Fungal transformation of cedryl acetate and α-glucosidase inhibition assay, quantum mechanical calculations and molecular docking studies of its metabolites

Abstract

The fungal transformation of cedryl acetate (1) was investigated for the first time by using Cunninghamella elegans. The metabolites obtained include, 10β-hydroxycedryl acetate (3), 2α, 10β-dihydroxycedryl acetate (4), 2α-hydroxy-10-oxocedryl acetate (5), 3α,10β-dihydroxycedryl acetate (6), 3α,10α-dihydroxycedryl acetate (7), 10β,14α-dihydroxy cedryl acetate (8), 3β,10β-cedr-8(15)-ene-3,10-diol (9), and 3α,8β,10β -dihydroxycedrol (10). Compounds 1, 2, and 4 showed α-glucosidase inhibitory activity, whereby 1 was more potent than the standard inhibitor, acarbose, against yeast α-glucosidase. Detailed docking studies were performed on all experimentally active compounds to study the molecular interaction and 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 homolog, the intestinal maltase, by an average value of approximately −1.4  kcal/mol, however, no significant difference was observed in the case of pancreatic amylase.

Introduction

It is well known that odoriferous essential oils, which are of high value in the perfume trade, contain some minor constituents which can be regarded as the real odor carriers of these products. This has been demonstrated by the studies carried out on cedrol (2), which is a major constituent of essential oils of Juniperus species [1]. Cedrol (2) possesses a rigid tricyclic sesquiterpene structure and is known to have sedative effects [2]. It is abundantly available as a fragrance or as a synthon for synthesis of related compounds. The microbiological hydroxylation of cedrol (2) by Beauveria species [3], and Cephalosporium aphidicola [4], has been shown to take place predominantly at C(3). Hydroxylations of compound 2 with Curvularia lunata [5], Rhizopus stolonifer [6], and Streptomyces bikiniensis [6] have been less regiospecific, and generally take place at C(2), C(3), C(4), C(9), C(10), and C(12).

The zygomycete fungi of the genus Cuninghamella have the ability to metabolize drugs in a manner similar to that in mammals. In the course of our work on microbial transformation of bioactive natural products [7], [8], [9], [10], [11], [12], [13], we have studied the transformation of various sesquiterpenes such as (−) ambrox, (+) sclareolide, (+) isolongifolene and (+) isolongifolol [14], [15], [16]. In the present study, we have chosen cedryl acetate (1), a tricyclic sesquiterpene isolated from the plant Psidium caudatum [17], as a model compound and investigated its metabolism by Cunninghamella elegans to obtain interesting metabolites with unique structures, as well as to assess the directing role of the acetate group at C(8).

α-Glucosidase inhibitors have been used for the control of blood glucose levels via control of the degradation of dietary disaccharides and starch. Glucosidase inhibitors are valuable in a number of applications such as their use in the study of protein glycosylation and control of viral infections through interference with the, normal glycosylation of viral coat protein [18]. In an ongoing project aimed to develop new α-glucosidase inhibitors, we screened a large number of compounds including cedryl acetate (1) and cedrol (2). Both exhibited potent α-glucosidase inhibitory activity. Based on this we carried out the microbial transformation of the most potent compound 1, and screened the transformed products for the same activity. We have reported several α-glucosidase inhibitors more potent than acarbose [19]. However, this is the first report describing the α-glucosidase inhibitory activity of cedrol (2), cedryl acetate (1), and some of the transformed products of 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 [20] have 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 program [21]. Avogadro [22], Gabedit [23], VMD [24] and Chimera [25] have been used for the structure building, analysis and visualization for our calculations.