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Research ArticleVirtual Screening of Acetylcholinesterase Inhibitors Using theLipinskis Rule of Five and ZINC Databank
Pablo Andrei Nogara,1 Rogrio de Aquino Saraiva,2 Diones Caeran Bueno,1
Llian Juliana Lissner,1 Cristiane Lenz Dalla Corte,1 Marcos M. Braga,1
Denis Broock Rosemberg,1 and Joo Batista Teixeira Rocha1
1Departamento de Bioqumica e Biologia Molecular, Programa de Pos-Graduacao em Ciencias Biologicas: Bioqumica Toxicologica,Centro de Ciencias Naturais e Exatas, Universidade Federal de Santa Maria, 97105-900 Santa Maria, RS, Brazil2Grupo de Estudos emBioqumica, Farmacologia e ToxicologiaMolecular, UnidadeAcademica de SerraTalhada,Universidade FederalRural de Pernambuco, 56900-000 Serra Talhada, PE, Brazil
Correspondence should be addressed to Joao Batista Teixeira Rocha; firstname.lastname@example.org
Received 23 May 2014; Revised 16 July 2014; Accepted 17 July 2014
Academic Editor: Miroslav Pohanka
Copyright 2015 Pablo Andrei Nogara et al. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.
Alzheimers disease (AD) is a progressive and neurodegenerative pathology that can affect people over 65 years of age. It causesseveral complications, such as behavioral changes, language deficits, depression, and memory impairments. One of the methodsused to treat AD is the increase of acetylcholine (ACh) in the brain by using acetylcholinesterase inhibitors (AChEIs). In this study,we used the ZINC databank and the Lipinskis rule of five to perform a virtual screening and a molecular docking (using AutoDock Vina 1.1.1) aiming to select possible compounds that have quaternary ammonium atom able to inhibit acetylcholinesterase(AChE) activity. The molecules were obtained by screening and further in vitro assays were performed to analyze the most potentinhibitors through the IC
50value and also to describe the interactionmodels between inhibitors and enzyme bymolecular docking.
The results showed that compound D inhibited AChE activity from different vertebrate sources and butyrylcholinesterase (BChE)from Equus ferus (EfBChE), with IC
50ranging from 1.69 0.46 to 5.64 2.47 M. Compound D interacted with the peripheral
anionic subsite in both enzymes, blocking substrate entrance to the active site. In contrast, compound C had higher specificity asinhibitor of EfBChE. In conclusion, the screening was effective in finding inhibitors of AChE and BuChE from different organisms.
Alzheimers disease (AD) was first reported by the pathol-ogist Alois Alzheimer in 1907. It is a neurological disordercharacterized by a significant decrease in hippocampal andcortical levels of the neurotransmitter acetylcholine (ACh) with formation of extracellular amyloid plaques andintracellular neurofibrillary tangles that lead to neurotoxicity. The AD affects up to 5% of people over 65 years,rising to 20% of those over 80 years . One of the majortherapeutic strategies adopted for AD treatment is based onthe cholinergic hypothesis. Clinically, AD is associated withcognitive, functional, and behavioral symptoms, which canbe explained by the cholinergic neurotransmission deficitwith the loss of cholinergic neurons .
The neurotransmitter ACh plays a key role in learningandmemory processes by activating nicotinic andmuscarinicreceptors of the central nervous system (CNS) .The acetyl-cholinesterase (AChE) is an enzyme that hydrolyzes ACh toacetate and choline in the synaptic cleft, terminating the AChneurotransmission .The inhibitory effect onAChE activityincreases ACh in synaptic cleft with overactivation of thecholinergic transmission . Since disruption of cholinergicneurotransmission is involved in different brain functions,the search for new acetylcholinesterase inhibitors (AChEIs) isrelevant as an early step to selectmolecules that can be used inpreclinical trials as potential pharmacological agents or evento synthesize other kinds of compounds, such as insecticides.
Virtual screening is established as an effective methodfor filtering compounds in the course of new drug discovery
Hindawi Publishing CorporationBioMed Research InternationalVolume 2015, Article ID 870389, 8 pageshttp://dx.doi.org/10.1155/2015/870389
2 BioMed Research International
(a) (b) (c) (d)
Figure 1: Molecular overlapping of the crystal ligands (red) and the best pose of ligands proposed by Auto Dock Vina 1.1.1 program (green),for the enzymes 1QON (a), 2VQ6 (b), 3I6M (c), and 2BDS (d). The nonpolar hydrogen atoms were omitted.
. During this long process, it is possible to search forcompounds with specific features that can, potentially, lead tothe development of effective therapeutic agents. For instance,the consideration of the Lipinskis rule of five , thatis, molecular weight lower than 500Da, number of donorhydrogen bonds less than 5, number of acceptor hydrogenbonds less than 10, and the log lower than 5, is ofimportance for the screening of drugs with pharmacologicalactivity.
The molecular docking is a method that can predictthe most favorable orientation of a molecule (ligand) wheninteracting with a macromolecular target, such as an enzymeor a receptor, to form a stable complex.The crucial thermody-namic parameter involved in this method is the binding freeenergy (binding), which checks the theoretical stability ofthe ligand-protein complex . Based on this principle, themain objective of the present study was to propose a strategyof virtual screening to unravel potential newAChEIs by usingthe virtual molecules ZINC bank and selecting compoundsthat obey the Lipinskis rule of five which have quaternaryammonium atom (because of the similarity with ACh). Wealso assessed the inhibitory activity of selected compounds invitro, in order to check which compounds have the highestinhibitory activity using different AChE sources, purifiedAChE from Electrophorus electricus (EeAChE), AChE fromDanio rerio (DrAChE), and human AChE (HsAChE). Fur-thermore in order to verify whether the selected compoundscould also inhibit butyrylcholinesterase (BChE) activity, weinvestigated the effects of these compounds on purified BChEfrom Equus ferus (EfBChE).
2. Materials and Methods
2.1. In Silico Analysis. To search for new drugs with bindingaffinity to AChE, we used the virtual molecules ZINC bank(http://zinc.docking.org/), where approximately 5.5 millionof different molecular structures are deposited . First,we selected only tridimensional structures of compoundswith quaternary ammonium atom that were in accordancewith the Lipinskis rule of five. In addition, another rule wasalso included: the number of rotatable bonds had to be lessthan 10 . The molecules obtained were downloaded and
their geometry optimized using the software Avogadro 0.9.4following the MMFF94 method.
The molecular docking simulation was used as a secondscreening, aiming to search for compounds with higherinhibitory capacity and to propose an interaction model.We used different crystallographic structures of AChEfrom Protein Data Bank (PDB) (http://www.pdb.org/). TheCHIMERA 1.5.3 softwarewas used to removemolecules, ions,andwater and tominimize the structure of proteins, using theGasteiger charges with 500 steps of minimization.
After obtaining the ligands and enzymes, their structureswere converted to pdbqt format, using the Auto Dock Tools1.5.4 program, inwhich all the rotatable bonds of ligandswereallowed to rotate freely, and the receptors were consideredrigid. For docking studies, we used the Auto Dock Vina 1.1.1, with 1 A of spacing between the grid points. The gridbox was centered on the active site of the enzymes with highresolution, allowing the program to search for additionalplaces of probable interactions between the ligands and thereceptor. Other configurations were considered default.
The type of enzyme, species, PDB code, RMSD value,coordinates, and size of the grid box are shown in Table 1.Importantly, some enzymes do not present the RMSD valuebecause they do not have inhibitor on their structures. Thefigures of structures with RMSD are represented in Figure 1.The RMSD value (less than 2 A) is a criterion often used forcorrecting bound structure prediction . The redockingswere performed with the same configurations of the previousperformed dockings.
For in vitro assays, we selected the compounds that pre-sented lower binding energy (binding) in all enzymes usedfor the screening. The interactions between ligand-proteinwere visualized by Accelrys Discovery Studio Visualizer 2.5.
2.2. In Vitro Analysis. The compounds selected as inhibitorsof AChE activity were obtained commercially from MolPort(http://www.molport.com/buy-chemicals/index). They weredissolved in dimethyl sulfoxide (DMSO), at a final concen-tration of 0.1%.
The cholinesterase activities were measured based onEllman et al.s method . The increase of absorbancewas monitored at 412 nm in a reaction mixture containing
BioMed Research International 3
Table 1: Information about the AChE enzymes: species, PDB code, coordinates and size of grid box, and RMSD value.
Species PDB code Coordinates of grid box Size of grid box RMSD value (A)
1DX4: 30.311 : 44: 70.424 : 48 : 10.617 : 52
1QO9: 28.259 : 44: 70.453 : 52 : 12.592 : 44
1QON: 29.403 : 40
1.03: 71.508 : 44: 11.697 : 40
2VQ6: 5.254 : 48: 65.479 : 44 1.94: 64.028 : 48
3I6M: 2.092 : 56: 64.337 : 44 0.41: 64.75 : 48
1EA5: 4.957 : 48: 64.084 : 44 : 65.094 : 48
Mus musculus 1J06: 32.473 : 48: