NADPHnet: a novel strategy to predict compounds for regulation of NADPH metabolism via network-based methods.

Identification of compounds to modulate NADPH metabolism is crucial for understanding complex diseases and developing effective therapies. However, the complex nature of NADPH metabolism poses challenges in achieving this goal. In this study, we proposed a novel strategy named NADPHnet to predict key proteins and drug-target interactions related to NADPH metabolism via network-based methods. Different from traditional approaches only focusing on one single protein, NADPHnet could screen compounds to modulate NADPH metabolism from a comprehensive view. Specifically, NADPHnet identified key proteins involved in regulation of NADPH metabolism using network-based methods, and characterized the impact of natural products on NADPH metabolism using a combined score, NADPH-Score. NADPHnet demonstrated a broader applicability domain and improved accuracy in the external validation set. This approach was further employed along with molecular docking to identify 27 compounds from a natural product library, 6 of which exhibited concentration-dependent changes of cellular NADPH level within 100 µM, with Oxyberberine showing promising effects even at 10 µM. Mechanistic and pathological analyses of Oxyberberine suggest potential novel mechanisms to affect diabetes and cancer. Overall, NADPHnet offers a promising method for prediction of NADPH metabolism modulation and advances drug discovery for complex diseases.

Computational insights into the G-protein-biased activation and inactivation mechanisms of the µ opioid receptor.

The µ opioid receptor (OR), a member of the class A subfamily of G-protein coupled receptors (GPCRs), is a major target for the treatment of pain. G-protein biased µ-OR agonists promise to be developed as analgesics. Thus, TRV130, the first representative µ-OR ligand with G-protein bias, has entered into phase III clinical trials. To identify the detailed G-protein-biased activation and inactivation mechanisms of the µ-OR, we constructed five µ-OR systems that were in complexes with the G-protein-biased agonists TRV130 and BU72, the antagonists ß-FNA and naltrexone, as well as the free receptor. We performed a series of conventional molecular dynamics simulations and analyses of G-protein-biased activation and inactivation mechanisms of µ-OR. Our results, together with previously reported mutation results, revealed the operating mode of the activation switch composed of residues W6.48 and Y7.43 (Ballesteros/Weinstein numbering), the activity of which was responsible for down- and up-regulation, respectively, of the ß-arrestin signaling, which in turn affected G-protein-biased activation of µ-OR. TRV130 was found to stabilize W6.48 by interacting with Y7.43. In addition, we obtained useful information regarding µ-OR-biased activation, such as strong stabilization of W7.35 through a hydrophobic ring interaction in the TRV130 system. These findings may facilitate understanding of µ-OR biased activation and the design of new biased ligands for GPCRs.

Computational insights into the subtype selectivity and "message-address-efficacy" mechanisms of opioid receptors through JDTic binding and unbinding.

In drug design and discovery, binding affinity and selectivity are two basic properties of a drug candidate. Opioid receptors (ORs) are the main targets of strong analgesics. Like some other class A members of G-protein-coupled receptors (GPCRs), ORs exhibit complex selectivity on their ligands. The diversity of binding activity and selectivity among opioids has deeply attracted researchers for a long time. To investigate the subtype selectivity of µ, δ and κ ORs in detail, using the κ-selective antagonist JDTic as a probe, we performed a series of computational simulations, including molecular dynamics and metadynamics, on JDTic-µ/δ/κ-OR complexes. From the simulations, we found that the decisive factor of JDTic selectivity on the µ-subtype was the 2.63 position, which affected the efficacy of JDTic through changing the dynamics of the Q2.60 residue. In addition to the 2.63-position residue, the 7.35 position was the other crucial aspect of JDTic selectivity for the δ-subtype. Based on the results, we suggest a new concept, the "message-address-efficacy" hypothesis, to explain the relationships among the affinity, selectivity and function between ORs and opioids. Thus, all the detailed dynamics of JDTic-bound ORs might be helpful to deeply understand the subtype selectivity and binding mechanisms of other GPCRs.

Insights into the molecular mechanisms of Polygonum multiflorum Thunb-induced liver injury: a computational systems toxicology approach.

An increasing number of cases of herb-induced liver injury (HILI) have been reported, presenting new clinical challenges. In this study, taking Polygonum multiflorum Thunb (PmT) as an example, we proposed a computational systems toxicology approach to explore the molecular mechanisms of HILI. First, the chemical components of PmT were extracted from 3 main TCM databases as well as the literature related to natural products. Then, the known targets were collected through data integration, and the potential compound-target interactions (CTIs) were predicted using our substructure-drug-target network-based inference (SDTNBI) method. After screening for hepatotoxicity-related genes by assessing the symptoms of HILI, a compound-target interaction network was constructed. A scoring function, namely, Ascore, was developed to estimate the toxicity of chemicals in the liver. We conducted network analysis to determine the possible mechanisms of the biphasic effects using the analysis tools, including BiNGO, pathway enrichment, organ distribution analysis and predictions of interactions with CYP450 enzymes. Among the chemical components of PmT, 54 components with good intestinal absorption were used for analysis, and 2939 CTIs were obtained. After analyzing the mRNA expression data in the BioGPS database, 1599 CTIs and 125 targets related to liver diseases were identified. In the top 15 compounds, seven with Ascore values >3000 (emodin, quercetin, apigenin, resveratrol, gallic acid, kaempferol and luteolin) were obviously associated with hepatotoxicity. The results from the pathway enrichment analysis suggest that multiple interactions between apoptosis and metabolism may underlie PmT-induced liver injury. Many of the pathways have been verified in specific compounds, such as glutathione metabolism, cytochrome P450 metabolism, and the p53 pathway, among others. Hepatitis symptoms, the perturbation of nine bile acids and yellow or tawny urine also had corresponding pathways, justifying our method. In conclusion, this computational systems toxicology method reveals possible toxic components and could be very helpful for understanding the mechanisms of HILI. In this way, the method might also facilitate the identification of novel hepatotoxic herbs.

SM22α inhibits lamellipodium formation and migration via Ras-Arp2/3 signaling in synthetic VSMCs.

We previously demonstrated that smooth muscle (SM) 22α promotes the migration activity in contractile vascular smooth muscle cells (VSMCs). Based on the varied functions exhibited by SM22α in different VSMC phenotypes, we investigated the effect of SM22α on VSMC migration under pathological conditions. The results demonstrated that SM22α overexpression in synthetic VSMCs inhibited platelet-derived growth factor (PDGF)-BB-induced cell lamellipodium formation and migration, which was different from its action in contractile cells. The results indicated two distinct mechanisms underlying inhibition of lamellipodium formation by SM22α, increased actin dynamic stability and decreased Ras activity via interference with interactions between Ras and guanine nucleotide exchange factor. The former inhibited actin cytoskeleton rearrangement in the cell cortex, while the latter significantly disrupted actin nucleation activation of the Arp2/3 complex. Baicalin, a herb-derived flavonoid compound, inhibited VSMC migration via upregulation of SM22α expression in vitro and in vivo. These data suggest that SM22α regulates lamellipodium formation and cell migration in a phenotype-dependent manner in VSMCs, which may be a new therapeutic target for vascular lesion formation.

[Progress in study of selective ERß ligands].

Estrogen receptors (ERs) are members of nuclear receptors and related to several diseases such as cancer, inflammation and osteoporosis. ERs have two forms, ERα and ERß, which have different functions and organism distributions. Compounds selectively targeting ERß can regulate important physiological functions and avoid the side effects caused by targeting ERα. Therefore, selective ERß ligands have received considerable research interest in recent years. In this article, different kinds of selective ERß ligands were summarized and their structure-activity relationships were also analyzed.

Structure-based ensemble-QSAR model: a novel approach to the study of the EGFR tyrosine kinase and its inhibitors.

AIM: To develop a novel 3D-QSAR approach for study of the epidermal growth factor receptor tyrosine kinase (EGFR TK) and its inhibitors. METHODS: One hundred thirty nine EGFR TK inhibitors were classified into 3 clusters. Ensemble docking of these inhibitors with 19 EGFR TK crystal structures was performed. Three protein structures that showed the best recognition of each cluster were selected based on the docking results. Then, a novel QSAR (ensemble-QSAR) building method was developed based on the ligand conformations determined by the corresponding protein structures. RESULTS: Compared with the 3D-QSAR model, in which the ligand conformations were determined by a single protein structure, ensemble-QSAR exhibited higher R2 (0.87) and Q2 (0.78) values and thus appeared to be a more reliable and better predictive model. Ensemble-QSAR was also able to more accurately describe the interactions between the target and the ligands. CONCLUSION: The novel ensemble-QSAR model built in this study outperforms the traditional 3D-QSAR model in rationality, and provides a good example of selecting suitable protein structures for docking prediction and for building structure-based QSAR using available protein structures.

Selective ligands of estrogen receptor ß discovered using pharmacophore mapping and structure-based virtual screening.

AIM: To discover novel ligands of estrogen receptor (ER) ß using pharmacophore mapping and structure-based screening. METHODS: A computer-aided strategy combining pharmacophore mapping and structure-based screening was used to screen the Maybridge and Enamine databases. Yeast two-hybrid (Y2H) assay was used to detect the activity and selectivity of the chosen compounds. The transcriptional activities of the chosen compounds were demonstrated with luciferase reporter assays. The anti-proliferative effects of ER antagonists against MCF-7 and MDA-MB-231 breast cancer cells were examined using MTT assay, and the mechanisms of action were analyzed with flow cytometry analysis and Western blotting. RESULTS: Through in silico screen, 95 compounds were chosen for testing in Y2H assay, which led to 20 potent ligands, including 10 agonists, 8 antagonists and 2 partial agonists with EC50 or IC50 values at µmol/L. Furthermore, 6 agonists exhibited absolute selectivity for ERß, and 3 agonists showed higher selectivity for ERß. The agonists 1g and 1h (10, 25, and 50 µmol/L) dose-dependently increased ER transcriptional activities, whereas the antagonists 2a and 2d (10, 25, and 50 µmol/L) caused dose-dependent inhibition on the activities. The antagonists and partial agonists at 100 µmol/L suppressed the proliferation of ERα positive MCF-7 cells and ERß positive MDA-MB-231 cells, but were more effective against MDA-MB-231 cells. Treatment of MDA-MB-231 cells with antagonists 2a and 2d (25 and 50 µmol/L) dose-dependently increased the population of cells in the S phase. Both 2a and 2d treatment dose-dependently decreased the expression levels of cyclin A and CDK2. Meanwhile, the downregulation of cyclin E was only caused by 2d, while 2a treatment did not cause significant changes in the protein levels of cyclin E. CONCLUSION: The selective ligands discovered in this study are promising drug candidates to be used as molecular probes to explore the differences between ERα and ERß.

[Progress in the ligands and their complex structures of farnesoid X receptor].

Farnesoid X receptor (FXR) belongs to the nuclear receptor superfamily. It is highly related to the formation of metabolic syndrome and the glucose homeostasis, and therefore represents an important drug target against metabolic diseases and diabetes. In recent years, great progress has been made in the agonists, antagonists, and crystal structures of FXR. The diverse FXR ligands and their structure-activity relationship are reviewed in this article. The advances in the crystal structures of FXR in complex with different ligands are also introduced.

[Progress in study of the structure, catalytic mechanism and inhibitors of aromatase].

Aromatase is a key enzyme responsible for in vivo estrogen biosynthesis. Inhibition of the activity of the aromatase has become an alterative way for treatment of breast cancer. In this review, the structure and catalytic mechanism of the aromatase is briefly introduced followed by thorough review of the progress in the study of the steroidal and non-steroidal aromatase inhibitors. This review is focused on the natural compounds that exhibit the aromatase inhibition, which include flavonoids, xanthones, coumarins, and sesquiterpenes. The structure-activity relationship of these compounds is also discussed.

A Novel Mitochondrial-Related Gene Signature for the Tumor Immune Microenvironment Evaluation and Prognosis Prediction in Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) remains the most common deadly disease and has a poor prognosis. More and more studies have reported that mitochondrial-related genes (MTRGs) were associated with the clinical outcomes of multiple tumors solely. In this study, we aimed to develop a novel prognostic model based on MTRGs. Differentially expressed MTRGs were identified from TCGA-LUAD and GSE31210 cohorts. Univariate Cox regression analysis was utilized to screen differentially expressed MTRGs that were related to prognosis of LUAD. Then, LASSO Cox regression analysis was used to develop a prognostic signature. ESTIMATE was used for estimating the fractions of immune cell types. In this study, we identified 44 overlapping differentially expressed MTRGs in TCGA-LUAD and GSE31210 cohorts. Among 44 overlapping differentially expressed MTRGs, nine genes were associated with prognosis of LUAD. When the penalty parameter lambda was the minimum, there were six genes meeting the conditions of constructing the signature, including SERPINB5, CCNB1, FGR MAOB, SH3BP5, and CYP24A1. The survival analysis suggested that prognosis of patients in the high-risk group was significantly worse than that in the low-risk group. Cox regression analyses showed that the risk score was an independent predictor of LUAD prognosis. As with the results of ESTIMATE score, the degree of immune cell infiltration in the low-risk group was higher than that in the high-risk group, such as TIL, Treg, and B cells. In addition, TMB and cancer stem cell infiltration were higher in the low-risk group than the high-risk group. In conclusion, we developed a novel MTRG signature acting as a negative independent prognostic factor. In the future, individualized treatments and medical decision-making may benefit from using the predicted model.

[Application of NIR spectroscopy technology in the field of insect pests detection].

Near infrared spectroscopy (NIRS) is the most rapidly developing and the most noticeable spectrographic technique in the 80's (the last century). Its principle in detection of insect pests was introduced. The applications of NIRS to the field of insect pests detection were mainly summarized. The applications of near-infrared reflectance spectroscopy (NIRS) in detection of insect pests in stored-products, seed and forage or in leaves of plants are more active due to its rapid, timely, less expensive, non-destructive, and straightforward analytic characteristics. The applications of NIRS to the field of detection of insect pests in our country are rare and only on the beginning. So, there are still some further applications of NIRS in detection of insect pests in future, such as analyzing trace elements in fruit and biosecurity inspection. In the present paper, the authors analyzed the NIRS applications status home and abroad, and discussed the applied prospects to promote its applications to the field of research and practice of detection of insect pests in our country.

Bioassay of estrogenic activity of effluent and influent in a farm wastewater treatment plant using an in vitro recombinant assay with yeast cells.

OBJECTIVE: Environmental estrogens at an elevated concentration are known to produce adverse effects on human and animal life. However, the majority of researches have been focused on industrial discharges, while the impact of livestock wastes as a source of endocrine disrupters in aquatic environments has been rarely elucidated. In order to investigate the contribution of environmental estrogens from livestock, the estrogenic activity in water samples from a farm wastewater treatment plant was analyzed by a recombinant yeast screening method. METHODS: The extracts prepared from 15 selected water samples from the farm wastewater treatment plant, among which 6 samples were from pre-treatment section (influents) and 9 from post-treatment section (effluents), were analyzed for estrogenic activity by cellar bioassay. Yeast cells transfected with the expression plasmid of human estrogen receptor and the Lac Z reporter plasmid encoding beta-galactossidase, were used to measure the estrogen-like compounds in the farm wastewater treatment plant. RESULTS: The wastewater samples from influents showed a higher estrogenic potency than the effluent samples showing a low induction of beta-galactossidase relative to solvent control condition. By comparison with a standard curve for 17 beta-estradiol (E2), estrogenic potency in water samples from the influents was calculated as E2-equivalent and ranged from 0.1 to 150 pM E2-equivalent. The estrogenic potency in water samples from the effluents was significantly lower than that in the influents, and 7 water samples had less detectable limit in the total of 9 samples. CONCLUSION: Yeast bioassay of estrogenic activity in most of the samples from the farm wastewater after disposal by traditional sewage treatment showed negative results.

Improved gravitation field algorithm and its application in hierarchical clustering.

BACKGROUND: Gravitation field algorithm (GFA) is a new optimization algorithm which is based on an imitation of natural phenomena. GFA can do well both for searching global minimum and multi-minima in computational biology. But GFA needs to be improved for increasing efficiency, and modified for applying to some discrete data problems in system biology. METHOD: An improved GFA called IGFA was proposed in this paper. Two parts were improved in IGFA. The first one is the rule of random division, which is a reasonable strategy and makes running time shorter. The other one is rotation factor, which can improve the accuracy of IGFA. And to apply IGFA to the hierarchical clustering, the initial part and the movement operator were modified. RESULTS: Two kinds of experiments were used to test IGFA. And IGFA was applied to hierarchical clustering. The global minimum experiment was used with IGFA, GFA, GA (genetic algorithm) and SA (simulated annealing). Multi-minima experiment was used with IGFA and GFA. The two experiments results were compared with each other and proved the efficiency of IGFA. IGFA is better than GFA both in accuracy and running time. For the hierarchical clustering, IGFA is used to optimize the smallest distance of genes pairs, and the results were compared with GA and SA, singular-linkage clustering, UPGMA. The efficiency of IGFA is proved.

Inferring gene regulatory networks by singular value decomposition and gravitation field algorithm.

Reconstruction of gene regulatory networks (GRNs) is of utmost interest and has become a challenge computational problem in system biology. However, every existing inference algorithm from gene expression profiles has its own advantages and disadvantages. In particular, the effectiveness and efficiency of every previous algorithm is not high enough. In this work, we proposed a novel inference algorithm from gene expression data based on differential equation model. In this algorithm, two methods were included for inferring GRNs. Before reconstructing GRNs, singular value decomposition method was used to decompose gene expression data, determine the algorithm solution space, and get all candidate solutions of GRNs. In these generated family of candidate solutions, gravitation field algorithm was modified to infer GRNs, used to optimize the criteria of differential equation model, and search the best network structure result. The proposed algorithm is validated on both the simulated scale-free network and real benchmark gene regulatory network in networks database. Both the Bayesian method and the traditional differential equation model were also used to infer GRNs, and the results were used to compare with the proposed algorithm in our work. And genetic algorithm and simulated annealing were also used to evaluate gravitation field algorithm. The cross-validation results confirmed the effectiveness of our algorithm, which outperforms significantly other previous algorithms.

[Construction of the recombinant adenovirus expressing the CVB3 sVP1-C3d3 protein and study on its immunological effects in mice].

AIM: To construct recombinant adenovirus Ad/C3d3-sVP1 and investigate the immune effects against coxsackievirus infection in mouse. METHODS: The recombinant adenovirus Ad/sVP1-C3d3 was constructed and packaged. BALB/c mouse were divided into four groups: Ad/sVP1-C3d3 group, Ad/VP1 group, Ad group and PBS group. The mice in each group were immunized by intramuscular injection. The titers of sera IgG and neutralizing antibody were detected by ELISA method and trace neutralization assay, respectively.The specific CTL cytotoxic activity was detected by CCK-8 assay. The mice in each group were challenged with lethal dose of coxsackievirus, the titers of the sera virus were titrated. RESULTS: The recombinant adenovirus Ad/sVP1-C3d3 was successfully constructed. It's observed that the titers of CVB3 VP1 specific antibody and neutralizing antibody were much higher than those of the other three groups(P<0.01). CTL cytotoxicity activities was much higher than PBS and Ad group(P<0.01), but little higher than Ad/VP1 group(P<0.05).The titer of sera virus was lower than Ad and PBS groups after CVB3 challenged(P<0.05). CONCLUSION: Both the celluar and humoral immune responses in mice could been significantly enhanced by Ad/sVP1-C3d3.

Gravitation field algorithm and its application in gene cluster.

BACKGROUND: Searching optima is one of the most challenging tasks in clustering genes from available experimental data or given functions. SA, GA, PSO and other similar efficient global optimization methods are used by biotechnologists. All these algorithms are based on the imitation of natural phenomena. RESULTS: This paper proposes a novel searching optimization algorithm called Gravitation Field Algorithm (GFA) which is derived from the famous astronomy theory Solar Nebular Disk Model (SNDM) of planetary formation. GFA simulates the Gravitation field and outperforms GA and SA in some multimodal functions optimization problem. And GFA also can be used in the forms of unimodal functions. GFA clusters the dataset well from the Gene Expression Omnibus. CONCLUSIONS: The mathematical proof demonstrates that GFA could be convergent in the global optimum by probability 1 in three conditions for one independent variable mass functions. In addition to these results, the fundamental optimization concept in this paper is used to analyze how SA and GA affect the global search and the inherent defects in SA and GA. Some results and source code (in Matlab) are publicly available at http://ccst.jlu.edu.cn/CSBG/GFA.

Synthesis and characteristic of the Fe3O4@SiO2@Eu(DBM)3.2H2O/SiO2 luminomagnetic microspheres with core-shell structure.

The core-shell structured luminomagnetic microsphere composed of a Fe(3)O(4) magnetic core and a continuous SiO(2) nanoshell doped with Eu(DBM)(3).2H(2)O fluorescent molecules was fabricated by a modified Stöber method combined with a layer-by-layer assembly technique. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), confocal microscopy, photoluminescence (PL), and superconducting quantum interface device (SQUID) were employed to characterize the Fe(3)O(4)@SiO(2)@Eu(DBM)(3).2H(2)O/SiO(2) microspheres. The experimental results show that the microshpere has a typical diameter of ca. 500 nm consisting of the magnetic core with about 340 nm in diameter and silica shell doped with europium complex with an average thickness of about 80 nm. It possesses magnetism with a saturation magnetization of 25.84 emu/g and negligible coercivity and remanence at room temperature and exhibits strong red emission peak originating from electric-dipole transition (5)D(0)-->(7)F(2) (611 nm) of Eu(3+) ions. The luminomagnetic microspheres can be uptaken by HeLa cells and there is no adverse cell reaction. These results suggest that the luminomagnetic microspheres with magnetic resonance response and fluorescence probe property may be useful in biomedical imaging and diagnostic applications.

[Immune effects of four coxsackievirus B3 VP1 DNA fusion vaccines in mice].

AIM: To compare the immunogenicity and protective effects on CVB3 infected mice of four DNA fusion vaccines coupling coxsackievirus B3 (CVB3) VP1 with macrophage-derived chemokine (MDC), C3d3, shiga toxin B subuit (STxB) and mouse beta-defensin-2 (mBD2), respectively. METHODS: BALB/c mice were divided into 6 groups randomly and inoculated in quadriceps at 3-week interval for 3 times with pcDNA3, pcDNA3/VP1, pcDNA3/MDC-VP1, pcDNA3/VP1-C3d3, pcDNA3/STxB-VP1 and pcDNA3/mBD2 -VP1, respectively. Fourteen days after every inoculation, serum samples were collected and CVB3 specific neutralizing antibodies were determined. Three weeks after the last immunization, the mice were treated in three ways. First, the spleen cells were isolated from 3 mice of each group and specific CTL activities were tested. Second, 3 mice of each group were further challenged with 3LDLD(50); CVB3 and sacrificed 7 days later, and their blood viral titers were evaluated. Third, the rest mice of each group were subjected to intraperitoneal (i.p.) challenge with 5LDLD(50); CVB3 and their survival was observed. RESULTS: The neutralizing antibodies against CVB3 were induced in pcDNA3/VP1, pcDNA3/MDC-VP1, pcDNA3/VP1-C3d3, pcDNA3/STxB-VP1 and pcDNA3/mBD2 -VP1 groups, and antibody titers correlated with the number of injections (P<0.01). After three immunizations, the antibody titers in pcDNA3/MDC-VP1, pcDNA3/VP1-C3d3 and pcDNA3/mBD2 -VP1 groups were higher than the ones in pcDNA3/VP1and pcDNA3/STxB-VP1 groups (P<0.01). The specific CTL activities in both pcDNA3/STxB-VP1 and pcDNA3/mBD2-VP1 groups were significantly stronger than those in the other groups (P<0.01). After CVB3 challenge, the blood viral titers in the pcDNA3/MDC-VP1, pcDNA3/VP1-C3d3 and pcDNA3/mBD2-VP1 groups were lower than those in the other groups (P<0.01), and the pcDNA3/MDC-VP1 and pcDNA3/VP1-C3d3 mice survived longer than the others (P<0.05). CONCLUSION: Both pcDNA3/MDC-VP1 and pcDNA3/VP1-C3d3 vaccines could induce stronger immune responses, resulting in higher survival rates and better protective effects on CVB3 infection than pcDNA3/STxB-VP1, pcDNA3/mBD2-VP1 and pcDNA3/VP1 vaccines.

Molecular docking and 3D-QSAR studies of 2-substituted 1-indanone derivatives as acetylcholinesterase inhibitors.

AIM: To explore the binding mode of 2-substituted 1-indanone derivatives with acetylcholinesterase (AChE) and provide hints for the future design of new derivatives with higher potency and specificity. METHODS: The GOLD-docking conformations of the compounds in the active site of the enzyme were used in subsequent studies. The highly reliable and predictive three-dimensional quantitative structure-activity relationship (3D-QSAR) models were achieved by comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) methods. The predictive capabilities of the models were validated by an external test set. Moreover, the stabilities of the 3D-QSAR models were verified by the leave-4-out cross-validation method. RESULTS: The CoMFA and CoMSIA models were constructed successfully with a good cross-validated coefficient (q(2)) and a non-cross-validated coefficient (r(2)). The q(2)and r(2)obtained from the leave-1-out cross validation method were 0.784 and 0.974 in the CoMFA model and 0.736 and 0.947 in the CoMSIA model, respectively. The coefficient isocontour maps obtained from these models were compatible with the geometrical and physicochemical properties of AChE. CONCLUSION: The contour map demonstrated that the binding affinity could be enhanced when the small protonated nitrogen moiety was replaced by a more hydrophobic and bulky group with a highly partial positive charge. The present study provides a better understanding of the interaction between the inhibitors and AChE, which is helpful for the discovery of new compounds with more potency and selective activity.