Impact of in-silico predictive pharmacology and toxicology studies on usage of experimental animals used in the drug discovery and developmentShaik. Sana Banu, K Chandana, SK Thahajeb, V. Roopavani, N. Vishnupriya and B. V krishnaReddyDepartment of Pharmacology, Raos College of Pharmacy, NelloreAbstract: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.

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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

IN

D

File

NDA

Isolate proteininvolved in

disease (2-5 years)

Identify disease

Preclinical testing(1-3 years)

Find a drug effectiveagainst disease protein(2-5 years)

Formulation &Scale-up

Human clinical trials

(2-10 years)

FDA approval

(2-3 years)2

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.

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The Process of drug discovery and development

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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 targetsand “personalized” targets

Screening up to 100,000 compounds aday for activity against a target protein

Using a computer topredict activity

Rapidly producing vast numbersof compounds

Computer graphics & models help improve activity

Tissue and computer models begin to replace animal testing

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In silico models Computer aided molecular drug design

Quantitative structure activity relationship

Computer assisted learning

Computer or mathematical analysis

Microfluidic chips

DNA chips

Organ on chip

Human on chip

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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.

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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 .

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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

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Softwares for Drug designing 1. Sanjeevini: A complete drug design software.

2. Drug-DNA Interaction Energy server: Calculates the Drug-DNA interaction energy.

3. Binding Affinity Prediction of Protein-Ligand Server(BAPPL):Computes the binding free

energy of a protein-ligand complex.

4. 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

In silico toxicologyIn silico or computational toxicology is an area of very

active development and great potential.A prediction of potential toxicity requires several stages;1. Collation and organisation of data available for the

compound, or if this is not available, information for related compounds.

2. An asssessment of the quality of the data3. Generation of additional information about the

compound usingcomputational techniques at various levels of complexity

4. Use of an appropriate strategy to predict toxicity-i.e a statistically valid method which makes best use of all available information.

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IN SILICO PREDECTIVE TOXICOLOGY

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In silico toxicity prediction

Expert or Rule based system

Eg:DEREKQSAR ModelEg:TOPKAT

Such models however cannot replicate complicated

interactions in the whole system

Can computer models and cell cultures animal research?

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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.

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.

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