Diseases caused by parasites have an overwhelming impact on public health
throughout the world, particularly in the tropics and subtropics. Malaria and
leishmaniasis are two such widely known neglected parasitic diseases. The current
global situation indicates more than one million deaths from these two diseases every
year despite several efforts by WHO to combat them. Vectors for carrying and
transmitting these parasites are arthropods. Use of insect repellents is a vital
countermeasure in reducing these arthropod-related diseases. However, despite access
to many available drugs for treatment of these diseases, their growing resistance poses
serious concerns and necessitates development of novel countermeasures. The present
chapter discusses how the in silico methodologies can be utilized to develop
pharmacophore models to identify novel antimalarials, antileishmanial, and insect
repellents. The models presented in this chapter not only provided important molecular
insights to better understand the “interaction pharmacophores” but also guided
generation of templates for virtual screening of compound databases to identify novel
bioactive agents. The pharmacophore models presented here demonstrated a new
computational approach for organizing molecular characteristics that were both
statistically and mechanistically significant for potent activity and useful for
identification of novel analogues as well.
Keywords: In Silico pharmacophore models, CATALYST methodology,
parasites, malaria, leishmaniasis, arthropods, insect repellents, virtual screening,
compound database, quantum chemical (QM) calculations, stereo-electronic
properties, molecular electrostatic potentials (MEPs), drug design, drug discovery,
novel compounds.
