The drug repositioning - reuse of registered medicinal substances in new indications -
is becoming popular as the cost of a new drug development process is increasing in the
pharmaceutical industry, whereas the yearly number of new patented drugs is decreasing.
Finding new therapeutic areas of existing and tested drugs is not only of economic interest,
but social too.
The joint study of the side effect profile and chemical structure of drugs allows a radically
different drug similarity metric. It relies on the hypothesis if the side effect profile of
two drugs is similar in several side effects, their targets are probably the same, or at least
they are in the same pathway. In some sense this approach outperforms techniques based
on chemical similarity measure because it measures the effect of the drug on the organism
as whole. Therefore the application of chemical descriptors and side effect similarity in a
common framework is desirable.
In this paper we overview earlier results for the hypothesis of common proteins in case
of similar joint chemical and side effect profiles. Then we propose improvements such as
using publicly available placebo-controlled side effect prevalence data instead of simple term
frequency based text mining approach., and using many heterogeneous systems biological
Using large number of heterogeneous data sources requires a new approach which is
based on the combination of these similarities in the kernel space. This idea has already
been successfully applied in gene prioritization using heterogeneous data sources.
I adapted this MKL (Multiple Kernel Learning) based approach for the prioritization of
drugs for a new indication.
The long-term goal of our research is to support drug repositioning with the joint usage
of chemical features and side effects, to gain deeper insight of the side effect as a phe-
nomenon, and the effects that influence them. This work has been carried out within a
joint research of the Bioinformatics Research Group at BUTE Department Of Measure-
ment and Information Systems and the Semmelweis University Department of Organic