The discovery of new pharmaceuticals via computer modeling is one of
the key challenges in modern medicine. The advent of global networks of genomic,
proteomic and metabolomic endeavors is ushering in an increasing number of novel
and clinically important targets for screening. Computational methods are anticipated
to play a pivotal role in exploiting the structural and functional information to
understand specific molecular recognition events of the target macromolecule with
candidate hits leading ultimately to the design of improved leads for the target. In this
review, we sketch a system independent, comprehensive physicochemical pathway
for lead molecule design focusing on the emerging in silico trends and techniques.
We survey strategies for the generation of candidate molecules, docking them with
the target and ranking them based on binding affinities. We present a molecular
level treatment for distinguishing affinity from specificity of a ligand for a given
target. We also discuss some significant aspects of drug absorption, distribution,
metabolism, excretion and toxicity (ADMET) and highlight improved protocols
required for higher quality and throughput of in silico methods employed at early
stages of discovery. We present a realization of the various stages in the pathway
proposed with select examples from the literature and from our own research to
demonstrate the way in which an iterative process of computer design and validation
can aid in developing potent leads. The review thus summarizes recent advances and
presents a viewpoint on improvements envisioned in the years to come for automated
computer aided lead molecule discovery.
Keywords: Computer aided drug discovery, In silico lead design, Binding affinity and
specificity, ADMET.