Artificial neural networks (ANNs) are frequently being used for drug design and
the discovery process. ANN mimics the capacity of the human brain in terms of
its structure and function. The brain is composed of several neurons that are
capable of storing, retrieving, and connecting pieces of information. It is
capable of recognizing patterns based on prior learning and training. There
are nearly 100 billion neurons in the human brain with around 100 trillion
synaptic connections. Therefore, information processing in the brain is a consequence
of the myriad number of neurons present as well as the capacity of these
neurons to communicate among themselves for a meaningful interpretation of
the information [1].
Biological neurons are composed of dendrites (capable of taking up the signal);
the cell body (information processing); the axon (passing on the information);
and synapses (communicating with other neurons). The power of the brain lies
in its ability to relay signals across several neurons within fraction of seconds.
This ability to process the procured information and interpret it is not only genetic
but largely based on the acquired skill set. Neuroscientists have made
progress in mapping the brain and deciphering the functions of several neurons. However, the functioning of the brain still remains a mystery, and so
far no computer can mimic the functioning of the brain completely. With an
increase in computational power, networks that could function similarly to
the brain are being developed. Such networks are called ANNs.neurons. However, the functioning of the brain still remains a mystery, and so
far no computer can mimic the functioning of the brain completely. With an
increase in computational power, networks that could function similarly to
the brain are being developed. Such networks are called ANNs.