In Silico discovery of Histone-lysine N-methyltransferase SETD2

inhibitors.

Juan Carlos Torres Sánchez1

Gretel Saraí Montañez Próspere1

Adriana O. Díaz 1

Dr. Hector M. Maldonado 2

1RISE Program, University of Puerto Rico at Cayey; 2Universidad Central del Caribe, Medical School.

Outline of the Presentation

• Background and SignificanceA. Methyltransferases

B. Histone-lysine N Methyltransferase

• Hypothesis

• Methodology

• Results

• Conclusions

• Future Work

• Acknowledgments/Questions

In Silico discovery of Histone-lysine N-methyltransferase SETD2 inhibitors.

Background and SignificanceMethyltranferases:

• 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)

Background and SignificanceHistone 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 and/or arginine residues of histone proteins.

• 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.

• Abnormal expression or activity of methylation-regulating enzymes has been noted in some types of human cancers, suggesting associations between histone methylation and malignant transformation of cells or formation of tumors

• 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.

Background and SignificanceHistone Methyltranferases (HMT):

Hypothesis

“Selective, high-affinity inhibitors of Histone-lysine N-methyltransferase SETD2 can be identified via an In Silico approach targeting this protein SAM binding site”.

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.

2. 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.

3. Perform a secondary screening to identify “top-hits” or potential lead compounds (AutoDock Vina)

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/

Pharmacophore Model 01 Pharmacophore Model 02

ZINC00000000

Results: Pharmacophore model generation.3H6L.pdb3H6L.pdb3H6L.pdb

ZINC00000000 ZINC00000000

Affinity # of Drugs

-9.7 1

-9.5 1

-9.4 3

-9.3 13

-9.2 16

-9.1 10

-9 15

TOTAL 59

Compound Name affinity Model

1 MTHLY_01 -9.7 M01_0.32 MTHLY_02 -9.5 M02_0.03 MTHLY_03 -9.4 M01_0.24 MTHLY_04 -9.4 M02_0.35 MTHLY_05 -9.4 M01_0.36 MTHLY_06 -9.3 M01_0.47 MTHLY_07 -9.3 M01_0.38 MTHLY_08 -9.3 M02_0.29 MTHLY_09 -9.3 M02_0.010 MTHLY_10 -9.3 M02_0.411 MTHLY_11 -9.3 M01_0.312 MTHLY_12 -9.3 M02_0.413 MTHLY_13 -9.3 M02_0.214 MTHLY_14 -9.3 M02_0.315 MTHLY_15 -9.3 M02_0.416 MTHLY_16 -9.3 M01_0.317 MTHLY_17 -9.3 M02_0.018 MTHLY_18 -9.3 M02_0.319 MTHLY_19 -9.2 M02_0.420 MTHLY_20 -9.2 M01_0.521 MTHLY_21 -9.2 M01_0.222 MTHLY_22 -9.2 M02_0.223 MTHLY_23 -9.2 M02_0.224 MTHLY_24 -9.2 M02_0.225 MTHLY_25 -9.2 M02_0.0

• A database of >100,000 lead-like compounds where used for screening against our two Pharmacophore models.

• A total of 18,082 compounds fulfill all requirements of Model 1 while 13,587 compounds where obtained with Model 2.

• 21 % of these compounds where selected by both models.

Results: Docking and ranking of top-hits.

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.

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.

Acknowledgments

• Dr. Maldonado

• Adriana Díaz

• Dra. Díaz

• Dra. Gonzalez

Questions?...

Thanks for your attention.