Computer simulation of molecular docking between methylene blue and some proteins of Porphyromonas gingivalis / 北京大学学报(医学版)

OBJECTIVE@#To study the binding target of photosensitizer and bacteria in antimicrobial photodynamic therapy with computer-simulated target prediction and molecular docking research methods and to calculate the binding energy.@*METHODS@#The protein names of Porphyromonas gingivalis (Pg) were obtained and summarized in Uniprot database and RCSB PDB database; the structure diagrams of methy-lene blue were screened in SciFinder database, PubChem database, ChemSpider database, and Chemical Book, and ChemBioDraw software was used to draw and confirm the three-dimensional structure for target prediction and Cytoscape software was used to build a visual network diagram; a protein interaction network was searched and built between the methylene blue target and the common target of Pg in the String database; then we selected FimA, Mfa4, RgpB, and Kgp K1 proteins, used AutoDock software to calculate the docking energy of methylene blue and the above-mentioned proteins and performed molecular docking.@*RESULTS@#The target prediction results showed that there were 19 common targets between the 268 potential targets of methylene blue and 1 865 Pg proteins. The 19 targets were: groS, radA, rplA, dps, fabH, pyrG, thyA, panC, RHO, frdA, ileS, bioA, def, ddl, TPR, murA, lepB, cobT, and gyrB. The results of the molecular docking showed that methylene blue could bind to 9 sites of FimA protein, with a binding energy of -6.26 kcal/mol; with 4 sites of Mfa4 protein and hydrogen bond formation site GLU47, and the binding energy of -5.91 kcal/mol, the binding energy of LYS80, the hydrogen bond forming site of RgpB protein, was -5.14 kcal/mol, and the binding energy of 6 sites of Kgp K1 protein and the hydrogen bond forming site GLY1114 of -5.07 kcal/mol.@*CONCLUSION@#Computer simulation of target prediction and molecular docking technology can initially reveal the binding, degree of binding and binding sites of methylene blue and Pg proteins. This method provides a reference for future research on the screening of binding sites of photosensitizers to cells and bacteria.

Study on Mechanism of Quercetin in Heart Failure Based on Network Pharmacology and Experimental Validation / 中国实验方剂学杂志

Objective:To predict the therapeutic targets and related signaling pathways of quercetin in the treatment of heart failure （HF） by network pharmacology and molecular docking methods，and further clarify its mechanisms through <italic>in vitro</italic> cell model. Method:The pharmacological targets of quercetin were obtained by SwissTargetPrediction and Targetnet databases； the heart failure related targets were obtained by Online Mendelian Inheritance in Man（OMIM），GeneCards and Therapeutic Target Database（TTD） databases； the protein-protein interaction（PPI） network was analyzed by STRING database（Search Tool for Recurring Instances of Neighbouring Genes），and the PPI network diagram of quercetin for heart failure target was established. Cytoscape 3.7.2 software was used for analyzing and screening the anti-heart failure network nodes of quercetin，and the obtained targets were enriched with gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analysis by DAVID database. In order to explore the mechanism of quercetin in the treatment of heart failure，we used cell model to verify the function in heart failure treatment. Results:The predicted results showed that there were 23 targets for the treatment of heart failure，such as Matrix Metallopeptidase-9（MMP-9），androgen receptor（AR），coagulation factor 2（F2），insulin like growth factor 1 receptor（IGF1R），epidermal growth factor receptor（EGFR），janus kinase-2（JAK2），cytochrome P450 family 19 subfamily A member 1（CYP19A1），estrogen receptor-1（ESR1），tumor necrosis factor（TNF），protein tyrosine phosphatase receptor type C（PTPRC） and cytochrome P450 family 17 subfamily A member 1（CYP17A1） etc. The results suggest that quercetin may play a role in the treatment of heart failure by intervening in the physiological processes of cardiovascular cell proliferation and metabolism，regulating hypoxia-inducible factor 1 （HIF-1）signaling pathway and steroid hormone biosynthesis. Conclusion:Quercetin has the characteristics of multi-target，multi-channel and multi-channel in the treatment of heart failure. It may play a role in the treatment of heart failure by regulating MMP-9，EGFR and other key genes，participating in the biological process of cardiac and vascular cell proliferation and metabolism.

Bufotenine and its derivatives: synthesis, analgesic effects identification and computational target prediction / 中国天然药物

Natural product bufotenine (5) which could be isolated from Venenum Bufonis, has been widely used as a tool in central nervous system (CNS) studies. We present here its quaternary ammonium salt (6) which was synthesized with high yields using 5-benzyloxyindole as raw materials, and we firstly discover its analgesic effects in vivo. The analgesic evaluation showed that compounds 5 and 6 had stronger effects on the behavior of formalin induced pain in mice. Moreover, the combination of compound 6 and morphine has a synergistic effect. We intended to explain the molecular mechanism of this effect. Therefore, 36 analgesic-related targets (including 15 G protein-coupled receptors, 6 enzymes, 13 ion channels, and 2 others) were systemically evaluated using reverse docking. The results indicate that bufotenine and its derivatives are closely related to acetyl cholinesterase (AChE) or α

Computational Prediction of miR130a Target Genes in Cancer

@#Introduction: Cancer is one of the main causes of mortality globally and the incidence has been rising over the years. Studies have shown that miRNAs have the potential as cancer biomarkers. The miR-130a has been reported to be upregulated in several types of cancer, which indicate the important roles of miR-130a in cancer development and metastasis. The aim of this study is to identify potential target genes and to predict the regulatory function of miR130a-3p and 5p in cancer. Methods: Three bioinformatics platforms namely miRWalk, the Database for annotations, visualization and integrated discovery (DAVID) Gene Functional Classification Tool and miRanda-miRSVR analysis tools were used to identify possible interaction between miR-130a and its target. Protein-protein interaction (PPI) network for the predicted target genes was then constructed. Results: The analyses have identified nine predicted target genes for miR-130a-3p (RAPGEF4, SOS2, NRP1, RPS6KB1, MET, IL15, ACVR1, RYR2 and ITPR1), and ten for miR-130a-5p (BCL11A, SPOPL, NLK, PPARGC1A, POU4F2, CPEB4, ST18, RSBN1L, ELF5 and ARID4B), that might play an important role in the development of cancer. Findings from this report suggest that miR-130a may involves in controlling cancer related genes; MET, ACVR1 and BCL11A. miR-130a-3p may regulates MET which involves in apoptosis and metastasis, and ACVR1 which involves in metastasis and angiogenesis. miR-130a-5p may regulates BCL11A which involves in apoptosis, proliferation and tumorigenesis. Conclusion: This study has highlighted the molecular interaction of miR-130a with associated genes and pathways, suggesting therapeutic potential of miR130a as personalised targeted therapy for cancer.

D3Targets-2019-nCoV: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against COVID-19

A highly effective medicine is urgently required to cure coronavirus disease 2019 (COVID-19). For the purpose, we developed a molecular docking based webserver, namely D3Targets-2019-nCoV, with two functions, one is for predicting drug targets for drugs or active compounds observed from clinic or / studies, the other is for identifying lead compounds against potential drug targets docking. This server has its unique features, (1) the potential target proteins and their different conformations involving in the whole process from virus infection to replication and release were included as many as possible; (2) all the potential ligand-binding sites with volume larger than 200 Å on a protein structure were identified for docking; (3) correlation information among some conformations or binding sites was annotated; (4) it is easy to be updated, and is accessible freely to public (https://www.d3pharma.com/D3Targets-2019-nCoV/index.php). Currently, the webserver contains 42 proteins [20 severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) encoded proteins and 22 human proteins involved in virus infection, replication and release] with 69 different conformations/structures and 557 potential ligand-binding pockets in total. With 6 examples, we demonstrated that the webserver should be useful to medicinal chemists, pharmacologists and clinicians for efficiently discovering or developing effective drugs against the SARS-CoV-2 to cure COVID-19.

Prediction and Analysis of the Components and Therapeutic Targets of Agarwood Essential Oil / 中国药学杂志

OBJECTIVE: To predict and analyze the chemical constituents-therapeutic targets of agarwood essential oil by network pharmacology. METHODS: First, the components of agarwood essential oil were determined and analyze by GC-MS and the compound database was built. Then, ADME and target prediction based on the structural data was performed by virtual computation. Finally, the predicted targets were classified and compared with the known therapeutic targets for sleep disorders, anxiety and depression-related diseases, so as to predict the therapeutic targets for diseases and construct the compound-therapeutic target-disease network. RESULTS: Agarwood essential oil can regulate the neural activity through ligand-receptor interaction pathway, cAMP signaling pathway, 5-hydroxytryptamine neural pathway, cholinergic neural pathway, dopaminergic neural pathway and other multiple pathways. Meanwhile, 11 compounds were screened out to have potential effects on 30 therapeutic targets related to insomnia, anxiety and depression. CONCLUSION: Agarwood essential oil has potential preventive and therapeutic effects on sleep disorders, anxiety, depression and other neurological diseases, which provides theoretical basis and data support for in-depth research and development of agarwood essential oil's sedative-hypnotic effects and its mechanism.

Exploiture and application of an internet-based Computation Platform for Integrative Pharmacology of Traditional Chinese Medicine / 中国中药杂志

Recently, integrative pharmacology(IP) has become a pivotal paradigm for the modernization of traditional Chinese medicines(TCM) and combinatorial drugs discovery, which is an interdisciplinary science for establishing the in vitro and in vivo correlation between absorption, distribution, metabolism, and excretion/pharmacokinetic(ADME/PK) profiles of TCM and the molecular networks of disease by the integration of the knowledge of multi-disciplinary and multi-stages. In the present study, an internet-based Computation Platform for IP of TCM(TCM-IP, www.tcmip.cn) is established to promote the development of the emerging discipline. Among them, a big data of TCM is an important resource for TCM-IP including Chinese Medicine Formula Database, Chinese Medical Herbs Database, Chemical Database of Chinese Medicine, Target Database for Disease and Symptoms, et al. Meanwhile, some data mining and bioinformatics approaches are critical technology for TCM-IP including the identification of the TCM constituents, ADME prediction, target prediction for the TCM constituents, network construction and analysis, et al. Furthermore, network beautification and individuation design are employed to meet the consumer's requirement. We firmly believe that TCM-IP is a very useful tool for the identification of active constituents of TCM and their involving potential molecular mechanism for therapeutics, which would wildly applied in quality evaluation, clinical repositioning, scientific discovery based on original thinking, prescription compatibility and new drug of TCM, et al.

Application of computational methods for anticancer drug discovery, design, and optimization / Aplicación de métodos computacionales para el descubrimiento, diseño y optimización de fármacos contra el cáncer

Abstract: Developing a novel drug is a complex, risky, expensive and time-consuming venture. It is estimated that the conventional drug discovery process ending with a new medicine ready for the market can take up to 15 years and more than a billion USD. Fortunately, this scenario has recently changed with the arrival of new approaches. Many novel technologies and methodologies have been developed to increase the efficiency of the drug discovery process, and computational methodologies have become a crucial component of many drug discovery programs. From hit identification to lead optimization, techniques such as ligand- or structure-based virtual screening are widely used in many discovery efforts. It is the case for designing potential anticancer drugs and drug candidates, where these computational approaches have had a major impact over the years and have provided fruitful insights into the field of cancer. In this paper, we review the concept of rational design presenting some of the most representative examples of molecules identified by means of it. Key principles are illustrated through case studies including specifically successful achievements in the field of anticancer drug design to demonstrate that research advances, with the aid of in silico drug design, have the potential to create novel anticancer drugs.

Resumen: El desarrollo de un nuevo fármaco es un proceso complejo y arriesgado que requiere una enorme cantidad de tiempo y dinero. Se estima que el proceso estándar para producir un nuevo fármaco, desde su descubrimiento hasta que acaba en el mercado, puede tardar hasta 15 años y tener un costo de mil millones de dólares (USD). Por fortuna, este escenario ha cambiado recientemente con la llegada de nuevas tecnologías y metodologías. Entre ellas, los métodos computacionales se han convertido en un componente determinante en muchos programas de descubrimiento de fármacos. En un esfuerzo por incrementar las posibilidades de encontrar nuevas moléculas con potencial farmacológico, se utilizan técnicas como el cribado virtual de quimiotecas construidas con base en ligandos o estructuras para la identificación de hits y hasta para la optimización de compuestos líder. En lo que respecta al diseño y descubrimiento de nuevos candidatos a fármacos contra el cáncer, estos enfoques tienen, a la fecha, un impacto importante y aportan nuevas posibilidades terapéuticas. En este artículo se revisa el concepto del diseño racional de moléculas con potencial farmacológico, ilustrando los principios clave con algunos de los ejemplos más representativos y exitosos de moléculas identificadas mediante estas aproximaciones. Se incluyen casos desarrollados en el campo del diseño de fármacos contra el cáncer con la finalidad de mostrar cómo, con la ayuda del diseño asistido por computadora, se pueden generar nuevos fármacos que den esperanza a millones de pacientes.

Baicalein prolongs the lifespan of Drosophila melanogaster through antioxidation activity / 药学学报

In order to explore the anti-aging effect of baicalein, female Drosophila melanogaster as a model organism was used to study the effects of baicalein on natural aging model and aging models induced by hydrogen peroxide (H2O2) and paraquat. The bioinformatics approach was used to predict the possible target for the anti-aging activity of baicalein, and the target pathways were identified. The oxidative stress pathway was a focus in experiment. Baicalein at concentrations of 0.04 mg·mL-1 and 0.2 mg·mL-1 extended the mean and maximum lifespans in the natural aging model, and effectively reduced the damages of oxidative stress by H2O2 and paraquat. 31 senescence-related targets together with the oxidative stress pathway were modulated by baicalein. The experiments revealed that baicalein might delay aging process through attenuation of the oxidative stress response by decreasing the reactive oxygen species (ROS), malondialdehyde (MDA) and oxidized glutathione (GSSG) in Drosophila melanogaster.

IsomiRs have functional importance

Since the inception of deep sequencing, isomiRs are consistently observed to be produced by most miRNA genes in a variety of cell types. IsomiRs appear as a variation in length from the canonical sequence annotated in miRBase, due to an addition or deletion of one or more nucleotides at the 5’ or 3’ ends or both. As the seed sequence is located at the 5’ end of the microRNA, the target mRNA will be theoretically different. Therefore, 5’isomiRs might potentially target a new set mRNA compared to their canonical counterpart. This article gives an overview of investigations that explored the functional potential of isomiRs such as their ability to incorporate into Argonaute protein, the differential expression of isomiRs in various tissue types and cell lines, and the differences of mRNA targets between isomiR and its canonical microRNA. In addition, this article provides a brief introduction of RNA sponges as a potential way to inhibit isomiRs.

Computing Methods for Herb Target Prediction:Technique Discussion and Experimental Analysis / 世界科学技术-中医药现代化

Due to the importance of molecular mechanisms of drug actions, network pharmacology has become a new perspective on drug mechanism research and novel drug discovery. Drug target prediction using computational methods, is one of the key research topics in network pharmacology. This paper reviewed the related research on drug target prediction methods. Furthermore, general principles of drug target prediction methods and key steps of them in recent years were summarized. Given the diversity of Chinese medicine ingredients, the network controlla-bility of herbs and the lack of high-quality pharmacological data, the network regulation mechanism of Chinese herb research will meet even more difficulties than modern drug research. Therefore, this paper also discussed main is-sues and research trends of Chinese herb target prediction. Finally, combining with the actual consolidated network data of Chinese herbs, chemical structure similarity computation and link prediction methods, the network-based herb target prediction method was proposed to demonstrate key research steps. Furthermore, we discussed the most significant research topics that we should addressed to enhance the high quality results of herb target prediction.

Linking Ayurveda and Western medicine by integrative analysis.

In this article, we discuss our recent work in elucidating the mode-of-action of compounds used in traditional medicine including Ayurvedic medicine. Using computational (‘in silico’) approach, we predict potential targets for Ayurvedic anticancer compounds, obtained from the Indian Plant Anticancer Database given its chemical structure. In our analysis, we observed that: (i) the targets predicted can be connected to cancer pathogenesis i.e. steroid-5-alpha reductase 1 and 2 and estrogen receptor-β, and (ii) predominantly hormone-dependent cancer targets were predicted for the anti-cancer compounds. Through the use of our in silico target prediction, we conclude that understanding how traditional medicine such as Ayurveda work through linking with the ‘western’ understanding of chemistry and protein targets can be a fruitful avenue in addition to bridging the gap between the two different schools of thinking. Given that compounds used in Ayurveda have been tested and used for thousands of years (although not in the same approach as Western medicine), they can potentially be developed into potential new drugs. Hence, to further advance the case of Ayurvedic medicine, we put forward some suggestions namely: (a) employing and integrating novel analytical methods given the advancements of ‘omics’ and (b) sharing experimental data and clinical results on studies done on Ayurvedic compounds in an easy and accessible way.