Login Register Cart 0
Generic placeholder image

Letters in Drug Design & Discovery

Editor-in-Chief

ISSN (Print): 1570-1808
ISSN (Online): 1875-628X

Back
Research Article

A Combined QSAR and Molecular Docking Approach for Identifying Pyrimidine Derivatives as Penicillin Binding Protein Inhibitors

Author(s): Smriti Sharma*, Brij K. Sharma, Surabhi Jain and Puja Gulyani

Volume 19, Issue 12, 2022

Published on: 25 May, 2022

Page: [1121 - 1135] Pages: 15

DOI: 10.2174/1570180819666220427101322

Price: $65

Abstract

Background: Antimicrobial resistance has been rising continuously in the past few years due to the overuse and exploitation of existing antimicrobials. This has motivated the search for a novel scaffold that has the capability of rapid antimicrobial action. The hybridized pyrimidines have attracted us due to their widespread biological activities, such as anti-bacterial and antifungal activities.

Objective: The present study incorporates a series of pyrimidine-based antimicrobial agents for the 2D quantitative structure-activity relationship analysis (2D QSAR) and docking analysis.

Methods: The exploration of the chemical structures in combination with the biological activity in CPMLR led to the detection of six descriptors (Constitutional descriptors, Topological descriptors, Modified Burden Eigenvalues and 2D autocorrelations) for modeling the activity. The resulted QSAR model has been validated using a combinatorial protocol in multiple linear regression (CP-MLR) and partial least squares (PLS) analysis.

Results: The best QSAR model displays the r2 t value of 0.594, Q2 LOO value of 0.779, Q2 L5O value of 0.767. Further docking study was executed using Autodock Vina against Penicillin-binding protein (PBP2a).

Conclusion: From the results, Compounds 4, 11and 24 were found to possess a good binding affinity towards PBP2a.

Keywords: Pyrimidine, combinatorial protocol in multiple linear regression (CP-MLR), PLS analysis, dragon descriptors, docking, penicillin-binding protein.

« Previous Next »
Graphical Abstract

[1]
Gaynes, R. The discovery of penicillin-new insights after more than 75 years of clinical use. Emerg. Infect. Dis., 2017, 23(5), 849-853.
[http://dx.doi.org/10.3201/eid2305.161556]
[2]
Lima, L.M. Silva, B.N.M.D.; Barbosa, G.; Barreiro, E.J. β-lactam antibiotics: An overview from a medicinal chemistry perspective. Eur. J. Med. Chem., 2020, 208, 112829.
[http://dx.doi.org/10.1016/j.ejmech.2020.112829] [PMID: 33002736]
[3]
Jackson, N.; Czaplewski, L.; Piddock, L.J.V. Discovery and development of new antibacterial drugs: Learning from experience? J. Antimicrob. Chemother., 2018, 73(6), 1452-1459.
[http://dx.doi.org/10.1093/jac/dky019] [PMID: 29438542]
[4]
Sharma, D.; Misba, L.; Khan, A.U. Antibiotics versus biofilm: An emerging battleground in microbial communities. Antimicrob. Resist. Infect. Control, 2019, 8, 76.
[http://dx.doi.org/10.1186/s13756-019-0533-3] [PMID: 31131107]
[5]
Olivares, E.; Badel-Berchoux, S.; Provot, C.; Prévost, G.; Bernardi, T.; Jehl, F. Clinical impact of antibiotics for the treatment of Pseudo-monas aeruginosa biofilm infections. Front. Microbiol., 2020, 10, 2894.
[http://dx.doi.org/10.3389/fmicb.2019.02894] [PMID: 31998248]
[6]
Hung, C.L.; Chen, C.C. Computational approaches for drug discovery. Drug Dev. Res., 2014, 75(6), 412-418.
[http://dx.doi.org/10.1002/ddr.21222] [PMID: 25195585]
[7]
Brogi, S. Computational approaches for drug discovery. Molecules, 2019, 24(17), 3061-3066.
[http://dx.doi.org/10.3390/molecules24173061] [PMID: 31443558]
[8]
Peter, S.C.; Dhanja, J.K.; Malik, V. Quantitative Structure-Activity Relationship (QSAR): Modeling approaches to biological applications. In: Enc Bioinformat Computat Biology , 2019; pp. 661-676.
[9]
Hanna, M.M. New pyrimido[5,4-e]pyrrolo[1,2-c]pyrimidines: Synthesis, 2D-QSAR, anti-inflammatory, analgesic and ulcerogenicity stud-ies. Eur. J. Med. Chem., 2012, 55, 12-22.
[http://dx.doi.org/10.1016/j.ejmech.2012.06.048] [PMID: 22818041]
[10]
Nandi, S.; Bagchi, M.C. QSAR of aminopyrido[2,3-d]pyrimidin-7-yl derivatives: Anticancer drug design by computed descriptors. J. Enzyme Inhib. Med. Chem., 2009, 24(4), 937-948.
[http://dx.doi.org/10.1080/14756360802519327] [PMID: 19555178]
[11]
Sharma, S.; Sharma, B.K.; Prabhakar, Y.S. Juglone derivatives as antitubercular agents: A rationale for the activity profile. Eur. J. Med. Chem., 2009, 44(7), 2847-2853.
[http://dx.doi.org/10.1016/j.ejmech.2008.12.015] [PMID: 19167787]
[12]
Khalil, T.E.; Dissouky, A.E.; Wahaib, D.A.; Abrar, N.M.; El-Sayed, D.S. Synthesis, characterization, antimicrobial activity, 3D-QSAR, DFT, and molecular docking of some ciprofloxacin derivatives and their copper(II) complexes. Appl. Organomet. Chem., 2020, 34(12), e5998.
[http://dx.doi.org/10.1002/aoc.5998]
[13]
Navratna, V.; Nadig, S.; Sood, V.; Prasad, K.; Arakere, G.; Gopal, B. Molecular basis for the role of Staphylococcus aureus penicillin bind-ing protein 4 in antimicrobial resistance. J. Bacteriol., 2010, 192(1), 134-144.
[http://dx.doi.org/10.1128/JB.00822-09] [PMID: 19854906]
[14]
Tooke, C.L. Hinchliffe, P.; Bragginton, E.C.; Colenso, C.K.; Hirvonen, V.H.A.; Takebayashi, Y.; Spencer, J. β-Lactamases and β-Lactamase Inhibitors in the 21st Century. J. Mol. Biol., 2019, 431(18), 3472-3500.
[http://dx.doi.org/10.1016/j.jmb.2019.04.002] [PMID: 30959050]
[15]
AlNeyadi, S.S.; Salem, A.A.; Ghattas, M.A.; Atatreh, N.; Abdou, I.M. Antibacterial activity and mechanism of action of the benzazole acrylonitrile-based compounds: In vitro, spectroscopic, and docking studies. Eur. J. Med. Chem., 2017, 136, 270-282.
[http://dx.doi.org/10.1016/j.ejmech.2017.05.010] [PMID: 28500995]
[16]
Sharma, S.; Saquib, M.; Verma, S.; Mishra, N.N.; Shukla, P.K.; Srivastava, R.; Prabhakar, Y.S.; Shaw, A.K. Synthesis of 2,3,6-trideoxy sugar triazole hybrids as potential new broad spectrum antimicrobial agents. Eur. J. Med. Chem., 2014, 83, 474-489.
[http://dx.doi.org/10.1016/j.ejmech.2014.06.048] [PMID: 24992075]
[17]
Miethke, M.; Pieroni, M.; Weber, T.; Brönstrup, M.; Hammann, P.; Halby, L.; Arimondo, P.B.; Glaser, P.; Aigle, B.; Bode, H.B.; Moreira, R.; Li, Y.; Luzhetskyy, A.; Medema, M.H.; Pernodet, J.L.; Stadler, M.; Tormo, J.R.; Genilloud, O.; Truman, A.W.; Weissman, K.J.; Taka-no, E.; Sabatini, S.; Stegmann, E.; Brötz-Oesterhelt, H.; Wohlleben, W.; Seemann, M.; Empting, M.; Hirsch, A.K.H.; Loretz, B.; Lehr, C.M.; Titz, A.; Herrmann, J.; Jaeger, T.; Alt, S.; Hesterkamp, T.; Winterhalter, M.; Schiefer, A.; Pfarr, K.; Hoerauf, A.; Graz, H.; Graz, M.; Lindvall, M.; Ramurthy, S.; Karlén, A.; van Dongen, M.; Petkovic, H.; Keller, A.; Peyrane, F.; Donadio, S.; Fraisse, L.; Piddock, L.J.V.; Gilbert, I.H.; Moser, H.E.; Müller, R. Towards the sustainable discovery and development of new antibiotics. Nat. Rev. Chem., 2021, 5(10), 726-749.
[http://dx.doi.org/10.1038/s41570-021-00313-1] [PMID: 34426795]
[18]
O’Daniel, P.I.; Peng, Z.; Pi, H.; Testero, S.A.; Ding, D.; Spink, E.; Leemans, E.; Boudreau, M.A.; Yamaguchi, T.; Schroeder, V.A.; Wolter, W.R.; Llarrull, L.I.; Song, W.; Lastochkin, E.; Kumarasiri, M.; Antunes, N.T.; Espahbodi, M.; Lichtenwalter, K.; Suckow, M.A.; Vakulen-ko, S.; Mobashery, S.; Chang, M. Discovery of a new class of non-β-lactam inhibitors of penicillin-binding proteins with Gram-positive antibacterial activity. J. Am. Chem. Soc., 2014, 136(9), 3664-3672.
[http://dx.doi.org/10.1021/ja500053x] [PMID: 24517363]
[19]
Suresh, L.; Sagar Vijay Kumar, P.; Poornachandra, Y.; Ganesh Kumar, C.; Babu, N.J.; Chandramouli, G.V.P. An expeditious four-component domino protocol for the synthesis of novel thiazolo[3,2-a]thiochromeno[4,3-d]pyrimidine derivatives as antibacterial and an-tibiofilm agents. Bioorg. Med. Chem., 2016, 24(16), 3808-3817.
[http://dx.doi.org/10.1016/j.bmc.2016.06.025] [PMID: 27344213]
[20]
Narwal, S.; Kumar, S.; Verma, P.K. Design, synthesis and antimicrobial evaluation of pyrimidin-2-ol/thiol/amine analogues. Chem. Cent. J., 2017, 11(52), 1-9.
[21]
Chemdraw ultra 6.0 and Chem3D ultra, Cambridge Soft Corporation, Cambridge, USA. Available from: http://www.cambridgesoft.com
[22]
Dragon software (version 1.11-2001) by Todeschini R.; Consonni V. Milano, Italy. Available from: http://www.talete.mi.it/dragon.htm
[23]
Prabhakar, Y.S. A combinatorial approach to the variable selection in multiple linear regression: Analysis of Selwood et al. Data Set-a case study. QSAR Comb. Sci., 2003, 22(6), 583-595.
[http://dx.doi.org/10.1002/qsar.200330814]
[24]
Sharma, B.K.; Pilania, P.; Singh, P.; Prabhakar, Y.S. Combinatorial protocol in multiple linear regression/partial least-squares directed rationale for the caspase-3 inhibition activity of isoquinoline-1,3,4-trione derivatives. SAR QSAR Environ. Res., 2010, 21(1), 169-185.
[http://dx.doi.org/10.1080/10629360903570545] [PMID: 20373219]
[25]
Sharma, S.; Sharma, B.K.; Sharma, S.K.; Singh, P.; Prabhakar, Y.S. Topological descriptors in modeling the agonistic activity of human A3 adenosine receptor ligands: The derivatives of 2-chloro-N(6)-substituted-4′-thioadenosine-5′-uronamide. Eur. J. Med. Chem., 2009, 44(4), 1377-1382.
[http://dx.doi.org/10.1016/j.ejmech.2008.09.022] [PMID: 18973967]
[26]
Sharma, B.K.; Pilania, P.; Sarbhai, K.; Singh, P.; Prabhakar, Y.S. Chemometric descriptors in modeling the carbonic anhydrase inhibition activity of sulfonamide and sulfamate derivatives. Mol. Divers., 2010, 14(2), 371-384.
[http://dx.doi.org/10.1007/s11030-009-9181-5] [PMID: 19657719]
[27]
Wold, S. Cross-validatory estimation of the number of components in factor and principal components models. Technometrics, 1978, 20(4), 397-405.
[http://dx.doi.org/10.1080/00401706.1978.10489693]
[28]
Kettaneh, N.; Berglund, A.; Wold, S. PCA and PLS with very large data sets. Comput. Stat. Data Anal., 2005, 48, 69-85.
[http://dx.doi.org/10.1016/j.csda.2003.11.027]
[29]
Ståhle, L.; Wold, S. Multivariate data analysis and experimental design in biomedical research. Prog. Med. Chem., 1988, 25, 291-338.
[http://dx.doi.org/10.1016/S0079-6468(08)70281-9] [PMID: 3076969]
[30]
Akaike, H. Information theory and an extension of the minimum likelihood principle. Spring Ser Stat,, 1973, 267-281.
[31]
Akaike, H. A new look at the statistical identification model. IEEE Trans. Automat. Contr., 1974, AC-19, 716-723.
[http://dx.doi.org/10.1109/TAC.1974.1100705]
[32]
Kubinyi, H. Variable selection in QSAR studies. I. An evolutionary algorithm. QSAR, 1994, 13, 285-294.
[http://dx.doi.org/10.1002/qsar.19940130306]
[33]
Kubinyi, H. Variable selection in QSAR studies. II. A highly efficient combination of systematic search and evolution. QSAR, 1994, 13, 393-401.
[http://dx.doi.org/10.1002/qsar.19940130403]
[34]
Friedman, J.H. Multivariate adaptive regression splines. Ann. Stat., 1991, 19(1), 1-67.
[35]
Gramatica, P. Principles of QSAR models validation: Internal and external. QSAR Comb. Sci., 2007, 26(5), 694-701.
[http://dx.doi.org/10.1002/qsar.200610151]
[36]
Trott, O.; Olson, A.J. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem., 2010, 31(2), 455-461.
[PMID: 19499576]
[37]
Sabe, V.T.; Ntombela, T.; Jhamba, L.A.; Maguire, G.E.M.; Govender, T.; Naicker, T.; Kruger, H.G. Current trends in computer aided drug design and a highlight of drugs discovered via computational techniques: A review. Eur. J. Med. Chem., 2021, 224(224), 113705.
[http://dx.doi.org/10.1016/j.ejmech.2021.113705] [PMID: 34303871]
[38]
Adeniji, S.E.; Uba, S.; Uzairu, A. In silico study for evaluating the binding mode and interaction of 1, 2, 4-triazole and its derivatives as potent inhibitors against Lipoate protein B (LipB). J. King Saud Univ. Sci., 2020, 32(1), 475-485.
[http://dx.doi.org/10.1016/j.jksus.2018.07.014]
[39]
Daina, A.; Michielin, O.; Zoete, V. SwissADME: A free web tool to evaluate pharmacokinetics, drug-Likeness and medicinal chemistry friendliness of small molecules. Sci. Rep., 2017, 7, 42717.
[http://dx.doi.org/10.1038/srep42717]
[40]
PreADMET server Available from: https://preadmet.bmdrc.kr https://preadmet.bmdrc.kr Accessed on Feb 11, 2022.
[41]
Di, L.; Kerns, E.H. Drug-like properties: Concepts, structure design and methods from adme to toxicity optimization, 1st ed; Elsevier: London, UK, , 2016.

Rights & Permissions Print Cite
Article Metrics
21
2
© 2024 Bentham Science Publishers | Privacy Policy