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Anuradha C, Mol PP, Chandrasekar A, Backiyarani S, Thangavelu R, Selvarajan R. Unveiling the dynamic expression of PR-1 during Musa spp. infection by Fusarium oxysporum fsp. Cubense: a cloning and characterization study. Mol Biol Rep 2024; 51:362. [PMID: 38403791 DOI: 10.1007/s11033-024-09258-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 01/15/2024] [Indexed: 02/27/2024]
Abstract
BACKGROUND Pathogen-related proteins (PR) are pivotal in plant defense, combating diverse biotic and abiotic stresses. While multiple gene families contribute to banana resistance against Fusarium oxysporum f sp. cubense (Foc), Pseudocercospora eumusae, and Pratylenchus coffeae, the significance of PR-1 genes in defense is paramount. METHODS Three PR-1 genes, up-regulated under diverse biotic stresses, were cloned from both resistant and susceptible cultivars of Foc, P. eumusae, and P. coffeae. Molecular characterization, phylogenetic analysis, and docking studies with the Foc TR4 CP gene were conducted. RESULTS Through transcriptomic and real-time studies, three PR-1 genes (Ma02_g15050, Ma02_g15060, and Ma04_g34800) from Musa spp. were identified. These genes exhibited significant up-regulation in resistant cultivars when exposed to Foc, P. eumusae, and P. coffeae. Cloning of these genes was successfully performed from both resistant and susceptible cultivars of Foc race 1 and TR4, P. eumusae, and P. coffeae. Distinct characteristics were observed among the PR-1 genes, with groups 1 and 2 being acidic with signal peptides, and group 3 being basic without signal peptides. All cloned PR-1 proteins belonged to the CAP superfamily (PF00188). Phylogenetic analysis revealed clustering patterns for acidic PR-1 proteins, and KEGG orthology showed associations with vital pathways, including MAPK signaling, plant hormone signal transduction, and plant-pathogen interaction. Secondary and tertiary structure analyses confirmed sequence conservation across studied species. Docking studies explored interactions between the cerato-platanin (CP) gene from Foc TR4 and Ma02_g15060 from banana, suggesting the potential hindrance of PR-1 antifungal activity through direct interaction. CONCLUSIONS The findings underscore the crucial role of cloned PR-1 genes in banana plant defense mechanisms against a broad spectrum of biotic stresses. These genes, especially those in groups 1 and 2, hold promise as candidates for developing stress-tolerant banana cultivars. The study provides valuable insights into the molecular aspects of banana defense strategies, emphasizing the potential applications of PR-1 genes in enhancing banana resilience.
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Affiliation(s)
- Chelliah Anuradha
- ICAR-National Research Centre for Banana, Thogamalai Road, Thayanur Post, Tiruchirappalli, Tamil Nadu, 620 102, India.
| | - Punchakkara Prashina Mol
- ICAR-National Research Centre for Banana, Thogamalai Road, Thayanur Post, Tiruchirappalli, Tamil Nadu, 620 102, India
| | - Arumugam Chandrasekar
- ICAR-National Research Centre for Banana, Thogamalai Road, Thayanur Post, Tiruchirappalli, Tamil Nadu, 620 102, India
| | - Suthanthiram Backiyarani
- ICAR-National Research Centre for Banana, Thogamalai Road, Thayanur Post, Tiruchirappalli, Tamil Nadu, 620 102, India
| | - Raman Thangavelu
- ICAR-National Research Centre for Banana, Thogamalai Road, Thayanur Post, Tiruchirappalli, Tamil Nadu, 620 102, India
| | - Ramasamy Selvarajan
- ICAR-National Research Centre for Banana, Thogamalai Road, Thayanur Post, Tiruchirappalli, Tamil Nadu, 620 102, India
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Pathira Kankanamge LS, Ruffner LA, Touch MM, Pina M, Beuning PJ, Ondrechen MJ. Functional annotation of haloacid dehalogenase superfamily structural genomics proteins. Biochem J 2023; 480:1553-1569. [PMID: 37747786 DOI: 10.1042/bcj20230057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 09/20/2023] [Accepted: 09/25/2023] [Indexed: 09/26/2023]
Abstract
Haloacid dehalogenases (HAD) are members of a large superfamily that includes many Structural Genomics proteins with poorly characterized functionality. This superfamily consists of multiple types of enzymes that can act as sugar phosphatases, haloacid dehalogenases, phosphonoacetaldehyde hydrolases, ATPases, or phosphate monoesterases. Here, we report on predicted functional annotations and experimental testing by direct biochemical assay for Structural Genomics proteins from the HAD superfamily. To characterize the functions of HAD superfamily members, nine representative HAD proteins and 21 structural genomics proteins are analyzed. Using techniques based on computed chemical and electrostatic properties of individual amino acids, the functions of five structural genomics proteins from the HAD superfamily are predicted and validated by biochemical assays. A dehalogenase-like hydrolase, RSc1362 (Uniprot Q8XZN3, PDB 3UMB) is predicted to be a dehalogenase and dehalogenase activity is confirmed experimentally. Four proteins predicted to be sugar phosphatases are characterized as follows: a sugar phosphatase from Thermophilus volcanium (Uniprot Q978Y6) with trehalose-6-phosphate phosphatase and fructose-6-phosphate phosphatase activity; haloacid dehalogenase-like hydrolase from Bacteroides thetaiotaomicron (Uniprot Q8A2F3; PDB 3NIW) with fructose-6-phosphate phosphatase and sucrose-6-phosphate phosphatase activity; putative phosphatase from Eubacterium rectale (Uniprot D0VWU2; PDB 3DAO) as a sucrose-6-phosphate phosphatase; and hypothetical protein from Geobacillus kaustophilus (Uniprot Q5L139; PDB 2PQ0) as a fructose-6-phosphate phosphatase. Most of these sugar phosphatases showed some substrate promiscuity.
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Affiliation(s)
| | - Lydia A Ruffner
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, U.S.A
| | - Mong Mary Touch
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, U.S.A
| | - Manuel Pina
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, U.S.A
| | - Penny J Beuning
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, U.S.A
| | - Mary Jo Ondrechen
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, U.S.A
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Mills CL, Yin P, Leifer B, Ferrins L, O’Doherty GA, Beuning PJ, Ondrechen MJ. Functional Characterization of Structural Genomics Proteins in the Crotonase Superfamily. ACS Chem Biol 2022; 17:395-403. [PMID: 35060718 DOI: 10.1021/acschembio.1c00842] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Members of the Crotonase superfamily, a mechanistically diverse family of proteins that share a conserved quaternary structure, can often catalyze more than one reaction. However, the spectrum of activity for its members has not been well studied. We report on measured crotonase and hydrolase activity for eight structural genomics (SG) proteins from the Crotonase superfamily plus two previously characterized proteins, intended as controls: human enoyl CoA hydratase (ECH) and Anabaena β-diketone hydrolase. Like most of the 15,000+ SG protein structures deposited in the Protein Data Bank (PDB), the eight SG proteins are of unknown or uncertain biochemical function. The functional characterization of the eight SG proteins is guided by the Structurally Aligned Local Sites of Activity (SALSA), a local-structure-based computational approach to functional annotation. For human ECH, the turnover number for hydrolase activity is threefold higher than that for ECH activity, although the catalytic efficiency is 160-fold higher for ECH. Three SG proteins originally annotated as ECHs were predicted by SALSA to be hydrolases and are observed to have higher catalytic efficiencies for hydrolase activity than for ECH activity, on par with the previously characterized hydrolase. Among the five SG proteins predicted by SALSA to be ECHs, all but one also show some hydrolase activity; all five exhibit lower ECH activity than the human ECH with respect to the crotonyl-CoA substrate. Here, we show examples demonstrating that SALSA can correct functional misannotations even within enzyme families that display promiscuous activity.
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Affiliation(s)
- Caitlyn L. Mills
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, United States
| | - Pengcheng Yin
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, United States
| | - Becky Leifer
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, United States
| | - Lori Ferrins
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, United States
| | - George A. O’Doherty
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, United States
| | - Penny J. Beuning
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, United States
| | - Mary Jo Ondrechen
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, United States
- Department of Inorganic and Analytical Chemistry, Budapest University of Technology and Economics, 4 Szent Gellért tér, 1111 Budapest, Hungary
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Ngu L, Winters JN, Nguyen K, Ramos KE, DeLateur NA, Makowski L, Whitford PC, Ondrechen MJ, Beuning PJ. Probing remote residues important for catalysis in Escherichia coli ornithine transcarbamoylase. PLoS One 2020; 15:e0228487. [PMID: 32027716 PMCID: PMC7004355 DOI: 10.1371/journal.pone.0228487] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2019] [Accepted: 01/16/2020] [Indexed: 12/14/2022] Open
Abstract
Understanding how enzymes achieve their tremendous catalytic power is a major question in biochemistry. Greater understanding is also needed for enzyme engineering applications. In many cases, enzyme efficiency and specificity depend on residues not in direct contact with the substrate, termed remote residues. This work focuses on Escherichia coli ornithine transcarbamoylase (OTC), which plays a central role in amino acid metabolism. OTC has been reported to undergo an induced-fit conformational change upon binding its first substrate, carbamoyl phosphate (CP), and several residues important for activity have been identified. Using computational methods based on the computed chemical properties from theoretical titration curves, sequence-based scores derived from evolutionary history, and protein surface topology, residues important for catalytic activity were predicted. The roles of these residues in OTC activity were tested by constructing mutations at predicted positions, followed by steady-state kinetics assays and substrate binding studies with the variants. First-layer mutations R57A and D231A, second-layer mutation H272L, and third-layer mutation E299Q, result in 57- to 450-fold reductions in kcat/KM with respect to CP and 44- to 580-fold reductions with respect to ornithine. Second-layer mutations D140N and Y160S also reduce activity with respect to ornithine. Most variants had decreased stability relative to wild-type OTC, with variants H272L, H272N, and E299Q having the greatest decreases. Variants H272L, E299Q, and R57A also show compromised CP binding. In addition to direct effects on catalytic activity, effects on overall protein stability and substrate binding were observed that reveal the intricacies of how these residues contribute to catalysis.
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Affiliation(s)
- Lisa Ngu
- Department of Chemistry & Chemical Biology, Northeastern University, Boston, MA, United States of America
| | - Jenifer N. Winters
- Department of Chemistry & Chemical Biology, Northeastern University, Boston, MA, United States of America
| | - Kien Nguyen
- Department of Physics, Northeastern University, Boston, MA, United States of America
| | - Kevin E. Ramos
- Department of Chemistry & Chemical Biology, Northeastern University, Boston, MA, United States of America
| | - Nicholas A. DeLateur
- Department of Chemistry & Chemical Biology, Northeastern University, Boston, MA, United States of America
| | - Lee Makowski
- Department of Chemistry & Chemical Biology, Northeastern University, Boston, MA, United States of America
- Department of Bioengineering, Northeastern University, Boston, MA, United States of America
| | - Paul C. Whitford
- Department of Physics, Northeastern University, Boston, MA, United States of America
| | - Mary Jo Ondrechen
- Department of Chemistry & Chemical Biology, Northeastern University, Boston, MA, United States of America
- * E-mail: (MJO); (PJB)
| | - Penny J. Beuning
- Department of Chemistry & Chemical Biology, Northeastern University, Boston, MA, United States of America
- * E-mail: (MJO); (PJB)
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Mills CL, Garg R, Lee JS, Tian L, Suciu A, Cooperman GD, Beuning PJ, Ondrechen MJ. Functional classification of protein structures by local structure matching in graph representation. Protein Sci 2018; 27:1125-1135. [PMID: 29604149 PMCID: PMC5980557 DOI: 10.1002/pro.3416] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Revised: 03/21/2018] [Accepted: 03/26/2018] [Indexed: 11/08/2022]
Abstract
As a result of high‐throughput protein structure initiatives, over 14,400 protein structures have been solved by Structural Genomics (SG) centers and participating research groups. While the totality of SG data represents a tremendous contribution to genomics and structural biology, reliable functional information for these proteins is generally lacking. Better functional predictions for SG proteins will add substantial value to the structural information already obtained. Our method described herein, Graph Representation of Active Sites for Prediction of Function (GRASP‐Func), predicts quickly and accurately the biochemical function of proteins by representing residues at the predicted local active site as graphs rather than in Cartesian coordinates. We compare the GRASP‐Func method to our previously reported method, Structurally Aligned Local Sites of Activity (SALSA), using the Ribulose Phosphate Binding Barrel (RPBB), 6‐Hairpin Glycosidase (6‐HG), and Concanavalin A‐like Lectins/Glucanase (CAL/G) superfamilies as test cases. In each of the superfamilies, SALSA and the much faster method GRASP‐Func yield similar correct classification of previously characterized proteins, providing a validated benchmark for the new method. In addition, we analyzed SG proteins using our SALSA and GRASP‐Func methods to predict function. Forty‐one SG proteins in the RPBB superfamily, nine SG proteins in the 6‐HG superfamily, and one SG protein in the CAL/G superfamily were successfully classified into one of the functional families in their respective superfamily by both methods. This improved, faster, validated computational method can yield more reliable predictions of function that can be used for a wide variety of applications by the community.
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Affiliation(s)
- Caitlyn L Mills
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts
| | - Rohan Garg
- College of Computer and Information Science, Northeastern University, Boston, Massachusetts
| | - Joslynn S Lee
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts
| | - Liang Tian
- Department of Mathematics, Northeastern University, Boston, Massachusetts
| | - Alexandru Suciu
- Department of Mathematics, Northeastern University, Boston, Massachusetts
| | - Gene D Cooperman
- College of Computer and Information Science, Northeastern University, Boston, Massachusetts
| | - Penny J Beuning
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts
| | - Mary Jo Ondrechen
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts
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Parasuram R, Mills CL, Wang Z, Somasundaram S, Beuning PJ, Ondrechen MJ. Local structure based method for prediction of the biochemical function of proteins: Applications to glycoside hydrolases. Methods 2016; 93:51-63. [DOI: 10.1016/j.ymeth.2015.11.010] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2015] [Revised: 11/05/2015] [Accepted: 11/09/2015] [Indexed: 01/07/2023] Open
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Mills CL, Beuning PJ, Ondrechen MJ. Biochemical functional predictions for protein structures of unknown or uncertain function. Comput Struct Biotechnol J 2015; 13:182-91. [PMID: 25848497 PMCID: PMC4372640 DOI: 10.1016/j.csbj.2015.02.003] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2014] [Revised: 02/06/2015] [Accepted: 02/11/2015] [Indexed: 01/07/2023] Open
Abstract
With the exponential growth in the determination of protein sequences and structures via genome sequencing and structural genomics efforts, there is a growing need for reliable computational methods to determine the biochemical function of these proteins. This paper reviews the efforts to address the challenge of annotating the function at the molecular level of uncharacterized proteins. While sequence- and three-dimensional-structure-based methods for protein function prediction have been reviewed previously, the recent trends in local structure-based methods have received less attention. These local structure-based methods are the primary focus of this review. Computational methods have been developed to predict the residues important for catalysis and the local spatial arrangements of these residues can be used to identify protein function. In addition, the combination of different types of methods can help obtain more information and better predictions of function for proteins of unknown function. Global initiatives, including the Enzyme Function Initiative (EFI), COMputational BRidges to EXperiments (COMBREX), and the Critical Assessment of Function Annotation (CAFA), are evaluating and testing the different approaches to predicting the function of proteins of unknown function. These initiatives and global collaborations will increase the capability and reliability of methods to predict biochemical function computationally and will add substantial value to the current volume of structural genomics data by reducing the number of absent or inaccurate functional annotations.
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Affiliation(s)
- Caitlyn L Mills
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, United States
| | - Penny J Beuning
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, United States
| | - Mary Jo Ondrechen
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, United States
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Wang Z, Yin P, Lee JS, Parasuram R, Somarowthu S, Ondrechen MJ. Protein function annotation with Structurally Aligned Local Sites of Activity (SALSAs). BMC Bioinformatics 2013; 14 Suppl 3:S13. [PMID: 23514271 PMCID: PMC3584854 DOI: 10.1186/1471-2105-14-s3-s13] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Background The prediction of biochemical function from the 3D structure of a protein has proved to be much more difficult than was originally foreseen. A reliable method to test the likelihood of putative annotations and to predict function from structure would add tremendous value to structural genomics data. We report on a new method, Structurally Aligned Local Sites of Activity (SALSA), for the prediction of biochemical function based on a local structural match at the predicted catalytic or binding site. Results Implementation of the SALSA method is described. For the structural genomics protein PY01515 (PDB ID 2aqw) from Plasmodium yoelii, it is shown that the putative annotation, Orotidine 5'-monophosphate decarboxylase (OMPDC), is most likely correct. SALSA analysis of YP_001304206.1 (PDB ID 3h3l), a putative sugar hydrolase from Parabacteroides distasonis, shows that its active site does not bear close resemblance to any previously characterized member of its superfamily, the Concanavalin A-like lectins/glucanases. It is noted that three residues in the active site of the thermophilic beta-1,4-xylanase from Nonomuraea flexuosa (PDB ID 1m4w), Y78, E87, and E176, overlap with POOL-predicted residues of similar type, Y168, D153, and E232, in YP_001304206.1. The substrate recognition regions of the two proteins are rather different, suggesting that YP_001304206.1 is a new functional type within the superfamily. A structural genomics protein from Mycobacterium avium (PDB ID 3q1t) has been reported to be an enoyl-CoA hydratase (ECH), but SALSA analysis shows a poor match between the predicted residues for the SG protein and those of known ECHs. A better local structural match is obtained with Anabaena beta-diketone hydrolase (ABDH), a known β-diketone hydrolase from Cyanobacterium anabaena (PDB ID 2j5s). This suggests that the reported ECH function of the SG protein is incorrect and that it is more likely a β-diketone hydrolase. Conclusions A local site match provides a more compelling function prediction than that obtainable from a simple 3D structure match. The present method can confirm putative annotations, identify misannotation, and in some cases suggest a more probable annotation.
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Affiliation(s)
- Zhouxi Wang
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA
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Volkamer A, Kuhn D, Rippmann F, Rarey M. Predicting enzymatic function from global binding site descriptors. Proteins 2012; 81:479-89. [DOI: 10.1002/prot.24205] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2012] [Revised: 09/21/2012] [Accepted: 10/11/2012] [Indexed: 11/09/2022]
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Somarowthu S, Ondrechen MJ. POOL server: machine learning application for functional site prediction in proteins. ACTA ACUST UNITED AC 2012; 28:2078-9. [PMID: 22661648 PMCID: PMC3400966 DOI: 10.1093/bioinformatics/bts321] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Summary: We present an automated web server for partial order optimum likelihood (POOL), a machine learning application that combines computed electrostatic and geometric information for high-performance prediction of catalytic residues from 3D structures. Input features consist of THEMATICS electrostatics data and pocket information from ConCavity. THEMATICS measures deviation from typical, sigmoidal titration behavior to identify functionally important residues and ConCavity identifies binding pockets by analyzing the surface geometry of protein structures. Both THEMATICS and ConCavity (structure only) do not require the query protein to have any sequence or structure similarity to other proteins. Hence, POOL is applicable to proteins with novel folds and engineered proteins. As an additional option for cases where sequence homologues are available, users can include evolutionary information from INTREPID for enhanced accuracy in site prediction. Availability: The web site is free and open to all users with no login requirements at http://www.pool.neu.edu. Contact:m.ondrechen@neu.edu Supplementary Information:Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Srinivas Somarowthu
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA
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RECENT ADVANCES ON STRUCTURAL BIOINFORMATICS, CELL MOTION SIMULATION, FUNCTIONAL MODULE IDENTIFICATION, COPY NUMBER VARIATION, AND PROTEASE SUBSTRATE PREDICTION AND SOME CRITICAL COMMENTS ON HMMER2. J Bioinform Comput Biol 2011. [DOI: 10.1142/s0219720011005380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Han GW, Ko J, Farr CL, Deller MC, Xu Q, Chiu HJ, Miller MD, Sefcikova J, Somarowthu S, Beuning PJ, Elsliger MA, Deacon AM, Godzik A, Lesley SA, Wilson IA, Ondrechen MJ. Crystal structure of a metal-dependent phosphoesterase (YP_910028.1) from Bifidobacterium adolescentis: Computational prediction and experimental validation of phosphoesterase activity. Proteins 2011; 79:2146-60. [PMID: 21538547 DOI: 10.1002/prot.23035] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2010] [Revised: 03/07/2011] [Accepted: 03/15/2011] [Indexed: 11/09/2022]
Abstract
The crystal structures of an unliganded and adenosine 5'-monophosphate (AMP) bound, metal-dependent phosphoesterase (YP_910028.1) from Bifidobacterium adolescentis are reported at 2.4 and 1.94 Å, respectively. Functional characterization of this enzyme was guided by computational analysis and then confirmed by experiment. The structure consists of a polymerase and histidinol phosphatase (PHP, Pfam: PF02811) domain with a second domain (residues 105-178) inserted in the middle of the PHP sequence. The insert domain functions in binding AMP, but the precise function and substrate specificity of this domain are unknown. Initial bioinformatics analyses yielded multiple potential functional leads, with most of them suggesting DNA polymerase or DNA replication activity. Phylogenetic analysis indicated a potential DNA polymerase function that was somewhat supported by global structural comparisons identifying the closest structural match to the alpha subunit of DNA polymerase III. However, several other functional predictions, including phosphoesterase, could not be excluded. Theoretical microscopic anomalous titration curve shapes, a computational method for the prediction of active sites from protein 3D structures, identified potential reactive residues in YP_910028.1. Further analysis of the predicted active site and local comparison with its closest structure matches strongly suggested phosphoesterase activity, which was confirmed experimentally. Primer extension assays on both normal and mismatched DNA show neither extension nor degradation and provide evidence that YP_910028.1 has neither DNA polymerase activity nor DNA-proofreading activity. These results suggest that many of the sequence neighbors previously annotated as having DNA polymerase activity may actually be misannotated.
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Affiliation(s)
- Gye Won Han
- Joint Center for Structural Genomics, Scripps Research Institute, La Jolla, California 92037, USA
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Somarowthu S, Yang H, Hildebrand DG, Ondrechen MJ. High-performance prediction of functional residues in proteins with machine learning and computed input features. Biopolymers 2011; 95:390-400. [DOI: 10.1002/bip.21589] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Zhao XM, Li Y, Li M, Chen L. Advances in genome informatics. J Bioinform Comput Biol 2010; 8 Suppl 1:v-viii. [PMID: 21155015 DOI: 10.1142/s0219720010005294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Affiliation(s)
- Xing-Ming Zhao
- Institute of Systems Biology, Shanghai University, Shanghai, P R China.
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