Informatics & Methods in drug design

Informatics & Methods
in Drug Design
Abhijit Debnath
Asst. Professor
NIET, Pharmacy Institute
Greater Noida
Unit: 4
Course Details
(B Pharm 8th Sem)
Abhijit Debnath | BP807ET-CADD | Unit-4
Tuesday, July 20, 2021 1
Noida Institute of Engineering and Technology
(Pharmacy Institute) Greater Noida
Subject Name: CADD (Elective)
(BP 807 ET)

SYLLABUS

• Introduction to Bioinformatics, chemoinformatics.
• ADME databases, chemical, biochemical and pharmaceutical databases.
CONTENT

Objectives: Upon completion of the subject student shall be able to;
1. Bioinformatics,
2. Chemoinformatics
3. ADME databases, chemical, biochemical and pharmaceutical databases
COURSE OBJECTIVE

CO Statement Domain Bloom’s level
CO4.1 Applying the Bioinformatics, in Drug Discovery. Cognitive L3
CO4.2 Applying the chemoinformatics in Drug Discovery. Cognitive L3
CO4.3 Applying the ADME in Drug Discovery. Cognitive L3
• After completion of this unit it is expected that students will
be able to
COURSE OUTCOME (CO)

PO 1 Pharmacy Knowledge
PO 2 Planning Abilities
PO 3 Problem analysis
PO 4 Modern tool usage
PO 5 Leadership skills
PO 6 Professional Identity
PO 7 Pharmaceutical Ethics
PO 8 Communication
PO 9 The Pharmacist and
society
PO 10 Environment and
sustainability
PO 11 Life-long learning
PROGRAMME OUTCOMES (POs)

Cos PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11
CO4.1 3 3 3 2 3 3 3 2 3 2 3
CO4.2 3 3 3 2 3 3 3 2 3 2 3
CO4.3 3 3 3 2 3 3 3 2 3 2 3
CO-PO MAPPING

• Learning the basics of ADME, Bioinformatics and Chemoinformatic to
Optimize Drug Design Process.
Topic Objective mapping with CO
TOPIC OBJECTIVE

Unit Topics Mapping with
CO4.1
Informatics & Methods in
drug design
Application of Bioinformatics in Drug Discovery 3
• After completion of this unit it is expected that students will be able to
TOPIC OBJECTIVE MAPPING WITH CO

CO4.2
drug design
Chemoinformatics in Drug Discovery 3

CO4.3
drug design
ADME in Lead Optimization 3

• Students must have basic knowledge of Biochemistry and Medicinal Chemistry
• Students must have basic knowledge of Drug Discovery, Pharmacology.
• Students must have basic knowledge of ADME.
PREREQUISITE AND RECAP

Bioinformatics CO4.1

Bioinformatics
 Introduction to Bioinformatics
 Bioinformatics Tools
 Genome Sequence Analysis
 Proteomics & Protein’s 3D Structure Prediction
 Drug Design
 Virtual High-Throughput Screening (VHTS)
 Research Achievements
CO4.1

 Application of CS and informatics to biological and
Drug Development science
 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 the
discovery of new biological insights as well as to
create a global perspective from which unifying
principles in biology can be discerned
Introduction to Bioinformatics
CO4.1

Bioinformatics Tools
The processes of designing a new drug using bioinformatics tools have open a new area of research. However,
computational techniques assist one in searching drug target and in designing drug in silco, but it takes long time and money. In
order to design a new drug one need to follow the following path.
1. Identify target disease
2. Study Interesting Compounds
3. Detection 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
CO4.1

1. 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.
CO1
CO4.1

2. 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.
CO1
CO4.1

3. Detection 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.
CO1
CO4.1

4. Rational Drug Design Techniques
 These techniques attempt 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 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
biomolecules.
 Ideally experimentally determined (x-ray or NMR) structure is desired, but biomolecules are very
difficult to crystallize.
CO1
CO4.1

5. 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.
CO1
CO4.1

6. 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.
CO1
CO4.1

7. 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.
CO1
CO4.1

8. 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.
CO1
CO4.1

 In CADD research, one often knows the genetic sequence of multiple organisms or the
amino acid sequence of proteins from several species.
 It is very useful to determine how similar or dissimilar the organisms are based on gene or
protein sequences.
 With this information one can infer the evolutionary relationships of the organisms, search for
similar sequences in bioinformatic databases and find related species to those under
investigation.
4. There are many bioinformatic sequence analysis tools that can be used to determine the
level of sequence similarity.
Genome Sequence Analysis
CO1
CO4.1

Proteomics & Protein’s 3D Structure Prediction
CO1
CO4.1

 Another common challenge in CADD research is determining the 3-D structure of proteins.
 Most drug targets are proteins, so it's important toknow their 3-D structure in detail. It's estimated that
the human body has 500,000 to 1 million proteins.
 However, the 3-D structure is known for only a small fraction of these. Homology modeling is one
method used to predict 3-D structure.
 In homology modeling, the amino acid sequence of a specific protein (target) is known, and the 3-D
structures of proteins related to the target (templates) are known.
 Bioinformatics software tools are then used to predict the 3-D structure of the target based on the known
3-D structures of the templates.
 MODELLER is a well-known tool in homology modeling, and the SWISS-MODEL Repository is a
database of protein structures created with homology modeling.
Proteomics & Protein’s 3D Structure Prediction
Homology Modelling
CO1
CO4.1

Drug Design
CO1
CO4.1
• Computer-Aided Drug Design (CADD) is a specialized discipline
that uses computational methods to simulate drug-receptor
interactions.
• CADD methods are heavily dependent on bioinformatics tools,
applications and databases. As such, there is considerable overlap
in CADD research and bioinformatics.

 Pharmaceutical companies are always searching for new leads to develop into drug compounds.
 One search method is virtual high-throughput screening. In vHTS, protein targets are screened against databases of small-
molecule compounds to see which molecules bind strongly to the target.
Virtual High-Throughput Screening (VHTS)
 If there is a "hit" with a particular compound, it can be extracted from the database for further
testing.
 With today's computational resources, several million compounds can be screened in a few
days on sufficiently large clustered computers.
 Pursuing a handful of promising leads for further development can save researchers
considerable time and expense.
e.g.. ZINC is a good example of a VHTS compound library.
CO1
CO4.1

Applied Areas
CO1
CO4.1

Research Achievements
CO1
CO4.1

CO1
CO4.1
 Software developed
1. SVMProt: Protein function prediction software
http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi
2. INVDOCK: Drug target prediction software
3. MoViES: Molecular vibrations evaluation server
http://ang.cz3.nus.edu.sg/cgi-bin/prog/norm.pl

CO1
CO4.1
 Bioinformatics database developed
1. Therapeutic target database
http://xin.cz3.nus.edu.sg/group/cjttd/ttd.asp
2. Drug adverse reaction target database
http://xin.cz3.nus.edu.sg/group/drt/dart.asp
3. Drug ADME associated protein database
http://xin.cz3.nus.edu.sg/group/admeap/admeap.asp
4. Kinetic data of biomolecular interactions database
http://xin.cz3.nus.edu.sg/group/kdbi.asp
5. Computed ligand binding energy database
http://xin.cz3.nus.edu.sg/group/CLIBE/CLIBE.asp

CO1
CO4.1
 Traditional medicine research tools developed
1. Traditional medicine information database
2. Herbal ingredient and content database
3. Natural product effect and consumption info system
4. Traditional medicine recipe prediction and validation system
5. Herbal target identification system

Cheminformatics CO2

Cheminformatics
 What is cheminformatics?
 Basic of cheminformatics
 Why Cheminformatics?
 Recent developments
 Scope in Cheminformatics
 Evolution of Cheminformatics
 Chemical Information System(CIS)
 Milestones in Cheminformatics
 Definitions of Chemoinformatics
 QSAR
 From cheminformatics to combichem.
 History of chemical information science
 Societies, Conferences and Journals
CO2

Cheminformatics
CO2
CO4.2

What is cheminformatics?
The most accepted definitions of Cheminformatics are…
• 1. “Cheminformatics is the combinationation of chemical synthesis , biological screening
and data mining approaches used to guide drug discovery and development.”
• “C I is the use of computer software to assist in the acquisition , analysis and management of
data and information relating to chemical compounds and their properties.”
• CI applies IT to chemical data and includes topics such as chemical databases, combinatorial
library design, structure-activity relationships and structure based drug design .
• The CI offer programs and databases(mainly for organic and sometimes for inorganic
applications) related to small molecules, complementing the activities of the bioinformatics
group who concentrate on biological macromolecules
CO2
CO4.2

 Like bioinformatics, CI is still being defined. In BI computers are used to
store, retrieve and assist in understanding biological information, CI is
the organization of chemical data in a logical form to facilitate the
process of understanding and making inferences. Instead of a text-based
retrieval system, CI uses chemical structure that researchers provide as
input to identify similar compounds that might be screened for biological
activity.
 BI deals with large molecules such as proteins and CI deals with small
molecules that are sythesized in chemical processes says Phil Mchale
vice president for product marketing at MDL Information System.
Basic of cheminformatics
CO2
CO4.2

The various companies engaged in making use of CI are
• MDL is a CI company that enables its customers to store, retrieve, analyze and make decision based on
chemical structures. Also it links BI and CI world.
• Tripos also a CI company focusing mainly on chemical information and chemical properties for compounds
involved in the early drug discovery stages.
CO2
CO4.2

The various companies engaged in making use of CI are …
 Pharmacopeia is a software company which includes a BI arm, Genetics computer group as well as molecular
simulations, Synopsys scientific systems and oxford molecular group . The last two business form the CI part of
pharmacopeia.
 Chem Navigator has developed an application that allows researchers to submit a precise structure for comparison
with more than one million compounds in its library.
 At chem navigator website, commercially available compounds can be identified , purchased and delivered to the
researcher promptly and efficiently.
 Anadys pharmaceuticals is a drug discovery company using CI for linking chemistry and biology.
CO2
CO4.2

• The effective management of information is increasingly recognized by both public
and private sector organizations of all sorts.
• In chemistry, information systems have long played a vital role in pharmaceuticals ,
agro chemical and biotechnological research and where there is a need to handle
not only information in traditional, textual and numeric databases, but also
databases containing information about 2D and 3D structure of molecules.
Why Cheminformatics?
CO2
CO4.2

Recent developments
• Computational chemistry
• Modern combinatorial chemistry
• Drug design and discovery
• Data sequence, mining and visualisation
• Chemical database design and their management
• Chemical information sources
• Medicinal chemistry etc.,has resulted in the emergence of the discipline of CI, which
involves the creation, retrieval, organization, dissemination and processing of
chemical information .
CO2
CO4.2

Scope in Cheminformatics
 CI is the latest area is now becoming a reality in India too
 Till data advance countries like US, UK, Japan and few European countries were working on this .
 In India CI is making inroad in Indian software, Department of Bio-Tech Govt of India , R& D organizations
pharmaceuticals and other industries too.
 With thousands of jobs and crores of grants by Govt of India, CI professionals are growing day by day not
only in India but also in abroad .
 CI companies are in great need of people with knowledge of chemistry and computer skills to handle the
data generated by chemical researchers.
CO2
CO4.2

Evolution of Cheminformatics
Chemical Information ( 18th century-1960)
Chemoinformatics (1961-2000)
Cheminformatics (2000-prsent)
CO2
CO4.2
• All these terms basically mean the same thing and the use of information technology and management for the
process of drug discovery.
• Chemical information employs chemical structures, data storage and computational methods .
e.g compound registration databases , on-line chemical literature, SAR analysis (structure activity relationship) and
molecule- property calculation.

Chemical Information System(CIS)
• The main purpose of this is to identify a chemical substance, find compounds
similar to the target compounds and demine the location of the compound,
and it is an inventory system.
• Chemical similarity searching databases by chemical similarities is among
the oldest and most useful techniques in molecular modeling as practiced by
the pharmaceutical industry. It works because it is generally true that
molecules with similar structure have similar biological activities
CO2
CO4.2

Chemical Information System(CIS)…
The chemical information systems and services have been established for many years
(i) Justus Liebig in 1832 founded Annalender pharmacie
(ii) Chemical abstarct was started in 1907
(iii) First compuetr-based system was established over 40 years ago
CO2
CO4.2

Milestones in Cheminformatics
(i) Identification of a user-defined structural pattern in a database structure.
(ii) Use of graph -searching Algorithm.
(iii) For the storage and retrieval of 2D chemical structure .(later, 3D also)
CO2
CO4.2

• The first journal for the subject , Journal of chemical documentation started in 1961.
• The name changed to Journal of chemical information and computer science in 1975.
• The first book computer handling of chemical structure information appeared on this subject in 1971
• The first international conference on this subject was held in 1973 at Noordwijkerhout and every three years since
1987.
• The use of information technology management has become a critical part of the drug discovery process”
• Chemoinformatics is the mixing of those information resources to transform data into information and information
into knowledge for the intended purpose of making better decisions faster in the area of lead identification and
organist ion ” F.K Brown (1998)
• (It deals with the mixing of IT and management to tranform data….)
Milestones in Cheminformatics
CO2
CO4.2
CO4.2
CO4.2
CO4.2

Definitions of Chemoinformatics
 In cheminformatics there are only two primary questions
i. What to test next ? and
ii. What to make next?
 The main processes within drug discovery are lead identification where lead is
something that has activity in the low micro molecular range and lead
optimization, which is the process of transforming a lead into a drug candidate.
 “Chemoinformatics is a generic term that encompasses the design , creation,
organization, management, retrieval, analysis ,dissemination, visualization and
use of chemical information”
 Development of effective and efficient tools that can exploit the chemical and
biological explosion.
CO2
CO4.2

QSAR: Quantitative Structure Activity Relationship
• QSAR – are mathematical relationship linking chemical structure and pharmacological activity in a
quantitative manner for a series of compounds , methods, which can be used in QSAR include various
regression and pattern recognition techniques.
(i) 2D Structure Searching (ii) 3D Structure Searching
(iii) 2D Similarity Searching (iv) Current interest in 3D similarity measures
CO2
CO4.2

From cheminformatics to Combinatorial Chemistry
 The drive in pharmaceutical currently and most currently in the decades to come, is the human genome project (HGP).
The information stored in our three billion base pairs is a “gold mine” for new molecular targets to treat diseases with
huge unmark therapeutic need. eg., AIDS and Cancer
 Millions of gene sequences will translate into thousands of high throughput screens (HTS). Thousands of HTS will require
millions of new chemicals. Millions of new chemicals will require millions of input regarding structure, purity, diversity, etc.
 There is no way the technology currently available in the industry can cope with these numbers. With the advent of
combinatorial chemistry (combichem) there is a high demand for synthetic chemists as well as combichem and chemical
information scientists.
CO2
CO4.2

History of chemical information science
 Chemical information has been collected and indexed for more than 100 years now, for most of the time in the
form of books and journals.
 The printed materials (costly and time consuming) .
 Books also go missing and journals spend time at the binders
 Since people are at the mercy of whatever index is available and searching in time consuming
 Photocopy of the printed page – word processors (or) computer program
 Chemistry material started appearing “on-line” form 1982
 In 1995, the world wide web started emerging
 The oldest means of communication with talks and demonstration remains important till the date.
CO2
CO4.2

History of chemical information science
 The royal society and other academies had formalized many scientists communicate their results to one another
by private letters (or) through scientific correspondents. The royal society published ‘Philosophical Transactions’
giving birth to the scientific paper.
CO2
CO4.2

• 1778: Chemisches Journal is thought to be the first chem. Journal. Lornez Von Crell established and published it
from 1778 to 1784. It was renamed as Chemisches Annalen and published from 1784 to 1803.
• 1789: Antoine Laurent Lavoisier et al established Annales de chimie.
• 1832: Annalen der Pharmacie – changed the name to Justus Liebigs Annalen der chemie and then to European
Journal of Organic Chemistry.
• 1841: The chemical society of London was established.
• 1847: Quarterly Journal of the chemical society of Londen (later Journal of the chemical society) was first
published in 1871. It began including abstract of the chemical literature.
• 1848: The American Association of Advancement of Science (AAAS) was founded (a sec devoted to chem).
• 1857: The Societe Chemique de Paris…
Societies, Conferences and Journals
CO2
CO4.2

ADME DatabasesCO4.3

ADME Databases
 What is ADME
 Various ADME Databases
CO4.3

ADME CO3
CO4.3

ADME Databases CO3
CO4.3
The molecular property prediction flow chart.
Orange dash arrows depict representations
with information loss. Blue solid arrows
represent the mathematical transformation
without information loss. Yellow
arrowsrepresent the learning process.
Starting from the upper left, a molecule is
composed of a group of atoms held together
by chemical bonds in 3D space. Analytical
chemistry techniques can be used to identify
the composition of atoms and bonds in a
molecule. A typical way of representing
molecules is through a 2D molecular graph,
aka, molecular structure.

 PACT-F. (Preclinical And Clinical Trials Knowledge Base on Bioavailability). Preclinical And Clinical Trials Knowledge Base
on Bioavailability (PACT-F).
 TOXNET. Databases on toxicology, hazardous chemicals, environmental health, and toxic releases that can be accessed
using a common search interface. provided by the Unied States NLM.
 Leadscope Toxicity Database. Database of 160,000 chemical structures with toxicity data. Distributed by Leadscope.
 WOMBAT-PK. Database for Clinical Pharmacokinetics and Drug Target Information. WOMBAT-PK contains 1260 entries
(1260 unique SMILES), totaling over 9,450 clinical pharmacokinetic measurements;
ADME Databases CO3
CO4.3

 Cloe Knowledge. Open Access ADME/PK Database for a range of marketed drugs. Maintained by Cyprotex.
 PHYSPROP. The Physical Properties Database (PHYSPROP) contains chemical structures, names, and physical
properties for over 41,000 chemicals.
 SIDER. Contains information on marketed medicines and their recorded adverse drug reactions. The
information is extracted from public documents and package inserts.
ADME Databases CO3
CO4.3

 admetSAR. admetSAR provides the manually curated data for diverse chemicals associated with known Absorption, Distribution,
Metabolism, Excretion and Toxicity profiles.
 The ADME databases. Databases for benchmarking the results of experiments, validating the accuracy of existing ADME predictive models,
and building new predictive models.
 The ADME database. Provides comprehensive data for structurally diverse compounds associated with known ADME properties, including
human oral bioavailability, enzymes metabolism, inhibition and induction, transport, plasma protein binding and bloodbrain barrier.
Distributed by Aureus.
 UCSF-FDA Transportal. The purpose of this database is to be a useful repository of information on transporters important in the drug
discovery process as a part of the US Food and Drug Administration-led Critical Path Initiative.
ADME Databases CO3
CO4.3

 SuperTarget Database. Database of about 332828 drug-target relations.
 DART. (Drug Adverse Reaction Target). A database for facilitating the search for drug adverse reaction target. It
contains information about known drug adverse rection targets,
 DITOP. (Drug-Induced Toxicity Related Proteins). Database of proteins that mediate toxicities through their
interaction with drugs or reactive metabolites. .
 ADMEAP. A database for facilitating the search for drug Absorption, Distribution, Metabolism, Excretion associated
proteins. It contains information about known drug ADME associated proteins, functions, similarities, substrates /
ADME Databases CO3
CO4.3

 SIDER. (Side Effect Resource). contains information on marketed medicines and their recorded adverse drug reactions. The information is extracted from
public documents and package inserts.
 SAR Genetox Database. Genetic toxicity database to be used as a resource for developing predictive modeling training sets. Distributed by Leadscope.
 SAR Carcinogenicity Database. Carcinogenicity database with validated structures to be used as a resource for preparing training sets. Distributed by
Leadscope.
 HMDB. The Human Metabolome Database (HMDB) is a freely available electronic database containing detailed information about small molecule
metabolites found in the human body. The database contains chemical data, clinical data, and molecular biology/biochemistry data.
 t3db. (Toxin and Toxin Target Database). Combines detailed toxin data with comprehensive toxin target information. The database currently houses over
2900 toxins described by over 34 200 synonyms, including pollutants, pesticides, drugs, and food toxins, which are linked to over 1300 corresponding toxin
target records.
ADME Databases CO3
CO4.3

 SuperToxic. Collection of toxic compounds from literature and web sources. The current version of this database compiles approx. 60,000
compounds with about 100,000 synonyms.
 SuperHapten. Comprehensive database for small immunogenic compounds. Contains currently 7257 haptens, 453 commercially available
related antibodies and 24 carriers
 HaptenDB. Database of about 1087 haptens that includes common and chemical name of Hapten, molecular mass, physical and chemical
properties, biological importance and the structure. Provided by the Institute of Microbial Technology, India.
 SuperCyp. Comprehensive database on Cytochrome P450 enzymes including a tool for analysis of CYP-drug interactions. Provided by Charité
Berlin, Structural Bioinformatics Group.
 PROMISCUOUS. Exhaustive resource of protein-protein and drug-protein interactions with the aim of providing a uniform data set for drug
repositioning and further analysis
ADME Databases CO3
CO4.3

Youtube /other Video Links
https://www.youtube.com/watch?v=-k8msfqMI6Y
https://www.youtube.com/watch?v=3Tvdf2AUekg
https://www.youtube.com/watch?v=tCEQesj50gg
Faculty Video Links/ Youtube & NPTEL Video Links and Online
Courses Details (if any)

Summary
Many of the drug molecules actually failed to come to the market due to low ADME and Toxicity. So it is
necessary to identify the ADME. Bioinformatics can play a big role in identifying the ADME and toxicity
of a drug molecule.

DAILY QUIZ
Q.1. Which of the following is an example of Homology and similarity tool?
(a) BLAST
(b) RasMol
(c) EMBOSS
(d) PROSPECT
Q.2. In which year did the SWISSPROT protein sequence database begin?
(a) 1988
(b) 1985
(c) 1986
(d) 1987
Q.3. Which of the following scientists created the first Bioinformatics database?
(a) Dayhoff
(b) Pearson
(c) Richard Durbin
(d) Michael.J.Dunn

DAILY QUIZ
Q.4. The human genome contains approximately__________.
(a) 6 billion base pairs
(b) 5 billion base pairs
(c) 3 billion base pairs
(d) 4 billion base pairs
Q.5. Which of the following tools is used for the identification of motifs?
(a) BLAST
(b) COPIA
(c) PROSPECT
(d) Pattern hunter
Q.6. The first molecular biology server expasy was in the year __________.
(a) 1992
(b) 1993
(c) 1994
(d) 1995

DAILY QUIZ
Q.7. What is the deposition of cDNA into the inert structure called?
(a) DNA probes
(b) DNA polymerase
(c) DNA microarrays
(d) DNA fingerprinting
Q.8. The identification of drugs through the genomic study is called__________.
(a) Genomics
(b) Pharmacogenomics
(c) Pharmacogenetics
(d) Cheminformatics

DAILY QUIZ
Q.9. Which of the following compounds has desirable properties to become a drug?
(a) Fit drug
(b) Lead
(c) Fit compound
(d) All of the above
Q.10. Proteomics refers to the study of __________.
(a) Set of proteins in a specific region of the cell
(b) Biomolecules
(c) Set of proteins
(d) The entire set of expressed proteins in the cell
Q.9. Which of the following compounds has desirable properties to become a drug?
(a) Fit drug
(b) Lead
(c) Fit compound

DAILY QUIZ
Q.10. Proteomics refers to the study of __________.
(a) Set of proteins in a specific region of the cell
(b) Biomolecules
(c) Set of proteins
(d) The entire set of expressed proteins in the cell

WEEKLY ASSIGNMENT
Q.1. What is ADME
Q.2. Differentiate between Bioinformatics and Pharmacoinformatics
Q.3 What is chemoinformatics..
Q.4. Write various ADME databases?
Q.5. Write various chemical databases?
Q.6. Write various biochemical databases?
Q.7. Write various pharmaceutical databases?
Q.8. What are the differences between Database and webserver
Q.9 Discuss the various cases of Drug Discovery
Q.10 Write the advantages of Informatics in Drug Discovery

MCQ s
Q.1. The process of finding the relative location of genes on a chromosome is called __________.
(a) Gene tracking
(b) Genome walking
(c) Genome mapping
(d) Chromosome walking
Q.2. The computational methodology that tries to find the best matching between two molecules, a receptor and
ligand are called __________.
(a) Molecular fitting
(b) Molecular matching
(c) Molecular docking
(d) Molecule affinity checking
Q.3. Which of the following are not the application of bioinformatics?
(a) Drug designing
(b) Data storage and management
(c) Understand the relationships between organisms
(d) None of the above

MCQ s
Q.4. The term “invitro” is the Latin word which refers to__________.
(a) Within the lab
(b) Within the glass
(c) Outside the lab
(d) Outside the glass
Q.5. The stepwise method for solving problems in computer science is called__________.
(a) Flowchart
(b) Algorithm
(c) Procedure
(d) Sequential design
Q.6. The term Bioinformatics was coined by __________.
(a) J.D Watson
(b) Pauline Hogeweg
(c) Margaret Dayhoff
(d) Frederic Sanger

MCQ s
Q.7. The laboratory work using computers and associated with web-based analysis generally online is referred to as
__________.
(a) In silico
(b) Dry lab
(c) Wet lab
Q.8. Which of the following is the first completed and published gene sequence?
(a) ΦX174
(b) T4 phage
(c) M13 phage
(d) Lambda phage
Q.9. The laboratory work using computers and computer-generated models generally offline is referred to as
__________.
(a) Insilico
(b) Wet lab
(c) Dry lab

MCQ s
Q.10. The computer simulation refers to __________.
(a) Dry lab
(b) Invitro
(c) In silico
(d) Wet lab

EXPECTED QUESTIONS FOR UNIVERSITY EXAM #
.
Q.1. Write the application Informatics Methods in drug design.
Q.2. Write the differences between Pharmacoinformatics & chemoinformatics
Q.3. What is Bioavailability, Solubility, Permeability? How do you will calculate by using computer.
Q.4. Write the applications of Bioinformatics in Drug Discovery
Q.5. Describe the importance of ADME in Drug Discovery

PREVIOUS YEAR QUESTION PAPER
Thursday, May 13, 2021 Abhijit Debnath | BP807ET-CADD | Unit-1 80

REFERENCES AND BOOKS TO BE FOLLOWED
• Delgado JN, Remers WA eds “Wilson & Gisvold’s Text Book of Organic Medicinal & Pharmaceutical Chemistry”
Lippincott, New York.
• Foye WO “Principles of Medicinal chemistry ‘Lea & Febiger.
• Koro lkovas A, Burckhalter JH. “Essentials of Medicinal Chemistry” Wiley Interscience.
• Wolf ME, ed “The Basis of Medicinal Chemistry, Burger’s Medicinal Chemistry” John Wiley & Sons, New York.

Informatics & Methods in drug design

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