51
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Abrusán G, Ascher DB, Inouye M. Known allosteric proteins have central roles in genetic disease. PLoS Comput Biol 2022; 18:e1009806. [PMID: 35139069 PMCID: PMC10138267 DOI: 10.1371/journal.pcbi.1009806] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 04/27/2023] [Accepted: 01/05/2022] [Indexed: 12/15/2022] Open
Abstract
Allostery is a form of protein regulation, where ligands that bind sites located apart from the active site can modify the activity of the protein. The molecular mechanisms of allostery have been extensively studied, because allosteric sites are less conserved than active sites, and drugs targeting them are more specific than drugs binding the active sites. Here we quantify the importance of allostery in genetic disease. We show that 1) known allosteric proteins are central in disease networks, contribute to genetic disease and comorbidities much more than non-allosteric proteins, and there is an association between being allosteric and involvement in disease; 2) they are enriched in many major disease types like hematopoietic diseases, cardiovascular diseases, cancers, diabetes, or diseases of the central nervous system; 3) variants from cancer genome-wide association studies are enriched near allosteric proteins, indicating their importance to polygenic traits; and 4) the importance of allosteric proteins in disease is due, at least partly, to their central positions in protein-protein interaction networks, and less due to their dynamical properties.
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Affiliation(s)
- György Abrusán
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, School of Medicine, University of Cambridge, Cambridge, United Kingdom
- * E-mail:
| | - David B. Ascher
- Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom
- Structural Biology and Bioinformatics, Department of Biochemistry, Bio21 Institute, University of Melbourne, Melbourne, Australia
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, School of Medicine, University of Cambridge, Cambridge, United Kingdom
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Australia
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, United Kingdom
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, United Kingdom
- The Alan Turing Institute, London, United Kingdom
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52
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Cheng WWL, Arcario MJ, Petroff JT. Druggable Lipid Binding Sites in Pentameric Ligand-Gated Ion Channels and Transient Receptor Potential Channels. Front Physiol 2022; 12:798102. [PMID: 35069257 PMCID: PMC8777383 DOI: 10.3389/fphys.2021.798102] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 12/02/2021] [Indexed: 12/17/2022] Open
Abstract
Lipids modulate the function of many ion channels, possibly through direct lipid-protein interactions. The recent outpouring of ion channel structures by cryo-EM has revealed many lipid binding sites. Whether these sites mediate lipid modulation of ion channel function is not firmly established in most cases. However, it is intriguing that many of these lipid binding sites are also known sites for other allosteric modulators or drugs, supporting the notion that lipids act as endogenous allosteric modulators through these sites. Here, we review such lipid-drug binding sites, focusing on pentameric ligand-gated ion channels and transient receptor potential channels. Notable examples include sites for phospholipids and sterols that are shared by anesthetics and vanilloids. We discuss some implications of lipid binding at these sites including the possibility that lipids can alter drug potency or that understanding protein-lipid interactions can guide drug design. Structures are only the first step toward understanding the mechanism of lipid modulation at these sites. Looking forward, we identify knowledge gaps in the field and approaches to address them. These include defining the effects of lipids on channel function in reconstituted systems using asymmetric membranes and measuring lipid binding affinities at specific sites using native mass spectrometry, fluorescence binding assays, and computational approaches.
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Affiliation(s)
- Wayland W L Cheng
- Department of Anesthesiology, Washington University in St. Louis, St. Louis, MO, United States
| | - Mark J Arcario
- Department of Anesthesiology, Washington University in St. Louis, St. Louis, MO, United States
| | - John T Petroff
- Department of Anesthesiology, Washington University in St. Louis, St. Louis, MO, United States
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53
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Extracting phylogenetic dimensions of coevolution reveals hidden functional signals. Sci Rep 2022; 12:820. [PMID: 35039514 PMCID: PMC8764114 DOI: 10.1038/s41598-021-04260-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 12/17/2021] [Indexed: 11/08/2022] Open
Abstract
Despite the structural and functional information contained in the statistical coupling between pairs of residues in a protein, coevolution associated with function is often obscured by artifactual signals such as genetic drift, which shapes a protein's phylogenetic history and gives rise to concurrent variation between protein sequences that is not driven by selection for function. Here, we introduce a background model for phylogenetic contributions of statistical coupling that separates the coevolution signal due to inter-clade and intra-clade sequence comparisons and demonstrate that coevolution can be measured on multiple phylogenetic timescales within a single protein. Our method, nested coevolution (NC), can be applied as an extension to any coevolution metric. We use NC to demonstrate that poorly conserved residues can nonetheless have important roles in protein function. Moreover, NC improved the structural-contact predictions of several coevolution-based methods, particularly in subsampled alignments with fewer sequences. NC also lowered the noise in detecting functional sectors of collectively coevolving residues. Sectors of coevolving residues identified after application of NC were more spatially compact and phylogenetically distinct from the rest of the protein, and strongly enriched for mutations that disrupt protein activity. Thus, our conceptualization of the phylogenetic separation of coevolution provides the potential to further elucidate relationships among protein evolution, function, and genetic diseases.
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54
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Roychowdury H, Romero PA. Microfluidic deep mutational scanning of the human executioner caspases reveals differences in structure and regulation. Cell Death Dis 2022; 8:7. [PMID: 35013287 PMCID: PMC8748541 DOI: 10.1038/s41420-021-00799-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 12/02/2021] [Accepted: 12/14/2021] [Indexed: 12/19/2022]
Abstract
The human caspase family comprises 12 cysteine proteases that are centrally involved in cell death and inflammation responses. The members of this family have conserved sequences and structures, highly similar enzymatic activities and substrate preferences, and overlapping physiological roles. In this paper, we present a deep mutational scan of the executioner caspases CASP3 and CASP7 to dissect differences in their structure, function, and regulation. Our approach leverages high-throughput microfluidic screening to analyze hundreds of thousands of caspase variants in tightly controlled in vitro reactions. The resulting data provides a large-scale and unbiased view of the impact of amino acid substitutions on the proteolytic activity of CASP3 and CASP7. We use this data to pinpoint key functional differences between CASP3 and CASP7, including a secondary internal cleavage site, CASP7 Q196 that is not present in CASP3. Our results will open avenues for inquiry in caspase function and regulation that could potentially inform the development of future caspase-specific therapeutics.
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Affiliation(s)
| | - Philip A Romero
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA. .,Department of Chemical & Biological Engineering, University of Wisconsin-Madison, Madison, WI, USA. .,The University of Wisconsin Carbone Cancer Center, Madison, WI, USA.
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55
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Mixed component metal-organic frameworks: Heterogeneity and complexity at the service of application performances. Coord Chem Rev 2022. [DOI: 10.1016/j.ccr.2021.214273] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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56
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Chu WT, Yan Z, Chu X, Zheng X, Liu Z, Xu L, Zhang K, Wang J. Physics of biomolecular recognition and conformational dynamics. REPORTS ON PROGRESS IN PHYSICS. PHYSICAL SOCIETY (GREAT BRITAIN) 2021; 84:126601. [PMID: 34753115 DOI: 10.1088/1361-6633/ac3800] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 11/09/2021] [Indexed: 06/13/2023]
Abstract
Biomolecular recognition usually leads to the formation of binding complexes, often accompanied by large-scale conformational changes. This process is fundamental to biological functions at the molecular and cellular levels. Uncovering the physical mechanisms of biomolecular recognition and quantifying the key biomolecular interactions are vital to understand these functions. The recently developed energy landscape theory has been successful in quantifying recognition processes and revealing the underlying mechanisms. Recent studies have shown that in addition to affinity, specificity is also crucial for biomolecular recognition. The proposed physical concept of intrinsic specificity based on the underlying energy landscape theory provides a practical way to quantify the specificity. Optimization of affinity and specificity can be adopted as a principle to guide the evolution and design of molecular recognition. This approach can also be used in practice for drug discovery using multidimensional screening to identify lead compounds. The energy landscape topography of molecular recognition is important for revealing the underlying flexible binding or binding-folding mechanisms. In this review, we first introduce the energy landscape theory for molecular recognition and then address four critical issues related to biomolecular recognition and conformational dynamics: (1) specificity quantification of molecular recognition; (2) evolution and design in molecular recognition; (3) flexible molecular recognition; (4) chromosome structural dynamics. The results described here and the discussions of the insights gained from the energy landscape topography can provide valuable guidance for further computational and experimental investigations of biomolecular recognition and conformational dynamics.
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Affiliation(s)
- Wen-Ting Chu
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, People's Republic of China
| | - Zhiqiang Yan
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, People's Republic of China
| | - Xiakun Chu
- Department of Chemistry & Physics, State University of New York at Stony Brook, Stony Brook, NY 11794, United States of America
| | - Xiliang Zheng
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, People's Republic of China
| | - Zuojia Liu
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, People's Republic of China
| | - Li Xu
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, People's Republic of China
| | - Kun Zhang
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, People's Republic of China
| | - Jin Wang
- Department of Chemistry & Physics, State University of New York at Stony Brook, Stony Brook, NY 11794, United States of America
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57
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Mokhtari DA, Appel MJ, Fordyce PM, Herschlag D. High throughput and quantitative enzymology in the genomic era. Curr Opin Struct Biol 2021; 71:259-273. [PMID: 34592682 PMCID: PMC8648990 DOI: 10.1016/j.sbi.2021.07.010] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 07/23/2021] [Indexed: 12/28/2022]
Abstract
Accurate predictions from models based on physical principles are the ultimate metric of our biophysical understanding. Although there has been stunning progress toward structure prediction, quantitative prediction of enzyme function has remained challenging. Realizing this goal will require large numbers of quantitative measurements of rate and binding constants and the use of these ground-truth data sets to guide the development and testing of these quantitative models. Ground truth data more closely linked to the underlying physical forces are also desired. Here, we describe technological advances that enable both types of ground truth measurements. These advances allow classic models to be tested, provide novel mechanistic insights, and place us on the path toward a predictive understanding of enzyme structure and function.
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Affiliation(s)
- D A Mokhtari
- Department of Biochemistry, Stanford University, Stanford, CA, 94305, USA
| | - M J Appel
- Department of Biochemistry, Stanford University, Stanford, CA, 94305, USA
| | - P M Fordyce
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA; ChEM-H Institute, Stanford University, Stanford, CA, 94305, USA; Department of Genetics, Stanford University, Stanford, CA, 94305, USA; Chan Zuckerberg Biohub San Francisco, CA, 94110, USA.
| | - D Herschlag
- Department of Biochemistry, Stanford University, Stanford, CA, 94305, USA; Department of Chemical Engineering, Stanford University, Stanford, CA, 94305, USA; ChEM-H Institute, Stanford University, Stanford, CA, 94305, USA.
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58
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Zhao VY, Rodrigues JV, Lozovsky ER, Hartl DL, Shakhnovich EI. Switching an active site helix in dihydrofolate reductase reveals limits to subdomain modularity. Biophys J 2021; 120:4738-4750. [PMID: 34571014 PMCID: PMC8595743 DOI: 10.1016/j.bpj.2021.09.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 09/14/2021] [Accepted: 09/22/2021] [Indexed: 11/23/2022] Open
Abstract
To what degree are individual structural elements within proteins modular such that similar structures from unrelated proteins can be interchanged? We study subdomain modularity by creating 20 chimeras of an enzyme, Escherichia coli dihydrofolate reductase (DHFR), in which a catalytically important, 10-residue α-helical sequence is replaced by α-helical sequences from a diverse set of proteins. The chimeras stably fold but have a range of diminished thermal stabilities and catalytic activities. Evolutionary coupling analysis indicates that the residues of this α-helix are under selection pressure to maintain catalytic activity in DHFR. Reversion to phenylalanine at key position 31 was found to partially restore catalytic activity, which could be explained by evolutionary coupling values. We performed molecular dynamics simulations using replica exchange with solute tempering. Chimeras with low catalytic activity exhibit nonhelical conformations that block the binding site and disrupt the positioning of the catalytically essential residue D27. Simulation observables and in vitro measurements of thermal stability and substrate-binding affinity are strongly correlated. Several E. coli strains with chromosomally integrated chimeric DHFRs can grow, with growth rates that follow predictions from a kinetic flux model that depends on the intracellular abundance and catalytic activity of DHFR. Our findings show that although α-helices are not universally substitutable, the molecular and fitness effects of modular segments can be predicted by the biophysical compatibility of the replacement segment.
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Affiliation(s)
- Victor Y Zhao
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - João V Rodrigues
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - Elena R Lozovsky
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts
| | - Daniel L Hartl
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts.
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59
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Naganathan AN, Kannan A. A hierarchy of coupling free energies underlie the thermodynamic and functional architecture of protein structures. Curr Res Struct Biol 2021; 3:257-267. [PMID: 34704074 PMCID: PMC8526763 DOI: 10.1016/j.crstbi.2021.09.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 09/08/2021] [Accepted: 09/30/2021] [Indexed: 12/22/2022] Open
Abstract
Protein sequences and structures evolve by satisfying varied physical and biochemical constraints. This multi-level selection is enabled not just by the patterning of amino acids on the sequence, but also via coupling between residues in the native structure. Here, we employ an energetically detailed statistical mechanical model with millions of microstates to extract such long-range structural correlations, i.e. thermodynamic coupling free energies, from a diverse family of protein structures. We find that despite the intricate and anisotropic distribution of coupling patterns, the majority of residues (>70%) are only marginally coupled contributing to functional motions and catalysis. Physical origins of ‘sectors’, determinants of native ensemble heterogeneity in extant, ancient and designed proteins, and the basis for allostery emerge naturally from coupling free energies. The statistical framework highlights how evolutionary selection and optimization occur at the level of global interaction network for a given protein fold impacting folding, function, and allosteric outputs. Evolution of protein structures occurs at the level of global interaction network. More than 70% of the protein residues are weakly or marginally coupled. Functional ‘sector’ regions are a manifestation of marginal coupling. Coupling indices vary across the entire proteins in extant-ancient and natural-designed pairs. The proposed methodology can be used to understand allostery and epistasis.
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Affiliation(s)
- Athi N Naganathan
- Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, 600036, India
| | - Adithi Kannan
- Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, 600036, India
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60
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Ni D, Chai Z, Wang Y, Li M, Yu Z, Liu Y, Lu S, Zhang J. Along the allostery stream: Recent advances in computational methods for allosteric drug discovery. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1585] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Duan Ni
- College of Pharmacy Ningxia Medical University Yinchuan China
- The Charles Perkins Centre University of Sydney Sydney New South Wales Australia
| | - Zongtao Chai
- Department of Hepatic Surgery VI, Eastern Hepatobiliary Surgery Hospital Second Military Medical University Shanghai China
| | - Ying Wang
- State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Mingyu Li
- State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education Shanghai Jiao Tong University School of Medicine Shanghai China
| | | | - Yaqin Liu
- Medicinal Chemistry and Bioinformatics Center Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Shaoyong Lu
- College of Pharmacy Ningxia Medical University Yinchuan China
- State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education Shanghai Jiao Tong University School of Medicine Shanghai China
- Medicinal Chemistry and Bioinformatics Center Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Jian Zhang
- College of Pharmacy Ningxia Medical University Yinchuan China
- State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education Shanghai Jiao Tong University School of Medicine Shanghai China
- Medicinal Chemistry and Bioinformatics Center Shanghai Jiao Tong University School of Medicine Shanghai China
- School of Pharmaceutical Sciences Zhengzhou University Zhengzhou China
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61
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Evolution of dynamical networks enhances catalysis in a designer enzyme. Nat Chem 2021; 13:1017-1022. [PMID: 34413499 DOI: 10.1038/s41557-021-00763-6] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 06/30/2021] [Indexed: 02/08/2023]
Abstract
Activation heat capacity is emerging as a crucial factor in enzyme thermoadaptation, as shown by the non-Arrhenius behaviour of many natural enzymes. However, its physical origin and relationship to the evolution of catalytic activity remain uncertain. Here we show that directed evolution of a computationally designed Kemp eliminase reshapes protein dynamics, which gives rise to an activation heat capacity absent in the original design. These changes buttress transition-state stabilization. Extensive molecular dynamics simulations show that evolution results in the closure of solvent-exposed loops and a better packing of the active site. Remarkably, this gives rise to a correlated dynamical network that involves the transition state and large parts of the protein. This network tightens the transition-state ensemble, which induces a negative activation heat capacity and non-linearity in the activity-temperature dependence. Our results have implications for understanding enzyme evolution and suggest that selectively targeting the conformational dynamics of the transition-state ensemble by design and evolution will expedite the creation of novel enzymes.
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62
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Shams A, Higgins SA, Fellmann C, Laughlin TG, Oakes BL, Lew R, Kim S, Lukarska M, Arnold M, Staahl BT, Doudna JA, Savage DF. Comprehensive deletion landscape of CRISPR-Cas9 identifies minimal RNA-guided DNA-binding modules. Nat Commun 2021; 12:5664. [PMID: 34580310 PMCID: PMC8476515 DOI: 10.1038/s41467-021-25992-8] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 09/10/2021] [Indexed: 11/28/2022] Open
Abstract
Proteins evolve through the modular rearrangement of elements known as domains. Extant, multidomain proteins are hypothesized to be the result of domain accretion, but there has been limited experimental validation of this idea. Here, we introduce a technique for genetic minimization by iterative size-exclusion and recombination (MISER) for comprehensively making all possible deletions of a protein. Using MISER, we generate a deletion landscape for the CRISPR protein Cas9. We find that the catalytically-dead Streptococcus pyogenes Cas9 can tolerate large single deletions in the REC2, REC3, HNH, and RuvC domains, while still functioning in vitro and in vivo, and that these deletions can be stacked together to engineer minimal, DNA-binding effector proteins. In total, our results demonstrate that extant proteins retain significant modularity from the accretion process and, as genetic size is a major limitation for viral delivery systems, establish a general technique to improve genome editing and gene therapy-based therapeutics.
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Affiliation(s)
- Arik Shams
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Sean A Higgins
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, 94720, USA
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, 94720, USA
- Scribe Therapeutics, Alameda, CA, 94501, USA
| | - Christof Fellmann
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, 94720, USA
- Gladstone Institutes, San Francisco, CA, 94158, USA
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Thomas G Laughlin
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, 94720, USA
- Division of Biological Sciences, University of California, San Diego, San Diego, CA, 92093, USA
| | - Benjamin L Oakes
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, 94720, USA
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, 94720, USA
- Scribe Therapeutics, Alameda, CA, 94501, USA
| | - Rachel Lew
- Gladstone Institutes, San Francisco, CA, 94158, USA
| | - Shin Kim
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, 94720, USA
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Maria Lukarska
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, 94720, USA
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Madeline Arnold
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Brett T Staahl
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, 94720, USA
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, 94720, USA
- Scribe Therapeutics, Alameda, CA, 94501, USA
| | - Jennifer A Doudna
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, 94720, USA
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, 94720, USA
- Gladstone Institutes, San Francisco, CA, 94158, USA
- Graduate Group in Biophysics, University of California, Berkeley, Berkeley, CA, 94720, USA
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA, 94720, USA
- Howard Hughes Medical Institute, University of California, Berkeley, Berkeley, CA, 94720, USA
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
- Department of Chemistry, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - David F Savage
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, 94720, USA.
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, 94720, USA.
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63
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Markin CJ, Mokhtari DA, Sunden F, Appel MJ, Akiva E, Longwell SA, Sabatti C, Herschlag D, Fordyce PM. Revealing enzyme functional architecture via high-throughput microfluidic enzyme kinetics. Science 2021; 373:373/6553/eabf8761. [PMID: 34437092 DOI: 10.1126/science.abf8761] [Citation(s) in RCA: 84] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 05/24/2021] [Indexed: 12/21/2022]
Abstract
Systematic and extensive investigation of enzymes is needed to understand their extraordinary efficiency and meet current challenges in medicine and engineering. We present HT-MEK (High-Throughput Microfluidic Enzyme Kinetics), a microfluidic platform for high-throughput expression, purification, and characterization of more than 1500 enzyme variants per experiment. For 1036 mutants of the alkaline phosphatase PafA (phosphate-irrepressible alkaline phosphatase of Flavobacterium), we performed more than 670,000 reactions and determined more than 5000 kinetic and physical constants for multiple substrates and inhibitors. We uncovered extensive kinetic partitioning to a misfolded state and isolated catalytic effects, revealing spatially contiguous regions of residues linked to particular aspects of function. Regions included active-site proximal residues but extended to the enzyme surface, providing a map of underlying architecture not possible to derive from existing approaches. HT-MEK has applications that range from understanding molecular mechanisms to medicine, engineering, and design.
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Affiliation(s)
- C J Markin
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA
| | - D A Mokhtari
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA
| | - F Sunden
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA
| | - M J Appel
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA
| | - E Akiva
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA
| | - S A Longwell
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - C Sabatti
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA.,Department of Statistics, Stanford University, Stanford, CA 94305, USA
| | - D Herschlag
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA. .,Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA.,ChEM-H Institute, Stanford University, Stanford, CA 94305, USA
| | - P M Fordyce
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA. .,ChEM-H Institute, Stanford University, Stanford, CA 94305, USA.,Department of Genetics, Stanford University, Stanford, CA 94305, USA.,Chan Zuckerberg Biohub; San Francisco, CA 94110, USA
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64
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Abstract
Correlated motions in proteins arising from the collective movements of residues have long been proposed to be fundamentally important to key properties of proteins, from allostery and catalysis to evolvability. Recent breakthroughs in structural biology have made it possible to capture proteins undergoing complex conformational changes, yet intrinsic correlated motions within a conformation remain one of the least understood facets of protein structure. For many decades, the analysis of total X-ray scattering held the promise of animating crystal structures with correlated motions. With recent advances in both X-ray detectors and data interpretation methods, this long-held promise can now be met. In this Perspective, we will introduce how correlated motions are captured in total scattering and provide guidelines for the collection, interpretation, and validation of data. As structural biology continues to push the boundaries, we see an opportunity to gain atomistic insight into correlated motions using total scattering as a bridge between theory and experiment.
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Affiliation(s)
- Da Xu
- Department of Chemistry and Chemical Biology, Cornell University, 259 East Avenue, Ithaca, New York 14853, United States
| | - Steve P Meisburger
- Department of Chemistry and Chemical Biology, Cornell University, 259 East Avenue, Ithaca, New York 14853, United States
| | - Nozomi Ando
- Department of Chemistry and Chemical Biology, Cornell University, 259 East Avenue, Ithaca, New York 14853, United States
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65
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Cobos ES, Sánchez IE, Chemes LB, Martinez JC, Murciano-Calles J. A Thermodynamic Analysis of the Binding Specificity between Four Human PDZ Domains and Eight Host, Viral and Designed Ligands. Biomolecules 2021; 11:biom11081071. [PMID: 34439737 PMCID: PMC8393326 DOI: 10.3390/biom11081071] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 07/14/2021] [Accepted: 07/16/2021] [Indexed: 02/01/2023] Open
Abstract
PDZ domains are binding modules mostly involved in cell signaling and cell–cell junctions. These domains are able to recognize a wide variety of natural targets and, among the PDZ partners, viruses have been discovered to interact with their host via a PDZ domain. With such an array of relevant and diverse interactions, PDZ binding specificity has been thoroughly studied and a traditional classification has grouped PDZ domains in three major specificity classes. In this work, we have selected four human PDZ domains covering the three canonical specificity-class binding mode and a set of their corresponding binders, including host/natural, viral and designed PDZ motifs. Through calorimetric techniques, we have covered the entire cross interactions between the selected PDZ domains and partners. The results indicate a rather basic specificity in each PDZ domain, with two of the domains that bind their cognate and some non-cognate ligands and the two other domains that basically bind their cognate partners. On the other hand, the host partners mostly bind their corresponding PDZ domain and, interestingly, the viral ligands are able to bind most of the studied PDZ domains, even those not previously described. Some viruses may have evolved to use of the ability of the PDZ fold to bind multiple targets, with resulting affinities for the virus–host interactions that are, in some cases, higher than for host–host interactions.
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Affiliation(s)
- Eva S. Cobos
- Departamento Química Física, Unidad de Excelencia de Química Aplicada a Biomedicina y Medioambiente, Facultad de Ciencias, e Instituto de Biotecnología, Universidad de Granada, 18071 Granada, Spain; (E.S.C.); (J.C.M.)
| | - Ignacio E. Sánchez
- Laboratorio de Fisiología de Proteínas, Facultad de Ciencias Exactas y Naturales, Consejo Nacional de Investigaciones Científicas y Técnicas, Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, 1428 Buenos Aires, Argentina;
| | - Lucía B. Chemes
- Instituto de Investigaciones Biotecnológicas (IIBiO-CONICET), Universidad Nacional de San Martín, 1650 Buenos Aires, Argentina;
| | - Jose C. Martinez
- Departamento Química Física, Unidad de Excelencia de Química Aplicada a Biomedicina y Medioambiente, Facultad de Ciencias, e Instituto de Biotecnología, Universidad de Granada, 18071 Granada, Spain; (E.S.C.); (J.C.M.)
| | - Javier Murciano-Calles
- Departamento Química Física, Unidad de Excelencia de Química Aplicada a Biomedicina y Medioambiente, Facultad de Ciencias, e Instituto de Biotecnología, Universidad de Granada, 18071 Granada, Spain; (E.S.C.); (J.C.M.)
- Correspondence:
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66
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Chatzigoulas A, Cournia Z. Rational design of allosteric modulators: Challenges and successes. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1529] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Alexios Chatzigoulas
- Biomedical Research Foundation Academy of Athens Athens Greece
- Department of Informatics and Telecommunications National and Kapodistrian University of Athens Athens Greece
| | - Zoe Cournia
- Biomedical Research Foundation Academy of Athens Athens Greece
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67
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La Sala G, Gunnarsson A, Edman K, Tyrchan C, Hogner A, Frolov AI. Unraveling the Allosteric Cross-Talk between the Coactivator Peptide and the Ligand-Binding Site in the Glucocorticoid Receptor. J Chem Inf Model 2021; 61:3667-3680. [PMID: 34156843 DOI: 10.1021/acs.jcim.1c00323] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The glucocorticoid receptor (GR) is a nuclear receptor that controls critical biological processes by regulating the transcription of specific genes. There is a known allosteric cross-talk between the ligand and coregulator binding sites within the GR ligand-binding domain that is crucial for the control of the functional response. However, the molecular mechanisms underlying such an allosteric control remain elusive. Here, molecular dynamics (MD) simulations, bioinformatic analysis, and biophysical measurements are integrated to capture the structural and dynamic features of the allosteric cross-talk within the GR. We identified a network of evolutionarily conserved residues that enables the allosteric signal transduction, in agreement with experimental data. MD simulations clarify how such a network is dynamically interconnected and offer a mechanistic explanation of how different peptides affect the intensity of the allosteric signal. This study provides useful insights to elucidate the GR allosteric regulation, ultimately providing a foundation for designing novel drugs.
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Affiliation(s)
- Giuseppina La Sala
- Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Anders Gunnarsson
- Discovery Science, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Karl Edman
- Discovery Science, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Christian Tyrchan
- Medicinal Chemistry, Research and Early Development, Respiratory & Immunology, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Anders Hogner
- Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Andrey I Frolov
- Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
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68
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McCormick JW, Russo MA, Thompson S, Blevins A, Reynolds KA. Structurally distributed surface sites tune allosteric regulation. eLife 2021; 10:68346. [PMID: 34132193 PMCID: PMC8324303 DOI: 10.7554/elife.68346] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 06/15/2021] [Indexed: 11/30/2022] Open
Abstract
Our ability to rationally optimize allosteric regulation is limited by incomplete knowledge of the mutations that tune allostery. Are these mutations few or abundant, structurally localized or distributed? To examine this, we conducted saturation mutagenesis of a synthetic allosteric switch in which Dihydrofolate reductase (DHFR) is regulated by a blue-light sensitive LOV2 domain. Using a high-throughput assay wherein DHFR catalytic activity is coupled to E. coli growth, we assessed the impact of 1548 viable DHFR single mutations on allostery. Despite most mutations being deleterious to activity, fewer than 5% of mutations had a statistically significant influence on allostery. Most allostery disrupting mutations were proximal to the LOV2 insertion site. In contrast, allostery enhancing mutations were structurally distributed and enriched on the protein surface. Combining several allostery enhancing mutations yielded near-additive improvements to dynamic range. Our results indicate a path toward optimizing allosteric function through variation at surface sites. Many proteins exhibit a property called ‘allostery’. In allostery, an input signal at a specific site of a protein – such as a molecule binding, or the protein absorbing a photon of light – leads to a change in output at another site far away. For example, the protein might catalyze a chemical reaction faster or bind to another molecule more tightly in the presence of the input signal. This protein ‘remote control’ allows cells to sense and respond to changes in their environment. An ability to rapidly engineer new allosteric mechanisms into proteins is much sought after because this would provide an approach for building biosensors and other useful tools. One common approach to engineering new allosteric regulation is to combine a ‘sensor’ or input region from one protein with an ‘output’ region or domain from another. When researchers engineer allostery using this approach of combining input and output domains from different proteins, the difference in the output when the input is ‘on’ versus ‘off’ is often small, a situation called ‘modest allostery’. McCormick et al. wanted to know how to optimize this domain combination approach to increase the difference in output between the ‘on’ and ‘off’ states. More specifically, McCormick et al. wanted to find out whether swapping out or mutating specific amino acids (each of the individual building blocks that make up a protein) enhances or disrupts allostery. They also wanted to know if there are many possible mutations that change the effectiveness of allostery, or if this property is controlled by just a few amino acids. Finally, McCormick et al. questioned where in a protein most of these allostery-tuning mutations were located. To answer these questions, McCormick et al. engineered a new allosteric protein by inserting a light-sensing domain (input) into a protein involved in metabolism (a metabolic enzyme that produces a biomolecule called a tetrahydrofolate) to yield a light-controlled enzyme. Next, they introduced mutations into both the ‘input’ and ‘output’ domains to see where they had a greater effect on allostery. After filtering out mutations that destroyed the function of the output domain, McCormick et al. found that only about 5% of mutations to the ‘output’ domain altered the allosteric response of their engineered enzyme. In fact, most mutations that disrupted allostery were found near the site where the ‘input’ domain was inserted, while mutations that enhanced allostery were sprinkled throughout the enzyme, often on its protein surface. This was surprising in light of the commonly-held assumption that mutations on protein surfaces have little impact on the activity of the ‘output’ domain. Overall, the effect of individual mutations on allostery was small, but McCormick et al. found that these mutations can sometimes be combined to yield larger effects. McCormick et al.’s results suggest a new approach for optimizing engineered allosteric proteins: by introducing mutations on the protein surface. It also opens up new questions: mechanically, how do surface sites affect allostery? In the future, it will be important to characterize how combinations of mutations can optimize allosteric regulation, and to determine what evolutionary trajectories to high performance allosteric ‘switches’ look like.
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Affiliation(s)
- James W McCormick
- The Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, United States.,Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, United States
| | - Marielle Ax Russo
- The Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, United States.,Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, United States
| | - Samuel Thompson
- Department of Bioengineering, Stanford University, Stanford, United States
| | - Aubrie Blevins
- The Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, United States
| | - Kimberly A Reynolds
- The Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, United States.,Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, United States
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69
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Jernigan R, Jia K, Ren Z, Zhou W. Large-scale multiple inference of collective dependence with applications to protein function. Ann Appl Stat 2021; 15:902-924. [DOI: 10.1214/20-aoas1431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Robert Jernigan
- Department of Biochemistry, Biophysics, and Molecular Biology, Program of Bioinformatics and Computational Biology, Iowa State University
| | - Kejue Jia
- Department of Biochemistry, Biophysics, and Molecular Biology, Program of Bioinformatics and Computational Biology, Iowa State University
| | - Zhao Ren
- Department of Statistics, University of Pittsburgh
| | - Wen Zhou
- Department of Statistics, Colorado State University
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70
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Atsavapranee B, Stark CD, Sunden F, Thompson S, Fordyce PM. Fundamentals to function: Quantitative and scalable approaches for measuring protein stability. Cell Syst 2021; 12:547-560. [PMID: 34139165 DOI: 10.1016/j.cels.2021.05.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 04/16/2021] [Accepted: 05/07/2021] [Indexed: 12/11/2022]
Abstract
Folding a linear chain of amino acids into a three-dimensional protein is a complex physical process that ultimately confers an impressive range of diverse functions. Although recent advances have driven significant progress in predicting three-dimensional protein structures from sequence, proteins are not static molecules. Rather, they exist as complex conformational ensembles defined by energy landscapes spanning the space of sequence and conditions. Quantitatively mapping the physical parameters that dictate these landscapes and protein stability is therefore critical to develop models that are capable of predicting how mutations alter function of proteins in disease and informing the design of proteins with desired functions. Here, we review the approaches that are used to quantify protein stability at a variety of scales, from returning multiple thermodynamic and kinetic measurements for a single protein sequence to yielding indirect insights into folding across a vast sequence space. The physical parameters derived from these approaches will provide a foundation for models that extend beyond the structural prediction to capture the complexity of conformational ensembles and, ultimately, their function.
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Affiliation(s)
| | - Catherine D Stark
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA; ChEM-H, Stanford University, Stanford, CA 94305, USA
| | - Fanny Sunden
- Department of Biochemistry, Stanford University, Stanford, CA 94305, USA
| | - Samuel Thompson
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
| | - Polly M Fordyce
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; ChEM-H, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94110, USA.
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71
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Yanagisawa K, Moriwaki Y, Terada T, Shimizu K. EXPRORER: Rational Cosolvent Set Construction Method for Cosolvent Molecular Dynamics Using Large-Scale Computation. J Chem Inf Model 2021; 61:2744-2753. [PMID: 34061535 DOI: 10.1021/acs.jcim.1c00134] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Cosolvent molecular dynamics (CMD) simulations involve an MD simulation of a protein in the presence of explicit water molecules mixed with cosolvent molecules to perform hotspot detection, binding site identification, and binding energy estimation, while other existing methods (e.g., MixMD, SILCS, and MDmix) utilize small molecules that represent functional groups of compounds. However, the cosolvent selections employed in these methods differ and there are only a few cosolvents that are commonly used in these methods. In this study, we proposed a systematic method for constructing a set of cosolvents for drug discovery, termed the EXtended PRObes set construction by REpresentative Retrieval (EXPRORER). First, we extracted typical substructures from FDA-approved drugs, generated 138 cosolvent structures, and for each cosolvent molecule, we conducted CMD simulations to generate a spatial probability distribution map of cosolvent atoms (PMAP). Analyses of PMAP similarity revealed that a cosolvent pair with a PMAP similarity greater than 0.70-0.75 shared similar structural features. We present a method for the construction of a cosolvent subset that satisfies a similarity threshold for all cosolvents, and we tested the constructed sets for four proteins. To our knowledge, this is the first study to include a systematic proposal for cosolvent set construction, and thus, the EXPRORER cosolvents will provide deeper insights into ligand binding sites of various proteins.
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Affiliation(s)
- Keisuke Yanagisawa
- Department of Computer Science, School of Computing, Tokyo Institute of Technology, Tokyo 152-8550, Japan.,Department of Biotechnology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan
| | - Yoshitaka Moriwaki
- Agricultural Bioinformatics Research Unit, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan
| | - Tohru Terada
- Department of Biotechnology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan.,Collaborative Research Institute for Innovative Microbiology, The University of Tokyo, Tokyo 113-8657, Japan.,Agricultural Bioinformatics Research Unit, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan
| | - Kentaro Shimizu
- Department of Biotechnology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan.,Collaborative Research Institute for Innovative Microbiology, The University of Tokyo, Tokyo 113-8657, Japan.,Agricultural Bioinformatics Research Unit, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan
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72
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Miton CM, Buda K, Tokuriki N. Epistasis and intramolecular networks in protein evolution. Curr Opin Struct Biol 2021; 69:160-168. [PMID: 34077895 DOI: 10.1016/j.sbi.2021.04.007] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 04/01/2021] [Accepted: 04/21/2021] [Indexed: 12/01/2022]
Abstract
Proteins are molecular machines composed of complex, highly connected amino acid networks. Their functional optimization requires the reorganization of these intramolecular networks by evolution. In this review, we discuss the mechanisms by which epistasis, that is, the dependence of the effect of a mutation on the genetic background, rewires intramolecular interactions to alter protein function. Deciphering the biophysical basis of epistasis is crucial to our understanding of evolutionary dynamics and the elucidation of sequence-structure-function relationships. We featured recent studies that provide insights into the molecular mechanisms giving rise to epistasis, particularly at the structural level. These studies illustrate the convoluted and fascinating nature of the intramolecular networks co-opted by epistasis during the evolution of protein function.
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Affiliation(s)
- Charlotte M Miton
- Michael Smith Laboratories, University of British Columbia, Vancouver, V6T 1Z4, BC, Canada
| | - Karol Buda
- Michael Smith Laboratories, University of British Columbia, Vancouver, V6T 1Z4, BC, Canada
| | - Nobuhiko Tokuriki
- Michael Smith Laboratories, University of British Columbia, Vancouver, V6T 1Z4, BC, Canada.
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73
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D'Amico RN, Bosken YK, O'Rourke KF, Murray AM, Admasu W, Chang CEA, Boehr DD. Substitution of a Surface-Exposed Residue Involved in an Allosteric Network Enhances Tryptophan Synthase Function in Cells. Front Mol Biosci 2021; 8:679915. [PMID: 34124159 PMCID: PMC8187860 DOI: 10.3389/fmolb.2021.679915] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 05/11/2021] [Indexed: 11/13/2022] Open
Abstract
Networks of noncovalent amino acid interactions propagate allosteric signals throughout proteins. Tryptophan synthase (TS) is an allosterically controlled bienzyme in which the indole product of the alpha subunit (αTS) is transferred through a 25 Å hydrophobic tunnel to the active site of the beta subunit (βTS). Previous nuclear magnetic resonance and molecular dynamics simulations identified allosteric networks in αTS important for its function. We show here that substitution of a distant, surface-exposed network residue in αTS enhances tryptophan production, not by activating αTS function, but through dynamically controlling the opening of the indole channel and stimulating βTS activity. While stimulation is modest, the substitution also enhances cell growth in a tryptophan-auxotrophic strain of Escherichia coli compared to complementation with wild-type αTS, emphasizing the biological importance of the network. Surface-exposed networks provide new opportunities in allosteric drug design and protein engineering, and hint at potential information conduits through which the functions of a metabolon or even larger proteome might be coordinated and regulated.
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Affiliation(s)
- Rebecca N D'Amico
- Department of Chemistry, The Pennsylvania State University, University Park, PA, United States
| | - Yuliana K Bosken
- Department of Chemistry, The University of California Riverside, Riverside, CA, United States
| | - Kathleen F O'Rourke
- Department of Chemistry, The Pennsylvania State University, University Park, PA, United States
| | - Alec M Murray
- Department of Chemistry, The Pennsylvania State University, University Park, PA, United States
| | - Woudasie Admasu
- Department of Chemistry, The Pennsylvania State University, University Park, PA, United States
| | - Chia-En A Chang
- Department of Chemistry, The University of California Riverside, Riverside, CA, United States
| | - David D Boehr
- Department of Chemistry, The Pennsylvania State University, University Park, PA, United States
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74
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Sequeiros-Borja CE, Surpeta B, Brezovsky J. Recent advances in user-friendly computational tools to engineer protein function. Brief Bioinform 2021; 22:bbaa150. [PMID: 32743637 PMCID: PMC8138880 DOI: 10.1093/bib/bbaa150] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 06/03/2020] [Accepted: 06/16/2020] [Indexed: 12/14/2022] Open
Abstract
Progress in technology and algorithms throughout the past decade has transformed the field of protein design and engineering. Computational approaches have become well-engrained in the processes of tailoring proteins for various biotechnological applications. Many tools and methods are developed and upgraded each year to satisfy the increasing demands and challenges of protein engineering. To help protein engineers and bioinformaticians navigate this emerging wave of dedicated software, we have critically evaluated recent additions to the toolbox regarding their application for semi-rational and rational protein engineering. These newly developed tools identify and prioritize hotspots and analyze the effects of mutations for a variety of properties, comprising ligand binding, protein-protein and protein-nucleic acid interactions, and electrostatic potential. We also discuss notable progress to target elusive protein dynamics and associated properties like ligand-transport processes and allosteric communication. Finally, we discuss several challenges these tools face and provide our perspectives on the further development of readily applicable methods to guide protein engineering efforts.
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Affiliation(s)
- 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 and the International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Bartłomiej Surpeta
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University and the International Institute of Molecular and Cell Biology in Warsaw, 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 and the International Institute of Molecular and Cell Biology in Warsaw
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75
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Murugan A, Husain K, Rust MJ, Hepler C, Bass J, Pietsch JMJ, Swain PS, Jena SG, Toettcher JE, Chakraborty AK, Sprenger KG, Mora T, Walczak AM, Rivoire O, Wang S, Wood KB, Skanata A, Kussell E, Ranganathan R, Shih HY, Goldenfeld N. Roadmap on biology in time varying environments. Phys Biol 2021; 18:10.1088/1478-3975/abde8d. [PMID: 33477124 PMCID: PMC8652373 DOI: 10.1088/1478-3975/abde8d] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 01/21/2021] [Indexed: 02/02/2023]
Abstract
Biological organisms experience constantly changing environments, from sudden changes in physiology brought about by feeding, to the regular rising and setting of the Sun, to ecological changes over evolutionary timescales. Living organisms have evolved to thrive in this changing world but the general principles by which organisms shape and are shaped by time varying environments remain elusive. Our understanding is particularly poor in the intermediate regime with no separation of timescales, where the environment changes on the same timescale as the physiological or evolutionary response. Experiments to systematically characterize the response to dynamic environments are challenging since such environments are inherently high dimensional. This roadmap deals with the unique role played by time varying environments in biological phenomena across scales, from physiology to evolution, seeking to emphasize the commonalities and the challenges faced in this emerging area of research.
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Affiliation(s)
- Arvind Murugan
- James Franck Institute, Department of Physics, University of Chicago, Chicago, IL 60637, United States of America
| | - Kabir Husain
- James Franck Institute, Department of Physics, University of Chicago, Chicago, IL 60637, United States of America
| | - Michael J Rust
- Department of Molecular Genetics and Cell Biology, University of Chicago, Chicago, IL 60637, United States of America
- Department of Physics, University of Chicago, Chicago, IL 60637, United States of America
| | - Chelsea Hepler
- Department of Medicine, Feinberg School of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University, Chicago, IL 60611, United States of America
| | - Joseph Bass
- Department of Medicine, Feinberg School of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University, Chicago, IL 60611, United States of America
| | - Julian M J Pietsch
- SynthSys: Centre for Synthetic and Systems Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, United Kingdom
| | - Peter S Swain
- SynthSys: Centre for Synthetic and Systems Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, United Kingdom
| | - Siddhartha G Jena
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, United States of America
| | - Jared E Toettcher
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, United States of America
| | - Arup K Chakraborty
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, United States of America
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, United States of America
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, United States of America
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139, United States of America
- Ragon Institute of the Massachusetts General Hospital, Massachusetts Institute of Technology, and Harvard, Cambridge, MA 02139, United States of America
| | - Kayla G Sprenger
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139, United States of America
- Ragon Institute of the Massachusetts General Hospital, Massachusetts Institute of Technology, and Harvard, Cambridge, MA 02139, United States of America
| | - T Mora
- Laboratoire de physique, Ecole normale supérieure, CNRS, PSL Research University, Paris, France
| | - A M Walczak
- Laboratoire de physique, Ecole normale supérieure, CNRS, PSL Research University, Paris, France
| | - O Rivoire
- Center for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, PSL Research University, Paris, France
| | - Shenshen Wang
- Department of Physics and Astronomy, University of California, Los Angeles, Los Angeles, CA 90095, United States of America
| | - Kevin B Wood
- Departments of Biophysics and Physics, University of Michigan, Ann Arbor, MI 48109-1055, United States of America
| | - Antun Skanata
- Center for Genomics and Systems Biology, New York University, 12 Waverly Place, Rm. 206, New York, NY 10003, United States of America
| | - Edo Kussell
- Center for Genomics and Systems Biology, New York University, 12 Waverly Place, Rm. 206, New York, NY 10003, United States of America
| | - Rama Ranganathan
- Center for Physics of Evolving Systems, Biochemistry & Molecular Biology, and the Pritzker School for Molecular Engineering, University of Chicago, Chicago IL 60637, United States of America
| | - Hong-Yan Shih
- Department of Physics, University of Illinois at Urbana-Champaign, Champaign, Illinois 61801, United States of America
- Institute of Physics, Academia Sinica, Taipei 11529, Taiwan
| | - Nigel Goldenfeld
- Department of Physics, University of Illinois at Urbana-Champaign, Champaign, Illinois 61801, United States of America
- Carl R Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Champaign, Illinois 61801, United States of America
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76
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Pearce S, Tucker CL. Dual Systems for Enhancing Control of Protein Activity through Induced Dimerization Approaches. Adv Biol (Weinh) 2021; 5:e2000234. [PMID: 34028215 PMCID: PMC8144547 DOI: 10.1002/adbi.202000234] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 11/29/2020] [Indexed: 12/25/2022]
Abstract
To reveal the underpinnings of complex biological systems, a variety of approaches have been developed that allow switchable control of protein function. One powerful approach for switchable control is the use of inducible dimerization systems, which can be configured to control activity of a target protein upon induced dimerization triggered by chemicals or light. Individually, many inducible dimerization systems suffer from pre-defined dynamic ranges and overwhelming sensitivity to expression level and cellular context. Such systems often require extensive engineering efforts to overcome issues of background leakiness and restricted dynamic range. To address these limitations, recent tool development efforts have explored overlaying dimerizer systems with a second layer of regulation. Albeit more complex, the resulting layered systems have enhanced functionality, such as tighter control that can improve portability of these tools across platforms.
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Affiliation(s)
- Sarah Pearce
- Department of Pharmacology, University of Colorado School of Medicine, Aurora, 80045, Colorado, USA
| | - Chandra L. Tucker
- Department of Pharmacology, University of Colorado School of Medicine, Aurora, 80045, Colorado, USA
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77
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Structural basis of the human Scribble-Vangl2 association in health and disease. Biochem J 2021; 478:1321-1332. [PMID: 33684218 PMCID: PMC8038854 DOI: 10.1042/bcj20200816] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 02/24/2021] [Accepted: 03/08/2021] [Indexed: 01/01/2023]
Abstract
Scribble is a critical cell polarity regulator that has been shown to work as either an oncogene or tumor suppressor in a context dependent manner, and also impacts cell migration, tissue architecture and immunity. Mutations in Scribble lead to neural tube defects in mice and humans, which has been attributed to a loss of interaction with the planar cell polarity regulator Vangl2. We show that the Scribble PDZ domains 1, 2 and 3 are able to interact with the C-terminal PDZ binding motif of Vangl2 and have now determined crystal structures of these Scribble PDZ domains bound to the Vangl2 peptide. Mapping of mammalian neural tube defect mutations reveal that mutations located distal to the canonical PDZ domain ligand binding groove can not only ablate binding to Vangl2 but also disrupt binding to multiple other signaling regulators. Our findings suggest that PDZ-associated neural tube defect mutations in Scribble may not simply act in a Vangl2 dependent manner but as broad-spectrum loss of function mutants by disrupting the global Scribble-mediated interaction network.
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78
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Hoffmann MD, Mathony J, Upmeier Zu Belzen J, Harteveld Z, Aschenbrenner S, Stengl C, Grimm D, Correia BE, Eils R, Niopek D. Optogenetic control of Neisseria meningitidis Cas9 genome editing using an engineered, light-switchable anti-CRISPR protein. Nucleic Acids Res 2021; 49:e29. [PMID: 33330940 PMCID: PMC7969004 DOI: 10.1093/nar/gkaa1198] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 10/30/2020] [Accepted: 11/30/2020] [Indexed: 12/26/2022] Open
Abstract
Optogenetic control of CRISPR–Cas9 systems has significantly improved our ability to perform genome perturbations in living cells with high precision in time and space. As new Cas orthologues with advantageous properties are rapidly being discovered and engineered, the need for straightforward strategies to control their activity via exogenous stimuli persists. The Cas9 from Neisseria meningitidis (Nme) is a particularly small and target-specific Cas9 orthologue, and thus of high interest for in vivo genome editing applications. Here, we report the first optogenetic tool to control NmeCas9 activity in mammalian cells via an engineered, light-dependent anti-CRISPR (Acr) protein. Building on our previous Acr engineering work, we created hybrids between the NmeCas9 inhibitor AcrIIC3 and the LOV2 blue light sensory domain from Avena sativa. Two AcrIIC3-LOV2 hybrids from our collection potently blocked NmeCas9 activity in the dark, while permitting robust genome editing at various endogenous loci upon blue light irradiation. Structural analysis revealed that, within these hybrids, the LOV2 domain is located in striking proximity to the Cas9 binding surface. Together, our work demonstrates optogenetic regulation of a type II-C CRISPR effector and might suggest a new route for the design of optogenetic Acrs.
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Affiliation(s)
- Mareike D Hoffmann
- Dept. of Infectious Diseases/Virology, Medical Faculty, University of Heidelberg, 69120 Heidelberg, Germany
| | - Jan Mathony
- Centre for Synthetic Biology, Technical University of Darmstadt, 64287 Darmstadt, Germany.,Department of Biology, Technical University of Darmstadt,64287 Darmstadt, Germany.,PhD Student, BZH graduate school, Heidelberg University, 69120 Heidelberg, Germany
| | | | - Zander Harteveld
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne CH-1015, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne CH-1015, Switzerland
| | - Sabine Aschenbrenner
- Centre for Synthetic Biology, Technical University of Darmstadt, 64287 Darmstadt, Germany.,Department of Biology, Technical University of Darmstadt,64287 Darmstadt, Germany
| | | | - Dirk Grimm
- Dept. of Infectious Diseases/Virology, Medical Faculty, University of Heidelberg, 69120 Heidelberg, Germany.,BioQuant, Cluster of Excellence CellNetworks, University of Heidelberg, 69120 Heidelberg, Germany.,German Center for Infection Research (DZIF) and German Center for Cardiovascular Research (DZHK), partner site Heidelberg, 69120 Heidelberg, Germany
| | - Bruno E Correia
- Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne CH-1015, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne CH-1015, Switzerland
| | - Roland Eils
- Digital Health Center, Berlin Institute of Health (BIH) and Charité, Berlin 10178, Germany.,Health Data Science Unit, BioQuant and Medical Faculty of Heidelberg University, Heidelberg 69120, Germany
| | - Dominik Niopek
- Centre for Synthetic Biology, Technical University of Darmstadt, 64287 Darmstadt, Germany.,Department of Biology, Technical University of Darmstadt,64287 Darmstadt, Germany
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79
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Nedrud D, Coyote-Maestas W, Schmidt D. A large-scale survey of pairwise epistasis reveals a mechanism for evolutionary expansion and specialization of PDZ domains. Proteins 2021; 89:899-914. [PMID: 33620761 DOI: 10.1002/prot.26067] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 02/02/2021] [Accepted: 02/18/2021] [Indexed: 12/21/2022]
Abstract
Deep mutational scanning (DMS) facilitates data-driven models of protein structure and function. Here, we adapted Saturated Programmable Insertion Engineering (SPINE) as a programmable DMS technique. We validate SPINE with a reference single mutant dataset in the PSD95 PDZ3 domain and then characterize most pairwise double mutants to study epistasis. We observe wide-spread proximal negative epistasis, which we attribute to mutations affecting thermodynamic stability, and strong long-range positive epistasis, which is enriched in an evolutionarily conserved and function-defining network of "sector" and clade-specifying residues. Conditional neutrality of mutations in clade-specifying residues compensates for deleterious mutations in sector positions. This suggests that epistatic interactions between these position pairs facilitated the evolutionary expansion and specialization of PDZ domains. We propose that SPINE provides easy experimental access to reveal epistasis signatures in proteins that will improve our understanding of the structural basis for protein function and adaptation.
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Affiliation(s)
- David Nedrud
- Department of Biochemistry, Molecular Biology & Biophysics, University of Minnesota, Minneapolis, Minnesota, USA
| | - Willow Coyote-Maestas
- Department of Biochemistry, Molecular Biology & Biophysics, University of Minnesota, Minneapolis, Minnesota, USA
| | - Daniel Schmidt
- Department of Genetics, Cell Biology & Development, University of Minnesota, Minneapolis, Minnesota, USA
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80
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Yan W, Yu C, Chen J, Zhou J, Shen B. ANCA: A Web Server for Amino Acid Networks Construction and Analysis. Front Mol Biosci 2020; 7:582702. [PMID: 33330622 PMCID: PMC7711068 DOI: 10.3389/fmolb.2020.582702] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 10/19/2020] [Indexed: 02/05/2023] Open
Abstract
Amino acid network (AAN) models empower us to gain insights into protein structures and functions by describing a protein 3D structure as a graph, where nodes represent residues and edges as amino acid interactions. Here, we present the ANCA, an interactive Web server for Amino Acids Network Construction and Analysis based on a single structure or a set of structures from the Protein Data Bank. The main purpose of ANCA is to provide a portal for three types of an environment-dependent residue contact energy (ERCE)-based network model, including amino acid contact energy network (AACEN), node-weighted amino acid contact energy network (NACEN), and edge-weighted amino acid contact energy network (EACEN). For comparison, the C-alpha distance-based network model is also included, which can be extended to protein–DNA/RNA complexes. Then, the analyses of different types of AANs were performed and compared from node, edge, and network levels. The network and corresponding structure can be visualized directly in the browser. The ANCA enables researchers to investigate diverse concerns in the framework of AAN, such as the interpretation of allosteric regulation and functional residues. The ANCA portal, together with an extensive help, is available at http://sysbio.suda.edu.cn/anca/.
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Affiliation(s)
- Wenying Yan
- Center for Systems Biology, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Chunjiang Yu
- School of Biotechnology, Suzhou Industrial Park Institute of Services Outsourcing, Suzhou, China
| | - Jiajia Chen
- School of Chemistry, Biology and Materials Engineering, Suzhou University of Science and Technology, Suzhou, China
| | - Jianhong Zhou
- Public Library of Science, San Francisco, CA, United States
| | - Bairong Shen
- Institutes for Systems Genetics, West China Hospital, Sichuan University, Chengdu, China
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81
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Guclu TF, Kocatug N, Atilgan AR, Atilgan C. N-Terminus of the Third PDZ Domain of PSD-95 Orchestrates Allosteric Communication for Selective Ligand Binding. J Chem Inf Model 2020; 61:347-357. [PMID: 33331776 DOI: 10.1021/acs.jcim.0c01079] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
PDZ domains constitute common models to study single-domain allostery without significant structural changes. The third PDZ domain of PSD-95 (PDZ3) is known to have selective structural features that confer unique modulatory roles to this unit. In this model system, two residues, H372 directly connected to the binding site and G330 holding an off-binding-site position, were designated to assess the effect of mutations on binding selectivity. It has been observed that the H372A and G330T-H372A mutations change ligand preferences from class I (T/S amino acid at position -2 of the ligand) to class II (hydrophobic amino acid at the same position). Alternatively, the G330T single mutation leads to the recognition of both ligand classes. We have performed a series of molecular dynamics (MD) simulations for wild-type, H372A, and G330T single mutants and a double mutant of PDZ3 in the absence and presence of both types of ligands. With the combination of free-energy difference calculations and a detailed analysis of MD trajectories, "class switching" and "class bridging" behavior of PDZ3 mutants, as well as their effects on ligand selection and binding affinities are explained. We show that the dynamics of the charged N-terminus plays a fundamental role in determining the binding preferences in PDZ3 by altering the electrostatic energy. These findings are corroborated by simulations on N-terminus-truncated versions of these systems. The dynamical allostery orchestrated by the N-terminus offers a fresh perspective to the study of communication pathways in proteins.
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Affiliation(s)
- Tandac F Guclu
- Faculty of Engineering and Natural Sciences, Sabanci University, 34956 Istanbul, Turkey
| | - Nazli Kocatug
- Faculty of Engineering and Natural Sciences, Sabanci University, 34956 Istanbul, Turkey
| | - Ali Rana Atilgan
- Faculty of Engineering and Natural Sciences, Sabanci University, 34956 Istanbul, Turkey
| | - Canan Atilgan
- Faculty of Engineering and Natural Sciences, Sabanci University, 34956 Istanbul, Turkey
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82
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Fenwick RB, Oyen D, van den Bedem H, Dyson HJ, Wright PE. Modeling of Hidden Structures Using Sparse Chemical Shift Data from NMR Relaxation Dispersion. Biophys J 2020; 120:296-305. [PMID: 33301748 DOI: 10.1016/j.bpj.2020.11.2267] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 10/30/2020] [Accepted: 11/11/2020] [Indexed: 12/24/2022] Open
Abstract
NMR relaxation dispersion measurements report on conformational changes occurring on the μs-ms timescale. Chemical shift information derived from relaxation dispersion can be used to generate structural models of weakly populated alternative conformational states. Current methods to obtain such models rely on determining the signs of chemical shift changes between the conformational states, which are difficult to obtain in many situations. Here, we use a "sample and select" method to generate relevant structural models of alternative conformations of the C-terminal-associated region of Escherichia coli dihydrofolate reductase (DHFR), using only unsigned chemical shift changes for backbone amides and carbonyls (1H, 15N, and 13C'). We find that CS-Rosetta sampling with unsigned chemical shift changes generates a diversity of structures that are sufficient to characterize a minor conformational state of the C-terminal region of DHFR. The excited state differs from the ground state by a change in secondary structure, consistent with previous predictions from chemical shift hypersurfaces and validated by the x-ray structure of a partially humanized mutant of E. coli DHFR (N23PP/G51PEKN). The results demonstrate that the combination of fragment modeling with sparse chemical shift data can determine the structure of an alternative conformation of DHFR sampled on the μs-ms timescale. Such methods will be useful for characterizing alternative states, which can potentially be used for in silico drug screening, as well as contributing to understanding the role of minor states in biology and molecular evolution.
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Affiliation(s)
- R Bryn Fenwick
- Department of Integrative Structural and Computational Biology and Skaggs Institute of Chemical Biology, The Scripps Research Institute, La Jolla, California.
| | - David Oyen
- Department of Integrative Structural and Computational Biology and Skaggs Institute of Chemical Biology, The Scripps Research Institute, La Jolla, California
| | - Henry van den Bedem
- SLAC National Accelerator Laboratory, Stanford University, Menlo Park, California, and Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California
| | - H Jane Dyson
- Department of Integrative Structural and Computational Biology and Skaggs Institute of Chemical Biology, The Scripps Research Institute, La Jolla, California
| | - Peter E Wright
- Department of Integrative Structural and Computational Biology and Skaggs Institute of Chemical Biology, The Scripps Research Institute, La Jolla, California.
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83
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Dudola D, Hinsenkamp A, Gáspári Z. Ensemble-Based Analysis of the Dynamic Allostery in the PSD-95 PDZ3 Domain in Relation to the General Variability of PDZ Structures. Int J Mol Sci 2020; 21:ijms21218348. [PMID: 33172212 PMCID: PMC7672539 DOI: 10.3390/ijms21218348] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 10/28/2020] [Accepted: 10/30/2020] [Indexed: 11/16/2022] Open
Abstract
PDZ domains are abundant interaction hubs found in a number of different proteins and they exhibit characteristic differences in their structure and ligand specificity. Their internal dynamics have been proposed to contribute to their biological activity via changes in conformational entropy upon ligand binding and allosteric modulation. Here we investigate dynamic structural ensembles of PDZ3 of the postsynaptic protein PSD-95, calculated based on previously published backbone and side-chain S2 order parameters. We show that there are distinct but interdependent structural rearrangements in PDZ3 upon ligand binding and the presence of the intramolecular allosteric modulator helix α3. We have also compared these rearrangements in PDZ1-2 of PSD-95 and the conformational diversity of an extended set of PDZ domains available in the PDB database. We conclude that although the opening-closing rearrangement, occurring upon ligand binding, is likely a general feature for all PDZ domains, the conformer redistribution upon ligand binding along this mode is domain-dependent. Our findings suggest that the structural and functional diversity of PDZ domains is accompanied by a diversity of internal motional modes and their interdependence.
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Affiliation(s)
- Dániel Dudola
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter u. 50/A, 1083 Budapest, Hungary; (D.D.); (A.H.)
| | - Anett Hinsenkamp
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter u. 50/A, 1083 Budapest, Hungary; (D.D.); (A.H.)
- 3in-PPCU Research Group, 2500 Esztergom, Hungary
| | - Zoltán Gáspári
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter u. 50/A, 1083 Budapest, Hungary; (D.D.); (A.H.)
- Correspondence:
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84
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Tseng CY, Wang Y, Zocchi G. Enzyme-DNA chimeras: Construction, allostery, applications. Methods Enzymol 2020; 647:257-281. [PMID: 33482992 DOI: 10.1016/bs.mie.2020.09.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
We describe the operational principle, synthesis, and applications of the enzyme-DNA chimeras. These are supramolecular constructions where a DNA spring is coupled to an enzyme and introduces artificial allosteric control of the enzyme. This method is universal and can be applied to various enzymes and proteins. In addition, this method is versatile as the stresses applied by the DNA spring on the enzymes can be fine-tuned semi-continuously and thus their enzymatic activities can be modulated gradually. We give detailed protocols for the synthesis of these molecules. Summarizing our experience with different enzymes, we explain their use for fundamental studies of conformational plasticity, as well as the potential as molecular probes.
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Affiliation(s)
| | - Yong Wang
- Department of Physics, Cell and Molecular Biology Program, Materials Science and Engineering Program, University of Arkansas, Fayetteville, AR, United States
| | - Giovanni Zocchi
- Department of Physics and Astronomy, University of California Los Angeles, Los Angeles, CA, United States
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85
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Mathony J, Niopek D. Enlightening Allostery: Designing Switchable Proteins by Photoreceptor Fusion. Adv Biol (Weinh) 2020; 5:e2000181. [PMID: 33107225 DOI: 10.1002/adbi.202000181] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 10/01/2020] [Indexed: 11/05/2022]
Abstract
Optogenetics harnesses natural photoreceptors to non-invasively control selected processes in cells with previously unmet spatiotemporal precision. Linking the activity of a protein of choice to the conformational state of a photosensor domain through allosteric coupling represents a powerful method for engineering light-responsive proteins. It enables the design of compact and highly potent single-component optogenetic systems with fast on- and off-switching kinetics. However, designing protein-photoreceptor chimeras, in which structural changes of the photoreceptor are effectively propagated to the fused effector protein, is a challenging engineering problem and often relies on trial and error. Here, recent advances in the design and application of optogenetic allosteric switches are reviewed. First, an overview of existing optogenetic tools based on inducible allostery is provided and their utility for cell biology applications is highlighted. Focusing on light-oxygen-voltage domains, a widely applied class of small blue light sensors, the available strategies for engineering light-dependent allostery are presented and their individual advantages and limitations are highlighted. Finally, high-throughput screening technologies based on comprehensive insertion libraries, which could accelerate the creation of stimulus-responsive receptor-protein chimeras for use in optogenetics and beyond, are discussed.
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Affiliation(s)
- Jan Mathony
- Department of Biology and Centre for Synthetic Biology, Technische Universität Darmstadt, Schnittspahnstrasse 12, Darmstadt, 64287, Germany.,BZH graduate school, Heidelberg University, Im Neuheimer Feld 328, Heidelberg, 69120, Germany
| | - Dominik Niopek
- Department of Biology and Centre for Synthetic Biology, Technische Universität Darmstadt, Schnittspahnstrasse 12, Darmstadt, 64287, Germany
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86
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Agarwal PK, Bernard DN, Bafna K, Doucet N. Enzyme dynamics: Looking beyond a single structure. ChemCatChem 2020; 12:4704-4720. [PMID: 33897908 PMCID: PMC8064270 DOI: 10.1002/cctc.202000665] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Indexed: 12/23/2022]
Abstract
Conventional understanding of how enzymes function strongly emphasizes the role of structure. However, increasing evidence clearly indicates that enzymes do not remain fixed or operate exclusively in or close to their native structure. Different parts of the enzyme (from individual residues to full domains) undergo concerted motions on a wide range of time-scales, including that of the catalyzed reaction. Information obtained on these internal motions and conformational fluctuations has so far uncovered and explained many aspects of enzyme mechanisms, which could not have been understood from a single structure alone. Although there is wide interest in understanding enzyme dynamics and its role in catalysis, several challenges remain. In addition to technical difficulties, the vast majority of investigations are performed in dilute aqueous solutions, where conditions are significantly different than the cellular milieu where a large number of enzymes operate. In this review, we discuss recent developments, several challenges as well as opportunities related to this topic. The benefits of considering dynamics as an integral part of the enzyme function can also enable new means of biocatalysis, engineering enzymes for industrial and medicinal applications.
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Affiliation(s)
- Pratul K. Agarwal
- Department of Physiological Sciences and High-Performance Computing Center, Oklahoma State University, Stillwater, Oklahoma 74078
- Arium BioLabs, 2519 Caspian Drive, Knoxville, Tennessee 37932
| | - David N. Bernard
- Centre Armand-Frappier Santé Biotechnologie, Institut national de la recherche scientifique (INRS), Université du Québec, 531 Boulevard des Prairies, Laval, Quebec, H7V 1B7, Canada
| | - Khushboo Bafna
- Department of Chemistry and Chemical Biology, and Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, New York 12180
| | - Nicolas Doucet
- Centre Armand-Frappier Santé Biotechnologie, Institut national de la recherche scientifique (INRS), Université du Québec, 531 Boulevard des Prairies, Laval, Quebec, H7V 1B7, Canada
- PROTEO, the Quebec Network for Research on Protein Function, Structure, and Engineering, 1045 Avenue de la Médecine, Université Laval, Québec, QC, G1V 0A6, Canada
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87
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Real-time observation of ligand-induced allosteric transitions in a PDZ domain. Proc Natl Acad Sci U S A 2020; 117:26031-26039. [PMID: 33020277 DOI: 10.1073/pnas.2012999117] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
While allostery is of paramount importance for protein regulation, the underlying dynamical process of ligand (un)binding at one site, resulting time evolution of the protein structure, and change of the binding affinity at a remote site are not well understood. Here the ligand-induced conformational transition in a widely studied model system of allostery, the PDZ2 domain, is investigated by transient infrared spectroscopy accompanied by molecular dynamics simulations. To this end, an azobenzene-derived photoswitch is linked to a peptide ligand in a way that its binding affinity to the PDZ2 domain changes upon switching, thus initiating an allosteric transition in the PDZ2 domain protein. The subsequent response of the protein, covering four decades of time, ranging from ∼1 ns to ∼μs, can be rationalized by a remodeling of its rugged free-energy landscape, with very subtle shifts in the populations of a small number of structurally well-defined states. It is proposed that structurally and dynamically driven allostery, often discussed as limiting scenarios of allosteric communication, actually go hand-in-hand, allowing the protein to adapt its free-energy landscape to incoming signals.
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88
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Shaaya M, Fauser J, Zhurikhina A, Conage-Pough JE, Huyot V, Brennan M, Flower CT, Matsche J, Khan S, Natarajan V, Rehman J, Kota P, White FM, Tsygankov D, Karginov AV. Light-regulated allosteric switch enables temporal and subcellular control of enzyme activity. eLife 2020; 9:e60647. [PMID: 32965214 PMCID: PMC7577742 DOI: 10.7554/elife.60647] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 09/22/2020] [Indexed: 12/24/2022] Open
Abstract
Engineered allosteric regulation of protein activity provides significant advantages for the development of robust and broadly applicable tools. However, the application of allosteric switches in optogenetics has been scarce and suffers from critical limitations. Here, we report an optogenetic approach that utilizes an engineered Light-Regulated (LightR) allosteric switch module to achieve tight spatiotemporal control of enzymatic activity. Using the tyrosine kinase Src as a model, we demonstrate efficient regulation of the kinase and identify temporally distinct signaling responses ranging from seconds to minutes. LightR-Src off-kinetics can be tuned by modulating the LightR photoconversion cycle. A fast cycling variant enables the stimulation of transient pulses and local regulation of activity in a selected region of a cell. The design of the LightR module ensures broad applicability of the tool, as we demonstrate by achieving light-mediated regulation of Abl and bRaf kinases as well as Cre recombinase.
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Affiliation(s)
- Mark Shaaya
- Department of Pharmacology and Regenerative Medicine, The University of Illinois at Chicago, College of MedicineChicagoUnited States
| | - Jordan Fauser
- Department of Pharmacology and Regenerative Medicine, The University of Illinois at Chicago, College of MedicineChicagoUnited States
| | - Anastasia Zhurikhina
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of MedicineAtlantaUnited States
| | - Jason E Conage-Pough
- The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of TechnologyCambridgeUnited States
- Center for Precision Cancer Medicine, Massachusetts Institute of TechnologyCambridgeUnited States
- Department of Biological Engineering, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Vincent Huyot
- Department of Pharmacology and Regenerative Medicine, The University of Illinois at Chicago, College of MedicineChicagoUnited States
| | - Martin Brennan
- Department of Pharmacology and Regenerative Medicine, The University of Illinois at Chicago, College of MedicineChicagoUnited States
| | - Cameron T Flower
- The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of TechnologyCambridgeUnited States
- Center for Precision Cancer Medicine, Massachusetts Institute of TechnologyCambridgeUnited States
- Department of Biological Engineering, Massachusetts Institute of TechnologyCambridgeUnited States
- Program in Computational and Systems Biology, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Jacob Matsche
- Department of Pharmacology and Regenerative Medicine, The University of Illinois at Chicago, College of MedicineChicagoUnited States
| | - Shahzeb Khan
- Department of Pharmacology and Regenerative Medicine, The University of Illinois at Chicago, College of MedicineChicagoUnited States
| | - Viswanathan Natarajan
- Department of Pharmacology and Regenerative Medicine, The University of Illinois at Chicago, College of MedicineChicagoUnited States
| | - Jalees Rehman
- Department of Pharmacology and Regenerative Medicine, The University of Illinois at Chicago, College of MedicineChicagoUnited States
- University of Illinois Cancer Center, The University of Illinois at ChicagoChicagoUnited States
- Division of Cardiology, Department of Medicine, The University of Illinois, College of MedicineChicagoUnited States
| | - Pradeep Kota
- Marsico Lung Institute, Cystic Fibrosis Center and Department of Medicine, University of North CarolinaChapel HillUnited States
| | - Forest M White
- The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of TechnologyCambridgeUnited States
- Center for Precision Cancer Medicine, Massachusetts Institute of TechnologyCambridgeUnited States
- Department of Biological Engineering, Massachusetts Institute of TechnologyCambridgeUnited States
- Program in Computational and Systems Biology, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Denis Tsygankov
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of MedicineAtlantaUnited States
| | - Andrei V Karginov
- Department of Pharmacology and Regenerative Medicine, The University of Illinois at Chicago, College of MedicineChicagoUnited States
- University of Illinois Cancer Center, The University of Illinois at ChicagoChicagoUnited States
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89
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Abstract
The ribosome translates the genetic code into proteins in all domains of life. Its size and complexity demand long-range interactions that regulate ribosome function. These interactions are largely unknown. Here, we apply a global coevolution method, statistical coupling analysis (SCA), to identify coevolving residue networks (sectors) within the 23S ribosomal RNA (rRNA) of the large ribosomal subunit. As in proteins, SCA reveals a hierarchical organization of evolutionary constraints with near-independent groups of nucleotides forming physically contiguous networks within the three-dimensional structure. Using a quantitative, continuous-culture-with-deep-sequencing assay, we confirm that the top two SCA-predicted sectors contribute to ribosome function. These sectors map to distinct ribosome activities, and their origins trace to phylogenetic divergences across all domains of life. These findings provide a foundation to map ribosome allostery, explore ribosome biogenesis, and engineer ribosomes for new functions. Despite differences in chemical structure, protein and RNA enzymes appear to share a common internal logic of interaction and assembly.
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90
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Mihaljević L, Urban S. Decoding the Functional Evolution of an Intramembrane Protease Superfamily by Statistical Coupling Analysis. Structure 2020; 28:1329-1336.e4. [PMID: 32795403 DOI: 10.1016/j.str.2020.07.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 06/12/2020] [Accepted: 07/24/2020] [Indexed: 11/18/2022]
Abstract
How evolution endowed membrane enzymes with specific abilities, and then tuned them to the needs of different cells, is poorly understood. We examined whether statistical coupling analysis (SCA) can be applied to rhomboid proteases, the most widely distributed membrane proteins, to identify amino acid "sectors" that evolved independently to acquire a specific function. SCA revealed three coevolving residue networks that form two sectors. Sector 1 determines substrate specificity, but is paradoxically scattered across the protein, consistent with dynamics driving rhomboid-substrate interactions. Sector 2 is hierarchically composed of a subgroup that maintains the catalytic site, and another that maintains the overall fold, forecasting evolution of rhomboid pseudoproteases. Changing only sector 1 residues of a "recipient" rhomboid converted its substrate specificity and catalytic efficiency to that of the "donor." While used only twice over a decade ago, SCA should be generally applicable to membrane proteins, and our sector grafting approach provides an efficient strategy for designing enzymes.
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Affiliation(s)
- Ljubica Mihaljević
- Department of Molecular Biology & Genetics, Johns Hopkins University School of Medicine, Room 507 PCTB, 725 North Wolfe Street, Baltimore, MD 21205, USA
| | - Siniša Urban
- Department of Molecular Biology & Genetics, Johns Hopkins University School of Medicine, Room 507 PCTB, 725 North Wolfe Street, Baltimore, MD 21205, USA.
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91
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Schober AF, Mathis AD, Ingle C, Park JO, Chen L, Rabinowitz JD, Junier I, Rivoire O, Reynolds KA. A Two-Enzyme Adaptive Unit within Bacterial Folate Metabolism. Cell Rep 2020; 27:3359-3370.e7. [PMID: 31189117 DOI: 10.1016/j.celrep.2019.05.030] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Revised: 04/05/2019] [Accepted: 05/09/2019] [Indexed: 11/29/2022] Open
Abstract
Enzyme function and evolution are influenced by the larger context of a metabolic pathway. Deleterious mutations or perturbations in one enzyme can often be compensated by mutations to others. We used comparative genomics and experiments to examine evolutionary interactions with the essential metabolic enzyme dihydrofolate reductase (DHFR). Analyses of synteny and co-occurrence across bacterial species indicate that DHFR is coupled to thymidylate synthase (TYMS) but relatively independent from the rest of folate metabolism. Using quantitative growth rate measurements and forward evolution in Escherichia coli, we demonstrate that the two enzymes adapt as a relatively independent unit in response to antibiotic stress. Metabolomic profiling revealed that TYMS activity must not exceed DHFR activity to prevent the depletion of reduced folates and the accumulation of the intermediate dihydrofolate. Comparative genomics analyses identified >200 gene pairs with similar statistical signatures of modular co-evolution, suggesting that cellular pathways may be decomposable into small adaptive units.
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Affiliation(s)
- Andrew F Schober
- The Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Andrew D Mathis
- The Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Christine Ingle
- The Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Junyoung O Park
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ 08544, USA
| | - Li Chen
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
| | - Joshua D Rabinowitz
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
| | - Ivan Junier
- Centre National de la Recherche Scientifique, Université Grenoble Alpes, TIMC-IMAG, F-38000 Grenoble, France
| | - Olivier Rivoire
- Center for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, PSL Research University, F-75005 Paris, France
| | - Kimberly A Reynolds
- The Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
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92
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Wang J, Jain A, McDonald LR, Gambogi C, Lee AL, Dokholyan NV. Mapping allosteric communications within individual proteins. Nat Commun 2020; 11:3862. [PMID: 32737291 PMCID: PMC7395124 DOI: 10.1038/s41467-020-17618-2] [Citation(s) in RCA: 88] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2019] [Accepted: 06/30/2020] [Indexed: 02/05/2023] Open
Abstract
Allostery in proteins influences various biological processes such as regulation of gene transcription and activities of enzymes and cell signaling. Computational approaches for analysis of allosteric coupling provide inexpensive opportunities to predict mutations and to design small-molecule agents to control protein function and cellular activity. We develop a computationally efficient network-based method, Ohm, to identify and characterize allosteric communication networks within proteins. Unlike previously developed simulation-based approaches, Ohm relies solely on the structure of the protein of interest. We use Ohm to map allosteric networks in a dataset composed of 20 proteins experimentally identified to be allosterically regulated. Further, the Ohm allostery prediction for the protein CheY correlates well with NMR CHESCA studies. Our webserver, Ohm.dokhlab.org, automatically determines allosteric network architecture and identifies critical coupled residues within this network.
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Affiliation(s)
- Jian Wang
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, 17033-0850, USA
| | - Abha Jain
- Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-7363, USA
| | - Leanna R McDonald
- Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-7363, USA
| | - Craig Gambogi
- Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-7363, USA
| | - Andrew L Lee
- Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-7363, USA
| | - Nikolay V Dokholyan
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, 17033-0850, USA.
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Departments of Biochemistry & Molecular Biology, Penn State College of Medicine, Hershey, PA, 17033-0850, USA.
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93
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The Conformational Plasticity Vista of PDZ Domains. Life (Basel) 2020; 10:life10080123. [PMID: 32726937 PMCID: PMC7460260 DOI: 10.3390/life10080123] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 07/19/2020] [Accepted: 07/25/2020] [Indexed: 02/01/2023] Open
Abstract
The PDZ domain (PSD95-Discs large-ZO1) is a widespread modular domain present in the living organisms. A prevalent function in the PDZ family is to serve as scaffolding and adaptor proteins connecting multiple partners in signaling pathways. An explanation of the flexible functionality in this domain family, based just on a static perspective of the structure-activity relationship, might fall short. More dynamic and conformational aspects in the protein fold can be the reasons for such functionality. Folding studies indeed showed an ample and malleable folding landscape for PDZ domains where multiple intermediate states were experimentally detected. Allosteric phenomena that resemble energetic coupling between residues have also been found in PDZ domains. Additionally, several PDZ domains are modulated by post-translational modifications, which introduce conformational switches that affect binding. Altogether, the ability to connect diverse partners might arise from the intrinsic plasticity of the PDZ fold.
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94
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Thompson S, Zhang Y, Ingle C, Reynolds KA, Kortemme T. Altered expression of a quality control protease in E. coli reshapes the in vivo mutational landscape of a model enzyme. eLife 2020; 9:53476. [PMID: 32701056 PMCID: PMC7377907 DOI: 10.7554/elife.53476] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2019] [Accepted: 07/09/2020] [Indexed: 12/03/2022] Open
Abstract
Protein mutational landscapes are shaped by the cellular environment, but key factors and their quantitative effects are often unknown. Here we show that Lon, a quality control protease naturally absent in common E. coli expression strains, drastically reshapes the mutational landscape of the metabolic enzyme dihydrofolate reductase (DHFR). Selection under conditions that resolve highly active mutants reveals that 23.3% of all single point mutations in DHFR are advantageous in the absence of Lon, but advantageous mutations are largely suppressed when Lon is reintroduced. Protein stability measurements demonstrate extensive activity-stability tradeoffs for the advantageous mutants and provide a mechanistic explanation for Lon’s widespread impact. Our findings suggest possibilities for tuning mutational landscapes by modulating the cellular environment, with implications for protein design and combatting antibiotic resistance.
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Affiliation(s)
- Samuel Thompson
- Graduate Group in Biophysics, University of California San Francisco, San Francisco, United States
| | - Yang Zhang
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, United States
| | - Christine Ingle
- The Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, United States
| | - Kimberly A Reynolds
- The Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, United States.,Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, United States
| | - Tanja Kortemme
- Graduate Group in Biophysics, University of California San Francisco, San Francisco, United States.,Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, United States.,Chan Zuckerberg Biohub, San Francisco, United States
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95
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Chan YH, Zeldovich KB, Matthews CR. An allosteric pathway explains beneficial fitness in yeast for long-range mutations in an essential TIM barrel enzyme. Protein Sci 2020; 29:1911-1923. [PMID: 32643222 PMCID: PMC7454521 DOI: 10.1002/pro.3911] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 07/03/2020] [Accepted: 07/07/2020] [Indexed: 11/06/2022]
Abstract
Protein evolution proceeds by a complex response of organismal fitness to mutations that can simultaneously affect protein stability, structure, and enzymatic activity. To probe the relationship between genotype and phenotype, we chose a fundamental paradigm for protein evolution, folding, and design, the (βα)8 TIM barrel fold. Here, we demonstrate the role of long-range allosteric interactions in the adaptation of an essential hyperthermophilic TIM barrel enzyme to mesophilic conditions in a yeast host. Beneficial fitness effects observed with single and double mutations of the canonical βα-hairpin clamps and the α-helical shell distal to the active site revealed an underlying energy network between opposite faces of the cylindrical β-barrel. We experimentally determined the fitness of multiple mutants in the energetic phase plane, contrasting the energy barrier of the chemical reaction and the folding free energy of the protein. For the system studied, the reaction energy barrier was the primary determinant of organism fitness. Our observations of long-range epistatic interactions uncovered an allosteric pathway in an ancient and ubiquitous enzyme that may provide a novel way of designing proteins with a desired activity and stability profile.
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Affiliation(s)
- Yvonne H Chan
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, Massachusetts, USA.,Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts, USA.,Sanofi Pasteur, Cambridge, Massachusetts, USA
| | - Konstantin B Zeldovich
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts, USA.,Sanofi Pasteur, Cambridge, Massachusetts, USA
| | - Charles R Matthews
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, Massachusetts, USA
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96
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Pillai AS, Chandler SA, Liu Y, Signore AV, Cortez-Romero CR, Benesch JLP, Laganowsky A, Storz JF, Hochberg GKA, Thornton JW. Origin of complexity in haemoglobin evolution. Nature 2020; 581:480-485. [PMID: 32461643 PMCID: PMC8259614 DOI: 10.1038/s41586-020-2292-y] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Accepted: 04/07/2020] [Indexed: 02/02/2023]
Abstract
Most proteins associate into multimeric complexes with specific architectures1,2, which often have functional properties such as cooperative ligand binding or allosteric regulation3. No detailed knowledge is available about how any multimer and its functions arose during evolution. Here we use ancestral protein reconstruction and biophysical assays to elucidate the origins of vertebrate haemoglobin, a heterotetramer of paralogous α- and β-subunits that mediates respiratory oxygen transport and exchange by cooperatively binding oxygen with moderate affinity. We show that modern haemoglobin evolved from an ancient monomer and characterize the historical 'missing link' through which the modern tetramer evolved-a noncooperative homodimer with high oxygen affinity that existed before the gene duplication that generated distinct α- and β-subunits. Reintroducing just two post-duplication historical substitutions into the ancestral protein is sufficient to cause strong tetramerization by creating favourable contacts with more ancient residues on the opposing subunit. These surface substitutions markedly reduce oxygen affinity and even confer cooperativity, because an ancient linkage between the oxygen binding site and the multimerization interface was already an intrinsic feature of the protein's structure. Our findings establish that evolution can produce new complex molecular structures and functions via simple genetic mechanisms that recruit existing biophysical features into higher-level architectures.
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Affiliation(s)
- Arvind S Pillai
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
| | - Shane A Chandler
- Department of Chemistry, Chemistry Research Laboratory, University of Oxford, Oxford, UK
| | - Yang Liu
- Department of Chemistry, Texas A&M University, College Station, TX, USA
| | - Anthony V Signore
- School of Biological Sciences, University of Nebraska, Lincoln, NE, USA
| | | | - Justin L P Benesch
- Department of Chemistry, Chemistry Research Laboratory, University of Oxford, Oxford, UK
| | - Arthur Laganowsky
- Department of Chemistry, Texas A&M University, College Station, TX, USA
| | - Jay F Storz
- School of Biological Sciences, University of Nebraska, Lincoln, NE, USA
| | - Georg K A Hochberg
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
- Max Planck Institute for Terrestrial Microbiology, Marburg, Germany
| | - Joseph W Thornton
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA.
- Department of Human Genetics, University of Chicago, Chicago, IL, USA.
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97
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Bhat AS, Dustin Schaeffer R, Kinch L, Medvedev KE, Grishin NV. Recent advances suggest increased influence of selective pressure in allostery. Curr Opin Struct Biol 2020; 62:183-188. [PMID: 32302874 DOI: 10.1016/j.sbi.2020.02.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Revised: 02/21/2020] [Accepted: 02/25/2020] [Indexed: 12/19/2022]
Abstract
Allosteric regulation of protein functions is ubiquitous in organismal biology, but the principles governing its evolution are not well understood. Here we discuss recent studies supporting the large-scale existence of latent allostery in ancestor proteins of superfamilies. As suggested, the evolution of allostery could be driven by the need for specificity in paralogs of slow evolving protein complexes with conserved active sites. The same slow evolution is displayed by purifying selection exhibited in allosteric proteins with somatic mutations involved in cancer, where disease-associated mutations are enriched in both orthosteric and allosteric sites. Consequently, disease-associated variants can be used to identify druggable allosteric sites that are specific for paralogs in protein superfamilies with otherwise similar functions.
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Affiliation(s)
- Archana S Bhat
- Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, United States
| | - Richard Dustin Schaeffer
- Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, United States
| | - Lisa Kinch
- Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, United States
| | - Kirill E Medvedev
- Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, United States
| | - Nick V Grishin
- Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, United States; Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, United States.
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98
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Coyote-Maestas W, Nedrud D, Okorafor S, He Y, Schmidt D. Targeted insertional mutagenesis libraries for deep domain insertion profiling. Nucleic Acids Res 2020; 48:e11. [PMID: 31745561 PMCID: PMC6954442 DOI: 10.1093/nar/gkz1110] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Revised: 09/22/2019] [Accepted: 11/08/2019] [Indexed: 11/21/2022] Open
Abstract
Domain recombination is a key principle in protein evolution and protein engineering, but inserting a donor domain into every position of a target protein is not easily experimentally accessible. Most contemporary domain insertion profiling approaches rely on DNA transposons, which are constrained by sequence bias. Here, we establish Saturated Programmable Insertion Engineering (SPINE), an unbiased, comprehensive, and targeted domain insertion library generation technique using oligo library synthesis and multi-step Golden Gate cloning. Through benchmarking to MuA transposon-mediated library generation on four ion channel genes, we demonstrate that SPINE-generated libraries are enriched for in-frame insertions, have drastically reduced sequence bias as well as near-complete and highly-redundant coverage. Unlike transposon-mediated domain insertion that was severely biased and sparse for some genes, SPINE generated high-quality libraries for all genes tested. Using the Inward Rectifier K+ channel Kir2.1, we validate the practical utility of SPINE by constructing and comparing domain insertion permissibility maps. SPINE is the first technology to enable saturated domain insertion profiling. SPINE could help explore the relationship between domain insertions and protein function, and how this relationship is shaped by evolutionary forces and can be engineered for biomedical applications.
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Affiliation(s)
- Willow Coyote-Maestas
- Dept. of Biochemistry, Molecular Biology & Biophysics, University of Minnesota, Minneapolis, MN 55455, USA
| | - David Nedrud
- Dept. of Biochemistry, Molecular Biology & Biophysics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Steffan Okorafor
- Dept. of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Yungui He
- Dept. of Genetics, Cell Biology & Development, University of Minnesota, Minneapolis, MN 55455, USA
| | - Daniel Schmidt
- Dept. of Genetics, Cell Biology & Development, University of Minnesota, Minneapolis, MN 55455, USA
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99
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Amacher JF, Brooks L, Hampton TH, Madden DR. Specificity in PDZ-peptide interaction networks: Computational analysis and review. JOURNAL OF STRUCTURAL BIOLOGY-X 2020; 4:100022. [PMID: 32289118 PMCID: PMC7138185 DOI: 10.1016/j.yjsbx.2020.100022] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 02/26/2020] [Accepted: 02/29/2020] [Indexed: 01/03/2023]
Abstract
Globular PDZ domains typically serve as protein-protein interaction modules that regulate a wide variety of cellular functions via recognition of short linear motifs (SLiMs). Often, PDZ mediated-interactions are essential components of macromolecular complexes, and disruption affects the entire scaffold. Due to their roles as linchpins in trafficking and signaling pathways, PDZ domains are attractive targets: both for controlling viral pathogens, which bind PDZ domains and hijack cellular machinery, as well as for developing therapies to combat human disease. However, successful therapeutic interventions that avoid off-target effects are a challenge, because each PDZ domain interacts with a number of cellular targets, and specific binding preferences can be difficult to decipher. Over twenty-five years of research has produced a wealth of data on the stereochemical preferences of individual PDZ proteins and their binding partners. Currently the field lacks a central repository for this information. Here, we provide this important resource and provide a manually curated, comprehensive list of the 271 human PDZ domains. We use individual domain, as well as recent genomic and proteomic, data in order to gain a holistic view of PDZ domains and interaction networks, arguing this knowledge is critical to optimize targeting selectivity and to benefit human health.
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Affiliation(s)
- Jeanine F Amacher
- Department of Biochemistry and Cell Biology, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA.,Department of Chemistry, Western Washington University, Bellingham, WA 98225, USA
| | - Lionel Brooks
- Department of Biology, Western Washington University, Bellingham, WA 98225, USA
| | - Thomas H Hampton
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA
| | - Dean R Madden
- Department of Biochemistry and Cell Biology, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA
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100
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Sun A, Xu K, Liu H, Li H, Shi Y, Zhu X, Liang T, Li X, Cao X, Ji Y, Jiang T, Xu C, Liu X. The evolution of zebrafish RAG2 protein is required for adapting to the elevated body temperature of the higher endothermic vertebrates. Sci Rep 2020; 10:4126. [PMID: 32139788 PMCID: PMC7057966 DOI: 10.1038/s41598-020-61019-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 02/19/2020] [Indexed: 11/21/2022] Open
Abstract
The recombination activating gene (RAG or RAG1/RAG2 complex)-mediated adaptive immune system is a hallmark of jawed vertebrates. It has been reported that RAG originated in invertebrates. However, whether RAG further evolved once it arose in jawed vertebrates remains largely unknown. Here, we found that zebrafish RAG (zRAG) had a lower activity than mouse RAG (mRAG). Intriguingly, the attenuated stability of zebrafish RAG2 (zRAG2), but not zebrafish RAG1, caused the reduced V(D)J recombination efficiency compared to mRAG at 37 °C which are the body temperature of most endotherms except birds. Importantly, the lower temperature 28 °C, which is the best temperature for zebrafish growth, made the recombination efficiency of zRAG similar to that of mRAG by improving the stability of zRAG2. Consistent with the prementioned observation, the V(D)J recombination of Rag2KI/KI mice, which zRAG2 was substituted for mRAG2, was also severely impaired. Unexpectedly, Rag2KI/KI mice developed cachexia syndromes accompanied by premature death. Taken together, our findings illustrate that the evolution of zebrafish RAG2 protein is required for adapting to the elevated body temperature of the higher endothermic vertebrates.
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Affiliation(s)
- Ao Sun
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Ke Xu
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Haifeng Liu
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Hua Li
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yaohuang Shi
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.,School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Xiaoyan Zhu
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Tao Liang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xinyue Li
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xianxia Cao
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.,School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Yanhong Ji
- Department of Pathogenic Biology and Immunology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Centre, Xi'an, Shaanxi, 710061, China
| | - Taijiao Jiang
- Center of System Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China
| | - Chenqi Xu
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xiaolong Liu
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China. .,School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
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