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
Isolate protein
involved in
disease (2-5 years)
Identify disease
Preclinical testing
(1-3 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 demonstrating3

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
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
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

9. 9

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
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

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;
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 data
3. 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.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