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Research Paper

In silico investigation of riboswitches in fungi: structural and dynamical insights into TPP riboswitches in Aspergillus oryzae

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 90-103 | Received 29 Jul 2021, Accepted 02 Dec 2021, Published online: 06 Jan 2022

References

  • Breaker RR. Riboswitches and the RNA world. Cold Spring Harb Perspect Biol. 2012;4(2): a003566.
  • Serganov A, Nudler E. A decade of riboswitches. Cell. 2013;152(1–2): 17–24.
  • Lin JC, Thirumalai D. Gene regulation by riboswitches with and without negative feedback loop. Biophys J Internet]. 2012;103(11): 2320–2330.
  • Mellin JR, Cossart P. Unexpected versatility in bacterial riboswitches. Trends Genet Internet].2015;31(3): 150–156.
  • Antunes D, Jorge NAN, Garcia de Souza Costa M, et al. Unraveling RNA dynamical behavior of TPP riboswitches: a comparison between Escherichia coli and Arabidopsis thaliana. Sci Rep. 2019;9(1): 1–13.
  • Antunes D, Jorge NAN, Caffarena ER, et al. Using RNA sequence and structure for the prediction of riboswitch aptamer: a comprehensive review of available software and tools. Front Genet. 2018;8(JAN): 1–16.
  • Winkler W, Nahvi A, Breaker RR. Thiamine derivatives bind messenger RNAs directly to regulate bacterial gene expression. Nature. 2002;419(6910): 952–956.
  • Wakchaure PD, Ganguly B. Molecular level insights into the inhibition of gene expression by thiamine pyrophosphate (TPP) analogs for TPP riboswitch: a well-tempered metadynamics simulations study. J Mol Graph Model Internet]. 2021;104: 107849.
  • Machtel P, Bąkowska-Żywicka K, Żywicki M. Emerging applications of riboswitches – from antibacterial targets to molecular tools. J Appl Genet. 2016;57(4): 531–541.
  • Bastet L, Turcotte P, Wade JT, et al. Maestro of regulation: riboswitches orchestrate gene expression at the levels of translation, transcription and mRNA decay. RNA Biol. 2018;15(6): 679–682.
  • Serganov A, Polonskaia A, Breaker RR, et al. Structural basis for gene regulation by a thiamine pyrophosphate-sensing riboswitch. Nature. 2006;441(7097): 1167–1171.
  • Mukherjee S, Retwitzer MD, Barash D, et al.Phylogenomic and comparative analysis of the distribution and regulatory patterns of TPP riboswitches in fungi.Sci Rep Internet. 2018;8(1): 1–13.
  • Moldovan MA, Petrova SA, Gelfand MS. Comparative genomic analysis of fungal TPP-riboswitches. Fungal Genet Biol Internet]. 2018;114(6): 34–41.
  • Sudarsan N, Cohen-Chalamish S, Nakamura S, et al. Thiamine pyrophosphate riboswitches are targets for the antimicrobial compound pyrithiamine. Chem Biol. 2005;12(12): 34–41.
  • Kawasaki T, Sanemori H, Egi Y, et al. Biochemical studies on pyrithiamine-resistant mutants of Escherichia coli K12. J Biochem. 1976;79(5): 1035–1042.
  • Romagnoli G, Luttik MAH, Kötter P, et al. Substrate specificity of thiamine pyrophosphate-dependent 2-oxo-acid decarboxylases in Saccharomyces cerevisiae. Appl Environ Microbiol. 2012;78(21): 7538–7548.
  • Eram MS, Ma K. Decarboxylation of pyruvate to acetaldehyde for ethanol production by hyperthermophiles. Biomolecules. 2013;3(4): 578–596.
  • Wilkinson HC, Dalby PA. The Two-Species Model of transketolase explains donor substrate-binding, inhibition and heat-activation. Sci Rep Internet]. 2020;10(1): 1–10.
  • Wilkinson HC, Dalby PA. Novel insights into transketolase activation by cofactor binding identifies two native species subpopulations. Sci Rep Internet]. 2019;9(1): 1–13.
  • Regulski EE, Breaker RR. In-line probing analysis of riboswitches. Methods Mol Biol. 2008;419(5): 53–67.
  • Kesherwani M, Kutumbarao NHV, Velmurugan D. Conformational dynamics of thim riboswitch to understand the gene regulation mechanism using markov state modeling and the residual fluctuation network approach. J Chem Inf Model. 2018;58(8): 1638–1651.
  • Eriksson HE. Implementation of thiamine pyrophosphate (TPP) riboswitches as synthetic biosensors and regulatory tools in cyanobacteria. 2018. Available from: http://www.teknat.uu.se/student
  • Rodrigues ML, Albuquerque PC. Searching for a change: the need for increased support for public health and research on fungal diseases. PLoS Negl Trop Dis. 2018;12(6): 1–5.
  • Infections GAF for F. GAFFI [Internet]. Available from: https://www.gaffi.org/antifungal-drug-maps
  • Lahmer T, Kriescher S, Herner A, et al. Invasive pulmonary aspergillosis in critically ill patients with severe COVID-19 pneumonia: results from the prospective AspCOVID-19 study. PLoS One Internet]. 2021;16(3): 1–16.
  • Friedman DZP, Schwartz IS. Emerging fungal infections: new patients, new patterns, and new pathogens. J Fungi. 2019;5(3): 3.
  • Forsberg K, Woodworth K, Walters M, et al. Candida auris: the recent emergence of a multidrug-resistant fungal pathogen. Med Mycol. 2019;57(1): 1–12.
  • Spanamberg A, Ravazzolo AP, Denardi LB, et al. Antifungal susceptibility profile of Aspergillus fumigatus isolates from avian lungs. Pesqui Vet Bras. 2020;40(2): 102–106.
  • Wiederhold NP. Antifungal resistance: current trends and future strategies to combat. Infect Drug Resist. 2017;10: 249–259.
  • Panchal V, Brenk R. Riboswitches as drug targets for antibiotics. Antibiotics. 2021;10(1): 1–22.
  • Kubodera T, Watanabe M, Yoshiuchi K, et al. Thiamine-regulated gene expression of Aspergillus oryzae thiA requires splicing of the intron containing a riboswitch-like domain in the 5′-UTR. FEBS Lett. 2003;555(3): 516–520.
  • Machida M, Yamada O, Gomi K. Genomics of aspergillus oryzae: learning from the history of koji mold and exploration of its future. DNA Res. 2008;15(4): 173–183.
  • Eran E, Zohar Y, Wallach I. SimTree: a Tool for Computing Similarity Between RNA Secondary Structures [Internet]. 2005. Available from: http://bioinfo.cs.technion.ac.il/SimTree
  • Chen L, Cressina E, Dixon N, et al. Probing riboswitch–ligand interactions using thiamine pyrophosphate analogues. Org Biomol Chem. 2012;10(30): 5924–5931.
  • Chen J, Wang X, Pang L, et al. Effect of mutations on binding of ligands to guanine riboswitch probed by free energy perturbation and molecular dynamics simulations. Nucleic Acids Res. 2019;47(13): 6618–6631.
  • Ganai SA, Abdullah E, Rashid R, et al. Combinatorial In Silico Strategy towards Identifying Potential Hotspots during Inhibition of Structurally Identical HDAC1 and HDAC2 Enzymes for Effective Chemotherapy against Neurological Disorders. Front Mol Neurosci Internet]. 2017;10(November): 1–17
  • Forouzesh N, Mishra N. An effective MM/GBSA protocol for absolute binding free energy calculations: a case study on SARS-CoV-2 spike protein and the human ACE2 receptor. Molecules. 2021;26(8): 8.
  • Adasme-Carreño F, Muñoz-Gutierrez C, Caballero J, et al. Performance of the MM/GBSA scoring using a binding site hydrogen bond network-based frame selection: the protein kinase case. Phys Chem Chem Phys. 2014;16(27): 14047–14058.
  • Padhi S, Pradhan M, Bung N, et al. TPP riboswitch aptamer: role of Mg 2+ ions, ligand unbinding, and allostery. J Mol Graph Model Internet]. 2019;88: 282–291.
  • Ryde SG, U. The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Informa. 2015;10(5): 449–461.
  • Wang E, Sun H, Wang J, et al. End-Point Binding Free Energy Calculation with MM/PBSA and MM/GBSA: strategies and Applications in Drug Design. Chem Rev. 2019;119(16): 9478–9508.
  • Brieg M, Setzler J, Albert S, et al. Generalized Born implicit solvent models for small molecule hydration free energies. Phys Chem Chem Phys. 2017;19(2): 1677–1685.
  • Zeller F, Zacharias M. Evaluation of generalized born model accuracy for absolute binding free energy calculations. J Phys Chem B. 2014;118(27): 7467–7474.
  • Forrey C, Douglas JF, Gilson MK. The fundamental role of flexibility on the strength of molecular binding. Soft Matter. 2012;8(23): 6385–6392.
  • Donovan PD, Holland LM, Lombardi L, et al. TPP riboswitch-dependent regulation of an ancient thiamin transporter in Candida. PLoS Genet. 2018;14(5): 1–19.
  • Williams CJ, Headd JJ, Moriarty NW, et al. MolProbity: more and better reference data for improved all-atom structure validation. Protein Sci. 2018;27(1): 293–315.
  • Chen VB, Arendall WB, Headd JJ, et al. MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallogr Sect D Biol Crystallogr. 2010;66(1): 12–21.
  • Chou F-C, Nathaniel Echols TCT, Das R. RNA Structure Refinement using the ERRASER-Phenix pipeline. Methods Mol Biol. 2016;1320: 269–282.
  • Zgarbová M, Otyepka M, Šponer J, et al. Refinement of the Cornell Nucleic acids force field based on reference quantum chemical calculations of glycosidic torsion profiles. J Chem Theory Comput. 2011;7(9): 2886–2902.
  • Cornell WD, Cieplak P, Bayly CI, et al. A Second Generation Force Field for the Simulation of Proteins, Nucleic Acids, and Organic Molecules. J Am Chem Soc Internet]. 1996;118(9): 2309. Available from: http://pubs.acs.org/doi/abs/10.1021/ja955032e
  • Kemena C, Bussotti G, Capriotti E, et al. Using tertiary structure for the computation of highly accurate multiple RNA alignments with the SARA-Coffee package. Bioinformatics. 2013;29(9): 1112–1119.
  • Darty K, Alain Denise YP, Ponty Y. VARNA: interactive drawing and editing of the RNA secondary structures. Bioinforma Appl Note. 2009;25(15): 1974–1975
  • Rother M, Milanowska K, Puton T, et al. ModeRNA server: an online tool for modeling RNA 3D structures. Struct Bioinforma. 2011;27(17): 2441–2442
  • Ra L, Mb S. LigPlot+: multiple ligand-protein interaction diagrams for drug discovery. J Chem Inf Model. 2011;51(10): 2778–2786.
  • Pettersen EF, Goddard TD, Huang CC, et al. UCSF Chimera — a Visualization System for Exploratory Research and Analysis. 2004.
  • Case DA, Belfon K, Ben-Shalom IY, et al., . . 2020. AMBER 2020. University of California, San Francisco.
  • Maier JA, Martinez C, Kasavajhala K, et al. ff14SB: improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB. J Chem Theory Comput. 2015;11(8): 3696–3713.
  • Wang J, Wang W, Kollman PA, et al. Automatic atom type and bond type perception in molecular mechanical calculations. J Mol Graph Model. 2006;25(2): 247–260.
  • Mark P, Nilsson L. Structure and Dynamics of the TIP3P, SPC, and SPC/E Water Models at 298 K. J Phys Chem A Internet]. 2001;105(43): 9954–9960.
  • Berendsen HJC, Postma JPM, van Gunsteren WF, et al. Molecular dynamics with coupling to an external bath. J Chem Phys. 1984;81(8): 3684–3690.
  • Abraham MJ, Murtola T, Schulz R, et al. Gromacs: high performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX. 2015;1-2(2): 19–25.
  • Bottaro S, Bussi G, Pinamonti G, et al. Barnaba: software for analysis of nucleic acid structures and trajectories. Rna. 2019;25(2): 219–231.
  • Rohart F, Eslami A, Matigian N, et al. MINT: a multivariate integrative method to identify reproducible molecular signatures across independent experiments and platforms. BMC Bioinformatics. 2017;18(1): 1–13.