Rapporteur, ensc, Montpellier








télécharger 0.86 Mb.
titreRapporteur, ensc, Montpellier
page19/22
date de publication22.04.2017
taille0.86 Mb.
typeRapport
c.21-bal.com > comptabilité > Rapport
1   ...   14   15   16   17   18   19   20   21   22

The tool bar: navigate in your database and select compounds



The database viewer displays 1000 molecules by page. You can change the pages using the five blue icons. The   icon allows to directly go to a page entering is number.

You can select desired compounds using the  icon.




You can select the providers. By default all providers are selected. In the query part of the screen you can define filters for the selection. You must choose the parameter, the equality sign, the value and then click Add to define a new parameter. There is no limit in the number of filters you can define.

Parameters:

  • id: internal ID of the compound

  • md5ichi: hascode of the unique identifier

  • mw: molecular weight of the compounds, without counter-ion(s) and at pH=7

  • logP

  • TPSA: Topological Polar Surface Area

  • Hba: number of H bond acceptors

  • Hbd: number of H bond donors

  • rotatable bonds

  • halogens

  • single_chains: single chains longer than ≤ -(CH2)6CH3 (0 for no, 1 for yes)

  • perfluorinated_chain: presence of -CF2CF2CF3 (0 for no, 1 for yes)

  • SSSRs: number of Smallest Sets of Smallest Rings

  • big_ring_size: size of the bigger ring found by SSSRs

  • O: number of O atoms

  • N: number of N atoms

  • S: number of S atoms

  • NO2: number of NO2

  • SO2: number of SO2

  • CF3: number of CF3

  • CF3_halogens: number of CF3 and other halogen atoms

  • NOS: number of N, O and S atoms

  • bad_atoms: number of atoms other than C, O, N, S, P, F, Cl, Br, I, Na, K, Mg, Ca, or Li

  • is_reactive: presence of a reactive function (0 for no, 1 for yes)

  • is_warhead: presence of a warhead type substructure (0 for no, 1 for yes)

  • is_promiscuous: the molecule is known to be a promiscuous inhibitor (0 for no, 1 for yes)

  • is_privileged: if > -1, then a privileged structure is detected in the structure of the molecule

  • absorption: not used yet

  • caco2: not used yet

  • solubility: not used yet

  • BBB: not used yet

  • drug-like_failures: number of non-fitted drug-like criteria

  • lead-like_failures: number of non-fitted lead-like criteria

  • PDL_score: our internal Progressive 'Drug-Like' score. ≤ 1 means the compounds is estimated drug-like, more than 2 means the compounds is absolutely not drug-like

  • PLL_score: our internal Progressive 'Lead-Like' score. ≤ 1 means the compounds is estimated lead-like, more than 2 means the compounds is absolutely not lead-like

  • CFMS: Cleaning For My Screening. By default it is based on PDL and add penalties for the presence of reactive functions, warheads, primiscuous aggregating inhibitors, single chains, perfluorinated chains, and for the abscence of N or O

  • scaffold: scaffold id (scaffold used is rings + linkers)

  • framework: id of the general 2D shape of the molecule

  • ClogP: not used yet.

  • entrie_date

Example of a drug-like selection:




Example of a selection for screening:


A screening selection can be done in the same way that a drug-like selection, but using the criteria bad_atoms=0 and CFMS=0. By default, CFMS is the same thing that PDL, but it takes into account additional features such as reactive functions.


CFMS can be personalized using the   icon. Then, you can choose the base of CFMS ('drug-like' or 'lead-like' i.e. PDL or PLL) the additional penalties can be chosen. Clicking Ok after user's choices will recompute the new CFMS value for all the compounds of the current database.

The reactive functions and warheads penalties can also be personalized through Configure in the main menu of ScreeningAssistant :




The False Positive Filters window is now open:



This window will allow you to modify definitions of reactive functions and warheads. You can create and delete sub-structures filters using New and Delete buttons. The name of a property can be changed double clicking on it. The Structure field let you to edit the SMARTS code of the filter. If you have MarvinBeans.jar in your classpath, the sub-structure can be edited graphically.

The modification of the filters will apply when new compounds are added.

2D chemical space covered by the selected compounds can be viewed using the  icon. Here is an example of chemical space:




This chemical space use the PCA1 and PCA2 axis equation computed on 18 000 diverse molecule selected from 2.6 millions with the descriptors used are SSKey3DS, MW and logP.

i Nous utiliserons dans le suite de ce document le terme « liaisons pouvant tourner » comme traduction du terme anglo-saxon « rotatable bonds ». Les terminologies françaises et anglaises sont réductrices de la notion. Une définition détaillée de ce type de liaison est donné chapitre 2 partie II. B. 8. a.

i Un code de hachage est le résultat de la conversion par une fonction de hachage d’un grand ensemble en un ensemble plus petit. La fonction MD5 permet ainsi de convertir un ensemble de données de n’importe quelle taille en une chaîne de 32 caractères hexadécimaux (128 bits).

ii Nous avons gardé le terme anglosaxon fingerprint, car la traduction française « empreinte digitale » n’est généralement pas employé en chemoinformatique. Nous utiliserons ce mot au masculin.

i La notation de « O », appelée notation de Landeau, est utilisée pour indiquer à quelle vitesse une fonction augmente ou diminue. Cette notation est très utilisée pour définir la complexité d’un algorithme. Des explications détaillées sont disponibles à l’adresse suivante : http://fr.wikipedia.org/wiki/Notations_de_Landau

1. Schmid, E.F.; Smith, D.A. Keynote review: Is declining innovation in the pharmaceutical industry a myth? Drug Discov. Today 2005, 10, 1031-1039.

2. PhRMA Annual Survey, 2005, http://www.phrma.org/publications/publications/17.03.2005.1142.cfm

3. Jorgensen, W. L. The many roles of computation in drug discovery. Science 2004, 303, 1813-1818.

4. Irwin, J.J.; Shoichet, B.K. ZINC - A Free Database of Commercially Available Compounds for Virtual Screening. J. Chem. Inf. Model. 2005, 45, 177-182.

5. Hann, M. M.; Oprea, T. I. Pursuing the leadlikeness concept in pharmaceutical research. Curr Opin Chem Biol 2004, 8, 255-263.

6. Bohacek, R.S.; McMartin, C.; Guida, W.C. The Art and Practiceof Structure-based Drug Design: a Molecular Modelling Perspective. Med. Res. Rev. 1996, 16, 3-50;

7. Ertl, P. Cheminformatics Analysis of Organic Substituents: Identification of the Most Common. J. Chem. Inf. Comput. Sci. 2003, 43, 374-380.

8. Schuffenhauer, A.; Popov, M.; Schopfer, U.; Acklin, P.; Stanek, J. Jacoby, E. Molecular Diversity Management Strategies for Building and Enhancement of Diverse and Focused Lead Discovery Compound Screening Collections. Comb Chem High Throughput Screen 2004, 7, 771-781.

9. Chemical Abstracts Services. http://www.cas.org/cgi-bin/regreport.pl

10. ChemNavigator, 6126 Nancy Ridge Drive, Suite 117, San Diego, CA 92121, USA, www.chemnavigator.com

11. Chen, J.; Swamidass, S.J.; Dou, Y.; Bruand, J.; Baldi, P. ChemDB: a public database of small molecules and related chemoinformatics resources. Bioinformatics 2005, 21, 4133-4139.

12. ChemBank, http://chembank.broad.harvard.edu/

13. PubMed, http://pubchem.ncbi.nlm.nih.gov/

14. Database System Comparisons, http://cdb.ics.uci.edu/CHEM/Web/cgibin/supplement/Comparison.py

15. Beavers, M. P.; Chen, X. Structure-based combinatorial library design: methodologies and applications. J Mol Graph Model. 2002, 20, 463-468.

16. Sybyl, Tripos, http://www.tripos.com

17. Cerius2, Accelrys, http://www.accelrys.com/products/cerius2/

18. MOE, Chemical Computing Group, www.chemcomp.com

19. Wolber, G.; Langer, T. CombiGen : A novel software package for the rapid generation of virtual combinatorial libraries. In H.-D. Höltje and W. Sippl, Rational approaches to drug design, 2000, 390-399.

20. Krier, M.; Araujo-Junior, J.X., Schmitt, M.; Duranton, J.; Justiano-Basaran, H.; Lugnier, C.; Bourguignon, J.J.; Rognan, D. Design of small-sized libraries by combinatorial assembly of linkers and functional groups to a given scaffold: application to the structure-based optimization of a phosphodiesterase 4 inhibitor. J.Med.Chem 2005, 48, 3816-3822.

21. Reddy, T. R. K.; Mutter, R.; Heal, W.; Guo, K.; Gillet, V. J.; Pratt, S.; Chen, B. Library Design, Synthesis, and Screening: Pyridine Dicarbonitriles as Potential Prion Disease Therapeutics. J. Med. Chem. 2006, 49, 607-615.

22. Chen, G.; Zheng, S.; Luo, X.; Shen, J.; Zhu, W.; Liu, H.; Gui, C.; Zhang, J.; Zheng, M.; Puah, C. M.; Chen, K.; Jiang, H. Focused Combinatorial Library Design Based on Structural Diversity, Druglikeness and Binding Affinity Score. J. Comb. Chem. 2005, 7, 398-406.

23. Flower, D.R. DISSIM: a program for the analysis of chemical diversity. Chem. Rev. 1998, 16, 239-253.

24 Murray, C. W.; Clark, D. E.; Auton, T. R.; Firth, M.A.; Li, J.; Sykes, R.A.; Waszkowycz, B.; Westhead, D.R.; Young, S.C. PRO_SELECT: combining structure-based drug design and combinatorial chemistry for rapid lead discovery. 1. Technology. J. Comput. Aided Mol. Des. 1997, 11, 193-207.

25. Sun, Y.; Ewing, T. J. A.; Skillman, A. G.; Kuntz, I. D. CombiDOCK: Structure-based combinatorial docking and library design. J. Comput. Aided Mol. Des. 1998, 12, 597-604.

26. Sprous, D. G.; Lowis, D. R.; Leonard, J. M.; Heritage, T.; Burkett, S. N. Baker, D. S.; Clark, R. D. OptiDock: virtual HTS of combinatorial libraries by efficient sampling of binding modes in product space. J. Comb. Chem. 2004, 6, 530-539.

27. Makino, S.; Ewing, T. J. A.; Kuntz, I. D. DREAM++: Flexible docking program for virtual combinatorial libraries. J. Comput. Aided Mol. Des. 1999, 13, 513-532.

28. Nishibata, Y.; Itai, A. Automatic creation of drug candidate structures based on receptor structure. Starting point for artificial lead generation. Tetrahedron 1991, 47, 8885-8990.

29. Bohm, H. J. The computer program LUDI: A new method for the de novo design of enzyme inhibitors. J. Comput.-Aided Mol. Des. 1992, 6, 61-78.

30. Gillet, V.; Johnson, A. P.; Mata, P.; Sike, S.; Williams, P. SPROUT: A program for structure generation. J. Comput.-Aided Mol. Des. 1993, 7, 127-153.

31. Eisen, M. B.; Wiley, D. C.; Karplus, M.; Hubbard, R. E. HOOK: A program for finding novel molecular architectures that satisfy the chemical and steric requirements of a macromolecule binding site. Proteins 1994, 19, 199-221.

32. Schneider, G.; Lee, M. L.; Stahl, M.; Schneider, P. De novo design of molecular architectures by evolutionary assembly of drug derived building blocks. J. Comput.-Aided Mol. Des. 2000, 14, 487-494.

33. LeapFrog, 6.8 ed.; Tripos, Inc.: St Louis, MO.

34. Pegg, S. C.; Haresco, J. J.; Kuntz, I. D. A genetic algorithm for structure-based de novo design. J. Comput.-Aided Mol. De. 2001, 15, 911-933.

35. Wang, R.; Gao, Y.; Lai, L. LigBuilder: A Multi-Purpose Program for Structure-Based Drug Design. J. Mol. Model. 2000, 6, 498-516.

36. Clark, D. E.; Frenkel, D.; Levy, S. A.; Li, J.; Murray, C. W.; et al. PRO-LIGAND: An approach to de novo molecular design. 1.Application to the design of organic molecules. J. Comput.-Aided Mol. Des. 1995, 9, 13-32.

37. Pearlman, D.A.; Murcko, M.A. CONCERTS: dynamic connection of fragments as an approach to de novo ligand design. J. Med. Chem. 1996, 39, 1651-63.

38. Bohacek, R.S.; McMartin, C. Multiple Highly Diverse Structures Complementary to Enzyme Binding Sites: Results of Extensive Application of a de Novo Design Method Incorporating Combinatorial Growth. J. Am. Chem. Soc. 1994, 116, 5560-5571.

39. Douguet, D.; Munier-Lehmann, H.; Labesse, G.; Pochet, S. LEA3D: a computer-aided ligand design for structure-based drug design. J.Med.Chem 2005, 48, 2457-2468.

40. CMC, MDL Information Systems, http://www.mdl.com/products/knowledge/medicinal_chem/

41. KEGG, http://www.genome.ad.jp/dbget/ligand.html

42. Maniyar, D. M.; Nabney, I. T.; Williams, B. S.; Sewing, A. Data Visualization during the Early Stages of Drug Discovery. J. Chem. Inf. Model.
1   ...   14   15   16   17   18   19   20   21   22

similaire:

Rapporteur, ensc, Montpellier iconDe la franc maconnerie a montpellier
Écrit à son ami Pierre Jacques Astruc, conseiller maître en la cour des comptes, aides et finances de Montpellier

Rapporteur, ensc, Montpellier iconEconomies d’eau : Réutilisation des eaux de pluie
«Eaux» de l’Afssa 15 cnrs- umr 5119-Université Montpellier 2- montpellier 16 ehesp- rennes 17 Laboratoire de Santé publique et Environnement-Faculté...

Rapporteur, ensc, Montpellier iconÉconomies d’eau : Réutilisation des eaux de pluie
«Eaux» de l’Afssa 15 cnrs- umr 5119-Université Montpellier 2- montpellier 16 ehesp- rennes 17 Laboratoire de Santé publique et Environnement-Faculté...

Rapporteur, ensc, Montpellier iconRapporteur

Rapporteur, ensc, Montpellier iconRapporteur : Saddek Aouadi, Professeur, Université d’Annaba

Rapporteur, ensc, Montpellier iconRapporteur trigonométrique circulaire pour série générale et technologique...

Rapporteur, ensc, Montpellier iconCmi montpellier informatique

Rapporteur, ensc, Montpellier iconSociete regionale de medecine et d’hygiene du travail de montpellier

Rapporteur, ensc, Montpellier iconRapporteur : Philippe Cléris Le Grand Paris et l’Eure. Ou un début...

Rapporteur, ensc, Montpellier iconL ycee agricole prive
«blanco», équerre, compas, rapporteur, taille-crayon, crayon à papier, double décimètre, stylos noir, bleu, vert, rouge et crayons...








Tous droits réservés. Copyright © 2016
contacts
c.21-bal.com