1
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Meador K, Castells-Graells R, Aguirre R, Sawaya MR, Arbing MA, Sherman T, Senarathne C, Yeates TO. A suite of designed protein cages using machine learning and protein fragment-based protocols. Structure 2024; 32:751-765.e11. [PMID: 38513658 PMCID: PMC11162342 DOI: 10.1016/j.str.2024.02.017] [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: 10/19/2023] [Revised: 01/22/2024] [Accepted: 02/23/2024] [Indexed: 03/23/2024]
Abstract
Designed protein cages and related materials provide unique opportunities for applications in biotechnology and medicine, but their creation remains challenging. Here, we apply computational approaches to design a suite of tetrahedrally symmetric, self-assembling protein cages. For the generation of docked conformations, we emphasize a protein fragment-based approach, while for sequence design of the de novo interface, a comparison of knowledge-based and machine learning protocols highlights the power and increased experimental success achieved using ProteinMPNN. An analysis of design outcomes provides insights for improving interface design protocols, including prioritizing fragment-based motifs, balancing interface hydrophobicity and polarity, and identifying preferred polar contact patterns. In all, we report five structures for seven protein cages, along with two structures of intermediate assemblies, with the highest resolution reaching 2.0 Å using cryo-EM. This set of designed cages adds substantially to the body of available protein nanoparticles, and to methodologies for their creation.
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Affiliation(s)
- Kyle Meador
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA
| | | | - Roman Aguirre
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA
| | - Michael R Sawaya
- UCLA-DOE Institute for Genomics and Proteomics, Los Angeles, CA 90095, USA
| | - Mark A Arbing
- UCLA-DOE Institute for Genomics and Proteomics, Los Angeles, CA 90095, USA
| | - Trent Sherman
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA
| | - Chethaka Senarathne
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA
| | - Todd O Yeates
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA; UCLA-DOE Institute for Genomics and Proteomics, Los Angeles, CA 90095, USA.
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2
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Wallace HM, Yang H, Tan S, Pan HS, Yang R, Xu J, Jo H, Condello C, Polizzi NF, DeGrado WF. De novo design of peptides that bind specific conformers of α-synuclein. Chem Sci 2024; 15:8414-8421. [PMID: 38846390 PMCID: PMC11151861 DOI: 10.1039/d3sc06245g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 03/14/2024] [Indexed: 06/09/2024] Open
Abstract
Insoluble amyloids rich in cross-β fibrils are observed in a number of neurodegenerative diseases. Depending on the clinicopathology, the amyloids can adopt distinct supramolecular assemblies, termed conformational strains. However, rapid methods to study amyloids in a conformationally specific manner are lacking. We introduce a novel computational method for de novo design of peptides that tile the surface of α-synuclein fibrils in a conformationally specific manner. Our method begins by identifying surfaces that are unique to the conformational strain of interest, which becomes a "target backbone" for the design of a peptide binder. Next, we interrogate structures in the PDB with high geometric complementarity to the target. Then, we identify secondary structural motifs that interact with this target backbone in a favorable, highly occurring geometry. This method produces monomeric helical motifs with a favorable geometry for interaction with the strands of the underlying amyloid. Each motif is then symmetrically replicated to form a monolayer that tiles the amyloid surface. Finally, amino acid sequences of the peptide binders are computed to provide a sequence with high geometric and physicochemical complementarity to the target amyloid. This method was applied to a conformational strain of α-synuclein fibrils, resulting in a peptide with high specificity for the target relative to other amyloids formed by α-synuclein, tau, or Aβ40. This designed peptide also markedly slowed the formation of α-synuclein amyloids. Overall, this method offers a new tool for examining conformational strains of amyloid proteins.
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Affiliation(s)
- Hailey M Wallace
- Department of Pharmaceutical Chemistry, The Cardiovascular Research Institution, University of California San Francisco CA 94158 USA
| | - Hyunjun Yang
- Department of Pharmaceutical Chemistry, The Cardiovascular Research Institution, University of California San Francisco CA 94158 USA
- Institute for Neurodegenerative Diseases, University of California San Francisco CA 94143 USA
| | - Sophia Tan
- Department of Pharmaceutical Chemistry, The Cardiovascular Research Institution, University of California San Francisco CA 94158 USA
| | - Henry S Pan
- Department of Pharmaceutical Chemistry, The Cardiovascular Research Institution, University of California San Francisco CA 94158 USA
| | - Rose Yang
- Department of Pharmaceutical Chemistry, The Cardiovascular Research Institution, University of California San Francisco CA 94158 USA
| | - Junyi Xu
- Department of Pharmaceutical Chemistry, The Cardiovascular Research Institution, University of California San Francisco CA 94158 USA
| | - Hyunil Jo
- Department of Pharmaceutical Chemistry, The Cardiovascular Research Institution, University of California San Francisco CA 94158 USA
| | - Carlo Condello
- Institute for Neurodegenerative Diseases, University of California San Francisco CA 94143 USA
- Department of Neurology, University of California San Francisco CA 94143 USA
| | - Nicholas F Polizzi
- Dana Farber Cancer Institute, Harvard Medical School Boston MA 02215 USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School Boston MA 02215 USA
| | - William F DeGrado
- Department of Pharmaceutical Chemistry, The Cardiovascular Research Institution, University of California San Francisco CA 94158 USA
- Institute for Neurodegenerative Diseases, University of California San Francisco CA 94143 USA
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3
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Le TKD, Hioki Y, Duong TH, Kita M, Chavasiri W. Globunoids A-D, undescribed bichalconoid and biflavanoids with α-glucosidase and α-amylase inhibitory activities from Knema globularia stems. PHYTOCHEMISTRY 2024; 221:114066. [PMID: 38494085 DOI: 10.1016/j.phytochem.2024.114066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 03/11/2024] [Accepted: 03/14/2024] [Indexed: 03/19/2024]
Abstract
A bichalconoid, globunoid A (1) and three biflavanones, globunoids B-D (2-4), previously undescribed, were isolated from the stems of Knema globularia, along with fourteen known analogues 5-18. The chemical structures of 1-4 were elucidated by the comprehensive spectroscopic analysis including UV, IR, HRESIMS, and NMR; the absolute configurations were determined based on their NOESY data, DP4+ statistical analysis, and ECD calculation. Up to now, compounds 2 and 3 represent the first 3,3″-linked biflavanone structures. Among the isolated compounds, 2, 3, and 2,3-dihydrocalodenin B (6) potently inhibited α-glucosidase and α-amylase activities, with IC50 values in the range 1.1-7.5 μM. Furthermore, the most active compound 6 was found to be a non-competitive inhibitor against these two enzymes.
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Affiliation(s)
- Thi-Kim-Dung Le
- Center of Excellence in Natural Products Chemistry, Department of Chemistry, Chulalongkorn University, Pathumwan, Bangkok, 10330, Thailand
| | - Yusuke Hioki
- Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, 464-8601, Japan
| | - Thuc-Huy Duong
- Department of Chemistry, Ho Chi Minh City University of Education, 280 an Duong Vuong Street, District 5, Ho Chi Minh City, 748342, Viet Nam
| | - Masaki Kita
- Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, 464-8601, Japan
| | - Warinthorn Chavasiri
- Center of Excellence in Natural Products Chemistry, Department of Chemistry, Chulalongkorn University, Pathumwan, Bangkok, 10330, Thailand; Nanotec-CU Center of Excellence on Food and Agriculture, Department of Chemistry, Chulalongkorn University, Bangkok, 10330, Thailand.
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4
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Le TKD, Duong TH, Chavasiri W. Three new constituents from the stems of Knema globularia and their α-glucosidase inhibitory activity. Nat Prod Res 2024:1-9. [PMID: 38613424 DOI: 10.1080/14786419.2024.2341994] [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: 02/11/2024] [Accepted: 04/03/2024] [Indexed: 04/15/2024]
Abstract
Three new metabolites (1-3) were isolated from the stems of Knema globularia, along with five known compounds, including kaempferol (4), quercetin (5), isovanillic acid (6), protocatechuic acid (7), and gallic acid (8). Their structures were deduced using NMR spectroscopic, mass spectrometric analyses, and literature data. The absolute configurations of 1-3 were established by electronic circular dichroism (ECD) spectroscopy. α-Glucosidase inhibitory activities of those compounds were evaluated using a spectrophotometric method, compounds 1-3 showed very strong effects towards α-glucosidase with IC50 values 1.59, 0.58 and 1.37 µM, respectively (the positive control, acarbose, IC50 93.63 µM). Simultaneously, enzyme kinetics study indicated that 2 was a mix-type inhibitor. 2 interacted well in the active site of α-glucosidase enzyme, primarily through hydrogen bonds and hydrophobic interactions.
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Affiliation(s)
- Thi-Kim-Dung Le
- Laboratory of Biophysics, Institute for Advanced Study in Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - Thuc-Huy Duong
- Department of Chemistry, Ho Chi Minh City University of Education, Ho Chi Minh City, Vietnam
| | - Warinthorn Chavasiri
- Center of Excellence in Natural Products Chemistry, Department of Chemistry, Faculty of Science, Chulalongkorn University, Bangkok, Thailand
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5
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Wallace HM, Yang H, Tan S, Pan HS, Yang R, Xu J, Jo H, Condello C, Polizzi NF, DeGrado WF. De novo Design of Peptides that Bind Specific Conformers of α-Synuclein. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.14.567090. [PMID: 38014268 PMCID: PMC10680688 DOI: 10.1101/2023.11.14.567090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Insoluble amyloids rich in cross-β fibrils are observed in a number of neurodegenerative diseases. Depending on the clinicopathology, the amyloids can adopt distinct supramolecular assemblies, termed conformational strains. However, rapid methods to study amyloid in a conformationally specific manner are lacking. We introduce a novel computational method for de novo design of peptides that tile the surface of α-synuclein fibrils in a conformationally specific manner. Our method begins by identifying surfaces that are unique to the conformational strain of interest, which becomes a "target backbone" for the design of a peptide binder. Next, we interrogate structures in the PDB database with high geometric complementarity to the target. Then, we identify secondary structural motifs that interact with this target backbone in a favorable, highly occurring geometry. This method produces monomeric helical motifs with a favorable geometry for interaction with the strands of the underlying amyloid. Each motif is then symmetrically replicated to form a monolayer that tiles the amyloid surface. Finally, amino acid sequences of the peptide binders are computed to provide a sequence with high geometric and physicochemical complementarity to the target amyloid. This method was applied to a conformational strain of α-synuclein fibrils, resulting in a peptide with high specificity for the target relative to other amyloids formed by α-synuclein, tau, or Aβ40. This designed peptide also markedly slowed the formation of α-synuclein amyloids. Overall, this method offers a new tool for examining conformational strains of amyloid proteins.
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6
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Goldbach N, Benna I, Wicky BIM, Croft JT, Carter L, Bera AK, Nguyen H, Kang A, Sankaran B, Yang EC, Lee KK, Baker D. De novo design of monomeric helical bundles for pH-controlled membrane lysis. Protein Sci 2023; 32:e4769. [PMID: 37632837 PMCID: PMC10578055 DOI: 10.1002/pro.4769] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 07/10/2023] [Accepted: 08/24/2023] [Indexed: 08/28/2023]
Abstract
Targeted intracellular delivery via receptor-mediated endocytosis requires the delivered cargo to escape the endosome to prevent lysosomal degradation. This can in principle be achieved by membrane lysis tightly restricted to endosomal membranes upon internalization to avoid general membrane insertion and lysis. Here, we describe the design of small monomeric proteins with buried histidine containing pH-responsive hydrogen bond networks and membrane permeating amphipathic helices. Of the 30 designs that were experimentally tested, all expressed in Escherichia coli, 13 were monomeric with the expected secondary structure, and 4 designs disrupted artificial liposomes in a pH-dependent manner. Mutational analysis showed that the buried histidine hydrogen bond networks mediate pH-responsiveness and control lysis of model membranes within a very narrow range of pH (6.0-5.5) with almost no lysis occurring at neutral pH. These tightly controlled lytic monomers could help mediate endosomal escape in designed targeted delivery platforms.
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Affiliation(s)
- Nicolas Goldbach
- Institute for Protein DesignUniversity of WashingtonSeattleWashingtonUSA
- Molecular Life SciencesTechnical University of MunichMunichGermany
| | - Issa Benna
- Institute for Protein DesignUniversity of WashingtonSeattleWashingtonUSA
- Department of BioengineeringUniversity of WashingtonSeattleWashingtonUSA
| | - Basile I. M. Wicky
- Institute for Protein DesignUniversity of WashingtonSeattleWashingtonUSA
- Department of BiochemistryUniversity of WashingtonSeattleWashingtonUSA
| | - Jacob T. Croft
- Department of Medicinal ChemistryUniversity of WashingtonSeattleWashingtonUSA
| | - Lauren Carter
- Institute for Protein DesignUniversity of WashingtonSeattleWashingtonUSA
- Department of BiochemistryUniversity of WashingtonSeattleWashingtonUSA
| | - Asim K. Bera
- Institute for Protein DesignUniversity of WashingtonSeattleWashingtonUSA
- Department of BiochemistryUniversity of WashingtonSeattleWashingtonUSA
| | - Hannah Nguyen
- Institute for Protein DesignUniversity of WashingtonSeattleWashingtonUSA
- Department of BiochemistryUniversity of WashingtonSeattleWashingtonUSA
| | - Alex Kang
- Institute for Protein DesignUniversity of WashingtonSeattleWashingtonUSA
- Department of BiochemistryUniversity of WashingtonSeattleWashingtonUSA
| | - Banumathi Sankaran
- Molecular Biophysics and Integrated BioimagingLawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - Erin C. Yang
- Institute for Protein DesignUniversity of WashingtonSeattleWashingtonUSA
- Department of BiochemistryUniversity of WashingtonSeattleWashingtonUSA
- Biological Physics, Structure and Design Graduate ProgramUniversity of WashingtonSeattleWashingtonUSA
| | - Kelly K. Lee
- Department of Medicinal ChemistryUniversity of WashingtonSeattleWashingtonUSA
- Biological Physics, Structure and Design Graduate ProgramUniversity of WashingtonSeattleWashingtonUSA
- Department of MicrobiologyUniversity of WashingtonSeattleWashingtonUSA
| | - David Baker
- Institute for Protein DesignUniversity of WashingtonSeattleWashingtonUSA
- Department of BiochemistryUniversity of WashingtonSeattleWashingtonUSA
- Howard Hughes Medical InstituteUniversity of WashingtonSeattleWashingtonUSA
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7
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Meador K, Castells-Graells R, Aguirre R, Sawaya MR, Arbing MA, Sherman T, Senarathne C, Yeates TO. A Suite of Designed Protein Cages Using Machine Learning Algorithms and Protein Fragment-Based Protocols. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.09.561468. [PMID: 37873110 PMCID: PMC10592684 DOI: 10.1101/2023.10.09.561468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Designed protein cages and related materials provide unique opportunities for applications in biotechnology and medicine, while methods for their creation remain challenging and unpredictable. In the present study, we apply new computational approaches to design a suite of new tetrahedrally symmetric, self-assembling protein cages. For the generation of docked poses, we emphasize a protein fragment-based approach, while for de novo interface design, a comparison of computational protocols highlights the power and increased experimental success achieved using the machine learning program ProteinMPNN. In relating information from docking and design, we observe that agreement between fragment-based sequence preferences and ProteinMPNN sequence inference correlates with experimental success. Additional insights for designing polar interactions are highlighted by experimentally testing larger and more polar interfaces. In all, using X-ray crystallography and cryo-EM, we report five structures for seven protein cages, with atomic resolution in the best case reaching 2.0 Å. We also report structures of two incompletely assembled protein cages, providing unique insights into one type of assembly failure. The new set of designed cages and their structures add substantially to the body of available protein nanoparticles, and to methodologies for their creation.
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Affiliation(s)
- Kyle Meador
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, USA 90095
| | | | - Roman Aguirre
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, USA 90095
| | - Michael R. Sawaya
- UCLA-DOE Institute for Genomics and Proteomics, Los Angeles, CA, USA 90095
| | - Mark A. Arbing
- UCLA-DOE Institute for Genomics and Proteomics, Los Angeles, CA, USA 90095
| | - Trent Sherman
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, USA 90095
| | - Chethaka Senarathne
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, USA 90095
| | - Todd O. Yeates
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, USA 90095
- UCLA-DOE Institute for Genomics and Proteomics, Los Angeles, CA, USA 90095
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8
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Lisiecki J, Szabelski P. Structural Quantification of the Surface-Confined Metal-Organic Precursors Simulated with the Lattice Monte Carlo Method. Molecules 2023; 28:molecules28104253. [PMID: 37241994 DOI: 10.3390/molecules28104253] [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: 04/22/2023] [Revised: 05/15/2023] [Accepted: 05/16/2023] [Indexed: 05/28/2023] Open
Abstract
The diversity of surface-confined metal-organic precursor structures, which recently have been observed experimentally, poses a question of how the individual properties of a molecular building block determine those of the resulting superstructure. To answer this question, we use the Monte Carlo simulation technique to model the self-assembly of metal-organic precursors that precede the covalent polymerization of halogenated PAH isomers. For this purpose, a few representative examples of low-dimensional constructs were studied, and their basic structural features were quantified using such descriptors as the orientational order parameter, radial distribution function, and one- and two-dimensional structure factors. The obtained results demonstrated that the morphology of the precursor (and thus the subsequent polymer) could be effectively tuned by a suitable choice of molecular parameters, including size, shape, and intramolecular distribution of halogen substituents. Moreover, our theoretical investigations showed the effect of the main structural features of the precursors on the related indirect characteristics of these constructs. The results reported herein can be helpful in the custom designing and characterization of low-dimensional polymers with adjustable properties.
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Affiliation(s)
- Jakub Lisiecki
- Department of Theoretical Chemistry, Institute of Chemical Sciences, Faculty of Chemistry, Maria Curie-Skłodowska University, Pl. M.C. Skłodowskiej 3, 20-031 Lublin, Poland
| | - Paweł Szabelski
- Department of Theoretical Chemistry, Institute of Chemical Sciences, Faculty of Chemistry, Maria Curie-Skłodowska University, Pl. M.C. Skłodowskiej 3, 20-031 Lublin, Poland
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9
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Kibler RD, Lee S, Kennedy MA, Wicky BIM, Lai SM, Kostelic MM, Li X, Chow CM, Carter L, Wysocki VH, Stoddard BL, Baker D. Stepwise design of pseudosymmetric protein hetero-oligomers. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.07.535760. [PMID: 37066191 PMCID: PMC10104133 DOI: 10.1101/2023.04.07.535760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Pseudosymmetric hetero-oligomers with three or more unique subunits with overall structural (but not sequence) symmetry play key roles in biology, and systematic approaches for generating such proteins de novo would provide new routes to controlling cell signaling and designing complex protein materials. However, the de novo design of protein hetero-oligomers with three or more distinct chains with nearly identical structures is a challenging problem because it requires the accurate design of multiple protein-protein interfaces simultaneously. Here, we describe a divide-and-conquer approach that breaks the multiple-interface design challenge into a set of more tractable symmetric single-interface redesign problems, followed by structural recombination of the validated homo-oligomers into pseudosymmetric hetero-oligomers. Starting from de novo designed circular homo-oligomers composed of 9 or 24 tandemly repeated units, we redesigned the inter-subunit interfaces to generate 15 new homo-oligomers and recombined them to make 17 new hetero-oligomers, including ABC heterotrimers, A2B2 heterotetramers, and A3B3 and A2B2C2 heterohexamers which assemble with high structural specificity. The symmetric homo-oligomers and pseudosymmetric hetero-oligomers generated for each system share a common backbone, and hence are ideal building blocks for generating and functionalizing larger symmetric assemblies.
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Affiliation(s)
- Ryan D. Kibler
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Sangmin Lee
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
| | - Madison A. Kennedy
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, WA 98006, USA
| | - Basile I. M. Wicky
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Stella M. Lai
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210, USA
- Resource for Native Mass Spectrometry Guided Structural Biology, The Ohio State University, Columbus, OH 43210, USA
| | - Marius M. Kostelic
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210, USA
- Resource for Native Mass Spectrometry Guided Structural Biology, The Ohio State University, Columbus, OH 43210, USA
| | - Xinting Li
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Cameron M. Chow
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Lauren Carter
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Vicki H. Wysocki
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210, USA
- Resource for Native Mass Spectrometry Guided Structural Biology, The Ohio State University, Columbus, OH 43210, USA
| | - Barry L. Stoddard
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, WA 98006, USA
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
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10
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Pande V, Joshi T, Pandey SC, Sati D, Mathpal S, Pande V, Chandra S, Samant M. Molecular docking and molecular dynamics simulation approaches for evaluation of laccase-mediated biodegradation of various industrial dyes. J Biomol Struct Dyn 2022; 40:12461-12471. [PMID: 34459700 DOI: 10.1080/07391102.2021.1971564] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Dyes are being increasingly utilized across the globe, but there is no appropriate method of bioremediation for their full mineralization from the environment. Laccases are key enzymes that help microbes to degrade dyes as well as their intermediate metabolites. Various dyes have been reported to be degraded by bacteria, but it is still unclear how these enzymes function during dye degradation. To effectively eradicate toxic dyes from the system, it is essential to understand the molecular function of enzymes. As a result, the interaction of laccase with different toxic dyes was investigated using molecular docking. Based on the highest binding energy we have screened ten dyes with positive interaction with laccase. Evaluating the MD simulation results, three out of ten dyes were more stable as potential targets for degradation by laccase of Bacillus subtilis. As a result, subsequent research focused solely on the results of three substrates: pigment red, fuchsin base, and Sudan IV. Analysis of MD simulation revealed that pigments red 23, fuchsin base, and Sudan IV form hydrogen and hydrophobic bond as well as Vander Waals interactions with the active site of laccase to keep it stable in aqueous solution. The conformation of laccase is greatly altered by the inclusion of all three substrates in the active site. The MD simulation findings show that laccase complexes remain stable throughout the catalytic reaction. Therefore, this research provides a molecular understanding of laccase expression and its role in the bioremediation of the pigments red 23, fuchsin base, and Sudan IV.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Veni Pande
- Cell and Molecular Biology Laboratory, Department of Zoology (DST-FIST sponsored), Kumaun University, Almora, Uttarakhand, India.,Department of Biotechnology, Kumaun University, Bhimtal, Uttarakhand, India
| | - Tushar Joshi
- Department of Biotechnology, Kumaun University, Bhimtal, Uttarakhand, India
| | - Satish Chandra Pandey
- Cell and Molecular Biology Laboratory, Department of Zoology (DST-FIST sponsored), Kumaun University, Almora, Uttarakhand, India.,Department of Biotechnology, Kumaun University, Bhimtal, Uttarakhand, India
| | - Diksha Sati
- Cell and Molecular Biology Laboratory, Department of Zoology (DST-FIST sponsored), Kumaun University, Almora, Uttarakhand, India
| | - Shalini Mathpal
- Department of Biotechnology, Kumaun University, Bhimtal, Uttarakhand, India
| | - Veena Pande
- Department of Biotechnology, Kumaun University, Bhimtal, Uttarakhand, India
| | - Subhash Chandra
- Computational Biology & Biotechnology Laboratory, Department of Botany, Soban Singh Jeena University, Almora, Uttarakhand, India
| | - Mukesh Samant
- Cell and Molecular Biology Laboratory, Department of Zoology (DST-FIST sponsored), Kumaun University, Almora, Uttarakhand, India
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11
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Bermeo S, Favor A, Chang YT, Norris A, Boyken SE, Hsia Y, Haddox HK, Xu C, Brunette TJ, Wysocki VH, Bhabha G, Ekiert DC, Baker D. De novo design of obligate ABC-type heterotrimeric proteins. Nat Struct Mol Biol 2022; 29:1266-1276. [PMID: 36522429 PMCID: PMC9758053 DOI: 10.1038/s41594-022-00879-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 10/20/2022] [Indexed: 12/23/2022]
Abstract
The de novo design of three protein chains that associate to form a heterotrimer (but not any of the possible two-chain heterodimers) and that can drive the assembly of higher-order branching structures is an important challenge for protein design. We designed helical heterotrimers with specificity conferred by buried hydrogen bond networks and large aromatic residues to enhance shape complementary packing. We obtained ten designs for which all three chains cooperatively assembled into heterotrimers with few or no other species present. Crystal structures of a helical bundle heterotrimer and extended versions, with helical repeat proteins fused to individual subunits, showed all three chains assembling in the designed orientation. We used these heterotrimers as building blocks to construct larger cyclic oligomers, which were structurally validated by electron microscopy. Our three-way junction designs provide new routes to complex protein nanostructures and enable the scaffolding of three distinct ligands for modulation of cell signaling.
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Affiliation(s)
- Sherry Bermeo
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Biological Physics, Structure and Design Graduate Program, University of Washington, Seattle, WA, USA
| | - Andrew Favor
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Molecular Engineering and Sciences Institute, University of Washington, Seattle, WA, USA
| | - Ya-Ting Chang
- Department of Cell Biology, New York University School of Medicine, New York, NY, USA
| | - Andrew Norris
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, USA
- Resource for Native Mass Spectrometry Guided Structural Biology, The Ohio State University, Columbus, OH, USA
| | - Scott E Boyken
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Yang Hsia
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Hugh K Haddox
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Chunfu Xu
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - T J Brunette
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Vicki H Wysocki
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, USA
- Resource for Native Mass Spectrometry Guided Structural Biology, The Ohio State University, Columbus, OH, USA
| | - Gira Bhabha
- Department of Cell Biology, New York University School of Medicine, New York, NY, USA
| | - Damian C Ekiert
- Department of Cell Biology, New York University School of Medicine, New York, NY, USA
- Department of Microbiology, New York University School of Medicine, New York, NY, USA
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle, WA, USA.
- Institute for Protein Design, University of Washington, Seattle, WA, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
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12
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Qing R, Hao S, Smorodina E, Jin D, Zalevsky A, Zhang S. Protein Design: From the Aspect of Water Solubility and Stability. Chem Rev 2022; 122:14085-14179. [PMID: 35921495 PMCID: PMC9523718 DOI: 10.1021/acs.chemrev.1c00757] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Indexed: 12/13/2022]
Abstract
Water solubility and structural stability are key merits for proteins defined by the primary sequence and 3D-conformation. Their manipulation represents important aspects of the protein design field that relies on the accurate placement of amino acids and molecular interactions, guided by underlying physiochemical principles. Emulated designer proteins with well-defined properties both fuel the knowledge-base for more precise computational design models and are used in various biomedical and nanotechnological applications. The continuous developments in protein science, increasing computing power, new algorithms, and characterization techniques provide sophisticated toolkits for solubility design beyond guess work. In this review, we summarize recent advances in the protein design field with respect to water solubility and structural stability. After introducing fundamental design rules, we discuss the transmembrane protein solubilization and de novo transmembrane protein design. Traditional strategies to enhance protein solubility and structural stability are introduced. The designs of stable protein complexes and high-order assemblies are covered. Computational methodologies behind these endeavors, including structure prediction programs, machine learning algorithms, and specialty software dedicated to the evaluation of protein solubility and aggregation, are discussed. The findings and opportunities for Cryo-EM are presented. This review provides an overview of significant progress and prospects in accurate protein design for solubility and stability.
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Affiliation(s)
- Rui Qing
- State
Key Laboratory of Microbial Metabolism, School of Life Sciences and
Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
- Media
Lab, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
- The
David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
| | - Shilei Hao
- Media
Lab, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
- Key
Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing 400030, China
| | - Eva Smorodina
- Department
of Immunology, University of Oslo and Oslo
University Hospital, Oslo 0424, Norway
| | - David Jin
- Avalon GloboCare
Corp., Freehold, New Jersey 07728, United States
| | - Arthur Zalevsky
- Laboratory
of Bioinformatics Approaches in Combinatorial Chemistry and Biology, Shemyakin−Ovchinnikov Institute of Bioorganic
Chemistry RAS, Moscow 117997, Russia
| | - Shuguang Zhang
- Media
Lab, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
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13
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Precision materials: Computational design methods of accurate protein materials. Curr Opin Struct Biol 2022; 74:102367. [DOI: 10.1016/j.sbi.2022.102367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2021] [Revised: 02/22/2022] [Accepted: 02/28/2022] [Indexed: 11/23/2022]
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14
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Talluri S. Algorithms for protein design. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2022; 130:1-38. [PMID: 35534105 DOI: 10.1016/bs.apcsb.2022.01.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Computational Protein Design has the potential to contribute to major advances in enzyme technology, vaccine design, receptor-ligand engineering, biomaterials, nanosensors, and synthetic biology. Although Protein Design is a challenging problem, proteins can be designed by experts in Protein Design, as well as by non-experts whose primary interests are in the applications of Protein Design. The increased accessibility of Protein Design technology is attributable to the accumulated knowledge and experience with Protein Design as well as to the availability of software and online resources. The objective of this review is to serve as a guide to the relevant literature with a focus on the novel methods and algorithms that have been developed or applied for Protein Design, and to assist in the selection of algorithms for Protein Design. Novel algorithms and models that have been introduced to utilize the enormous amount of experimental data and novel computational hardware have the potential for producing substantial increases in the accuracy, reliability and range of applications of designed proteins.
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Affiliation(s)
- Sekhar Talluri
- Department of Biotechnology, GITAM, Visakhapatnam, India.
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15
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Abstract
Proteins have shown promise as therapeutics and diagnostics, but their effectiveness is limited by our inability to spatially target their activity. To overcome this limitation, we developed a computationally guided method to design inactive proenzymes or zymogens, which are activated through cleavage by a protease. Since proteases are differentially expressed in various tissues and disease states, including cancer, these proenzymes could be targeted to the desired microenvironment. We tested our method on the therapeutically relevant protein carboxypeptidase G2 (CPG2). We designed Pro-CPG2s that are inhibited by 80 to 98% and are partially to fully reactivatable following protease treatment. The developed methodology, with further refinements, could pave the way for routinely designing protease-activated protein-based therapeutics and diagnostics that act in a spatially controlled manner. Confining the activity of a designed protein to a specific microenvironment would have broad-ranging applications, such as enabling cell type-specific therapeutic action by enzymes while avoiding off-target effects. While many natural enzymes are synthesized as inactive zymogens that can be activated by proteolysis, it has been challenging to redesign any chosen enzyme to be similarly stimulus responsive. Here, we develop a massively parallel computational design, screening, and next-generation sequencing-based approach for proenzyme design. For a model system, we employ carboxypeptidase G2 (CPG2), a clinically approved enzyme that has applications in both the treatment of cancer and controlling drug toxicity. Detailed kinetic characterization of the most effectively designed variants shows that they are inhibited by ∼80% compared to the unmodified protein, and their activity is fully restored following incubation with site-specific proteases. Introducing disulfide bonds between the pro- and catalytic domains based on the design models increases the degree of inhibition to 98% but decreases the degree of restoration of activity by proteolysis. A selected disulfide-containing proenzyme exhibits significantly lower activity relative to the fully activated enzyme when evaluated in cell culture. Structural and thermodynamic characterization provides detailed insights into the prodomain binding and inhibition mechanisms. The described methodology is general and could enable the design of a variety of proproteins with precise spatial regulation.
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16
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Abstract
The task of protein sequence design is central to nearly all rational protein engineering problems, and enormous effort has gone into the development of energy functions to guide design. Here, we investigate the capability of a deep neural network model to automate design of sequences onto protein backbones, having learned directly from crystal structure data and without any human-specified priors. The model generalizes to native topologies not seen during training, producing experimentally stable designs. We evaluate the generalizability of our method to a de novo TIM-barrel scaffold. The model produces novel sequences, and high-resolution crystal structures of two designs show excellent agreement with in silico models. Our findings demonstrate the tractability of an entirely learned method for protein sequence design. Rational protein design to achieve a given protein backbone conformation is needed to engineer specific functions. Here Anand et al. describe a machine learning method using a learned neural network potential for fixed-backbone protein design.
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17
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Pulavarti SVSRK, Maguire JB, Yuen S, Harrison JS, Griffin J, Premkumar L, Esposito EA, Makhatadze GI, Garcia AE, Weiss TM, Snell EH, Kuhlman B, Szyperski T. From Protein Design to the Energy Landscape of a Cold Unfolding Protein. J Phys Chem B 2022; 126:1212-1231. [PMID: 35128921 PMCID: PMC9281400 DOI: 10.1021/acs.jpcb.1c10750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Understanding protein folding is crucial for protein sciences. The conformational spaces and energy landscapes of cold (unfolded) protein states, as well as the associated transitions, are hardly explored. Furthermore, it is not known how structure relates to the cooperativity of cold transitions, if cold and heat unfolded states are thermodynamically similar, and if cold states play important roles for protein function. We created the cold unfolding 4-helix bundle DCUB1 with a de novo designed bipartite hydrophilic/hydrophobic core featuring a hydrogen bond network which extends across the bundle in order to study the relative importance of hydrophobic versus hydrophilic protein-water interactions for cold unfolding. Structural and thermodynamic characterization resulted in the discovery of a complex energy landscape for cold transitions, while the heat unfolded state is a random coil. Below ∼0 °C, the core of DCUB1 disintegrates in a largely cooperative manner, while a near-native helical content is retained. The resulting cold core-unfolded state is compact and features extensive internal dynamics. Below -5 °C, two additional cold transitions are seen, that is, (i) the formation of a water-mediated, compact, and highly dynamic dimer, and (ii) the onset of cold helix unfolding decoupled from cold core unfolding. Our results suggest that cold unfolding is initiated by the intrusion of water into the hydrophilic core network and that cooperativity can be tuned by varying the number of core hydrogen bond networks. Protein design has proven to be invaluable to explore the energy landscapes of cold states and to robustly test related theories.
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Affiliation(s)
- Surya V S R K Pulavarti
- Department of Chemistry, University at Buffalo, The State University of New York, Buffalo, New York 14260, United States
| | - Jack B Maguire
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Shirley Yuen
- Department of Chemistry, University at Buffalo, The State University of New York, Buffalo, New York 14260, United States
| | - Joseph S Harrison
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Jermel Griffin
- Department of Chemistry, University at Buffalo, The State University of New York, Buffalo, New York 14260, United States
| | - Lakshmanane Premkumar
- Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Edward A Esposito
- Malvern Panalytical Inc, Northhampton, Massachsetts 01060, United States
| | - George I Makhatadze
- Department of Biological Sciences, Rensselaer Polytechnic Institute, Troy, New York 08544, United States
| | - Angel E Garcia
- Center for Non Linear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - Thomas M Weiss
- Stanford Synchrotron Radiation Lightsource, Stanford Linear Accelerator Center, Stanford University, Menlo Park, California 94025, United States
| | - Edward H Snell
- Hauptman-Woodward Medical Research Institute, 700 Ellicott Street, Buffalo, New York 14203, United States.,Department of Materials Design and Innovation, University at Buffalo, The State University of New York, Buffalo, New York 14260, United States
| | - Brian Kuhlman
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Thomas Szyperski
- Department of Chemistry, University at Buffalo, The State University of New York, Buffalo, New York 14260, United States
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18
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Abdi SAH, Alzahrani A, Alghamdi S, Alquraini A, Alghamdi A. Hexaconazole exposure ravages biosynthesis pathway of steroid hormones: revealed by molecular dynamics and interaction. Toxicol Res (Camb) 2022; 11:60-76. [PMID: 35237412 PMCID: PMC8882804 DOI: 10.1093/toxres/tfab113] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 10/05/2021] [Accepted: 11/03/2021] [Indexed: 12/25/2023] Open
Abstract
Widespread application of hexaconazole for agriculture purpose poses a threat to human health by disrupting normal endocrine homeostasis. To avoid adverse health effects on human, it is crucial to identify the effects of hexaconazole on key enzymes responsible for steroidal hormone synthesis. In view of this, present study was conducted to investigate the interaction mechanisms of hexaconazole with key enzymes in comparison with their food drug administration (FDA) approved inhibitor by molecular docking and molecular dynamics simulations. Results indicate that hexaconazole contacts with the active site of the key enzymes required for steroidal hormonal synthesis. Results pertaining to root-mean-square deviation, root-mean-square calculation, radius of gyration, hydrogen bonding and solvent accessible surface area exhibited that the interaction pattern and stability of interaction of hexaconazole was similar to enzyme specific inhibitor. In addition, ligand and enzyme complex interaction energy of hexaconazole was almost similar to key enzyme and FDA-approved enzyme specific inhibitor complex. This study offers a molecular level of understanding of hexaconazole with different enzymes required for steroidal hormonal synthesis. Findings of the study clearly suggest that hexaconazole has efficacy to stably interact with various enzyme required to progress the pathway of hormonal synthesis. If incessant exposure of hexaconazole occurs during agricultural work it may lead to ravage hormonal synthesis or potent endocrine disruption. The result of binding energy and complex interaction energy is depicted in the graphical abstract.
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Affiliation(s)
- Sayed Aliul Hasan Abdi
- Department of Pharmaceutical Chemistry, Faculty of Clinical Pharmacy, Albaha University, 1988, Saudi Arabia
| | - Abdulaziz Alzahrani
- Department of Pharmaceutical Chemistry, Faculty of Clinical Pharmacy, Albaha University, 1988, Saudi Arabia
| | - Saleh Alghamdi
- Department of Clinical Pharmacy, Faculty of Clinical Pharmacy, Albaha University, 1988, Saudi Arabia, Saudi Arabia
| | - Ali Alquraini
- Department of Pharmaceutical Chemistry, Faculty of Clinical Pharmacy, Albaha University, 1988, Saudi Arabia
| | - Adel Alghamdi
- Department of Pharmaceutical Chemistry, Faculty of Clinical Pharmacy, Albaha University, 1988, Saudi Arabia
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19
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Boral A, Khamaru M, Mitra D. Designing synthetic transcription factors: A structural perspective. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2022; 130:245-287. [PMID: 35534109 DOI: 10.1016/bs.apcsb.2021.12.003] [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: 06/14/2023]
Abstract
In this chapter, we discuss different design strategies of synthetic proteins, especially synthetic transcription factors. Design and engineering of synthetic transcription factors is particularly relevant for the need-based manipulation of gene expression. With recent advances in structural biology techniques and with the emergence of other precision biochemical/physical tools, accurate knowledge on structure-function relations is increasingly becoming available. Besides discussing the underlying principles of design, we go through individual cases, especially those involving four major groups of transcription factors-basic leucine zippers, zinc fingers, helix-turn-helix and homeodomains. We further discuss how synthetic biology can come together with structural biology to alter the genetic blueprint of life.
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Affiliation(s)
- Aparna Boral
- Department of Life Sciences, Presidency University, Kolkata, West Bengal, India
| | - Madhurima Khamaru
- Department of Life Sciences, Presidency University, Kolkata, West Bengal, India
| | - Devrani Mitra
- Department of Life Sciences, Presidency University, Kolkata, West Bengal, India.
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20
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Interpreting neural networks for biological sequences by learning stochastic masks. NAT MACH INTELL 2022; 4:41-54. [DOI: 10.1038/s42256-021-00428-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
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21
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Woodall NB, Weinberg Z, Park J, Busch F, Johnson RS, Feldbauer MJ, Murphy M, Ahlrichs M, Yousif I, MacCoss MJ, Wysocki VH, El-Samad H, Baker D. De novo design of tyrosine and serine kinase-driven protein switches. Nat Struct Mol Biol 2021; 28:762-770. [PMID: 34518698 PMCID: PMC8601088 DOI: 10.1038/s41594-021-00649-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 07/26/2021] [Indexed: 02/07/2023]
Abstract
Kinases play central roles in signaling cascades, relaying information from the outside to the inside of mammalian cells. De novo designed protein switches capable of interfacing with tyrosine kinase signaling pathways would open new avenues for controlling cellular behavior, but, so far, no such systems have been described. Here we describe the de novo design of two classes of protein switch that link phosphorylation by tyrosine and serine kinases to protein-protein association. In the first class, protein-protein association is required for phosphorylation by the kinase, while in the second class, kinase activity drives protein-protein association. We design systems that couple protein binding to kinase activity on the immunoreceptor tyrosine-based activation motif central to T-cell signaling, and kinase activity to reconstitution of green fluorescent protein fluorescence from fragments and the inhibition of the protease calpain. The designed switches are reversible and function in vitro and in cells with up to 40-fold activation of switching by phosphorylation.
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Affiliation(s)
- Nicholas B Woodall
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Zara Weinberg
- Department of Biochemistry & Biophysics, University of California San Francisco, San Francisco, CA, USA
| | - Jesslyn Park
- Department of Biochemistry & Biophysics, University of California San Francisco, San Francisco, CA, USA
| | - Florian Busch
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, USA
- Resource for Native Mass Spectrometry Guided Structural Biology, The Ohio State University, Columbus, OH, USA
| | - Richard S Johnson
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Michael Murphy
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Maggie Ahlrichs
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Issa Yousif
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Department of Bioengineering, University of Washington, Seattle, WA, USA
| | - Michael J MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Vicki H Wysocki
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, USA
- Resource for Native Mass Spectrometry Guided Structural Biology, The Ohio State University, Columbus, OH, USA
| | - Hana El-Samad
- Department of Biochemistry & Biophysics, University of California San Francisco, San Francisco, CA, USA
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle, WA, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
- Institute for Protein Design, University of Washington, Seattle, WA, USA.
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22
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Maguire JB, Grattarola D, Mulligan VK, Klyshko E, Melo H. XENet: Using a new graph convolution to accelerate the timeline for protein design on quantum computers. PLoS Comput Biol 2021; 17:e1009037. [PMID: 34570773 PMCID: PMC8496835 DOI: 10.1371/journal.pcbi.1009037] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 10/07/2021] [Accepted: 09/14/2021] [Indexed: 11/30/2022] Open
Abstract
Graph representations are traditionally used to represent protein structures in sequence design protocols in which the protein backbone conformation is known. This infrequently extends to machine learning projects: existing graph convolution algorithms have shortcomings when representing protein environments. One reason for this is the lack of emphasis on edge attributes during massage-passing operations. Another reason is the traditionally shallow nature of graph neural network architectures. Here we introduce an improved message-passing operation that is better equipped to model local kinematics problems such as protein design. Our approach, XENet, pays special attention to both incoming and outgoing edge attributes. We compare XENet against existing graph convolutions in an attempt to decrease rotamer sample counts in Rosetta's rotamer substitution protocol, used for protein side-chain optimization and sequence design. This use case is motivating because it both reduces the size of the search space for classical side-chain optimization algorithms, and allows larger protein design problems to be solved with quantum algorithms on near-term quantum computers with limited qubit counts. XENet outperformed competing models while also displaying a greater tolerance for deeper architectures. We found that XENet was able to decrease rotamer counts by 40% without loss in quality. This decreased the memory consumption for classical pre-computation of rotamer energies in our use case by more than a factor of 3, the qubit consumption for an existing sequence design quantum algorithm by 40%, and the size of the solution space by a factor of 165. Additionally, XENet displayed an ability to handle deeper architectures than competing convolutions.
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Affiliation(s)
- Jack B. Maguire
- Menten AI, Inc., Palo Alto, California, United States of America
| | - Daniele Grattarola
- Faculty of Informatics, Università della Svizzera italiana, Lugano, Switzerland
| | - Vikram Khipple Mulligan
- Center for Computational Biology, Flatiron Institute, New York, New York, United States of America
| | - Eugene Klyshko
- Menten AI, Inc., Palo Alto, California, United States of America
- Department of Physics, University of Toronto, Toronto, Ontario, Canada
| | - Hans Melo
- Menten AI, Inc., Palo Alto, California, United States of America
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23
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Bhatt P, Joshi T, Bhatt K, Zhang W, Huang Y, Chen S. Binding interaction of glyphosate with glyphosate oxidoreductase and C-P lyase: Molecular docking and molecular dynamics simulation studies. JOURNAL OF HAZARDOUS MATERIALS 2021; 409:124927. [PMID: 33450511 DOI: 10.1016/j.jhazmat.2020.124927] [Citation(s) in RCA: 69] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 12/14/2020] [Accepted: 12/20/2020] [Indexed: 05/12/2023]
Abstract
Widespread application of glyphosate poses a threat to living organisms. Microbial strains are able to degrade glyphosate via contrasting metabolic pathways with the help of enzymes. Glyphosate oxidoreductase (GOX) and C-P lyase are the key enzymes for the biodegradation of glyphosate and its intermediate metabolite aminomethylphosphonic acid (AMPA) in microbes. The microbial degradation of glyphosate has been reported, but the underlying molecular mechanism is still unclear. Therefore, in this study, the interaction mechanism of GOX and C-P lyase with glyphosate and AMPA were investigated by using molecular docking and molecular dynamics (MD) simulations. The results indicate that glyphosate contacts with the active site of GOX and C-P lyase by hydrogen bonds as well as hydrophobic and van der Waals interactions in aqueous solution to maintain its stability. The presence of glyphosate and AMPA in the active site significantly changes the conformation of GOX and C-P lyase. The results of the MD simulations confirm that GOX and C-P lyase complexes are stable during the catalytic reaction. This study offers a molecular level of understanding of the expression and function of GOX and C-P lyase for the bioremediation of glyphosate.
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Affiliation(s)
- Pankaj Bhatt
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, Guangdong Province Key Laboratory of Microbial Signals and Disease Control, Integrative Microbiology Research Centre, South China Agricultural University, Guangzhou 510642, China; Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China
| | - Tushar Joshi
- Department of Biotechnology, Kumaun University, Bhimtal Campus, Bhimtal, Uttarakhand 263136, India
| | - Kalpana Bhatt
- Department of Botany and Microbiology, Gurukul Kangri University, Haridwar, Uttarakhand 249404, India
| | - Wenping Zhang
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, Guangdong Province Key Laboratory of Microbial Signals and Disease Control, Integrative Microbiology Research Centre, South China Agricultural University, Guangzhou 510642, China; Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China
| | - Yaohua Huang
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, Guangdong Province Key Laboratory of Microbial Signals and Disease Control, Integrative Microbiology Research Centre, South China Agricultural University, Guangzhou 510642, China; Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China
| | - Shaohua Chen
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, Guangdong Province Key Laboratory of Microbial Signals and Disease Control, Integrative Microbiology Research Centre, South China Agricultural University, Guangzhou 510642, China; Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China.
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24
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Meinen BA, Bahl CD. Breakthroughs in computational design methods open up new frontiers for de novo protein engineering. Protein Eng Des Sel 2021; 34:6243354. [DOI: 10.1093/protein/gzab007] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 02/16/2021] [Accepted: 03/08/2021] [Indexed: 02/03/2023] Open
Abstract
Abstract
Proteins catalyze the majority of chemical reactions in organisms, and harnessing this power has long been the focus of the protein engineering field. Computational protein design aims to create new proteins and functions in silico, and in doing so, accelerate the process, reduce costs and enable more sophisticated engineering goals to be accomplished. Challenges that very recently seemed impossible are now within reach thanks to several landmark advances in computational protein design methods. Here, we summarize these new methods, with a particular emphasis on de novo protein design advancements occurring within the past 5 years.
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Affiliation(s)
- Ben A Meinen
- Institute for Protein Innovation, Harvard Institutes of Medicine 4 Blackfan Circle, Room 941 Boston, MA 02115-5701 Boston, USA
- Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Christopher D Bahl
- Institute for Protein Innovation, Harvard Institutes of Medicine 4 Blackfan Circle, Room 941 Boston, MA 02115-5701 Boston, USA
- Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
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25
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Pan X, Kortemme T. Recent advances in de novo protein design: Principles, methods, and applications. J Biol Chem 2021; 296:100558. [PMID: 33744284 PMCID: PMC8065224 DOI: 10.1016/j.jbc.2021.100558] [Citation(s) in RCA: 90] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 03/12/2021] [Accepted: 03/16/2021] [Indexed: 02/06/2023] Open
Abstract
The computational de novo protein design is increasingly applied to address a number of key challenges in biomedicine and biological engineering. Successes in expanding applications are driven by advances in design principles and methods over several decades. Here, we review recent innovations in major aspects of the de novo protein design and include how these advances were informed by principles of protein architecture and interactions derived from the wealth of structures in the Protein Data Bank. We describe developments in de novo generation of designable backbone structures, optimization of sequences, design scoring functions, and the design of the function. The advances not only highlight design goals reachable now but also point to the challenges and opportunities for the future of the field.
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Affiliation(s)
- Xingjie Pan
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California, USA; UC Berkeley - UCSF Graduate Program in Bioengineering, University of California San Francisco, San Francisco, California, USA.
| | - Tanja Kortemme
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California, USA; UC Berkeley - UCSF Graduate Program in Bioengineering, University of California San Francisco, San Francisco, California, USA; Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, California, USA.
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26
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Adolf-Bryfogle J, Teets FD, Bahl CD. Toward complete rational control over protein structure and function through computational design. Curr Opin Struct Biol 2020; 66:170-177. [PMID: 33276237 DOI: 10.1016/j.sbi.2020.10.015] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 10/08/2020] [Accepted: 10/19/2020] [Indexed: 11/28/2022]
Abstract
The grand challenge of protein design is a general method for producing a polypeptide with arbitrary functionality, conformation, and biochemical properties. To that end, a wide variety of methods have been developed for the improvement of native proteins, the design of ideal proteins de novo, and the redesign of suboptimal proteins with better-performing substructures. These methods employ informatic comparisons of function-structure-sequence relationships as well as knowledge-based evaluation of protein properties to narrow the immense protein sequence search space down to an enumerable and often manually evaluable set of structures that meet specified criteria. While arbitrary manipulation of protein-protein interfaces and molecular catalysis remains an unsolved problem, and no protein shape or behavior manipulation algorithm is universally applicable, the promising results thus far are a strong indicator that a general approach to the arbitrary manipulation of polypeptides is within reach.
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Affiliation(s)
- Jared Adolf-Bryfogle
- Institute for Protein Innovation, Boston, MA 02115, USA; Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA; Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Frank D Teets
- Institute for Protein Innovation, Boston, MA 02115, USA; Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA; Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Christopher D Bahl
- Institute for Protein Innovation, Boston, MA 02115, USA; Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA; Department of Pediatrics, Harvard Medical School, Boston, MA, USA.
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27
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Pan X, Thompson MC, Zhang Y, Liu L, Fraser JS, Kelly MJS, Kortemme T. Expanding the space of protein geometries by computational design of de novo fold families. Science 2020; 369:1132-1136. [PMID: 32855341 DOI: 10.1126/science.abc0881] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 07/14/2020] [Indexed: 01/03/2023]
Abstract
Naturally occurring proteins vary the precise geometries of structural elements to create distinct shapes optimal for function. We present a computational design method, loop-helix-loop unit combinatorial sampling (LUCS), that mimics nature's ability to create families of proteins with the same overall fold but precisely tunable geometries. Through near-exhaustive sampling of loop-helix-loop elements, LUCS generates highly diverse geometries encompassing those found in nature but also surpassing known structure space. Biophysical characterization showed that 17 (38%) of 45 tested LUCS designs encompassing two different structural topologies were well folded, including 16 with designed non-native geometries. Four experimentally solved structures closely matched the designs. LUCS greatly expands the designable structure space and offers a new paradigm for designing proteins with tunable geometries that may be customizable for novel functions.
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Affiliation(s)
- Xingjie Pan
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA. .,UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco, CA, USA
| | - Michael C Thompson
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA
| | - Yang Zhang
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA
| | - Lin Liu
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA
| | - James S Fraser
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA.,Quantitative Biosciences Institute, University of California, San Francisco, CA, USA
| | - Mark J S Kelly
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA
| | - Tanja Kortemme
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA. .,UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco, CA, USA.,Quantitative Biosciences Institute, University of California, San Francisco, CA, USA.,Chan Zuckerberg Biohub, San Francisco, CA, USA
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28
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Leman JK, Weitzner BD, Lewis SM, Adolf-Bryfogle J, Alam N, Alford RF, Aprahamian M, Baker D, Barlow KA, Barth P, Basanta B, Bender BJ, Blacklock K, Bonet J, Boyken SE, Bradley P, Bystroff C, Conway P, Cooper S, Correia BE, Coventry B, Das R, De Jong RM, DiMaio F, Dsilva L, Dunbrack R, Ford AS, Frenz B, Fu DY, Geniesse C, Goldschmidt L, Gowthaman R, Gray JJ, Gront D, Guffy S, Horowitz S, Huang PS, Huber T, Jacobs TM, Jeliazkov JR, Johnson DK, Kappel K, Karanicolas J, Khakzad H, Khar KR, Khare SD, Khatib F, Khramushin A, King IC, Kleffner R, Koepnick B, Kortemme T, Kuenze G, Kuhlman B, Kuroda D, Labonte JW, Lai JK, Lapidoth G, Leaver-Fay A, Lindert S, Linsky T, London N, Lubin JH, Lyskov S, Maguire J, Malmström L, Marcos E, Marcu O, Marze NA, Meiler J, Moretti R, Mulligan VK, Nerli S, Norn C, Ó'Conchúir S, Ollikainen N, Ovchinnikov S, Pacella MS, Pan X, Park H, Pavlovicz RE, Pethe M, Pierce BG, Pilla KB, Raveh B, Renfrew PD, Burman SSR, Rubenstein A, Sauer MF, Scheck A, Schief W, Schueler-Furman O, Sedan Y, Sevy AM, Sgourakis NG, Shi L, Siegel JB, Silva DA, Smith S, Song Y, Stein A, Szegedy M, Teets FD, Thyme SB, Wang RYR, Watkins A, Zimmerman L, Bonneau R. Macromolecular modeling and design in Rosetta: recent methods and frameworks. Nat Methods 2020; 17:665-680. [PMID: 32483333 PMCID: PMC7603796 DOI: 10.1038/s41592-020-0848-2] [Citation(s) in RCA: 402] [Impact Index Per Article: 100.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 04/22/2020] [Indexed: 12/12/2022]
Abstract
The Rosetta software for macromolecular modeling, docking and design is extensively used in laboratories worldwide. During two decades of development by a community of laboratories at more than 60 institutions, Rosetta has been continuously refactored and extended. Its advantages are its performance and interoperability between broad modeling capabilities. Here we review tools developed in the last 5 years, including over 80 methods. We discuss improvements to the score function, user interfaces and usability. Rosetta is available at http://www.rosettacommons.org.
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Affiliation(s)
- Julia Koehler Leman
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA.
- Department of Biology, New York University, New York, New York, USA.
| | - Brian D Weitzner
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Lyell Immunopharma Inc., Seattle, WA, USA
| | - Steven M Lewis
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biochemistry, Duke University, Durham, NC, USA
- Cyrus Biotechnology, Seattle, WA, USA
| | - Jared Adolf-Bryfogle
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Nawsad Alam
- Department of Microbiology and Molecular Genetics, IMRIC, Ein Kerem Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Rebecca F Alford
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Melanie Aprahamian
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, OH, USA
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Kyle A Barlow
- Graduate Program in Bioinformatics, University of California San Francisco, San Francisco, CA, USA
| | - Patrick Barth
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Baylor College of Medicine, Department of Pharmacology, Houston, TX, USA
| | - Benjamin Basanta
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Biological Physics Structure and Design PhD Program, University of Washington, Seattle, WA, USA
| | - Brian J Bender
- Department of Pharmacology, Vanderbilt University, Nashville, TN, USA
| | - Kristin Blacklock
- Institute of Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Jaume Bonet
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Scott E Boyken
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Lyell Immunopharma Inc., Seattle, WA, USA
| | - Phil Bradley
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Chris Bystroff
- Department of Biological Sciences, Rensselaer Polytechnic Institute, Troy, NY, USA
| | - Patrick Conway
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Seth Cooper
- Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA
| | - Bruno E Correia
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Brian Coventry
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Rhiju Das
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Frank DiMaio
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Lorna Dsilva
- Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA
| | - Roland Dunbrack
- Institute for Cancer Research, Fox Chase Cancer Center, Philadelphia, PA, USA
| | - Alexander S Ford
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Brandon Frenz
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Cyrus Biotechnology, Seattle, WA, USA
| | - Darwin Y Fu
- Department of Chemistry, Vanderbilt University, Nashville, TN, USA
| | - Caleb Geniesse
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Ragul Gowthaman
- University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD, USA
- Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD, USA
| | - Jeffrey J Gray
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA
- Program in Molecular Biophysics, Johns Hopkins University, Baltimore, MD, USA
| | - Dominik Gront
- Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, Warsaw, Poland
| | - Sharon Guffy
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Scott Horowitz
- Department of Chemistry & Biochemistry, University of Denver, Denver, CO, USA
- The Knoebel Institute for Healthy Aging, University of Denver, Denver, CO, USA
| | - Po-Ssu Huang
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Thomas Huber
- Research School of Chemistry, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Tim M Jacobs
- Program in Bioinformatics and Computational Biology, Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - David K Johnson
- Center for Computational Biology, University of Kansas, Lawrence, KS, USA
| | - Kalli Kappel
- Biophysics Program, Stanford University, Stanford, CA, USA
| | - John Karanicolas
- Institute for Cancer Research, Fox Chase Cancer Center, Philadelphia, PA, USA
| | - Hamed Khakzad
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Institute for Computational Science, University of Zurich, Zurich, Switzerland
- S3IT, University of Zurich, Zurich, Switzerland
| | - Karen R Khar
- Cyrus Biotechnology, Seattle, WA, USA
- Center for Computational Biology, University of Kansas, Lawrence, KS, USA
| | - Sagar D Khare
- Institute of Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
- Department of Chemistry and Chemical Biology, The State University of New Jersey, Piscataway, NJ, USA
- Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
- Computational Biology and Molecular Biophysics Program, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Firas Khatib
- Department of Computer and Information Science, University of Massachusetts Dartmouth, Dartmouth, MA, USA
| | - Alisa Khramushin
- Department of Microbiology and Molecular Genetics, IMRIC, Ein Kerem Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Indigo C King
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Cyrus Biotechnology, Seattle, WA, USA
| | - Robert Kleffner
- Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA
| | - Brian Koepnick
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Tanja Kortemme
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Georg Kuenze
- Department of Chemistry, Vanderbilt University, Nashville, TN, USA
- Center for Structural Biology, Vanderbilt University, Nashville, TN, USA
| | - Brian Kuhlman
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Daisuke Kuroda
- Medical Device Development and Regulation Research Center, School of Engineering, University of Tokyo, Tokyo, Japan
- Department of Bioengineering, School of Engineering, University of Tokyo, Tokyo, Japan
| | - Jason W Labonte
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA
- Department of Chemistry, Franklin & Marshall College, Lancaster, PA, USA
| | - Jason K Lai
- Baylor College of Medicine, Department of Pharmacology, Houston, TX, USA
| | - Gideon Lapidoth
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Andrew Leaver-Fay
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Steffen Lindert
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, OH, USA
| | - Thomas Linsky
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Nir London
- Department of Microbiology and Molecular Genetics, IMRIC, Ein Kerem Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Joseph H Lubin
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Sergey Lyskov
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jack Maguire
- Program in Bioinformatics and Computational Biology, Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Lars Malmström
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Institute for Computational Science, University of Zurich, Zurich, Switzerland
- S3IT, University of Zurich, Zurich, Switzerland
- Division of Infection Medicine, Department of Clinical Sciences Lund, Faculty of Medicine, Lund University, Lund, Sweden
| | - Enrique Marcos
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Research in Biomedicine Barcelona, The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Orly Marcu
- Department of Microbiology and Molecular Genetics, IMRIC, Ein Kerem Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Nicholas A Marze
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jens Meiler
- Center for Structural Biology, Vanderbilt University, Nashville, TN, USA
- Departments of Chemistry, Pharmacology and Biomedical Informatics, Vanderbilt University, Nashville, TN, USA
- Institute for Chemical Biology, Vanderbilt University, Nashville, TN, USA
| | - Rocco Moretti
- Department of Chemistry, Vanderbilt University, Nashville, TN, USA
| | - Vikram Khipple Mulligan
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Santrupti Nerli
- Department of Computer Science, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Christoffer Norn
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Shane Ó'Conchúir
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Noah Ollikainen
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Sergey Ovchinnikov
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA
| | - Michael S Pacella
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Xingjie Pan
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Hahnbeom Park
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Ryan E Pavlovicz
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Cyrus Biotechnology, Seattle, WA, USA
| | - Manasi Pethe
- Department of Chemistry and Chemical Biology, The State University of New Jersey, Piscataway, NJ, USA
- Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Brian G Pierce
- University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD, USA
- Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD, USA
| | - Kala Bharath Pilla
- Research School of Chemistry, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Barak Raveh
- Department of Microbiology and Molecular Genetics, IMRIC, Ein Kerem Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - P Douglas Renfrew
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA
| | - Shourya S Roy Burman
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Aliza Rubenstein
- Institute of Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
- Computational Biology and Molecular Biophysics Program, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Marion F Sauer
- Chemical and Physical Biology Program, Vanderbilt Vaccine Center, Vanderbilt University, Nashville, TN, USA
| | - Andreas Scheck
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - William Schief
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Ora Schueler-Furman
- Department of Microbiology and Molecular Genetics, IMRIC, Ein Kerem Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Yuval Sedan
- Department of Microbiology and Molecular Genetics, IMRIC, Ein Kerem Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Alexander M Sevy
- Chemical and Physical Biology Program, Vanderbilt Vaccine Center, Vanderbilt University, Nashville, TN, USA
| | - Nikolaos G Sgourakis
- Department of Chemistry and Biochemistry, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Lei Shi
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Justin B Siegel
- Department of Chemistry, University of California, Davis, Davis, CA, USA
- Department of Biochemistry and Molecular Medicine, University of California, Davis, Davis, California, USA
- Genome Center, University of California, Davis, Davis, CA, USA
| | | | - Shannon Smith
- Department of Chemistry, Vanderbilt University, Nashville, TN, USA
| | - Yifan Song
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
- Cyrus Biotechnology, Seattle, WA, USA
| | - Amelie Stein
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Maria Szegedy
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Frank D Teets
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Summer B Thyme
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Ray Yu-Ruei Wang
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Andrew Watkins
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA
| | - Lior Zimmerman
- Department of Microbiology and Molecular Genetics, IMRIC, Ein Kerem Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Richard Bonneau
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA.
- Department of Biology, New York University, New York, New York, USA.
- Department of Computer Science, New York University, New York, NY, USA.
- Center for Data Science, New York University, New York, NY, USA.
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29
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Brunette TJ, Bick MJ, Hansen JM, Chow CM, Kollman JM, Baker D. Modular repeat protein sculpting using rigid helical junctions. Proc Natl Acad Sci U S A 2020; 117:8870-8875. [PMID: 32245816 PMCID: PMC7183188 DOI: 10.1073/pnas.1908768117] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
The ability to precisely design large proteins with diverse shapes would enable applications ranging from the design of protein binders that wrap around their target to the positioning of multiple functional sites in specified orientations. We describe a protein backbone design method for generating a wide range of rigid fusions between helix-containing proteins and use it to design 75,000 structurally unique junctions between monomeric and homo-oligomeric de novo designed and ankyrin repeat proteins (RPs). Of the junction designs that were experimentally characterized, 82% have circular dichroism and solution small-angle X-ray scattering profiles consistent with the design models and are stable at 95 °C. Crystal structures of four designed junctions were in close agreement with the design models with rmsds ranging from 0.9 to 1.6 Å. Electron microscopic images of extended tetrameric structures and ∼10-nm-diameter "L" and "V" shapes generated using the junctions are close to the design models, demonstrating the control the rigid junctions provide for protein shape sculpting over multiple nanometer length scales.
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Affiliation(s)
- T J Brunette
- Department of Biochemistry, University of Washington, Seattle, WA 98195;
- Institute for Protein Design, University of Washington, Seattle, WA 98195
| | - Matthew J Bick
- Department of Biochemistry, University of Washington, Seattle, WA 98195
- Institute for Protein Design, University of Washington, Seattle, WA 98195
| | - Jesse M Hansen
- Department of Biochemistry, University of Washington, Seattle, WA 98195
- Graduate Program in Biological Physics, Structure, and Design, University of Washington, Seattle, WA 98195
| | - Cameron M Chow
- Department of Biochemistry, University of Washington, Seattle, WA 98195
- Institute for Protein Design, University of Washington, Seattle, WA 98195
| | - Justin M Kollman
- Department of Biochemistry, University of Washington, Seattle, WA 98195
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle, WA 98195
- Institute for Protein Design, University of Washington, Seattle, WA 98195
- Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195
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30
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Surpeta B, Sequeiros-Borja CE, Brezovsky J. Dynamics, a Powerful Component of Current and Future in Silico Approaches for Protein Design and Engineering. Int J Mol Sci 2020; 21:E2713. [PMID: 32295283 PMCID: PMC7215530 DOI: 10.3390/ijms21082713] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 04/10/2020] [Accepted: 04/12/2020] [Indexed: 12/13/2022] Open
Abstract
Computational prediction has become an indispensable aid in the processes of engineering and designing proteins for various biotechnological applications. With the tremendous progress in more powerful computer hardware and more efficient algorithms, some of in silico tools and methods have started to apply the more realistic description of proteins as their conformational ensembles, making protein dynamics an integral part of their prediction workflows. To help protein engineers to harness benefits of considering dynamics in their designs, we surveyed new tools developed for analyses of conformational ensembles in order to select engineering hotspots and design mutations. Next, we discussed the collective evolution towards more flexible protein design methods, including ensemble-based approaches, knowledge-assisted methods, and provable algorithms. Finally, we highlighted apparent challenges that current approaches are facing and provided our perspectives on their further development.
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Affiliation(s)
- Bartłomiej Surpeta
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Uniwersytetu Poznanskiego 6, 61-614 Poznan, Poland; (B.S.); (C.E.S.-B.)
- International Institute of Molecular and Cell Biology in Warsaw, Ks Trojdena 4, 02-109 Warsaw, Poland
| | - Carlos Eduardo Sequeiros-Borja
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Uniwersytetu Poznanskiego 6, 61-614 Poznan, Poland; (B.S.); (C.E.S.-B.)
- International Institute of Molecular and Cell Biology in Warsaw, Ks Trojdena 4, 02-109 Warsaw, Poland
| | - Jan Brezovsky
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Uniwersytetu Poznanskiego 6, 61-614 Poznan, Poland; (B.S.); (C.E.S.-B.)
- International Institute of Molecular and Cell Biology in Warsaw, Ks Trojdena 4, 02-109 Warsaw, Poland
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31
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Liu Y, Zhan L, Xu C, Jiang H, Zhu C, Sun L, Sun C, Li X. α-Glucosidase inhibitors from Chinese bayberry (Morella rubra Sieb. et Zucc.) fruit: molecular docking and interaction mechanism of flavonols with different B-ring hydroxylations. RSC Adv 2020; 10:29347-29361. [PMID: 35521141 PMCID: PMC9055920 DOI: 10.1039/d0ra05015f] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Accepted: 07/29/2020] [Indexed: 11/21/2022] Open
Abstract
Inhibition of α-glucosidase alleviates postprandial high glycemic levels in diabetic or prediabetic population.
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Affiliation(s)
- Yilong Liu
- Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology
- Zhejiang University
- Hangzhou
- China
| | - Liuhuan Zhan
- Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology
- Zhejiang University
- Hangzhou
- China
| | - Chang Xu
- Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology
- Zhejiang University
- Hangzhou
- China
| | - Huamin Jiang
- Hangzhou Lichuan Ecological Agriculture Development Co., Ltd
- Hangzhou
- China
| | - Changqing Zhu
- Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology
- Zhejiang University
- Hangzhou
- China
| | - Linxiao Sun
- Key Laboratory of Diagnosis and Treatment of Severe Hepato-Pancreatic Diseases of Zhejiang Province
- Zhejiang Provincial Top Key Discipline in Surgery
- Wenzhou Medical University First Affiliated Hospital
- Wenzhou
- China
| | - Chongde Sun
- Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology
- Zhejiang University
- Hangzhou
- China
| | - Xian Li
- Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology
- Zhejiang University
- Hangzhou
- China
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Kuhlman B. Designing protein structures and complexes with the molecular modeling program Rosetta. J Biol Chem 2019; 294:19436-19443. [PMID: 31699898 DOI: 10.1074/jbc.aw119.008144] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Proteins perform an amazingly diverse set of functions in all aspects of life. Critical to the function of many proteins are the highly specific three-dimensional structures they adopt. For this reason, there is strong interest in learning how to rationally design proteins that adopt user-defined structures. Over the last 25 years, there has been significant progress in the field of computational protein design as rotamer-based sequence optimization protocols have enabled accurate design of protein tertiary and quaternary structure. In this award article, I will summarize how the molecular modeling program Rosetta is used to design new protein structures and describe how we have taken advantage of this capability to create proteins that have important applications in research and medicine. I will highlight three protein design stories: the use of protein interface design to create therapeutic bispecific antibodies, the engineering of light-inducible proteins that can be used to recruit proteins to specific locations in the cell, and the de novo design of new protein structures from pieces of naturally occurring proteins.
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Affiliation(s)
- Brian Kuhlman
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina 27599-7260 .,Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
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Xu Z, Cen YK, Zou SP, Xue YP, Zheng YG. Recent advances in the improvement of enzyme thermostability by structure modification. Crit Rev Biotechnol 2019; 40:83-98. [DOI: 10.1080/07388551.2019.1682963] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- Zhe Xu
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, China
- Engineering Research Center of Bioconversion and Biopurification of Ministry of Education, Zhejiang University of Technology, Hangzhou, China
| | - Yu-Ke Cen
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, China
- Engineering Research Center of Bioconversion and Biopurification of Ministry of Education, Zhejiang University of Technology, Hangzhou, China
| | - Shu-Ping Zou
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, China
- Engineering Research Center of Bioconversion and Biopurification of Ministry of Education, Zhejiang University of Technology, Hangzhou, China
| | - Ya-Ping Xue
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, China
- Engineering Research Center of Bioconversion and Biopurification of Ministry of Education, Zhejiang University of Technology, Hangzhou, China
| | - Yu-Guo Zheng
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, China
- Engineering Research Center of Bioconversion and Biopurification of Ministry of Education, Zhejiang University of Technology, Hangzhou, China
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Kuhlman B, Bradley P. Advances in protein structure prediction and design. Nat Rev Mol Cell Biol 2019; 20:681-697. [PMID: 31417196 PMCID: PMC7032036 DOI: 10.1038/s41580-019-0163-x] [Citation(s) in RCA: 373] [Impact Index Per Article: 74.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/19/2019] [Indexed: 12/18/2022]
Abstract
The prediction of protein three-dimensional structure from amino acid sequence has been a grand challenge problem in computational biophysics for decades, owing to its intrinsic scientific interest and also to the many potential applications for robust protein structure prediction algorithms, from genome interpretation to protein function prediction. More recently, the inverse problem - designing an amino acid sequence that will fold into a specified three-dimensional structure - has attracted growing attention as a potential route to the rational engineering of proteins with functions useful in biotechnology and medicine. Methods for the prediction and design of protein structures have advanced dramatically in the past decade. Increases in computing power and the rapid growth in protein sequence and structure databases have fuelled the development of new data-intensive and computationally demanding approaches for structure prediction. New algorithms for designing protein folds and protein-protein interfaces have been used to engineer novel high-order assemblies and to design from scratch fluorescent proteins with novel or enhanced properties, as well as signalling proteins with therapeutic potential. In this Review, we describe current approaches for protein structure prediction and design and highlight a selection of the successful applications they have enabled.
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Affiliation(s)
- Brian Kuhlman
- Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill, NC, USA.
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA.
| | - Philip Bradley
- Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
- Institute for Protein Design, University of Washington, Seattle, WA, USA.
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