Application and advance of artificial intelligence in biomedical field / 中国药科大学学报

@#Artificial intelligence (AI) has developed rapidly in the twentieth century, and has substantialy changed the modern way of life.At the same time, AI has greatly contributed to the development of the pharmaceutical industry, playing a key role in precision medicine, intelligent diagnosis, computer-aided drug design, and clinical trial decision-making, and has also greatly developed itself through its integration with the pharmaceutical industry.This paper outlines the key issues in research, describes the key applications of AI in the health and pharmaceutical industries, and finally analyzes the opportunities and challenges of AI in the health pharmaceutical industry to provide reference for the development of AI in the health and pharmaceutical fields.

Research of the mechanism of Huganning tablet in the treatment of nonalcoholic fatty liver disease based on network pharmacology and computer-aided drug design / 药学学报

In this study, we explored the mechanism of Huganning tablet (HGNP) in the treatment of nonalcoholic fatty liver disease (NAFLD) based on network pharmacology and computer-aided drug design. Firstly, the potential ingredients and targets of HGNP were identified from TCMSP database, Swiss Target Prediction database, Chinese pharmacopoeia (2015) and literatures, and then the targets of HGNP intersected with NAFLD disease targets that obtained in GeneCards database to acquired potential targets. The bioconductor bioinformatics package of R software was used for gene ontology (GO) enrichment and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis. The network of “potential ingredient-key target-pathway” was formed in Cytoscape software to study the interactions between potential ingredients of HGNP, key targets, pathways and NAFLD. Based on the results of network pharmacology, the molecular docking analysis of the key targets and potential active ingredients in HGNP tablets with top degree in the network was conducted using Discovery Studio 2020 software, followed by molecular dynamics simulations, binding free energy calculation, drug-likeness properties analysis and ADMET (absorption, distribution, metabolism, excretion and toxicity) properties prediction. In vitro, HepG2 cells were used to establish steatosis model, and the effects of five key compounds on hepatocyte steatosis were analyzed by oil red O staining and triglyceride (TG) content determination. The results showed that 141 ingredients and 151 potential targets were obtained. A total of 2 526 items and 151 pathways were identified by GO and KEGG enrichment analysis. The molecular docking suggested that five components, isorhamnetin, salvianolic acid B, emodin, resveratrol and rhein, exhibited strong binding ability with key targets [retinoic acid receptor RXR-alpha (RXRA), tumor necrosis factor (TNF), glycogen synthase kinase-3 beta (GSK3B), serine/threonine-protein kinase 1 (AKT1)]. It was further verified that isorhamnetin and salvianolic acid B bind to key targets with good structural stability and binding affinity based on molecular dynamics simulations and binding free energy calculations. The drug-likeness properties, pharmacokinetic properties and toxicity of five key compounds were more comprehensively analyzed through drug-likeness properties analysis and ADMET properties prediction. In vitro, all five compounds, isorhamnetin, salvianolic acid B, emodin, resveratrol, and rhein, improved hepatocyte steatosis of HepG2 cells, confirming the reliability of the present study. In conclusion, based on network pharmacology, computer-aided drug design and in vitro validation, this study investigated the mechanism of HGNP for the treatment of NAFLD at multiple levels and provided a basis for its clinical application.

Application and development of systems biology in computer-aided drug design / 中国中药杂志

With the advances in medicine, people have deeply understood the complex pathogenesis of diseases. Revealing the mechanism of action and therapeutic effect of drugs from an overall perspective has become the top priority of drug design. However, the traditional drug design methods cannot meet the current needs. In recent years, with the rapid development of systems biology, a variety of new technologies including metabolomics, genomics, and proteomics have been used in drug research and development. As a bridge between traditional pharmaceutical theory and modern science, computer-aided drug design(CADD) can shorten the drug development cycle and improve the success rate of drug design. The application of systems biology and CADD provides a methodological basis and direction for revealing the mechanism and action of drugs from an overall perspective. This paper introduces the research and application of systems biology in CADD from different perspectives and proposes the development direction, providing reference for promoting the application.

FBDD and drugs originated from FBDD / 药学学报

The binding of small molecule drugs to targets is mostly through non-covalent bonds, and hydrogen bond, electrostatic, hydrophobic and van der Waals interactions function to maintain the binding force. The more these binding factors lead to strong bindings and high activities. However, it is often accompanied by the increase of molecular size, resulting in pharmacokinetic problems such as membrane penetration and absorption, as well as metabolism, which ultimately affects the drug success. Fragment-based drug discovery (FBDD) is to screen high-quality fragment library to find hits. Combine with structural biology, FBDD generates lead compounds by means of fragment growth, linking and fusion, and finally drug candidates by the optimization operation. During the value chain FBDD is closely related to structure-based drug discovery (SBDD). In this paper, the principle of FBDD is briefly described by several launched drugs.

Molecular mechanism of Cigu Xiaozhi formula interfering with HSC-T6 cell activation by regulating HIF-1α signaling pathway based on computer aided drug design / 药学学报

In this study, we investigated the effect of Cigu Xiaozhi formula on HSC-T6 activity in hypoxic microenvironment based on network pharmacology and computer-aided drug design, and predicted and verified its possible targets and related signaling pathways. The potential active components and targets of Cigu Xiaozhi formula were screened by searching Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Encyclopaedia of Traditional Chinese Medicine (ETCM) and Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) databases, and the liver fibrosis related targets retrieved from Gene Cards and Pharm GK database were integrated to obtain the potential targets of Cigu Xiaozhi formula in the treatment of liver fibrosis. GO enrichment analysis and KEGG signaling pathway enrichment analysis were performed on Omic Share platform, and Cytoscape software was used to construct the "potential active ingredient-key target-pathway" network. The active components and target proteins were subjected to molecular docking analysis by Auto Dock software. According to the results of molecular dynamics simulation and binding free energy calculation, the top 5 active components with degree were scored. The active components stigmasterol and β-sitosterol were subjected to molecular docking. CoCl2 was used to induce HSC-T6 cells to construct hypoxia model in vitro. The cell viability was detected by CCK-8 assay, and the optimal time and concentration of hypoxia model of HSC-T6 cells was determined to be 100 µmol·L-1 CoCl2 for 24 h. Under hypoxia condition, HSC-T6 cells were activated, the wound healing rate was significantly increased, and the fluorescence signal of activation marker protein α-smooth muscle actin (α-SMA) was significantly enhanced. However, 6% drug-containing serum could inhibit the activation of HSC-T6 cells, and the wound healing rate was significantly decreased, and the fluorescence signal of α-SMA was significantly weakened. Further studies showed that the expressions of hypoxia-inducible factor-1α (HIF-1α), α-SMA and key proteins of Hedgehog (Hh) signaling pathway in HSC-T6 cells were up-regulated under hypoxia, while the expressions of HIF-1α, α-SMA, Patched-1 (Ptch-1) and glioma related oncogene homology-1 (Gli-1) were down-regulated in 6% drug-containing serum group, the YC-1 group and the cyclopamine group. These results indicated that HIF-1α and Hh signaling pathways were involved in the activation of HSC-T6 cells, and the traditional Chinese medicine Cigu Xiaozhi formula could inhibit the activation of HSC-T6 cells, and the mechanism may be related to the inhibition of HIF-1α expression and the blocking of Hh signaling pathway. In conclusion, Cigu Xiaozhi formula can inhibit the activation of HSC-T6 cells by directly acting on HIF-1α and Hh signaling pathway, and exert an anti-hepatic fibrosis effect. The animal experimental protocol has been reviewed and approved by Laboratory Animal Ethics Committee of Gansu University of Chinese Medicine, in compliance with the Institutional Animal Care Guidelines.

Analysis of in vitro activity and compatibility of Dunhuang Yifang Dabupi Decoction on gastric cancer based on computer-aided drug design / 药学学报

Based on the research system of computer-aided drug design combined with complex network analysis, the potential mechanism of Dunhuang Dabupi Decoction in preventing and treating gastric cancer (GC) is analyzed, and the scientific connotation of its prescription rules is explored through the efficacy grouping. To study the effect of Dabupi Decoction freeze-dried powder solution on the proliferation activity of gastric cancer cells through cell experiments; the TCMSP and TCMID databases were used to collect the compound components of Dabupi Decoction. Swiss Target Prediction is used to predict potential targets of compounds. DrugBank, GeneCards, TTD, and DisGeNET were used to collect potential targets for gastric cancer. Analyze protein interactions of potential targets through the STRING database. DAVID database was used for KEGG enrichment analysis; Dabupi Decoction was divided into Wenzhong group (dried ginger), Yiqi group (ginseng, licorice, Atractylodes macrocephala), nourishing Yin group (Ophiopogon japonicus, Schisandra) and Jiangni group according to its efficacy characteristics. The inverse group (inula) has 4 functional compatibility groups. Cytoscape was used to construct a network of "medicinal flavor-potential active ingredient-key target" respectively, and the network was used to analyze the scientific connotation of the compatibility of efficacy groups. The Schrödinger software was used to verify the molecular docking of the core components and the core targets. The material basis of the Dabupi Decoction to prevent and treat gastric cancer was discovered through the combination of pattern analysis and combined free energy calculation. The core drug was analyzed from the perspective of dynamics through molecular dynamics simulation. Potential targets and representative potential compounds interact with each other. Cell experiments confirmed that Dabupitang freeze-dried powder solution can down-regulate the mitochondrial membrane potential of AGS gastric cancer cells, block the cell cycle in the G0/G1 phase (P < 0.05), and inhibit its proliferation (P < 0.05). The pathways enriched by the four functional groups contained in Dabupi Decoction are mainly distributed in the body's energy metabolism, inflammation-immune system regulation, and cycle-apoptotic functions. Each module is connected by a common target gene and has its own focus. The results of molecular docking showed that the compounds liquiritigenin, quercetin, kaempferol, isorhamnetin, methylophiopogonanone A, etc. may be the effective multi-target components of Dabupi Decoction. Estrogen receptor 1, androgen receptor, ATP-binding cassette superfamily G member 2, epidermal growth factor receptor, glycogen synthase kinase-3 beta and other targets have good affinity with each potential active compound, which may be a potential target of Dabupi Decoction for preventing and treating gastric cancer. Among them, kaempferol and the drug target EGFR not only have good binding ability, but also have good binding stability. This study is based on computer-aided drug design combined with complex network analysis strategies to initially reveal the material basis and molecular mechanism of Dabupi Decoction in the prevention and treatment of gastric cancer. It also explores the scientific connotation of Dabupi Decoction in the prevention and treatment of gastric cancer with different efficacy groups, and its clinical application provide chemical bioinformatics basis.

Material basis and molecular mechanism of Angelicae Sinensis Radix in activating blood:based on computer-aided drug design / 中国中药杂志

Angelicae Sinensis Radix excels in activating blood, but the scientific mechanism has not been systematically analyzed, thus limiting the development of the medicinal. This study employed the computer-aided drug design methods, such as structural similarity-based target reverse prediction, complex network analysis, molecular docking, binding free energy calculation, cluster analysis, and ADMET(absorption, distribution, metabolism, excretion, toxicity) calculation, and enzyme activity assay in vitro, to explore the components and mechanism of Angelicae Sinensis Radix in activating blood. Target reverse prediction and complex network analysis yielded 40 potential anticoagulant targets of the medicinal. Gene Ontology(GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis indicated that the targets mainly acted on the complement and coagulation cascade signaling pathway to exert the anticoagulant function. Among them, the key enzymes thrombin(THR) and coagulation factor Xa(FXa) in coagulation cascade and thrombosis were the drug targets for thromboembolic diseases. At the same time, molecular docking and cluster analysis showed that the medicinal had high selectivity for FXa. According to binding free energy score, 8 potential active components were selected for enzyme activity assay in vitro. The results demonstrated that 8 components inhibited THR and FXa, and the inhibition was stronger on FXa than on THR. The pharmacophore model of 8 active compounds was constructed, which suggested that the components had the common pharmacophore AAHH. The ADMET calculation result indicated that they had good pharmacokinetic properties and were safe. Based on target reverse prediction, complex network analysis, molecular docking and binding free energy calculation, anticoagulant activity in vitro, spatial binding conformation of molecules and targets, pharmacophore model construction, and ADMET calculation, this study preliminarily clarified the material basis and molecular mechanism of Angelicae Sinensis Radix in activating blood from the perspective of big data, and calculated the pharmacology and toxicology parameters of the active components. Our study, for the first time, revealed that the medicinal had obvious selectivity and pertinence for different coagulation proteins, reflecting the unique effect of different Chinese medicinals and the biological basis. Therefore, this study can provide clues for precision application of Angelicae Sinensis Radix and the development of the blood-activating components with modern technology.

Progress on the application of artificial intelligence technology in ligand-based and receptor structure-based drug screening / 药学学报

Artificial intelligence technology is being widely applied in drug screening. This paper introduces the characteristics of artificial intelligence, and summarizes the application and progress of artificial intelligence technology especially deep learning in drug screening, from ligand-based and receptor structure-based aspects. This paper also introduces how to apply artificial intelligence to drug design from these two aspects. Finally, we discuss the main limitations, challenges, and prospects of artificial intelligence technology in the field of drug screening.

Gains from no real PAINS: Where 'Fair Trial Strategy' stands in the development of multi-target ligands

Compounds that selectively modulate multiple targets can provide clinical benefits and are an alternative to traditional highly selective agents for unique targets. High-throughput screening (HTS) for multitarget-directed ligands (MTDLs) using approved drugs, and fragment-based drug design has become a regular strategy to achieve an ideal multitarget combination. However, the unexpected presence of pan-assay interference compounds (PAINS) suspects in the development of MTDLs frequently results in nonspecific interactions or other undesirable effects leading to artefacts or false-positive data of biological assays. Publicly available filters can help to identify PAINS suspects; however, these filters cannot comprehensively conclude whether these suspects are "bad" or innocent. Additionally, these

Design, synthesis and biological evaluation of pyrazolo3,4-

Fibroblast growth factor receptors (FGFRs) have emerged as promising targets for anticancer therapy. In this study, we synthesized and evaluated the biological activity of 66 pyrazolo[3,4-

Synthesis and biological evaluation of oleanolic acid analogs based on survivin target / 中国药学杂志

OBJECTIVE: To design and synthesize a series of oleanolic acid analogs posessing anti-tumor activity based on survivin target. METHODS: Using the techniques of computer-aided drug design, the docking of Survivin and known active small molecules was simulated and then the key amino acid residue fragment of the target protein was analyzed. It led to the discovery of active groups capable of binding to the critical sites. Through using the natural product, oleanolic acid, as a lead compound, the active groups were introduced onto its A-ring, and the carboxyl group at the C-28 position was modified using amidation. SGC-7901 and A549 cells were used to screen the antitumor activity in vitro through the standard MTT method. RESULTS: Ten new oleanolic acid derivatives were designed and synthesized,and their structures were confirmed by MS and NMR. The compounds 5 and Ⅱ5 exhibited more potent cytotoxicity than the positive control drugs. CONCLUSION: The novel oleanolic acid analogues have better antitumor activity than the parent compound, which are worthy of further study.

Effects and mechanism research of total saponins of Panax japonicas improving lipid metabolism in HepG2 cells based on computer aided drug design / 中草药

Objective To research the effects of total saponins of Panax japonicas (TSPJ) improving lipid metabolism in HepG2 cells, and to predict and verify TPSJ possible targets based on computer aided drug design. Methods HepG2 cells fatty degeneration model was induced with palmitic-acid (PA). The HepG2 cells were divided into five groups: the control group, the model group, the high-dose group (50 mg/L), the middle-dose group (25 mg/L), and the low-dose group (12.5 mg/L). The cells of five groups were cultured continuously for 24 h. The intracellular lipid accumulation was qualitative and quantitative detected by Oil red and Nile red staining. The content of triglyceride (TG) was detected by detection kit. TPSJ possible targets were predicted by computer. The expressions of related proteins were detected by immunofluorescence. Results The lipid accumulation model of HepG2 cells was successfully established for 24 h with the 100 μmol/L concentration of PA. TSPJ can significantly improve the lipid accumulation (P < 0.01), and decrease the content of triglyceride (TG) of HepG2 cells. The possible target of TSPJ may be estrogen-related receptors based on computer aided drug design. Compared with the control group, the expression levels of estrogen receptor β (ERβ) protein in model group were decreased. Compared with the model group, the expression level of ERβ protein in high-, middle-, and low-dose group were upregulated. Conclusion TSPJ can significantly improve the lipid metabolism of HepG2 cells, and the target of TSPJ might be ERβ.

Computer Aided Drug Designing

Designing of drugs and their development are a time and resource consuming process. There is an increasing effort to introduce the role of computational approach to chemical and biological space in order to organise the design and development of drugs and their optimisation. The role of Computer Aided Drug Designing (CADD) are nowadays expressed in Nanotechnology, Molecular biology, Biochemistry etc. It is a diverse discipline where various forms of applied and basic researches are interlinked with each other. Computer aided or in Silico drug designing is required to detect hits and leads. Optimise/ alter the absorption, distribution, metabolism, excretion and toxicity profile and prevent safety issues. Some commonly used computational approaches include ligand-based drug design, structure-based drug design, and quantitative structure-activity and quantitative structure-property relationships. In today's world, due to an avid interest of regulatory agencies and, even pharmaceutical companies in advancing drug discovery and development process by computational means, it is expected that its power will grow as technology continues to evolve. The main purpose of this review article is to give a brief glimpse about the role Computer Aided Drug Design has played in modern medical science and the scope it carries in the near future, in the service of designing newer drugs along with lesser expenditure of time and money

Study on the Computer Virtual Screening of Antithrombotic Active Ingredients in Chuanxiong Rhizoma / 中国药房

OBJECTIVE:To find the active ingredient of on antithrombotic chuanxiong rhizoma using computer aided drug de-sign. METHODS:Usingthrombosisas keyword,thrombosis related proteins were searched and screened in therapeutic target da-tabase;target proteins'three-dimensional structure were downloaded in protein database,then the protein preparing tool were used to determine the coordinates of the active area center. PyRx software and Discovery Studio Visualizer were used to match the 247 small molecules of chuanxiong rhizoma with target protein that downloaded from Taiwan traditional Chinese medicine database. The active molecules were screened and binding force was analyzed. RESULTS:Active molecules of neochlorogenic acid,1-H-benz-imidazole-2-amine,3,8-dihydrodiligustilide,chuanxiongterpene were selected by blinding energy,and there were high binding ac-tivity among these active molecules,thrombin,antithrombinⅢ,coagulation factorⅩa and thrombomodulin,and the binding ener-gy were -6.1,-4.5,-7.7,-8.6 kJ/mol. Analysis results showed van Edward force and electrostatic interactions played an im-portant role in their respective docking. CONCLUSIONS:Neochlorogenic acid,1-H-benzimidazole-2-amine,3,8-dihydrodiligusti-lide,chuanxiongterpene may be the antithrombotic activity ingredients of Chuanxiong rhizoma.

New perspectives on the computational characterization of the kinetics of binding-unbinding in drug design: implications for novel therapies / Nuevas perspectivas sobre la caracterización computacional de la cinética de unión-desunión en el diseño de fármacos: implicaciones para terapias de vanguardia

Abstract: The efficiency and the propensity of a drug to be bound to its target protein have been inseparable concepts for decades now. The correlation between the pharmacological activity and the binding affinity has been the first rule to design and optimize a new drug rationally. However, this argument does not prove to be infallible when the results of in vivo assays have to be confronted. Only recently, we understand that other magnitudes as the kinetic rates of binding and unbinding, or the mean residence time of the complex drug-protein, are equally relevant to draw a more accurate model of the mechanism of action of a drug. It is in this scenario where new computational techniques to simulate the all-atom dynamics of the biomolecular system find its valuable place on the challenge of designing new molecules for more effective and less toxic therapies.

Resumen: La eficiencia de un fármaco se ha relacionado habitualmente con su constante de afinidad, magnitud que puede ser medida experimentalmente in vitro y que cuantifica la propensión mostrada por la molécula ligando para interaccionar con su proteína diana. Este modo de entender el mecanismo de acción ha guiado durante años el desarrollo de nuevas moléculas con potencial farmacológico. Sin embargo, dicho modelo o criterio no es infalible cuando se confronta con los resultados de ensayos in vivo. Otras magnitudes, como las constantes cinéticas de asociación o disociación o el tiempo de residencia del ligando acoplado a su proteína diana, demuestran ser igualmente necesarias para comprender y predecir la capacidad farmacológica del compuesto químico. En este nuevo escenario, con ayuda de las técnicas computacionales de simulación molecular, la correcta caracterización del proceso dinámico de unión y desunión del ligando y receptor resulta imprescindible para poder diseñar racionalmente nuevas moléculas que permitan terapias más eficaces y menos tóxicas.

Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

Structure-based drug design studies of the interactions of ent-kaurane diterpenes derived from Wedelia paludosa with the Plasmodium falciparum sarco/endoplasmic reticulum Ca2+-ATPase PfATP6

Malaria is responsible for more deaths around the world than any other parasitic disease. Due to the emergence of strains that are resistant to the current chemotherapeutic antimalarial arsenal, the search for new antimalarial drugs remains urgent though hampered by a lack of knowledge regarding the molecular mechanisms of artemisinin resistance. Semisynthetic compounds derived from diterpenes from the medicinal plant Wedelia paludosa were tested in silico against the Plasmodium falciparum Ca2+-ATPase, PfATP6. This protein was constructed by comparative modelling using the three-dimensional structure of a homologous protein, 1IWO, as a scaffold. Compound 21 showed the best docking scores, indicating a better interaction with PfATP6 than that of thapsigargin, the natural inhibitor. Inhibition of PfATP6 by diterpene compounds could promote a change in calcium homeostasis, leading to parasite death. These data suggest PfATP6 as a potential target for the antimalarial ent-kaurane diterpenes.

Estudos QSAR e Ancoragem Molecular de Inibidores da Atividade Biológica do Fator de Inibição da Migração dos Macrófagos (MIF) / QSAR Modeling and Molecular Docking Study of Inhibitors of Macrophage Migration Inhibitory Factor (MIF)

Cumarina e 4-Cromonas são promissores inibidores de fator inibição da migração de macrófagos (MIF), uma proteína envolvida em doenças inflamatórias, como artrite reumatóide e outras patologias. Estudos teóricos de QSAR e ancoragem molecular de um conjunto de compostos mostraram correlação com estudos experimentais. Os descritores doadores de ligação hidrogênio e momento dipolo total foram capazes de prever atividade inibitória de compostos contra o MIF (MIFi). Paralelamente, estudos de ancoragem molecular também foram capazes de identificar ligações hidrogênio e hidrofóbicas entre os ligantes e o MIF. Como resultado, ambas as metodologias mostraram as contribuições de ligação de hidrogênio e interações hidrofóbicas para explicar a atividade de compostos inibidores de MIF, descrevendo os grupos farmacofóricos destes compostos. Adicionalmente, um conjunto de cumarinas naturais e sintéticas foi submetido aos modelos QSAR e de ancoragem molecular a fim de que as suas atividades contra MIF fossem preditas. Ambas as metodologias de modelagem molecular puderam estimar as interações intermoleculares entre inibidores e a enzima, os quais foram muito similares a compostos descritos previamente. Estes resultados podem ser úteis para o desenho de novos compostos contra doenças inflamatórias como artrite reumatóide.

Coumarin and Chromen-4-one are promising inhibitors of Macrophage Migration Inhibitory Factor (MIF), a protein involved in rheumatoid arthritis and other inflammatory diseases. Quantum structure-activity relationship (QSAR) and docking theoretical studies were undertaken on a set of compounds of known activity and showed agreement with previous experimental studies. Two descriptors, hydrogen donor sites and the total dipole, were able to predict MIF inhibitory activity (MIFi). The docking studies corroborated the QSAR studies. As a result, both methods indicated contributions of hydrogen bonds and hydrophobic interactions that explain the activity of the MIF inhibitors, describing the pharmacophore groups these molecules. Additionally, a set of natural and synthetic coumarins was subjected to the QSAR and docking models in order to predict their possible MIF inhibitory activity. Both molecular modeling methods were able to estimate the intermolecular interactions between inhibitors and enzyme, which were very similar to those of previously described compounds. These results could be useful to design new compounds against inflammatory diseases such as rheumatoid arthritis.

Construction of the pharmacophore model of acetylcholinesterase inhibitor / 药学学报

Based on ninety three acetylcholinesterase inhibitors (AChEIs) which have the same mechanism of action but are different in structural characteristics, the pharmacophore model for acetylcholinesterase inhibitor was constructed by the CATALYST system. The optimal pharmacophore model with three hydrophobic units, a ring aromatic unit and a hydrogen-bond acceptor unit were confirmed (Weight=3.29, RMS=0.53, total cost-null cost=62.75, Correl=0.93, Config=19.05). This pharmacophore model will act on the double active site of acetylcholinesterase and is able to predict the activity of known acetylcholinesterase inhibitors that are used for clinical treatment of Alzheimer's disease (AD), and can be further used to identify structurally diverse compounds that have higher activity treating with Alzheimer's disease (AD) by virtual screening.