1. In Silico discovery of Histone-lysine N-methyltransferase SETD2 inhibitors.
Torres, Juan C. and Montañez, Gretel
UPR Cayey, Puerto Rico
Abstract
Protein methyltranferase have been linked to a series of genetic diseases and
aberrations.Histone methyltransferases (HMTs) methyl group is transferred from a donor
molecule, which is usually Sulfur-adenosyl methionine; SAM, to an acceptor. The protein
methyltransferases (PMTs) have emerged as a novel target class in the area of oncology
because they have been identified with the influence of cancer tumor genesis. Using several
software and databases, two Pharmacophore models were created and screened to obtain
possible lead-like compounds. As a result, only five pieces of the database were used for the
screening of the models and was able to filter 20% of the database that was screened. A total
31,669 compounds where docked In Silico to the target protein and the results ranked
according to their predicted binding energies and 58 drugs had binding energies from -9.7 to
-9.0. This In Silico process focused in finding potential lead compounds that will inhibit the
methylation of histone proteins and thus preventing cancer outgrowth.
Introduction transferedfrom a donor molecule, which is
This investigation project is part of a usually Sulfur-adenosyl methionine; SAM,
bigger scale investigation in which a RISE to an acceptor. The methylation occurs on
student is working with methyltranferases, nucleic bases in DNA or amino acids in
in the Dengue virus. Recently, it has been protein structures. There have been several
discovered thatmethyltranferases are also methyltransferasesidentified, including
involved in cancer. Methyltransferase, also DNA methyltransferase,
known as methylase, is a tranferase tRNAmethyltransferase and protein
enzyme type in which a methyl group is methyltransferase.

2. Histone methyltransferases (HMTs) order the DNA into structural units called
transfer a methyl group from the cofactor nucleosomes.
S-adenosyl methionine to lysine or Methylation of histones is important
arginine residues on histone tails, thereby biologically, as it is the principal
regulating chromatin compaction, binding epigenetic modification of chromatin that
of effector proteins and gene transcription. determines gene expression, genomic
HMTs constitute an emerging target class stability, etc. Furthermore some abnormal
in diverse disease areas, and selective expression or activity of methylation-
chemical probes are necessary for target regulating enzymes has been noted in some
validation (Campagna et al. 2011). types of human cancers, suggesting
Consistent with the histone code, recent associations between histone methylation
studies indicate that methylation of histone and malignant transformation of cells or
H3 lysine 9 (H3 Lys9), a modification formation of tumors (Duns et al. 2010). It
associated with transcriptionally silent is now generally accepted that in addition
heterochromatin, is critical for long-range to genetic aberrations, cancer can be
chromatin regulatory processes (Rice et al. initiated by epigenetic changes in which
2003). gene expression is altered without genomic
This investigation work is with protein abnormalities.
methyltranferases focusing in histone The protein methyltransferases (PMTs)
methyltranferases, which are histone- have emerged as a novel target class,
modifying enzymes. These groups of especially for oncology indications where
enzymes catalyze the transfer of three specific genetic alterations, affecting PMT
methyl groups to lysine. Histones are activity, drive cancer tumor genesis. This
highly alkaline proteins found in In Silico process focused in finding
eukaryotic cell nuclei that package and potential lead compounds that will inhibit

3. the methylation of histone proteins and models shown in figure 1. As a result, a
thus preventing cancer outgrowth. total of 18,082 compounds fulfilled all the
Methodology requirements of Model 1, while 13,587
The 3D structure of the protein Histone- compounds where obtained with Model 2.
lysine N-methyltransferase SETD2 was Out of both models 21% of these
downloaded from pdb.org. Investigators compounds where selected. In Figure 2,
identified a new target for drug the table demonstrates the lead-like
development in the Histone-lysine N- compounds in ranking binding energy. The
methyltransferase SETD2 by analysis of highest binding energy was -9.7 and from -
benzene mapping and the interactions of 9.7 to -9.0 there were 58 drugs.
previously identified compounds. Using
the information of the previously identified
compounds, we created two
Pharmacophore Models, using the software
LigandScout, for the selected target and
performed a virtual pre-screening of Drug Pharmacophore Model 01
Databases against our models. Finally, a
secondary screening to identify “top-hits”
or potential lead compounds by ranking
binding energy also using the software
AutoDockVina was performed.
Pharmacophore Model 02
Results
Figure 1. The two Pharmacophore Models that
where created and used to screen the databases
A database, of approximately 150,000 for potential lead-like compounds.
lead-like compounds, was used for the
screening against our two Pharmacophore

4. development. Two distinct pharmacophore
Compound Affinity
Model models where generated and used to filter
Name (kcal/mol)
the original database of small chemical
1 MTHLY_01 -9.7 M01_0.3
2 MTHLY_02 -9.5 M02_0.0 compounds to less than 20% of the total
3 MTHLY_03 -9.4 M01_0.2
4 MTHLY_04 -9.4 M02_0.3 number of compounds.
5 MTHLY_05 -9.4 M01_0.3
A total of 31,669 compounds where
6 MTHLY_06 -9.3 M01_0.4
7 MTHLY_07 -9.3 M01_0.3 docked In Silico to the target protein and
8 MTHLY_08 -9.3 M02_0.2
9 MTHLY_09 -9.3 M02_0.0 the results ranked according to their
10 MTHLY_10 -9.3 M02_0.4
11 MTHLY_11 -9.3 M01_0.3 predicted binding energies. A group of
12 MTHLY_12 -9.3 M02_0.4
drug-like-compounds with high binding
13 MTHLY_13 -9.3 M02_0.2
14 MTHLY_14 -9.3 M02_0.3 energies (less than -9.0 kcal/mol) was
15 MTHLY_15 -9.3 M02_0.4
16 MTHLY_16 -9.3 M01_0.3 identified in the secondary screening
17 MTHLY_17 -9.3 M02_0.0
18 MTHLY_18 -9.3 M02_0.3 consistent with the possibility of high
19 MTHLY_19 -9.2 M02_0.4
affinity interactions. Our screenings with
20 MTHLY_20 -9.2 M01_0.5
21 MTHLY_21 -9.2 M01_0.2 our models gave great results for just being
22 MTHLY_22 -9.2 M02_0.2
23 MTHLY_23 -9.2 M02_0.2 a pilot investigation.
24 MTHLY_24 -9.2 M02_0.2
25 MTHLY_25 -9.2 M02_0.0 For future work we would complete the
Figure 2. The list of the top 25 drugs with ranking screening of the lead-like database, which
binding energy. This gives the possibility that some
of these lead-like compounds could be potential is about 1.7 million compounds, using both
drugs that would inhibit the methylation process.
Pharmacophore models. The results of the
Conclusion top-hits are evaluated and if appropriate
Initial analysis of the Histone-lysine N- ranking binding energy, the information
methyltransferase SETD2 suggests that the would be used to refine the Pharmacophore
binding site for the methyl donor model and repeat the screening cycle. If
compound SAM can be used as potential the refinement of the model gives good
targets for In Silico drug discovery and

5. results, the next steps is to obtain/purchase histone methylation (Tamaru and Selker
some of the predicted high affinity 2001). Leading to a potential area of
compounds and testtheir potential as possible future work in the correlation
inhibitors in a bioassay. Also, it has been between DNA and protein methylation.
noted that DNA methylation depends on
Acknowledgment
Juan Carlos Torres and Gretel Montañez acknowledge the RISE program for funding. This
work was mentored by Dr. Hector Maldonado and his student co-worker Adriana Díaz.
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