Epitopes based drug design for dengue virus envelope protein: A computational approach

Dengue virus (DENV) has emerged as a rapidly spreading epidemic throughout the tropical and subtropical regions around the globe. No suitable drug has been designed yet to fight against DENV, therefore, the need for safe and effective antiviral drug has become imperative. The envelope protein of DENV is responsible for mediating the fusion process between viral and host membranes. This work reports an in silico approach to target B and T cell epitopes for dengue envelope protein inhibition. A conserved region “QHGTI” in B and T cell epitopes of dengue envelope glycoprotein was confirmed to be valid for targeting by visualizing its interactions with the host cell membrane TIM-1 protein which acts as a receptor for serotype 2 and 3. A reverse pharmacophore mapping approach was used to generate a seven featured pharmacophore model on the basis of predicted epitope. This pharmacophore model as a 3D query was used to virtually screen a chemical compounds dataset “Chembridge”. A total of 1010 compounds mapped on the developed pharmacophore model. These retrieved hits were subjected to filtering via Lipinski’s rule of five, as a result 442 molecules were shortlisted for further assessment using molecular docking. Finally, 14 hits of different structural properties having interactions with the active site residues of dengue envelope glycoprotein were selected as lead candidates. These structurally diverse lead candidates have strong likelihood to act as further starting structures in the development of novel and potential drugs for the treatment of dengue fever.     

Marine derived compounds as binders of the White spot syndrome virus VP28 envelope protein: In silico insights from molecular dynamics and binding free energy calculations

White spot syndrome virus (WSSV) remains as one of the most dreadful pathogen of the shrimp aquaculture industry owing to its high virulence. The cumulative mortality reaches up to 100% within in 2–10 days in a shrimp farm. Currently, no chemotherapeutics are available to control WSSV. The viral envelope protein, VP28, located on the surface of the virus particle acts as a vital virulence factor in the initial phases of inherent WSSV infection in shrimp. Hence, inhibition of envelope protein VP28 could be a novel way to deal with infection by inhibiting its interaction in the endocytic pathway. In this direction, a timely attempt was made to recognize a potential drug candidate of marine origin against WSSV using VP28 as a target by employing in silico docking and molecular dynamic simulations. A virtual library of 388 marine bioactive compounds was extracted from reports published in Marine Drugs. The top ranking compounds from docking studies were chosen from the flexible docking based on the binding affinities (ΔGb). In addition, the MD simulation and binding free energy analysis were implemented to validate and capture intermolecular interactions. The results suggested that the two compounds obtained a negative binding free energy with −40.453 kJ/mol and −31.031 kJ/mol for compounds with IDs 30797199 and 144162 respectively. The RMSD curve indicated that 30797199 moves into the hydrophobic core, while the position of 144162 atoms changes abruptly during simulation and is mostly stabilized by water bridges. The shift in RMSD values of VP28 corresponding to ligand RMSD gives an insight into the ligand induced conformational changes in the protein. This study is first of its kind to elucidate the explicit binding of chemical inhibitor to WSSV major structural protein VP28.     

Lectins and/or xyloglucans/alginate layers as supports for immobilization of dengue virus particles

Formation of stable thin films of mixed xyloglucan (XG) and alginate (ALG) onto Si/SiO(2) wafers was achieved under pH 11.6, 50mM CaCl(2), and at 70 degrees C. XG-ALG films presented mean thickness of (16+/-2)nm and globules rich surface, as evidenced by means of ellipsometry and atomic force microscopy (AFM), respectively. The adsorption of two glucose/mannose-binding seed (Canavalia ensiformis and Dioclea altissima) lectins, coded here as ConA and DAlt, onto XG-ALG surfaces took place under pH 5. Under this condition both lectins present positive net charge. ConA and DAlt adsorbed irreversibly onto XG-ALG forming homogenous monolayers approximately (4+/-1)nm thick. Lectins adsorption was mainly driven by electrostatic interaction between lectins positively charged residues and carboxylated (negatively charged) ALG groups. Adhesion of four serotypes of dengue virus, DENV (1-4), particles to XG-ALG surfaces were observed by ellipsometry and AFM. The attachment of dengue particles onto XG-ALG films might be mediated by (i) H bonding between E protein (located at virus particle surface) polar residues and hydroxyl groups present on XG-ALG surfaces and (ii) electrostatic interaction between E protein positively charged residues and ALG carboxylic groups. DENV-4 serotype presented the weakest adsorption onto XG-ALG surfaces, indicating that E protein on DENV-4 surface presents net charge (amino acid sequence) different from E proteins of other serotypes. All four DENV particles serotypes adsorbed similarly onto lectin films adsorbed. Nevertheless, the addition of 0.005mol/L of mannose prevented dengue particles from adsorbing onto lectin films. XG-ALG and lectin layers serve as potential materials for the development of diagnostic methods for dengue.     

Development of an electrochemical membrane-based nanobiosensor for ultrasensitive detection of dengue virus

A sensitive membrane-based electrochemical nanobiosensor is developed for the detection of dengue type 2 virus (DENV-2) using nanoporous alumina-modified platinum electrode. Its sensing mechanism relies on the monitoring of electrode's Faradaic current response toward redox probe, ferrocenemethanol, which is sensitive toward the formation of immune complexes within the alumina nanochannels. Anti-DENV-2 monoclonal antibody (clone 3H5, isotype IgG) is used as the biorecognition element in this work. The stepwise additions of antibody, bovine serum albumin (BSA) and DENV-2 are characterized by differential pulse voltammetry (DPV). A low detection limit of 1 pfu mL⁻¹ with linear range from 1 to 10³ pfu mL⁻¹ (R² = 0.98) can be achieved by the nanobiosensor. The nanobiosensor is selective toward DENV-2 with insignificant cross reaction with non-specific viruses, Chikungunya virus, West Nile virus and dengue type 3 virus (DENV-3). Relative standard deviation (RSD) for triplicate analysis of 5.9% indicates an acceptable level of reproducibility. The first direct quantitation of DENV-2 concentration in whole mosquito vector is demonstrated using this electrochemical nanobiosensor.     

Development of immunochips for the detection of dengue viral antigens

Recently, dengue virus has become a new emerging disease in the world. However, the procedures currently used for the detection of dengue virus are cumbersome and time-consuming. This is unfavorable for early stage epidemiological control and effective medical treatment. A new detection system was developed based on the quartz crystal microbalance (QCM) coating using two monoclonal antibodies that act specifically against the dengue virus envelope protein (E-protein) and non-structural 1 protein (NS-1 protein), respectively. Three different immobilizing methods, the glutaraldehyde (GA) method, protein A method and carbodiimide method (1-ethyl-3-(3-dimethyl- aminopropyl) carbodiimide, EDC) were used to prepare the immunochips. The “cocktail” immunochip, which has both antibodies attached, was also fabricated and used in comparison. The results showed that the protein A method was the best among the three. The sensitivity of the immunochip was 100-fold greater than the conventional sandwich ELISA method. The cocktail immunochip had a higher signal level than the normal immunochip. The time required for detection was shorter (about 1 h) and a blood specimen could be used to detect the virus in the viremia phase.     

Identification of novel anti cancer agents by applying insilico methods for inhibition of TSPO protein

Cancer is a genomic disease characterised as impaired cellular energy metabolism. Cancer cells derive most of their energy from oxidative phosphorylation unlike normal ones during cell progression TSPO protein present in external mitochondrial membrane, is involved in various cellular functions like Cell proliferation, mitochondrial respiration, synthesis of steroids and also participates in import of cholesterol into the inner mitochondrial membrane from outside of the membrane of mitochondria.The 3D model of TSPO protein is built using comparative homology modelling techniques and validated by proSA, Ramachandran plot and ERRAT in the present work. Active site prediction is carried out using SiteMap and literature, which allows the prediction of the important binding pockets for the identification of putative active site. New molecular entities as TSPO inhibitors were obtained from Virtual screening using MS Spectrum databank in Schrodinger suite and were prioritised based on Glide Score. Docking was performed using Autodock to identify molecules with different scaffolds and were prioritised based on binding energy and RMSD values. Qikprop is used to calculate pharmacokinetic properties of the screened molecules which are found to be in permissible range as possible novel inhibitors of TSPO protein to supress cell proliferation.     

Dihydropyrazole and dihydropyrrole structures based design of Kif15 inhibitors as novel therapeutic agents for cancer

Mitotic Kinesin motors, Eg5 and Kif15, have recently emerged as good targets for cancer as they play an inevitable role during mitosis. But, most of the Eg5 inhibitors were found ineffective when the cancer cells develop resistance to them by escalating the expression of Kif15 as alternative to Eg5. Therefore, the drugs that target Kif15 became necessary to be used either as a single or in combination with Eg5 inhibitors. The present study used 39 dihydropyrazole and 13 dihydropyrrole derivatives that were having in vitro inhibitory potential against kinesin motors to develop a common pharmacophore hypothesis AHRR and atom-based QSAR model. The model was used for virtual screening of ZINC database and the resultant hits were docked against Kif15. The four drug candidates with high docking score were examined for their activity and pharmacokinetic behaviour. Based on the results these drugs could be considered as lead candidates in further drug development for cancer.     

Discovery of potential Zika virus RNA polymerase inhibitors by docking-based virtual screening

Zika virus (ZIKV) infection has been associated with Guillain-Barre syndrome in adults and microcephaly in infants. The existence of insufficient structural data in most of the protein databases hinders the synthesis of anti-ZIKV pharmaceutics. In this work, we attempted to model the catalytic domain of the ZIKV RNA polymerase (RdRpC) along with a detailed assessment of conserved aspartates in ZIKV RdRpC palm domain as potential drug targets. The conserved and catalytically active aspartate residues present in the predicted RdRpC protein were virtually screened against a ZINC database for inhibitors, and the selected potential drug candidates were further filtered based on their ADMET profiles. One of the pharmacokinetically active compounds (Ligand 6) showed a remarkable docking profile against the strictly conserved aspartate residues of the RdRpC active site. We hypothesize that the Ligand 6 may form a potential drug candidate for RdRpC inhibition in the clinical treatment of ZIKV infection.     

Pharmacophore-based design,synthesis, and biological evaluation of novel 3-（（3,4-dichlorophenyl）（4-substituted benzyl）amino） propanamides as cholesteryl ester transfer protein （CETP） inhibitors

Cholesteryl ester transfer protein （CETP） is a plasma glycoprotein that plays an important role in decreasing high-density lipoprotein cholesterol （HDL-C） levels and increasing low-density lipoprotein cholesterol （LDL-C） levels. Inhibition of CETP may be a new therapy for treating atherosclerosis. Herein, we report the development of a ligand-based pharmacophore model and pharmacophore-based virtual screening of the ZINC/big-n-greasy database, leading to the identification of compound H-10 as a potential CETP inhibitor in vitro. Based on H-10, a series of 3-（（3,4-dichlorophenyl）（4-substituted benzyl）amino） propanamides were designed, synthesized, and evaluated against CETP. Compound 41 was found to have the best activity, resulting in 85.0% inhibition of CETP at l0 μmol/L.     

Computational prediction and biochemical characterization of novel RNA aptamers to Rift Valley fever virus nucleocapsid protein

Rift Valley fever virus (RVFV) is a potent human and livestock pathogen endemic to sub-Saharan Africa and the Arabian Peninsula that has potential to spread to other parts of the world. Although there is no proven effective and safe treatment for RVFV infections, a potential therapeutic target is the virally encoded nucleocapsid protein (N). During the course of infection, N binds to viral RNA, and perturbation of this interaction can inhibit viral replication. To gain insight into how N recognizes viral RNA specifically, we designed an algorithm that uses a distance matrix and multidimensional scaling to compare the predicted secondary structures of known N-binding RNAs, or aptamers, that were isolated and characterized in previous in vitro evolution experiment. These aptamers did not exhibit overt sequence or predicted structure similarity, so we employed bioinformatic methods to propose novel aptamers based on analysis and clustering of secondary structures. We screened and scored the predicted secondary structures of novel randomly generated RNA sequences in silico and selected several of these putative N-binding RNAs whose secondary structures were similar to those of known N-binding RNAs. We found that overall the in silico generated RNA sequences bound well to N in vitro. Furthermore, introduction of these RNAs into cells prior to infection with RVFV inhibited viral replication in cell culture. This proof of concept study demonstrates how the predictive power of bioinformatics and the empirical power of biochemistry can be jointly harnessed to discover, synthesize, and test new RNA sequences that bind tightly to RVFV N protein. The approach would be easily generalizable to other applications.     

Discovery of novel inhibition site centered on 114-bit tryptophan of Thioredoxin reductase 1 through computer-aided drug design

Thioredoxin reductase 1 (TrxR1) is an oxidoreductase playing the important role in the tumor cells. It is a new type of drug therapy target. Most of the existing TrxR1 inhibitors act directly covalently on the active sites. Herein, molecular docking-based virtual screening approach was used to screen inhibitors with new binding site of TrxR1 from the SPECS database. After experimental test, compound 22 was identified as the reversibility inhibitor of TrxR1 U498C mutant (It has similar structure and function to replace the wild-type TrxR1 which is difficult to express) with IC₅₀ value of 15.31 ± 0.57 μM. The molecular docking results showed that the interaction between compound 22 and TrxR1 was centered on inactive site Trp¹¹⁴. Furthermore, phenazine compounds 24–30 with similar structures as 22 were also screened out from our phenazine database. Compounds 24–27 had longer chain structures and better inhibitory activity than compound 22, while compounds 28–30 were the opposite. Compounds 24–27 can be more stably bound in the protein cavity on Trp¹¹⁴ than compounds 28–30. Then we verified amino acids centered on Trp¹¹⁴ can regulate TrxR1 activity by amino acids mutation. Taken together, A new inhibition site are found that can regulate TrxR1 U498C mutant activity by acting on amino acids sequence at inactive sites centered on Trp¹¹⁴ and can provide ideas for the discovery and research of new TrxR1 inhibitors.     

Identification of glucosyl-3-phosphoglycerate phosphatase as a novel drug target against resistant strain of Mycobacterium tuberculosis (XDR1219) by using comparative metabolic pathway approach

Tuberculosis (TB) is a major global health challenge. It has been afflicting human for thousands of years and is still severely affecting a huge population. The etiological agent of the disease is Mycobacterium tuberculosis (MTB) that survives in the human host in latent, dormant, and non-replicative state by evading the immune system. It is one of the leading causes of infection related death worldwide. The situation is exacerbated by the massive increase in the resistant strains such as multi-drug resistant TB (MDR-TB) and extensive drug-resistant TB (XDR-TB). The resistance is as severe that it resulted in failure of the current chemotherapy regimens (i.e. anti-tubercular drugs). It is therefore imperative to discover the new anti-tuberculosis drug targets and their potential inhibitors. Current study has made the use of in silico approaches to perform the comparative metabolic pathway analysis of the MTBXDR1219 with the host i.e. H. sapiens. We identified several metabolic pathways which are unique to pathogen only. By performing subtractive genomic analysis 05 proteins as potential drug target are retrieved. This study suggested that the identified proteins are essential for the bacterial survival and non-homolog to the host proteins. Furthermore, we selected glucosyl-3-phosoglycerate phosphatase (GpgP, EC 5.4.2.1) out of the 05 proteins for molecular docking analysis and virtual screening. The protein is involved in the biosynthesis of methylglucose lipopolysaccharides (MGLPs) which regulate the biosynthesis of mycolic acid. Mycolic acid is the building block of the unique cell wall of the MTB which is responsible for the resistance and pathogenicity. A relatively larger library consisting of 10,431 compounds was screened using AutoDock Vina to predict the binding modes and to rank the potential inhibitors. No potent inhibitor against MTB GpgP has been reported yet, therefore ranking of compounds is performed by making a comparison with the substrate i.e. glucosyl-3-phosphoglycerate. The obtained results provide the understanding of underlying mechanism of interactions of ligands with protein. Follow up study will include the study of the Protein-Protein Interactions (PPIs), and to propose the potential inhibitors against them.     

Identification of potential influenza virus endonuclease inhibitors through virtual screening based on the 3D-QSAR model

Influenza endonucleases have appeared as an attractive target of antiviral therapy for influenza infection. With the purpose of designing a novel antiviral agent with enhanced biological activities against influenza endonuclease, a three-dimensional quantitative structure-activity relationships (3D-QSAR) model was generated based on 34 influenza endonuclease inhibitors. The comparative molecular similarity index analysis (CoMSIA) with a steric, electrostatic and hydrophobic (SEH) model showed the best correlative and predictive capability (q ² = 0.763, r ² = 0.969 and F = 174.785), which provided a pharmacophore composed of the electronegative moiety as well as the bulky hydrophobic group. The CoMSIA model was used as a pharmacophore query in the UNITY search of the ChemDiv compound library to give virtual active compounds. The 3D-QSAR model was then used to predict the activity of the selected compounds, which identified three compounds as the most likely inhibitor candidates.     

Balancing target flexibility and target denaturation in computational fragment‐based inhibitor discovery

Accounting for target flexibility and selecting “hot spots” most likely to be able to bind an inhibitor continue to be challenges in the field of structure‐based drug design, especially in the case of protein–protein interactions. Computational fragment‐based approaches using molecular dynamics (MD) simulations are a promising emerging technology having the potential to address both of these challenges. However, the optimal MD conditions permitting sufficient target flexibility while also avoiding fragment‐induced target denaturation remain ambiguous. Using one such technology (Site Identification by Ligand Competitive Saturation, SILCS), conditions were identified to either prevent denaturation or identify and exclude trajectories in which subtle but important denaturation was occurring. The target system used was the well‐characterized protein cytokine IL‐2, which is involved in a protein–protein interface and, in its unliganded crystallographic form, lacks surface pockets that can serve as small‐molecule binding sites. Nonetheless, small‐molecule inhibitors have previously been discovered that bind to two “cryptic” binding sites that emerge only in the presence of ligand binding, highlighting the important role of IL‐2 flexibility. Using the above conditions, SILCS with hydrophobic fragments was able to identify both sites based on favorable fragment binding while avoiding IL‐2 denaturation. An important additional finding was that acetonitrile, a water‐miscible fragment, fails to identify either site yet can induce target denaturation, highlighting the importance of fragment choice. © 2012 Wiley Periodicals, Inc.     

Structure-based virtual screening of influenza virus RNA polymerase inhibitors from natural compounds: Molecular dynamics simulation and MM-GBSA calculation

The resistances of matrix protein 2 (M2) protein inhibitors and neuraminidase inhibitors for influenza virus have attracted much attention and there is an urgent need for new drug. The antiviral drugs that selectively act on RNA polymerase are less prone to resistance and possess fewer side effects on the patient. Therefore, there is increased interest in screening compounds that can inhibit influenza virus RNA polymerase. Three natural compounds were found by using molecular docking-based virtual screening, which could bind tightly within the polymerase acidic protein-polymerase basic protein 1 (PA-PB1) subunit of influenza virus polymerase. Firstly, their drug likeness properties were evaluated, which showed that the hepatotoxicity values of all the three compounds indicating they had less or no hepatotoxicity, and did not have the plasma protein biding (PPB) ability, the three compounds needed to be modified in some aspects, like bulky molecular size. The stability of the complexes of PA-hits was validated through molecular dynamics (MD) simulation, revealing compound 2 could form more stable complex with PA subunit. The torsional conformations of each rotatable bond of the ligands in PA subunit were also monitored, to investigate variation in the ligand properties during the simulation, compound 3 had fewer rotatable bonds, indicating that the molecule had stronger rigidity. The bar charts of protein–ligand contacts and contacts over the course of trajectory showed that four key residues (Glu623, Lys643, Asn703 and Trp706) of PA subunit that participated in hydrogen-bond, water bridge and hydrophobic interactions with the hit compounds. Finally, the binding free energy and contributed energies were calculated by using MM-GBSA method. Out of the three compounds, compound 1 showed the lowest total binding free energy. Among all the interactions, the contribution of the covalent binding and the van der Waals energy were more than other items, compound 1 formed more stable hydrogen bonds with the residues of PA subunit binding pocket. This study smoothed the path for the development of novel lead compounds with improved binding properties, high drug likeness, and low toxicity to humans for the treatment of influenza, which provided a good basis for further research on novel and effective influenza virus PA-PB1 interaction inhibitors.     

Multi-analyte single-membrane biosensor for the serotype-specific detection of Dengue virus

A multi-analyte biosensor based on nucleic acid hybridization and liposome signal amplification was developed for the rapid serotype-specific detection of Dengue virus. After RNA amplification, detection of Dengue virus specific serotypes can be accomplished using a single analysis within 25 min. The multi-analyte biosensor is based on single-analyte assays (see Baeumner et al (2002) Anal Chem 74:1442–1448) developed earlier in which four analyses were required for specific serotype identification of Dengue virus samples. The multi-analyte biosensor employs generic and serotype-specific DNA probes, which hybridize with Dengue RNA that is amplified by the isothermal nucleic acid sequence based amplification (NASBA) reaction. The generic probe (reporter probe) is coupled to dye-entrapping liposomes and can hybridize to all four Dengue serotypes, while the serotype-specific probes (capture probes) are immobilized through biotin–streptavidin interaction on the surface of a polyethersulfone membrane strip in separate locations. A mixture of amplified Dengue virus RNA sequences and liposomes is applied to the membrane and allowed to migrate up along the test strip. After the liposome-target sequence complexes hybridize to the specific probes immobilized in the capture zones of the membrane strip, the Dengue serotype present in the sample can be determined. The amount of liposomes immobilized in the various capture zones directly correlates to the amount of viral RNA in the sample and can be quantified by a portable reflectometer. The specific arrangement of the capture zones and the use of unlabeled oligonucleotides (cold probes) enabled us to dramatically reduce the cross-reactivity of Dengue virus serotypes. Therefore, a single biosensor can be used to detect the exact Dengue serotype present in the sample. In addition, the biosensor can simultaneously detect two serotypes and so it is useful for the identification of possible concurrent infections found in clinical samples. The various biosensor components have been optimized with respect to specificity and sensitivity, and the system has been ultimately tested using blind coded samples. The biosensor demonstrated 92% reliability in Dengue serotype determination. Following isothermal amplification of the target sequences, the biosensor had a detection limit of 50 RNA molecules for serotype 2, 500 RNA molecules for serotypes 3 and 4, and 50,000 molecules for serotype 1. The multi-analyte biosensor is portable, inexpensive, and very easy to use and represents an alternative to current detection methods coupled with nucleic acid amplification reactions such as electrochemiluminescence, or those based on more expensive and time consuming methods such as ELISA or tissue culture.     

Identification of Novel Influenza Polymerase PB2 Inhibitors Using a Cascade Docking Virtual Screening Approach

To discover novel inhibitors that target the influenza polymerase basic protein 2 (PB2) cap-binding domain (CBD), commercial ChemBridge compound libraries containing 384,796 compounds were screened using a cascade docking of LibDock–LigandFit–GOLD, and 60 compounds were selected for testing with cytopathic effect (CPE) inhibition assays and surface plasmon resonance (SPR) assay. Ten compounds were identified to rescue cells from H1N1 virus-mediated death at non-cytotoxic concentrations with EC₅₀ values ranging from 0.30 to 67.65 μM and could bind to the PB2 CBD of H1N1 with Kd values ranging from 0.21 to 6.77 μM. Among these, four compounds (11D4, 12C5, 21A5, and 21B1) showed inhibition of a broad spectrum of influenza virus strains, including oseltamivir-resistant ones, the PR/8-R292K mutant (H1N1, recombinant oseltamivir-resistant strain), the PR/8-I38T mutant (H1N1, recombinant baloxavir-resistant strain), and the influenza B/Lee/40 virus strain. These compounds have novel chemical scaffolds and relatively small molecular weights and are suitable for optimization as lead compounds. Based on sequence and structure comparisons of PB2 CBDs of various influenza virus subtypes, we propose that the Phe323/Gln325, Asn429/Ser431, and Arg355/Gly357 mutations, particularly the Arg355/Gly357 mutation, have a marked impact on the selectivities of PB2 CBD-targeted inhibitors of influenza A and influenza B.     

Discovery of potential inhibitor against human acetylcholinesterase: a molecular docking and molecular dynamics investigation

Alzheimer’s disease (AD) is a progressive neurodegenerative disease of central nervous system among elderly people. Human acetylcholinesterase (hAChE), an important enzyme in neuronal signaling, is responsible for the degradation of acetylcholine which in turn prevents the post synaptic signal transmissions. hAChE has been an attractive target of drug discovery for the search of therapeutics against AD. In the recent past hAChE has become hot target for the investigation of new potential therapeutics. We performed virtual screening of entire database against hAChE. Further, the extra precision molecular docking was carried out to refine the docking results and the best complex was passed for molecular dynamics simulations in order of understanding the hAChE dynamics and its behavior in complex with the ligand which corroborate the outcomes of virtual screening. This also provides binding free energy data that establishes the ligands efficiency for inhibiting hAChE. The computational findings discussed in this paper provide initial information of inhibitory effects of ligand, (drugbank entry DB00983), over hAChE.     

NMR spectroscopy techniques for screening and identifying ligand binding to protein receptors

Binding events of ligands to receptors are the key for an understanding of biological processes. Gaining insight into protein-protein and protein-ligand interactions in solution has recently become possible on an atomic level by new NMR spectroscopic techniques. These experiments identify binding events either by looking at the resonance signals of the ligand or the protein. Ideally, both techniques together deliver a complete picture of ligand binding to a receptor. The approaches discussed in this review allow screening of compound libraries as well as a detailed identification of the groups involved in the binding events. Also, characterization of the binding strength and kinetics is possible, competitive binding as well as allosteric effects can be identified, and it has even been possible to identify ligand binding to intact viruses and membrane-bound proteins.