Computational Drug Discovery and Design

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matching the interaction sites are grown and linked based on the
connecting rules. Predicted ligands are ranked by estimated
binding energy, structural complication and synthetic viability
[3, 10, 11]. Successful application of de novo drug design has
been studied in thrombin inhibitors, thymidylate synthase inhibi-
tors, carbonic anhydrase II inhibitors, antitrypanosomiasis, estro-
gen receptor antagonists, and antifungal and some antiviral agents
[12–22].
In this chapter, we portray the basic idea of de novo design
strategy to design an effective potent drug like candidate against the
biological targets. The art of de novo design is epitomized with an
example of vascular endothelial growth factor receptor-2 (VEGFR-
2) tyrosine kinase inhibitors build using computational methods.
An elementary scheme of de novo drug design is represented in
schematic diagram, shown in Fig.1.

2 Materials



  1. RCSB protein Data Bank (PDB) to obtain protein structure.

  2. Chimera1.9 for refinement of ligand and receptor structure
    and also for molecular visualization and interaction analysis.

  3. Modeller 9.15 for adding missing residues.

  4. LigBuilder V2.0 to design new molecules.

  5. FAF-Drugs2 to examine absorption, distribution, metabolism,
    and toxicity of the molecules.


Fig. 1(a) Schematic representation of de novo drug design methods and (b) de novo design strategy in
LigBuilder V2.0


De Novo Design of Ligands 73
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