Apart from the above-mentioned drugs, several other inhibitors of epigenetic
targets are discovered. Some of these inhibitors are depicted in Fig. 2.
4 Chemoinformatics Study on Epigenetic Modulators
This section briefly describes the key strategies to select and assess a small-molecule
library based on current best practices and theoretical guidelines. Once a target is
determined, one needs to design and select a chemical compound library. Recently,
we have developed a powerful and curated database to assist the researchers in
epigenetic drug discovery (www.epidbase.org). Our database has diverse molecules
and scaffolds that are found to be active against various epigenetic proteins. Detailed
methodology and analysis can be availed from our previously published study [46].
There are numerous chemoinformatics tools available to support the synthetic and
medicinal chemists in vetting the promising libraries [47–49]. These tools are
available in various forms to select building blocks, enumerate compounds, and also
calculate chemical descriptors and fingerprints to sketch the library. In order to
utilize these tools, an important prerequisite is to store and sort the molecules using
one of the data formatting systems such as SMILES (simplified molecular input line
entry specification format) or SDF (structure-data file format). Many software
packages including Schrodinger, Tripos, and Pipeline Pilot are powered with
structural, physicochemical, ADME, and diversity filtering tools.
Strategy 1. Analyze the chemical space and scaffold diversity
The term ‘scaffold’ represents the core structures of bioactive compounds and is
often used interchangeably with terms like ‘framework,’ ‘substructure,’ or ‘fragment.’ As proposed by Bemis and Murcko [50], the framework can be obtained by
trimming the side chain atoms which are not positioned in the connecting path
between two rings. The concept of chemical scaffold diversity is widely applied in
drug discovery. The chemical space in relevance to drug-like molecules is estimated
to be of 10
60 molecules (i.e., between 300 and 500 Da of molecular weight).
Practically, chemical space is infinite and meagerly populated and it is impossible to
mine out a drug. In drug discovery, a chemical library is not of significant use if the
biological and chemical space does not overlap [51]. Therefore, scaffolds should be
focused upon as the core of small chemical libraries to be synthesized or acquired.
There is a significant number of studies that have applied large substructure similarity to analyze the diversity based on ring systems in the structures [52–57]. Using
such a strategy enables the medicinal chemist to select structures which belong to
the same chemical family and have a common molecular framework. For example,
in our database, to narrow down the chemical space and select the scaffolds, we
searched the literature for known modulators of epigenetic proteins. Despite the
importance of epigenetic proteins in therapeutics, there were no resources or platforms available to comprehensively analyze the epigenetic modulators for drug
256
S. Loharch et al.
targets are discovered. Some of these inhibitors are depicted in Fig. 2.
4 Chemoinformatics Study on Epigenetic Modulators
This section briefly describes the key strategies to select and assess a small-molecule
library based on current best practices and theoretical guidelines. Once a target is
determined, one needs to design and select a chemical compound library. Recently,
we have developed a powerful and curated database to assist the researchers in
epigenetic drug discovery (www.epidbase.org). Our database has diverse molecules
and scaffolds that are found to be active against various epigenetic proteins. Detailed
methodology and analysis can be availed from our previously published study [46].
There are numerous chemoinformatics tools available to support the synthetic and
medicinal chemists in vetting the promising libraries [47–49]. These tools are
available in various forms to select building blocks, enumerate compounds, and also
calculate chemical descriptors and fingerprints to sketch the library. In order to
utilize these tools, an important prerequisite is to store and sort the molecules using
one of the data formatting systems such as SMILES (simplified molecular input line
entry specification format) or SDF (structure-data file format). Many software
packages including Schrodinger, Tripos, and Pipeline Pilot are powered with
structural, physicochemical, ADME, and diversity filtering tools.
Strategy 1. Analyze the chemical space and scaffold diversity
The term ‘scaffold’ represents the core structures of bioactive compounds and is
often used interchangeably with terms like ‘framework,’ ‘substructure,’ or ‘fragment.’ As proposed by Bemis and Murcko [50], the framework can be obtained by
trimming the side chain atoms which are not positioned in the connecting path
between two rings. The concept of chemical scaffold diversity is widely applied in
drug discovery. The chemical space in relevance to drug-like molecules is estimated
to be of 10
60 molecules (i.e., between 300 and 500 Da of molecular weight).
Practically, chemical space is infinite and meagerly populated and it is impossible to
mine out a drug. In drug discovery, a chemical library is not of significant use if the
biological and chemical space does not overlap [51]. Therefore, scaffolds should be
focused upon as the core of small chemical libraries to be synthesized or acquired.
There is a significant number of studies that have applied large substructure similarity to analyze the diversity based on ring systems in the structures [52–57]. Using
such a strategy enables the medicinal chemist to select structures which belong to
the same chemical family and have a common molecular framework. For example,
in our database, to narrow down the chemical space and select the scaffolds, we
searched the literature for known modulators of epigenetic proteins. Despite the
importance of epigenetic proteins in therapeutics, there were no resources or platforms available to comprehensively analyze the epigenetic modulators for drug
256
S. Loharch et al.