YENİ TETRAHİDRONAFTALEN-BENZİMİDAZOL TÜREVİ BİLEŞİKLERİN MOLEKÜLER DOKİNG ÇALIŞMALARI VE ONLARIN ANTİ-MRSA AKTİVİTELERİNİN KARŞILAŞTIRILMASI

Abstract

Amaç: Metisiline dirençli S. aureus (MRSA), birçok antibiyotiğe karşı dirençli olup, özellikle hastane ortamında mortaliteye neden olmaktadır. Önceden sentezlenmiş olan retinoidal bileşiklerin MRSA üzerindeki inhibitor aktivitesini incelemek adına bu bileşiklerin QSAR özellikleri hesaplanmış ve MRSA Pirüvat kinaz (PK) ile doking çalışmaları gerçekleştirilmiştir.

        Gereç ve Yöntem: Başlangıçta, ligand hazırlama gerçekleştirilmiştir. Bileşiklerin optimizasyonu için Hyperchem Professional kullanılmış, bu yazılımda Molecular Mechanics Force Field (MMFF) ve semi-empirik metod uygulanmıştır. Ligand dosyalarını pdb formatına dönüştürdükten sonra, yük ve torsiyon özellikleri AutoDockTools 1.5.6 ile eklenmiştir. MRSA pirüvat kinaz makromolekül dosyası (PDB ID: 3T07) protein data bank’tan alınmıştır. Bağlanma için uygun zincir UCSF Chimera ile belirlenmiştir. Makromoleküle polar hidrojenler ve Gasteiger yükleri AutoDockTools 1.5.6 ile eklenmiştir. Ligandın proteine bağlanma cebi, protein data bank’taki protein-ligand kompleksinden yola çıkılarak tespit edilmiştir. Retinoidal bileşiklerin MİK değerleri için Ates-Alagoz ve ark. tarafından yapılmış olan çalışmaya başvurulmuştur.

         Sonuç ve Tartışma: 1, 4, 5, 6, 7 numaralı bileşikler PK inhibitor aktiviteleri en yüksek adaylar olarak seçilmiştir. Bu bileşikler, nispeten düşük olan MİK değerlerine ek olarak önceden bildirilen PK inhibitörü aday bileşiklere benzer bağlanma şekilleri göstermiştir. PK’nın iki monomerik ünitesinde yer alan His365 ve Ile361 ile etkileşme, bu üniteler arasında bir köprü oluşturmaktadır. Yapılan QSAR hesaplamasına göre, en aktif olan bileşiklerde 1010 Å3’dan düşük moleküler hacim değerleri görülmektedir. Buna ek olarak, log P’nin aktivite üzerinde bir etkiye sahip olmadığı görülmüştür. Bu bağlanma şekli ve etkileşimler, söz konusu bileşiklerin MRSA Pirüvat kinaz’daki umut verici inhibitor aktivitelerinin nedeni olabilir.

Keywords

• Benzimidazol,doking,biyoinformatik,antibiyotikler,QSAR

MOLECULAR DOCKING STUDIES OF SOME TETRAHYDRONAPHTALENE-BENZIMIDAZOLE DERIVATIVES AND CORRELATION WITH THEIR CORRESPONDING ANTI-MRSA ACTIVITIES

Abstract

        Objective: Methicillin- resistant S. aureus (MRSA) is a type of bacteria which is resistant to various types of antibiotics and causes mortality in hospital environment and community. To further investigate the inhibition activity of previously synthesized retinoidal compounds against MRSA, docking studies of these compounds with MRSA pyruvate kinase (PK) were made.

        Material and Method: As a first step, ligand preparation procedure has been made. For optimization of compounds, Hyperchem Professional was used. Molecular Mechanics Force Field (MMFF) and semi-empirical methods have been implemented in this program. After converting the ligands to pdb files, charges and torsions were added via AutoDockTools 1.5.6. Macromolecule file for MRSA Pyruvate kinase (PDB ID:3T07) was procured from protein data bank. Appropriate chain for binding was chosen via UCSF Chimera. Polar hydrogens and Gasteiger charges were added to macromolecule via AutoDockTools 1.5.6. Gridbox has been predicted by protein- ligand complex which is currently present in protein data bank and prepared via same software.  Docking process was made via AutoDock Vina. For MIC values of retinoidal compounds, previous study by Ates-Alagoz et al. has been used. In addition, some QSAR properties were calculated via Hyperchem Professional and were also interpreted.

        Result and Discussion: Compounds 1, 4, 5, 6, 7 were selected for their PK inhibitor activities. Addition to their relatively lower MIC values, they also show similar binding modes to previously presented PK inhibitor candidates. Binding of compounds with His365 and Ile361 in both monomeric units of PK, creates a bridge that links these units. In terms of QSAR, molecular volume below 1010 Å3 is favorable. Moreover, log P does not have an impact on activity. This binding mode and interactions with aminoacid residues may be the cause of their promising inhibition activity against MRSA Pyruvate kinase.

Keywords

• benzimidazoles,docking,bioinformatics,antibiotics,QSAR

References

1. El Sayed, M.T., Sabry, N.M., A. Hamdy N., Voronkov, A., Ogungbe, I.V., Balakin, K. and Abdel-Aziz, M.S. (2018). Synthesis, Anti-Methicillin-resistant S. aureus (MRSA) Evaluation, Quantitative Structure-Activity Relationship and Molecular Modeling Studies of Some Novel Bis-indoles as Prospective MRSA Pyruvate Kinase Inhibitors. Letters in Drug Design & Discovery, 15, 336.
2. S. Lee A., Lencastre, H., Garau, J., Kluytmans, J., Malhotra-Kumar, S. Peschel A., Harbarth, S. (2018). Methicillin-resistant Staphylococcus aureus. Nature Reviews Disease Primers, 4, Article number 18033.
3. Valentini, G. (2000). The allosteric regulation of pyruvate kinase: a site-directed mutagenesis study. The Journal of Biological Chemistry, 275, 18145–18152.
4. Zoraghi, R., See, R.H., Gong, H., Lian, T., Swayze, R., Finlay, B.B., Brunham, R.C., McMaster, W.R., Reiner, N.E. (2010). Functional analysis, overexpression, and kinetic characterization of pyruvate kinase from methicillin-resistant Staphylococcus aureus. Biochemistry, 49, 7733–7747.
5. Muñoz, M.E., Ponce, E. (2003). Pyruvate kinase: current status of regulatory and functional properties. Comparative Biochemistry and Physiology B, 135, 197–218.
6. Emmerling, M., Bailey, J. E., Sauer, U. (1999). Glucose catabolism of Escherichia coli strains with increased activity and altered regulation of key glycolytic enzymes. Metabolic Engineering, 1, 117–127.
7. Fry, B., Zhu, T., Domach, M.M., Koepsel, R.R, Phalakornkule, C., Ataai, M.M. (2000). Characterization of growth and acid formation in a Bacillus subtilis pyruvate kinase mutant. Applied and Environmental Microbiology, 66, 4045–4049.
8. Siddiquee, K.A.Z., Arauzo-Bravo, M., Shimizu, K. (2004). Metabolic flux analysis of pykF gene knockout Escherichia coli based on 13C-labeling experiments together with measurements of enzyme activities and intracellular metabolite concentrations. Applied Microbiology and Biotechnology, 63, 407–417.

9. Zhai, Z., An, H., Wang, G., Luo, Y., Hao, Y. (2015). Functional role of pyruvate kinase from Lactobacillus bulgaricus in acid tolerance and identification of its transcription factor by bacterial one-hybrid. Scientific Reports, 5, 17024.
10. Ates-Alagoz, Z., Yildiz, S., Buyukbingol, E. (2007). Antimicrobial Activities of Some Tetrahydronaphthalene-Benzimidazole Derivatives. Chemotherapy, 53, 110-113.
11. HyperChem (TM) Professional 7.51, Hypercube, Inc., 1115 NW 4th Street, Gainesville, Florida 32601, USA.
12. Hanwell, M.D., Curtis, D.E., Lonie, D.C., Vandermeersch, T., Zurek, E. and Hutchison, G.R. (2012). “Avogadro: An advanced semantic chemical editor, visualization, and analysis platform”. Journal of Cheminformatics, 4, 17.
13. AutoDockTools, the free GUI for AutoDock. [http://autodock.scripps.edu/ resources/adt].
14. Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N., Bourne, P.E. (2000). The Protein Data Bank Nucleic Acids Research, 28, 235-242.
15. Zoraghi, R., Worrall, L., Raymond, H. S., Strangman, W., Popplewell, W. L., Gong, H., Samaai, T., Swayze Richard, D., Kaur, S., Vuckovic, M., Finlay, B.B., Brunham, R.C., McMaster William, R., Davies-Coleman Michael, T., Strynadka Natalie, C., Andersen, R.J., Neil E. Reiner. (2011). Methicillin-resistant Staphylococcus aureus (MRSA) Pyruvate Kinase as a Target for Bis-indole Alkaloids with Antibacterial Activities. The Journal of Biological Chemistry, 286:44716-44725.
16. Pettersen, E.F., Goddard, T.D., Huang, C.C., Couch, G.S., Greenblatt, D.M., Meng, E.C., Ferrin, T.E. (2004). UCSF Chimera--a visualization system for exploratory research and analysis. Journal of Computational Chemistry, 25(13), 1605-1612.
17. Trott, O., Olson, A.J. (2010). AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading. Journal of Computational Chemistry, 31, 455-461.
18. Dassault Systèmes BIOVIA, Discovery Studio Visualizer v17.2.0.16349, San Diego: Dassault Systèmes, 2017.