. Experimental validation of these mutations led to the identification of several functional enzymes. Among various E. coli strains tested for enzyme expression, Origami B (DE3) emerged as the most effective host. This facilitated the enzymatic conversion of CS-A to CS-E, achieving a conversion rate of over 50%, and marking the first successful biosynthesis of animal-free CS-E. These findings represent a significant advancement towards the large-scale synthesis of CS-E using cost-effective carbon sources, offering a sustainable alternative to traditional sourcing from endangered animals like sharks. KEY POINTS: • Functional expression of GalNAc4S-6ST in a simple prokaryote was accomplished. • First-time biosynthesis of animal-free chondroitin sulfate E was accomplished.
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Affiliation(s)
- Aditi Dey Tithi
- Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, 12180, USA
- Department of Chemical and Biological Engineering, Troy, NY, USA
| | - Yuefan Song
- Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, 12180, USA
| | - Elena Paskaleva
- Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, 12180, USA
| | - Mattheos Koffas
- Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, 12180, USA.
- Department of Chemical and Biological Engineering, Troy, NY, USA.
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2
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Milenkovic I, Blumenreich S, Hochfelder A, Azulay A, Biton IE, Zerbib M, Oren R, Tsoory M, Joseph T, Fleishman SJ, Futerman AH. Efficacy of an AAV vector encoding a thermostable form of glucocerebrosidase in alleviating symptoms in a Gaucher disease mouse model. Gene Ther 2024:10.1038/s41434-024-00476-8. [PMID: 39147866 DOI: 10.1038/s41434-024-00476-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 08/01/2024] [Accepted: 08/06/2024] [Indexed: 08/17/2024]
Abstract
Almost all attempts to date at gene therapy approaches for monogenetic disease have used the amino acid sequences of the natural protein. In the current study, we use a designed, thermostable form of glucocerebrosidase (GCase), the enzyme defective in Gaucher disease (GD), to attempt to alleviate neurological symptoms in a GD mouse that models type 3 disease, i.e. the chronic neuronopathic juvenile subtype. Upon injection of an AAVrh10 (adeno-associated virus, serotype rh10) vector containing the designed GCase (dGCase) into the left lateral ventricle of Gba-/-;Gbatg mice, a significant improvement in body weight and life-span was observed, compared to injection of the same mouse with the wild type enzyme (wtGCase). Moreover, a reduction in levels of glucosylceramide (GlcCer), and an increase in levels of GCase activity were seen in the right hemisphere of Gba-/-;Gbatg mice, concomitantly with a significant improvement in motor function, reduction of neuroinflammation and a reduction in mRNA levels of various genes shown previously to be elevated in the brain of mouse models of neurological forms of GD. Together, these data pave the way for the possible use of modified proteins in gene therapy for lysosomal storage diseases and other monogenetic disorders.
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Affiliation(s)
- Ivan Milenkovic
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 7610001, Israel
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Shani Blumenreich
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Ariel Hochfelder
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Aviya Azulay
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Inbal E Biton
- Department of Veterinary Resources, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Mirie Zerbib
- Department of Veterinary Resources, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Roni Oren
- Department of Veterinary Resources, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Michael Tsoory
- Department of Veterinary Resources, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Tammar Joseph
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Sarel J Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Anthony H Futerman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 7610001, Israel.
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3
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Listov D, Goverde CA, Correia BE, Fleishman SJ. Opportunities and challenges in design and optimization of protein function. Nat Rev Mol Cell Biol 2024; 25:639-653. [PMID: 38565617 PMCID: PMC7616297 DOI: 10.1038/s41580-024-00718-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/27/2024] [Indexed: 04/04/2024]
Abstract
The field of protein design has made remarkable progress over the past decade. Historically, the low reliability of purely structure-based design methods limited their application, but recent strategies that combine structure-based and sequence-based calculations, as well as machine learning tools, have dramatically improved protein engineering and design. In this Review, we discuss how these methods have enabled the design of increasingly complex structures and therapeutically relevant activities. Additionally, protein optimization methods have improved the stability and activity of complex eukaryotic proteins. Thanks to their increased reliability, computational design methods have been applied to improve therapeutics and enzymes for green chemistry and have generated vaccine antigens, antivirals and drug-delivery nano-vehicles. Moreover, the high success of design methods reflects an increased understanding of basic rules that govern the relationships among protein sequence, structure and function. However, de novo design is still limited mostly to α-helix bundles, restricting its potential to generate sophisticated enzymes and diverse protein and small-molecule binders. Designing complex protein structures is a challenging but necessary next step if we are to realize our objective of generating new-to-nature activities.
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Affiliation(s)
- Dina Listov
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Casper A Goverde
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bruno E Correia
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
| | - Sarel Jacob Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.
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4
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Cea PA, Pérez M, Herrera SM, Muñoz SM, Fuentes-Ugarte N, Coche-Miranda J, Maturana P, Guixé V, Castro-Fernandez V. Deciphering Structural Traits for Thermal and Kinetic Stability across Protein Family Evolution through Ancestral Sequence Reconstruction. Mol Biol Evol 2024; 41:msae127. [PMID: 38913681 PMCID: PMC11229819 DOI: 10.1093/molbev/msae127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 05/17/2024] [Accepted: 06/17/2024] [Indexed: 06/26/2024] Open
Abstract
Natural proteins are frequently marginally stable, and an increase in environmental temperature can easily lead to unfolding. As a result, protein engineering to improve protein stability is an area of intensive research. Nonetheless, since there is usually a high degree of structural homology between proteins from thermophilic organisms and their mesophilic counterparts, the identification of structural determinants for thermoadaptation is challenging. Moreover, in many cases, it has become clear that the success of stabilization strategies is often dependent on the evolutionary history of a protein family. In the last few years, the use of ancestral sequence reconstruction (ASR) as a tool for elucidation of the evolutionary history of functional traits of a protein family has gained strength. Here, we used ASR to trace the evolutionary pathways between mesophilic and thermophilic kinases that participate in the biosynthetic pathway of vitamin B1 in bacteria. By combining biophysics approaches, X-ray crystallography, and molecular dynamics simulations, we found that the thermal stability of these enzymes correlates with their kinetic stability, where the highest thermal/kinetic stability is given by an increase in small hydrophobic amino acids that allow a higher number of interatomic hydrophobic contacts, making this type of interaction the main support for stability in this protein architecture. The results highlight the potential benefits of using ASR to explore the evolutionary history of protein sequence and structure to identify traits responsible for the kinetic and thermal stability of any protein architecture.
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Affiliation(s)
- Pablo A Cea
- Departamento de Biología, Facultad de Ciencias, Laboratorio de Bioquímica y Biología Molecular, Universidad de Chile, Santiago, Chile
| | - Myriam Pérez
- Departamento de Biología, Facultad de Ciencias, Laboratorio de Bioquímica y Biología Molecular, Universidad de Chile, Santiago, Chile
| | - Sixto M Herrera
- Departamento de Biología, Facultad de Ciencias, Laboratorio de Bioquímica y Biología Molecular, Universidad de Chile, Santiago, Chile
| | - Sebastián M Muñoz
- Departamento de Biología, Facultad de Ciencias, Laboratorio de Bioquímica y Biología Molecular, Universidad de Chile, Santiago, Chile
| | - Nicolás Fuentes-Ugarte
- Departamento de Biología, Facultad de Ciencias, Laboratorio de Bioquímica y Biología Molecular, Universidad de Chile, Santiago, Chile
| | - José Coche-Miranda
- Departamento de Biología, Facultad de Ciencias, Laboratorio de Bioquímica y Biología Molecular, Universidad de Chile, Santiago, Chile
| | - Pablo Maturana
- Departamento de Biología, Facultad de Ciencias, Laboratorio de Bioquímica y Biología Molecular, Universidad de Chile, Santiago, Chile
| | - Victoria Guixé
- Departamento de Biología, Facultad de Ciencias, Laboratorio de Bioquímica y Biología Molecular, Universidad de Chile, Santiago, Chile
| | - Victor Castro-Fernandez
- Departamento de Biología, Facultad de Ciencias, Laboratorio de Bioquímica y Biología Molecular, Universidad de Chile, Santiago, Chile
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5
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Guan A, He Z, Wang X, Jia ZJ, Qin J. Engineering the next-generation synthetic cell factory driven by protein engineering. Biotechnol Adv 2024; 73:108366. [PMID: 38663492 DOI: 10.1016/j.biotechadv.2024.108366] [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: 11/02/2023] [Revised: 03/21/2024] [Accepted: 04/22/2024] [Indexed: 05/09/2024]
Abstract
Synthetic cell factory offers substantial advantages in economically efficient production of biofuels, chemicals, and pharmaceutical compounds. However, to create a high-performance synthetic cell factory, precise regulation of cellular material and energy flux is essential. In this context, protein components including enzymes, transcription factor-based biosensors and transporters play pivotal roles. Protein engineering aims to create novel protein variants with desired properties by modifying or designing protein sequences. This review focuses on summarizing the latest advancements of protein engineering in optimizing various aspects of synthetic cell factory, including: enhancing enzyme activity to eliminate production bottlenecks, altering enzyme selectivity to steer metabolic pathways towards desired products, modifying enzyme promiscuity to explore innovative routes, and improving the efficiency of transporters. Furthermore, the utilization of protein engineering to modify protein-based biosensors accelerates evolutionary process and optimizes the regulation of metabolic pathways. The remaining challenges and future opportunities in this field are also discussed.
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Affiliation(s)
- Ailin Guan
- College of Biomass Science and Engineering, Sichuan University, Chengdu 610065, China
| | - Zixi He
- College of Biomass Science and Engineering, Sichuan University, Chengdu 610065, China
| | - Xin Wang
- West China School of Pharmacy, Sichuan University, Chengdu 610041, China
| | - Zhi-Jun Jia
- West China School of Pharmacy, Sichuan University, Chengdu 610041, China
| | - Jiufu Qin
- College of Biomass Science and Engineering, Sichuan University, Chengdu 610065, China.
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6
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Wang J, Watson JL, Lisanza SL. Protein Design Using Structure-Prediction Networks: AlphaFold and RoseTTAFold as Protein Structure Foundation Models. Cold Spring Harb Perspect Biol 2024; 16:a041472. [PMID: 38438190 PMCID: PMC11216169 DOI: 10.1101/cshperspect.a041472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2024]
Abstract
Designing proteins with tailored structures and functions is a long-standing goal in bioengineering. Recently, deep learning advances have enabled protein structure prediction at near-experimental accuracy, which has catalyzed progress in protein design as well. We review recent studies that use structure-prediction neural networks to design proteins, via approaches such as activation maximization, inpainting, or denoising diffusion. These methods have led to major improvements over previous methods in wet-lab success rates for designing protein binders, metalloproteins, enzymes, and oligomeric assemblies. These results show that structure-prediction models are a powerful foundation for developing protein-design tools and suggest that continued improvement of their accuracy and generality will be key to unlocking the full potential of protein design.
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Affiliation(s)
- Jue Wang
- Department of Biochemistry, University of Washington, Seattle, Washington 98195, USA
- Institute for Protein Design, University of Washington, Seattle, Washington 98195, USA
- Graduate Program in Biological Physics, Structure and Design, University of Washington, Seattle, Washington 98195, USA
- DeepMind, London EC4A 3BF, United Kingdom
| | - Joseph L Watson
- Department of Biochemistry, University of Washington, Seattle, Washington 98195, USA
- Institute for Protein Design, University of Washington, Seattle, Washington 98195, USA
| | - Sidney L Lisanza
- Department of Biochemistry, University of Washington, Seattle, Washington 98195, USA
- Institute for Protein Design, University of Washington, Seattle, Washington 98195, USA
- Graduate Program in Biological Physics, Structure and Design, University of Washington, Seattle, Washington 98195, USA
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7
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Yu G, Zhao Q, Bi X, Wang J. DDAffinity: predicting the changes in binding affinity of multiple point mutations using protein 3D structure. Bioinformatics 2024; 40:i418-i427. [PMID: 38940145 PMCID: PMC11211828 DOI: 10.1093/bioinformatics/btae232] [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] [Indexed: 06/29/2024] Open
Abstract
MOTIVATION Mutations are the crucial driving force for biological evolution as they can disrupt protein stability and protein-protein interactions which have notable impacts on protein structure, function, and expression. However, existing computational methods for protein mutation effects prediction are generally limited to single point mutations with global dependencies, and do not systematically take into account the local and global synergistic epistasis inherent in multiple point mutations. RESULTS To this end, we propose a novel spatial and sequential message passing neural network, named DDAffinity, to predict the changes in binding affinity caused by multiple point mutations based on protein 3D structures. Specifically, instead of being on the whole protein, we perform message passing on the k-nearest neighbor residue graphs to extract pocket features of the protein 3D structures. Furthermore, to learn global topological features, a two-step additive Gaussian noising strategy during training is applied to blur out local details of protein geometry. We evaluate DDAffinity on benchmark datasets and external validation datasets. Overall, the predictive performance of DDAffinity is significantly improved compared with state-of-the-art baselines on multiple point mutations, including end-to-end and pre-training based methods. The ablation studies indicate the reasonable design of all components of DDAffinity. In addition, applications in nonredundant blind testing, predicting mutation effects of SARS-CoV-2 RBD variants, and optimizing human antibody against SARS-CoV-2 illustrate the effectiveness of DDAffinity. AVAILABILITY AND IMPLEMENTATION DDAffinity is available at https://github.com/ak422/DDAffinity.
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Affiliation(s)
- Guanglei Yu
- School of Computer Science and Engineering, Central South University, Changsha 410083, China
- Hunan Provincial Key Lab on Bioinformatics, Central South University, Changsha 410083, China
- Medical Engineering and Technology College, Xinjiang Medical University, Urumqi 830017, China
| | - Qichang Zhao
- School of Computer Science and Engineering, Central South University, Changsha 410083, China
- Hunan Provincial Key Lab on Bioinformatics, Central South University, Changsha 410083, China
| | - Xuehua Bi
- School of Computer Science and Engineering, Central South University, Changsha 410083, China
- Hunan Provincial Key Lab on Bioinformatics, Central South University, Changsha 410083, China
- Medical Engineering and Technology College, Xinjiang Medical University, Urumqi 830017, China
| | - Jianxin Wang
- School of Computer Science and Engineering, Central South University, Changsha 410083, China
- Hunan Provincial Key Lab on Bioinformatics, Central South University, Changsha 410083, China
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8
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Chen L, Yu K, Ma A, Zhu W, Wang H, Tang X, Tang Y, Li Y, Li J. Enhanced Thermostability of Nattokinase by Computation-Based Rational Redesign of Flexible Regions. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:14241-14254. [PMID: 38864682 DOI: 10.1021/acs.jafc.4c02335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2024]
Abstract
Nattokinase is a nutrient in healthy food natto that has the function of preventing and treating blood thrombus. However, its low thermostability and fibrinolytic activity limit its application in food and pharmaceuticals. In this study, we used bioinformatics analysis to identify two loops (loop10 and loop12) in the flexible region of nattokinase rAprY. Using this basis, we screened the G131S-S161T variant, which showed a 2.38-fold increase in half-life at 55 °C, and the M3 variant, which showed a 2.01-fold increase in activity, by using a thermostability prediction algorithm. Bioinformatics analysis revealed that the enhanced thermostability of the G131S-S161T variant was due to the increased rigidity and structural shrinkage of the overall structure. Additionally, the increased rigidity of the local region surrounding the active center and its mutated sites helps maintain its normal conformation in high-temperature environments. The increased catalytic activity of the M3 variant may be due to its more efficient substrate binding mechanism. We investigated strategies to improve the thermostability and fibrinolytic activity of nattokinase, and the resulting variants show promise for industrial production and application.
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Affiliation(s)
- Liangqi Chen
- Institute of Materia Medica, College of Pharmacy, Xinjiang University, Urumqi 830017, China
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi 830017, China
| | - Kongfang Yu
- Institute of Materia Medica, College of Pharmacy, Xinjiang University, Urumqi 830017, China
| | - Aixia Ma
- Institute of Materia Medica, College of Pharmacy, Xinjiang University, Urumqi 830017, China
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi 830017, China
| | - Wenhui Zhu
- Institute of Materia Medica, College of Pharmacy, Xinjiang University, Urumqi 830017, China
| | - Hong Wang
- Institute of Materia Medica, College of Pharmacy, Xinjiang University, Urumqi 830017, China
| | - Xiyu Tang
- Institute of Materia Medica, College of Pharmacy, Xinjiang University, Urumqi 830017, China
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi 830017, China
| | - Yaolei Tang
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi 830017, China
- The Third People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi 830000, China
| | - Yuan Li
- Institute of Materia Medica, College of Pharmacy, Xinjiang University, Urumqi 830017, China
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi 830017, China
| | - Jinyao Li
- Institute of Materia Medica, College of Pharmacy, Xinjiang University, Urumqi 830017, China
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi 830017, China
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9
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Kang ES, Kim NH, Lim HK, Jeon H, Han K, No YH, Kim K, Khaleel ZH, Shin D, Eom K, Nam J, Lee BS, Kim HJ, Suh M, Lee J, Thach TT, Hyun J, Kim YH. Structure-Guided Engineering of Thermodynamically Enhanced SaCas9 for Improved Gene Suppression. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024:e2404680. [PMID: 38944889 DOI: 10.1002/adma.202404680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Revised: 06/17/2024] [Indexed: 07/02/2024]
Abstract
Proteins with multiple domains play pivotal roles in various biological processes, necessitating a thorough understanding of their structural stability and functional interplay. Here, a structure-guided protein engineering approach is proposed to develop thermostable Cas9 (CRISPR-associated protein 9) variant for CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) interference applications. By employing thermodynamic analysis, combining distance mapping and molecular dynamics simulations, deletable domains are identified to enhance stability while preserving the DNA recognition function of Cas9. The resulting engineered Cas9, termed small and dead form Cas9, exhibits improved thermostability and maintains target DNA recognition function. Cryo-electron microscopy analysis reveals structural integrity with reduced atomic density in the deleted domain. Fusion with functional elements enables intracellular delivery and nuclear localization, demonstrating efficient gene suppression in diverse cell types. Direct delivery in the mouse brain shows enhanced knockdown efficiency, highlighting the potential of structure-guided engineering to develop functional CRISPR systems tailored for specific applications. This study underscores the significance of integrating computational and experimental approaches for protein engineering, offering insights into designing tailored molecular tools for precise biological interventions.
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Affiliation(s)
- Eun Sung Kang
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon, 16419, Republic of Korea
- IMNEWRUN INC., Suwon, 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Nam Hyeong Kim
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon, 16419, Republic of Korea
- IMNEWRUN INC., Suwon, 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Hyun-Kyoung Lim
- Biomedical Institute for Convergence at SKKU (BICS), Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Hyeyeon Jeon
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon, 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon, 16419, Republic of Korea
- Department of Nano Engineering, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Kayoung Han
- Biomedical Institute for Convergence at SKKU (BICS), Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Young Hyun No
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon, 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Kyungtae Kim
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Zinah Hilal Khaleel
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon, 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon, 16419, Republic of Korea
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, 16419, Republic of Korea
| | - Dongsun Shin
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon, 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon, 16419, Republic of Korea
- Department of Nano Engineering, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Kilho Eom
- Biomechanics Laboratory, College of Sport Science, Sungkyunkwan University (SKKU), Suwon, 16419, Republic of Korea
| | - Jiyoung Nam
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon, 16419, Republic of Korea
- IMNEWRUN INC., Suwon, 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Bok-Soo Lee
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon, 16419, Republic of Korea
- IMNEWRUN INC., Suwon, 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Han-Joo Kim
- IMNEWRUN INC., Suwon, 16419, Republic of Korea
| | - Minah Suh
- IMNEWRUN INC., Suwon, 16419, Republic of Korea
- Biomedical Institute for Convergence at SKKU (BICS), Sungkyunkwan University, Suwon, 16419, Republic of Korea
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, 16419, Republic of Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, 16419, Republic of Korea
- Department of Intelligent Precision Healthcare Convergence (IPHC), Sungkyunkwan University, Suwon, 16419, Republic of Korea
- KIST-SKKU Brain Research Center, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Jaecheol Lee
- IMNEWRUN INC., Suwon, 16419, Republic of Korea
- Biomedical Institute for Convergence at SKKU (BICS), Sungkyunkwan University, Suwon, 16419, Republic of Korea
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
- Department of Biopharmaceutical Convergence, Sungkyunkwan University, Suwon, 16419, Republic of Korea
- Department of Biohealth Regulatory Science, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | | | - Jaekyung Hyun
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Yong Ho Kim
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon, 16419, Republic of Korea
- IMNEWRUN INC., Suwon, 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon, 16419, Republic of Korea
- Biomedical Institute for Convergence at SKKU (BICS), Sungkyunkwan University, Suwon, 16419, Republic of Korea
- Department of Nano Engineering, Sungkyunkwan University, Suwon, 16419, Republic of Korea
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, 16419, Republic of Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, 16419, Republic of Korea
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10
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Schreiber S, Gercke D, Lenz F, Jose J. Application of an alchemical free energy method for the prediction of thermostable DuraPETase variants. Appl Microbiol Biotechnol 2024; 108:305. [PMID: 38643427 PMCID: PMC11033240 DOI: 10.1007/s00253-024-13144-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 03/25/2024] [Accepted: 04/09/2024] [Indexed: 04/22/2024]
Abstract
Non-equilibrium (NEQ) alchemical free energy calculations are an emerging tool for accurately predicting changes in protein folding free energy resulting from amino acid mutations. In this study, this method in combination with the Rosetta ddg monomer tool was applied to predict more thermostable variants of the polyethylene terephthalate (PET) degrading enzyme DuraPETase. The Rosetta ddg monomer tool efficiently enriched promising mutations prior to more accurate prediction by NEQ alchemical free energy calculations. The relative change in folding free energy of 96 single amino acid mutations was calculated by NEQ alchemical free energy calculation. Experimental validation of ten of the highest scoring variants identified two mutations (DuraPETaseS61M and DuraPETaseS223Y) that increased the melting temperature (Tm) of the enzyme by up to 1 °C. The calculated relative change in folding free energy showed an excellent correlation with experimentally determined Tm resulting in a Pearson's correlation coefficient of r = - 0.84. Limitations in the prediction of strongly stabilizing mutations were, however, encountered and are discussed. Despite these challenges, this study demonstrates the practical applicability of NEQ alchemical free energy calculations in prospective enzyme engineering projects. KEY POINTS: • Rosetta ddg monomer enriches stabilizing mutations in a library of DuraPETase variants • NEQ free energy calculations accurately predict changes in Tm of DuraPETase • The DuraPETase variants S223Y, S42M, and S61M have increased Tm.
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Affiliation(s)
- Sebastian Schreiber
- University of Münster, Institute of Pharmaceutical and Medicinal Chemistry, PharmaCampus, Corrensstr. 48, 48149, Münster, Germany
| | - David Gercke
- University of Münster, Institute of Pharmaceutical and Medicinal Chemistry, PharmaCampus, Corrensstr. 48, 48149, Münster, Germany
| | - Florian Lenz
- University of Münster, Institute of Pharmaceutical and Medicinal Chemistry, PharmaCampus, Corrensstr. 48, 48149, Münster, Germany
| | - Joachim Jose
- University of Münster, Institute of Pharmaceutical and Medicinal Chemistry, PharmaCampus, Corrensstr. 48, 48149, Münster, Germany.
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11
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Ertelt M, Meiler J, Schoeder CT. Combining Rosetta Sequence Design with Protein Language Model Predictions Using Evolutionary Scale Modeling (ESM) as Restraint. ACS Synth Biol 2024; 13:1085-1092. [PMID: 38568188 PMCID: PMC11036486 DOI: 10.1021/acssynbio.3c00753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Revised: 02/16/2024] [Accepted: 03/20/2024] [Indexed: 04/20/2024]
Abstract
Computational protein sequence design has the ambitious goal of modifying existing or creating new proteins; however, designing stable and functional proteins is challenging without predictability of protein dynamics and allostery. Informing protein design methods with evolutionary information limits the mutational space to more native-like sequences and results in increased stability while maintaining functions. Recently, language models, trained on millions of protein sequences, have shown impressive performance in predicting the effects of mutations. Assessing Rosetta-designed sequences with a language model showed scores that were worse than those of their original sequence. To inform Rosetta design protocols with language model predictions, we added a new metric to restrain the energy function during design using the Evolutionary Scale Modeling (ESM) model. The resulting sequences have better language model scores and similar sequence recovery, with only a minor decrease in the fitness as assessed by Rosetta energy. In conclusion, our work combines the strength of recent machine learning approaches with the Rosetta protein design toolbox.
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Affiliation(s)
- Moritz Ertelt
- Institute
for Drug Discovery, University Leipzig Medicine
Faculty, Liebigstr. 19, D-04103 Leipzig, Germany
- Center
for Scalable Data Analytics and Artificial Intelligence ScaDS.AI, D-04105 Leipzig, Germany
| | - Jens Meiler
- Institute
for Drug Discovery, University Leipzig Medicine
Faculty, Liebigstr. 19, D-04103 Leipzig, Germany
- Center
for Scalable Data Analytics and Artificial Intelligence ScaDS.AI, D-04105 Leipzig, Germany
- Department
of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United
States
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37235, United States
| | - Clara T. Schoeder
- Institute
for Drug Discovery, University Leipzig Medicine
Faculty, Liebigstr. 19, D-04103 Leipzig, Germany
- Center
for Scalable Data Analytics and Artificial Intelligence ScaDS.AI, D-04105 Leipzig, Germany
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12
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Teixeira EMGF, Kalume DE, Ferreira PF, Alves TA, Fontão APGA, Sampaio ALF, de Oliveira DR, Morgado-Díaz JA, Silva-López RE. A Novel Trypsin Kunitz-Type Inhibitor from Cajanus cajan Leaves and Its Inhibitory Activity on New Cancer Serine Proteases and Its Effect on Tumor Cell Growth. Protein J 2024; 43:333-350. [PMID: 38347326 DOI: 10.1007/s10930-023-10175-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/28/2023] [Indexed: 05/01/2024]
Abstract
A novel trypsin inhibitor from Cajanus cajan (TIC) fresh leaves was partially purified by affinity chromatography. SDS-PAGE revealed one band with about 15 kDa with expressive trypsin inhibitor activity by zymography. TIC showed high affinity for trypsin (Ki = 1.617 μM) and was a competitive inhibitor for this serine protease. TIC activity was maintained after 24 h of treatment at 70 °C, after 1 h treatments with different pH values, and β-mercaptoethanol increasing concentrations, and demonstrated expressive structural stability. However, the activity of TIC was affected in the presence of oxidizing agents. In order to study the effect of TIC on secreted serine proteases, as well as on the cell culture growth curve, SK-MEL-28 metastatic human melanoma cell line and CaCo-2 colon adenocarcinoma was grown in supplemented DMEM, and the extracellular fractions were submitted salting out and affinity chromatography to obtain new secreted serine proteases. TIC inhibited almost completely, 96 to 89%, the activity of these serine proteases and reduced the melanoma and colon adenocarcinoma cells growth of 48 and 77% respectively. Besides, it is the first time that a trypsin inhibitor was isolated and characterized from C. cajan leaves and cancer serine proteases were isolated and partial characterized from SK-MEL-28 and CaCo-2 cancer cell lines. Furthermore, TIC shown to be potent inhibitor of tumor protease affecting cell growth, and can be one potential drug candidate to be employed in chemotherapy of melanoma and colon adenocarcinoma.
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Affiliation(s)
- Erika Maria Gomes Ferreira Teixeira
- Departament of Natural Products, Institute of Pharmaceuticals Technology, FIOCRUZ, Av. Brasil 4365, Rio de Janeiro, Rio de Janeiro, 21045-900, Brazil
- Laboratory of Bioprospection and Applied Ethnopharmacology, Federal University of Rio de Janeiro, Rio de Janeiro, 21941-902, Brazil
| | - Dario Eluam Kalume
- Interdisciplinary Laboratory of Medical Research, IOC-Oswaldo Cruz Institute, FIOCRUZ, Av. Brasil 4365, Rio de Janeiro, Rio de Janeiro, CEP 21045-900, Brazil
| | - Patrícia Fernandes Ferreira
- Departament of Natural Products, Institute of Pharmaceuticals Technology, FIOCRUZ, Av. Brasil 4365, Rio de Janeiro, Rio de Janeiro, 21045-900, Brazil
| | - Thayane Aparecida Alves
- Departament of Natural Products, Institute of Pharmaceuticals Technology, FIOCRUZ, Av. Brasil 4365, Rio de Janeiro, Rio de Janeiro, 21045-900, Brazil
| | - Ana Paula G A Fontão
- Departament of Pharmacology, Institute of Pharmaceuticals Technology, FIOCRUZ, Av. Brasil 4365, Rio de Janeiro, Rio de Janeiro, CEP 21045-900, Brazil
| | - André Luís Franco Sampaio
- Departament of Pharmacology, Institute of Pharmaceuticals Technology, FIOCRUZ, Av. Brasil 4365, Rio de Janeiro, Rio de Janeiro, CEP 21045-900, Brazil
| | - Danilo Ribeiro de Oliveira
- Laboratory of Bioprospection and Applied Ethnopharmacology, Federal University of Rio de Janeiro, Rio de Janeiro, 21941-902, Brazil
| | - José Andrés Morgado-Díaz
- Cellular and Molecular Oncobiology Program, National Institute of Cancer (INCa), Rio de Janeiro, Brazil
| | - Raquel Elisa Silva-López
- Departament of Natural Products, Institute of Pharmaceuticals Technology, FIOCRUZ, Av. Brasil 4365, Rio de Janeiro, Rio de Janeiro, 21045-900, Brazil.
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13
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Liu L, Yang L, Cao S, Gao Z, Yang B, Zhang G, Zhu R, Wu D. CyclicPepedia: a knowledge base of natural and synthetic cyclic peptides. Brief Bioinform 2024; 25:bbae190. [PMID: 38678388 PMCID: PMC11056021 DOI: 10.1093/bib/bbae190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 02/28/2024] [Accepted: 04/09/2024] [Indexed: 04/30/2024] Open
Abstract
Cyclic peptides offer a range of notable advantages, including potent antibacterial properties, high binding affinity and specificity to target molecules, and minimal toxicity, making them highly promising candidates for drug development. However, a comprehensive database that consolidates both synthetically derived and naturally occurring cyclic peptides is conspicuously absent. To address this void, we introduce CyclicPepedia (https://www.biosino.org/iMAC/cyclicpepedia/), a pioneering database that encompasses 8744 known cyclic peptides. This repository, structured as a composite knowledge network, offers a wealth of information encompassing various aspects of cyclic peptides, such as cyclic peptides' sources, categorizations, structural characteristics, pharmacokinetic profiles, physicochemical properties, patented drug applications, and a collection of crucial publications. Supported by a user-friendly knowledge retrieval system and calculation tools specifically designed for cyclic peptides, CyclicPepedia will be able to facilitate advancements in cyclic peptide drug development.
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Affiliation(s)
- Lei Liu
- Department of Gastroenterology, Shanghai Tenth People's Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200072, P. R. China
| | - Liu Yang
- National Center, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, P. R. China
| | - Suqi Cao
- National Center, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, P. R. China
| | - Zhigang Gao
- Department of General Surgery, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, P. R. China
| | - Bin Yang
- Shanghai Southgene Technology Co., Ltd., Shanghai 201203, China
| | - Guoqing Zhang
- National Genomics Data Center & Bio-Med Big Data Center, Chinese Academy of Sciences Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, P. R. China
| | - Ruixin Zhu
- Department of Gastroenterology, Shanghai Tenth People's Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200072, P. R. China
| | - Dingfeng Wu
- National Center, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, P. R. China
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14
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Koch J, Romero‐Romero S, Höcker B. Stepwise introduction of stabilizing mutations reveals nonlinear additive effects in de novo TIM barrels. Protein Sci 2024; 33:e4926. [PMID: 38380781 PMCID: PMC10880431 DOI: 10.1002/pro.4926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 01/29/2024] [Accepted: 01/30/2024] [Indexed: 02/22/2024]
Abstract
Over the past decades, the TIM-barrel fold has served as a model system for the exploration of how changes in protein sequences affect their structural, stability, and functional characteristics, and moreover, how this information can be leveraged to design proteins from the ground up. After numerous attempts to design de novo proteins with this specific fold, sTIM11 was the first validated de novo design of an idealized four-fold symmetric TIM barrel. Subsequent efforts to enhance the stability of this initial design resulted in the development of DeNovoTIMs, a family of de novo TIM barrels with various stabilizing mutations. In this study, we present an investigation into the biophysical and thermodynamic effects upon introducing a varying number of stabilizing mutations per quarter along the sequence of a four-fold symmetric TIM barrel. We compared the base design DeNovoTIM0 without any stabilizing mutations with variants containing mutations in one, two, three, and all four quarters-designated TIM1q, TIM2q, TIM3q, and DeNovoTIM6, respectively. This analysis revealed a stepwise and nonlinear change in the thermodynamic properties that correlated with the number of mutated quarters, suggesting positive nonadditive effects. To shed light on the significance of the location of stabilized quarters, we engineered two variants of TIM2q which contain the same number of mutations but positioned in different quarter locations. Characterization of these TIM2q variants revealed that the mutations exhibit varying effects on the overall protein stability, contingent upon the specific region in which they are introduced. These findings emphasize that the amount and location of stabilized interfaces among the four quarters play a crucial role in shaping the conformational stability of these four-fold symmetric TIM barrels. Analysis of de novo proteins, as described in this study, enhances our understanding of how sequence variations can finely modulate stability in both naturally occurring and computationally designed proteins.
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Affiliation(s)
| | | | - Birte Höcker
- Department of BiochemistryUniversity of BayreuthBayreuthGermany
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15
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Vanella R, Küng C, Schoepfer AA, Doffini V, Ren J, Nash MA. Understanding activity-stability tradeoffs in biocatalysts by enzyme proximity sequencing. Nat Commun 2024; 15:1807. [PMID: 38418512 PMCID: PMC10902396 DOI: 10.1038/s41467-024-45630-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 01/26/2024] [Indexed: 03/01/2024] Open
Abstract
Understanding the complex relationships between enzyme sequence, folding stability and catalytic activity is crucial for applications in industry and biomedicine. However, current enzyme assay technologies are limited by an inability to simultaneously resolve both stability and activity phenotypes and to couple these to gene sequences at large scale. Here we present the development of enzyme proximity sequencing, a deep mutational scanning method that leverages peroxidase-mediated radical labeling with single cell fidelity to dissect the effects of thousands of mutations on stability and catalytic activity of oxidoreductase enzymes in a single experiment. We use enzyme proximity sequencing to analyze how 6399 missense mutations influence folding stability and catalytic activity in a D-amino acid oxidase from Rhodotorula gracilis. The resulting datasets demonstrate activity-based constraints that limit folding stability during natural evolution, and identify hotspots distant from the active site as candidates for mutations that improve catalytic activity without sacrificing stability. Enzyme proximity sequencing can be extended to other enzyme classes and provides valuable insights into biophysical principles governing enzyme structure and function.
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Affiliation(s)
- Rosario Vanella
- Institute of Physical Chemistry, Department of Chemistry, University of Basel, 4058, Basel, Switzerland.
- Department of Biosystems Science and Engineering, ETH Zurich, 4058, Basel, Switzerland.
| | - Christoph Küng
- Institute of Physical Chemistry, Department of Chemistry, University of Basel, 4058, Basel, Switzerland
- Department of Biosystems Science and Engineering, ETH Zurich, 4058, Basel, Switzerland
| | - Alexandre A Schoepfer
- Institute of Physical Chemistry, Department of Chemistry, University of Basel, 4058, Basel, Switzerland
- Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
- National Center for Competence in Research (NCCR), Catalysis, École Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
| | - Vanni Doffini
- Institute of Physical Chemistry, Department of Chemistry, University of Basel, 4058, Basel, Switzerland
- Department of Biosystems Science and Engineering, ETH Zurich, 4058, Basel, Switzerland
| | - Jin Ren
- Institute of Physical Chemistry, Department of Chemistry, University of Basel, 4058, Basel, Switzerland
- Department of Biosystems Science and Engineering, ETH Zurich, 4058, Basel, Switzerland
| | - Michael A Nash
- Institute of Physical Chemistry, Department of Chemistry, University of Basel, 4058, Basel, Switzerland.
- Department of Biosystems Science and Engineering, ETH Zurich, 4058, Basel, Switzerland.
- National Center for Competence in Research (NCCR), Molecular Systems Engineering, 4058, Basel, Switzerland.
- Swiss Nanoscience Institute, 4056, Basel, Switzerland.
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16
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Zhu T, Sun J, Pang H, Wu B. Computational Enzyme Redesign Enhances Tolerance to Denaturants for Peptide C-Terminal Amidation. JACS AU 2024; 4:788-797. [PMID: 38425901 PMCID: PMC10900485 DOI: 10.1021/jacsau.3c00792] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 01/20/2024] [Accepted: 01/22/2024] [Indexed: 03/02/2024]
Abstract
The escalating demand for biocatalysts in pharmaceutical and biochemical applications underscores the critical imperative to enhance enzyme activity and durability under high denaturant concentrations. Nevertheless, the development of a practical computational redesign protocol for improving enzyme tolerance to denaturants is challenging due to the limitations of relying solely on model-driven approaches to adequately capture denaturant-enzyme interactions. In this study, we introduce an enzyme redesign strategy termed GRAPE_DA, which integrates multiple data-driven and model-driven computational methods to mitigate the sampling biases inherent in a single approach and comprehensively predict beneficial mutations on both the protein surface and backbone. To illustrate the methodology's effectiveness, we applied it to engineer a peptidylamidoglycolate lyase, resulting in a variant exhibiting up to a 24-fold increase in peptide C-terminal amidation activity under 2.5 M guanidine hydrochloride. We anticipate that this integrated engineering strategy will facilitate the development of enzymatic peptide synthesis and functionalization under denaturing conditions and highlight the role of engineering surface residues in governing protein stability.
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Affiliation(s)
- Tong Zhu
- AIM Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Jinyuan Sun
- AIM Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Hua Pang
- AIM Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Bian Wu
- AIM Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
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17
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Huang J, Xie X, Zheng W, Xu L, Yan J, Wu Y, Yang M, Yan Y. In silico design of multipoint mutants for enhanced performance of Thermomyces lanuginosus lipase for efficient biodiesel production. BIOTECHNOLOGY FOR BIOFUELS AND BIOPRODUCTS 2024; 17:33. [PMID: 38402206 PMCID: PMC10894483 DOI: 10.1186/s13068-024-02478-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 02/15/2024] [Indexed: 02/26/2024]
Abstract
BACKGROUND Biodiesel, an emerging sustainable and renewable clean energy, has garnered considerable attention as an alternative to fossil fuels. Although lipases are promising catalysts for biodiesel production, their efficiency in industrial-scale application still requires improvement. RESULTS In this study, a novel strategy for multi-site mutagenesis in the binding pocket was developed via FuncLib (for mutant enzyme design) and Rosetta Cartesian_ddg (for free energy calculation) to improve the reaction rate and yield of lipase-catalyzed biodiesel production. Thermomyces lanuginosus lipase (TLL) with high activity and thermostability was obtained using the Pichia pastoris expression system. The specific activities of the mutants M11 and M21 (each with 5 and 4 mutations) were 1.50- and 3.10-fold higher, respectively, than those of the wild-type (wt-TLL). Their corresponding melting temperature profiles increased by 10.53 and 6.01 °C, [Formula: see text] (the temperature at which the activity is reduced to 50% after 15 min incubation) increased from 60.88 to 68.46 °C and 66.30 °C, and the optimum temperatures shifted from 45 to 50 °C. After incubation in 60% methanol for 1 h, the mutants M11 and M21 retained more than 60% activity, and 45% higher activity than that of wt-TLL. Molecular dynamics simulations indicated that the increase in thermostability could be explained by reduced atomic fluctuation, and the improved catalytic properties were attributed to a reduced binding free energy and newly formed hydrophobic interaction. Yields of biodiesel production catalyzed by mutants M11 and M21 for 48 h at an elevated temperature (50 °C) were 94.03% and 98.56%, respectively, markedly higher than that of the wt-TLL (88.56%) at its optimal temperature (45 °C) by transesterification of soybean oil. CONCLUSIONS An integrating strategy was first adopted to realize the co-evolution of catalytic efficiency and thermostability of lipase. Two promising mutants M11 and M21 with excellent properties exhibited great potential for practical applications for in biodiesel production.
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Affiliation(s)
- Jinsha Huang
- Key Laboratory of Molecular Biophysics, Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People's Republic of China
| | - Xiaoman Xie
- Key Laboratory of Molecular Biophysics, Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People's Republic of China
| | - Wanlin Zheng
- Key Laboratory of Molecular Biophysics, Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People's Republic of China
| | - Li Xu
- Key Laboratory of Molecular Biophysics, Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
| | - Jinyong Yan
- Key Laboratory of Molecular Biophysics, Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People's Republic of China
| | - Ying Wu
- Key Laboratory of Molecular Biophysics, Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People's Republic of China
| | - Min Yang
- Key Laboratory of Molecular Biophysics, Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People's Republic of China
| | - Yunjun Yan
- Key Laboratory of Molecular Biophysics, Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
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18
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Kim DN, McNaughton AD, Kumar N. Leveraging Artificial Intelligence to Expedite Antibody Design and Enhance Antibody-Antigen Interactions. Bioengineering (Basel) 2024; 11:185. [PMID: 38391671 PMCID: PMC10886287 DOI: 10.3390/bioengineering11020185] [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: 12/30/2023] [Revised: 01/30/2024] [Accepted: 02/06/2024] [Indexed: 02/24/2024] Open
Abstract
This perspective sheds light on the transformative impact of recent computational advancements in the field of protein therapeutics, with a particular focus on the design and development of antibodies. Cutting-edge computational methods have revolutionized our understanding of protein-protein interactions (PPIs), enhancing the efficacy of protein therapeutics in preclinical and clinical settings. Central to these advancements is the application of machine learning and deep learning, which offers unprecedented insights into the intricate mechanisms of PPIs and facilitates precise control over protein functions. Despite these advancements, the complex structural nuances of antibodies pose ongoing challenges in their design and optimization. Our review provides a comprehensive exploration of the latest deep learning approaches, including language models and diffusion techniques, and their role in surmounting these challenges. We also present a critical analysis of these methods, offering insights to drive further progress in this rapidly evolving field. The paper includes practical recommendations for the application of these computational techniques, supplemented with independent benchmark studies. These studies focus on key performance metrics such as accuracy and the ease of program execution, providing a valuable resource for researchers engaged in antibody design and development. Through this detailed perspective, we aim to contribute to the advancement of antibody design, equipping researchers with the tools and knowledge to navigate the complexities of this field.
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Affiliation(s)
- Doo Nam Kim
- Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352, USA
| | - Andrew D McNaughton
- Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352, USA
| | - Neeraj Kumar
- Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352, USA
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19
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Dieckhaus H, Brocidiacono M, Randolph NZ, Kuhlman B. Transfer learning to leverage larger datasets for improved prediction of protein stability changes. Proc Natl Acad Sci U S A 2024; 121:e2314853121. [PMID: 38285937 PMCID: PMC10861915 DOI: 10.1073/pnas.2314853121] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Accepted: 12/26/2023] [Indexed: 01/31/2024] Open
Abstract
Amino acid mutations that lower a protein's thermodynamic stability are implicated in numerous diseases, and engineered proteins with enhanced stability can be important in research and medicine. Computational methods for predicting how mutations perturb protein stability are, therefore, of great interest. Despite recent advancements in protein design using deep learning, in silico prediction of stability changes has remained challenging, in part due to a lack of large, high-quality training datasets for model development. Here, we describe ThermoMPNN, a deep neural network trained to predict stability changes for protein point mutations given an initial structure. In doing so, we demonstrate the utility of a recently released megascale stability dataset for training a robust stability model. We also employ transfer learning to leverage a second, larger dataset by using learned features extracted from ProteinMPNN, a deep neural network trained to predict a protein's amino acid sequence given its three-dimensional structure. We show that our method achieves state-of-the-art performance on established benchmark datasets using a lightweight model architecture that allows for rapid, scalable predictions. Finally, we make ThermoMPNN readily available as a tool for stability prediction and design.
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Affiliation(s)
- Henry Dieckhaus
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, NC27599
- Division of Chemical Biology and Medicinal Chemistry, University of North Carolina Eshelman School of Pharmacy, Chapel Hill, NC27599
| | - Michael Brocidiacono
- Division of Chemical Biology and Medicinal Chemistry, University of North Carolina Eshelman School of Pharmacy, Chapel Hill, NC27599
| | - Nicholas Z. Randolph
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, NC27599
- Department of Bioinformatics and Computational Biology, University of North Carolina School of Medicine, Chapel Hill, NC27599
| | - Brian Kuhlman
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, NC27599
- Department of Bioinformatics and Computational Biology, University of North Carolina School of Medicine, Chapel Hill, NC27599
- Lineberger Comprehensive Cancer Center, University of North Carolina School of Medicine, Chapel Hill, NC27599
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20
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Hait S, Kundu S. Revisiting structural organization of proteins at high temperature from a network perspective. Comput Biol Chem 2024; 108:107978. [PMID: 37956471 DOI: 10.1016/j.compbiolchem.2023.107978] [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: 08/01/2023] [Revised: 10/08/2023] [Accepted: 10/29/2023] [Indexed: 11/15/2023]
Abstract
Interactions between distantly placed amino acids in the primary chain (long-range) play a very crucial role in the formation and stabilization of the tertiary structure of a protein, while interactions between closely placed amino acids in the primary chain (short-range) mostly stabilize the secondary structures. Every protein needs to maintain marginal stability in order to perform its physiological functions in its native environment. The requirements for this stability in mesophilic and thermophilic proteins are different. Thermophilic proteins need to form more interactions as well as more stable interactions to survive in the extreme environment, they live in. Here, we aim to find out how the interacting amino acids in three-dimensional space are positioned in the primary chains in thermophilic and mesophilic. How does this arrangement help thermophiles to maintain their structural integrity at high temperatures? Working on a dataset of 1560 orthologous pairs we perceive that thermophiles are not only enriched with long-range interactions, they feature bigger connected clusters and higher network densities compared to their mesophilic orthologs, at higher interaction strengths between the amino acids. Moreover, we have observed the enrichment of different types of interactions at different secondary structural regions.
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Affiliation(s)
- Suman Hait
- Department of Biophysics, Molecular Biology and Bioinformatics, 92, Acharya Prafulla Chandra Road, Kolkata 700009, India.
| | - Sudip Kundu
- Department of Biophysics, Molecular Biology and Bioinformatics, 92, Acharya Prafulla Chandra Road, Kolkata 700009, India.
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21
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Li G, Yao S, Fan L. ProSTAGE: Predicting Effects of Mutations on Protein Stability by Using Protein Embeddings and Graph Convolutional Networks. J Chem Inf Model 2024; 64:340-347. [PMID: 38166383 PMCID: PMC10806799 DOI: 10.1021/acs.jcim.3c01697] [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: 10/21/2023] [Revised: 12/11/2023] [Accepted: 12/12/2023] [Indexed: 01/04/2024]
Abstract
Protein thermodynamic stability is essential to clarify the relationships among structure, function, and interaction. Therefore, developing a faster and more accurate method to predict the impact of the mutations on protein stability is helpful for protein design and understanding the phenotypic variation. Recent studies have shown that protein embedding will be particularly powerful at modeling sequence information with context dependence, such as subcellular localization, variant effect, and secondary structure prediction. Herein, we introduce a novel method, ProSTAGE, which is a deep learning method that fuses structure and sequence embedding to predict protein stability changes upon single point mutations. Our model combines graph-based techniques and language models to predict stability changes. Moreover, ProSTAGE is trained on a larger data set, which is almost twice as large as the most used S2648 data set. It consistently outperforms all existing state-of-the-art methods on mutation-affected problems as benchmarked on several independent data sets. The protein embedding as the prediction input achieves better results than the previous results, which shows the potential of protein language models in predicting the effect of mutations on proteins. ProSTAGE is implemented as a user-friendly web server.
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Affiliation(s)
- Gen Li
- Production and R&D Center
I of LSS, GenScript (Shanghai) Biotech Co.,
Ltd., Shanghai 200131, China
| | - Sijie Yao
- Production and R&D Center
I of LSS, GenScript (Shanghai) Biotech Co.,
Ltd., Shanghai 200131, China
| | - Long Fan
- Production and R&D Center
I of LSS, GenScript (Shanghai) Biotech Co.,
Ltd., Shanghai 200131, China
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22
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Hong SY, Yoon J, An YJ, Lee S, Cha HG, Pandey A, Yoo YJ, Joo JC. Statistical Analysis of the Role of Cavity Flexibility in Thermostability of Proteins. Polymers (Basel) 2024; 16:291. [PMID: 38276699 PMCID: PMC10819066 DOI: 10.3390/polym16020291] [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: 12/15/2023] [Revised: 01/14/2024] [Accepted: 01/17/2024] [Indexed: 01/27/2024] Open
Abstract
Conventional statistical investigations have primarily focused on the comparison of the simple one-dimensional characteristics of protein cavities, such as number, surface area, and volume. These studies have failed to discern the crucial distinctions in cavity properties between thermophilic and mesophilic proteins that contribute to protein thermostability. In this study, the significance of cavity properties, i.e., flexibility and location, in protein thermostability was investigated by comparing structural differences between homologous thermophilic and mesophilic proteins. Three dimensions of protein structure were categorized into three regions (core, boundary, and surface) and a comparative analysis of cavity properties using this structural index was conducted. The statistical analysis revealed that cavity flexibility is closely related to protein thermostability. The core cavities of thermophilic proteins were less flexible than those of mesophilic proteins (averaged B' factor values, -0.6484 and -0.5111), which might be less deleterious to protein thermostability. Thermophilic proteins exhibited fewer cavities in the boundary and surface regions. Notably, cavities in mesophilic proteins, across all regions, exhibited greater flexibility than those in thermophilic proteins (>95% probability). The increased flexibility of cavities in the boundary and surface regions of mesophilic proteins, as opposed to thermophilic proteins, may compromise stability. Recent protein engineering investigations involving mesophilic xylanase and protease showed results consistent with the findings of this study, suggesting that the manipulation of flexible cavities in the surface region can enhance thermostability. Consequently, our findings suggest that a rational or computational approach to the design of flexible cavities in surface or boundary regions could serve as an effective strategy to enhance the thermostability of mesophilic proteins.
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Affiliation(s)
- So Yeon Hong
- Department of Chemical and Biological Engineering, Inha Technical College, Inha-ro 100, Michuhol-gu, Incheon 22212, Republic of Korea;
| | - Jihyun Yoon
- Department of Biotechnology, The Catholic University of Korea, Bucheon-si 14662, Republic of Korea (S.L.)
| | - Young Joo An
- Department of Biotechnology, The Catholic University of Korea, Bucheon-si 14662, Republic of Korea (S.L.)
| | - Siseon Lee
- Department of Biotechnology, The Catholic University of Korea, Bucheon-si 14662, Republic of Korea (S.L.)
| | - Haeng-Geun Cha
- Department of Biotechnology, The Catholic University of Korea, Bucheon-si 14662, Republic of Korea (S.L.)
| | - Ashutosh Pandey
- Institute for Water and Wastewater Technology, Durban University of Technology, 19 Steve Biko Road, Durban 4000, South Africa;
- Department of Biotechnology, Faculty of Life Science and Technology, AKS University, Satna 485001, Madhya Pradesh, India
| | - Young Je Yoo
- School of Chemical and Biological Engineering, Seoul National University, Seoul 08826, Republic of Korea;
| | - Jeong Chan Joo
- Department of Biotechnology, The Catholic University of Korea, Bucheon-si 14662, Republic of Korea (S.L.)
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23
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Guan A, Hou Y, Yang R, Qin J. Enzyme engineering for functional lipids synthesis: recent advance and perspective. BIORESOUR BIOPROCESS 2024; 11:1. [PMID: 38647956 PMCID: PMC10992173 DOI: 10.1186/s40643-023-00723-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 12/24/2023] [Indexed: 04/25/2024] Open
Abstract
Functional lipids, primarily derived through the modification of natural lipids by various processes, are widely acknowledged for their potential to impart health benefits. In contrast to chemical methods for lipid modification, enzymatic catalysis offers distinct advantages, including high selectivity, mild operating conditions, and reduced byproduct formation. Nevertheless, enzymes face challenges in industrial applications, such as low activity, stability, and undesired selectivity. To address these challenges, protein engineering techniques have been implemented to enhance enzyme performance in functional lipid synthesis. This article aims to review recent advances in protein engineering, encompassing approaches from directed evolution to rational design, with the goal of improving the properties of lipid-modifying enzymes. Furthermore, the article explores the future prospects and challenges associated with enzyme-catalyzed functional lipid synthesis.
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Affiliation(s)
- Ailin Guan
- College of Biomass Science and Engineering, Sichuan University, Chengdu, 610065, China
| | - Yue Hou
- College of Biomass Science and Engineering, Sichuan University, Chengdu, 610065, China
| | - Run Yang
- College of Biomass Science and Engineering, Sichuan University, Chengdu, 610065, China
| | - Jiufu Qin
- College of Biomass Science and Engineering, Sichuan University, Chengdu, 610065, China.
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24
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Zheng F, Liu Y, Yang Y, Wen Y, Li M. Assessing computational tools for predicting protein stability changes upon missense mutations using a new dataset. Protein Sci 2024; 33:e4861. [PMID: 38084013 PMCID: PMC10751734 DOI: 10.1002/pro.4861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 11/14/2023] [Accepted: 12/06/2023] [Indexed: 12/28/2023]
Abstract
Insight into how mutations affect protein stability is crucial for protein engineering, understanding genetic diseases, and exploring protein evolution. Numerous computational methods have been developed to predict the impact of amino acid substitutions on protein stability. Nevertheless, comparing these methods poses challenges due to variations in their training data. Moreover, it is observed that they tend to perform better at predicting destabilizing mutations than stabilizing ones. Here, we meticulously compiled a new dataset from three recently published databases: ThermoMutDB, FireProtDB, and ProThermDB. This dataset, which does not overlap with the well-established S2648 dataset, consists of 4038 single-point mutations, including over 1000 stabilizing mutations. We assessed these mutations using 27 computational methods, including the latest ones utilizing mega-scale stability datasets and transfer learning. We excluded entries with overlap or similarity to training datasets to ensure fairness. Pearson correlation coefficients for the tested tools ranged from 0.20 to 0.53 on unseen data, and none of the methods could accurately predict stabilizing mutations, even those performing well in anti-symmetric property analysis. While most methods present consistent trends for predicting destabilizing mutations across various properties such as solvent exposure and secondary conformation, stabilizing mutations do not exhibit a clear pattern. Our study also suggests that solely addressing training dataset bias may not significantly enhance accuracy of predicting stabilizing mutations. These findings emphasize the importance of developing precise predictive methods for stabilizing mutations.
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Affiliation(s)
- Feifan Zheng
- MOE Key Laboratory of Geriatric Diseases and ImmunologySchool of Biology and Basic Medical Sciences, Suzhou Medical College of Soochow UniversitySuzhouChina
| | - Yang Liu
- MOE Key Laboratory of Geriatric Diseases and ImmunologySchool of Biology and Basic Medical Sciences, Suzhou Medical College of Soochow UniversitySuzhouChina
| | - Yan Yang
- MOE Key Laboratory of Geriatric Diseases and ImmunologySchool of Biology and Basic Medical Sciences, Suzhou Medical College of Soochow UniversitySuzhouChina
| | - Yuhao Wen
- MOE Key Laboratory of Geriatric Diseases and ImmunologySchool of Biology and Basic Medical Sciences, Suzhou Medical College of Soochow UniversitySuzhouChina
| | - Minghui Li
- MOE Key Laboratory of Geriatric Diseases and ImmunologySchool of Biology and Basic Medical Sciences, Suzhou Medical College of Soochow UniversitySuzhouChina
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25
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Salehi M. Evaluating the industrial potential of naturally occurring proteases: A focus on kinetic and thermodynamic parameters. Int J Biol Macromol 2024; 254:127782. [PMID: 37926323 DOI: 10.1016/j.ijbiomac.2023.127782] [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: 04/22/2023] [Revised: 10/07/2023] [Accepted: 10/28/2023] [Indexed: 11/07/2023]
Abstract
Thermodynamic and kinetic parameters, such as enthalpy, entropy, and free energy, are crucial in evaluating enzyme stability and activity. These parameters, including the free energy of activation (ΔG#) and the Gibbs free energy of inactivation (ΔG*), are important for predicting energy requirements and reaction rates. However, relying solely on these parameters is insufficient in selecting an enzyme for industrial processes. Numerous studies have explored the measurement of thermodynamic parameters for proteases. Unfortunately, some of the definitions and calculations of key parameters such as ΔG#, ΔG*, and substrate-binding free energy have contained significant errors. In this study, these mistakes have been addressed and corrected. Additionally, a new parameter called δ, defined as the difference between ΔG* and ΔG#, has been introduced for the first time. It is argued that δ provides a more reliable measure for predicting the potential industrial application of enzymes. The highest calculated value for δ was found to be 39.6 kJ·mol-1 at 55 °C. Furthermore, this study also presents a comprehensive collection and determination of all thermodynamic and kinetic parameters for proteases, providing researchers and professionals in the field with a valuable resource to compare and understand the relationships between these parameters and the industrial potential of enzymes.
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Affiliation(s)
- Mahmoud Salehi
- Department of Biology, Faculty of Basic Sciences and Engineering, Gonbad Kavous University, Gonbad Kavous, Iran.
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26
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Galano-Frutos JJ, Nerín-Fonz F, Sancho J. Calculation of Protein Folding Thermodynamics Using Molecular Dynamics Simulations. J Chem Inf Model 2023; 63:7791-7806. [PMID: 37955428 PMCID: PMC10751793 DOI: 10.1021/acs.jcim.3c01107] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/18/2023] [Accepted: 10/18/2023] [Indexed: 11/14/2023]
Abstract
Despite advances in artificial intelligence methods, protein folding remains in many ways an enigma to be solved. Accurate computation of protein folding energetics could help drive fields such as protein and drug design and genetic interpretation. However, the challenge of calculating the state functions governing protein folding from first-principles remains unaddressed. We present here a simple approach that allows us to accurately calculate the energetics of protein folding. It is based on computing the energy of the folded and unfolded states at different temperatures using molecular dynamics simulations. From this, two essential quantities (ΔH and ΔCp) are obtained and used to calculate the conformational stability of the protein (ΔG). With this approach, we have successfully calculated the energetics of two- and three-state proteins, representatives of the major structural classes, as well as small stability differences (ΔΔG) due to changes in solution conditions or variations in an amino acid residue.
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Affiliation(s)
- Juan J. Galano-Frutos
- Department
of Biochemistry, Molecular and Cell Biology, Faculty of Science, University of Zaragoza, 50009 Zaragoza, Spain
- Biocomputation
and Complex Systems Physics Institute (BIFI), Joint Unit GBs-CSIC, University of Zaragoza, 50018 Zaragoza, Spain
| | - Francho Nerín-Fonz
- Department
of Biochemistry, Molecular and Cell Biology, Faculty of Science, University of Zaragoza, 50009 Zaragoza, Spain
| | - Javier Sancho
- Department
of Biochemistry, Molecular and Cell Biology, Faculty of Science, University of Zaragoza, 50009 Zaragoza, Spain
- Biocomputation
and Complex Systems Physics Institute (BIFI), Joint Unit GBs-CSIC, University of Zaragoza, 50018 Zaragoza, Spain
- Aragon
Health Research Institute (IIS Aragón), 50009 Zaragoza, Spain
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27
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Sakhawat A, Khan MU, Rehman R, Khan S, Shan MA, Batool A, Javed MA, Ali Q. Natural compound targeting BDNF V66M variant: insights from in silico docking and molecular analysis. AMB Express 2023; 13:134. [PMID: 38015338 PMCID: PMC10684480 DOI: 10.1186/s13568-023-01640-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 11/09/2023] [Indexed: 11/29/2023] Open
Abstract
Brain-Derived Neurotrophic Factor (BDNF) is a neurotrophin gene family gene that encodes proteins vital for the growth, maintenance, and survival of neurons in the nervous system. The study aimed to screen natural compounds against BDNF variant (V66M), which affects memory, cognition, and mood regulation. BDNF variant (V66M) as a target structure was selected, and Vitamin D, Curcumin, Vitamin C, and Quercetin as ligands structures were taken from PubChem database. Multiple tools like AUTODOCK VINA, BIOVIA discovery studio, PyMOL, CB-dock, IMOD server, Swiss ADEMT, and Swiss predict ligands target were used to analyze binding energy, interaction, stability, toxicity, and visualize BDNF-ligand complexes. Compounds Vitamin D3, Curcumin, Vitamin C, and Quercetin with binding energies values of - 5.5, - 6.1, - 4.5, and - 6.7 kj/mol, respectively, were selected. The ligands bind to the active sites of the BDNF variant (V66M) via hydrophobic bonds, hydrogen bonds, and electrostatic interactions. Furthermore, ADMET analysis of the ligands revealed they exhibited sound pharmacokinetic and toxicity profiles. In addition, an MD simulation study showed that the most active ligand bound favorably and dynamically to the target protein, and protein-ligand complex stability was determined. The finding of this research could provide an excellent platform for discovering and rationalizing novel drugs against stress related to BDNF (V66M). Docking, preclinical drug testing and MD simulation results suggest Quercetin as a more potent BDNF variant (V66M) inhibitor and forming a more structurally stable complex.
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Affiliation(s)
- Azra Sakhawat
- Institute of Molecular Biology and Biotechnology, The University of Lahore, Lahore, Pakistan
| | - Muhammad Umer Khan
- Institute of Molecular Biology and Biotechnology, The University of Lahore, Lahore, Pakistan.
| | - Raima Rehman
- Institute of Molecular Biology and Biotechnology, The University of Lahore, Lahore, Pakistan
| | - Samiullah Khan
- Institute of Molecular Biology and Biotechnology, The University of Lahore, Lahore, Pakistan
| | - Muhammad Adnan Shan
- Centre for Applied Molecular Biology, University of the Punjab, Lahore, Pakistan
| | - Alia Batool
- Department of Plant Breeding and Genetics, Faculty of Agricultural Sciences, University of the Punjab, Lahore, Pakistan
| | - Muhammad Arshad Javed
- Department of Plant Breeding and Genetics, Faculty of Agricultural Sciences, University of the Punjab, Lahore, Pakistan
| | - Qurban Ali
- Department of Plant Breeding and Genetics, Faculty of Agricultural Sciences, University of the Punjab, Lahore, Pakistan.
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28
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Zhang J, Wang H, Luo Z, Yang Z, Zhang Z, Wang P, Li M, Zhang Y, Feng Y, Lu D, Zhu Y. Computational design of highly efficient thermostable MHET hydrolases and dual enzyme system for PET recycling. Commun Biol 2023; 6:1135. [PMID: 37945666 PMCID: PMC10636135 DOI: 10.1038/s42003-023-05523-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Accepted: 10/30/2023] [Indexed: 11/12/2023] Open
Abstract
Recently developed enzymes for the depolymerization of polyethylene terephthalate (PET) such as FAST-PETase and LCC-ICCG are inhibited by the intermediate PET product mono(2-hydroxyethyl) terephthalate (MHET). Consequently, the conversion of PET enzymatically into its constituent monomers terephthalic acid (TPA) and ethylene glycol (EG) is inefficient. In this study, a protein scaffold (1TQH) corresponding to a thermophilic carboxylesterase (Est30) was selected from the structural database and redesigned in silico. Among designs, a double variant KL-MHETase (I171K/G130L) with a similar protein melting temperature (67.58 °C) to that of the PET hydrolase FAST-PETase (67.80 °C) exhibited a 67-fold higher activity for MHET hydrolysis than FAST-PETase. A fused dual enzyme system comprising KL-MHETase and FAST-PETase exhibited a 2.6-fold faster PET depolymerization rate than FAST-PETase alone. Synergy increased the yield of TPA by 1.64 fold, and its purity in the released aromatic products reached 99.5%. In large reaction systems with 100 g/L substrate concentrations, the dual enzyme system KL36F achieved over 90% PET depolymerization into monomers, demonstrating its potential applicability in the industrial recycling of PET plastics. Therefore, a dual enzyme system can greatly reduce the reaction and separation cost for sustainable enzymatic PET recycling.
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Affiliation(s)
- Jun Zhang
- College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China
- Department of Chemical Engineering, Tsinghua University, Beijing, 100084, China
| | - Hongzhao Wang
- College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Zhaorong Luo
- Beijing Advanced Innovation Center for Soft Matter Science and Engineering, State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Zhenwu Yang
- College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Zixuan Zhang
- College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Pengyu Wang
- Department of Chemical Engineering, Tsinghua University, Beijing, 100084, China
| | - Mengyu Li
- College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Yi Zhang
- Beijing Advanced Innovation Center for Soft Matter Science and Engineering, State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Yue Feng
- Beijing Advanced Innovation Center for Soft Matter Science and Engineering, State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Diannan Lu
- Department of Chemical Engineering, Tsinghua University, Beijing, 100084, China.
| | - Yushan Zhu
- College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China.
- National Energy R&D Center for Biorefinery, Beijing University of Chemical Technology, Beijing, 100029, China.
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29
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Jung YJ, Choi JS, Ryu JY, Zhang Z, Lim YB. Cooperative Assembly of Self-Adjusting α-Helical Coiled Coils along the Length of an mRNA Chain to Form a Thermodynamically Stable Nanotube Carrier. J Am Chem Soc 2023; 145:23048-23056. [PMID: 37735109 DOI: 10.1021/jacs.3c05638] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/23/2023]
Abstract
Although mRNA delivery technology is very promising, problems in safety and transport arise due to the intrinsically low thermodynamic stability of the current mRNA carriers. Considering that mRNAs are filamentous and a nanotube is one of the most thermodynamically stable shapes among nanoassemblies, a nanotube is one of the most stable supramolecular structures that can be assembled with mRNA. Here, we develop a nanotube-shaped filamentous mRNA delivery platform that shows exceptionally high thermodynamic stability. The key to the development of the mRNA nanotube is the design of self-adjusting supramolecular building blocks (SABs) that have two disparate properties, i.e., dynamic property and stiffness, in a single molecule. The counterbalance of the dynamic property and stiffness in SABs enables the coating of mRNA by winding its way through the flexible and irregular mRNA chain via cooperative interactions. SAB nanotubes with targeting ligands installed show a high uptake efficiency in mammalian cells and controllable gene expression behavior. Thus, the mRNA nanotube provides an enabling technology toward the development of safe and stable mRNA vaccines and therapeutics.
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Affiliation(s)
- You-Jin Jung
- Department of Materials Science and Engineering, Yonsei University, Seoul 03722, Republic of Korea
| | - Jun Shik Choi
- Department of Materials Science and Engineering, Yonsei University, Seoul 03722, Republic of Korea
| | - Jung-Yeon Ryu
- Department of Materials Science and Engineering, Yonsei University, Seoul 03722, Republic of Korea
| | - Zhihao Zhang
- Department of Materials Science and Engineering, Yonsei University, Seoul 03722, Republic of Korea
| | - Yong-Beom Lim
- Department of Materials Science and Engineering, Yonsei University, Seoul 03722, Republic of Korea
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30
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Padhi AK, Kalita P, Maurya S, Poluri KM, Tripathi T. From De Novo Design to Redesign: Harnessing Computational Protein Design for Understanding SARS-CoV-2 Molecular Mechanisms and Developing Therapeutics. J Phys Chem B 2023; 127:8717-8735. [PMID: 37815479 DOI: 10.1021/acs.jpcb.3c04542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/11/2023]
Abstract
The continuous emergence of novel SARS-CoV-2 variants and subvariants serves as compelling evidence that COVID-19 is an ongoing concern. The swift, well-coordinated response to the pandemic highlights how technological advancements can accelerate the detection, monitoring, and treatment of the disease. Robust surveillance systems have been established to understand the clinical characteristics of new variants, although the unpredictable nature of these variants presents significant challenges. Some variants have shown resistance to current treatments, but innovative technologies like computational protein design (CPD) offer promising solutions and versatile therapeutics against SARS-CoV-2. Advances in computing power, coupled with open-source platforms like AlphaFold and RFdiffusion (employing deep neural network and diffusion generative models), among many others, have accelerated the design of protein therapeutics with precise structures and intended functions. CPD has played a pivotal role in developing peptide inhibitors, mini proteins, protein mimics, decoy receptors, nanobodies, monoclonal antibodies, identifying drug-resistance mutations, and even redesigning native SARS-CoV-2 proteins. Pending regulatory approval, these designed therapies hold the potential for a lasting impact on human health and sustainability. As SARS-CoV-2 continues to evolve, use of such technologies enables the ongoing development of alternative strategies, thus equipping us for the "New Normal".
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Affiliation(s)
- Aditya K Padhi
- Laboratory for Computational Biology & Biomolecular Design, School of Biochemical Engineering, Indian Institute of Technology (BHU), Varanasi 221005, Uttar Pradesh, India
| | - Parismita Kalita
- Molecular and Structural Biophysics Laboratory, Department of Biochemistry, North-Eastern Hill University, Shillong 793022, India
| | - Shweata Maurya
- Laboratory for Computational Biology & Biomolecular Design, School of Biochemical Engineering, Indian Institute of Technology (BHU), Varanasi 221005, Uttar Pradesh, India
| | - Krishna Mohan Poluri
- Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India
- Centre for Nanotechnology, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India
| | - Timir Tripathi
- Molecular and Structural Biophysics Laboratory, Department of Biochemistry, North-Eastern Hill University, Shillong 793022, India
- Department of Zoology, School of Life Sciences, North-Eastern Hill University, Shillong 793022, India
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31
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Turina P, Fariselli P, Capriotti E. K-Pro: Kinetics Data on Proteins and Mutants. J Mol Biol 2023; 435:168245. [PMID: 37625584 DOI: 10.1016/j.jmb.2023.168245] [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: 02/14/2023] [Revised: 08/16/2023] [Accepted: 08/17/2023] [Indexed: 08/27/2023]
Abstract
The study of protein folding plays a crucial role in improving our understanding of protein function and of the relationship between genetics and phenotypes. In particular, understanding the thermodynamics and kinetics of the folding process is important for uncovering the mechanisms behind human disorders caused by protein misfolding. To address this issue, it is essential to collect and curate experimental kinetic and thermodynamic data on protein folding. K-Pro is a new database designed for collecting and storing experimental kinetic data on monomeric proteins, with a two-state folding mechanism. With 1,529 records from 62 proteins corresponding to 65 structures, K-Pro contains various kinetic parameters such as the logarithm of the folding and unfolding rates, Tanford's β and the ϕ values. When available, the database also includes thermodynamic parameters associated with the kinetic data. K-Pro features a user-friendly interface that allows browsing and downloading kinetic data of interest. The graphical interface provides a visual representation of the protein and mutants, and it is cross-linked to key databases such as PDB, UniProt, and PubMed. K-Pro is open and freely accessible through https://folding.biofold.org/k-pro and supports the latest versions of popular browsers.
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Affiliation(s)
- Paola Turina
- Department of Pharmacy and Biotechnology (FaBiT), University of Bologna, Via F. Selmi 3, 40126 Bologna, Italy
| | - Piero Fariselli
- Department of Medical Sciences, University of Torino, Via Santena 19, 10126 Torino, Italy
| | - Emidio Capriotti
- Department of Pharmacy and Biotechnology (FaBiT), University of Bologna, Via F. Selmi 3, 40126 Bologna, Italy.
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32
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Khersonsky O, Goldsmith M, Zaretsky I, Hamer-Rogotner S, Dym O, Unger T, Yona M, Fridmann-Sirkis Y, Fleishman SJ. Stable Mammalian Serum Albumins Designed for Bacterial Expression. J Mol Biol 2023; 435:168191. [PMID: 37385581 DOI: 10.1016/j.jmb.2023.168191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 06/18/2023] [Accepted: 06/20/2023] [Indexed: 07/01/2023]
Abstract
Albumin is the most abundant protein in the blood serum of mammals and has essential carrier and physiological roles. Albumins are also used in a wide variety of molecular and cellular experiments and in the cultivated meat industry. Despite their importance, however, albumins are challenging for heterologous expression in microbial hosts, likely due to 17 conserved intramolecular disulfide bonds. Therefore, albumins used in research and biotechnological applications either derive from animal serum, despite severe ethical and reproducibility concerns, or from recombinant expression in yeast or rice. We use the PROSS algorithm to stabilize human and bovine serum albumins, finding that all are highly expressed in E. coli. Design accuracy is verified by crystallographic analysis of a human albumin variant with 16 mutations. This albumin variant exhibits ligand binding properties similar to those of the wild type. Remarkably, a design with 73 mutations relative to human albumin exhibits over 40 °C improved stability and is stable beyond the boiling point of water. Our results suggest that proteins with many disulfide bridges have the potential to exhibit extreme stability when subjected to design. The designed albumins may be used to make economical, reproducible, and animal-free reagents for molecular and cell biology. They also open the way to high-throughput screening to study and enhance albumin carrier properties.
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Affiliation(s)
- Olga Khersonsky
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel.
| | - Moshe Goldsmith
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Irina Zaretsky
- Antibody Engineering Unit, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Shelly Hamer-Rogotner
- Israel Structural Proteomics Center, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Orly Dym
- Israel Structural Proteomics Center, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Tamar Unger
- Israel Structural Proteomics Center, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Meital Yona
- Israel Structural Proteomics Center, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Yael Fridmann-Sirkis
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Sarel J Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel.
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33
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Chou Y, Hsieh C, Chen Y, Wang T, Wu W, Hwang C. Characterization of the pH-dependent protein stability of 3α-hydroxysteroid dehydrogenase/carbonyl reductase by differential scanning fluorimetry. Protein Sci 2023; 32:e4710. [PMID: 37354013 PMCID: PMC10357940 DOI: 10.1002/pro.4710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 06/21/2023] [Accepted: 06/21/2023] [Indexed: 06/25/2023]
Abstract
The characterization of protein stability is essential for understanding the functions of proteins. Hydroxysteroid dehydrogenase is involved in the biosynthesis of steroid hormones and the detoxification of xenobiotic carbonyl compounds. However, the stability of hydroxysteroid dehydrogenases has not yet been characterized in detail. Here, we determined the changes in Gibbs free energy, enthalpy, entropy, and heat capacity of unfolding for 3α-hydroxysteroid dehydrogenase/carbonyl reductase (3α-HSD/CR) by varying the pH and urea concentration through differential scanning fluorimetry and presented pH-dependent protein stability as a function of temperature. 3α-HSD/CR shows the maximum stability of 30.79 kJ mol-1 at 26.4°C, pH 7.6 and decreases to 7.74 kJ mol-1 at 25.7°C, pH 4.5. The change of heat capacity of 30.25 ± 1.38 kJ mol-1 K-1 is obtained from the enthalpy of denaturation as a function of melting temperature at varied pH. Two proton uptakes are linked to protein unfolding from residues with differential pKa of 4.0 and 6.5 in the native and denatured states, respectively. The large positive heat capacity change indicated that hydrophobic interactions played an important role in the folding of 3α-HSD/CR. These studies reveal the mechanism of protein unfolding in HSD and provide a convenient method to extract thermodynamic parameters for characterizing protein stability using differential scanning fluorimetry.
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Affiliation(s)
- Yun‐Hao Chou
- Graduate Institute of Medicine, College of MedicineKaohsiung Medical UniversityKaohsiungTaiwan
| | - Chia‐Lin Hsieh
- Graduate Institute of Medicine, College of MedicineKaohsiung Medical UniversityKaohsiungTaiwan
| | - Yan‐Liang Chen
- Graduate Institute of Medicine, College of MedicineKaohsiung Medical UniversityKaohsiungTaiwan
| | - Tzu‐Pin Wang
- Department of Medicinal and Applied ChemistryKaohsiung Medical UniversityKaohsiungTaiwan
| | - Wen‐Jeng Wu
- Department of Urology, Chung‐Ho Memorial HospitalKaohsiung Medical UniversityKaohsiungTaiwan
| | - Chi‐Ching Hwang
- Graduate Institute of Medicine, College of MedicineKaohsiung Medical UniversityKaohsiungTaiwan
- Department of Biochemistry, Faculty of Medicine, College of MedicineKaohsiung Medical UniversityKaohsiungTaiwan
- Department of Medical ResearchKaohsiung Medical University HospitalKaohsiungTaiwan
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34
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Dieckhaus H, Brocidiacono M, Randolph N, Kuhlman B. Transfer learning to leverage larger datasets for improved prediction of protein stability changes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.27.550881. [PMID: 37547004 PMCID: PMC10402116 DOI: 10.1101/2023.07.27.550881] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Amino acid mutations that lower a protein's thermodynamic stability are implicated in numerous diseases, and engineered proteins with enhanced stability are important in research and medicine. Computational methods for predicting how mutations perturb protein stability are therefore of great interest. Despite recent advancements in protein design using deep learning, in silico prediction of stability changes has remained challenging, in part due to a lack of large, high-quality training datasets for model development. Here we introduce ThermoMPNN, a deep neural network trained to predict stability changes for protein point mutations given an initial structure. In doing so, we demonstrate the utility of a newly released mega-scale stability dataset for training a robust stability model. We also employ transfer learning to leverage a second, larger dataset by using learned features extracted from a deep neural network trained to predict a protein's amino acid sequence given its three-dimensional structure. We show that our method achieves competitive performance on established benchmark datasets using a lightweight model architecture that allows for rapid, scalable predictions. Finally, we make ThermoMPNN readily available as a tool for stability prediction and design.
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Affiliation(s)
- Henry Dieckhaus
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
- Division of Chemical Biology and Medicinal Chemistry, University of North Carolina Eshelman School of Pharmacy, Chapel Hill, North Carolina, USA
| | - Michael Brocidiacono
- Division of Chemical Biology and Medicinal Chemistry, University of North Carolina Eshelman School of Pharmacy, Chapel Hill, North Carolina, USA
| | - Nicholas Randolph
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
- Department of Bioinformatics and Computational Biology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Brian Kuhlman
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
- Department of Bioinformatics and Computational Biology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
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35
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Ansbacher T, Tohar R, Cohen A, Cohen O, Levartovsky S, Arieli A, Matalon S, Bar DZ, Gal M, Weinberg E. A novel computationally engineered collagenase reduces the force required for tooth extraction in an ex-situ porcine jaw model. J Biol Eng 2023; 17:47. [PMID: 37461028 DOI: 10.1186/s13036-023-00366-4] [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: 05/07/2023] [Accepted: 07/05/2023] [Indexed: 07/20/2023] Open
Abstract
The currently employed tooth extraction methods in dentistry involve mechanical disruption of the periodontal ligament fibers, leading to inevitable trauma to the bundle bone comprising the socket walls. In our previous work, we have shown that a recombinantly expressed truncated version of clostridial collagenase G (ColG) purified from Escherichia coli efficiently reduced the force needed for tooth extraction in an ex-situ porcine jaw model, when injected into the periodontal ligament. Considering that enhanced thermostability often leads to higher enzymatic activity and to set the basis for additional rounds of optimization, we used a computational protein design approach to generate an enzyme to be more thermostable while conserving the key catalytic residues. This process generated a novel collagenase (ColG-variant) harboring sixteen mutations compared to ColG, with a nearly 4℃ increase in melting temperature. Herein, we explored the potential of ColG-variant to further decrease the physical effort required for tooth delivery using our established ex-situ porcine jaw model. An average reduction of 11% was recorded in the force applied to extract roots of mandibular split first and second premolar teeth treated with ColG-variant, relative to those treated with ColG. Our results show for the first time the potential of engineering enzyme properties for dental medicine and further contribute to minimally invasive tooth extraction.
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Affiliation(s)
- Tamar Ansbacher
- Department of Oral Biology, Goldschleger School of Dental Medicine, Faculty of Medicine, Tel Aviv University, 6997801, Tel Aviv, Israel
- Hadassah Academic College, 91010, Jerusalem, Israel
| | - Ran Tohar
- Department of Oral Biology, Goldschleger School of Dental Medicine, Faculty of Medicine, Tel Aviv University, 6997801, Tel Aviv, Israel
| | - Adi Cohen
- Department of Oral Biology, Goldschleger School of Dental Medicine, Faculty of Medicine, Tel Aviv University, 6997801, Tel Aviv, Israel
| | - Orel Cohen
- Department of Oral Biology, Goldschleger School of Dental Medicine, Faculty of Medicine, Tel Aviv University, 6997801, Tel Aviv, Israel
| | - Shifra Levartovsky
- Department of Oral Rehabilitation, Goldschleger School of Dental Medicine, Faculty of Medicine, Tel Aviv University, 6997801, Tel Aviv, Israel
| | - Adi Arieli
- Department of Oral Rehabilitation, Goldschleger School of Dental Medicine, Faculty of Medicine, Tel Aviv University, 6997801, Tel Aviv, Israel
| | - Shlomo Matalon
- Department of Oral Rehabilitation, Goldschleger School of Dental Medicine, Faculty of Medicine, Tel Aviv University, 6997801, Tel Aviv, Israel
| | - Daniel Z Bar
- Department of Oral Biology, Goldschleger School of Dental Medicine, Faculty of Medicine, Tel Aviv University, 6997801, Tel Aviv, Israel
| | - Maayan Gal
- Department of Oral Biology, Goldschleger School of Dental Medicine, Faculty of Medicine, Tel Aviv University, 6997801, Tel Aviv, Israel.
| | - Evgeny Weinberg
- Department of Oral Biology, Goldschleger School of Dental Medicine, Faculty of Medicine, Tel Aviv University, 6997801, Tel Aviv, Israel.
- Department of Periodontology and Oral Implantology, Goldschleger School of Dental Medicine, Faculty of Medicine, Tel Aviv University, 6997801, Tel Aviv, Israel.
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36
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Sun Q, He X, Fu Y. The "Beacon" Structural Model of Protein Folding: Application for Trp-Cage in Water. Molecules 2023; 28:5164. [PMID: 37446826 DOI: 10.3390/molecules28135164] [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: 05/30/2023] [Revised: 06/30/2023] [Accepted: 06/30/2023] [Indexed: 07/15/2023] Open
Abstract
Protein folding is a process in which a polypeptide must undergo folding process to obtain its three-dimensional structure. Thermodynamically, it is a process of enthalpy to overcome the loss of conformational entropy in folding. Folding is primarily related to hydrophobic interactions and intramolecular hydrogen bondings. During folding, hydrophobic interactions are regarded to be the driving forces, especially in the initial structural collapse of a protein. Additionally, folding is guided by the strong interactions within proteins, such as intramolecular hydrogen bondings related to the α-helices and β-sheets of proteins. Therefore, a protein is divided into the folding key (FK) regions related to intramolecular hydrogen bondings and the non-folding key (non-FK) regions. Various conformations are expected for FK and non-FK regions. Different from non-FK regions, it is necessary for FK regions to form the specific conformations in folding, which are regarded as the necessary folding pathways (or "beacons"). Additionally, sequential folding is expected for the FK regions, and the intermediate state is found during folding. They are reflected on the local basins in the free energy landscape (FEL) of folding. To demonstrate the structural model, molecular dynamics (MD) simulations are conducted on the folding pathway of the TRP-cage in water.
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Affiliation(s)
- Qiang Sun
- Key Laboratory of Orogenic Belts and Crustal Evolution, Ministry of Education, The School of Earth and Space Sciences, Peking University, Beijing 100871, China
| | - Xian He
- Key Laboratory of Orogenic Belts and Crustal Evolution, Ministry of Education, The School of Earth and Space Sciences, Peking University, Beijing 100871, China
| | - Yanfang Fu
- Key Laboratory of Orogenic Belts and Crustal Evolution, Ministry of Education, The School of Earth and Space Sciences, Peking University, Beijing 100871, China
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37
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Weinstein JY, Martí-Gómez C, Lipsh-Sokolik R, Hoch SY, Liebermann D, Nevo R, Weissman H, Petrovich-Kopitman E, Margulies D, Ivankov D, McCandlish DM, Fleishman SJ. Designed active-site library reveals thousands of functional GFP variants. Nat Commun 2023; 14:2890. [PMID: 37210560 DOI: 10.1038/s41467-023-38099-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 04/13/2023] [Indexed: 05/22/2023] Open
Abstract
Mutations in a protein active site can lead to dramatic and useful changes in protein activity. The active site, however, is sensitive to mutations due to a high density of molecular interactions, substantially reducing the likelihood of obtaining functional multipoint mutants. We introduce an atomistic and machine-learning-based approach, called high-throughput Functional Libraries (htFuncLib), that designs a sequence space in which mutations form low-energy combinations that mitigate the risk of incompatible interactions. We apply htFuncLib to the GFP chromophore-binding pocket, and, using fluorescence readout, recover >16,000 unique designs encoding as many as eight active-site mutations. Many designs exhibit substantial and useful diversity in functional thermostability (up to 96 °C), fluorescence lifetime, and quantum yield. By eliminating incompatible active-site mutations, htFuncLib generates a large diversity of functional sequences. We envision that htFuncLib will be used in one-shot optimization of activity in enzymes, binders, and other proteins.
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Affiliation(s)
| | - Carlos Martí-Gómez
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
| | - Rosalie Lipsh-Sokolik
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Shlomo Yakir Hoch
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Demian Liebermann
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Reinat Nevo
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Haim Weissman
- Department of Molecular Chemistry and Materials Science, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | | | - David Margulies
- Department of Chemical and Structural Biology, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Dmitry Ivankov
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - David M McCandlish
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
| | - Sarel J Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 7610001, Israel.
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38
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Chen Z, Wang X, Chen X, Huang J, Wang C, Wang J, Wang Z. Accelerating therapeutic protein design with computational approaches toward the clinical stage. Comput Struct Biotechnol J 2023; 21:2909-2926. [PMID: 38213894 PMCID: PMC10781723 DOI: 10.1016/j.csbj.2023.04.027] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/11/2023] [Accepted: 04/27/2023] [Indexed: 01/13/2024] Open
Abstract
Therapeutic protein, represented by antibodies, is of increasing interest in human medicine. However, clinical translation of therapeutic protein is still largely hindered by different aspects of developability, including affinity and selectivity, stability and aggregation prevention, solubility and viscosity reduction, and deimmunization. Conventional optimization of the developability with widely used methods, like display technologies and library screening approaches, is a time and cost-intensive endeavor, and the efficiency in finding suitable solutions is still not enough to meet clinical needs. In recent years, the accelerated advancement of computational methodologies has ushered in a transformative era in the field of therapeutic protein design. Owing to their remarkable capabilities in feature extraction and modeling, the integration of cutting-edge computational strategies with conventional techniques presents a promising avenue to accelerate the progression of therapeutic protein design and optimization toward clinical implementation. Here, we compared the differences between therapeutic protein and small molecules in developability and provided an overview of the computational approaches applicable to the design or optimization of therapeutic protein in several developability issues.
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Affiliation(s)
- Zhidong Chen
- Department of Pathology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518033, China
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Xinpei Wang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Xu Chen
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Juyang Huang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Chenglin Wang
- Shenzhen Qiyu Biotechnology Co., Ltd, Shenzhen 518107, China
| | - Junqing Wang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Zhe Wang
- Department of Pathology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518033, China
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39
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Zelnik ID, Mestre B, Weinstein JJ, Dingjan T, Izrailov S, Ben-Dor S, Fleishman SJ, Futerman AH. Computational design and molecular dynamics simulations suggest the mode of substrate binding in ceramide synthases. Nat Commun 2023; 14:2330. [PMID: 37087500 PMCID: PMC10122649 DOI: 10.1038/s41467-023-38047-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 04/13/2023] [Indexed: 04/24/2023] Open
Abstract
Until now, membrane-protein stabilization has relied on iterations of mutations and screening. We now validate a one-step algorithm, mPROSS, for stabilizing membrane proteins directly from an AlphaFold2 model structure. Applied to the lipid-generating enzyme, ceramide synthase, 37 designed mutations lead to a more stable form of human CerS2. Together with molecular dynamics simulations, we propose a pathway by which substrates might be delivered to the ceramide synthases.
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Affiliation(s)
- Iris D Zelnik
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Beatriz Mestre
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Jonathan J Weinstein
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Tamir Dingjan
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Stav Izrailov
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Shifra Ben-Dor
- Life Sciences Core Facilities, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Sarel J Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Anthony H Futerman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel.
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40
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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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41
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Roda S, Terholsen H, Meyer JRH, Cañellas-Solé A, Guallar V, Bornscheuer U, Kazemi M. AsiteDesign: a Semirational Algorithm for an Automated Enzyme Design. J Phys Chem B 2023; 127:2661-2670. [PMID: 36944360 PMCID: PMC10068746 DOI: 10.1021/acs.jpcb.2c07091] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
With advances in protein structure predictions, the number of available high-quality structures has increased dramatically. In light of these advances, structure-based enzyme engineering is expected to become increasingly important for optimizing biocatalysts for industrial processes. Here, we present AsiteDesign, a Monte Carlo-based protocol for structure-based engineering of active sites. AsiteDesign provides a framework for introducing new catalytic residues in a given binding pocket to either create a new catalytic activity or alter the existing one. AsiteDesign is implemented using pyRosetta and incorporates enhanced sampling techniques to efficiently explore the search space. The protocol was tested by designing an alternative catalytic triad in the active site of Pseudomonas fluorescens esterase (PFE). The designed variant was experimentally verified to be active, demonstrating that AsiteDesign can find alternative catalytic triads. Additionally, the AsiteDesign protocol was employed to enhance the hydrolysis of a bulky chiral substrate (1-phenyl-2-pentyl acetate) by PFE. The experimental verification of the designed variants demonstrated that F158L/F198A and F125A/F158L mutations increased the hydrolysis of 1-phenyl-2-pentyl acetate from 8.9 to 66.7 and 23.4%, respectively, and reversed the enantioselectivity of the enzyme from (R) to (S)-enantiopreference, with 32 and 55% enantiomeric excess (ee), respectively.
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Affiliation(s)
- Sergi Roda
- Barcelona Supercomputing Center (BSC), Plaça d'Eusebi Güell, 1-3, Barcelona 08034, Spain
| | - Henrik Terholsen
- Department of Biotechnology & Enzyme Catalysis, Institute of Biochemistry, University of Greifswald, Felix-Hausdorff-Str. 4, D-17487 Greifswald, Germany
| | - Jule Ruth Heike Meyer
- Department of Biotechnology & Enzyme Catalysis, Institute of Biochemistry, University of Greifswald, Felix-Hausdorff-Str. 4, D-17487 Greifswald, Germany
| | - Albert Cañellas-Solé
- Barcelona Supercomputing Center (BSC), Plaça d'Eusebi Güell, 1-3, Barcelona 08034, Spain
| | - Victor Guallar
- Barcelona Supercomputing Center (BSC), Plaça d'Eusebi Güell, 1-3, Barcelona 08034, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig de Lluís Companys, 23, Barcelona 08010, Spain
| | - Uwe Bornscheuer
- Department of Biotechnology & Enzyme Catalysis, Institute of Biochemistry, University of Greifswald, Felix-Hausdorff-Str. 4, D-17487 Greifswald, Germany
| | - Masoud Kazemi
- Barcelona Supercomputing Center (BSC), Plaça d'Eusebi Güell, 1-3, Barcelona 08034, Spain
- Biomatter Designs, Žirmu̅n̨ g. 139A, Vilnius 09120, Lithuania
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42
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Oh J, Durai P, Kannan P, Park J, Yeon YJ, Lee WK, Park K, Seo MH. Domain-wise dissection of thermal stability enhancement in multidomain proteins. Int J Biol Macromol 2023; 237:124141. [PMID: 36958447 DOI: 10.1016/j.ijbiomac.2023.124141] [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: 12/08/2022] [Revised: 03/17/2023] [Accepted: 03/19/2023] [Indexed: 03/25/2023]
Abstract
Stability is critical for the proper functioning of all proteins. Optimization of protein thermostability is a key step in the development of industrial enzymes and biologics. Herein, we demonstrate that multidomain proteins can be stabilized significantly using domain-based engineering followed by the recombination of the optimized domains. Domain-level analysis of designed protein variants with similar structures but different thermal profiles showed that the independent enhancement of the thermostability of a constituent domain improves the overall stability of the whole multidomain protein. The crystal structure and AlphaFold-predicted model of the designed proteins via domain-recombination provided a molecular explanation for domain-based stepwise stabilization. Our study suggests that domain-based modular engineering can minimize the sequence space for calculations in computational design and experimental errors, thereby offering useful guidance for multidomain protein engineering.
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Affiliation(s)
- Jisung Oh
- Natural Product Research Center, Korea Institute of Science and Technology, Gangneung 25451, South Korea; Department of Biochemical Engineering, Gangneung-Wonju National University, Gangneung 25457, South Korea
| | - Prasannavenkatesh Durai
- Natural Product Informatics Research Center, Korea Institute of Science and Technology, Gangneung 25451, South Korea
| | - Priyadharshini Kannan
- Natural Product Informatics Research Center, Korea Institute of Science and Technology, Gangneung 25451, South Korea
| | - Jaehui Park
- College of Pharmacy, Chungbuk National University, Chungbuk 28160, South Korea
| | - Young Joo Yeon
- Department of Biochemical Engineering, Gangneung-Wonju National University, Gangneung 25457, South Korea
| | - Won-Kyu Lee
- New Drug Development Center, Osong Medical Innovation Foundation, Chungbuk 28160, South Korea
| | - Keunwan Park
- Natural Product Informatics Research Center, Korea Institute of Science and Technology, Gangneung 25451, South Korea.
| | - Moon-Hyeong Seo
- Natural Product Research Center, Korea Institute of Science and Technology, Gangneung 25451, South Korea.
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43
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Lihan M, Lupyan D, Oehme D. Target-template relationships in protein structure prediction and their effect on the accuracy of thermostability calculations. Protein Sci 2023; 32:e4557. [PMID: 36573828 PMCID: PMC9878467 DOI: 10.1002/pro.4557] [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: 09/20/2022] [Revised: 12/22/2022] [Accepted: 12/23/2022] [Indexed: 12/28/2022]
Abstract
Improving protein thermostability has been a labor- and time-consuming process in industrial applications of protein engineering. Advances in computational approaches have facilitated the development of more efficient strategies to allow the prioritization of stabilizing mutants. Among these is FEP+, a free energy perturbation implementation that uses a thoroughly tested physics-based method to achieve unparalleled accuracy in predicting changes in protein thermostability. To gauge the applicability of FEP+ to situations where crystal structures are unavailable, here we have applied the FEP+ approach to homology models of 12 different proteins covering 316 mutations. By comparing predictions obtained with homology models to those obtained using crystal structures, we have identified that local rather than global sequence conservation between target and template sequence is a determining factor in the accuracy of predictions. By excluding mutation sites with low local sequence identity (<40%) to a template structure, we have obtained predictions with comparable performance to crystal structures (R2 of 0.67 and 0.63 and an RMSE of 1.20 and 1.16 kcal/mol for crystal structure and homology model predictions, respectively) for identifying stabilizing mutations when incorporating residue scanning into a cascade screening strategy. Additionally, we identify and discuss inherent limitations in sequence alignments and homology modeling protocols that translate into the poor FEP+ performance of a few select examples. Overall, our retrospective study provides detailed guidelines for the application of the FEP+ approach using homology models for protein thermostability predictions, which will greatly extend this approach to studies that were previously limited by structure availability.
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Affiliation(s)
- Muyun Lihan
- NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, and Center for Biophysics and Quantitative BiologyUniversity of Illinois Urbana‐ChampaignUrbanaIllinoisUSA
- Schrödinger Inc.CambridgeMassachusettsUSA
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44
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Lipsh-Sokolik R, Khersonsky O, Schröder SP, de Boer C, Hoch SY, Davies GJ, Overkleeft HS, Fleishman SJ. Combinatorial assembly and design of enzymes. Science 2023; 379:195-201. [PMID: 36634164 DOI: 10.1126/science.ade9434] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
The design of structurally diverse enzymes is constrained by long-range interactions that are necessary for accurate folding. We introduce an atomistic and machine learning strategy for the combinatorial assembly and design of enzymes (CADENZ) to design fragments that combine with one another to generate diverse, low-energy structures with stable catalytic constellations. We applied CADENZ to endoxylanases and used activity-based protein profiling to recover thousands of structurally diverse enzymes. Functional designs exhibit high active-site preorganization and more stable and compact packing outside the active site. Implementing these lessons into CADENZ led to a 10-fold improved hit rate and more than 10,000 recovered enzymes. This design-test-learn loop can be applied, in principle, to any modular protein family, yielding huge diversity and general lessons on protein design principles.
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Affiliation(s)
- R Lipsh-Sokolik
- Department of Biomolecular Sciences, Weizmann Institute of Science, 7610001 Rehovot, Israel
| | - O Khersonsky
- Department of Biomolecular Sciences, Weizmann Institute of Science, 7610001 Rehovot, Israel
| | - S P Schröder
- Leiden Institute of Chemistry, Leiden University, Einsteinweg 55, 2300 RA Leiden, Netherlands
| | - C de Boer
- Leiden Institute of Chemistry, Leiden University, Einsteinweg 55, 2300 RA Leiden, Netherlands
| | - S-Y Hoch
- Department of Biomolecular Sciences, Weizmann Institute of Science, 7610001 Rehovot, Israel
| | - G J Davies
- York Structural Biology Laboratory, Department of Chemistry, The University of York, Heslington, York YO10 5DD, UK
| | - H S Overkleeft
- Leiden Institute of Chemistry, Leiden University, Einsteinweg 55, 2300 RA Leiden, Netherlands
| | - S J Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, 7610001 Rehovot, Israel
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45
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Haji-Allahverdipoor K, Jalali Javaran M, Rashidi Monfared S, Khadem-Erfan MB, Nikkhoo B, Bahrami Rad Z, Eslami H, Nasseri S. Insights Into The Effects of Amino Acid Substitutions on The Stability of Reteplase Structure: A Molecular Dynamics Simulation Study. IRANIAN JOURNAL OF BIOTECHNOLOGY 2023; 21:e3175. [PMID: 36811105 PMCID: PMC9938932 DOI: 10.30498/ijb.2022.308798.3175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 07/06/2022] [Indexed: 02/24/2023]
Abstract
Background Reteplase (recombinant plasminogen activator, r-PA) is a recombinant protein designed to imitate the endogenous tissue plasminogen activator and catalyze the plasmin production. It is known that the application of reteplase is limited by the complex production processes and protein's stability challenges. Computational redesign of proteins has gained momentum in recent years, particularly as a powerful tool for improving protein stability and consequently its production efficiency. Hence, in the current study, we implemented computational approaches to improve r-PA conformational stability, which fairly correlates with protein's resistance to proteolysis. Objectives The current study was developed in order to evaluate the effect of amino acid substitutions on the stability of reteplase structure using molecular dynamic simulations and computational predictions. Materials and Methods Several web servers designed for mutation analysis were utilized to select appropriate mutations. Additionally, the experimentally reported mutation, R103S, converting wild type r-PA into non-cleavable form, was also employed. Firstly, mutant collection, consisting of 15 structures, was constructed based on the combinations of four designated mutations. Then, 3D structures were generated using MODELLER. Finally, 17 independent 20-ns molecular dynamics (MD) simulations were conducted and different analysis were performed like root-mean-square deviation (RMSD), root-mean-square fluctuations (RMSF), secondary structure analysis, number of hydrogen bonds, principal components analysis (PCA), eigenvector projection, and density analysis. Results Predicted mutations successfully compensated the more flexible conformation caused by R103S substitution, so, improved conformational stability was analyzed from MD simulations. In particular, R103S/A286I/G322I indicated the best results and remarkably enhanced the protein stability. Conclusion The conformational stability conferred by these mutations will probably lead to more protection of r-PA in protease-rich environments in various recombinant systems and potentially enhance its production and expression level.
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Affiliation(s)
- Kaveh Haji-Allahverdipoor
- Cellular and Molecular Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran
| | - Mokhtar Jalali Javaran
- Department of Biotechnology, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran
| | - Sajad Rashidi Monfared
- Department of Biotechnology, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran
| | - Mohamad Bagher Khadem-Erfan
- Cellular and Molecular Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran
| | - Bahram Nikkhoo
- Cellular and Molecular Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran
| | - Zhila Bahrami Rad
- Cellular and Molecular Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran
| | - Habib Eslami
- Department of Pharmacology and Toxicology, School of Pharmacy, Hormozgan University of Medicinal sciences, Bandar Abbas, Iran
| | - Sherko Nasseri
- Cellular and Molecular Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran
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46
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Khan T, Raza S. Exploration of Computational Aids for Effective Drug Designing and Management of Viral Diseases: A Comprehensive Review. Curr Top Med Chem 2023; 23:1640-1663. [PMID: 36725827 DOI: 10.2174/1568026623666230201144522] [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: 06/21/2022] [Revised: 11/14/2022] [Accepted: 12/19/2022] [Indexed: 02/03/2023]
Abstract
BACKGROUND Microbial diseases, specifically originating from viruses are the major cause of human mortality all over the world. The current COVID-19 pandemic is a case in point, where the dynamics of the viral-human interactions are still not completely understood, making its treatment a case of trial and error. Scientists are struggling to devise a strategy to contain the pandemic for over a year and this brings to light the lack of understanding of how the virus grows and multiplies in the human body. METHODS This paper presents the perspective of the authors on the applicability of computational tools for deep learning and understanding of host-microbe interaction, disease progression and management, drug resistance and immune modulation through in silico methodologies which can aid in effective and selective drug development. The paper has summarized advances in the last five years. The studies published and indexed in leading databases have been included in the review. RESULTS Computational systems biology works on an interface of biology and mathematics and intends to unravel the complex mechanisms between the biological systems and the inter and intra species dynamics using computational tools, and high-throughput technologies developed on algorithms, networks and complex connections to simulate cellular biological processes. CONCLUSION Computational strategies and modelling integrate and prioritize microbial-host interactions and may predict the conditions in which the fine-tuning attenuates. These microbial-host interactions and working mechanisms are important from the aspect of effective drug designing and fine- tuning the therapeutic interventions.
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Affiliation(s)
- Tahmeena Khan
- Department of Chemistry, Integral University, Lucknow, 226026, U.P., India
| | - Saman Raza
- Department of Chemistry, Isabella Thoburn College, Lucknow, 226007, U.P., India
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47
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Sanchez-Fernandez A, Basic M, Xiang J, Prevost S, Jackson AJ, Dicko C. Hydration in Deep Eutectic Solvents Induces Non-monotonic Changes in the Conformation and Stability of Proteins. J Am Chem Soc 2022; 144:23657-23667. [PMID: 36524921 PMCID: PMC9801427 DOI: 10.1021/jacs.2c11190] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The preservation of labile biomolecules presents a major challenge in chemistry, and deep eutectic solvents (DESs) have emerged as suitable environments for this purpose. However, how the hydration of DESs impacts the behavior of proteins is often neglected. Here, we demonstrate that the amino acid environment and secondary structure of two proteins (bovine serum albumin and lysozyme) and an antibody (immunoglobulin G) in 1:2 choline chloride:glycerol and 1:2 choline chloride:urea follow a re-entrant behavior with solvent hydration. A dome-shaped transition is observed with a folded or partially folded structure at very low (<10 wt % H2O) and high (>40 wt % H2O) DES hydration, while protein unfolding increases between those regimes. Hydration also affects protein conformation and stability, as demonstrated for bovine serum albumin in hydrated 1:2 choline chloride:glycerol. In the neat DES, bovine serum albumin remains partially folded and unexpectedly undergoes unfolding and oligomerization at low water content. At intermediate hydration, the protein begins to refold and gradually retrieves the native monomer-dimer equilibrium. However, ca. 36 wt % H2O is required to recover the native folding fully. The half-denaturation temperature of the protein increases with decreasing hydration, but even the dilute DESs significantly enhance the thermal stability of bovine serum albumin. Also, protein unfolding can be reversed by rehydrating the sample to the high hydration regime, also recovering protein function. This correlation provides a new perspective to understanding protein behavior in hydrated DESs, where quantifying the DES hydration becomes imperative to identifying the folding and stability of proteins.
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Affiliation(s)
- Adrian Sanchez-Fernandez
- Centro
Singular de Investigación en Química Biolóxica
e Materiais Moleculares (CIQUS), Universidade
de Santiago de Compostela, Rúa de Jenaro de la Fuente, s/n, Santiago de Compostela 15705, Spain,Food
Technology, Engineering and Nutrition, Lund
University, Box 124, Lund 221 00, Sweden,
| | - Medina Basic
- Food
Technology, Engineering and Nutrition, Lund
University, Box 124, Lund 221 00, Sweden
| | - Jenny Xiang
- Food
Technology, Engineering and Nutrition, Lund
University, Box 124, Lund 221 00, Sweden
| | - Sylvain Prevost
- Institut
Laue-Langevin, DS / LSS,
71 Avenue des Martyrs, Grenoble 38000, France
| | - Andrew J. Jackson
- European
Spallation Source, Box
176, Lund 221 00, Sweden,Department
of Physical Chemistry, Lund University, Box 124, Lund 221 00, Sweden
| | - Cedric Dicko
- Pure
and
Applied Biochemistry, Department of Chemistry, Lund University, Box
124, Lund SE-221 00, Sweden,Lund
Institute of Advanced Neutron and X-ray Science, SE-223 70 Lund, Sweden
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48
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Gil-Martínez J, Bernardo-Seisdedos G, Mato JM, Millet O. The use of pharmacological chaperones in rare diseases caused by reduced protein stability. Proteomics 2022; 22:e2200222. [PMID: 36205620 DOI: 10.1002/pmic.202200222] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 09/26/2022] [Accepted: 09/29/2022] [Indexed: 11/05/2022]
Abstract
Rare diseases are most often caused by inherited genetic disorders that, after translation, will result in a protein with altered function. Decreased protein stability is the most frequent mechanism associated with a congenital pathogenic missense mutation and it implies the destabilization of the folded conformation in favour of unfolded or misfolded states. In the cellular context and when experimental data is available, a mutant protein with altered thermodynamic stability often also results in impaired homeostasis, with the deleterious accumulation of protein aggregates, metabolites and/or metabolic by-products. In the last decades, a significant effort has enabled the characterization of rare diseases associated to protein stability defects and triggered the development of innovative therapeutic intervention lines, say, the use of pharmacological chaperones to correct the intracellular impaired homeostasis. Here, we review the current knowledge on rare diseases caused by reduced protein stability, paying special attention to the thermodynamic aspects of the protein destabilization, also focusing on some examples where pharmacological chaperones are being tested.
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Affiliation(s)
- Jon Gil-Martínez
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance (BRTA), Bizkaia, Spain
| | | | - José M Mato
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance (BRTA), Bizkaia, Spain.,CIBERehd, Instituto de Salud Carlos III, Madrid, Spain
| | - Oscar Millet
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance (BRTA), Bizkaia, Spain.,ATLAS Molecular Pharma, Bizkaia, Spain.,CIBERehd, Instituto de Salud Carlos III, Madrid, Spain
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49
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Valanciute A, Nygaard L, Zschach H, Maglegaard Jepsen M, Lindorff-Larsen K, Stein A. Accurate protein stability predictions from homology models. Comput Struct Biotechnol J 2022; 21:66-73. [PMID: 36514339 PMCID: PMC9729920 DOI: 10.1016/j.csbj.2022.11.048] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 11/22/2022] [Accepted: 11/23/2022] [Indexed: 11/27/2022] Open
Abstract
Calculating changes in protein stability (ΔΔG) has been shown to be central for predicting the consequences of single amino acid substitutions in protein engineering as well as interpretation of genomic variants for disease risk. Structure-based calculations are considered most accurate, however the tools used to calculate ΔΔGs have been developed on experimentally resolved structures. Extending those calculations to homology models based on related proteins would greatly extend their applicability as large parts of e.g. the human proteome are not structurally resolved. In this study we aim to investigate the accuracy of ΔΔG values predicted on homology models compared to crystal structures. Specifically, we identified four proteins with a large number of experimentally tested ΔΔGs and templates for homology modeling across a broad range of sequence identities, and selected three methods for ΔΔG calculations to test. We find that ΔΔG-values predicted from homology models compare equally well to experimental ΔΔGs as those predicted on experimentally established crystal structures, as long as the sequence identity of the model template to the target protein is at least 40%. In particular, the Rosetta cartesian_ddg protocol is robust against the small perturbations in the structure which homology modeling introduces. In an independent assessment, we observe a similar trend when using ΔΔGs to categorize variants as low or wild-type-like abundance. Overall, our results show that stability calculations performed on homology models can substitute for those on crystal structures with acceptable accuracy as long as the model is built on a template with sequence identity of at least 40% to the target protein.
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Affiliation(s)
- Audrone Valanciute
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Lasse Nygaard
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Henrike Zschach
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Michael Maglegaard Jepsen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Kresten Lindorff-Larsen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark,Corresponding authors.
| | - Amelie Stein
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark,Corresponding authors.
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50
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Yang T, Villois A, Kunka A, Grigolato F, Arosio P, Prokop Z, deMello A, Stavrakis S. Droplet-Based Microfluidic Temperature-Jump Platform for the Rapid Assessment of Biomolecular Kinetics. Anal Chem 2022; 94:16675-16684. [DOI: 10.1021/acs.analchem.2c03009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Affiliation(s)
- Tianjin Yang
- Institute for Chemical and Bioengineering, ETH Zürich, Vladimir Prelog Weg 1, 8093Zürich, Switzerland
| | - Alessia Villois
- Institute for Chemical and Bioengineering, ETH Zürich, Vladimir Prelog Weg 1, 8093Zürich, Switzerland
| | - Antonín Kunka
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00Brno, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital, Pekarska 53, 656 91Brno, Czech Republic
| | - Fulvio Grigolato
- Institute for Chemical and Bioengineering, ETH Zürich, Vladimir Prelog Weg 1, 8093Zürich, Switzerland
| | - Paolo Arosio
- Institute for Chemical and Bioengineering, ETH Zürich, Vladimir Prelog Weg 1, 8093Zürich, Switzerland
| | - Zbynek Prokop
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00Brno, Czech Republic
| | - Andrew deMello
- Institute for Chemical and Bioengineering, ETH Zürich, Vladimir Prelog Weg 1, 8093Zürich, Switzerland
| | - Stavros Stavrakis
- Institute for Chemical and Bioengineering, ETH Zürich, Vladimir Prelog Weg 1, 8093Zürich, Switzerland
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