Identification of potential bivalent inhibitors from natural compounds for acetylcholinesterase through in silico screening using multiple pharmacophores

The symptomatic cure observed in the treatment of Alzheimer's disease (AD) by FDA approved drugs could possibly be due to their specificity against the active site of acetylcholinesterase (AChE) and not by targeting its pathogenicity. The AD pathogenicity involved in AChE protein is mainly due to amyloid beta peptide aggregation, which is triggered specifically by peripheral anionic site (PAS) of AChE. In the present study, a workflow has been developed for the identification and prioritization of potential compounds that could interact not only with the catalytic site but also with the PAS of AChE. To elucidate the essential structural elements of such inhibitors, pharmacophore models were constructed using PHASE, based on a set of fifteen best known AChE inhibitors. All these models on validation were further restricted to the best seven. These were transferred to PHASE database screening platform for screening 89,425 molecules deposited at the “ZINC natural product database”. Novel lead molecules retrieved were subsequently subjected to molecular docking and ADME profiling. A set of 12 compounds were identified with high pharmacophore fit values and good predicted biological activity scores. These compounds not only showed higher affinity for catalytic residues, but also for Trp86 and Trp286, which are important, at PAS of AChE. The knowledge gained from this study, could lead to the discovery of potential AChE inhibitors that are highly specific for AD treatment as they are bivalent lead molecules endowed with dual binding ability for both catalytic site and PAS of AChE.     

Accurate prediction of the bound conformation of galanthamine in the active site of Torpedo californica acetylcholinesterase using molecular docking.

The alkaloid (-)-galanthamine is known to produce significant improvement of cognitive performances in patients with the Alzheimer's disease. Its mechanism of action involves competitive and reversible inhibition of acetylcholinesterase (AChE). Herein, we correctly predict the orientation and conformation of the galanthamine molecule in the active site of AChE from Torpedo californica (TcAChE) using a combination of rigid docking and flexible geometry optimization with a molecular mechanics force field. The quality of the predicted model is remarkable, as indicated by the value of the RMS deviation of approximately 0.5A when compared with the crystal structure of the TcAChE-galanthamine complex. A molecular model of the complex between TcAChE and a galanthamine derivative, SPH1107, with a long chain substituent on the nitrogen has been generated as well. The side chain of this ligand is predicted to extend along the enzyme active site gorge from the anionic subsite, at the bottom, to the peripheral anionic site, at the top. The docking procedure described in this paper can be applied to produce models of ligand-receptor complexes for AChE and other macromolecular targets of drug design.     

Proteomic identification and early validation of complement 1 inhibitor and pigment epithelium-derived factor: Two novel biomarkers of Alzheimer's disease in human plasma

Emerging disease modifying therapeutic strategies for Alzheimer's disease (AD) have generated a critical need for biomarkers of early stage disease. Here, we describe the identification and assessment of a number of candidate biomarkers in patients with mild to moderate probable AD. Plasma from 47 probable Alzheimer's patients and 47 matched controls were analysed by proteomics to define a significant number of proteins whose expression appeared to be associated with AD. These were compared to a similar proteomic comparison of a mouse transgenic model of amyloidosis, which showed encouraging overlap with the human data. From these studies a prioritised list of 31 proteins were then analysed by immunoassay and/or functional assay in the same human cohort to verify the changes observed. Eight proteins continued to show significance by either immunoassay or functional assay in the human plasma and these were tested in a further set of 100 probable AD patients and 100 controls from the original cohort. From our data it appeared that two proteins, serpin F1 (pigment epithelium-derived factor) and complement C1 inhibitor are down-regulated in plasma from AD patients.     

Perspectives for the structure-based design of acetylcholinesterase reactivators

Rational design of active molecules through structure-based methods has been gaining adepts during the last decades due to the wider availability of protein structures, most of them conjugated with relevant ligands. Acetylcholinesterase (AChE) is a molecular target with a considerable amount of data related to its sequence and 3-dimensional structure. In addition, there are structural insights about the mechanism of action of the natural substrate and drugs used in Alzheimer’s disease, organophosphorus compounds, among others. We looked for AChE structural data useful for in silico design of potential interacting molecules. In particular, we focused on information regarding the design of ligands aimed to reactivate AChE catalytic activity. The structures of 178 AChE were annotated and categorized on different subsets according to the nature of the ligand, source organisms and experimental details. We compared sequence homology among the active site from Torpedo californica, Mus musculus and Homo sapiens with the latter two species having the closest relationship (88.9% identity). In addition, the mechanism of organophosphorus binding and the design of effective reactivators are reviewed. A curated data collection obtained with information from several sources was included for researchers working on the field. Finally, a molecular dynamics simulation with human AChE indicated that the catalytic pocket volume stabilizes around 600 ų, providing additional clues for drug design.     

Redox proteomics studies of in vivo amyloid beta-peptide animal models of Alzheimer's disease: Insight into the role of oxidative stress

Alzheimer's disease (AD) is an age-related neurodegenerative disease. AD is characterized by the presence of senile plaques, neurofibrillary tangles, and synaptic loss. Amyloid β-peptide (Aβ), a component of senile plaques, has been proposed to play an important role in oxidative stress in AD brain and could be one of the key factors in the pathogenesis of AD. In the present review, we discuss some of the AD animal models that express Aβ, and compare the proteomics-identified oxidatively modified proteins between AD brain and those of Aβ models. Such a comparison would allow better understanding of the role of Aβ in AD pathogenesis thereby helping in developing potential therapeutics to treat or delay AD.     

Identification and validation of novel CSF biomarkers for early stages of Alzheimer's disease

The pathology of Alzheimer's disease (AD) begins years prior to clinical diagnosis. The development of antecedent biomarkers that indicate the presence of AD pathology and predict risk for decline in both cognitively normal and mildly impaired individuals will be useful as effective therapies are developed. While cerebrospinal fluid (CSF) markers such as amyloid-β (Aβ) 42 and tau are useful, additional biomarkers are needed. To identify new markers, we utilized 2-D difference gel electrophoresis (2-D DIGE) of individual CSF samples from subjects with very mild AD versus controls after depletion of high-abundant proteins. Protein spots displaying differential abundance between the two groups were identified with MS. A number of candidate biomarkers were identified in 18 gel features. Selected candidates were quantified in a larger clinical set using ELISA. The mean levels of α1-antichymotrypsin (ACT), antithrombin III (ATIII), and zinc-α2-glycoprotein (ZAG) were significantly higher in the mild AD group, and the mean level of carnosinase 1 (CNDP1) was decreased. When these biomarkers are optimally combined, there is a strong trend toward greater specificity and sensitivity based on clinical diagnosis than when used individually. Our findings provide novel biomarker candidates for very mild and mild AD that can be further assessed as antecedent markers and predictors of clinical progression.     

Binding conformation prediction between human acetylcholinesterase and cytochrome c using molecular modeling methods

The acetylcholinesterase (AChE) is important to terminate acetylcholine-mediated neurotransmission at cholinergic synapses. The pivotal role of AChE in apoptosome formation through the interactions with cytochrome c (Cyt c) was demonstrated in recent study. In order to investigate the proper binding conformation between the human AChE (hAChE) and human Cyt c (hCyt c), macro-molecular docking simulation was performed using DOT 2.0 program. The hCyt c was bound to peripheral anionic site (PAS) on hAChE and binding mode of the docked conformation was very similar to the reported crystal structure of the AChE and fasciculin-II (Fas-II) complex. Two 10ns molecular dynamics (MD) simulations were carried out to refine the binding mode of docked structure and to observe the differences of the binding conformations between the absent (Apo) and presence (Holo) of heme group. The key hydrogen bonding residues between hAChE and hCyt c proteins were found in Apo and Holo systems, as well as each Tyr341 and Trp286 residue of hAChE was participated in cation-pi (π) interactions with Lys79 of hCyt c in Apo and Holo systems, respectively. From the present study, although the final structures of the Apo and Holo systems have similar binding pattern, several differences were investigated in flexibilities, interface interactions, and interface accessible surface areas. Based on these results, we were able to predict the reasonable binding conformation which is indispensable for apoptosome formation.     

A systematic methodology for large scale compound screening: A case study on the discovery of novel S1PL inhibitors

Decrease in sphingosine 1-phosphate (S1P) concentration induces migration of pathogenic T cells to the blood stream, disrupts the CNS and it is implicated in multiple sclerosis (MS), a progressive inflammatory disorder of the central nervous system (CNS), and Alzheimer’s disease (AD). A promising treatment alternative for MS and AD is inhibition of the activity of the microsomal enzyme sphingosine 1-phosphate lyase (S1PL), which degrades intracellular S1P. This report describes an integrated systematic approach comprising virtual screening, molecular docking, substructure search and molecular dynamics simulation to discover novel S1PL inhibitors. Virtual screening of the ZINC database via ligand-based and structure-based pharmacophore models yielded 10000 hits. After molecular docking, common substructures of the top ranking hits were identified. The ligand binding poses were optimized by induced fit docking. MD simulations were performed on the complex structures to determine the stability of the S1PL-ligand complex and to calculate the binding free energy. Selectivity of the selected molecules was examined by docking them to hERG and cytochrome P450 receptors. As a final outcome, 15 compounds from different chemotypes were proposed as potential S1PL inhibitors. These molecules may guide future medicinal chemistry efforts in the discovery of new compounds against the destructive action of pathogenic T cells.     

A comparative study of feature extraction methods for the diagnosis of Alzheimer's disease using the ADNI database

Several approaches appear in literature in order to develop Computed-Aided-Diagnosis (CAD) systems for Alzheimer's disease (AD) detection. Although univariate models became very popular and nowadays they are widely used, recent investigations are focused on multivariate models which deal with a whole image as an observation. In this work, we compare two multivariate approaches that use different methodologies to relieve the small sample size problem. One of them is based on Gaussian Mixture Model (GMM) and models the Regions of Interests (ROIs) defined as differences between controls and AD subject. After GMM estimation using the EM algorithm, feature vectors are extracted for each image depending on the positions of the resulting Gaussians. The other method under study computes score vectors through a Partial Least Squares (PLS) algorithm based estimation and those vectors are used as features. Before extracting the score vectors, a binary mask based dimensional reduction of the input space is performed in order to remove low-intensity voxels. The validity of both methods is tested on the ADNI database by implementing several CAD systems with linear and nonlinear classifiers and comparing them with previous approaches such as VAF and PCA.     

Identifying stage of Alzheimer disease using multiclass particle swarm optimisation technique

ABSTRACT

Detecting brain structural changes from magnetic resonance (MR) images can facilitate early diagnosis and treatment of neurological and psychiatric diseases. Alzheimer Disease (AD) is a progressive neurodegenerative disorder that causes structural changes in patient’s brain. As such, it is essential to develop an algorithm for identifying the biomarkers of this disease stage. We developed a novel volumetric analysis of anatomical components of brain with multiclass particle swam optimisation technique (MPSO) approach to detect the stages of AD as potential biomarkers. To avoid image distortion bias correction is applied. We have used anatomical structures i.e. tissue and ventricle volume are used as criteria to categorise image features into four classes such as Alzheimer Mild cognitive decline, Alzheimer Moderate Cognitive decline and Alzheimer Severe Cognitive decline and healthy subject. This work was experimented with 30 AD and 10 normal cases. We observed that grey matter content was reduced from 4 to 20% of normal brain and volume of ventricle is increasing gradually from mild to severe cognitive decline. The statistical performance measures are calculated for proposed and existing work. The value shows that our empirical evaluation has superior diagnosis performance. We found that AD patient’s brain has reduced volume in grey matter and subsequently shrunk the volume of brain. The size of ventricle is also the major concern to predict the severity of AD disease. Therefore, the volumes of grey matter and ventricle size more discriminately classify the AD patient with severity from normal subject.     

Proteomics of Alzheimer's disease: Unveiling protein dysregulation in complex neuronal systems

Alzheimer's disease (AD) and its progressive dementia is multifactorial, develops relatively sporadically, and involves multiple pathologies in the complex biological system of the brain. For these reasons, genetics alone is not likely to explain the molecular basis of this disease. Proteomics is contributing valuable information about the underlying molecular defects involved in AD development and progression, which includes oxidative damage to specific proteins, altered levels of synaptic components, and protein compositions of Aβ plaques and neurofibrillary tangles (pathological hallmarks of AD). However, emerging strategies in the field of proteomics which include more specific targeting of disease-related anatomical regions, targeting of specific subcellular compartments of functional relevance, novel approaches for large scale identification of regulatory post-translational modifications such as phosphorylation and O-GlcNAc, improved chromatographic separations of peptides for more comprehensive analysis of samples, and high-throughput quantitative strategies directly coupled with MS should greatly enhance the future of AD proteomics. The characterization of AD-specific alterations in proteomes should provide further insight into mechanisms of disease development and progression, provide biomarkers predicting disease development, and provide novel targets for therapeutic intervention.     

β-淀粉样多肽自聚集抑制剂的电化学筛选方法研究

β-淀粉样多肽（Amyloidbeta,Aβ）的聚集物具有神经细胞毒性,可导致神经元凋亡,从而诱导阿尔茨海默症（Alzheimer’s disease,AD）的发生。能够抑制AB自聚集行为的化合物称为AB自聚集抑制剂。该抑制剂可抑制Aβ有毒聚集物的产生,从而降低Aβ所引起的神经细胞毒性,对AD病有一定的治疗效果。因此。筛选AB自聚集抑制剂对于AD的治疗有着重要的意义。在数以千万计的化合物中,要筛选出对Aβ自聚集有抑制效果的化合物需要借助众多的仪器和研究方法。该文总结了筛选AB自聚集抑制剂的几种方法．重点综述了几种低成本、快速、灵敏的电化学筛选方法。Aβ自聚集抑制剂的筛选对临床上AD病的治疗提供了理论基础,为治疗AD病这一复杂科学问题的研究起到了促进作用。     

Protocol for fast screening of multi-target drug candidates: Application to Alzheimer’s disease

The treatment of many diseases may require drugs that are capable to attack multiple targets simultaneously. Obviously, the virtual screening of multi-target drug candidates is much more time consuming compared to the single-target case. This, in particular, concerns the last step of virtual screening where the binding free energy is computed by conventional molecular dynamics simulation. To overcome this difficulty we propose a simple protocol which is relied on the fast steered molecular dynamics simulation and on available experimental data on binding affinity of reference ligand to a given target. Namely, first we compute non-equilibrium works generated during pulling ligands from the binding site using the steered molecular dynamics method. Then as top leads we choose only those compounds that have the non-equilibrium work larger than that of a reference compound for which the binding free energy has been already known from experiment.Despite many efforts no cures for AD (Alzheimer’s disease) have been found. One of possible reasons for this failure is that drug candidates were developed for a single target, while there are exist many possible pathways to AD. Applying our new protocol to five targets including amyloid beta fibril, peroxisome proliferator-activated receptor γ, retinoic X receptor α, β- and γ-secretases, we have found two potential drugs (CID 16040294 and CID 9998128) for AD from the large PubChem database. We have also shown that these two ligands can interfere with the activity of popular Acetylcholinesterase target through strong binding towards it.     

Analysis of the magnetoencephalogram background activity in Alzheimer's disease patients with auto-mutual information

The aim of the present study was to analyse the magnetoencephalogram (MEG) background activity in patients with Alzheimer's disease (AD), one of the most frequent disorders among elderly population. For this pilot study, we recorded the MEGs with a 148-channel whole-head magnetometer in 20 patients with probable AD and 21 age-matched control subjects. Artefact-free epochs of 3392 samples were analysed with auto-mutual information (AMI). Average AMI decline rates were lower for the AD patients' recordings than for control subjects' ones. Statistically significant differences were found using a Student's t-test (p<0.01) in 144 channels. Mean AMI values were analysed with a receiver operating characteristic curve. Sensitivity, specificity and accuracy values of 75%, 90.5% and 82.9% were obtained. Our results show that AMI estimations of the magnetic brain activity are different in both groups, hence indicating an abnormal type of dynamics associated with AD. This study suggests that AMI might help medical doctors in the diagnosis of the disease.     

AChE/PAMAM-Au/CNTs/GC传感器用于有机磷农药检测的研究

该文制备了一种多层AChE/PAMAM-Au/CNTs/GC乙酰胆碱酯酶的酶抑制电流型传感器应用于有机磷农药的检测,主要利用碳纳米管良好的导电性和吸附性,以及PAMAM(G4)-Au树枝状复合物特殊的结构及导电性能,利用有机磷农药对乙酰且日碱酯酶的抑制作用,以硫代乙酰胆碱(ATCh)为底物,实现了对有机磷农约的检测.实验表明,该方法快速简单,线性范围宽,灵敏度高.固定在传感器上的乙酰胆碱酯酶具有良好的酶动力学响应,其米氏常数(KMapp)为1.66 mmol/L.对有机磷农药呋喃丹的最低检测限达到4.0 nmol/L.     

Early diagnosis of Alzheimer’s disease based on Partial Least Squares and Support Vector Machine

An accurate and early diagnosis of the Alzheimer’s disease (AD) is of fundamental importance for the patient medical treatment. It has been shown that pathological manifestations of AD may be detected thought functional images even before that the patients becomes symptomatic. This fact has led researchers to propose new ways for analyzing functional data in order to get more accurate Computer-Aided Diagnosis (CAD) systems for this disorder. In this paper we show an effective approach for Single Photon Emission Computed Tomography feature extraction that improves the accuracy of CAD systems for AD. The proposed methodology uses a Partial Least Squares algorithm for extracting score vectors and the Out-Of-Bag error for selecting a number of scores that are used as features. Subsequently, a Support Vector Machine (SVM) based classifier determines the underlying class of the images, thus performing diagnostics. In order to test this approach we have used an image database for AD with 97 SPECT images from controls and AD patients. The images were visually labeled by experienced clinicians after the properly normalization. Several experiments have been developed to compare the proposed methodology and previous approaches. The results show that our method yields accuracy rates over 90%, outperforming several recently reported CAD systems for AD diagnosis.     

阿尔茨海默氏症研究中的磁共振成像数据分析

首先综述了当前结构磁共振成像、功能磁共振成像和扩散张量磁共振成像3种技术在阿尔茨海默氏症研究中的现状;其次介绍和分析了上述3种磁共振成像数据的主要处理方法;最后介绍了基于阿尔茨海默氏症的神经影像数据库及其诊断平台的建设状况.另外,也提到了此课题在该领域的一些研究进展.     

Proteomics analysis of plasma for potential biomarkers in the diagnosis of Alzheimer's disease

The objective of this study was to search for biological markers associated with Alzheimer's disease (AD). Plasma specimens obtained from ten pathologically diagnosed AD patients and ten non-demented (ND) control subjects were analyzed by a combination of 2-DE and MS. This strategy allowed us to identify six plasma proteins (alpha-1-antitrypsin, vitamin D-binding protein, inter-alpha-trypsin inhibitor family heavy chain-related protein, apolipoprotein J precursor, cAMP-dependent protein kinase catalytic subunit alpha 1, and an orf) whose 2-DE spot densities were different between the AD and ND groups. Due to their involvements in AD amyloid plaque formation, the plasma concentrations of alpha-1-antitrypsin and apolipoprotein J were further validated using either ELISA or Western blot. The results revealed that the plasma levels of alpha-1-antitrypsin in AD were higher than those of controls, confirming the 2-DE findings. However, no difference in total apolipoprotein J concentration was observed between the AD and ND groups. Considering the difference in resolving power to differentially quantitate protein isoforms provided by 2-DE and Western blot, 2-DE analysis combined with MS protein identification offers distinctive advantages when a disease-related protein isoform-specific variance is investigated.