This document discusses molecular docking, which is a technique used in bioinformatics and drug design to predict how biological molecules, like proteins and ligands, bind to each other. It begins by defining bioinformatics and explaining why molecular docking is important for applications like drug design and signal transduction. The document then discusses key concepts in molecular docking like rigid and flexible docking, different docking software tools, and challenges associated with molecular docking.

1. MOLECULAR DOCKING IN DRUG
DESIGN AND DEVELOPMENT
~ Pranavi Uppuluri

2.  CONTENTS;
1. WHAT IS BIOINFORMATICS ?
2. WHY IT’S NECESARRY ?
3. EXAMPLE OF A TECHNIQUE IN BIOINFORMATICS; MOLECULAR DOCKING
4. UNDERSTANDING THE BASIC TERMINOLOGY MOLECULAR MODELLING, MOLECULAR RECOGNITION,
PROTEIN, LIGANDS, BINDING ENERGY ETC
5. TYPES , MODELS, MECHANISM, BASIC REQUIREMENTS, TOOLS, SIGNIFICANCE AND BASIC
CHALLENGES OF DOCKING
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3.  WHAT IS BIOINFORMATICS ?
The science of collecting and analyzing the complex biological data.
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FIG 1; HUMAN GENOME Pranavi Uppuluri

4.  WHY IT’S NECESSARY ?
To study of large biological data with the help of software’s.
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FIG 2; APPLICATION’S OF BIOINFORMATICS
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5.  WHAT DOES MOLECULAR DOCKING MEANS ????
It is the process that involves placing molecules in appropriate configurations to interact
with a receptor. It is a natural process which occurs within seconds in a cell when bound to
each other to form a stable complex.
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TARGET LIGAND MOLECULAR DOCKING
FIG 3; MOLECULAR DOCKING
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6.  WHY IS DOCKING IMPORTANT???
SIGNAL TRANSDUCTION;
The associations between biologically relevant molecules such as proteins, nucleic acids,
carbohydrates, and lipids play a central role in signal transduction. Furthermore, the
relative orientations of two interacting partners may affect the type of signal produced (eg;
agonism vs antagonism). Docking is useful for predicting both signal strength and type of
signal produced.
DRUG DESIGNING;
Docking is frequently used to predict the binding orientation of a small molecule drug
candidates to their protein targets in order to predict the affinity and activity of the
small molecules. So plays an important role in the rational drug design.
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FIG 4; DOCKING
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7.  UNDERSTANDING THE TERMS MOLECULAR MODELLING AND MOLECULAR RECOGNITION
1. MOLECULAR MODELLING;
It is a technique for deriving, representing and manipulating the structures and reactions of
molecules, and those properties that are dependent on these three-dimensional structures in
molecular modelling.
2. MOLECULAR RECOGNITION;
It is the ability of biomolecules to recognize other biomolecules and selectively interact
with them in order to promote fundamental biological events such as transcription,
translation, signal transduction, transport, regulation, enzymatic catalysis, viral and
bacterial infection and immune response.
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FIG 5; MECHANISM OF MOLECULAR RECOGNITION
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9.  TYPES OF DOCKING;
There are 2 types of docking
1. Rigid docking
2. Flexible docking
1.RIGID DOCKING;
If we assume that the molecules are rigid, then we are looking for a transformation in 3D
space of one of the molecules which brings it to an optimal fit with the other molecules in
terms of a scoring function. Conformation of the ligand may be generated in the absence of
receptor or in the presence of receptor binding activity.
2. FLEXIBLE DOCKING;
We consider molecule flexibility then in addition to transformation, our aim to find the
confirmations of the receptor and the ligand molecules, as they appear in complex.
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FIG 6; RIGID AND FLEXIBLE DOCKING MODELS. FIG 7; COMPARISON OF ENTROPY LOSS DURING LIGAND RECEPTOR
INTERACTIONS IN DEPENDENCE OF RIGIDITY OF THE BACKBONE
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11.  DOCKING CAN BE IN BETWEEN……
1. PROTEIN – LIGAND
2. PROTEIN – PROTEIN
3. PROTEIN - NUCLEOTIDE
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FIG 8; PROTEIN – LIGAND DOCKING
FIG 10; PROTEIN – NUCLEOTIDE DOCKING
FIG 9; PROTEIN – PROTEIN DOCKING
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12.  MOLECULAR DOCKING MODELS
1. THE LOCK AND KEY THEORY;
Proposed by Emil Fischer In 1890.
A substrate fits into the active site of a macromolecule, just like a key fit into a lock.
2. THE INDUCED-FIT THEORY;
Proposed by Daniel Koshland in 1958.
The basic idea is that in the recognition process, both ligand and target, mutually adapt to
each other through small conformational changes, until an optimal fit is achieved.
3. THE CONFORMATION ENSEMBLE MODEL;
A Modification of induced-fit adaptation.
The plasticity of the protein allows it to switch from one state to another as a pre-
existing ensemble of conformational states
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FIG 11; MOLECULAR DOCKING MODELS.
(c) Conformational isomerism model
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14.  BASIC REQUIREMENTS FOR MOLECULAR DOCKING;
1. LIGAND REPRESENTATION;
Typically, the structure most likely to be dominant further adjusted by adding or removing
hydrogens provided approximate pKa values. It is important to make sure that accurate atom
typing occurs.
2. RECEPTOR REPRESENTATION;
The quality of receptor structure employed play’s central role in determining the success of
docking calculations. In general, the higher the resolution of the employed crystal structure
better will be the observed docking results. A recent review for accuracy, limitations and
pitfalls of the structure refinement protocols of protein ligand complexes in general
provided a critical assessment of the available structures.
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15.  MECHANISM OF DOCKING;
1.To perform a docking screen, the first requirement is a structure of the protein of
interest.
2.Usually, the structure has been determined using a biophysical technique such as x-ray
crystallography, or less often, NMR spectroscopy.
3.This protein structure and a database of ligands serve as inputs to a docking program.
4.The success of a docking program depends on two components such as search algorithm and
scoring function.
5. Searching Conformational Space; This space consists of all possible orientations and
conformations of the protein paired with ligand.
6. With present computing resources, it is impossible to exhaustively explore the search
space this would enumerating all possible distortions of each molecule and all possible
rotational and translational orientations of the ligand relative to the protein at a given
level of granularity.
7. Most docking programs in use account for flexible ligand, and several are attempting to
model a flexible protein receptor.
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16. 16
FIG 12; MECHANISM OF DOCKING
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17.  KEY STAGES IN DOCKING;
1. Target/ receptor selection and preparation
2. Ligand selection and preparation
3. Docking
4. Evaluating the docking results
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FIG 13; PROCESS OF DOCKING
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FIG 14; GENERAL WORKFLOW OF MOLECULAR DOCKING CALCULATIONS. THE APPROACHES
NORMALLY START BY OBTAINING 3D STRUCTURES OF TARGET AND LIGANDS. THEN,
PROTONATION STATES AND PARTIAL CHARGES ARE ASSIGNED. IF NOT PREVIOUSLY KNOWN,
THE TARGET BINDING SITE IS DETECTED, OR A BLIND DOCKING SIMULATION MAY BE
PERFORMED. MOLECULAR DOCKING CALCULATIONS ARE CARRIED OUT IN TWO MAIN STEPS:
POSING AND SCORING, THUS GENERATING A RANKED LIST OF POSSIBLE COMPLEXES
BETWEEN TARGET AND LIGANDS.
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19.  THREE COMPONENTS OF DOCKING SOFTWARE;
Docking software can be categorized based on the following criteria:
1. Molecular representation - a way to represent structures and properties (atomic, surface,
grid representation)
2. Scoring method - a method to assess the quality of docked complexes (force field,
knowledge-based approach, ...)
3. Searching algorithm - an efficient search algorithm that decides which poses to generate
(exhaustive search, Monte Carlo, genetic algorithms, simulated annealing, tabu search).
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TOOL TYPE DESCRIPTION IMPORTANCE
AutoDock Open-source
Molecular docking software that uses a Lamarckian
genetic algorithm to explore the binding energies
of different ligand poses within a protein
binding site.
AutoDock is one of the most popular molecular docking tools, due
to its accuracy, speed, and ease of use. It is widely used in drug
discovery research to predict the binding modes and affinities of
small-molecule ligands to proteins.
AutoDock Vina Open-source
An improved version of AutoDock that is faster
and more accurate.
AutoDock Vina is a good choice for virtual screening large
libraries of compounds, as it can quickly and efficiently identify
potential ligands that are likely to bind to a target protein.
Glide Commercial
A molecular docking software suite developed by
Schrödinger that uses a variety of algorithms to
predict the binding modes and affinities of
ligands to proteins.
Glide is a powerful molecular docking tool that is used in many
drug discovery programs. It is known for its accuracy and ability
to handle large and complex molecules.
DOCK Open-source
A molecular docking software suite that uses a
variety of algorithms to predict the binding
modes and affinities of ligands to proteins.
DOCK is a versatile molecular docking tool that can be used for a
variety of applications, including drug discovery, protein design,
and enzyme catalysis.
GOLD Commercial
A molecular docking software suite developed by
Cambridge Crystallographic Data Centre that uses
a genetic algorithm to search for the best
binding pose of a ligand to a protein.
GOLD is a popular molecular docking tool that is known for its
accuracy and ability to handle large and complex molecules. It is
also known for its user-friendly interface and comprehensive
documentation.
FlexX Commercial
A molecular docking software suite developed by
BioSolveIT that uses a fragment-based approach to
predict the binding modes and affinities of
ligands to proteins.
FlexX is a powerful molecular docking tool that is known for its
ability to handle flexible ligands and proteins. It is also known
for its accuracy and speed.
Surflex Commercial
A molecular docking software suite developed by
Molecular Simulations that uses a surface-based
approach to predict the binding modes and
affinities of ligands to proteins.
Surflex is a fast and accurate molecular docking tool that is
well-suited for virtual screening. It is also known for its user-
friendly interface.
TOOLS FOR DOCKING STUDY
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21.  SIGNIFICANT ROLE OF MOLECULAR DOCKING IN DRUG DESIGNING
1. HIT IDENTIFICATION
Quickly screen large databases of potential drugs in silico to identify molecules that are
likely to bind to protein target of interest.
2. LEAD OPTIMIZATION
To predict in where and in which relative orientation a ligand binds to a protein.
It can also be used to design more potent and selective analogs.
3. BIOREMEDIATION
Include;
I. Identification of potential target
II. Screening of potent drugs as activators/inhibitors against certain diseases
III. Designing of novel drugs by lead optimization
IV. Prediction of binding mode and nature of active site
V. Synthesis of chemical compounds with less time consumption.
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22. 
BASIC CHALLENGES IN MOLECULAR DOCKING
1. LIGAND CHEMISTRY;
1.The ligand preparation has prominent effect on the docking results as ligand recognition by
any biomolecule depends on 3-D orientation and electrostatic interaction.
2.By keeping approximate pKa values, the structure being most likely optimized by removing or
adding hydrogens but the tautomeric and protomeric states of the molecules which are to be
docked, still remained a major discrepancy.
3.Since almost all databases keep molecules in their neutral forms but under physiological
conditions they are actually ionized.
4.It is compulsory to ionize molecules prior to docking.
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23.  2. RECEPTOR FLEXIBILITY;
1. This is a major challenge in docking i.e., handling of flexible protein.
2. A biomolecule/protein adopts different conformations depending upon the ligand to which it
binds. This confirms that docking done with a rigid receptor will give a single conformation
of receptor, and with flexible receptor, the ligands may require many receptor conformations
to bind.
3. In this usually the most neglected aspect is different conformational states of proteins.
Since the protein flexibility is important as it accounts for better affinity to be achieved
between a given a drug and target.
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24.  3. SCORING FUNCTION;
1. Just like search algorithm is having potential to give optimum conformation, scoring
function should also be able to differentiate true binding modes from all the other parallel
modes.
2. A potential scoring function would be computationally much economical, unfavorable for
analyzing several binding modes. When there is accuracy, scoring functions make number of
suggestions to evaluate ligand affinity.
3. The physical phenomenon i.e., entropy and electrostatic interactions are disregarded in
scoring schemes. Hence the lack of suitable scoring function, both in terms of accuracy and
speed, is the main congestion in molecular docking programming.
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25.  REFERENCES;
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Journal of Harmonized Research in Pharmacy, 2(4), 215-218.
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26. "In the world of
molecules, docking
is the art of
finding the perfect
partner."
Pranavi Uppuluri