Chemistry Reference
In-Depth Information
partitioning ratio, volume of distribution, metabolism, half-life, excretion, urinary
excretion, clearance, toxicity, half lethal dose in rat or mouse,
etc
[40].
For new target families, chemical knowledge has to be generated. Beyond
biological target validation, the emphasis is on chemistry/physics to provide the
molecules (for which novel biology/pharmacology can be studied).
BINDING AFFINITY PREDICTION
The affinity of the ligand compound to the macromolecular receptor is assumed
closely related to its biological activity. Consequently, the key for computational
lead optimization is the accurate prediction of the ligand-receptor binding
affinities.
The essential components for determining affinity include contributions from
solvation and desolvation, electrostatic interactions between the ligand and the
receptor; enthalpic and entropic contributions resulting from changes in the number
of degrees of freedom; conformational changes of ligand and receptor experienced
upon complex formation and spatial complementarity of both binding partners.
In the absence of consonance regarding reliability/efficiency of methods to predict
affinities, whereas the most accurate are also more time-consuming, many
approaches are used for adapting different requirements to evaluate affinities
[324,339-361]. More details will be discussed in the following sections.
Scoring Functions
Computational tools such as docking play an important role in drug design
whereas an important problem is the determination and development of energy
scoring functions that can describe accurately the ligand-protein interactions [107,
142, 148, 295, 303, 304, 327, 331, 332, 346, 355, 358, 362-554].
There are typically three applications of the energy scoring functions in molecular
docking.
a)
Determination of the ligand site and its binding mode for a protein. By
evaluating the strength of the binding, molecular docking generates
