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Li Z, Chen M, Tian W, Wang L, Wu X. Investigating the role of polar amino acids driven by evolution in the active site architecture of GH11 xylanase. Int J Biol Macromol 2025; 315:144464. [PMID: 40403789 DOI: 10.1016/j.ijbiomac.2025.144464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2025] [Revised: 05/09/2025] [Accepted: 05/19/2025] [Indexed: 05/24/2025]
Abstract
Enzymes, as vital biomacromolecules, have developed significant plasticity, enabling adaptation to diverse environments and catalysis of numerous biochemical reactions. However, enzyme evolution is constrained by mutational limitations, as amino acid substitutions often impair structure or function, hampering optimization endeavors. To address this, we integrated structural bioinformatics with site-directed mutagenesis to investigate the evolutionary trends of four GH11 family xylanases (XynA, XynB, XynD, and XynE) from Aspergillus niger An76. Our analysis revealed that conserved residues in active sites are unevenly distributed, with highly conserved residues critical for catalysis and relatively conserved residues offering mutation potential. The mutation of Asp/Asn near catalytic residues at -1 subsite could not only alter the catalytic activity, but also shift the optimal pH by one unit. Additional mutants, including XynB-A143P, XynA-F142W, XynD-E20T, and XynD-E192Q, increased enzymatic activity by 17%, 46%, 82%, and 26%, respectively. More importantly, ancestral sequence reconstruction highlighted the importance of Arg at the -1 subsite of GH11 xylanases, and combinatorial mutation based on Y160R reinstated the pseudo-enzyme XynE's activity to 417.6 IU/mg. This study demonstrates the efficacy of evolutionary-informed mutagenesis for precise enzyme design, providing insights for optimizing GH11 family and other enzymes.
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Affiliation(s)
- Zhaoran Li
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao 266237, China
| | - Muyang Chen
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao 266237, China
| | - Wenya Tian
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao 266237, China
| | - Lushan Wang
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao 266237, China
| | - Xiuyun Wu
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao 266237, China.
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2
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Almeida de Jesus D, Batista DM, Monteiro EF, Salzman S, Carvalho LM, Santana K, André T. Structural changes and adaptative evolutionary constraints in FLOWERING LOCUS T and TERMINAL FLOWER1-like genes of flowering plants. Front Genet 2022; 13:954015. [PMID: 36246591 PMCID: PMC9556947 DOI: 10.3389/fgene.2022.954015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 08/29/2022] [Indexed: 11/13/2022] Open
Abstract
Regulation of flowering is a crucial event in the evolutionary history of angiosperms. The production of flowers is regulated through the integration of different environmental and endogenous stimuli, many of which involve the activation of different genes in a hierarchical and complex signaling network. The FLOWERING LOCUS T/TERMINAL FLOWER 1 (FT/TFL1) gene family is known to regulate important aspects of flowering in plants. To better understand the pivotal events that changed FT and TFL1 functions during the evolution of angiosperms, we reconstructed the ancestral sequences of FT/TFL1-like genes and predicted protein structures through in silico modeling to identify determinant sites that evolved in both proteins and allowed the adaptative diversification in the flowering phenology and developmental processes. In addition, we demonstrate that the occurrence of destabilizing mutations in residues located at the phosphatidylcholine binding sites of FT structure are under positive selection, and some residues of 4th exon are under negative selection, which is compensated by the occurrence of stabilizing mutations in key regions and the P-loop to maintain the overall protein stability. Our results shed light on the evolutionary history of key genes involved in the diversification of angiosperms.
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Affiliation(s)
- Deivid Almeida de Jesus
- Institute of Biology Genetics Graduate Program, Federal University of Rio de Janeiro Rio de Janeiro, Rio de Janeiro, Brazil
| | - Darlisson Mesquista Batista
- Programa de Pós-Graduação em Biodiversidade, Universidade Federal do Oeste do Pará Santarém, Pará, Santarém, Brazil
| | - Elton Figueira Monteiro
- Programa de Pós-Graduação em Biodiversidade, Universidade Federal do Oeste do Pará Santarém, Pará, Santarém, Brazil
| | - Shayla Salzman
- School of Integrative Plant Sciences. Section of Plant Biology. Cornell University Ithaca, New York, NY, United States
| | - Lucas Miguel Carvalho
- Center for Computing in Engineering and Sciences, State University of Campinas. Campinas, São Paulo, Brazil
| | - Kauê Santana
- Institute of Biodiversity, Federal University of Western Pará Santarém Pará, Santarém, Brazil
- *Correspondence: Kauê Santana, ; Thiago André,
| | - Thiago André
- Botany Department, University of Brasília, Brasília, Brazil
- *Correspondence: Kauê Santana, ; Thiago André,
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3
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Learning the local landscape of protein structures with convolutional neural networks. J Biol Phys 2021; 47:435-454. [PMID: 34751854 DOI: 10.1007/s10867-021-09593-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 10/18/2021] [Indexed: 10/19/2022] Open
Abstract
One fundamental problem of protein biochemistry is to predict protein structure from amino acid sequence. The inverse problem, predicting either entire sequences or individual mutations that are consistent with a given protein structure, has received much less attention even though it has important applications in both protein engineering and evolutionary biology. Here, we ask whether 3D convolutional neural networks (3D CNNs) can learn the local fitness landscape of protein structure to reliably predict either the wild-type amino acid or the consensus in a multiple sequence alignment from the local structural context surrounding site of interest. We find that the network can predict wild type with good accuracy, and that network confidence is a reliable measure of whether a given prediction is likely going to be correct or not. Predictions of consensus are less accurate and are primarily driven by whether or not the consensus matches the wild type. Our work suggests that high-confidence mis-predictions of the wild type may identify sites that are primed for mutation and likely targets for protein engineering.
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4
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Paul A, Subhadarshini S, Srinivasan N. Pseudokinases repurpose flexibility signatures associated with the protein kinase fold for noncatalytic roles. Proteins 2021; 90:747-764. [PMID: 34708889 DOI: 10.1002/prot.26271] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 09/22/2021] [Accepted: 10/18/2021] [Indexed: 01/27/2023]
Abstract
The bilobal protein kinase-like fold in pseudokinases lack one or more catalytic residues, conserved in canonical protein kinases, and are considered enzymatically deficient. Tertiary structures of pseudokinases reveal that their loops topologically equivalent to activation segments of kinases adopt contracted configurations, which is typically extended in active conformation of kinases. Herein, anisotropic network model based normal mode analysis (NMA) was conducted on 51 active conformation structures of protein kinases and 26 crystal structures of pseudokinases. Our observations indicate that although backbone fluctuation profiles are similar for individual kinase-pseudokinase families, low intensity mean square fluctuations in pseudo-activation segment and other sub-structures impart rigidity to pseudokinases. Analyses of collective motions from functional modes reveal that pseudokinases, compared to active kinases, undergo distinct conformational transitions using the same structural fold. All-atom NMA of protein kinase-pseudokinase pairs from each family, sharing high amino acid sequence identities, yielded distinct community clusters, partitioned by residues exhibiting highly correlated fluctuations. It appears that atomic fluctuations from equivalent activation segments guide community membership and network topologies for respective kinase and pseudokinase. Our findings indicate that such adaptations in backbone and side-chain fluctuations render pseudokinases competent for catalysis-independent roles.
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Affiliation(s)
- Anindita Paul
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India
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5
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Echave J. Evolutionary coupling range varies widely among enzymes depending on selection pressure. Biophys J 2021; 120:4320-4324. [PMID: 34480927 DOI: 10.1016/j.bpj.2021.08.042] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 07/19/2021] [Accepted: 08/30/2021] [Indexed: 10/20/2022] Open
Abstract
Recent studies proposed that enzyme-active sites induce evolutionary constraints at long distances. The physical origin of such long-range evolutionary coupling is unknown. Here, I use a recent biophysical model of evolution to study the relationship between physical and evolutionary couplings on a diverse data set of monomeric enzymes. I show that evolutionary coupling is not universally long-range. Rather, range varies widely among enzymes, from 2 to 20 Å. Furthermore, the evolutionary coupling range of an enzyme does not inform on the underlying physical coupling, which is short range for all enzymes. Rather, evolutionary coupling range is determined by functional selection pressure.
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Affiliation(s)
- Julian Echave
- Instituto de Ciencias Físicas, Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín, San Martín, Buenos Aires, Argentina.
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6
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Sharir-Ivry A, Xia Y. Quantifying evolutionary importance of protein sites: A Tale of two measures. PLoS Genet 2021; 17:e1009476. [PMID: 33826605 PMCID: PMC8026052 DOI: 10.1371/journal.pgen.1009476] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 03/09/2021] [Indexed: 12/05/2022] Open
Abstract
A key challenge in evolutionary biology is the accurate quantification of selective pressure on proteins and other biological macromolecules at single-site resolution. The evolutionary importance of a protein site under purifying selection is typically measured by the degree of conservation of the protein site itself. A possible alternative measure is the strength of the site-induced conservation gradient in the rest of the protein structure. However, the quantitative relationship between these two measures remains unknown. Here, we show that despite major differences, there is a strong linear relationship between the two measures such that more conserved protein sites also induce stronger conservation gradient in the rest of the protein. This linear relationship is universal as it holds for different types of proteins and functional sites in proteins. Our results show that the strong selective pressure acting on the functional site in general percolates through the rest of the protein via residue-residue contacts. Surprisingly however, catalytic sites in enzymes are the principal exception to this rule. Catalytic sites induce significantly stronger conservation gradients in the rest of the protein than expected from the degree of conservation of the site alone. The unique requirement for the active site to selectively stabilize the transition state of the catalyzed chemical reaction imposes additional selective constraints on the rest of the enzyme. Sites within proteins which are important for stability or function are under stronger selective pressure and evolve more slowly than other sites. Catalytic sites in enzymes are such highly conserved sites with relatively low evolutionary rates. Recently, catalytic sites were shown to induce a strong gradient of conservation such that the closer a residue is to the catalytic site, the more conserved it is. Here we show that there is a universal linear relationship between the degree of evolutionary conservation of a protein site and the conservation gradient it induces in the protein tertiary structure, applicable to all types of sites. Our findings suggest that selective pressure acting on a protein site generally percolates through the rest of the protein via residue-residue contacts. Remarkably however, catalytic sites induce significantly stronger conservation gradients than expected from their degree of conservation alone. Our results indicate that the strong conservation gradient induced by catalytic sites is driven by the unique function of enzyme catalysis, which requires the participation of many residues beyond the few key catalytic residues. Our results provide insights into evolutionary conservation patterns of and surrounding proteins functional sites, with implications for functional site prediction and protein design.
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Affiliation(s)
- Avital Sharir-Ivry
- Department of Bioengineering, McGill University, Montreal, Quebec, Canada
| | - Yu Xia
- Department of Bioengineering, McGill University, Montreal, Quebec, Canada
- * E-mail:
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7
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The Roles of Protein Structure, Taxon Sampling, and Model Complexity in Phylogenomics: A Case Study Focused on Early Animal Divergences. BIOPHYSICA 2021. [DOI: 10.3390/biophysica1020008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Despite the long history of using protein sequences to infer the tree of life, the potential for different parts of protein structures to retain historical signal remains unclear. We propose that it might be possible to improve analyses of phylogenomic datasets by incorporating information about protein structure. We test this idea using the position of the root of Metazoa (animals) as a model system. We examined the distribution of “strongly decisive” sites (alignment positions that support a specific tree topology) in a dataset comprising >1500 proteins and almost 100 taxa. The proportion of each class of strongly decisive sites in different structural environments was very sensitive to the model used to analyze the data when a limited number of taxa were used but they were stable when taxa were added. As long as enough taxa were analyzed, sites in all structural environments supported the same topology regardless of whether standard tree searches or decisive sites were used to select the optimal tree. However, the use of decisive sites revealed a difference between the support for minority topologies for sites in different structural environments: buried sites and sites in sheet and coil environments exhibited equal support for the minority topologies, whereas solvent-exposed and helix sites had unequal numbers of sites, supporting the minority topologies. This suggests that the relatively slowly evolving buried, sheet, and coil sites are giving an accurate picture of the true species tree and the amount of conflict among gene trees. Taken as a whole, this study indicates that phylogenetic analyses using sites in different structural environments can yield different topologies for the deepest branches in the animal tree of life and that analyzing larger numbers of taxa eliminates this conflict. More broadly, our results highlight the desirability of incorporating information about protein structure into phylogenomic analyses.
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8
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Paul A, Srinivasan N. Genome-wide and structural analyses of pseudokinases encoded in the genome of Arabidopsis thaliana provide functional insights. Proteins 2020; 88:1620-1638. [PMID: 32667690 DOI: 10.1002/prot.25981] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 05/26/2020] [Accepted: 07/12/2020] [Indexed: 12/31/2022]
Abstract
Protein Kinase-Like Non-Kinases (PKLNKs), commonly known as "pseudokinases", are homologous to eukaryotic Ser/Thr/Tyr protein kinases (PKs) but lack the crucial aspartate residue in the catalytic loop, indispensable for phosphotransferase activity. Therefore, they are predicted to be "catalytically inactive" enzyme homologs. Analysis of protein-kinase like sequences from Arabidopsis thaliana led to the identification of more than 120 pseudokinases lacking catalytic aspartate, majority of which are closely related to the plant-specific receptor-like kinase family. These pseudokinases engage in different biological processes, enabled by their diverse domain architectures and specific subcellular localizations. Structural comparison of pseudokinases with active and inactive conformations of canonical PKs, belonging to both plant and animal origin, revealed unique structural differences. The currently available crystal structures of pseudokinases show that the loop topologically equivalent to activation segment of PKs adopts a distinct-folded conformation, packing against the pseudoenzyme core, in contrast to the extended and inhibitory geometries observed for active and inactive states, respectively, of catalytic PKs. Salt-bridge between ATP-binding Lys and DFG-Asp as well as hydrophobic interactions between the conserved nonpolar residue C-terminal to the equivalent DFG motif and nonpolar residues in C-helix mediate such a conformation in pseudokinases. This results in enhanced solvent accessibility of the pseudocatalytic loop in pseudokinases that can possibly serve as an interacting surface while associating with other proteins. Specifically, our analysis identified several residues that may be involved in pseudokinase regulation and hints at the repurposing of pseudocatalytic residues to achieve mechanistic control over noncatalytic functions of pseudoenzymes.
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Affiliation(s)
- Anindita Paul
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India
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9
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A beginner's guide to molecular dynamics simulations and the identification of cross-correlation networks for enzyme engineering. Methods Enzymol 2020; 643:15-49. [PMID: 32896280 DOI: 10.1016/bs.mie.2020.04.020] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
The functional properties of proteins are decided not only by their relatively rigid overall structures, but even more importantly, by their dynamic properties. In a protein, some regions of structure exhibit highly correlated or anti-correlated motions with others, some are highly dynamic but uncorrelated, while other regions are relatively static. The residues with correlated or anti-correlated motions can form a so-called dynamic cross-correlation network, through which information can be transmitted. Such networks have been shown to be critical to allosteric transitions, and ligand binding, and have also been shown to be able to mediate epistatic interactions between mutations. As a result, they are likely to play a significant role in the development of new enzyme engineering strategies. In this chapter, protocols are provided for the assessment of dynamic cross-correlation networks, and for their application in protein engineering. Transketolase from E. coli is used as a model and the software GROMACS is applied for carrying out MD simulations to generate trajectories containing structural ensembles. The trajectory is then used for a dynamic cross correlation analysis using the R package, Bio3D. A matrix of all atom-wise cross-correlation coefficients is finally obtained, which can be displayed in a graphical representation termed a dynamical cross-correlation matrix.
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10
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Sharir-Ivry A, Xia Y. Non-catalytic Binding Sites Induce Weaker Long-Range Evolutionary Rate Gradients than Catalytic Sites in Enzymes. J Mol Biol 2019; 431:3860-3870. [DOI: 10.1016/j.jmb.2019.07.019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Revised: 06/26/2019] [Accepted: 07/11/2019] [Indexed: 01/02/2023]
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11
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Ribeiro AJM, Das S, Dawson N, Zaru R, Orchard S, Thornton JM, Orengo C, Zeqiraj E, Murphy JM, Eyers PA. Emerging concepts in pseudoenzyme classification, evolution, and signaling. Sci Signal 2019; 12:eaat9797. [PMID: 31409758 DOI: 10.1126/scisignal.aat9797] [Citation(s) in RCA: 68] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The 21st century is witnessing an explosive surge in our understanding of pseudoenzyme-driven regulatory mechanisms in biology. Pseudoenzymes are proteins that have sequence homology with enzyme families but that are proven or predicted to lack enzyme activity due to mutations in otherwise conserved catalytic amino acids. The best-studied pseudoenzymes are pseudokinases, although examples from other families are emerging at a rapid rate as experimental approaches catch up with an avalanche of freely available informatics data. Kingdom-wide analysis in prokaryotes, archaea and eukaryotes reveals that between 5 and 10% of proteins that make up enzyme families are pseudoenzymes, with notable expansions and contractions seemingly associated with specific signaling niches. Pseudoenzymes can allosterically activate canonical enzymes, act as scaffolds to control assembly of signaling complexes and their localization, serve as molecular switches, or regulate signaling networks through substrate or enzyme sequestration. Molecular analysis of pseudoenzymes is rapidly advancing knowledge of how they perform noncatalytic functions and is enabling the discovery of unexpected, and previously unappreciated, functions of their intensively studied enzyme counterparts. Notably, upon further examination, some pseudoenzymes have previously unknown enzymatic activities that could not have been predicted a priori. Pseudoenzymes can be targeted and manipulated by small molecules and therefore represent new therapeutic targets (or anti-targets, where intervention should be avoided) in various diseases. In this review, which brings together broad bioinformatics and cell signaling approaches in the field, we highlight a selection of findings relevant to a contemporary understanding of pseudoenzyme-based biology.
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Affiliation(s)
- António J M Ribeiro
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Sayoni Das
- Structural and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK
| | - Natalie Dawson
- Structural and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK
| | - Rossana Zaru
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Sandra Orchard
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Janet M Thornton
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Christine Orengo
- Structural and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK
| | - Elton Zeqiraj
- Astbury Centre for Structural Molecular Biology, Molecular and Cellular Biology, Faculty of Biological Sciences, Astbury Building, Room 8.109, University of Leeds, Leeds LS2 9JT, UK
| | - James M Murphy
- Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Victoria 3052, Australia
| | - Patrick A Eyers
- Department of Biochemistry, Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, UK.
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12
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Sharir-Ivry A, Xia Y. Using Pseudoenzymes to Probe Evolutionary Design Principles of Enzymes. Evol Bioinform Online 2019; 15:1176934319855937. [PMID: 31236007 PMCID: PMC6572901 DOI: 10.1177/1176934319855937] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Accepted: 05/15/2019] [Indexed: 12/24/2022] Open
Abstract
Enzymes are governed by unique evolutionary design principles as their catalytic sites were shown to induce long-range evolutionary conservation gradients. We have recently used a comparative bioinformatics approach to disentangle structural determinants from other possible determinants of the evolutionary conservation gradients. The approach is based on comparing the evolutionary patterns of enzymes to those of pseudoenzymes with the same tertiary structure where the catalytic functionality is turned off. This approach provides a way to evaluate several hypotheses regarding the origin of the observed evolutionary conservation gradient in enzymes. The conclusions from such comparative analyses are important for a better understanding of the unique evolutionary design principles of enzymes, which can in turn potentially guide the design of new and improved enzymes.
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Affiliation(s)
| | - Yu Xia
- Department of Bioengineering, McGill University, Montreal, QC, Canada
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