journal article·2019-06-18Open access

Prioritization of Drugs for Fungal Keratitis Eye Infections: An In-Silico Analysis

Punitha Thambidurai, Vinodhini Raja, Saranya Ashokapuram Selvam, Moorthy Kannaiyan, Gnanendra Shanmugam

Applied Sciences· Volume 9· Issue 12

Abstract

The fungal keratitis (FK) infections that cause cornea inflammations are more virulent than other bacterial keratitis infections and remain one of the most ethereal and challenging infections for ophthalmologists to diagnose and treat. Thus, the urgency in understanding the current perspectives of antifungal agents and their interactions with novel therapeutic targets and the identification of novel anti-fungal agents are at the frontline of studies in the pharmaceutical industry. In this study, DNA dependent RNA polymerase was modelled and virtually screened against eight antifungal agents, and it was found that Itraconazole (−22.0427 kJ/mol), Ketoconazole (−20.2194 kJ/mol), and Voriconazole (−12.6388 kJ/mol) exhibited better binding interactions. further, the structural and electronic properties of Itraconazole calculated through density functional theory studies revealed the sites of chemical reactivity that are vital in the compounds for possible interactions with RNA polymerase (RNAP). Hence, this study explores the binding efficacies of various anti-fungal agents through docking studies and their chemical entities, which might pave a significant path for the design of novel anti-fungal agents against hyalohyphomycetes causing keratitis.
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Research context

OpenAlex topics: Ocular Infections and Treatments · Antifungal resistance and susceptibility · Essential Oils and Antimicrobial Activity

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Microbiology, SAN International College of Arts and Science, Mavuthampathy Village, Navakkari, Coimbatore, Tamilnadu 641105, India

Department of Microbiology, Shri Sakthikailassh Women’s College, Military Road, Ammapet, Salem, Tamilnadu 636003, India

Department of Microbiology, Vivekanandha College of Arts and Sciences (W), Elayamplayam, Tiruchengode, Namakkal dist, Tamilnadu 637205, India

Microbial Genomics Lab, Department of Biotechnology, College of Life and Applied Sciences, Yeungnam University, Gyeongbuk, Gyeongsan 38541, Korea

References (48)

Show source-provided references
1. Current thoughts in fungal keratitis: Diagnosis and treatment10.1007/s12281-013-0150-1 ↗
2. Risk factors and clinical outcomes between fungal and bacterial keratitis: A comparative study
3. Aetiology of suppurative corneal ulcers in Ghana and south India, and epidemiology of fungal keratitis10.1136/bjo.86.11.1211 ↗
4. Microbial keratitis in South India: Influence of risk factors, climate, and geographical variation10.1080/09286580601001347 ↗
5. Spectrum of fungal keratitis in North India10.1097/01.ico.0000126435.25751.20 ↗
6. Review of epidemiological features, microbiological diagnosis and treatment outcome of microbial keratitis: Experience of over a decade10.4103/0301-4738.53051 ↗
7. Current perspectives on ophthalmic mycoses10.1128/CMR.16.4.730-797.2003 ↗
8. Epidemiology and aetiological diagnosis of corneal ulceration in Madurai, south India10.1136/bjo.81.11.965 ↗
9. Spectrum of oculomycosis in South India10.1111/j.1755-3768.1991.tb02053.x ↗
10. Varga, J., and Samson, R. (2008). Aspergillus species in human keratomycosis. Aspergillus in the Genomic Era, Wageningen Academic Publishers.10.3920/978-90-8686-635-9 ↗
11. Case of keratitis caused by Aspergillus tamari10.1128/JCM.00920-07 ↗
12. Mycotic keratitis due to Aspergillus nomius10.1128/JCM.01051-09 ↗
13. Infectious keratitis caused by Aspergillus tubingensis10.1097/ICO.0b013e3181967098 ↗
14. Keratitis caused by the recently described new species Aspergillus brasiliensis: Two case reports10.1186/1752-1947-4-68 ↗
15. Itraconazole resistance in Aspergillus fumigatus10.1128/AAC.41.6.1364 ↗
16. Azole resistance in Aspergillus fumigatus: Can we retain the clinical use of mold-active antifungal azoles?10.1093/cid/civ885 ↗
17. Spectrum of fungal keratitis at Wills Eye Hospital, Philadelphia, Pennsylvania10.1097/00003226-200005000-00010 ↗
18. Inhibition of RNA synthesis as a therapeutic strategy against Aspergillus and Fusarium: Demonstration of in vitro synergy between rifabutin and amphotericin B10.1128/AAC.42.3.509 ↗
19. Combined effect of amphotericin B and rifampin on Candida species10.1128/AAC.17.3.484 ↗
20. Combined in vitro effect of amphotericin B and rifampin on Cryptococcus neoformans10.1128/AAC.19.1.196 ↗
21. Effect of amphotericin B and rifampin against Coccidioides immitis in vitro and in vivo10.1128/AAC.9.3.406 ↗
22. Effects of rifamycin derivatives, alone and in combination with amphotericin B, against Histoplasma capsulatum10.1128/AAC.5.1.16 ↗
23. The role of general initiation factors in transcription by RNA polymerase II10.1016/0968-0004(96)10050-5 ↗
24. Hester, R.E., and Harrison, R.M. (2015). The pharmaceutical industry and the future of drug development. Pharmaceuticals in the Environment, The Royal Society of Chemistry.10.1039/9781782622345 ↗
25. Homology modeling of wild-type, D516V, and H526L Mycobacterium tuberculosis RNA polymerase and their molecular docking study with inhibitors10.1080/07391102.2008.10507185 ↗
26. Twilight zone of protein sequence alignments10.1093/protein/12.2.85 ↗
27. Assessment of protein models with three-dimensional profiles10.1038/356083a0 ↗
28. Pauling, L. (1948). The Nature of the Chemical Bond, Cornell University Pr.
29. Modeling, docking, simulation, and inhibitory activity of the benzimidazole analogue against β-tubulin protein from Brugia malayi for treating lymphatic filariasis10.1007/s00044-011-9763-5 ↗
30. Shanmugam, G., Lee, S.K., and Jeon, J. (2018). Identification of potential nematicidal compounds against the pine wood nematode, Bursaphelenchus xylophilus through an in silico approach. Molecules, 23.10.3390/molecules23071828 ↗
31. Comparative DFT study of phytochemical constituents of the fruits of Cucumis trigonus Roxb. and Cucumis sativus Linn10.1155/2014/623235 ↗
32. NCBI Reference sequence (RefSeq): A curated non-redundant sequence database of genomes, transcripts and proteins10.1093/nar/gki025 ↗
33. Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N., and Bourne, P.E. (2006). The Protein Data Bank, 1999–, International Tables for Crystallography Volume F: Crystallography of Biological Macromolecules, Springer.10.1107/97809553602060000722 ↗
34. Schizosacharomyces pombe RNA polymerase II at 3.6-Å resolution10.1073/pnas.0903361106 ↗
35. Comparative protein modelling by satisfaction of spatial restraints10.1006/jmbi.1993.1626 ↗
36. Modeller: Generation and refinement of homology-based protein structure models10.1016/S0076-6879(03)74020-8 ↗
37. The GROMOS biomolecular simulation program package10.1021/jp984217f ↗
38. Swiss-PDB viewer (deep view)10.1093/bib/2.2.195 ↗
39. PROCHECK: A program to check the stereochemical quality of protein structures10.1107/S0021889892009944 ↗
40. VERIFY3D: Assessment of protein models with three-dimensional profiles10.1016/S0076-6879(97)77022-8 ↗
41. ERRAT: An empirical atom-based method for validating protein structures10.1002/pro.5560020916 ↗
42. DoGSiteScorer: A web server for automatic binding site prediction, analysis and druggability assessment10.1093/bioinformatics/bts310 ↗
43. PubChem substance and compound databases10.1093/nar/gkv951 ↗
44. A fast flexible docking method using an incremental construction algorithm10.1006/jmbi.1996.0477 ↗
45. Identification of potent inhibitors for Salmonella typhimurium quorum sensing via virtual screening and pharmacophore modeling10.2174/1386207311301010003 ↗
46. Molecular complexes at a glance: Automated generation of two-dimensional complex diagrams10.1093/bioinformatics/btl150 ↗
47. A novel gene, CBP1, encoding a putative extracellular chitin-binding protein, may play an important role in the hydrophobic surface sensing of Magnaporthe grisea during appressorium differentiation10.1094/MPMI.2002.15.5.437 ↗
48. Frisch, M., Trucks, G., Schlegel, H., Scuseria, G., Robb, M., Cheeseman, J., Scalmani, G., Barone, V., Mennucci, B., and Petersson, G. (2009). Gaussian 09, Revision A, Gaussian, Inc.