presentation on in silico studies

effect of in silico pharmacology and toxicology studies on usage of experimental animals used in the drug discovery and development

1. Impact of in- silico predictive pharmacology and toxicology studies on usage of experimental animals used in the drug discovery and development Shaik . Sana Banu , K Chandana , SK Thahajeb , V. Roopavani , N. Vishnupriya and B. V krishnaReddy Department of Pharmacology, Raos College of Pharmacy, Nellore Abstract :Besides in-vitro cell lines and organ studies as an alternatives to animal experimentation, various other alternatives particularly, in- silico techniques are developed. These methods provide an alternative means for the drug and chemical testing, with reduced animal use up to some levels. For example, Software known as Computer Aided Drug Design (CADD) is used to predict the receptor binding site for a potential drug molecule. In addition, Quantitative Structure Activity Relationship (QSAR) computer program that uses mathematical descriptions by which the relationship between physicochemical properties of a drug molecule and its biological activity can be established. Further, recent QSAR software shows more appropriate results while predicting the carcinogenicity of any molecule. Advantages associated with these methods are time efficiency, requires less man power, and cost effectiveness. In this review, we have been described various in- silico approaches in details, by which we can reduce the total number of experimental animals in drug discovery and development to achieve the objectives of Russel and Burche’s 3 R’s in usage of experimental animals. 1

2. Drug discovery and development Drug development : It is a highly complex , tedious , competetive , costly and commercially risk process. Approaches to drug discovery : Natural sources Chemical synthesis Rational approaches Molecular modelling Combinational chemistry Biotechnology File IND File NDA Isolate protein involved in disease (2-5 years ) Identify disease Preclinical testing (1-3 years) Find a drug effective against disease protein (2-5 years) Formulation & Scale-up Human clinical trials (2-10 years ) FDA approval (2-3 years ) 2

3. Introduction of in silico studies In silico techniques are developed particularly as an alternative to animal experimentation. The development of  in silico  pharmacology and toxicology through the development of methods including databases, quantitative structure–activity relationships, similarity searching, pharmacophores , homology models and other molecular modelling , machine learning, data mining, network analysis tools and data analysis tools that use a computer. Some of these methods can be used for virtual ligand screening and virtual affinity profiling. Although these methods are not proven yet to ‘discover drugs' alone, they represent progress by increasingly demonstrating their ability to deliver enrichment in identifying active molecules for the target of interest. 3

4. The Process of drug discovery and development 4

5. Identify disease Isolate protein Find drug Preclinical testing GENOMICS, PROTEOMICS & BIOPHARM. HIGH THROUGHPUT SCREENING MOLECULAR MODELING VIRTUAL SCREENING COMBINATORIAL CHEMISTRY IN VITRO & IN SILICO ADME MODELS Potentially producing many more targets and “personalized” targets Screening up to 100,000 compounds a day for activity against a target protein Using a computer to predict activity Rapidly producing vast numbers of compounds Computer graphics & models help improve activity Tissue and computer models begin to replace animal testing 5

6. In silico models 6

7. Computer Aided Drug Design (CADD) Software known as) Computer Aided Drug Design (CADD is used to predict the receptor binding site for a potential drug molecule. CADD works to identify probable binding site and hence avoids testing of unwanted chemicals having no biological activity. 7

8. Quantitative Structure Activity Relationship (QSAR) Quantitative Structure Activity Relationship (QSAR) is the mathematical description of the relationship between physicochemical properties of a drug molecule and its biological activity . The activities like carcinogenicity and mutagenicity of a potential drug candidate are well predicted by the computer database. The recent QSAR software shows more appropriate results while predicting the carcinogenicity of any molecule. The advantages of computer models over conventional animal models are the speed and relatively inexpensive procedures . 8

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10. Computer assisted learning (CAL) CAL deals with a range of software packages which simulate the animal experiments Two softwares are curently used in india Expharm - developed by JIPMER, India X- cology 10

11. Softwares for Drug designing Sanjeevini : A complete drug design software. Drug-DNA Interaction Energy server: Calculates the Drug-DNA interaction energy. Binding Affinity Prediction of Protein-Ligand Server(BAPPL): Computes the binding free energy of a protein-ligand complex. ParDOCK - Automated Server for Rigid Docking: Predicts the binding mode of the ligand in receptor target site. 5. Lipinski Filters: Checks whether a drug satisfies the 5 Lipinski rules. 7. Molecular Volume Calculator : Calculates the volume of a molecule 8. DNA Sequence to Structure: Generates double helical secondary structure of DNA using conformational parameters taken from experimental fiber-diffraction studies. 9. RASPD for Preliminary Screening of Drugs: Preliminary screening of ligand molecules based on physico -chemical properties of the ligand and the active site of the protein. This will predict binding energy of drug/target at a preliminary stage. 11

12. In silico toxicology In silico or computational toxicology is an area of very active development and great potential. A prediction of potential toxicity requires several stages; Collation and organisation of data available for the compound, or if this is not available, information for related compounds. An asssessment of the quality of the data Generation of additional information about the compound usingcomputational techniques at various levels of complexity Use of an appropriate strategy to predict toxicity- i.e a statistically valid method which makes best use of all available information. 12

13. IN SILICO PREDECTIVE TOXICOLOGY 13 In silico toxicity prediction Expert or Rule based system Eg:DEREK QSAR Model Eg:TOPKAT Such models however cannot replicate complicated interactions in the whole system

14. Can computer models and cell cultures animal research ? 14 Computer models and cell cultures are good for screening and are used frequently. Such models cannot replicate complicated interactions in the whole system. Final testing depends on studies in animals, sometimes it is required by law. Animal and no-animal models used in conjunction achieve the best answer.

15. Conclusion : On the basis of existence scientific literature as discussed above, it may be suggested that in- silico techniques may be better alternatives for the drug and chemical testing, with reduced animal use up to some levels, since with the help of such software programs we can tailor make a new drug for the specific binding site and then in final stage animal testing is done to obtain confirmatory results. Further, recent QSAR software shows more appropriate results while predicting the carcinogenicity of any molecule. Advantages associated with these methods are, time efficiency, requires less man power, and cost effectiveness. Overall, by using in- silico approaches it can be possible to reduce the total number of experimental animals in drug discovery and development, by which we may achieve the objectives of Russel and Burche’s 3 Rs in usage of experimental animals. 15