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QSAR of Antioxidants
Thaipong, K., Boonprakob, U., Crosby, K., Cisneros-Zevallos, L., & Byrne, D. H. (2006). Comparison of ABTS, DPPH, FRAP, and ORAC assays for estimating antioxidant activity from guava fruit extracts. Journal of Food Composition and Analysis, 19(6-7), 669–675. doi:10.1016/j.jfca.2006.01.003
Todeschini, R., Consonni, V., & Pavan, M. (2001). DRAGON-software for the calculation of molecular descriptors. Release 1.12 for Windows. Retrieved from http://www.disat.unimib.it/chm
Valko, M., Leibfritz, D., Moncol, J., Cronin, M., Mazur, M., & Telser, J. (2007). Free radicals and anti­oxidants in normal physiological functions and human disease. The International Journal of Biochemistry & Cell Biology, 39(1), 44–84. doi:10.1016/j.biocel.2006.07.001 PMID:16978905
Vertuani, S., Angusti, A., & Manfredini, S. (2004). The antioxidants and proantioxidants network: An overview. Current Pharmaceutical Design, 10(14), 1677–1694. doi:10.2174/1381612043384655 PMID:15134565
Wold, S. (1978a). Cross-validatory estimation of the number of components in factor and principal component models. Technometrics, 20(4), 397–405. doi:10.1080/00401706.1978.10489693
Wold, S. (1991b). Validation of QSARs. Quantitative Structure Activity Relationship, 10(3), 191–193. doi:10.1002/qsar.19910100302
Wold, S., Johansson, E., & Cocchi, M. (1993). PLS—Partial least squares projections to latent structures. In 3D-QSAR in drug design, theory, methods, and applications (pp. 523–550). ESCOM Science Publishers.
Wolf, G. (2005). The discovery of the antioxidant function of vitamin E: The contribution of Henry A. Mattill. The Journal of Nutrition, 135(3), 363–366. PMID:15735064
Xu, L., & Zhang, W. J. (2001). Comparison of different methods for variable selection. Analytica Chimica Acta, 446(1-2), 477–483. doi:10.1016/S0003-2670(01)01271-5
Yamagami, C., Akamatsu, M., Motohashi, N., Hamadaa, S., & Tanahashia, T. (2005). Quantitative structure–activity relationship studies for antioxidant hydroxybenzalacetones by quantum chemical and 3-D-QSAR (CoMFA) analysis. Bioorganic & Medicinal Chemistry Letters, 15(11), 2845–2850. doi:10.1016/j.bmcl.2005.03.087 PMID:15911266
KEY TERMS AND DEFINITIONS
Antioxidant: A stable molecule that donates an electron to a free radical and neutralizes it, therefore reducing its capability to damage.
Computer Aided-Drug Design (CADD): The effective design of chemical structures with the desir­able therapeutic properties, it is a well-established area of computer aided molecular design (CAMD).
Curcumin: Naturally phenolic compound which is isolated from Curcuma longa Linn. It is widely used as food pigment and it has been reported to have many biological activities especially the favorable effect on antioxidation.
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QSAR of Antioxidants
Flavonoids: Groups of naturally occurring compounds of low molecular weight plant products,
based on the parent compound, flavone (2-phenylchromone) and have shown potential for application in a variety of pharmacological targets.
Free Radicals: Unstable molecules that lose one of its electrons and therefore become unbalanced
and highly reactive.
In Silico Methods: New developments in chemical testing that rely on computer simulation or
modeling. In silico pharmacology defines the use of this information in the design of computational models or simulations that can be used to make predictions, suggest hypotheses, and ultimately supply discoveries in therapeutics.
QSAR: Quantitative structure activity relationships is a way of finding a simple equation that cor-
relates structural molecular features (descriptors) with physicochemical properties, such as biological activities for a set of compounds by means of statistical methods.
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Chapter 7
QSAR Studies on Bacterial
Efux Pump Inhibitors
Khac-Minh Thai
University of Medicine and Pharmacy at HCMC,
Vietnam
Trong-Nhat Do
University of Medicine and Pharmacy at HCMC,
Vietnam
Thanh-Dao Tran
University of Medicine and Pharmacy at HCMC, Vietnam
University of Medicine and Pharmacy at HCMC,
University of Medicine and Pharmacy at HCMC,
Thuy-Viet-Phuong Nguyen
Vietnam
Duc-Khanh-Tho. Nguyen
Vietnam
ABSTRACT
Antimicrobial drug resistance occurs when bacteria undergo certain modifications to eliminate the effectiveness of drugs, chemicals, or other agents designed to cure infections. To date, the burden of resistance has remained one of the major clinical concerns as it renders prolonged and complicated treatments, thereby increasing the medical costs with lengthier hospital stays. Of complex causes for bacterial resistance, there has been increasing evidence that proved the significant role of efflux pumps in antibiotic resistance. Coadministration of Efflux Pump Inhibitors (EPIs) with antibiotics has been considered one of the promising ways not only to improve the efficacy but also to extend the clinical utility of existing antibiotics. This chapter begins with outlining current knowledge about bacterial efflux pumps and drug designs applied in identification of their modulating compounds. Following, the chapter addresses and provides a discussion on Quantitative Structure-Activity Relationship (QSAR) analyses in search of novel and potent efflux pump inhibitors.
DOI: 10.4018/978-1-4666-8136-1.ch007
Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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QSAR Studies on Bacterial Efux Pump Inhibitors
INTRODUCTION
Antimicrobial drugs have been important tools of healthcare in several decades because of their effective­ness in control of bacterial infections. Unfortunately, soon after their invention it was realized that some pathogens rapidly developed resistance to antibiotics (Neu, 1992; Wood, Gold, & Moellering Jr, 1996). People infected with antimicrobial-resistant organisms are more likely to have longer, more expensive hos­pital stays, and may be more likely to die as a result of the infection. Initially, this problem was overcome by discovery of new classes of antibiotics such as aminoglycosides, macrolides and glycopeptides, but the bacteria rapidly showed an impressive array of defensive mechanisms that conferred on them, resistance to many modes of attack (Wood et al., 1996). The main mechanisms whereby the bacteria develop resis­tance to antimicrobial agents include enzymatic inactivation (Bush & Miller, 1998; Sabatini et al., 2012), modification of the antibiotic attack site(s) (Ruiz, 2003; Sabatini et al., 2012), and reduction of intracellular drug concentration by changes in membrane permeability (Nikaido, 2003; Sabatini et al., 2012) or by the overexpression of efflux pumps (Li & Nikaido, 2009; Sabatini et al., 2012).
One primary mechanism of antibiotic resistance is extrusion of the foreign chemical, which is termed efflux. In 1980, tetracycline was reported that it could be actively effluxed from the bacterial cell (Mc­Murry, Petrucci, & Levy, 1980). From then on, many efflux-related mechanisms have been discovered. Overexpression of these efflux pumps may lead to antibiotic resistance. While efflux pump proteins are present in both Gram-positive and Gram-negative bacteria and also in eukaryotes, antibiotic resistance due to efflux is more of a problem in Gram-negative bacteria than in Gram-positive bacteria (Nikaido, 1996). This is because the presence of an outer membrane in Gram-negative bacteria shows comparatively lower permeability and complements the efflux activity of these pumps. Besides, studies of efflux pumps in Gram-negative bacteria have got more complicated as their double-membrane cells allow the expression of a tripartite efflux pump system such as AcrA/AcrB/TolC in Enterobacteriaceae, or MexA/MexB/OprM in Pseudomonas aeruginosa. One plausible practice to fight against multidrug efflux systems (MES) is the combination of conventional antimicrobial agents/antibiotics with small molecules that block MES known as multidrug efflux pump inhibitors (EPIs). An array of approaches in academic and industrial research settings, varying from high-throughput screening (HTS) ventures to bioassay guided purification and deter­mination, have yielded a number of promising EPIs in a series of pathogenic systems (Tegos et al., 2011).
Up to now, most inhibitors of efflux pumps have been discovered through traditional random screening of synthetic compounds or natural products libraries. The assays used are very simple and easily adapted to high-throughput screening. An alternative approach is to screen libraries of known drugs. The identifica­tion of a novel mode of action in an approved drug could considerably shorten the development route and lessen the risks associated with a new chemical entity.
OVERVIEW OF BACTERIAL EFFLUX PUMPS AND ANTIBIOTIC RESISTANCE
Bacterial Efflux Pumps
Efflux pumps in Gram-positive bacteria can be categorized into four families (Handzlik, Matys, & Kieć-Kononowicz, 2013), namely ABC (ATP-binding cassette) (Higgins, 2001), MFS (major facilitator superfamily) (Saier Jr et al., 1999), SMR (small multidrug resistance) (Chung & Saier Jr, 2001) (Jack, Yang, & H Saier, 2001), and MATE (multidrug and toxic compound extrusion) (Hvorup et al., 2003).
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QSAR Studies on Bacterial Efux Pump Inhibitors
For Gram-negative bacteria, many pump systems including Campylobacter jejuni (CmeABC) (Pumbwe & Piddock, 2002) (Lin, Michel, & Zhang, 2002), Escherichia coli (AcrAB-TolC, AcrEF­TolC, EmrB, EmrD) (Poole, 2000), Pseudomonas aeruginosa (MexAB-OprM, MexCD-OprJ, MexEF-OprN and MexXY-OprM) (Poole, 2000), Salmonella typhimurium (AcrAB) (Nikaido, 2001) have been described. These pumps basically belong to five major families, including the MFS (major facilitator superfamily), MATE (multidrug and toxic extrusion), SMR (small multi-drug resistance), ABC (ATP-binding cassette) and RND (resistance-nodulation-division) families (Saier Jr, 1998). Co­expression of multiple types of efflux pumps can bring an additive or multiplicative effect on drug resistance (Lee et al., 2000).
MFS is the largest superfamily of transporters involved in symport, uniport, or antiport of vari­ous small solutes (Saier Jr et al., 1999). Examples include sugars, neurotransmitters, amino acids, Krebs cycle metabolites, and importantly, drugs. Most MFS efflux pumps have 400-600 amino acid residues and possess either 12 or 14 putative transmembrane domains. In MFS transporters, negatively charged amino acid residues located in transmembrane helices appear to play a critical role in the protonation/deprotonation step during transport. Typical MFS efflux pumps in Gram­positive bacteria include NorA, NorB, MdeA, Tet38 (Staphylococcus aureus), LmrB, Bmr, Bmr3, Blt (Bacillus subtilis), MefA (Streptococcus pyogenes), MefE (Streptococcus pneumoniae) or CmlR (Streptococcus coelicor) (Borges-Walmsley, McKeegan, & Walmsley, 2003; Handzlik et al., 2013; Jarmuła, Obłąk, Wawrzycka, & Gutowicz, 2010; Markham & Neyfakh, 2001; Paulsen, Brown, & Skurray, 1996; Poole, 2005).
The SMR family consists of small multidrug transporters widespread among eubacteria (Bay, Rom­mens, & Turner, 2008). These proteins are about 100-amino acid residues long, with four transmembrane helices. The examples of SMR efflux pumps in Gram-positive bacteria are EbrAB (Bacillus subtilis) or Smr, QacG, QacH (Staphylococcus aureus) (Jarmuła et al., 2010; Kikukawa, Nara, Araiso, Miyauchi, & Kamo, 2006; Putman, van Veen, & Konings, 2000).
All ABC transporters contain four essential modules, two nucleotide binding domains (NBDs) and two transmembrane domains (TMDs). These four modules can be encoded by four separate genes or fused pairwise in all possible combinations (Hollenstein, Dawson, & Locher, 2007; Lubelski, Konings, & Driessen, 2007). Bacterial MultiDrug Resistance (MDR) is usually homo- or heterodimers in which one NBD is fused to one TMD. LmrA (Lactococcus lactis) and Rv1217c-Rv1218c (Mycobacterium tuberculosis) (Borges-Walmsley et al., 2003; Jarmuła et al., 2010; Wang et al., 2013) belong to this transport protein family.
The RND transporters are responsible for the high intrinsic antibiotic resistance which can be seen in Gram-negative bacteria, one component of the notorious “natural superbug” phenotype. They are also found in Gram-positive bacteria where their functions are largely unknown (Tseng et al., 1999). RND transporters are homo- or heterotrimers consisting of promoters of about 1100-amino acid residues in size. Each promoter consists of the 12 transmembrance helices and a large periplasmic domain.
Most MATE transporters consist of 400-550 amino acid residue polypeptides with 12 putative trans­membrane helices which share about 40% sequence similarity. An example of MATE efflux pump in Gram-positive bacteria is MepA protein found in Staphylococcus aureus (Handzlik et al., 2013; Omote, Hiasa, Matsumoto, Otsuka, & Moriyama, 2006; Wasaznik, Grinholc, & Bielawski, 2008). Currently, no high-resolution structures are available for this family of transporters. Secondary structure predictions showed the symmetric repetition of conserved regions in the N- and C-terminal halves of the proteins suggesting a gene duplication event.
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QSAR Studies on Bacterial Efux Pump Inhibitors
Bacterial Efflux Pump Inhibitors
For Gram-positive bacteria, the search for new EPIs performed in the last decade was mostly focused on the NorA of S. aureus (Handzlik et al., 2013). Many approaches have been made to explore new EPIs. EPI activity is often found by antibiotic–EPI combination assays using efflux-proficient and -deficient S. aureus strain pairs. Efflux inhibition is verified with fluorometric efflux assays using ethidium bro­mide, a nonspecific DNA intercalator. A number of EPIs targeting S. aureus NorA have been identified including current chemotherapeutic agents used as EPIs (e.g. reserpine, P-gp inhibitors, verapamil, proton pump inhibitors, phenothiazines, thioxanthenes, paroxetine and COX-2 inhibitors), naturally oc­curing EPIs (e.g. 4’,5’-O-dicaffeoylquinic acid, N-trans-feruloyl 4’-O-methyldopamine, resin glycosides, pheophorbide A, diterpenes, flavonoids and capsaicin) and synthetic EPIs (e.g. piperine analogs, fluoro­quinolone analogues, indole-based inhibitors, berberine-INF55 hybrids, substituted dihydronaphthalene and mesolonic compounds); of which hybrid molecules were suggested for further investigation. An EPIs must be nontoxic and highly selective in order to be a potential candidate for clinical use. In this context, reserpine cannot enter further developments due to its neurotoxicity at concentrations required to inhibit NorA (Markham & Neyfakh, 1996; Schindler, Jacinto, & Kaatz, 2013; Zhang & Ma, 2010).
For Gram-negative bacteria, promethazine, a phenothiazine, combines with penicillin G have been used to inhibit RND pumps in E. coli (Lehtinen & Lilius, 2007), as well as inhibit ABC pumps in yeast (Kolaczkowski, Michalak, & Motohashi, 2003). Phenothiazines are able to reverse MDR phenotypes of pathogenic bacteria like P. aeruginosa or S. typhimurium (Michalak, Wesolowska, Motohashi, Molnar, & Hendrich, 2006; Molnar et al., 1996). Paroxetine can inhibit AcrAB-TolC pump of E. coli (German, Kaatz, & Kerns, 2008; Kaatz, Moudgal, Seo, Hansen, & Kristiansen, 2003; Munoz-Bellido, Munoz-Criado, & Garcıa-Rodrıguez, 2000). It is pointed out that arylpiperazines reverse MDR in bacteria overexpressing AcrAB and AcrEF pumps. Moreover, NMP (1-naphthylmethylpiperazine) is the most effective inhibitor that enhances the intracellular concentration of drugs like chloramphenicol, tetracycline, linezolid, mac­rolides and fluoroquinolones (Kern et al., 2006). The structures with dihalogens among arylpiperidines have been shown to restore the antimicrobial activity of linezolid in E. coli (Thorarensen et al., 2001).
Quinolines have been shown the ability to re-establish various antibiotic activities like quinolones, cyclines and chloramphenicol. They are now applied as broad spectrum inhibitors for resistant E. aero- genes and K. pneumoniae to make them susceptible for the antimicrobials (Chevalier et al., 2004). The analogs of aminoglycoside paromomycin have been applied as inhibitors of the efflux pumps using the bacterium H. influenzae (Alekshun & Nelson, 2004). AcrAB efflux pump was inhibited by using antibodies in E. coli and this strategy has been patented (Oethinger & Levy, 2002). A recent report has introduced the use of antisense phosphorothioate oligonucleotide encapsulated in a novel anion liposome to restore the activity of fluoroquinolones in E. coli (Meng et al., 2011). This method could be utilized for a wide variety of pumps with known gene sequences. Using antibody or parts thereof in order to inhibit MexAB-OprM pumps in P. aeruginosa has been patented (Inoko & Yoshihara, 2011).
In addition, a list of about 200,000 synthetic and natural compounds was tested with the aim of find­ing potential compounds preventing the activity of levofloxacin against P. aeruginosa (Chamberland et al., 2002; Coban, Ekinci, & Durupinar, 2004; Lomovskaya et al., 2001; Lomovskaya & Watkins, 2001; Renau et al., 1999). MC-207, 110 (Phenylalanine Arginyl β - Naphthylamide/PAβN) was identified as an inhibitor of Mex pumps. The crystal structure of E. coli AcrB has been solved in the presence of MC- 207 and its binding to the pump has been proved (Edward, Aires, McDermott, & Nikaido, 2005). This compound has been shown to decrease the frequency of the emergence of highly levofloxacin resistant
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QSAR Studies on Bacterial Efux Pump Inhibitors
P. aeruginosa strains and also to reduce the intrinsic resistance of the bug to levofloxacin 8-folds (Co­ban et al., 2004; Lomovskaya et al., 2001; Renau et al., 1999). It is a competitive inhibitor of the efflux pumps and operates by binding to the same pocket or at a site closer to the antibiotic substrate binding site (Mahamoud, Chevalier, Alibert-Franco, Kern, & Pagès, 2007; Pagès, Masi, & Barbe, 2005). The compound has not only restored the activity of levofloxacin but has also been found to potentiate the activity of other antibiotics such as oxazolidinones, chloramphenicol, rifampicin, macrolides/ ketolides (Zechini & Versace, 2009). Furthermore, it has these effects not only for P. aeruginosa, but also for K. pneumoniae, C. jejuni, E. coli, S. typhimurium and E. aerogenes (Malléa, Chevalier, Eyraud, & Pagès, 2002; Mazzariol, Tokue, Kanegawa, Cornaglia, & Nikaido, 2000).
Drug Design Targets Bacterial Efflux Pumps
Structure-based drug design plays an important part of the success story in the discovery of new drug leads. It is known that a thorough understanding of MDR transporter structure and function, as well as mechanism, would considerably facilitate the drug discovery. There have been, however, the scarcity of atomic structures of these membrane proteins due to difficulties related to the process of protein expression and crystallization (Chang, Ray, & Swaan, 2005; Rosenbusch, 2001). Additionally, it was suggested that there are some limitations associated with protein structures solved by crystallography that should be taken into consideration (DePristo, de Bakker, & Blundell, 2004). To date, the number of available bacterial efflux pump structures is still small compared to the number of identified bacterial transporters, which were described in previous reviews (Delmar, Su, & Yu, 2014; S. Kumar & Varela, 2012; Li & Nikaido, 2009; Van Bambeke & Lee, 2006; Zechini & Versace, 2009). This has hindered the computer-aided discovery of efflux pump chemosensitizers. The Table 1 enumerates MDR transport­ers with determined structures, of which recently structure-found transporters have mostly belonged to Escherichia coli and Pseudomonas aeruginosa.
Regarding MDR Gram-negative bacteria, RND transporter AcrAB-TolC and its homologues (including MexAB-OprM and MexXY-OprM) are main contributors to bacterial survival during infection. Certain studies on Pseudomonas aeruginosa MexAB-OprM pump, using both ligand-based and structure-based pharmacophore approaches in combination with docking method, recommended several important structural modification favoring inhibitory potentiation of known inhibitors: the incorporation of a hydrophobic group at the 2-position of the pyridopyrimidine scaffold or the inclusion of an olefin spacer between the tetrazole and pyridopyrimidine scaffold can render a boost in potency of this derivative, hydrophilic substitution was feasible on a piperidine moiety at the 2-position without adversely affecting activity, paving the way for the increase of aqueous solubility (Nakayama et al., 2004); in another study, the compound ASN05108137 exhibited maximum similarity to the pharmacophore hypothesis of MC207110, the first inhibitor against MexAB-OprM efflux system of P.aeruginosa, and also showed the druglikeness property satisfying the Lipinski’s rule of five (Aparna, Mohanalakshmi, Dineshkumar, & Hopper, 2014).
In a recent study, the crystal structure of AcrB and MexB bound to the pyridopyrimidine derivative ABI­PP was determined. This result provides detailed insight into the mechanism by which the inhibitor ABI-PP acts on RND transporters thereby generating a structural basis for designing a universal inhibitor of multidrug efflux transporters (Nakashima et al., 2013). A pharmacophore study was aimed to circumvent the drug re­sistance in P.aeruginosa and E.coli by identifying natural compounds from plants having effect on MexB and its counterpart AcrB. Lanatoside C and daidzein were found to have a high possibility to counteract the MDR pumps in the resistance bacteria (Aparna, Dineshkumar, Mohanalakshmi, Velmurugan, & Hopper, 2014).
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QSAR Studies on Bacterial Efux Pump Inhibitors
Table 1. Bacterial MDR efflux pumps with determined X-ray structures
Bacterial Strain Protein
Family
Bacillus subtilis MFS BmrR 3Q5P 2.94 tetracycline (Bachas, Eginton,
Aquifex aeolicus MFS EmrA 4TKO 2.85 - (Hinchliffe et al.,
Neisseria gonorrhoeae RND MtrD 4MT1 3.54 - (H.-T. Lei et al.,
Campylobacter jejuni RND CmeR 3QQA 2.20 taurocholic acid (H. T. Lei et al.,
Vibrio cholerae MATE NorM 3MKT 3.65 - (He et al., 2010)
Escherichia coli ABC MacA 3FPP 2.99 - (Yum et al., 2009)
RND AcrB 4CDI 3.70 - (Du et al., 2014)
Pseudomonas aeruginosa RND MexB 3W9I 2.71 dodecyl-β-D-
(From Protein Data Bank).
Efflux
Pump
TolC 2VDE 3.20 chloride ion (Bavro et al., 2008)
OprM 3D5K 2.40 chloride ion and
PDB Code Resolution (Å) Bound Ligand Reference and
3Q5R 3.05 kanamycin (Bachas et al.,
3Q5S 3.10 acetylcholine (Bachas et al.,
3QPS 2.35 cholic acid (H. T. Lei et al.,
3MKU 4.20 rubidium ion (He et al., 2010)
4C48 3.30 dodecyl-β-D-
maltoside and nickel (II) ion
3W9H 3.05 ABI-PP (Nakashima et al.,
2HRT 3.00 citrate anion (Seeger et al.,
1EK9 2.10 - (Koronakis, Sharff,
maltoside
3W9J 3.15 dodecyl-β-D-
maltoside and ABI-PP
2V50 3.00 dodecyl-β-D-
maltoside
sodium ion
1WP1 2.56 - (Akama et al.,
Year of Release
Gunio, & Wade,
2011)
2011)
2011)
2014)
2014)
2011)
2011)
(Du et al., 2014)
2013)
2006)
Koronakis, Luisi, & Hughes, 2000)
(Nakashima et al.,
2013) (Nakashima et al.,
2013)
(Sennhauser, Bukowska, Briand, & Grütter, 2009)
(Phan et al., 2010)
2004)
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QSAR Studies on Bacterial Efux Pump Inhibitors
Another pharmacophore hypothesis was generated by the HipHop method to analyze the structure­activity relationships of active sites of protein-ligand interactions thereby increasing the knowledge of structure and mechanism of RND-type AdeABC EPIs in Acinetobacter baumannii. The achieved 3D common feature pharmacophore model revealed that two hydrogen bond acceptors (HBA) and three hydrophobic aromatic (HpAr) were found to be significant for binding to the active site of the target protein. Three HpAr features displayed the required substitution of bulky aromatic moieties, while two HBA atoms or groups were necessary in the molecule to bind to the target protein (Yilmaz et al., 2014).
More recently, structures of interest for rational design include the advent of the pseudo-atomic structure of complete AcrAB-TolC in complex with AcrZ, a modulatory protein partner from E.coli. It was found that the studied structure is likely to be similar to homologous assemblies in pathogenic spe­cies that infect humans such as Vibrio cholerae, P.aeruginosa, Neisseria gonorrhoeae and Salmonella enterica (Du et al., 2014).
QSAR APPROACHES IN SEARCH FOR EFFLUX PUMP INHIBITORS
QSAR Approaches in Search for EPIs in Gram Positive Bacteria
The methicillin-resistant Staphylococcus aureus (MRSA) is one of the most frequent nosocomial pathogens in developed countries. Among the Gram positive bacteria, S.aureus is responsible for a large number of deaths worldwide. MRSA is resistant to a variety of antibiotics including tetracyclines, aminoglycosides and fluoroquinolones. Studies found that NorA is a predominant protein efflux pump responsible for efflux mechanisms in S.aureus (Sabatini et al., 2012). For these reasons, NorA has been one of the most studied Gram-positive bacterial efflux pumps in the search for efflux pump inhibitors. Although other protein targets have been investigated and there are some newly found derivatives proved to have inhibitory activities towards those proteins, there is still a lack of QSAR studies focused on such inhibitors. With respect to NorA in S.aureus, while there have been a number of natural and synthetic product known to be inhibitors of NorA efflux pump, there is still a need to discover new and potent NorA inhibitors. However, the slow emergence of high-resolution structure of this pump has hampered the intelligent design of its modulators, necessitating a ligand-based approach. With currently available structural data regarding known NorA inhibitors, robust QSAR models were generated, paving the way for preliminary identification of compounds with NorA inhibitory activities, whereby more thorough research can be conducted in order to identify the inhibitors with high potentiality to become future “adjuvants” of antibiotics.
QSAR of Piperine Analogs for Bacterial NorA Efflux Inhibitors
Piperine, a major component of Piper nigrum, is a putative bacterial EPI (Khan, Mirza, Kumar, Verma, & Qazi, 2006). In addition, piperine has been found to be associated with several activities (Amit Nargotra et al., 2009): inhibiting several cytochrome P450-mediated pathways and phase II reactions in animal models (Atal, Zutshi, & Rao, 1981; Singh, Dubey, & Atal, 1986); inhibiting human P-glycoprotein (Bhardwaj et al., 2002) and potentially inhibiting rat hepatic microsomal constitutive and inducible cytochrome P450 activities (Koul et al., 2000).
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×
QSAR Studies on Bacterial Efux Pump Inhibitors
After screening a chemical library consisting of 200 structurally diverse compounds for inhibition of the NorA efflux pump, three piperine analogues, namely SK-20, SK-56 and SK-29, were found to be the most potent inhibitors of the NorA efflux pump. The structural adjustments of piperine that can lead to bacterial efflux pump inhibitors with significantly higher activities include: (i) the introduction of an alkyl group at the C-4 position mainly contributes to potentiation, and ethyl and n-propyl show highest effect; (ii) substitution of a piperidinyl moiety by an aromatic amine such as anisidine or toluidine renders greatest potentiation, whereas other substituents such as aniline, amino esters, pyrollidine, azepine and alkylamines (except isobutyl amine) appear to be less effective; (iii) unsaturation is a critical feature for potentiation, as di- and tetra-hydro piperine show much less activity than corresponding unsaturated analogues; (iv) the omission of amide carbonyl group leads to a decrease in potentiation; and (v) the presence of a 3,4-methylenedioxyphenyl or 4-methoxyphenyl group in structure of piperine derivatives can enhance potentiation (A. Kumar et al., 2008).
In the QSAR study of piperine analogs for bacterial NorA efflux pump inhibitors (Amit Nargotra et al., 2009), researchers at Indian Institute of Integrative Medicine, India employed the Cerius2 4.10 software package (from Accelrys Inc.) to calculate 2D descriptors differentiating the molecules in terms of their size, degree of branching, flexibility, and overall shape. A total set of 25 compounds was divided into 20 molecules in training set and 5 molecules in test set. The general structures of the compounds are given in Figure 1.
All the molecules were energy minimized using the Cerius2 OFF module with default parameters of Smart Minimizer. The QSAR model was generated using the genetic function approximation (GFA) method and its statistical significance was validated using randomization procedure. As a result, the final QSAR equation after removal of outliers was as follows:
log (PF) = 0.84 – 0.002
(N = 17; LOF = 0.015; r
Hf + 0.01 ×Jurs_PNSA-1 – 0.01 ×Shadow_XZ
2
= 0.962;
2
r
= 0.953; F-test = 110.08; LSE = 0.006; r = 0.981; q2 = 0.917)
adj
where PF (potentiation factor) of the compounds (efflux pump inhibitors – EPI) express the reduc­tion in the MIC values of ciprofloxacin, hence represent the potentiation of activity of ciprofloxa­cin in the presence of piperine analogs based efflux pump inhibitors; N is number of compounds
in training set, LOF is lack of fit score, r
2
is squared correlation coefficient, r
2
is square of ad-
adj
justed correlation coefficient, F-test is a variance-related static which compares two models differ­ing by one or more variables to see if the more complex model is more reliable than the less com-
Figure 1. General structures of compounds taken for QSAR study
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