(L-deprenyl), where there is formation of covalent bond between the inhibitor and
FAD cofactor, the predicted binding mode from molecular docking has reasonable
overlap with the one from crystal structure (refer to Fig. 2B). Figure 2 shows the
overlap of binding mode obtained from molecular docking with the experimental
crystal structure. The target is monoamine oxidase B, and two inhibitors were
considered, namely safinamide and selegiline. The former one is reversible MAO-B
inhibitor, while the latter one is irreversible inhibitor which covalently bonding to
the FAD cofactor.
4.2 Success Stories of Force-Field-Based Methods in Drug
Discovery Projects
Drug discovery for a new disease is a complex project which requires knowledge
from different domains, namely protein profiling (genomics), bioinformatics (for
doing comparative genomics for target discovery), structural biology (for structure
elucidation of the target), cheminformatics (chemical space), synthetic medicinal
chemistry (design and synthesis of molecules), toxicology, pharmacology, pharmacokinetic property estimation, binding assay experiments, clinical studies.
Computational approaches can be employed to speed up many of the intermediate
steps involved in the drug discovery such as target discovery (computational
comparative genomics), structure elucidation for a target (homology modelling)
and lead compound prediction (using cheminformatics, virtual screening and de
nova design) and ADMET property prediction (for screening the lead compounds
with appropriate pharmacokinetic properties) and toxicity prediction (by studying
the interaction of ligands with potential known off-targets). The chemical space
consists of billions of small molecules [30], and huge genomics database suggests
that there are thousands of targets and off-targets for studying the drug potency and
its toxicity which makes the computational approaches as irreplaceable workhorses
for the drug discovery projects. Thanks to such approaches, there are many drugs
which are in the clinical trial phase as well as some of them are approved by FDA
[31]. The lists include various drug compounds, namely Captopril, Dorzolamide,
Saquinavir, Zanamivir, Oseltamivir, Aliskiren, Boceprevir, Nolatrexed, TMI-005,
LY-517717, Rupintrivir and NVP-AUY922. In particular, the compounds
Captopril and Aliskiren are used for treating heart disease, hypertension, and
Saquinavir, Zanamivir, Oseltamivir, Rupintrivir are potential antiviral compounds
(for HIV type I and type II, influenza virus and human rhinovirus).
230
N. A. Murugan et al.
FAD cofactor, the predicted binding mode from molecular docking has reasonable
overlap with the one from crystal structure (refer to Fig. 2B). Figure 2 shows the
overlap of binding mode obtained from molecular docking with the experimental
crystal structure. The target is monoamine oxidase B, and two inhibitors were
considered, namely safinamide and selegiline. The former one is reversible MAO-B
inhibitor, while the latter one is irreversible inhibitor which covalently bonding to
the FAD cofactor.
4.2 Success Stories of Force-Field-Based Methods in Drug
Discovery Projects
Drug discovery for a new disease is a complex project which requires knowledge
from different domains, namely protein profiling (genomics), bioinformatics (for
doing comparative genomics for target discovery), structural biology (for structure
elucidation of the target), cheminformatics (chemical space), synthetic medicinal
chemistry (design and synthesis of molecules), toxicology, pharmacology, pharmacokinetic property estimation, binding assay experiments, clinical studies.
Computational approaches can be employed to speed up many of the intermediate
steps involved in the drug discovery such as target discovery (computational
comparative genomics), structure elucidation for a target (homology modelling)
and lead compound prediction (using cheminformatics, virtual screening and de
nova design) and ADMET property prediction (for screening the lead compounds
with appropriate pharmacokinetic properties) and toxicity prediction (by studying
the interaction of ligands with potential known off-targets). The chemical space
consists of billions of small molecules [30], and huge genomics database suggests
that there are thousands of targets and off-targets for studying the drug potency and
its toxicity which makes the computational approaches as irreplaceable workhorses
for the drug discovery projects. Thanks to such approaches, there are many drugs
which are in the clinical trial phase as well as some of them are approved by FDA
[31]. The lists include various drug compounds, namely Captopril, Dorzolamide,
Saquinavir, Zanamivir, Oseltamivir, Aliskiren, Boceprevir, Nolatrexed, TMI-005,
LY-517717, Rupintrivir and NVP-AUY922. In particular, the compounds
Captopril and Aliskiren are used for treating heart disease, hypertension, and
Saquinavir, Zanamivir, Oseltamivir, Rupintrivir are potential antiviral compounds
(for HIV type I and type II, influenza virus and human rhinovirus).
230
N. A. Murugan et al.