Materials for CADD
Melting points were measured in Buchi-510 instrument and
uncorrected. Spectra were recorded with the following instruments:
IR, Perkin Elmer spectrophotometer; 1H and 13C-NMR, 200 MHz
(Varian), 300 MHz (Gemini) and Unity 400 MHz (Gemini) and LCMS
and Micromass VG 7070H (70 eV). Column chromatography was
performed over silica gel (Achme 60-120 mesh or >300 mesh flash
chromatography) and TLC with silica gel MERCK GF254 (pre-coated).
The visualization of the spots in TLC plats was carried out either in
UV light (short wave 250nm) or exposing the plates to iodine vapors or
spraying with 10% sulfuric acid in methanol and subsequently
heating on hot plate.
Materials:
The following chemicals are used for experimental work;
Table Chemicals for experimental work
Name Grade source
1. 3, 4-Dimethoxy benzyl alcohol AR Merck chemical lab.
2. Benzy hydrol AR Aldrich chemical lab
3. Thio-2-naphthol AR Aldrich chemical lab
4. 4-Chloro thiophenol AR Aldrich chemical lab
5. 1-Phenyl-1-H-tetrazole-5-thiol AR Aldrich chemical lab
6. Si-Perchloric acid AR -
7. Acetonitrile AR Aldrich chemical lab
8. Benzeneselenol AR Aldrich chemical lab
24
4.3 General Experimental procedure:
To a stirred solution/solid of benzylic alcohol (1 mmol), thiol
derivative (1 mmol) in Acetonitrile (5 ml), HClO4.SiO2 (2 mmol) was
added. The reaction mixture was stirred at room temperature for 30-
45 minutes, and the reaction monitored by TLC. After completion of
reaction, the reaction mixture was filtered to remove catalyst. The
filtrate was concentrated by vacuum. The residue was purified by
silica gel column chromatography by eluting with ethyl acetate and n-
hexane to afford the pure product in 90-95% yield.
Similarly, 8 more compounds were synthesized using different
benzylic alcohols and different derivatives of thiol compounds.
4.4. Materials for CADD:
4.4.1. DATABASE:
1. NCBI (National Center for biotechnology information):
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) 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. The 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
24
BLAST co-author), David Landsman, and Eugene Koonin (a prolific
author on comparative genomics).
The NCBI Bookshelf is a collection of freely available,
downloadable, on-line versions of selected biomedical books. As of
March 2006, the Bookshelf had 55 titles covering aspects of
molecular biology, biochemistry, cell biology, genetics, microbiology, a
couple of disease states from a molecular and cellular point of view,
research methods, and virology. Some of the books are online versions
of previously published books, while others, such as Coffee Break
(book), are written and edited by NCBI staff. The Bookshelf is a
complement to the Entrez PubMed repository of peer-reviewed
publication abstracts in that Bookshelf contents provide established
perspectives on evolving areas of study and a context in which many
disparate individual pieces of reported research can be organized.
4.4.1.1. SWISS PROT (EXPASY):
Swiss-Prot is a manually crated biological database of protein
sequences. Swiss-Prot was created in 1986 by Amos Bairoch during
his PhD and developed by the Swiss Institute of Bioinformatics and
the European Bioinformatics Institute. Swiss-Prot strives to provide
reliable protein sequences associated with a high level of annotation
(such as the description of the function of a protein, its domains
structure, post-translational modifications, variants, etc.), a minimal
level of redundancy and high level of integration with other databases.
The target sequence was retrieved from SWISS PROT based on
the literature. The target sequence was submitted in Protein Blast to
compare the primary biological sequence information.
UniProtKB/Swiss-Prot is defined as annotated protein sequence
database .We makes every effort possible to ensure that all available
biochemical information accompanies the sequence data and that this
24
information is as complete and up-to-date as possible. This
annotation is a labor-intensive process that involves assessment of
information from published articles along with use of a variety of
programs/algorithms. Use is also made of Swiss-Prot itself in order to
maintain standard nomenclature and description comments. We
describe here the steps we take to add all relevant biochemical
information to new entries going into Swiss-Prot.
There are different scenarios with respect to biochemical
information that accompanies sequence data reports. Sometimes
scientists isolate and then biochemically characterize the protein
encoded by the gene they have sequenced. Other times they infer this
information through similarity to other proteins within the same,
conserved family. If it does not belong to a particular family they infer
through purely sequence similarity. Then we have the genome
sequence data that does not often have an accompanying citation
reporting any such classification. Below are the steps we use to
analyze these reports and how we assess what and how to add this
information to the sequence entries.
In all the scenarios below a new entry is taken from TrEMBL
and, generally, the first step is to get a copy of the article(s) given in
the reference lines. Then the sequence is aligned, using FastA or
Blast, against all existing Swiss-Prot and TrEMBL entries. This allows
us, quickly and easily, to assess if and how the sequence relates to
existing families in SWISS-PROT. The next step is to read the
article(s), assess the information given and add relevant comments
and features to the entry.
4.4.1.2. PDB (PROTEIN DATA BANK)
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-
24
ray crystallography or NMR spectroscopy and submitted by biologists
and biochemists from around the world, can be accessed at no charge
on the internet. The PDB is overseen by an organization called the
Worldwide Protein Data Bank, wwPDB. 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.
These data show that most structures are determined by X-ray
diffraction, but about 15% of structures are now determined by
protein NMR, and a few are even determined by cryo-electron
microscopy. The significance of the structure factor files, mentioned
above, is that, for PDB structures determined by X-ray diffraction that
have a structure file, the electron density map may be viewed. The
data of such structures is stored on the "electron density server",
where the electron maps can be viewed.
4.4.1.3. Drug Bank
The Drug Bank 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,
pathway) information.
The database contains nearly 4800 drug entries including:
>1480 FDA-approved small molecule drugs, 128 FDA-approved
biotech (protein /peptide) drugs, >71nutraceuticals, and > 3200
experimental drugs. More than 2500 protein (i.e. drug target, non-
redundant) sequences are linked to these drug entries.
24
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.
4.4.1.4. Pubchem
PubChem is a database of chemical molecules. The system is
maintained by the National Center for Biotechnology Information
(NCBI), a component of the National Library of Medicine, which is part
of the United States National Institutes of Health (NIH). PubChem can
be accessed for free through a web user interface. Millions of
compound structures and descriptive datasets can be freely
downloaded via FTP. PubChem contains substance descriptions and
small molecules with fewer than 1000 atoms and 1000 bonds. The
PubChem Compounds Database contains validated chemical depiction
information provided to describe substances in PubChem Substance.
Structures stored within PubChem Compounds are pre-clustered and
cross-referenced by identity and similarity groups. Additionally,
calculated properties and descriptors are available for searching and
filtering of chemical structures. The PubChem Substances Database
contains descriptions of chemical samples, from a variety of sources,
and links to PubMed citations, protein 3D structures, and biological
screening results that are available in bioassay. If the contents of a
chemical sample are known, the description includes links to
PubChem Compound.
4.4.1.5. NCBI
(National Center for Biotechnology Information) is a key
repository for biological sequences and related data. It is essential for
all of us to be familiar with the contents and tools available at this
repository. For example, for most of the whole-genome projects, NCBI
hosts a mirror page and integrates the data into its database.
24
It is recommended that you visit the NCBI web
site(http://www.ncbi.nlm.nih.gov) and explore the various databases
present on genome biology, cancer anatomy project, cluster of
orthologous groups, human genome and pages for other genomes
(including microbial genomes). Complete genome sequences of some of
the deadly pathogens are available (e.g., Mleprae, M genitaliaum, M
pneumoniae, H. injlueanzae, E. coli DH 5, etc.). In fact, for any newly
discovered pathogen, the complete genome sequence is likely to be the
first information available about the pathogen.
4.5 CASTp (computed atlas of surface topogragphy of protein)
CASTp is based on recent theoretical and algorithmic results of
Computational Geometry. It has many advantages:
1) Pockets and cavities are identified analytically,
2) The boundary between the bulk solvent and the pocket is defined
precisely,
3) All calculated parameters are rotationally invariant, and do not
involve discretization and they make no use of dot surface or grid
points.
Binding sites and active sites of proteins and DNAs are often
associated with structural pockets and cavities. castP server uses the
weighted Delaunay triangulation and the alpha complex for shape
measurements. It provides identification and measurements of surface
accessible pockets as well as interior inaccessible cavities, for proteins
and other molecules. It measures analytically the area and volume of
each pocket and cavity, both in solvent accessible surface (SA,
Richards' surface) and molecular surface (MS, Connolly's surface). It
also measures the number of mouth openings, area of the openings,
and circumference of mouth lips, in both SA and MS surfaces for each
pocket. You can request calculation for a particular molecule. The
results will be shown on the screen or emailed to you. The emailed
24
results include measured parameters for pockets, cavities and mouth
openings, as well as listing of wall atoms and mouth atoms for each
pocket.
Protein performs its function through interaction with other
molecules such as substrate, ligand, DNA and other domains of
proteins. The three-dimensional structure of protein provides the
necessary shape and physicochemical texture to facilitate these
interactions. Structural information of protein surface regions enables
detailed studies of the relationship of protein structure and function.
Specifically, characterization of protein surface regions helps to
analyze enzyme mechanism, to determine binding specificity and to
plan mutation studies. It can also help to identify the biological roles
of newly solved protein structures with an unknown function.
4.6 DIAL SERVER:
DIAL is a web server for the automatic identification of structural
domains given the three dimensional coordinates of a protein.
This version accepts user-upload PDB files.
Where the protein is known to exist as multimers and the
transformation matrix is available, the server internally
generates multimer coordinates and proposes structural domain
solutions for the entire quarternary arrangement.
This version can identify domain boundaries or multiple chain
entries and domain swapping events as well.
METHODS:
1. Secondary structures are identified on the basis of main chain
hydrogen bonding patterns, using the program SSTRUC (Smith,
unpublished results), which implements the algorithm of Kabsch and
Sander (1983) to define substructures: alpha helix, beta strand and
loop regions.
24
2. C-alpha distances between secondary structures are represented in
the form of naverage values termed “proximity indices”.
3. The calculated proximity indices are used to perform clustering
using KITSCH, which is a part of the phylogeny inference package
PHYLIP and the secondary structural organisation is indicated in the
form of dendrograms. Specific nodes in these dendrograms are
identified as tertiary structural clusters of the protein; these include
super secondary structures and domains.
4. A ratio of the average proximity indices to the average of all
proximity indices, weighted for the aggregation of small sub clusters
and termed the disjoint factor, is employed as a discriminatory
parameter to identify automatically clusters representing individual
domains.
4.7 SWISS-MODEL
Swiss-model server is used to generate 3d structure of the
protein molecule. When the input is given in the fasta format in the
swiss-model it automatically searches for the homologous protein
which shares the very similar structure (template) and by comparing
the template, swiss-model server model’s a protein structure with
reasonable accuracy.
SWISS-MODEL was initiated in 1993 by Manuel Peitsch, and
further developed at Glaxo Welcome Experimental Research in Geneva
and the SIB Swiss Institute of Bioinformatics by Manuel Peitsch,
Nicolas Guex and Torsten Schwede. Since 2001, SWISS-MODEL is
being developped by Torsten Schwede's Structural Bioinformatics
Group at the SIB & Biozentrum (University of Basel). The SWISS-
MODEL Repository, a relational database of annotated three-
dimensional comparative protein s tructure models, was established
in 2004. In 2005, SWISS-MODEL service was extended by SWISS-
24
MODEL Workspace, a web-based work bench for protein structure
modelling and assessment. Computational resources for the SWISS-
MODEL server are provided in collaboration by the Biozentrum
(University Basel), the Swiss Institute of Bioinformatics and the
Advanced Biomedical Computing Center (NCI Frederick, USA).
4.7.1 Swiss PDB viewer
Deep view (formerly called Swiss-PdbViewer) is a friendly but
powerful molecular graphics program. It is designed for full
compatibility with computing tools available from the Expert Protein
Analysis System, or ExPASy, Molecular Biology Server in Geneva,
Switzerland. While DeepView is simple to use for viewing structures
and creating vivid illustrations, it also shines as an analytical tool.
DeepView allows you to build models from scratch, simply by giving
an amino-acid sequence. DeepView can find hydrogen bonds within
proteins and between proteins and ligands. It allows us to examine
electron-density maps from crystallographic structure determination,
to judge the quality of maps and models, and to identify many
common types of problems in protein models. For proteins of known
sequence but unknown structure, DeepView submits amino acid
sequences to ExPASy to find homologous proteins, onto which you
can subsequently align your sequence to build a preliminary three-
dimensional model. Then DeepView submits your alignment to
ExPASy, where the SWISS-MODEL server builds a final model, called
a homology model, and returns it directly to DeepView.
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 SPDBV 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
24
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.
4.8 OPEN EYE
OpenEye provides software to the pharmaceutical industry for
molecular modeling and cheminformatics. It has done so since 1997 in its
continuing mission to provide novel software, new science and better
business practices to the industry. Central to our approach is the
importance of shape and electrostatics as primary variables of molecular
description, platform-independent code for high-throughput 2D and 3D
modeling, and a preference for the rigorous rather than the ad hoc.
OpenEye's portfolio of molecular modeling applications is
presented as a workflow involving ligand- and structure-based design
strategies. FILTER and QUACPAC prepare the input compounds by
removal of undesirables and application of a variety of charge models.
Next, OMEGA generates high quality 3D conformer ensembles. ROCS
searches compound libraries for 3D shape (and chemistry) similar
molecules. EON may then be used to refine the ROCS hits by
electrostatic similarity. BROOD searches fragment databases for
bioisosteric replacements using similar approaches to ROCS and
EON. FRED is OpenEye's docking and scoring application. Hit
structures may then be optimized with SZYBKI. VIDA is a powerful
graphical interface for visualization and effective communication of
results, which VIVANT can then export live into PowerPoint
presentations or web pages. AFITT is a standalone application for
ligand fitting to crystallographic density.
24
The Chemgauss scoring function combines the Shape gauss
scoring function with additional potentials between chemically
matched positions around the ligand pose. These chemically
complementary positions are generally not also atom positions, but
rather are placed near specific functional groups. For instance
acceptors have "lone pair" positions around them which denote
positions where polar hydrogen could be placed to create a hydrogen
bonding interaction. Similarly donors have "polar hydrogen" positions,
which denote positions its hydrogen could be in. For simple donors
without rotatable bonds these positions correspond to the actual polar
hydrogen position, but for rotatable bonds such as hydroxyls there are
several positions representing the ring of possible positions for the
polar hydrogen. A favorable hydrogen bond score is obtained when a
"polar hydrogen" position on one molecule overlaps a "lone pair"
position on another molecule.
Chemscore is scoring function is used the position of hydrogens
involved in hydrogen bonding is optimized with respect to the
hydrogen bond energy (this is done for both protein and ligand
donors). However, no optimization of heavy atoms on either the
protein or ligand is done.
PLP is a heavy atom scoring function, meaning all potentials are
based on distances from heavy atom centers (i.e. hydrogen position is
irrelevant, although the presence or absence of hydrogen is not, as it
can affect the atom typing). The PLP implementation in FRED adheres
to the reference as faithfully as possible, with the caveat that the
implementation in FRED has been extending to include favorable
interactions between acceptor and metal atoms.
The Screen score is a sum of the interactions of lipophilic atoms
on the ligand and the interactions between metals and acceptors
(which are treated as coordinating atoms for the purposes of this
term).
24
The Shapegauss scoring function represents all atoms as
smooth Gaussian functions. A pairwise potential between ligand and
protein atoms is applied that attempts to maximize their surface
contact and minimize their volume overlap (i.e., the potential is most
favorable when the atoms are touching but not overlapping). A
correction term is then applied to further penalize atoms which
significantly overlap the protein.
4.8.1 VIDA
VIDA is OpenEye's visualization and data analysis platform. It
was originally developed to solve the problem of browsing through
large amounts of molecular data. VIDA is not simply just a tool; it is
the instantiation of the OpenEye philosophy on visualization and data
analysis. The philosophy behind VIDA is relatively simple and can be
seen summarized below.
VIDA should:
handle enormous amounts of data gracefully (into the millions
of molecules)
provide multiple views of the data which can be display
simultaneously
run on all (reasonable) platforms
be configurable
provide basic access to all OpenEye functionality for free
have a really simple licensing scheme
VIDA is the OpenEye philosophy made perceptible: it is a graphics
program designed from the ground up to visualize, manage and
manipulate large sets of molecular information. Where other programs
choke at 1000 structures, VIDA happily digests 100,000s.
5 METHODOLOGY
24
5.1 Synthesis of 2-{[4-(benzyloxy)-3-
methoxybenzyl]thio}naphthalene.
S
O
O
2-{[4-(benzyloxy)-3-methoxybenzyl]thio}naphthalene
Molecular Formula : C25H27O2S
IR (KBr) :2924.63, 2857.46, 1507.02,
1457.73, 1257.73, 1220.69,
1135.36, 740.64, 464.41cm-1
1H NMR (300 MHz, CDCl3) : 7.60-7.75(m,4H),7.43-7.18(m,8H)
6.83-6.76(m,1H),6.69-
6.73(s,2H),5.05(s,2H),
4.09(s,2H),3.75(s,3H).
13C : 149.70, 147.493, 137.168,
134.023, 133.761, 131.926,
130.296, 129.303, 125.694
126.422, 127.218, 127.759,
127.938, 128.235, 128.461,
113.972, 112.526, 70.983,
24
121.048.55.707, 38.944
Mass (ESI MS) m/z : 409(M+Na)+
To a stirred solution of 3-methoxy, 4-benzyloxy benzylalcohol (1
mmol), Thio-2-napthol (1 mmol) in Acetonitrile (5 ml), HClO4.SiO2 (2
mmol) was added. The reaction mixture was stirred at room
temperature for 15-32 minutes, and the reaction monitored by TLC.
After completion of reaction, the reaction mixture was filtered to
remove catalyst. To the filtrate add Saturated Sodium bicarbonate
solution, and the organic layer was concentrated by vacuum .The
residue was purified by silica gel column chromatography by eluting
with ethyl acetate and n-hexane to afford the pure product in 92%
yield.
5.2 Synthesis of 1-(benzyloxy)-4-[(phenylselenium) methyl]
benzene.
O
Se
O
1-(benzyloxy)-4-[(phenylselenium) methyl] benzene
Molecular Formula : C20H18OSe
IR (KBr) : 2925.39, 2856.93, 1510.51,
1462.58, 1244.66, 1173.91,
1138.70,1030.67, 734.87,
24
462.06
1H NMR (300 MHz, CDCl3) : 7.14-7.43(m,10H),6.78-6.85
(d,1H)6.58-6.77(m,3H),
5.07(s,2H),4.00(s,2H),3.76(s,3H)
13C : 149.403, 147.083, 137.140,
133.801, 131.718, 128.909,
129.355, 127.753, 127.228,
120.871, 113.952, 113.747,
112.500, 130.363, 71.051,
55.800, 32.191.
Mass (ESI MS) m/z : 406(M+Na)
To a stirred solution of 3-methoxy,4-benzyloxy benzyl alcohol (1
mmol), Benzeneselenol (1 mmol) in Acetonitrile (5 ml), HClO4.SiO2 (2
mmol) was added. The reaction mixture was stirred at room
temperature for 35 minutes, and the reaction monitored by TLC. After
completion of reaction, the reaction mixture was filtered to remove
catalyst. To the filtrate add Saturated Sodium bicarbonate solution,
and the organic layer was concentrated by vacuum The residue was
purified by silica gel column chromatography by eluting with ethyl
acetate and n-hexane to afford the pure product in 90% yield.
5.3 Synthesis of 1-(benzyloxy)-4-{{(4-chlorophenyl) thio] methyl}-
2-methoxybenzene.
24
O
O
S Cl
1-(benzyloxy)-4-{{(4-chlorophenyl) thio] methyl}-2-methoxybenzene
Molecular Formula : C21H19ClO2S
IR (KBr) : 2927.78, 2871.83, 1510.30
1468.08, 1262.33, 1229.93
1091.22, 997.79, 807.62,
742.69,481.82 cm-1
1H NMR (300 MHz, CDCl3) : 7.22-7.42(m,5H),
7.13-7.21(s,4H),
6.61-6.78(m,3H),5.07(s,2H),
3.96(s,2H),3.82(s,3H)
13C :149.603, 147.401, 137.014,
134.688, 132.418, 131.497,
129.991, 128.435, 127.749,
127.199, 120.944, 113.860,
112.371, 70.968, 55.812, 39.204
Mass (ESI MS) m/z : 393(M+Na)+
24
To a stirred solution 3-methoxy, 4-benzyloxy benzylalcohol (1
mmol), 4-chlorothiophenol (1 mmol) in Acetonitrile (5 ml), HClO4.SiO2
(2 mmol) was added. The reaction mixture was stirred at room
temperature for 41 minutes, and the reaction monitored by TLC. After
completion of reaction, the reaction mixture was filtered to remove
catalyst. To the filtrate add Saturated Sodium bicarbonate solution,
and the organic layer was concentrated by vacuum. The residue was
purified by silica gel column chromatography by eluting with ethyl
acetate and n-hexane to afford the pure product in 89% yield.
5.4 Synthesis of 1-{[4-(benzyloxy)-3-methoxybenzyl]thio}-5-phen
yl-1H tetrazole
N N
N
S N
O
O
1-{[4-(benzyloxy)-3-methoxybenzyl]thio}-5-phenyl-1H tetrazole.
Molecular Formula : C22H20N4O2S
IR (KBr) : 2924.40, 2854.86, 1645.91,
1512.37, 1459.75, 1263.97
1223.16, 740.14, 469.43
1H NMR (300 MHz, CDCl3) : 7.43-7.23(m,7H),6.78-6.81(m,1H)
6.76(s,1H), 6.67-6.72(s,1H),
5.10(s,2H),4.30(d,2H),3.87(s,3H)
24
Mass (ESI MS) m/z : 427(M+Na)+
To a stirred solution 3-methoxy, 4-benzyloxy benzylalcohol (1
mmol), 1-phenyl-1-H-tetrazole-5-thiol (1 mmol) in Acetonitrile (5 ml),
HClO4.SiO2 (2 mmol) was added. The reaction mixture was stirred at
room temperature for 45 minutes, and the reaction monitored by TLC.
After completion of reaction, the reaction mixture was filtered to
remove catalyst. To the filtrate add Saturated Sodium bicarbonate
solution, and the organic layer was concentrated by vacuum. The
residue was purified by silica gel column chromatography by eluting
with ethyl acetate and n-hexane to afford the pure product in 94%
yield.
5.5 Synthesis of 1-Chloro-4-[(1, 1-diphenyl)thio]benzene
Cl
S
1-Chloro-4-[(1,1-diphenyl)thio]benzene.
Molecular Formula : C19H15ClS
IR (KBr) : 2924.68,1443.30,1382.41,
1082.49,1003.28,692.42,
496.04
1H NMR (300 MHz, CDCl3) :7.39-7.45(m,4H),7.37-7.22(m,6H)
24
7.15-7.19(m,4H),5.50(s,1H)
Mass (ESI MS) m/z : 349(M+K)+
To a stirred solid of Benzyl alcohol (1 mmol), 4-chlorothio
phenol (1 mmol) in Acetonitrile (5 ml), HClO4.SiO2 (2 mmol) was
added. The reaction mixture was stirred at room temperature for 15-
39 minutes, and the reaction monitored by TLC. After completion of
reaction, the reaction mixture was filtered to remove catalyst. To the
filtrate add Saturated Sodium bicarbonate solution, and the organic
layer was concentrated by vacuum. The residue was purified by silica
gel column chromatography by eluting with ethyl acetate and n-
hexane to afford the pure product in 95% yield.
5.6 Synthesis of 1-[(3, 4-dimethoxybenzyl)thio]naphthalene.
S
O
O
1-[(3, 4-dimethoxybenzyl)thio]naphthalene.
Molecular Formula : C19H18O2S
IR (KBr) : 2927.45, 2837.41,1508.30,
1449.8,1258.23, 1232.81,
1145.53,1022.05, 811.90,
741.27,464.21
1H NMR (300 MHz, CDCl3) :7.64-7.76(m,4H),7.45-7.33(m,3H).
24
6.81-6.68(m,3H),4.12(s,2H),
3.83(s,3H),3.76(s,3H)
Mass (ESI MS) m/z : 333(M+Na)+
To a stirred solution of 3, 4-dimethoxy benzyl alcohol (1 mmol),
Thio-2-napthol (1 mmol) in Acetonitrile (5 ml), HClO4.SiO2 (2 mmol)
was added. The reaction mixture was stirred at room temperature for
43 minutes, and the reaction monitored by TLC. After completion of
reaction, the reaction mixture was filtered to remove catalyst. To the
filtrate add Saturated Sodium bicarbonate solution, and the organic
layer was concentrated by vacuum. The residue was purified by silica
gel column chromatography by eluting with ethyl acetate and n-
hexane to afford the pure product in 93% yield.
5.7 Synthesis of 4-{[(4-chlorophenyl)thio]methyl}-1,2-
dimethoxybenzene.
Cl
S
O
O
4-{[(4-chlorophenyl)thio]methyl}-1,2-dimethoxybenzene
Molecular Formula : C15H15ClO2S
IR (KBr) : 2924.20, 2855.06, 1513.10,
24
1465.84, 1267.23, 1234.14,
1021.42, 808.39, 479.10
1H NMR (300 MHz, CDCl3) :3.97(s, 2H), 3.82(s, 3H),3.80(s,3H)
7.21-7.14(m, 4H),6.71-6.74(s,1H)
6.68-6.71(s, 2H).
13C :148.979, 148.345, 134.763,
131.359, 129.275132.360
128.766, 120.893, 11.895
11.030, 55.561, 39.143
To a stirred solution of 3, 4-dimethoxy benzyl alcohol (1 mmol),
4-chlorothio phenol (1 mmol) in Acetonitrile (5 ml), HClO4.SiO2 (2
mmol) was added. The reaction mixture was stirred at room
temperature for 45 minutes, and the reaction monitored by TLC. After
completion of reaction, the reaction mixture was filtered to remove
catalyst. To the filtrate add Saturated Sodium bicarbonate solution,
and the organic layer was concentrated by vacuum. The residue was
purified by silica gel column chromatography by eluting with ethyl
acetate and n-hexane to afford the pure product in 93% yield.
5.8 Synthesis of 4-[(1, 1-diphenyl)thio]naphthalene.
24
S
4-[(1, 1-diphenyl)thio]naphthalene
Molecular Formula : C23H18S
IR (KBr) : 2922.18, 1735.43, 1584.82,
1488.17, 1444.72, 816.03,
740.74, 692.73, 474.83
1H NMR (300 MHz, CDCl3) : 7.71-7.64(m,1H),7.63-7.52(m,3H)
7.45-7.32(m,6H),7.31-7.13(m,7H)
5.60(s,1H)
To a stirred solid of Benzyl alcohol (1 mmol), Thio-2-napthol (1
mmol) in Acetonitrile (5 ml), HClO4.SiO2 (2 mmol) was added. The
reaction mixture was stirred at room temperature for 42 minutes, and
the reaction monitored by TLC. After completion of reaction, the
reaction mixture was filtered to remove catalyst. To the filtrate add
Saturated Sodium bicarbonate solution, and the organic layer was
concentrated by vacuum. The residue was purified by silica gel
column chromatography by eluting with ethyl acetate and n-hexane to
afford the pure product in 91% yield.
6 Active site Identification:
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Active site of Signal transducer and activator of transcription 4 was
identified using CASTp server. A new program, CASTp, for automatically
locating and measuring protein pockets and cavities, is based on precise
computational geometry methods, including alpha shape and discrete flow
theory. CASTp identifies and measures pockets and pocket mouth
openings, as well as cavities. The program specifies the atoms lining
pockets, pocket openings, and buried cavities; the volume and area of
pockets and cavities; and the area and circumference of mouth openings.
7 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.
8 SWISS-PROT
The sequence of receptor is retrieved from swiss-prot in FASTA format
8.1 SWISS-MODEL
Swiss-model server is used to generate 3d structure of the
protein molecule. When the input is given in the fasta format in the
swiss-model it automatically searches for the homologous protein
which shares the very similar structure (template) and by comparing
the template, swiss-model server model’s a protein structure with
reasonable accuracy.
SWISS-MODEL was initiated in 1993 by Manuel Peitsch, and
further developed at Glaxo Welcome Experimental Research in Geneva
and the SIB Swiss Institute of Bioinformatics by Manuel Peitsch,
24
Nicolas Guex and Torsten Schwede. Since 2001, SWISS-MODEL is
being developped by Torsten Schwede's Structural Bioinformatics
Group at the SIB & Biozentrum (University of Basel). The SWISS-
MODEL Repository, a relational database of annotated three-
dimensional comparative protein s tructure models, was established
in 2004. In 2005, SWISS-MODEL service was extended by SWISS-
MODEL Workspace, a web-based work bench for protein structure
modelling and assessment. Computational resources for the SWISS-
MODEL server are provided in collaboration by the Biozentrum
(University Basel), the Swiss Institute of Bioinformatics and the
Advanced Biomedical Computing Center (NCI Frederick, USA).
8.2 Swiss PDB viewer:
Deep view (formerly called Swiss-PdbViewer) is a friendly but powerful
molecular graphics program. It is designed for full compatibility with
computing tools available from the Expert Protein Analysis System, or
ExPASy, Molecular Biology Server in Geneva, Switzerland. While
DeepView is simple to use for viewing structures and creating vivid
illustrations, it also shines as an analytical tool. DeepView allows you
to build models from scratch, simply by giving an amino-acid
sequence. DeepView can find hydrogen bonds within proteins and
between proteins and ligands. It allows us to examine electron-density
maps from crystallographic structure determination, to judge the
quality of maps and models, and to identify many common types of
problems in protein models. For proteins of known sequence but
unknown structure, DeepView submits amino acid sequences to
ExPASy to find homologous proteins, onto which you can
subsequently align your sequence to build a preliminary three-
dimensional model. Then DeepView submits your alignment to
ExPASy, where the SWISS-MODEL server builds a final model, called
a homology model, and returns it directly to DeepView.
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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 SPDBV 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.
9 Docking method:
The ligands, including all hydrogen atoms, were built and optimsed
with chemsketch software suite. Extremely Fast Rigid Exhaustive
Docking (FRED) version 2.1 was used for docking studies (OpenEye
Scientific Software, Santa Fe, NM). It is an implementation of
multiconformer docking, meaning that a conformational search of the
ligand is first carried out, and all relevant low-energy conformations
are then rigidly placed in the binding site. This two-step process
allows only the remaining six rotational and translational degrees of
freedom for the rigid conformer to be considered. The FRED process
uses a series of shape-based filters and the default scoring function is
based on Gaussian shape fitting (Diaz, et al, 2004).
.
9.1 Docking by open-eye
In the field of molecular modeling, docking is a method which
predicts the preferred orientation of one molecule to a second when
bound to each other to form a stable complex (Lengauer T, 1996).
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Docking is frequently used to predict the binding orientation of small
molecule drug candidates to their protein targets in order to in turn
predict the affinity and activity of the small molecule. Two approaches
are particularly popular within the molecular docking community.
One approach uses a matching technique that describes the protein
and the ligand as complementary surfaces (Feig M, 2004).The second
approach simulates the actual docking process in which the ligand-
protein pair wise interaction energies are calculated. Docking program
depends on two components: the search algorithm and the scoring
function. Hence docking plays an important role in the rational design
of drugs (Kitchen DB, 2004).
Open Eye provides software to the pharmaceutical industry for
molecular modeling and cheminformatics. It has done so since 1997
in its continuing mission to provide novel software, new science.
Central to our approach is the importance of shape and electrostatics
as primary variables of molecular description, platform-independent
code for high-throughput 2D and 3D modeling, and a preference for
the rigorous rather than the ad hoc. We invite you to learn more about
us and whether we can contribute to your endeavour.
OpenEye's portfolio of molecular modeling applications is
presented as a workflow involving ligand- and structure-based design
strategies. FILTER and QUACPAC prepare the input compounds by
removal of undesirables and application of a variety of charge models.
Next, OMEGA generates high quality 3D conformer ensembles. ROCS
searches compound libraries for 3D shape (and chemistry) similar
molecules. EON may then be used to refine the ROCS hits by
electrostatic similarity. BROOD searches fragment databases for
bioisosteric replacements using similar approaches to ROCS and
EON. FRED is OpenEye's docking and scoring application. Hit
structures may then be optimized with SZYBKI. VIDA is a powerful
graphical interface for visualization and effective communication of
results, which VIVANT can then export live into PowerPoint
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presentations or web pages. AFITT is a standalone application for
ligand fitting to crystallographic density.
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