Abstract
The fuzzy oil drop model was applied to analyze the structure of macromomycin, the apoprotein of the antitumor antibiotic auromomycin, revealing the differentiation of β-structural fragments present in β-sandwich. The seven-stranded antiparallel β-barrel and two antiparallel β-sheet ribbons represent the highly ordered geometry of the structure. However, participation in hydrophobic core formation appears different. The structure of the complete domain represents the status of the irregular hydrophobic core; however, some β-structural fragments appear to represent the hydrophobicity density distribution accordant with the idealized distribution of hydrophobicity as expected using the fuzzy oil drop model. Four β-structural fragments generating one common layer appear to be unstable in respect to the general structure of the hydrophobic core. This area is expected to be more flexible than other parts of the molecule. The protein binds the ligand – chromophore, two 2-methyl-2,4-pentanediol – in a well-defined cleft. The presence of this cleft makes the general structure of the hydrophobic core irregular (as it may be interpreted using the fuzzy oil drop model). Two short loops generated by two SS bonds fit very well to the general distribution of hydrophobicity density as expected for the model. No information about the potential amyloidogenic character of this protein is given in the literature; however, the specificity of the hydrophobicity distribution profile is found to be highly similar to the one observed in transthyretin (Banach M, Konieczny L, Roterman I. The fuzzy oil drop model, based on hydrophobicity density distribution, generalizes the influence of water environment on protein structure and function. J Theor Biol 2014;359:6–17), suggesting a possible tendency to turn to the amyloid form. A detailed analysis of macromomycin will be given, and a comparable analysis with other proteins of β-sandwich or β-barrel will be presented.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: None declared.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
References
1. Banach M, Konieczny L, Roterman I. The fuzzy oil drop model, based on hydrophobicity density distribution, generalizes the influence of water environment on protein structure and function. J Theor Biol 2014;359:6–17.10.1016/j.jtbi.2014.05.007Search in Google Scholar PubMed
2. Kalinowska B, Banach M, Konieczny L, Roterman I. Application of divergence entropy to characterize the structure of the hydrophobic core in DNA interacting proteins. Entropy 2015;17: 1477–507.10.3390/e17031477Search in Google Scholar
3. Van Roey P, Beerman TA. Crystal structure analysis of auromomycin apoprotein (macromomycin) shows importance of protein side chains to chromophore binding selectivity. Proc Natl Acad Sci USA 1989;86:6587–91.10.1073/pnas.86.17.6587Search in Google Scholar PubMed PubMed Central
4. Banach M, Prymula K, Jurkowski W, Konieczny L. Fuzzy oil drop model to interpret the structure of antifreeze proteins and their mutants. J Mol Mod 2012;18:229–37.10.1007/s00894-011-1033-4Search in Google Scholar PubMed PubMed Central
5. Roterman I, Konieczny L, Jurkowski W, Prymula K, Banach M. Two-intermediate model to characterize the structure of fast-folding proteins. J Theor Biol 2011;283:60–70.10.1016/j.jtbi.2011.05.027Search in Google Scholar PubMed
6. Banach M, Konieczny L, Roterman I. Can the structure of hydrophobic core determine the complexation site? In: Roterman-Konieczna I, editor. Identification of ligand binding site and protein-protein interaction area. Dordrecht: Springer, 2013: 41–54.Search in Google Scholar
7. Banach M, Konieczny L, Roterman I. Use of the “fuzzy oil drop” model to identify the complexation area in protein homodimers. In: Roterman-Konieczna I, editor. Protein folding in silico. Oxford: Woodhead Publishing, 2012:95–122.Search in Google Scholar
8. Prymula K, Jadczyk T, Roterman I. Catalytic residues in hydrolases: analysis of methods designer for ligand-binding site in proteins J Comp Aid Mol Des 2011;25:117–33.10.1007/s10822-010-9402-0Search in Google Scholar PubMed PubMed Central
9. Kalinowska B, Banach M, Konieczny L, Marchewka D, Roterman I. Intrinsically disordered proteins-relation to general model expressing the active role of the water environment. Adv Protein Chem Struct Biol 2014;94:315–46.10.1016/B978-0-12-800168-4.00008-1Search in Google Scholar PubMed
10. Kalinowska B, Banach M, Konieczny L, Roterman I. Divergence entropy to characterise the structure of hydrophobic core in proteins. Entropy 2015;17:1477–507.10.3390/e17031477Search in Google Scholar
11. Banach M, Prudhomme N, Carpentier M, Duprat E, Papandreou N, Kalinowska B, et al. Contribution to the prediction of the fold code: application to immunoglobulin and flavodoxin cases. PLoS One 2015;10:e0125098.10.1371/journal.pone.0125098Search in Google Scholar PubMed PubMed Central
12. Roterman-Konieczna I, editor. Protein folding in silico: protein folding versus protein structure prediction. Oxford: Woodhead Publishing (currently Elsevier), 2012.10.1533/9781908818256Search in Google Scholar
13. Levitt MA. A simplified representation of protein conformations for rapid simulation of protein holding. J Mol Biol 1976;104: 59–107.10.1016/0022-2836(76)90004-8Search in Google Scholar
14. Kullback S, Leibler RA. On information and sufficiency. Ann Math Stat 1951;22:79–86.10.1214/aoms/1177729694Search in Google Scholar
15. Banach M, Konieczny L, Roterman I. Ligand binding site recognition. In: Roterman-Konieczna I, editor. Protein folding in silico. Oxford: Woodhead Publishing, 2012:78–94.Search in Google Scholar
16. Laskowski RA. Enhancing the functional annotation of PDB structures in PDBsum using key figures extracted from the literature. Bioinformatics 2007;23:1824–7.10.1093/bioinformatics/btm085Search in Google Scholar
17. Das P, Kapoor D, Halloran KT, Zhou R, Matthews CR. Interplay between drying and stability of a TIM barrel protein: a combined simulation-experimental study. J Am Chem Soc 2013;135: 1882–90.10.1021/ja310544tSearch in Google Scholar
18. Galzitskaya OV, Ivankov DN, Finkelstein AV. Folding nuclei in proteins. FEBS Lett 2001;489:113–8.10.1016/S0014-5793(01)02092-0Search in Google Scholar
©2015 by De Gruyter
