IN SILICO ANALYSIS AND MOLECULAR DOCKING OF CURCUMIN ANALOGS AND ANTIFUNGAL COMPOUNDS AGAINST CRITICAL PROTEINS OF ASPERGILLUS SPECIES: A COMPARATIVE INVESTIGATION
Main Article Content
Keywords
Aspergillus, Curcumin analogs, Molecular docking, Virtual screening, ADMET
Abstract
Aspergillosis, primarily caused by Aspergillus fumigatus, is a fungal infection that affects immunocompromised patients. With the increasing resistance to antifungal azoles caused by their overuse, there is a need for new therapies. This study focused on identifying key proteins that play a critical role in medication resistance and infection propagation in Aspergillus, with the aim of discovering new treatments. Six essential proteins have been identified in Aspergillus following a comprehensive literature review. These proteins comprise Cyp51A and Cyp51B enzymes, as well as MDR1-4 efflux pumps. In silico homology modeling and molecular docking analyses were performed using SWISS-MODEL and Autodock Vina in PyRx to estimate the inhibitory activity of candidate drugs against these proteins. These compounds were also tested for toxicity using the ProTox-II and pkCSM servers. Drug-likeness and ADME properties were assessed using the SwissADME server. The prediction of the PASS and Molinspiration webservers determined the pharmacological and biological activities of the compounds. The three ligands, pramiconazole, curcumin difluorinated (CDF), and curcumin, exhibited significant binding affinity to target proteins, indicating their potential to inhibit the overexpression of Aspergillus target protein genes. These compounds have demonstrated superior medicinal properties and lower toxicity compared to standard drugs used against Aspergillus. In conclusion, through molecular docking and in silico screening, pramiconazole, CDF, and curcumin have shown improved pharmacological properties compared to current treatments for aspergillosis. These compounds hold promise as alternative treatments that could potentially overcome antifungal resistance.
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[11] Fisher MC, Alastruey-Izquierdo A, Berman J, Bicanic T, Bignell EM, Bowyer P, et al. Tackling the emerging threat of antifungal resistance to human health. Nature Reviews Microbiology 2022;20:557-71.
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[15] Zhen C, Lu H, Jiang Y. Novel Promising Antifungal Target Proteins for Conquering Invasive Fungal Infections. Frontiers in Microbiology 2022;13:911322.
[16] Menezes RdP, Bessa MAdS, Siqueira CdP, Teixeira SC, Ferro EAV, Martins MM, et al. Antimicrobial, Antivirulence, and Antiparasitic Potential of Capsicum chinense Jacq. Extracts and Their Isolated Compound Capsaicin. Antibiotics 2022;11:1154.
[17] Kowalska J, Tyburski J, Krzymińska J, Jakubowska M. Cinnamon powder: an in vitro and in vivo evaluation of antifungal and plant growth promoting activity. European Journal of Plant Pathology 2020;156:237-43.
[18] Xi K-Y, Xiong S-J, Li G, Guo C-Q, Zhou J, Ma J-W, et al. Antifungal Activity of Ginger Rhizome Extract against Fusarium solani. Horticulturae 2022;8:983.
[19] Archana H, Bose VG. Evaluation of phytoconstituents from selected medicinal plants and its synergistic antimicrobial activity. Chemosphere 2022;287:132276.
[20] Simonetti G, Brasili E, Pasqua G. Antifungal Activity of Phenolic and Polyphenolic Compounds from Different Matrices of Vitis vinifera L. against Human Pathogens. Molecules 2020;25.
[21] Adamczak A, Ożarowski M, Karpiński TM. Curcumin, a natural antimicrobial agent with strain-specific activity. Pharmaceuticals 2020;13:153.
[22] Akter J, Amzad Hossain M, Sano A, Takara K, Zahorul Islam M, Hou D-X. Antifungal Activity of Various Species and Strains of Turmeric (Curcuma SPP.) Against Fusarium Solani Sensu Lato. Pharmaceutical Chemistry Journal 2018;52:320-5.
[23] Jennings MR, Parks RJ. Curcumin as an Antiviral Agent. Viruses 2020;12.
[24] Naderi MJJ, Mahmoudi A, Kesharwani P, Jamialahmadi T, Sahebkar A. Recent advances of nanotechnology in the treatment and diagnosis of polycystic ovary syndrome. Journal of Drug Delivery Science and Technology 2022:104014.
[25] Nagargoje AA, Akolkar SV, Siddiqui MM, Subhedar DD, Sangshetti JN, Khedkar VM, et al. Quinoline based monocarbonyl curcumin analogs as potential antifungal and antioxidant agents: Synthesis, bioevaluation and molecular docking study. Chemistry & Biodiversity 2020;17:e1900624.
[26] Shaker B, Ahmad S, Lee J, Jung C, Na D. In silico methods and tools for drug discovery. Computers in biology and medicine 2021;137:104851.
[27] Meylani V, Putra RR, Miftahussurur M, Sukardiman S, Hermanto FE, Abdullah A. Molecular docking analysis of Cinnamomum zeylanicum phytochemicals against Secreted Aspartyl Proteinase 4–6 of Candida albicans as anti-candidiasis oral. Results in Chemistry 2023;5:100721.
[28] Shrivastava M, Sharma P, Singh R. Identification of potential CYP51 inhibiting anti-Aspergillus phytochemicals using molecular docking and ADME/T studies. Chemical Biology Letters 2021;8:18-21.
[29] Robbins N, Caplan T, Cowen LE. Molecular evolution of antifungal drug resistance. Annual review of microbiology 2017;71:753-75.
[30] UniProt: the universal protein knowledgebase. Nucleic Acids Res 2017;45:D158-d69.
[31] Sofi M, Shafi A, Masoodi K. Chapter 22-Introduction to computer-aided drug design. Bioinformatics for everyone 2022:215-29.
[32] Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, Gumienny R, et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic acids research 2018;46:W296-W303.
[33] Wiltgen M. Algorithms for Structure Comparison and Analysis: Homology Modelling of Proteins. In: Ranganathan S, Gribskov M, Nakai K, Schönbach C, editors. Encyclopedia of Bioinformatics and Computational Biology. Oxford: Academic Press; 2019. p. 38-61.
[34] Sahay A, Piprodhe A, Pise M. In silico analysis and homology modeling of strictosidine synthase involved in alkaloid biosynthesis in catharanthus roseus. Journal of Genetic Engineering and Biotechnology 2020;18:1-6.
[35] Guruprasad K, Reddy BV, Pandit MW. Correlation between stability of a protein and its dipeptide composition: a novel approach for predicting in vivo stability of a protein from its primary sequence. Protein Eng 1990;4:155-61.
[36] Ikai A. Thermostability and aliphatic index of globular proteins. J Biochem 1980;88:1895-8.
[37] Kyte J, Doolittle RF. A simple method for displaying the hydropathic character of a protein. J Mol Biol 1982;157:105-32.
[38] Agnihotry S, Pathak RK, Singh DB, Tiwari A, Hussain I. Chapter 11 - Protein structure prediction. In: Singh DB, Pathak RK, editors. Bioinformatics: Academic Press; 2022. p. 177-88.
[39] Silakari O, Singh PK. Chapter 5 - Homology modeling: Developing 3D structures of target proteins missing in databases. In: Silakari O, Singh PK, editors. Concepts and Experimental Protocols of Modelling and Informatics in Drug Design: Academic Press; 2021. p. 107-30.
[40] Irwin JJ, Sterling T, Mysinger MM, Bolstad ES, Coleman RG. ZINC: a free tool to discover chemistry for biology. Journal of chemical information and modeling 2012;52:1757-68.
[41] Kim S, Thiessen PA, Bolton EE, Chen J, Fu G, Gindulyte A, et al. PubChem substance and compound databases. Nucleic acids research 2016;44:D1202-D13.
[42] Bertoni M, Kiefer F, Biasini M, Bordoli L, Schwede T. Modeling protein quaternary structure of homo-and hetero-oligomers beyond binary interactions by homology. Scientific reports 2017;7:1-15.
[43] Kontoyianni M. Docking and virtual screening in drug discovery. Proteomics for drug discovery: Methods and protocols 2017:255-66.
[44] Dallakyan S, Olson AJ. Small-molecule library screening by docking with PyRx. Chemical biology: methods and protocols 2015:243-50.
[45] Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, et al. UCSF Chimera—a visualization system for exploratory research and analysis. Journal of computational chemistry 2004;25:1605-12.
[46] Biovia DS. Discovery studio modeling environment. Release; 2017.
[47] Daina A, Michielin O, Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific reports 2017;7:42717.
[48] Noe M, Peakman M-C. Drug discovery technologies: Current and future trends. 2017.
[49] Banerjee P, Eckert AO, Schrey AK, Preissner R. ProTox-II: a webserver for the prediction of toxicity of chemicals. Nucleic acids research 2018;46:W257-W63.
[50] Pires DE, Blundell TL, Ascher DB. pkCSM: predicting small-molecule pharmacokinetic and toxicity properties using graph-based signatures. Journal of medicinal chemistry 2015;58:4066-72.
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Dec 27, 2023
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Mohammad Javad Javid-Naderi, Hossein Zarrinfar, & Tahany Al-Shemary. (2023). IN SILICO ANALYSIS AND MOLECULAR DOCKING OF CURCUMIN ANALOGS AND ANTIFUNGAL COMPOUNDS AGAINST CRITICAL PROTEINS OF ASPERGILLUS SPECIES: A COMPARATIVE INVESTIGATION. Journal of Population Therapeutics and Clinical Pharmacology, 30(19), 1345-1365. https://doi.org/10.53555/jptcp.v30i19.3571
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Author Biographies
Mohammad Javad Javid-Naderi
Department of Medical Biotechnology and Nanotechnology, Faculty of Medicine, Mashhad University of Medical Sciences, Iran
Hossein Zarrinfar
Allergy Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
Tahany Al-Shemary
Department of Microbiology, College of Medicine, Kuwait University, Jabriya, Kuwait
How to Cite
Mohammad Javad Javid-Naderi, Hossein Zarrinfar, & Tahany Al-Shemary. (2023). IN SILICO ANALYSIS AND MOLECULAR DOCKING OF CURCUMIN ANALOGS AND ANTIFUNGAL COMPOUNDS AGAINST CRITICAL PROTEINS OF ASPERGILLUS SPECIES: A COMPARATIVE INVESTIGATION. Journal of Population Therapeutics and Clinical Pharmacology, 30(19), 1345-1365. https://doi.org/10.53555/jptcp.v30i19.3571