α-Glucosidase inhibitory activity of compounds
Abstract
Docking is a powerful approach to perform virtual screening on large library of compounds, rank the conformations using a scoring function, and propose structural hypotheses of how the ligands inhibit the target, which is invaluable in lead optimization. Using experimentally proven active compounds, detailed docking studies were performed to determine the mechanism of molecular interaction and its binding mode in the active site of the modeled yeast α-glucosidase and human intestinal maltase-glucoamylase. All active ligands were found to have greater binding affinity with the yeast α-glucosidase as compared to that of human homologs, intestinal, and pancreatic maltase, by an average value of ~−1.3 and ~−0.8 kcal/mol, respectively. Thirty quinoline derivatives have been synthesized and evaluated against β-glucuronidase inhibitory potential. Twenty-four analogs, which showed outstanding β-glucuronidase activity, have IC50 values ranging between 2.11 ± 0.05 and 46.14 ± 0.95 μM than standard D-saccharic acid 1,4-lactone (IC50 = 48.4 ± 1.25 μM). Structure activity relationship and the interaction of the active compounds and enzyme active site with the help of docking studies were established. In addition, Small series of morpholine hydrazones synthesized to form morpholine hydrazones scaffold. The in vitro anti-cancer potential of all these compounds were checked against human cancer cell lines such as HepG2 (Human hepatocellular liver carcinoma) and MCF-7 (Human breast adenocarcinoma). Molecular docking studies were also performed to understand the binding interaction.
Keywords
- docking studies
- α-glucosidase inhibitors
- cedryl acetate
- quinoline
- β-glucuronidase inhibitors
- morpholine hydrazone
1. Introduction
Due to the current problems and complicated challenges faced by medicinal chemists docking is a most demanding and efficient discipline in order to rational design new therapeutic agents for treating the human disease. Previously, the strategy for discovering new drugs consisted of taking a lead structure and developing a chemical program for finding analog molecules exhibiting the desired biological properties, the whole process involved several trial and error cycles patiently developed and analyzed by medicinal chemists utilizing their experience to ultimately select a candidate analog for further development. The entire process when looked at today, conceptually inelegant. These days picture are quite reverse after the emergence of computational chemistry discipline in science world. The concepts used in three-dimensional (3D) drug design are quite simple. New molecules are conceived either on the basis of similarities with known reference structures or on the basis of their complementarity with the 3D structure of known active sites. Molecular modeling is a discipline that contributes to the understanding of these processes in a qualitative and sometimes quantitative way [1, 2].
In this chapter we have presented a brief introduction of the available molecular docking methods, and their development and applications in drug discovery especially for synthetic and bio-transformed derivatives.
2. Quantum mechanical calculations and molecular docking studies of α-glucosidase inhibitors
Inhibitors of a-glucosidase regarded as a convincing therapeutic target in the development of drugs against diseases such as obesity, diabetes, HIV, and cancer [3, 4]. In this connection, few synthetic a-glucosidase inhibitors (AGI’s), such as acarbose, miglitol, and voglibose are in use since last two decades. Among the six drug classes for the management of diabetes mellitus (DM), α-glucosidase inhibitors are one of them. These inhibitors are quite target specific as they act in the intestine locally, in contrast to other oral anti-hyperglycemic drugs, which in addition, alter certain biochemical processes in the human body [5]. Therefore, discovery and development of novel
2.1. Cedrol, cedryl acetate: microbial transformed metabolites
Development of novel α-glucosidase inhibitors requires screening of a large number of compounds. Cedryl acetate (
The structures have been also optimized computationally at Hartree-Fock (HF) level of theory using valence triple-zeta plus diffuse and polarization functions (6–311++G*) basis sets for H, C, N, and O atoms to get insight into the 3D structure of these metabolites. GAMESS package [8] has been used for all quantum chemical calculations. Molecular docking studies have been also performed to delineate the ligand-protein interactions at molecular level using autodock vina programs [9]. Avogadro [10], Gabedit [11], VMD [12], and Chimera [13] have been used for the structure building, analysis, and visualization for our calculations.
2.2. α-Glucosidase inhibitory activity
Compounds one, two, four, and six were tested for inhibition of the α-glucosidase enzyme. For the first time, the cedrol (
Compound | IC50* (in mM ± S.E.M) | Binding energy in kcal/mol (Yeast a-glucosidase) |
Binding energy in kcal/mol (Human maltase glucoamylase) |
Binding energy in kcal/mol (Human pancreatic amylase; 1 U33.pdb) |
|
---|---|---|---|---|---|
C-terminal domain (3TOP.pdb) |
N-terminal domain (3L4T.pdb) |
||||
1 | 94 ± 15 | −8.4 | −6.9 | −6.5 | −7.9 |
2 | 130 ± 15 | −7.4 | −6.6 | −6.2 | −7.9 |
4 | 690 ± 16 | −7.9 | −6.3 | −7.1 | −7.6 |
6 | Inactive | −8.2 | −6.4 | −6.5 | −7.6 |
Acarbose | 780 ± 20 | — | — | — | — |
Deoxynojirimycin | 425.6 ± 8.14 | — | — | — | — |
2.3. Geometry optimization
The biological activity of ligands is a function of their 3D structures. Thus, it is crucial to have an accurate description of the ligand in 3D space. Hartree-Fock (HF) approach have been used to obtain the structural details of all metabolites that were probed through the geometry optimization in the gaseous-phase with valence triple-zeta plus diffuse and polarization functions (6–311++G*) basis sets. We found in all the compounds studied, the distance of the bond between C and OH is 1.421 Å. The optimized geometry of these compounds also, showed a short length of carbonyl groups (C=O and COC=OCH3) distance of 1.208 Å. However, the bond order was slightly higher by a value of 0.11 in the case of C=O as expected. The carbon–oxygen bond in C-OCOCH3 was slightly larger as compared to that in CO-COCH3 (1.402 and 1.338 Å, respectively) due to a lower bond order by a value of 0.233. The presence of acetate group (-O-CO-CH3) in the molecule was lowered the dipole moment of the molecule as could be seen in Table 2. These compounds with a low dipole moment seem to be most active. However, due to limited experimental inhibitory assay data, it was difficult to make a generalize conclusion.
Compound | Dipole (Debye) |
---|---|
1 | 2.03 |
2 | 3.03 |
3 | 2.87 |
4 | 3.87 |
5 | 5.07 |
6 | 3.90 |
7 | 4.09 |
8 | 3.93 |
9 | 2.65 |
10 | 6.01 |
2.4. Molecular docking studies
The most ideal is to obtain the orientation of ligand in 3D space into the protein binding site for determination of ligand activity. The ligand-protein binding mode and interaction are a very crucial to understand the catalytic activity. This modeled protein has been used as our target protein. In Addition, to elucidate their binding activity with mammalian α-glucosidase, we performed molecular docking studies of the human intestinal and pancreatic maltase glucoamylase with the active compounds. We found no significant difference in the binding affinity of active ligands with yeast α-glucosidase and the human pancreatic maltase glucoamylase. However, some differences in the binding energy were observed when ligands bind with the human intestinal maltase (Table 1). The structural changes in the binding sites of these proteins are postulated to be the cause of this less affinity of ligands toward intestinal maltase as compared to the yeast α-glucosidase. Figure 2a shows the homology model of the yeast α-glucosidase with the ligand cluster into the binding site. Figure 2b displays the close view of the binding site with the best predicted orientation of ligands
Figure 3 displays the interactions of individual metabolites one, two, four, and six with the yeast α-glucosidase protein. Polar amino acid residues, that is, Asp349 and Arg439 have strong H-bonding with the acetate group of the ligand. Cedryl acetate (
3. Molecular docking studies of novel quinoline derivatives as potent β -glucuronidase inhibitors
Glucuronidase has been used in numerous biotechnology and research applications. Glucuronidase as a gene has been studied as a positive selection marker for transformed plants, bacteria, and fungi carrying glucuronidase gene [14, 15]. It is also widely has been used for the structural investigations of proteoglycans and for research purposes in many diagnostic research laboratories [16].
3.1. Novel quinoline derivatives as potent β -glucuronidase inhibitors
Quinoline is an aromatic compound having an aza-heterocyclic ring. It possesses a weak tertiary base that can undergo both nucleophilic and electrophilic substitution reactions. The quinoline moiety is present in several pharmacologically active compounds as it does not harm humans, when it is orally absorbed or inhaled.
Various classes of compounds that showed considerable potential as
3.2. β-Glucorinadase inhibitory activity
Thirty analogs of quinoline were synthesized, which have varied degree of
The most potent inhibition was noted in analog 13 that have hydroxy groups at 3, 4-positions on the phenyl part. Making comparison of analog 13 having IC50 value 2.11 ± 0.05
Similarly, effect of substituent position was also observed in other analogs such as 4, 5, and 6 having fluoro group. If we compare analog four, a
3.3. Docking studies
Molecular docking is a useful tool to obtain data on binding mode and to validate experimental results of active derivatives within the active site of
Utilizing docking approach, we identified the stable binding mode of six most active compounds (8, 12–15, and 23) that was further used in characterizing their inhibitory activity. Compounds with the most stable binding conformation suggest to strongly alignment to the core of
We predict that the hydrogen bonding interaction between the hydroxyl at C-4 of quinoline moiety and Glu451 plays a vital role. According to the docking result compound
Compound 15 showed that hydroxyl (OH) at C-4 of quinoline moiety for compound formed hydrogen bonding with Oε2 of Glu451 side chain at a longer distance (2.24 Å) as compared to previous compound (Figure 6). In this compound the quinoline benzene rings on forms a π-donor hydrogen bond with hydroxyl (OH) of Tyr508 at (3.96 Å). It was also observed that hydrazone linkage was oxygen of carbonyl (C=O) interacts with side chain of Tyr504 through a hydrogen bond at a distance of 2.80 Å. Both form hydrogen bonds were formed between hydroxyls at
In third most active compound 12 (Figure 7), it was observed that hydroxyl (OH) at Carbon no 4 exhibited hydrogen bonding with Oε2 of Glu451 side chain with a distance of 2.11 Å. On the other hand we noted that a more stable π-donor hydrogen bond with hydroxyl (OH) of Tyr508 at (3.77 Å) and benzene ring on quinoline moiety when compared with derivative 14. Docking studies also showed the hydrazone linkage interaction of oxygen of carbonyl (C=O) with side chain of Tyr504 through a hydrogen bond with length of 2.99 Å. There is also a hydrogen bonding of hydroxyl at
4. Morpholine hydrazone scaffold: synthesis, anticancer activity, and docking studies
Cancer is a broad term to describe a disease that characterized by the uncontrolled proliferation of cells resulting from the disruption or dysfunction of regulatory signaling pathways that are normally under tight control [20, 21]. In modern life, cancer is one of the big health killers. According to the American Association for cancer research (AACR) cancer progress report 2013, it expected that 580,350 Americans would die from the various type of cancer in the same year. Luckily, ultimate evolution has made against cancer. Approximately, from 1990 to 2012 almost 1,024,400 lives saved [22].
Currently chemotherapy is an ultimate clinic treatment to repel cancer [23]. Cisplatin drug has been commonly used in cancer treatment for decades [24, 25]. Though, its clinical value tends to be inadequate by the abrupt increase of drug resistance or new side effects [26]. Consequently, the exploration of unusual chemotherapeutic agents has sparked the great attention of scientists from varied disciplines.
The morpholine scaffold has been found to be an outstanding pharmacophore in medicinal chemistry and a number of molecules having morpholine skeleton are the clinically approved drugs [27].
Recently, we have reported synthesis, characterization, anti-cancer activity, and molecular docking studies of morpholine derivatives [32]. A small series of morpholine hydrazones synthesized by treating 5-morpholinothiophene-2-carbaldehyde with different aryl hydrazides to form morpholine hydrazones scaffold (
4.1. In vitro anti-cancer activity
All synthesized analogs (
S. No. | HepG2 | MCF-7 | S. No. | HepG2 | MCF-7 |
---|---|---|---|---|---|
2 | — | 30.0 ± 1.00 | 9 | 40.0 ± 0.93 | 11.22 ± 0.22 |
4 | 7.94 ± 7.94 | — | 11 | 19.95 ± 1.31 | 41.67 ± 1.62 |
5 | 19.95 ± 0.63 | 7.08 ± 0.42 | 12 | 31.0 ± 2.26 | — |
6 | 12.59 ± 1.22 | — | 13 | 6.31 ± 1.03 | — |
7 | 20.0 ± 0.32 | 14.13 ± 1.42 | 14 | 56.23 ± 0.56 | — |
8 | — | 1.26 ± 0.34 | 15 | 15.85 ± 0.82 | — |
Doxorubicin | 6.00 ± 0.80 | — | |||
Tamoxifen | — | 11.00 ± 0.40 | |||
Cisplatin | 12.00 ± 0.33 | 15.00 ± 0.80 |
Among them compound eight was found to be the excellent inhibitor against MCF-7 with IC50 value 1.26 ± 0.34 μmol/L, which is more potent than the standard inhibitor Tamoxifen (IC50 = 11.00 ± 0.40 μmol/L). Secondly, the compound five was found to be more potent with IC50 value 7.08 ± 0.42 μmol/L almost two fold better than the standard. The analogs such as two, seven, nine, and 11 also showed potent inhibition for this cell line, while remaining analogs found to be completely in active.
Compound 13 showed potent inhibition against HepG2 with IC50 value 6.31 ± 1.03 μmol/L when compared with the standard Doxorubicin (IC50 value 6.00 ± 0.80 μmol/L). Compound four and six were found second and third most active analogs among the series with IC50 value 7.94 ± 7.94 and 12.59 ± 1.22 μM, respectively. Other analogs such as five, seven, nine, 11, 12, 14, and 15 also showed good to moderate potential.
Molecular docking studies were performed to investigate the binding mode of the active compounds.
4.1.1. Molecular docking analysis of morpholinothiophene hydrazone compounds
The molecular docking procedure was widely used to predict the binding interaction of the compound in the binding pocket of the enzyme. The 3D crystal structure of the topoisomerase II enzyme (PDB id: 4FM9) was retrieved from the protein data bank. All the ions and water molecules removed and the hydrogen atoms added to the enzyme by the 3D protonation using the Molecular Operating Environment (MOE) software. The target enzymes were then energy minimized by the default parameters of the MOE for the stability and further assessment of the enzyme. The structures of the analogs of the morpholinothiophene hydrazone compounds built in MOE and energy minimized using the MMFF94x force field and gradient 0.05. The active site pocket of the enzyme found out by the site-finder implemented in the MOE software. The synthesized compounds docked into the active site of the target enzyme in MOE by the default parameters, that is, placement: Triangle matcher, Rescoring, and London dG. For each ligand, 10 conformations generated. The top-ranked conformation of each compound used for further analysis.
Molecular docking studies predicted the proper orientation of the compound five inside the binding pocket of topoisomerase II enzyme. From the docking conformation of this active compound, we have observed a docking score of
5. Conclusion
The molecular docking is now fully recognized and integrated in the research process. In the past the emergence of this new discipline had occasionally encountered some opposition here and there. At presents, the science is mature and there are a growing number of success stories that continuously expand the armory of drug research. Several considerations that can greatly improve the success and enrichment of true bioactive hit compounds are commonly overlooked at the initial stages of a molecular docking study. In this chapter, we tried to cover several of these considerations, including few examples, of molecular docking studies of natural and synthetic analogs of potent
Acknowledgments
Sadia Sultan would like to acknowledge Universiti Teknologi MARA for the financial support under the reference number UiTM 600-IRMI/FRGS 5/3 (0119/2016), Ministry of Higher Education Malaysia. One of our author Gurmeet Kaur Surindar Singh would also like to acknowledge Universiti Teknologi MARA for the financial support under the reference number UiTM 600-IRMI/FRGS 5/3 (28/2015), Ministry of Higher Education Malaysia. We also would like to highlight and acknowledge our previous published research under reference 7, 18, and 32.
References
- 1.
Meyer EF, Swanson MS, Williams JA. Pharmacology & Therapeutics. 2000; 85 :113-121 - 2.
Abraham DJ. Burger’s Medicinal Chemistry Drug Discovery. 6th ed. Vol. 12003. pp. 847-900 - 3.
Pili R, Chang J, Partis RA, Mueller RA, Chrest FJ. A. Passaniti Cancer. Research. 1995; 55 :2920 - 4.
Zitzmann N, Mehta AS, Carrouée S, et al. Proceedings of the National Academy of Sciences of the United States of America. 1999; 96 :11878 - 5.
Hitoshi S, Nagao M, Harada T, Nakajima Y, Tanimura-Inagaki K, et al. Journal of Diabetes Investigation. 2014; 23 :206-212 - 6.
Choudhary MI, Atif M, Shah SAA, Sultan S, Erum S, Khan SN, Atta-ur-Rahman. International Journal of Pharmaceutical Science. 2014; 6 :375-378 - 7.
Sultan S, Choudhary MI, Nahar Khan S, Fatima U, Ali RA, Atif M, Atta-ur-Rahman, Fatmi MQ. European Journal of Medicinal Chemistry. 2013; 62 :764-770 - 8.
Trott O, Olson AJ. Journal of Computational Chemistry. 2010; 31 :455-461 - 9.
Hanwell MD, Curtis DE, Lonie DC, Vandermeersch T, Zurek E, Hutchison GR. Journal of Cheminformatics. 2012; 4 :17 - 10.
Allouche AR. Journal of Computational Chemistry. 2011; 32 :174-182 - 11.
Humphrey W, Dalke A, Schulten K. Journal of Molecular Graphics. 1996; 14 :33-38 - 12.
Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE. Journal of Computational Chemistry. 2004; 25 :1605-1612 - 13.
Smith RV, Rosazza J. Journal of Pharmaceutical Sciences. 1975; 64 :1737-1759 - 14.
Wenzl P, Wong L, Kwang-won K, Jefferson RA. Molecular Biology and Evolution. 2005; 22 :308-316 - 15.
Basu C, Kausch AP, Chandlee JM. Biochemical and Biophysical Research Communications. 2004; 320 :7-10 - 16.
Kuroyama H, Tsutsui N, Hashimoto Y, Tsumuraya Y. Carbohydrate Research. 2001; 333 :27-39 - 17.
Khan KM, Rahim F, Halim SA, Taha M, Khan M, Perveen S, Haq Z, Mesaik MA, Choudhary MI. Bioorganic & Medicinal Chemistry. 2011; 19 :4288 - 18.
Taha M, Sultan S, Nuzar HA, Imran S, Ismail NH, Rahim F, Ullah H. Bioorganic and Medicinal Chemistry. 2016; 4 :3596 - 19.
Taha M, Ismail NH, Imran S, Ali M, Jamil W, Uddin N, Kashif SM. RSC Advances. 2016; 6 :3276 - 20.
Chen WS, Ou WZ, Wang LQ, et al. Dalton Transactions. 2013; 42 :15678-15686 - 21.
Rahman FU, Ali A, Guo R, et al. Dalton Transactions. 2015; 44 :2166-2175 - 22.
Sawyers CL, Abate-Shen C, Anderson KC, et al. AACR cancer progress report 2013. Clinical Cancer Research. 2013; 19 :S1-S98 - 23.
Robert NJ, Diéras V, Glaspy J, et al. Journal of Clinical Oncology. 2011; 29 :1252-1260 - 24.
Rosenberg B, Van Camp L, Krigas T. Nature. 1965; 205 :698-699 - 25.
Sak A, Grehl S, Engelhard M, et al. Clinical Cancer Research. 2009; 15 :2927-2934 - 26.
Galluzzi L, Senovilla L, Vitale I, et al. Oncogene. 2012; 31 :1869-1883 - 27.
Andrs M, Korabecny J, Jun D, et al. Journal of Medicinal Chemistry. 2015; 58 :41-71 - 28.
Dugave C, Demange L. Chemical Reviews. 2003; 103 :2475-2532 - 29.
Arrieta A, Oteagui D, Zubia A, et al. The Journal of Organic Chemistry. 2007; 72 :4313-4322 - 30.
Polak A. Annals of New York Academy of Sciences. 1988; 554 :221-228 - 31.
Kerkenaar A. Prous Science Publ., 1987; 1 :523-542. R.G.M.P - 32.
Taha M, Shah SAA, Afifi M, Sultan S, Ismail NH. Chinese Chemical Letters. 2017; 28 :607-611