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P pt rise insilico 2
1. In Silico discovery of Histone-
lysine N-methyltransferase SETD2
inhibitors.
Juan Carlos Torres Sánchez1
Gretel Saraí Montañez Próspere1
1
Adriana O. Díaz
2
Dr. Hector M. Maldonado
1RISE Program, University of Puerto Rico at Cayey;
2Universidad Central del Caribe, Medical School.
2. In Silico discovery of Histone-lysine N-methyltransferase SETD2 inhibitors.
Outline of the Presentation
• Background and Significance
A. Methyltransferases
B. Histone-lysine N Methyltransferase
• Hypothesis
• Methodology
• Results
• Conclusions
• Future Work
• Acknowledgments/Questions
3. Background and Significance
Methyltranferases:
• A methyltransferase, also known as a methylase, is a type of
tranferase enzyme that transfers a methyl group from a donor
molecule (usually S-adenosyl methionine; SAM) to an acceptor.
• Methylation often occurs on nucleic bases in DNA or amino acids
in protein structures.
• Several methyltransferases have ben identified including DNA
(cytosine-5)-methyltransferase 1 (DNMT1), tRNA
methyltransferase (TRDMT1) and protein methyltransferase
(SETD2)
4. Background and Significance
Histone Methyltranferases (HMT):
• HMT are histone-modifying enzymes, including histone-lysine N-
methyltransferase and histone-arginine N-methyltransferase.
• These group of enzymes catalyze the transfer of up to three methyl
groups to lysine.
• Histones are highly alkaline proteins found in eukaryotic cell nuclei
that package and order the DNA into structural units called
nucleosomes.
• Methylation of histones is important biologically because it is the
principal epigenetic modification of chromatin that determines gene
expression, genomic stability, etc.
5. Background and Significance
Histone Methyltranferases (HMT):
• Abnormal expression or activity of methylation-regulating enzymes
has been noted in some types of human cancers
• It is now generally accepted that in addition to genetic aberrations,
cancer can be initiated by epigenetic changes in which gene
expression is altered without genomic abnormalities.
• The protein methyltransferases (PMTs) have emerged as a novel
target class, especially for oncology indications where specific genetic
alterations, affecting PMT activity, drive cancer tumorigenesis.
7. Objectives:
1. Identify a new target for drug development in the
Histone-lysine N-methyltransferase SETD2 by analysis
of benzene mapping and the interactions of previously
identified compounds.
1. Using information from these interactions, create
Pharmacophore Models (LigandScout) for the selected
target and perform a virtual pre-screening of Drug
Databases against our model.
1. Perform a secondary screening to identify “top-hits” or
potential lead compounds (AutoDock Vina)
8. Methodology
Software Used:
• PyMOL Molecular Graphics System v1.3 http://www.pymol.org
• AutoDock (protein-protein docking software) http://autodock.scripps.edu/
• Auto Dock Tools: Graphical Interfase for AutoDock
http://mgltools.scripps.edu/downloads
• AutoDock Vina: improving the speed and accuracy of docking with a new scoring
function, efficient optimization and multithreading. http://vina.scripps.edu/
• LigandScout: Advanced Pharmacophore Modeling and Screening of Drug
Databases. http://www.inteligand.com/ligandscout/
Databases Used:
• SwissProt/TrEMBL; (Protein knowledgebase and Computer-annotated supplement
to Swiss-Prot) http://www.expasy.ch/sprot/
• Research Collaboratory for Structural Bioinformatics (RCSB) www.pdb.org
• ZINC: A free database for virtual screening: http://zinc.docking.org/
11. Results: Docking and ranking of top-hits.
• A database of >150,000 lead-like compounds Affinity
where used for screening against our two Compound
(kcal/m Model
Pharmacophore models. Name
ol)
1 MTHLY_01 -9.7 M01_0.3
2 MTHLY_02 -9.5 M02_0.0
• A total of 18,082 compounds fulfill all requirements 3 MTHLY_03 -9.4 M01_0.2
4 MTHLY_04 -9.4 M02_0.3
of Model 1 while 13,587 compounds where 5 MTHLY_05 -9.4 M01_0.3
obtained with Model 2. 6 MTHLY_06 -9.3 M01_0.4
7 MTHLY_07 -9.3 M01_0.3
8 MTHLY_08 -9.3 M02_0.2
• 21 % of these compounds where selected by both 9 MTHLY_09 -9.3 M02_0.0
10 MTHLY_10 -9.3 M02_0.4
models. 11 MTHLY_11 -9.3 M01_0.3
12 MTHLY_12 -9.3 M02_0.4
Affinity # of Drugs
13 MTHLY_13 -9.3 M02_0.2
-9.7 1 14 MTHLY_14 -9.3 M02_0.3
15 MTHLY_15 -9.3 M02_0.4
-9.5 1 16 MTHLY_16 -9.3 M01_0.3
17 MTHLY_17 -9.3 M02_0.0
-9.4 3 18 MTHLY_18 -9.3 M02_0.3
19 MTHLY_19 -9.2 M02_0.4
-9.3 13 20 MTHLY_20 -9.2 M01_0.5
21 MTHLY_21 -9.2 M01_0.2
-9.2 16 22 MTHLY_22 -9.2 M02_0.2
23 MTHLY_23 -9.2 M02_0.2
-9.1 10
24 MTHLY_24 -9.2 M02_0.2
-9 15 25 MTHLY_25 -9.2 M02_0.0
TOTAL 59
12. Conclusions
• Initial analysis of the Histone-lysine N-methyltransferase SETD2 suggests
that the binding site for the methyl donor compound SAM can be used as
potential targets for In Silico drug discovery and development.
• Two distinct pharmacophore models where generated and used to filter
the original database of small chemical compounds to less than 20% of
the total number of compounds.
• A total of 31,669 compounds where docked In Silico to the target protein
and the results ranked according to their predicted binding energies.
• A group of drugs-like-compounds with high binding energies (less than -
9.0 kcal/mol) were identified in the secondary screening consistent with
the possibility of high affinity interactions.
13. Future Work
• Complete the screening of the lead-like database (>1.7 million
compounds) using both Pharmacophore models.
• Evaluate results of top-hits and if appropriate use this
information to refine the Pharmacophore model and repeat the
screening cycle.
• Obtain/purchase some of the predicted high affinity
compounds and test their potential as inhibitors in a bioassay.
14. References
• Duns G, Berg E, Duivenbode I, Osinga J, Hollema H, Hofstra R, and Kok K. 2010.
Histone Methyltransferase Gene SETD2 Is a Novel Tumor Suppressor Gene in
Clear Cell Renal Cell Carcinoma. Cancer Res. 70:4287-4291
• Spannhoff A, Hauser A, Heinke R, Sippl W, and Jung M. 2009. The Emerging
Therapeutic Potential of Histone Methyltransferase and Demethylase Inhibitors.
ChemMedChem. 4:1568 – 1582
• Campagna V, Wai M, Nguyen K, Feher M, Najmanovich R, and Schapira M. 2011.
Structural Chemistry of the Histone Methyltransferases Cofactor Binding Site.
Chem. Inf. Model. 51:612–623
Bullete 1: suggesting associations between histone methylation and malignant transformation of cells or formation of tumors
A lead compound is a chemical compound that has pharmacological or biological activity.
You start with a biological problemFollowed by downloading the 3D stuctureThen you identify the hot stops.You find the optimal target for drug developmentGeneration of pharmacophore model Then primary screening with database of 1.7 million drugs Identification of top hitsAfter that a secondary screeningIdentify ranking Binding energyMaybe further refinementThen Bio Assay
Here you can see the Protein with SAMSAM donor of methyl groupIf you find a drug that blocks where the SAM is, then you can inhibit the mehtylation process
