STRUCTURE BASED DRUG DESIGN - MOLECULAR MODELLING AND DRUG DISCOVERY

1. MOLECULAR MODELING AND
DRUG DESIGNING
STRCUTURE BASED DRUG
DESIGN
M.THILAKAR,
LS1154,
4’th M.Sc. LIFE
SCIENCES,
BDU,
TRICHY.

2. ROAD TO NEW DRUGS
BASIC STUDIES PRE
CLINICAL
TRIAL
CLINICA
L TRAIL
REGISTRATIO
N
1-4 YEARS 5-6 YEARS 6-12.5
YEARS
12.5-14
YEARS
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3. ROAD TO NEW DRUGS
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4. STRUCTUAL
BIOINFORMATICS
Structural bioinformatics can facilitate the discovery, design, and
optimization of new chemical entities.
Range from : Drugs and Biological probes to biomaterials, catalysts, and
new macromolecules.
Molecular design is important in fields as diverse as organic chemistry,
physical chemistry, chemical engineering, chemical physics, bioengineering,
and molecular biology.
No single strategy or method has come forward that provides an optimum
solution to the many different challenges involved in designing materials
with new properties
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5. STARTING A STRUCTURE-BASED
DRUG DISCOVERY PROJECT –
GENERAL CONSIDERATIONS
Starts with target identification and verification to obtain a “verified drug
target”.
For structure-based drug design the three-dimensional structure of the
protein needs to be determined.
When identifying a drug target, we first need to answer some general
questions:
DRUG TARGET..??
Does the target protein
belong to a biochemical
pathway
If our aim is to inhibit a
protein belongs to a
pathogen, Are there any
related proteins in the
human host
If the protein is not so
well studied one could
also ask if it is actually
drugable.?
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6. WHY TARGET
IDENTIFICATIONS..????
Helps in mapping available interactions within the active site,
which in turn will help in the next step when new compounds will be
designed.
If there is no three-dimensional structure available for the protein target
one could try to find a structure of a homologous protein,
which may subsequently be used for homology modeling.
A search of sequence databases followed by sequence alignment and
analysis may easily answer questions related to the specificity of a particular
target in a given organism.
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8. STRUCTURE-BASED DESIGN
The first step in structure based drug design is the determination of the 3D
structure of the target macromolecule,
Primarily by X-ray crystallography and NMR spectroscopy or computational
methods such as homology modeling or ab-initio methods
The negative image of the receptor defines the space available for ligand
binding.
There may be many potential binding sites.
The actual binding site can be located by comparison with known protein–
ligand complexes or through homology to related complexes.
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9. SOURCE :
Structural Bioinformatics Edited by Philip E Bourne and Helge Weissig
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10. SITE-DIRECTED LIGAND
GENERATION
Site-directed ligand generation branches into two main approaches:
Docking methods search available databases for matches to an active site,
whereas de novo design seeks to generate new ligands by connecting atoms or
molecular fragments uniquely chosen for a particular receptor.
Docking is the computational equivalent of high-throughput screening.
De novo design can suggest chemically novel ligand classes that are not
limited to previously synthesized compounds .
SITE-DIRECTED
LIGAND
GENERATION
DOCKING
BUILDING
(DE NOVO DESIGN)
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11. DOCKING
The aim of molecular docking is to evaluate the feasible binding
genome tries of a putative ligand with a target whose 3D
structure is known.
The binding geometries, often called binding modes or poses
include both the positioning of the ligand relative to the receptor
(ligand configuration) and the conformational state(s) of the
ligand and the receptor.
Docking methods can therefore be evaluated by their ability to
rapidly and accurately dock large numbers of small molecules
into the binding site of a receptor, allowing for a rank ordering
in terms of strength of interaction with a particular receptor.
Therefore, the essential feature of any treatment of ligand-
receptor interaction is the correct estimation of free energy of
binding.
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12. TASKS OF DOCKING
There are three basic tasks any docking procedure must accomplish:
(1) Characterization of the binding site;
(2) Positioning of the ligand into the binding site (orienting); and
(3) Evaluating the strength of interaction for a specific ligand-receptor complex
(“scoring”).
In order to screen large databases, automated docking is required.
GEOMETRIC SEARCH METHODS : Include systematic search grids as well as descriptor
matching.
ENERGY SEARCH METHODS : Include accomplishes the alignment of the ligands by
minimizing the ligand-receptor interaction energy using Monte Carlo or molecular
dynamics simulations or genetic algorithms
AUTOMATED
SEARCHING METHODS
GEOMETRIC SEARCH
METHOD
ENERGY SEARCH
METHOD
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14. VIRTUAL LIBRARY DESIGN
The advent of combinatorial chemistry has stimulated the development of
computational screening of libraries of compounds that, themselves, might
either be real or assembled on the computer.
It is possible to make many more compounds computationally than can be
synthesized or screened experimentally.
Virtual screening and the use of library design principles are thus being
used to prioritize experimental efforts to make the best use of chemical and
screening resources.
The advantage of virtual screening over random high-throughput
screening is the generation of directed libraries considering molecular
properties that meet criteria required for drug-likeness ADME and exhibit
specificity for the selected target.
The limiting aspect in designing virtual libraries is the synthetic
accessibility of the products by combinatorial library synthesis techniques.3/19/2015 LS1154 - M. THILAKAR 14

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16. SOURCE :
STRUCTURAL BIOINFORMATICS EDITED BY PHILIP E BOURNE AND
HELGE WEISSIG
DE-NOVO
DESIGN
The central concept of de novo
design is the construction of
molecules that have not
necessarily been synthesized
previously.
There are three basic classes of
de novo design methods:
Fragment-positioning methods,
Fragment-connecting methods,
and
Sequential-grow methods.
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17. 1. FRAGMENT PLACEMENT
Instead of completely building up a new ligand, these methods
determine favorable binding positions for single atoms or small
fragments (GRID [Goodford, 1985]; MCSS [Miranker and Karplus, 1991.
The underlying assumption is that a small number of well-placed
fragments will account for significant binding interaction, while the
rest of the molecule serves as a scaffold that links active fragments
together.
The fragments are chosen to capture the basic molecular interactions
such as hydrogen bonding (donor/acceptor) and hydrophobicity, and to
optimally represent the functional groups and structural subunits
present in a larger diverse library.
The placement procedure uses either a molecular mechanics force
field or a rule-based approach derived from an analysis of structural
databases.
Both the fragment connection method and the anchor-and-grow
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18. 2. CONNECTION METHODS
Site point connection methods attempt to place small molecules in the
binding pocket to match site points that provide favorable interactions.
The site points are either derived directly by rules or by previous
fragment placement, as described in fragment placement.
Fragment connection methods retrieve scaffolds from a database in
order to connect isolated fragments by overlaying corresponding bond
vectors.
A suitable linker (rigid or flexible) provides a compatible geometry
for connecting the critical fragments.
In a final step, the linker has to be tested for overlap with the
receptor.
The large number of available programs using connection strategies
reflects the fact that molecular fragments are a standard tool of
chemists.3/19/2015 LS1154 - M. THILAKAR 18

19. 3. SEQUENTIAL GROW
The step-by-step construction of ligand within a binding pocket is another
useful approach for generating new potential leads or optimizing the
functionality of a known inhibitor.
First, a seed atom or fragment is placed in the binding site and then the new
ligand is successively built up by bonding additional structural elements.
Flexibility is introduced by conformational searching and minimization or by
random orientations accepted by Monte Carlo criteria.
The building procedure is guided by scoring the growing ligand at each
step.
The final results often depend on the selection of the initial position.
Since the selection of each added unit is based on its binding score, smaller
binding ligands are generated compared to fragment joining methods.
Another, less obvious, difficulty is the vastness of chemical space compared
with the (relatively) small number of compounds that are feasible from the
standpoint of synthetic chemistry (Clark, Murray, and Li, 1997).3/19/2015 LS1154 - M. THILAKAR 19

20. LIMITATIONS
All the de novo methods face a common set of problems.
Since the overall shape of the generated compounds is imposed by the
binding site, it is not guaranteed that the generated conformations of the
ligands are energetically optimal.
Point charges (used in force fields) are constantly changing during the
building process.
Also, as noted the synthetic accessibility has to be addressed.
Linking methods have not yet been thoroughly explored.
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22. COMPUTER-AIDED DRUG DESIGN
CADD – STRUCTUR BASED DRUG DESIGN
LIGAND-BASED
(ANALOG-BASED) DESIGN
> Relies on a set of known ligands and is
particularly valuable
If no structural information about the receptor is
available.
> Hence, it is generally applicable to all classes of
drugs.
TARGET-BASED
(RECEPTOR-BASED) DESIGN
> Usually starts with the structure of a receptor
site.
Such as the active site in a protein
> This structure can be generated from direct
experimentation or can be deduced from
experimental structures through homology
modeling.
(Al-Lazikani et al., 2001).
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23. LIGAND-BASED DESIGN
Based on the known Ligands and their structural activity.
It is necessary to have experimental affinities and molecular properties
of a set of active compounds, for which the chemical structures are
known.
ANALOG BASED DRUG
DESIGN
PHARMACOPHORE
MAPS
QUANTITATIVE
STRUCTURE-ACTIVITY
RELATIONSHIPS (QSAR)
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24. LIGAND-BASED DRUG
DESIGNVIRTUAL
SCREENING
•2D, 3D and QSAR
method.
DE NOVO DRUG
DESIGN
• MODELS :
Simulations and
Knowledge based
modelling
• CONSTRUCTION OF
ALGORITHMS : Incremental3/19/2015 LS1154 - M. THILAKAR 24

25. 2D STRUCTURE MATCHING
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26. 2D SUB - STRUCTURE MATCHING
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27. 3D STRUCTURE MATCHING
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29. FRONT PAGE OF
MOLECULAR
ENVIRONMENT3/19/2015 LS1154 - M. THILAKAR 29

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32. IDENTIFYING THE TARGET
AND DOCKING
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36. HOW TO DRAW DRUG IN
CHEMDRAW
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38. DOCKING WITH OUR NEW
DRUG
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42. LIGAND INTERACTIONS
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48. REFERENCES
 Structural Bioinformatics Edited by Philip E Bourne and Helge Weissig Pg :
441-497
Structure-Based Drug Design: Docking and Scoring by Romano T. Kroemer
Current Protein and Peptide Science, 2007, 8, 312-328
Virtual screening and molecular docking by Dr. Sander B Nabruus, Centre for
Molecular and Biomolecular informatics, Radboud university.
Introduction to structure based drug design - A practical guide by Tara
phillips, Christophe lmj verlinde and Wim Gj HOL Structure 15 July
1994, 2:577-587.
Structure-Based Drug Design By Thomas Funkhouser, Princeton University
CS597A, Fall 2005
From laptop to benchtop to bedside: Structure-based Drug Design on
Protein Targets Lu Chen et al., Curr Pharm Des . 2012 ; 18(9): 1217–1239.
http://www.proteinstructures.com/SBDD/structure-drug.html
http://publications.nigms.nih.gov/structlife/chapter4.html
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