Ligand-based Virtual Screening, Quantum Mechanics Calculations, and Normal Mode Analysis of Phytochemical Compounds Targeting Toll‐Interacting Protein (Tollip) Against Bacterial Diseases

Jump To References Section

Authors

  • Sk Injamamul Islam
     1Department of Fisheries, Faculty of Biological Science and Technology, Jashore University of Science and Technology, Jashore – 7408 ,BD
  • M. Norjit Singh
     Department of Animal Sciences, CAU, Imphal – 795004, Manipur ,IN
  • C. Sonia
     ICAR-NEH Region, Manipur Centre, Lamphelpat – 795004, Manipur ,IN
  • Md Akib Ferdous
     Department of Fisheries, Faculty of Biological Science and Technology, Jashore University of Science and Technology, Jashore – 7408 ,BD
  • Nasim Habib
     Department of Fisheries, Faculty of Biological Science and Technology, Jashore University of Science and Technology, Jashore – 7408 ,BD
  • Saloa Sanjida
     Department of Environmental Science and Technology, Faculty of Applied Science, Jashore University of Science and Technology, Jashore – 7408 ,BD
  • Md Jamadul Islam
     Department of Fisheries, Faculty of Biological Science and Technology, Jashore University of Science and Technology, Jashore – 7408 ,BD
  • Nahidul Islam
     Department of Fisheries, Faculty of Biological Science and Technology, Jashore University of Science and Technology, Jashore – 7408 ,BD
  • Mohamed H. Hamad
     Infectious Diseases, Department of Animal Medicine, Faculty of Veterinary Medicine, Zagazig University, Zagazig City – 44511, Sharkia Province ,EG

DOI:

https://doi.org/10.18311/ti/2023/v30i2/30768

Keywords:

Allium sativum, ADMET, Bacteria, Docking, Tollip
BIOINFORMATICS

Abstract

The Labeo rohita (Rohu) Toll interacting protein (Tollip) is ubiquitously expressed in the kidneys, gills, spleen, liver, and blood. Tollip in L. rohita has higher eukaryotic structural features and is produced in response to bacterial infections. Several bacterial diseases, such as Aeromonas hydrophila and Vibrio spp, have been reported in the internal organs of L. rohita. The consequences of these bacterial infections can be 100% mortality of fish. There are currently no medicines or vaccines available to prevent or treat infections caused by the involvement of this protein. During bacterial infections, it was discovered that Tollip plays an essential function as a negative regulator of the MyD88-dependent TLR signalling pathway. Therefore, the study aimed to evaluate the inhibitory potentiality of the Allium sativum compound against Tollip. A. sativum has been reported to show potential antibacterial activity against numerous microbial pathogens. Still, activity against the Tollip-promoted pathogens has not yet been reported. In silico virtual screen and molecular docking methods were used in this study to calculate the binding affinity of 48 drug compounds of A. sativum against the receptor Tollip. The docking and normal mode analysis methods predict 2 (PubChem CID: 122130381 and CID 12303662) inhibitory compounds that bind strongly with the Tollip with a binding affinity of -9.2 and -8.8 kcal/mol, respectively. The ADMET properties of the compounds also verified the drug resemblance features of the two compounds of A. sativum. Furthermore, to evaluate the efficacy of these two potential inhibitors, more in-vitro testing is required.

Downloads

Download data is not yet available.

Downloads

Published

2023-05-19

How to Cite

Islam, S. I., Singh, M. N., Sonia, C., Ferdous, M. A., Habib, N., Sanjida, S., Islam, M. J., Islam, N., & Hamad, M. H. (2023). Ligand-based Virtual Screening, Quantum Mechanics Calculations, and Normal Mode Analysis of Phytochemical Compounds Targeting Toll‐Interacting Protein (Tollip) Against Bacterial Diseases. Toxicology International, 30(2), 139–153. https://doi.org/10.18311/ti/2023/v30i2/30768

Issue

Volume 30, Issue 2, April-June 2023

Section

Articles
Crossref
Scopus
Google Scholar
Europe PMC
Received 2022-07-19
Accepted 2022-11-21
Published 2023-05-19

 

References

Huang R, Lv J, Luo D, Liao L, Zhu Z, Wang Y. Identification, characterization and the interaction of Tollip and IRAK-1 in grass carp (Ctenopharyngodon idellus). Fish and Shellfish Immunology. 2012; 33(3):459–67. PMid: 22659441. https:// doi.org/10.1016/j.fsi.2012.05.025 DOI: https://doi.org/10.1016/j.fsi.2012.05.025

Shan S, Wang L, Zhang F, Zhu Y, An L, Yang G. Characterization and expression analysis of Toll-interacting protein in common carp, Cyprinus carpio L., responding to bacterial and viral challenge. SpringerPlus. 2016; 5(1):1– 10. PMid: 27330905 PMCid: PMC4870529. https://doi. org/10.1186/s40064-016-2293-3 DOI: https://doi.org/10.1186/s40064-016-2293-3

Lu Y, Li C, Wang D, Su X, Jin C, Li Y, et al. Characterization of two negative regulators of the Toll-like receptor pathway in Apostichopus japonicus: Inhibitor of NF-κB and Tollinteracting protein. Fish and Shellfish Immunology. 2013; 35(5):1663–9. PMid: 23978566. https://doi.org/10.1016/j. fsi.2013.08.014 DOI: https://doi.org/10.1016/j.fsi.2013.08.014

Jalil A, Ashfaq UA, Shahzadi S, Javed MR, Rasul I, Rehman S-u, et al. Screening and design of antidiabetic compounds sourced from the leaves of neem (Azadirachta indica). Bioinformation. 2013; 9(20):1031. PMid: 24497731 PMCid: PMC3910360. https://doi.org/10.6026/97320630091031 DOI: https://doi.org/10.6026/97320630091031

Srivastava AK, Maurya R. Antihyperglycemic activity of compounds isolated from Indian medicinal plants. 2010.

El-Saber Batiha G, Magdy Beshbishy A, G. Wasef L, Elewa YH, A. Al-Sagan A, Abd El-Hack ME, et al. Chemical constituents and pharmacological activities of garlic (Allium sativum L.): A review. Nutrients. 2020; 12(3):872. PMid: 32213941 PMCid: PMC7146530. https://doi.org/10.3390/ nu12030872 DOI: https://doi.org/10.3390/nu12030872

Labh S, Shakya S. Medicinal uses of garlic (Allium sativum) improves fish health and acts as an immunostimulant in aquaculture. 2014; 2:44–7.

Lim SM, Xie T, Westover KD, Ficarro SB, Tae HS, Gurbani D, et al. Development of small molecules targeting the pseudokinase Her3. Bioorganic and Medicinal Chemistry Letters. 2015; 25(16):3382–9. PMid: 26094118 PMCid: PMC4633287. https://doi.org/10.1016/j.bmcl.2015.04.103 DOI: https://doi.org/10.1016/j.bmcl.2015.04.103

Hughes JP, Rees S, Kalindjian SB, Philpott KL. Principles of early drug discovery. British Journal of Pharmacology. 2011; 162(6):1239–49. PMid: 21091654 PMCid: PMC3058157. https://doi.org/10.1111/j.1476-5381.2010.01127.x DOI: https://doi.org/10.1111/j.1476-5381.2010.01127.x

Szymański P, Markowicz M, Mikiciuk-Olasik E. Adaptation of high-throughput screening in drug discovery-toxicological screening tests. International Journal of Molecular Sciences. 2011; 13(1):427–52. PMid: 22312262 PMCid: PMC3269696. https://doi.org/10.3390/ijms13010427 DOI: https://doi.org/10.3390/ijms13010427

Kumar V, Jung Y-S, Liang P-H. Anti-SARS coronavirus agents: A patent review (2008-present). Expert opinion on therapeutic patents. 2013; 23(10):1337–48. PMid: 23905913. https://doi.org/10.1517/13543776.2013.823159 DOI: https://doi.org/10.1517/13543776.2013.823159

Wichapong K, Nueangaudom A, Pianwanit S, Sippl W, Kokpol S. Identification of potential hit compounds for Dengue virus NS2B/NS3 protease inhibitors by combining virtual screening and binding free energy calculations. Trop Biomed. 2013; 30(3):388–408.

Islam S, Mou M, Sanjida S, Mahfuj MsE. An In-silico Approach for Identifying Phytochemical Inhibitors Against Nervous Necrosis Virus (NNV) in Asian Sea Bass by Targeting Capsid Protein. Genetics of Aquatic Organisms. 2022; 6:487. https://doi.org/10.4194/GA487 DOI: https://doi.org/10.4194/GA487

Islam S, Mou M. Functional Annotation of Uncharacterized Protein from Photobacterium damselae subsp. piscicida (Pasteurella piscicida) and Comparison of Drug Target Between Conventional Medicine and Phytochemical Compound Against Disease Treatment in Fish: An In-silico Approach. Genetics of Aquatic Organisms. 2022; 6:453. https://doi.org/10.4194/GA453

Wu J, Hu B, Sun X, Wang H, Huang Y, Zhang Y, et al. In silico study reveals existing drugs as α-glucosidase inhibitors: Structure-based virtual screening validated by experimental investigation. Journal of Molecular Structure. 2020; 1218:128532. https://doi.org/10.1016/j. molstruc.2020.128532 DOI: https://doi.org/10.1016/j.molstruc.2020.128532

Wu C, Liu Y, Yang Y, Zhang P, Zhong W, Wang Y, et al. Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods. Acta Pharmaceutica Sinica B. 2020; 10(5):766–88. PMid: 32292689 PMCid: PMC7102550. https://doi.org/10.1016/j. apsb.2020.02.008 DOI: https://doi.org/10.1016/j.apsb.2020.02.008

Islam S, Sanjida S, Mahfuj MsE, Islam MJ, Mou M. Computer-aided drug design of Azadirachta indica compounds against nervous necrosis virus by targeting grouper heat shock cognate protein 70 (GHSC70): Quantum mechanics calculations and molecular dynamic simulation approaches. Genomics and Informatics. 2022;20. PMid: 36239110 PMCid: PMC9576468. https://doi.org/10.5808/ gi.21063 DOI: https://doi.org/10.5808/gi.21063

Sanjida S, Mou M, Islam S, Mahfuj MsE. Identification of potential antiviral drug compound against Erythrocytic necrosis virus by targeting Major capsid protein. International Journal of Life Sciences and Biotechnology. 2022. https://doi.org/10.38001/ijlsb.1074392

Combet C, Blanchet C, Geourjon C, Deleage G. NPS@: Network protein sequence analysis. Trends in Biochemical Sciences. 2000; 25(3):147–50. PMid: 10694887. https://doi. org/10.1016/S0968-0004(99)01540-6 DOI: https://doi.org/10.1016/S0968-0004(99)01540-6

Xu J, Mcpartlon M, Li J. Improved protein structure prediction by deep learning irrespective of co-evolution information. Nature Machine Intelligence. 2021; 3(7):601– 9. PMid: 34368623 PMCid: PMC8340610. https://doi. org/10.1038/s42256-021-00348-5 DOI: https://doi.org/10.1038/s42256-021-00348-5

Islam S, Mou M, Sanjida S, Mahfuj MsE, Alam M, Ara Y. An In-silico analysis of the molecular interactions between PmCBP-VP24 and PmCBP-VP28 protein complex to understand the initial initiating events of shrimp WSSV infection. International Journal of Life Sciences and Biotechnology. 2022. https://doi.org/10.38001/ijlsb.1055840 DOI: https://doi.org/10.38001/ijlsb.1055840

Islam S, Mou M, Sanjida S, Mahfuj MsE. Functional annotation and characterization of a hypothetical protein from Pseudoalteromonas spp. Identify Potential Biomarker: An In-silico Approach. Aquatic Food Studies. 2022; 2:57. DOI: 10.5281/zenodo.6589947 https://doi.org/10.4194/AFS57 DOI: https://doi.org/10.4194/AFS57

Sanjida S, Mou MJ, Islam SI, Sarower-E-Mahfuj M. An In-silico approaches for identification of potential natural antiviral drug candidates against Erythrocytic necrosis virus (Iridovirus) by targeting Major capsid protein: A Quantum mechanics calculations approach. International Journal of Life Sciences and Biotechnology. 2022: 294–315. https://doi.org/10.38001/ijlsb.1074392 DOI: https://doi.org/10.38001/ijlsb.1074392

Wiederstein M, Sippl MJ. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic acids research. 2007; 35(suppl_2):W407–W10. PMid:175: PMC1933241. https:// doi.org/10.1093/nar/gkm290 DOI: https://doi.org/10.1093/nar/gkm290

Ramachandran GN, Ramakrishnan C, Sasisekharan V. Stereochemistry of polypeptide chain configurations. J mol Biol. 1963; 7:95–9. PMid: 13990617. https://doi. org/10.1016/S0022-2836(63)80023-6 DOI: https://doi.org/10.1016/S0022-2836(63)80023-6

Islam SI, Sanjida S, Mou MJ, Sarower-E-Mahfuj M, Nasir S. In-silico functional annotation of a hypothetical protein from Edwardsiella tarda revealed Proline metabolism and apoptosis in fish. International Journal of Life Sciences and Biotechnology. 2022; 5(1):78–96. https://doi.org/10.38001/ ijlsb.1032171

Islam SI, Jahan MM. Functional annotation of uncharacterized protein from photobacterium damselae subsp. piscicida (pasteurella piscicida) and comparison of drug target between conventional medicine and phytochemical compound against disease treatment in fish: An In-silico Approach. Genetics of Aquatic Organisms. 2022; 6(3). https://doi.org/10.4194/GA453 DOI: https://doi.org/10.4194/GA453

Mohanraj K, Karthikeyan BS, Vivek-Ananth R, Chand R, Aparna S, Mangalapandi P, et al. IMPPAT: A curated database of Indian medicinal plants, phytochemistry and therapeutics. Scientific reports. 2018; 8(1):1–17. PMid: 29531263 PMCid: PMC5847565. https://doi.org/10.1038/ s41598-018-22631-z DOI: https://doi.org/10.1038/s41598-018-22631-z

Dallakyan S, Olson AJ. Small-molecule library screening by docking with PyRx. Chemical Biology: Springer; 2015. p. 243–50. PMid: 25618350. https://doi.org/10.1007/978-1- 4939-2269-7_19 DOI: https://doi.org/10.1007/978-1-4939-2269-7_19

Li Y, Meng Q, Yang M, Liu D, Hou X, Tang L, et al. Current trends in drug metabolism and pharmacokinetics. Acta Pharmaceutica Sinica B. 2019; 9(6):1113–44. PMid: 31867160 PMCid: PMC6900561. https://doi.org/10.1016/j. apsb.2019.10.001 DOI: https://doi.org/10.1016/j.apsb.2019.10.001

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(1):1–13. PMid: 28256516 PMCid: PMC5335600. https://doi.org/10.1038/srep42717 DOI: https://doi.org/10.1038/srep42717

Li C, Wang J, Wang Y, Gao H, Wei G, Huang Y, et al. Recent progress in drug delivery. Acta pharmaceutica sinica B. 2019; 9(6):1145–62. PMid: 31867161 PMCid: PMC6900554. https://doi.org/10.1016/j.apsb.2019.08.003 DOI: https://doi.org/10.1016/j.apsb.2019.08.003

Friesner RA, Guallar V. Ab initio quantum chemical and mixed quantum mechanics/molecular mechanics (QM/ MM) methods for studying enzymatic catalysis. Annual Review of Physical Chemistry. 2005; 56:389. PMid: 15796706. https://doi.org/10.1146/annurev.physchem. 55.091602.094410 DOI: https://doi.org/10.1146/annurev.physchem.55.091602.094410

Maity A, Samanta S, Biswas D, Chakravorty D. Studies on nanoconfinement effect of NiO-SiO2 spin glass within mesoporous Al2O3 template. Journal of Alloys and Compounds. 2021; 887:161447. https://doi.org/10.1016/j. jallcom.2021.161447 DOI: https://doi.org/10.1016/j.jallcom.2021.161447

Hanwell MD, Curtis DE, Lonie DC, Vandermeersch T, Zurek E, Hutchison GR. Avogadro: An advanced semantic chemical editor, visualization, and analysis platform. Journal of Cheminformatics. 2012; 4(1):1–17. PMid: 22889332 PMCid: PMC3542060. https://doi.org/10.1186/1758-2946- 4-17 DOI: https://doi.org/10.1186/1758-2946-4-17

Li Y, Evans JN. The Fukui function: A key concept linking frontier molecular orbital theory and the hard-soft-acidbase principle. Journal of the American Chemical Society. 1995; 117(29):7756–9. https://doi.org/10.1021/ja00134a021 DOI: https://doi.org/10.1021/ja00134a021

Pandey RK, Verma P, Sharma D, Bhatt TK, Sundar S, Prajapati VK. High-throughput virtual screening and quantum mechanics approach to develop imipramine analogues as leads against trypanothione reductase of leishmania. Biomedicine and Pharmacotherapy. 2016; 83:141–52. PMid: 27470561. https://doi.org/10.1016/j.biopha.2016.06.010 DOI: https://doi.org/10.1016/j.biopha.2016.06.010

López-Blanco JR, Aliaga JI, Quintana-Ortí ES, Chacón P. iMODS: Internal coordinates normal mode analysis server. Nucleic Acids Research. 2014; 42(W1):W271–W6. PMid: 24771341 PMCid: PMC4086069. https://doi.org/10.1093/ nar/gku339 DOI: https://doi.org/10.1093/nar/gku339

Bharadwaj S, Dubey A, Yadava U, Mishra SK, Kang SG, Dwivedi VD. Exploration of natural compounds with anti- SARS-CoV-2 activity via inhibition of SARS-CoV-2 Mpro. Briefings in bioinformatics. 2021; 22(2):1361–77. PMid: 33406222 PMCid: PMC7929395. https://doi.org/10.1093/ bib/bbaa382 DOI: https://doi.org/10.1093/bib/bbaa382

Miar M, Shiroudi A, Pourshamsian K, Oliaey AR, Hatamjafari F. Theoretical investigations on the HOMOLUMO gap and global reactivity descriptor studies, natural bond orbital, and nucleus-independent chemical shifts analyses of 3-phenylbenzo [d] thiazole-2 (3 H)-imine and its para-substituted derivatives: Solvent and substituent effects. Journal of Chemical Research. 2021; 45(1-2):147– 58. https://doi.org/10.1177/1747519820932091 DOI: https://doi.org/10.1177/1747519820932091

Li D, Wu M. Pattern recognition receptors in health and diseases. Signal Transduct Target Ther. 2021; 6(1):291. PMid: 34344870 PMCid: PMC8333067. https://doi.org/10.1038/ s41392-021-00687-0 DOI: https://doi.org/10.1038/s41392-021-00687-0

Zhang J, Kong X, Zhou C, Li L, Nie G, Li X. Toll-like receptor recognition of bacteria in fish: ligand specificity and signal pathways. Fish Shellfish Immunol. 2014; 41(2):380–8. PMid: 25241605. https://doi.org/10.1016/j.fsi.2014.09.022 DOI: https://doi.org/10.1016/j.fsi.2014.09.022

Gerold G, Zychlinsky A, de Diego JL. What is the role of Toll-like receptors in bacterial infections? Semin Immunol. 2007; 19(1):41–7. PMid: 17280841. https://doi. org/10.1016/j.smim.2006.12.003 DOI: https://doi.org/10.1016/j.smim.2006.12.003

Mohanty A, Sadangi S, Paichha M, Saha A, Das S, Samanta M. Toll-interacting protein in the freshwater fish Labeo rohita exhibits conserved structural motifs of higher eukaryotes and is distinctly expressed in pathogenassociated molecular pattern stimulations and bacterial infections. Microbiol Immunol. 2021; 65(8):281–9. PMid: 32237168. https://doi.org/10.1111/1348-0421.12792

Ramesh D, Souissi S. Antibiotic resistance and virulence traits of bacterial pathogens from infected freshwater fish, Labeo rohita. Microb Pathog. 2018; 116:113–9. PMid: 29339308. https://doi.org/10.1016/j.micpath.2018.01.019 DOI: https://doi.org/10.1016/j.micpath.2018.01.019

Mohanty A, Sadangi S, Paichha M, Saha A, Das S, Samanta M. Toll-interacting protein in the freshwater fish Labeo rohita exhibits conserved structural motifs of higher eukaryotes and is distinctly expressed in pathogen-associated molecular pattern stimulations and bacterial infections. Microbiology and Immunology. 2021; 65(8):281–9. PMid: 32237168. https://doi.org/10.1111/1348-0421.12792 DOI: https://doi.org/10.1111/1348-0421.12792

Chakraborty SB, Horn P, Hancz C. Application of phytochemicals as growth‐promoters and endocrine modulators in fish culture. Reviews in Aquaculture. 2014; 6(1):1–19. https://doi.org/10.1111/raq.12021 DOI: https://doi.org/10.1111/raq.12021

Valenzuela-Gutiérrez R, Lago-Lestón A, Vargas-Albores F, Cicala F, Martínez-Porchas M. Exploring the garlic (Allium sativum) properties for fish aquaculture. Fish Physiol Biochem. 2021; 47(4):1179–98. PMid: 34164770. https:// doi.org/10.1007/s10695-021-00952-7 DOI: https://doi.org/10.1007/s10695-021-00952-7

Madhavi Sastry G, Adzhigirey M, Day T, Annabhimoju R, Sherman W. Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments. Journal of Computer-Aided Molecular Design. 2013; 27(3):221–34. PMid: 23579614. https://doi.org/10.1007/ s10822-013-9644-8 DOI: https://doi.org/10.1007/s10822-013-9644-8

Islam S, Mou M. Analysis of a Hypothetical Protein from Vibrio Harveyi Identified Possible Connection with Biopolymer Metabolism: An In-Silico Approach. Journal of Applied Biological Sciences. 2022; 16:191–205. https://doi. org/10.5281/zenodo.6589947

Islam S, Sanjida S, Mou M, Mahfuj MsE, Nasir S. In-silico functional annotation of a hypothetical protein from Edwardsiella tarda revealed Proline metabolism and apoptosis in fish. International Journal of Life Sciences and Biotechnology. 2022; 5:78–96. https://doi.org/10.38001/ ijlsb.1032171 DOI: https://doi.org/10.38001/ijlsb.1032171

Lipinski CA. Lead- and drug-like compounds: The ruleof- five revolution. Drug Discov Today Technol. 2004; 1(4):337–41. PMid: 24981612. https://doi.org/10.1016/j. ddtec.2004.11.007 DOI: https://doi.org/10.1016/j.ddtec.2004.11.007

Pollastri MP. Overview on the Rule of Five. Curr Protoc Pharmacol. 2010; Chapter 9: Unit 9.12. PMid: 22294375. https://doi.org/10.1002/0471141755.ph0912s49 DOI: https://doi.org/10.1002/0471141755.ph0912s49

Aljahdali MO, Molla MHR, Ahammad F. compounds identified from marine mangrove plant (Avicennia alba) as potential antiviral drug candidates against WDSV, an In-Silico Approach. Mar Drugs. 2021; 19(5). PMid: 33925208 PMCid: PMC8145693. https://doi.org/10.3390/ md19050253 DOI: https://doi.org/10.3390/md19050253