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ASSIGNMENT NO 1
ROLE OF BIOINFORMATICS IN PHARMACEUTICAL
INDUSTRY
SUBMITTED BY : MUZNA KASHAF
ROLL NUMBER : (16261514-030)
SUBMITTED TO : Dr. SOBIA
COUSE TITLE : BIOINFORMATICS
SEMESTER : VIII
DEPARTMENT of ZOOLOGY
UNIVERSITY of GUJRAT,
SUB-CAMPUS RAWALPINDI
CONTENTS:
 INTRODUCTION
 BIOINFORMATICS IN PHARMA INDUSTRY
o Identify Target Disease
o Study Interesting Compounds
o Detect the Molecular Bases for Disease
o Rational Drug Design Techniques
o Refinement of Compounds
o Quantitative Structure Activity Relationships (QSAR)
o Solubility of Molecule
o Drug Testing
 DRUG DEVELOPMENT
 FORMULATION DESIGN
 CRYSTALLISATION AND STRUCTURE DETERMINATION
 POLYMER MODELING
 RESEARCH ACHIEVEMENTS
INTRODUCTION:
Bioinformatics is the field of science in which biology, computer science, and information
technology merge to form a single discipline. The ultimate goal of the field is to enable they
discovery of new biological insights as well as to create a global perspective from which
unifying principles in biology can be discerned.
BIOINFORMATICS IN PHARMA INDUSTRY
Bioinformatics provides the computational support for functional genomics which will link
the behavior of cells, organism and population to the information encoded in the genomes, as
well as structural genomics. The utility of bioinformatics lies in the identification of useful
genes leading to the development of new gene products. The subject covers topics such as
protein modeling and sequence alignment, expression data analysis, and comparartive
genomics. It combines algorithmic, statistical and database methods for studying biological
problems also.
The greatest achievement of bioinformatics method is the Human Genome Project. Because
of this the nature and priorities of bioinformatics research and applications are changing.
Many experts believe that this will affect bioinformatics in several ways. For instance some
scientists also believe what some people refer to as research or medical informatics, the
management of all biomedical experimental data associated with particular molecules or
patients – from mass spectroscopy, to in vitro assays to clinical side-effects-move from the
concern of those working in drug company and hospital IT (information technology) into the
mainstream of cell and molecular biology and migrate from the commercial and clinical to
academic sectors.
In order to design a new drug one need to follow the following path.
1. Identify target disease
2. Study Interesting Compounds
3. Detect the Molecular Bases for Disease
4. Rational Drug Design Techniques
5. Refinement of Compounds
6. Quantitative Structure Activity Relationships (QSAR)
7. Solubility of Molecule
8. Drug Testing
Identify Target Disease:-
One needs to know all about the disease and existing or traditional remedies. It is also
important to look at very similar afflictions and their known treatments. Target identification
alone is not sufficient in order to achieve a successful treatment of a disease. A real drug
needs to be developed. This drug must influence the target protein in such a way that it does
not interfere with normal metabolism. Bioinformatics methods have been developed to
virtually screen the target for compounds that bind and inhibit the protein.
Study Interesting Compounds:-
One needs to identify and study the lead compounds that have some activity against a disease.
These may be only marginally useful and may have severe side effects. These compounds
provide a starting point for refinement of the chemical structures.
Detect the Molecular Bases for Disease:-
If it is known that a drug must bind to a particular spot on a particular protein or nucleotide
then a drug can be tailor made to bind at that site. This is often modeled computationally
using any of several different techniques.
Traditionally, the primary way of determining what compounds would be tested
computationally was provided by the researchers' understanding of molecular interactions. A
second method is the brute force testing of large numbers of compounds from a database of
available structures.
Rational drug design techniques:-
These techniques attempt to reproduce to reproduce the researchers understanding of how to
choose likely compounds built into a software package that is capable of modeling a very
large number of compounds in an automated way. Many different algorithms have bee have
been used for this type of testing, many of which were adapted from artificial intelligence
applications.
The complexity of biological systems makes it very difficult to determine the structures of
large bio molecules. 4. Ideally experimentally determined structure is desired, but bio
molecules are very difficult to crystallize.
Refinement of compounds:-
Once you got a number of lead compounds have been found, computational and laboratory
techniques have been very successful in refining the molecular structures to give a greater
drug activity and fewer side effects.
Done both in the laboratory and computationally by examining the molecular structures to
determine which aspects are responsible for both the drug activity and the side effects.
Quantitative Structure Activity Relationships (QSAR):-
Computational technique should be used to detect the functional group in your compound in
order to refine your drug. QSAR consists of computing every possible number that can
describe a molecule then doing an enormous curve fit to find out which aspects of the
molecule correlate well with the drug activity or side effect severity. This information can
then be used to suggest new chemical modifications for synthesis and testing.
Solubility of Molecule:-
One need to check whether the target molecule is water soluble or readily soluble in fatty
tissue will affect what part of the body it becomes concentrated in. The ability to get a drug to
the correct part of the body is an important factor in its potency.
Ideally there is a continual exchange of information between the researchers doing QSAR
studies, synthesis and testing. These techniques are frequently used and often very successful
since they do not rely on knowing the biological basis of the disease which can be very
difficult to determine.
Drug Testing:-
Once a drug has been shown to be effective by an initial assay technique, much more testing
must be done before it can be given to human patients. Animal testing is the primary type of
testing at this stage. Eventually, the compounds, which are deemed suitable at this stage, are
sent on to clinical trials. In the clinical trials, additional side effects may be found and human
dosages are determined.
DRUG DEVELOPMENT
Only 10% of drug molecules identified in research make it through development. This means
that many potential drugs do not make it to market, and expensive time and resources are
invested m molecules that will generate no revenue. Simulation and informatics can
significantly increase these odds by improving the efficiency of drug development, cutting
costs, and improving margins.
FORMULATION DESIGN
Formulation is the process of mixing Ingredients in such a way as to produce a new or
improved product. The formulation department must balance the different marketing and
deliverability requirements with cost and chemical constraints to come up with the best
possible drug delivery method at the best price. With laboratory results stored in legacy
systems, it takes expert company knowledge and experience to know which methods and
suppliers are available, let alone to locate them quickly. In many cases scientists find that it is
easier to repeat an experiment than to find previous results. This situation is compounded in
global R&D set-ups, and after mergers and acquisitions.
CRYSTALLISATION AND STRUCTURE DETERMINATION
Determining the crystal structure of an active compound is one of the first steps in
pharmaceutical development. The crystal structure of a drug affects how easy it is to
formulate, its bio-avail- ability, and its shelf life. Knowledge of the different possible
polymorphs of a crystal can also give better patent protection for a drug.
POLYMER MODELING
Drug delivery is a complex task. The drug must be delivered in a way that transports the
active component intact to the appropriate part of the body. The way the cell takes up the
drug is also very important: drugs that go to parts of the body other than the intended target
are wasted and may lead to unwanted side effects.
Many delivery devices are polymeric with the drug either emulsified in the polymer. Drug
delivery systems have mesoscale structures; between 10 to 1000 nm. The amount of
computing power required to model these systems at an atomistic level is prohibitive, and
macroscale techniques such as Finite element analysis or computational fluid dynamics do
not give the required level of detail. Mesoscale modeling, focusing on the nanometer length
scale, is helping scientists to develop colloidal delivery systems for drugs.
The great advances in human healthcare that are presaged by the Human Genome Project can
be realized by the pharmaceutical industry. A prerequisite for this will be the successful
integration of bioinformatics into most aspects of drug discovery. Although, from a scientific
viewpoint, this is not a difficult problem, there are formidable technological obstacles. Once
these are overcome, rapid progress can be expected.
RESEARCH ACHIEVEMENTS
 Software developed
 Bioinformatics data base developed
 Traditional medicine research tools developed
REFERENCES:
 COLE, N. and BAWDEN, D. (1996), "BIOINFORMATICS IN THE
PHARMACEUTICAL INDUSTRY", Journal of Documentation, Vol. 52 No. 1, pp.
51-68.
 https://biointelligence.wordpress.com/2009/08/11/bioinformatics-in-pharma-industry/
 applications-of-bioinformatics-in-drug-discovery-and-process-1224581485976714-
9.pdf
 https://www.ncbi.nlm.nih.gov/pubmed/8987464

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Bioinformatics role in Pharmaceutical industries

  • 1. ASSIGNMENT NO 1 ROLE OF BIOINFORMATICS IN PHARMACEUTICAL INDUSTRY SUBMITTED BY : MUZNA KASHAF ROLL NUMBER : (16261514-030) SUBMITTED TO : Dr. SOBIA COUSE TITLE : BIOINFORMATICS SEMESTER : VIII DEPARTMENT of ZOOLOGY UNIVERSITY of GUJRAT, SUB-CAMPUS RAWALPINDI
  • 2. CONTENTS:  INTRODUCTION  BIOINFORMATICS IN PHARMA INDUSTRY o Identify Target Disease o Study Interesting Compounds o Detect the Molecular Bases for Disease o Rational Drug Design Techniques o Refinement of Compounds o Quantitative Structure Activity Relationships (QSAR) o Solubility of Molecule o Drug Testing  DRUG DEVELOPMENT  FORMULATION DESIGN  CRYSTALLISATION AND STRUCTURE DETERMINATION  POLYMER MODELING  RESEARCH ACHIEVEMENTS
  • 3. INTRODUCTION: Bioinformatics is the field of science in which biology, computer science, and information technology merge to form a single discipline. The ultimate goal of the field is to enable they discovery of new biological insights as well as to create a global perspective from which unifying principles in biology can be discerned. BIOINFORMATICS IN PHARMA INDUSTRY Bioinformatics provides the computational support for functional genomics which will link the behavior of cells, organism and population to the information encoded in the genomes, as well as structural genomics. The utility of bioinformatics lies in the identification of useful genes leading to the development of new gene products. The subject covers topics such as protein modeling and sequence alignment, expression data analysis, and comparartive genomics. It combines algorithmic, statistical and database methods for studying biological problems also. The greatest achievement of bioinformatics method is the Human Genome Project. Because of this the nature and priorities of bioinformatics research and applications are changing. Many experts believe that this will affect bioinformatics in several ways. For instance some scientists also believe what some people refer to as research or medical informatics, the management of all biomedical experimental data associated with particular molecules or patients – from mass spectroscopy, to in vitro assays to clinical side-effects-move from the concern of those working in drug company and hospital IT (information technology) into the mainstream of cell and molecular biology and migrate from the commercial and clinical to academic sectors. In order to design a new drug one need to follow the following path. 1. Identify target disease 2. Study Interesting Compounds 3. Detect the Molecular Bases for Disease 4. Rational Drug Design Techniques 5. Refinement of Compounds 6. Quantitative Structure Activity Relationships (QSAR) 7. Solubility of Molecule 8. Drug Testing
  • 4. Identify Target Disease:- One needs to know all about the disease and existing or traditional remedies. It is also important to look at very similar afflictions and their known treatments. Target identification alone is not sufficient in order to achieve a successful treatment of a disease. A real drug needs to be developed. This drug must influence the target protein in such a way that it does not interfere with normal metabolism. Bioinformatics methods have been developed to virtually screen the target for compounds that bind and inhibit the protein. Study Interesting Compounds:- One needs to identify and study the lead compounds that have some activity against a disease. These may be only marginally useful and may have severe side effects. These compounds provide a starting point for refinement of the chemical structures. Detect the Molecular Bases for Disease:- If it is known that a drug must bind to a particular spot on a particular protein or nucleotide then a drug can be tailor made to bind at that site. This is often modeled computationally using any of several different techniques. Traditionally, the primary way of determining what compounds would be tested computationally was provided by the researchers' understanding of molecular interactions. A second method is the brute force testing of large numbers of compounds from a database of available structures. Rational drug design techniques:- These techniques attempt to reproduce to reproduce the researchers understanding of how to choose likely compounds built into a software package that is capable of modeling a very large number of compounds in an automated way. Many different algorithms have bee have been used for this type of testing, many of which were adapted from artificial intelligence applications. The complexity of biological systems makes it very difficult to determine the structures of large bio molecules. 4. Ideally experimentally determined structure is desired, but bio molecules are very difficult to crystallize. Refinement of compounds:- Once you got a number of lead compounds have been found, computational and laboratory techniques have been very successful in refining the molecular structures to give a greater drug activity and fewer side effects. Done both in the laboratory and computationally by examining the molecular structures to determine which aspects are responsible for both the drug activity and the side effects.
  • 5. Quantitative Structure Activity Relationships (QSAR):- Computational technique should be used to detect the functional group in your compound in order to refine your drug. QSAR consists of computing every possible number that can describe a molecule then doing an enormous curve fit to find out which aspects of the molecule correlate well with the drug activity or side effect severity. This information can then be used to suggest new chemical modifications for synthesis and testing. Solubility of Molecule:- One need to check whether the target molecule is water soluble or readily soluble in fatty tissue will affect what part of the body it becomes concentrated in. The ability to get a drug to the correct part of the body is an important factor in its potency. Ideally there is a continual exchange of information between the researchers doing QSAR studies, synthesis and testing. These techniques are frequently used and often very successful since they do not rely on knowing the biological basis of the disease which can be very difficult to determine. Drug Testing:- Once a drug has been shown to be effective by an initial assay technique, much more testing must be done before it can be given to human patients. Animal testing is the primary type of testing at this stage. Eventually, the compounds, which are deemed suitable at this stage, are sent on to clinical trials. In the clinical trials, additional side effects may be found and human dosages are determined. DRUG DEVELOPMENT Only 10% of drug molecules identified in research make it through development. This means that many potential drugs do not make it to market, and expensive time and resources are invested m molecules that will generate no revenue. Simulation and informatics can significantly increase these odds by improving the efficiency of drug development, cutting costs, and improving margins. FORMULATION DESIGN Formulation is the process of mixing Ingredients in such a way as to produce a new or improved product. The formulation department must balance the different marketing and deliverability requirements with cost and chemical constraints to come up with the best possible drug delivery method at the best price. With laboratory results stored in legacy systems, it takes expert company knowledge and experience to know which methods and suppliers are available, let alone to locate them quickly. In many cases scientists find that it is
  • 6. easier to repeat an experiment than to find previous results. This situation is compounded in global R&D set-ups, and after mergers and acquisitions. CRYSTALLISATION AND STRUCTURE DETERMINATION Determining the crystal structure of an active compound is one of the first steps in pharmaceutical development. The crystal structure of a drug affects how easy it is to formulate, its bio-avail- ability, and its shelf life. Knowledge of the different possible polymorphs of a crystal can also give better patent protection for a drug. POLYMER MODELING Drug delivery is a complex task. The drug must be delivered in a way that transports the active component intact to the appropriate part of the body. The way the cell takes up the drug is also very important: drugs that go to parts of the body other than the intended target are wasted and may lead to unwanted side effects. Many delivery devices are polymeric with the drug either emulsified in the polymer. Drug delivery systems have mesoscale structures; between 10 to 1000 nm. The amount of computing power required to model these systems at an atomistic level is prohibitive, and macroscale techniques such as Finite element analysis or computational fluid dynamics do not give the required level of detail. Mesoscale modeling, focusing on the nanometer length scale, is helping scientists to develop colloidal delivery systems for drugs. The great advances in human healthcare that are presaged by the Human Genome Project can be realized by the pharmaceutical industry. A prerequisite for this will be the successful integration of bioinformatics into most aspects of drug discovery. Although, from a scientific viewpoint, this is not a difficult problem, there are formidable technological obstacles. Once these are overcome, rapid progress can be expected. RESEARCH ACHIEVEMENTS  Software developed  Bioinformatics data base developed  Traditional medicine research tools developed
  • 7. REFERENCES:  COLE, N. and BAWDEN, D. (1996), "BIOINFORMATICS IN THE PHARMACEUTICAL INDUSTRY", Journal of Documentation, Vol. 52 No. 1, pp. 51-68.  https://biointelligence.wordpress.com/2009/08/11/bioinformatics-in-pharma-industry/  applications-of-bioinformatics-in-drug-discovery-and-process-1224581485976714- 9.pdf  https://www.ncbi.nlm.nih.gov/pubmed/8987464