Presentation on theme: "NoTox: Toxicity Analysis of Molecules and their derivatives Primary Advisor : Professor David J. Wild Bioinformatics Advisor: Professor Sun Kim."— Presentation transcript:
NoTox: Toxicity Analysis of Molecules and their derivatives Primary Advisor : Professor David J. Wild Bioinformatics Advisor: Professor Sun Kim.
What is Computational Toxicology Computational toxicology is an emerging field that constitutes methodical approaches to analyze the harmful effects on the environment and public health due to exposure to chemicals. Computational toxicology may be defined as the application of the tools developed using computational biology concepts to analyze the risk that some chemicals pose to human health and the environment.
Types of toxicology The different types of toxicology include Toxicogenomics Aquatic Toxicology Chemical toxicology Ecotoxicology Environment toxicology Medical Toxicology Forensic Toxicology Ref: Wikipedia
How is computational toxicology studies important to biology Computational toxicity is an increasingly important field with implications throughout biomedical science and drug discovery. To name a few applications Providing molecular profiling approaches to toxicology Drug toxicity Gene- Drug interaction studies Toxicological analysis of Biological molecules and their derivatives
Shortcomings The shortcomings of most computational toxicology methods are Most toxicity methods concentrate on determining whether a particular compound has toxic properties or not. The methods do not necessarily help in understanding whether modifying a particular molecule synthetically to reduce toxic effects is possible. It also does not concentrate on identifying and analysing the reason for toxicity of most molecules.
Problems analyzed If we have a toxic molecule, can we find a synthetic alternative that might be non toxic If we have a non-toxic molecule, might it be metabolized or changed in the body to something toxic? We use some cheminformatics representations called SMILES and SMIRKS to deal with these problems
Terminologies - SMILES/SMIRKS SMILES is the acronym for Simplified Molecular Input Line Entry Specification. Each molecule has a unique canonicalized SMILES representation (Eg c1ccccc1 represents benzene). SMIRKS is a reaction transform language. In general two different kinds of SMIRKS are in use to show transformations. Functional group transformations and molecular framework modifications. An example for SMIRKS would be [O:1]=[C:2][Cl:3].[N:4][H:5]>>[O:1]=[C:2][N:4] this is an example of a simple displacement reaction representation
Drug Guru - Literature Review Drug Guru is a web based computer software program that applies medicinal chemistry transformation reactions to an input structure. The transformation reactions are medicinal chemistry design rules of thumb taken from other drug discovery programs. The output of this program is a list of analogs that can be used for further synthesis. Ref: 
Screen shot of drug guru
Drug Guru to NoTox Drug Guru uses smirks to develop alternative compounds based on medicinal chemistry reactions. NoTox combines the concept of Drug Guru with a different field – Toxicity.
NoTox Tool to predict alternatives for a given molecule based on reaction transformations Tool to test the toxicity of any given molecule Helps in comparing the toxicity of the original and the derived molecule
NoTox - Input Requirements The input query (Original molecule) should be in the form of SMILES. The reaction transformations should be in the form of SMIRKS The SMIRKS used are a more specific form of the reaction.
Flowchart of NOTOX
Smirksgen The program generates derivatives for a given molecule based on the specified reaction transformation rules. Openeye software for library generation The smirksgen program is developed in Python and it takes in input from a GUI developed using HTML
Toxicity prediction using Toxtree Toxtree is an open source application that uses the decision tree approach to identify the toxicity of a molecule represented as SMILES. It provides 5 plugins. In NoTox, we make use of the Cramer's rule decision tree approach to determine toxicity. The input molecules are classified in the increasing levels of toxicity as Class 1, Class II and Class III
NoTox - Features available Apart from Smirksgen and Toxtree, NoTox Provides access to another tool WENDI that helps in the profiling of any particular molecule. NoTox also has a feature that helps in the validation of the input SMILES
Screen shot of NoTox
OBJECTIVE Identifying a molecule with desirable properties and activity towards the human body. Observing the Toxicological effects due to the activity of the identified molecule.
WHY ATP?? ATP acts as a coenzyme in most intracellular energy transfer reactions. ATP acts as a substrate for kinases in signal transduction pathways. It is a major component of the Krebs cycle.
Mechanism of action of ATP and Its Uses The main action of ATP is phosphorylation. A double displacement reaction takes place between the phosphate molecule in ATP and the hydroxyl hydrogen of the reacting molecule. The reaction is depicted as follows. R-OH. ATP >> R-O-phosphate. ADP
Testing effect of ATP on human body Our objective is to study the toxicological effects of ATP on the human body. We use our tool NoTox to study the toxicological effects due to the reaction of ATP with other molecules.
Input data Using Smiles The test molecules were obtained by doing a substructure search in pubchem and the test set was a list of 100 molecules that contained a substructure that can react with ATP. The smiles format was obtained for these molecules using the molinspiration software.
The reaction transformations 500 reactions from Kegg involving ATP were studied and the mechanism of each reaction was observed and generalized to 2 SMIRKS rules one each for aromatic and aliphatic compounds
The result The toxicity of the input molecule was usually Class 1 or Class 2 The toxicity of the derivative was always found to be Class 3. It was observed that the reaction of a molecule with ATP increases the toxicity of the derivative. This suggests that ATP increases the toxicity in the body when it reacts with the biological molecules.
Evidence for the result Journal articles substantiate the observed result that ATP increases the toxicity of the molecule it reacts with. Some of the examples of the journal articles are Mallick.N, Rai.LC. Metal induced inhibition of photosynthesis, photosynthetic electron transport chain and ATP content of Anabaena doliolum and Chlorella vulgaris: interaction with exogenous ATP, Biomed Environ Sci Sep;5(3): Lundy, Paul ; Frew, R. ; Vair, C. ; Nelson, P. ; Gong, W,Mediation of Sulfur Mustard Cellular Toxicity by ATP: A Possible Mechanism of Action of Sulfur Mustard Toxicity, ADA KOBAYASHI K. ; RATAIN M. J. ; Pharmacodynamics and long-term toxicity of etoposide, Cancer chemotherapy and pharmacology ISSN CODEN CCPHDZ
Summary NoTox can be used to search for non-toxic alternatives to toxic compounds, and to find possible toxic metabolites Initial experiments indicate the method is useful Further work should be carried out to evaluate NoTox for both of these applications
Future Work An evaluation study that looks at the following can be performed Known toxic compounds and their derivatives Use information from metabolic database to evaluate the toxic effects due to any particular metabolic pathway.
References Kent D.Stewart, Melisa Shiroda, Craig A. James, Drug Guru: A computer Software Program for drug design using medicinal chemistry rules, doi: /j. bmc Robert J.Kavlock et.al, Computational Toxicology- A state of the Science mini review, doi: /toxsci/kfm297 Mallick.N, Rai.LC. Metal induced inhibition of photosynthesis, photosynthetic electron transport chain and ATP content of Anabaena doliolum and Chlorella vulgaris: interaction with exogenous ATP, Biomed Environ Sci Sep;5(3): Lundy, Paul ; Frew, R. ; Vair, C. ; Nelson, P. ; Gong, W,Mediation of Sulfur Mustard Cellular Toxicity by ATP: A Possible Mechanism of Action of Sulfur Mustard Toxicity, ADA KOBAYASHI K. ; RATAIN M. J. ; Pharmacodynamics and long-term toxicity of etoposide, Cancer chemotherapy and pharmacology ISSN CODEN CCPHDZ Wikipedia
Acknowledgements Professor David Wild Professor Sun Kim The faculty of the Bioinformatics and the Cheminformatics department. Linda Hostetter and Rachel Lawmaster.