Chemicals used in synthesis:
5.1.1 Active ingredients:-
Di methyl 3 oxoglutatrate, Malononitrile, Sulphur, Methyl bromo acetate, Strontium Hydroxide.
5.1.2 Catalysts:-
Cetrimide, Tri ethyl amine.
5.1.3 Bases:-
Tri ethyl amine, Potassium Carbonate, Lye solution.
5.1.4 Solvents:-
Methanol, Toluene, Acetonitrile, con HCl, Iso propyl alcohol, Distilled Water, De mineralized
water.
5.1.5 Miscellaneous:-
Activated Carbon, Nitrogen Gas.
5.2 Glassware used in this work:
Single neck round bottom flask, triple neck round bottom flask, Four necks round bottom flask,
Pipette, Stirrer rod, TLC Chamber, Test tubes, Capillary tubes, Condenser, Beaker, Iodine
Chamber etc…
5.3 Instruments used in this work:
Stirrer, Condensing Chamber, HPLC, Analytical Balance, Electrical Balance, Agitator,
Distillation apparatus, Hot air oven, Melting Range apparatus, Moisture Content Apparatus.
5.3.1 HPLC:
High performance liquid chromatography is basically a highly improved form of
column chromatography. Instead of a solvent being allowed to drip through a column under
gravity, it is forced through under high pressures of up to 400 atmospheres. That makes it much
faster. It also allows you to use a very much smaller particle size for the column packing material
which gives a much greater surface area for interactions between the stationary phase and the
molecules flowing past it. This allows a much better separation of the components of the
mixture. The other major improvement over column chromatography concerns the detection
methods which can be used. These methods are highly automated and extremely sensitive.
5.3.4 FTIR:
FTIR is most useful for identifying chemicals that are either organic or inorganic. It can
be utilized to quantitate some components of an unknown mixture. It can be applied to the
analysis of solids, liquids, and gasses. The term Fourier Transform Infrared Spectroscopy (FTIR)
refers to a fairly recent development in the manner in which the data is collected and converted
from an interference pattern to a spectrum. Today's FTIR instruments are computerized which
makes them faster and more sensitive than the older dispersive instruments.
5.3.3 Mass Spectrometry:
In order to measure the characteristics of individual molecules, a mass spectrometer
converts them to ions so that they can be moved about and manipulated by external electric and
magnetic fields. The three essential functions of a mass spectrometer, and the associated
components, are
The Ion Source:
A small sample is ionized, usually to cations by loss of an electron.
The Mass Analyzer:
The ions are sorted and separated according to their mass and charge.
The Detector:
The separated ions are then measured, and the results displayed on a chart.
5.4 Miscellaneous Apparatus:-
Buckner funnel, Water bath, Ice bath, Watt Mann Filter papers, Trace papers, Glass Funnel,
Stand, Spatula etc…
5.5 DATABASES:
5.5.1 NCBI: -
The National Center for Biotechnology Information (NCBI) is part of the United States National
Library of Medicine (NLM), a branch of the National Institutes of Health. The NCBI is located
in Bethesda, Maryland (38°59′42″N 77°05′58″W) and was founded in 1988 through legislation
sponsored by Senator Claude Pepper. The NCBI houses genome sequencing data in GenBank
and an index of biomedical research articles in PubMed Central and PubMed, as well as other
information relevant to biotechnology. All these databases are available online through the
Entrez search engine. NCBI is directed by David Lipman, one of the original authors of the
BLAST sequence alignment program and a widely respected figure in Bioinformatics. He also
leads an intramural research program, including groups led by Stephen Altschul (another BLAST
co-author), David Landsman, and Eugene Koonin (aprolific author on comparative genomics).
5.5.2 GenBank
The NCBI has had responsibility for making available the GenBank DNA sequence database
[a]
since 1992. GenBank co ordinates with individual laboratories and other sequence databases
such as those of the European Molecular Biology Laboratory (EMBL) and the DNA Data Bank
[b]
of Japan (DDBJ). Since 1992, NCBI has grown to provide other databases in addition to
GenBank. NCBI provides Online Mendelian Inheritance in Man, the Molecular Modeling
Database (3D protein structures), dbSNP a database of single-nucleotide polymorphisms, the
Unique Human Gene Sequence Collection, a Gene Map of the human genome, a Taxonomy
Browser, and coordinates with the National Cancer Institute to provide the Cancer Genome
Anatomy Project. The NCBI assigns a unique identifier (Taxonomy ID number) to each species
of organism. The NCBI has software tools that are available by WWW browsing or by FTP. For
example, BLAST is a sequence similarity searching program. BLAST can do sequence
comparisons against the GenBank DNA database in less than 15 seconds
5.5.3 DRUG BANK:-
The DrugBank database available at the University of Alberta is a bioinformatics and
cheminformatics resource that combines detailed drug (i.e. chemical, pharmacological and
pharmaceutical) data with comprehensive drug target (i.e. sequence, structure, and pathway)
information. [c] The database contains nearly 4800 drug entries including:
• > 1480 FDA-approved small molecule drugs,
• 128 FDA-approved biotech (protein/peptide) drugs,
• > 71 nutraceuticals, and
• > 3200 experimental drugs. [d]
More than 2500 protein (i.e. drug target, non-redundant) sequences are linked to these drug
[d]
entries. Each Drug Card entry contains more than 100 data fields with half of the information
being devoted to drug/chemical data and the other half devoted to drug target or protein data. It is
maintained by David Wishart and Craig Knox. [c]
5.5.4 SWISSPROT:-
UniProt is the Universal Protein resource, a central repository of protein data created by
combining the Swiss-Prot, TrEMBL and PIR-PSD databases. The UniProt Consortium
comprises the European Bioinformatics Institute (EBI), the Swiss Institute of Bioinformatics
(SIB), and the Protein Information Resource (PIR). EBI located at the Wellcome Trust Genome
Campus in Hinxton, UK, hosts a large resource of bioinformatics databases and services. SIB,
located in Geneva, Switzerland, maintains the ExPASy (Expert Protein Analysis System) servers
that are a central resource for proteomics tools and databases. PIR, hosted by the National
Biomedical Research Foundation (NBRF) at the Georgetown University Medical Center in
Washington, DC, USA, is heir to the oldest protein sequence database, Margaret Dayhoff's Atlas
[e]
of Protein Sequence and Structure, first published in 1965. In 2002, EBI, SIB, and PIR joined
forces as the UniProt Consortium [f]
5.5.5 PDB:-
The Protein Data Bank (PDB) is a repository for the 3-D structural data of large biological
molecules, such as proteins and nucleic acids. (See also crystallographic database). The data,
typically obtained by X-ray crystallography or NMR spectroscopy and submitted by biologists
and biochemists from around the world, are freely accessible on the Internet via the websites of
[g] [h] [i]
its member organizations (PDBe , PDBj , and RCSB ). The PDB is overseen by an
organization called the Worldwide Protein Data Bank. The PDB is a key resource in areas of
structural biology, such as structural genomics. Most major scientific journals, and some funding
agencies, such as the NIH in the USA, now require scientists to submit their structure data to the
PDB. If the contents of the PDB are thought of as primary data, then there are hundreds of
derived (i.e., secondary) databases that categorize the data differently. For example, both SCOP
and CATH categorize structures according to type of structure and assumed evolutionary
relations; GO categorize structures based on genes.
5.6 SOFTWARES AND SERVERS:
5.6.1 SBASE:-
SBASE (http://www.icgeb.trieste.it/sbase) is an on-line collection of protein domain
sequences and related computational tools designed to facilitate detection of domain homologies
based on simple database search. The 10th 'jubilee release' of the SBASE library of protein
domain sequences contains 1 052 904 protein sequence segments annotated by structure,
function, ligand-binding or cellular topology, clustered into over 6000 domain groups. Domain
identification and functional prediction are based on a comparison of BLAST search outputs
with a knowledge base of biologically significant similarities extracted from known domain
groups. The knowledge base is generated automatically for each domain group from the
comparison of within-group ('self') and out-of-group ('non-self') similarities. This is a memory-
based approach wherein group-specific similarity functions are automatically learned from the
database.
5.6.2 Blast
BLAST searches for high scoring sequence alignments between the query sequence and
sequences in the database using a heuristic approach that approximates the Smith-Waterman
algorithm. The exhaustive Smith-Waterman approach is too slow for searching large genomic
databases such as Gene Bank. Therefore, the BLAST algorithm uses a heuristic approach that is
slightly less accurate than Smith-Waterman but over 50 times faster. The speed and relatively good
accuracy of BLAST are the key technical innovation of the BLAST programs and arguably why the
tool is the most popular bioinformatics search tool
BLAST is actually a family of programs (all included in the blast all executable). The following are
some of the programs, ranked mostly in order of importance:
a) Nucleotide-nucleotide BLAST (blastN): This program, given a DNA query, returns the most
similar DNA sequences from the DNA database that the user specifies.
b) Protein-protein BLAST (blastP): This program, given a protein query, returns the most similar
protein sequences from the protein database that the user specifies.
c) Position-Specific Iterative BLAST (PSI-BLAST): One of the more recent BLAST programs, this
program is used for finding distant relatives of a protein. First, a list of all closely related proteins is
created. Then these proteins are combined into a "profile" that is a sort of average sequence. A query
against the protein database is then run using this profile, and a larger group of proteins found. This
larger group is used to construct another profile, and the process is repeated. By including related
proteins in the search PSI-BLAST is much more sensitive in picking up distant evolutionary
relationships than the standard protein-protein BLAST.
d) Nucleotide 6-frame translation-protein (blastx): This program compares the six-frame conceptual
translation products of a nucleotide query sequence (both strands) against a protein sequence
database.
e) Nucleotide 6-frame translation-nucleotide 6-frame translation (tblastX): This program is the
slowest of the BLAST family. It translates the query nucleotide sequence in all six possible frames
and compares it against the six-frame translations of a nucleotide sequence database. The purpose of
tblastx is to find very distant relationships between nucleotide sequences.
f) Protein-nucleotide 6-frame translation (tblastn): This program compares a protein query against the
six-frame translations of a nucleotide sequence database.
g) Large numbers of query sequences (megablast): When comparing large numbers of input
sequences via the command-line BLAST, "megablast" is much faster than running BLAST multiple
times. It basically concatenates many input sequences together to form a large sequence before
searching the BLAST database, then post-analyze the search results to glean individual alignments
and statistical values" [52,53].
5.6.3 Homology modeling
All homology-modeling methods consist of the following four steps:
(i) Template selection;
(ii) Target template alignment;
(iii) Model building; and
(iv) Evaluation.
These steps can be iteratively repeated, until a satisfying model structure is achieved. Several
different techniques for model building have been developed. The SWISS-MODEL server approach
can be described as rigid fragment assembly is outlined briefly.
5.6.4 Template selection
The SWISS-MODEL server template library Ex: PDB is extracted from the PDB. In order to
allow a stable and automated workflow of the server, the PDB coordinate files are split into individual
protein chains and unreliable entries, e.g. theoretical models and low quality structures providing only
C coordinates, are removed. Additional information useful for template selection is gathered and
added to the file header, e.g. probable quaternary structure, quality indicators like empirical force
field energy or ANOLEA mean force potential scores. To select templates for a given protein, the
sequences of the template structure library are searched. If these templates cover distinct regions of
the target sequence, the modeling process will be split into separate independent batches.
5.6.5 Alignment
Up to five template structures per batch are superposed using an iterative least squares
algorithm. A structural alignment is generated after removing incompatible templates, i.e. omitting
structures with high C root mean square deviations to the first template. A local pair-wise alignment
of the target sequence to the main template structures is calculated, followed by a heuristic step to
improve the alignment for modeling purposes. The placement of insertions and deletions is optimized
considering the template structure context. In particular, isolated residues in the alignment (‘islands’)
are moved to the flanks to facilitate the loop building process [55].
5.6.6 Model building
To generate the core of the model, the backbone atom positions of the template structure are
averaged. The templates are thereby weighted by their sequence similarity to the target sequence,
while significantly deviating atom positions are excluded. The template coordinates cannot be used to
model regions of insertions or deletions in the target-template alignment. To generate those parts, an
ensemble of fragments compatible with the neighboring stems is constructed using constraint space
programming (CSP). The best loop is selected using a scoring scheme, which accounts for force field
energy, steric hindrance and favorable interactions like hydrogen bond formation. If no suitable loop
can be identified, the flanking residues are included to the rebuilt fragment to allow for more
flexibility. In cases where CSP does not give a satisfying solution and for loops above 10 residues, a
loop library derived from experimental structures is searched to find compatible loop fragments [57].
5.6.7 Side chain modeling
The reconstruction of the model side chains is based on the weighted positions of
corresponding residues in the template structures. Starting with conserved residues, the model side
chains are built by iso-sterically replacing template structure side chains. Possible side chain
conformations are selected from a backbone dependent rotamer library, which has been constructed
carefully taking into account the quality of the source structures. A scoring function assessing
favorable interactions (hydrogen bonds, disulfide bridges) and unfavorably close contacts is applied to
select the most likely conformation.
5.6.8 Verify 3D
Verify3D Structure Evaluation Server is a tool designed to help in the refinement of
crystallographic structures. It will provide a visual analysis of the quality of a putative crystal
structure for a protein. Verify3D expects this crystal structure to be submitted in PDB format.
Verify3D works best on proteins with at least 100 residues.
5.6.9 Ramachandran plot
A Ramachandran plot developed by G.N.Ramachandran is a way to visualize dihedral angles φ
against ψ of amino acid residues in protein structure. It shows the possible conformations of φ and ψ
angles for a polypeptide A scatter plot showing the disposition of back bone φ and ψ torsion angles
for each residue in a protein or set of proteins. Certain combinations of φ and ψ angles are preferred
strongly are reported in a series of residues and these patterns are easily detected. It tells the stereo
chemical quality of a protein structure.
Glycine has a hydrogen atom, instead of a methyl group at the β position. Hence it is least
restricted and this is apparent in the Ramachandran plot for Glycine for which the allowable area is
considerably larger. In contrast, the Ramachandran plot for Proline shows only a very limited number
of possible combinations of ψ and φ. Since bond length and angles are fairly invariant in the known
protein structures, the key to protein folding lies in the torsion angles of the backbone. The quality of
the structures and of Ramachandran plot statistics in particular, was notably improved while
preserving the agreement with the experimental constraints the compatibility scores above zero.
5.6.10 Energy minimization
Deviations in the protein structure geometry, which have been introduced by the modeling
algorithm when joining rigid fragments are regularized in the last modeling step by steepest descent
energy minimization using the NAMD/VMD molecular dynamics simulation package. Empirical
force fields are useful to detect parts of the model with conformational errors. Energy minimization or
molecular dynamics methods are in general not able to improve the accuracy of the models, and are
used in SWISS-MODEL only to regularize the structure. However, the successful application of
restricted molecular dynamics for improving homology models has recently been reported for a few
test cases. To derive more general rules of engagement of molecular dynamics, further systematic
experiments have to be conducted.
5.6.10.1 Force field:
Force filed refers to the functional form parameter sets which are used to find out potential
energy of a system. It includes parameter which is obtained through experimental works and
quantum mechanics calculations. In this Energy minimization tool used force field energy is
CHRAM++. The four modeling steps—template superposition, target-template alignment, model
building and energy minimization—have to be implemented in the program. The minimized uses
algorithm to identify the geometrics of the molecule corresponding to the minimum points on the
potential surface energy. The minimum reduced the unwanted forces which are present in the
molecule and lower the energy level of the molecule. There are many algorithms available in the
minimization process, Some of the minimization methods used in the smart minimizer is steepest
decent method, conjugate gradient method, Newton raphson method and quasi Newton method
from the DS protocols the minimization protocol is selected and run, then it gives the minimized
protein with fixed constraint then the minimized protein is saved for further studies.
5.6.11 CASTp
Computed Atlas of Surface Topography of proteins (CASTp) provides an online resource for
locating, delineating and measuring concave surface regions on three-dimensional structures of
proteins. These include pockets located on protein surfaces and voids buried in the interior of
proteins. The measurement includes the area and volume of pocket or void by solvent accessible
surface model (Richards' surface) and by molecular surface model (Connolly's surface), all calculated
analytically. CASTp can be used to study surface features and functional regions of proteins. CASTp
includes a graphical user interface, flexible interactive visualization, as well as on-the-fly calculation
for user uploaded structures.
5.6.12 ChemSketch
ACD/ChemSketch is an integrated software package from Advanced Chemistry Development
Inc. for drawing chemical structures, reactions, schematic diagrams and designing other chemistry-
related reports and presentations. Structure mode for drawing chemical structures and calculating
their properties.
5.6.13 Docking
Docking studies are computational techniques for the exploration of the possible binding
modes of a substrate to a given receptor, enzyme or other binding site. Docking studies have become
nearly indispensable for study of macromolecular structures and interactions. Mechanical model
construction requires heroic patience and endurance to complete a structure which may contain
several thousand atoms while computer graphics can build and display in seconds. Macromolecular
modeling by Docking studies provides most detailed possible view of drug-receptor interaction and
has created a new rational approach to drug design where the structure of drug is designed based on
its fit to three dimensional structures of receptor site, rather than by analogy to other active structures
of random leads [60, 61].
5.7 PK/DB
PK/DB (a freely available database for pharmacokinetic properties) was designed with
the aim of creating robust databases for pharmacokinetic studies and in silico ADME
(Absorption, Distribution, Metabolism, and Excretion) prediction. The database contains high
quality data for structurally diverse compounds associated with known ADME properties,
including human oral bioavailability, human intestinal absorption, plasma protein binding, and
blood - brain barrier, among others.