Humans in the modern society can be exposed to a large number of chemicals through
several different routes on a regular basis. Thus, in order to control risks to mankind, the
adverse effects associated with exposure chemicals, especially their toxicities, should be
assessed in advance. Additionally, poor pharmacokinetics, side effects and compound
toxicity are not only frequent causes of latestage failures in drug development but also a
source of unnecessary animal tests. In the past decade, computer (in silico) based models
matured into powerful tools for simulating and quantifying biochemical processes at a
molecular level. In silico methods are nowadays routinely used in the early stages of drug
development. In the context of the REACH (Registration, Evaluation and Authorization of
Chemicals) initiative of the European Union, computerbased models have received additional
attention as they can predict the toxic potential of the existing and hypothetical compounds.
The talk will focus on the development and application of in silico methods for prediction of
toxic outcomes in chemical compounds (1). For example, a drug or a chemical compound
might interact with a molecular target which can result in interactions with multiple molecular
targets including both therapeutic as well as offtarget with different affinities. In this process,
consequently it can activate different signaling pathways or interact with functional pathways
(2). Furthermore, such interactions at cellular level can produce toxic effects on certain organs.
This can be further extended to the adverse drug reactions (ADRs) profile of population sharing
similar toxicological pathways or network (3).

1. M. Drwal, P. Banerjee, M. Dunkel, M. Wettig and R. Preissner
ProTox: A web server for the in silico prediction of rodent oral toxicity
Nucleic Acids Res. 42(Webserver issue 2014) : W53-58.

2. P. Banerjee, V.B. Siramshetty, M.N. Drwal and R. Preissner.
Computational methods for prediction of in vitro effects of new chemical structures
J Cheminform (2016) 8:51.

3. I.G. Metushi, A. Wriston,P. Banerjee, B.O. Gohlke, A.M. English, A. Lucas, C. Moore, J. Sidney,
S. Buus, D.A. Ostrov, S. Mallal, E. Phillips, J. Shabanowitz, D.F. Hunt, R. Preissner and B. Peters
Acyclovir Has Low but Detectable Influence on HLA-B*57:01 Specificity without Inducing
Hypersensitivity. PLoS ONE 10(5): e0124878 (2015).