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INTRODUCTION
Drug design is the approach of finding drugs by design, based on their
biological targets. Typically a drug target is a key molecule involved in aparticular metabolic or signalling pathway that is specific to a disease
condition or pathology, or to the infectivity or survival of a microbial
pathogen.
Rational drug design is a process used in the biopharmaceutical industry to
discover and develop new drug compounds. RDD uses a variety of
computational methods to identify novel compounds, design compounds for
selectivity, efficacy and safety, and develop compounds into clinical trial
candidates. These methods fall into several natural categories structure-
based drug design, ligand-based drug design, de novo design and homology
modeling depending on how much information is available about drug
targets and potential drug compounds. Well focus on structure-based drug
design in this article and describe a few of its salient features
Structure-based drug design is one of several methods in the rational drug
design toolbox. Drug targets are typically key molecules involved in a specific
metabolic or cell signaling pathway that is known, or believed, to be related
to a particular disease state. Drug targets are most often proteins and
enzymes in these pathways. Drug compounds are designed to inhibit, restore
or otherwise modify the structure and behavior of disease-related proteins
and enzymes. SBDD uses the known 3D geometrical shape or structure of
proteins to assist in the development of new drug compounds. The 3D
structure of protein targets is most often derived from x-ray crystallographyor nuclear magnetic resonance (NMR) techniques. X-ray and NMR methods
can resolve the structure of proteins to a resolution of a few angstroms
(about 500,000 times smaller than the diameter of a human hair). At this
level of resolution, researchers can precisely examine the interactions
between atoms in protein targets and atoms in potential drug compounds
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that bind to the proteins. This ability to work at high resolution with both
proteins and drug compounds makes SBDD one of the most powerful
methods in drug design.
Bioinformatics plays an important role in the design of new drug compounds.
Drug discovery has long been a multidisciplinary effort to optimize ligands
properties (potency, selectivity, pharmacokinetics) towards a single
macromolecular target. It is estimated that, out of the 2025 000 human
genes supposed to encode for ca. 3000 druggable targets only a subset of
that pharmacological space has currently been investigated by the
pharmaceutical industry. Remarkably, medicinal chemistry followed a parallel
boost with the miniaturization and parallelization of compound synthesis,
such that over 10 million non-redundant chemical structures covers the
actual chemical space, out of which ca. 1000 have been approved as drugs.
Therefore, only a small fraction of compounds describing the current
chemical space has been tested on a fraction of the entire target space.
LEUKEMIA : AN INTRODUCTION
Leukemia is a cancer of the blood or bone marrow and is characterized by
an abnormal proliferation (production by multiplication) of blood cells,
usually white blood cells (leukocytes). It is part of the broad group of
diseases called hematological neoplasms.
Damage to the bone marrow, by way of displacing the normal bone marrow
cells with higher numbers of immature white blood cells, results in a lack of
blood platelets, which are important in the blood clotting process. This
means people with leukemia may become bruised, bleed excessively, or
develop pinprick bleeds (petechiae). White blood cells, which are involved
in fighting pathogens, may be suppressed or dysfunctional. This could cause
the patient's immune system to be unable to fight off a simple infection or to
start attacking other body cells.
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Finally, the red blood cell deficiency leads to anemia, which may cause
dyspnea. All symptoms can be attributed to other diseases; for diagnosis,
blood tests and a bone marrow examination are required.
Some other related symptoms:
Fever, chills, night sweats and other flu-like symptoms
Weakness and fatigue
Swollen or bleeding gums
Neurological symptoms (headache)
Enlarged liver and spleen
Frequent infection
Bone pain Joint pain
Dizziness
Swollen tonsils
Combining these two classifications provides a total of four maincategories:
Acute Chronic
lymphocytic
leukemia
Acute lymphocytic leukemia(also known as AcuteLymphoblastic Leukemia, or ALL)is the most common type ofleukemia in young children. Thisdisease also affects adults,especially those age 65 and older.
Chronic lymphocytic
leukemia (CLL) most oftenaffects adults over the age of55. It sometimes occurs inyounger adults, but it almostnever affects children.
myelogenous
leukemia (or"myeloid")
Acute myelogenous
leukemia (also known as AcuteMyeloid Leukemia, or AML) occursmore commonly in adults than inchildren. This type of leukemia waspreviously called "acutenonlymphocytic leukemia".
Chronic myelogenousleukemia (CML) occursmainly in adults. A very smallnumber of children alsodevelop this disease
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There is no single known cause for all of the different types of leukemia. The
different leukemias likely have different causes, and very little is certain
about what causes them. Researchers have strong suspicions about four
possible causes:
natural or artificial ionizing radiation
certain kinds of chemicals
some viruses
genetic predispositions
Acute myeloid leukemia (AML), also known as acute myelogenous leukemia,
is a cancer of the myeloid line ofwhite blood cells, characterized by the rapid
proliferation of abnormal cells which accumulate in the bone marrow and
interfere with the production of normal blood cells. AML is the most
common acute leukemia affecting adults, and its incidence increases with
age. Although AML is a relatively rare disease, accounting for approximately
1.2% of cancer deaths in the United States, its incidence is expected to
increase as the population ages.
The World Health Organization (WHO) classification of acute myeloid
leukemia attempts to be more clinically useful and to produce more
meaningful prognostic information than the FAB criteria. Each of the WHO
categories contains numerous descriptive sub-categories of interest to the
hematopathologist and oncologist; however, most of the clinically
significant information in the WHO schema is communicated via
categorization into one of the five subtypes listed below.
The WHO subtypes of AML are:
AML with characteristic genetic abnormalities, which includes
AML with translocations between chromosome 8 and 21 [t(8;21)],
inversions in chromosome 16 [inv(16)], or translocations between
chromosome 15 and 17 [t(15;17)]. Patients with AML in this category
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Transcription 3.7 kb; 2979 bp open reading frame
Protein
Description Size: 993 amino acids; 112804 Da;
FLT3 is a class III receptor tyrosine kinase (RTK) structurally
related to the receptors for platelet derived growth factor
(PDGF), colony stimulating factor 1 (CSF1), and KIT ligand
(KL).; these RTK contain five immunoglobulin-like domains in
the extracellular region and an intracelular tyrosine kinase
domain splitted in two by a specific hydrophilic insertion (kinase
insert); immunoprecipitation of the human FLT3 protein results
in the appearance of a minor band of Mr 130 000 and a majorband of Mr 155 000/160 000; the high-molecular-weight band
corresponds to the mature, N-glycosylated form, and the low-
molecular-weight band to the immature, high mannose-
containing form; N-linked glycosylations account for 50 000
daltons.
Expression FLT3 expression was described on bone marrow CD34-positive
cells, corresponding to multipotential, myeloid and B-lymphoid
progenitor cells, and on monocytic cells; FLT3 expression is
restricted to cells of the fetal liver expressing high levels of
CD34; in addition, the FLT3 protein is expressed on blast cells
from most ANLL and B-ALL.
Localisation Subcellular location: Type I membrane protein. 3D structure:
PDB id 1RJB (3D).
Function FLT3 receptor function can be defined by the activity of its
ligand (FL); FL is an early acting factor and supports thesurvival, proliferation and differentiation of primitive
hemopoietic progenitor cells. Ligand binding to FLT3 promotes
receptor dimerization and subsequent signalling through
posphorylation of multiple cytoplasmatic proteins, including
SHC, SHP-2, SHIP, Cbl, Cbl-b, Gab1 and Gab2, as well as the
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activation of several downstream signalling pathways, such as
the Ras/Raf/MAPK and PI3 kinase cascades.
Function: Receptor for the FL cytokine. Has a tyrosine-protein
kinase activity. Catalytic activity: ATP + a protein tyrosine =
ADP + protein tyrosine phosphate.
Similarity: Belongs to the Tyr protein kinase family. CSF-
1/PDGF receptor subfamily. Contains 1 immunoglobulin-like C2-
type domain.
Homology Other tyrosine kinases: KIT, PDGFRA, PDGFRB, VEGFR
Mutations
Somatic Mutations in the FLT3 gene are the most frequent geneticaberration that have been described in acute myeloid leukemia.
With 20-25% length mutations in the juxtamembrane domain are
the most frequent, followed by 7-8% mutations in the second
tyrosine kinase kinase domain, mostly point mutations in codon
835 or deletions of codon 836. Also point mutations in the juxta
membrane domain have been described and the number of new
mutations all over the total gene is still growing.
Implicated in
Entity FLT3-length mutation (FLT3-LM)
Disease Internal tandem duplications and/or insertions and, rarely,
deletions in the FLT3-gene are implicated in 20-25% of all
acute myeloid leukemias (AML). It was also described to be
involved in 5-10 % myelodysplastic syndromes (MDS)
refractory anaemia with excess of blasts (RAEB 1 and RAEB 2)and rare cases with acute lymphoblastic leukemia (ALL) The
duplicated sequence belongs to exon 11 but sometimes
involves intron 11 and exon 12. The most frequently used
nomenclature is FLT3-ITD (internal tandem duplication).
Because of the very heterogenous molecular structure the
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term FLT3-LM (length mutation) seems to be more adequate.
Prognosis An unfavourable impact on prognosis especially a high relapse
rate of the FLT3-LM has been shown by many study groups.
Patients with loss of the wildtype allele have an even worse
prognosis than the mutated with retention of the wildtype
allele. Perspective : It is of special interest that this mutation
allows to perform PCR-based minimal residual disease
detection in a high number of these high risk AML patients.
Cytogenetics FLT3-LM are highly correlated with a) normal karyotype,
b) t(15;17)(q25;q21)
c) CYTOGENETICS Perspective: It is of special interest that
this mutation allows to perform PCR-based minimal residual
disease detection in a high number of these high risk AML
patients.
Oncogenesis This mutation leads to constitutive ligand independent
autophosphorylation of the receptor. The FLT3-LM vary in size
and position in a nearly patient specific manner. Overall the
aberrant structure of the juxtamembrane domain disrupts a
negative regulatory domain, which leads to the constitutive
receptor activation. Several Groups have reported qualitative
differences in the intracellular signals provided by wild type
and mutated receptors.Mutated receptor weakly works through
MAP kinase and Akt but instead through strong and
constitutively activated STAT5.
Entity FLT3 Tyrosine Kinase Domain Mutation (FLT3-TKD)
Disease In the second tyrosine kinase domain point mutations and
small deletions mostly of codons 835 and 836, respectively,
can be found in 7-8% of all AML.
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Prognosis No independent impact on prognosis shown yet.
Cytogenetics In contrast to the FLT3-LM they do not seem to be specifically
correlated to a certain AML type.
Oncogenesis These mutations also lead to constitutive autoactivation of the
receptor. It has been suggested that TKD mutation may both
trigger the activation loop and stabilize it in the active state.
Pathways Of Formation And Action Of Flt3 protein
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Fig- Production And Action Of Flt3 protein
FLT3 is a class III receptor tyrosine kinase (RTK) structurally related to the
receptors for platelet derived growth factor (PDGF), colony stimulating factor
1 (CSF1), and KIT ligand (KL).; these RTK contain five immunoglobulin-like
domains in the extracellular region and an intracelular tyrosine kinase
domain splitted in two by a specific hydrophilic insertion (kinase insert);
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immunoprecipitation of the human FLT3 protein results in the appearance of
a minor band of Mr 130 000 and a major band of Mr 155 000/160 000; the
high-molecular-weight band corresponds to the mature, N-glycosylated form,
and the low-molecular-weight band to the immature, high mannose-
containing form; N-linked glycosylations account for 50 000 daltons.
FLT3 expression was described on bone marrow CD34-positive cells,
corresponding to multipotential, myeloid and B-lymphoid progenitor cells,
and on monocytic cells; FLT3 expression is restricted to cells of the fetal liver
expressing high levels of CD34; in addition, the FLT3 protein is expressed on
blast cells from most ANLL and B-ALL.
FLT3 receptor function can be defined by the activity of its ligand (FL); FL is
an early acting factor and supports the survival, proliferation and
differentiation of primitive hemopoietic progenitor cells. Ligand binding to
FLT3 promotes receptor dimerization and subsequent signalling through
posphorylation of multiple cytoplasmatic proteins, including SHC, SHP-2,
SHIP, Cbl, Cbl-b, Gab1 and Gab2, as well as the activation of several
downstream signalling pathways, such as the Ras/Raf/MAPK and PI3 kinase
cascades.
Function: Receptor for the FL cytokine. Has a tyrosine-protein kinase
activity. Catalytic activity: ATP + a protein tyrosine = ADP + protein tyrosine
phosphate.
Similarity: Belongs to the Tyr protein kinase family. CSF-1/PDGF receptor
subfamily. Contains 1 immunoglobulin-like C2-type domain.
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FIG. . Flt3 protein cascade
FMS-related tyrosine kinase 3 (FLT3, also called Flk2), is a member of the
type III receptor tyrosine kinase family, which includes c-Kit, PDGFR and M-CSF receptors. FLT3 is expressed on early hematopoietic progenitor cells and
supports growth and differentiation within the hematopoietic system (1,2).
FLT3 is activated after binding with its ligand FL, which results in a cascade of
tyrosine autophosphorylation and tyrosine phosphorylation of downstream
targets (3). The p85 subunit of PI3 kinase, SHP2, GRB2 and Shc are
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associated with FLT3 after FL stimulation (4-6). Tyr589/591 is located in the
juxtamembrane region of FLT3 and may play an important role in regulation
of FLT3 tyrosine kinase activity. Somatic mutations of FLT3 consisting of
internal tandem duplications (ITDs) occur in 20% of patients with acute
myeloid leukemia
REVIEW OF LITERATURE
Mizuki et-al, 2003 reported The receptor tyrosine kinase Flt3 is expressed
and functionally important in early myeloid progenitor cells and in the majority
of acute myeloid leukemia (AML) blasts. Internal tandem duplications (ITDs) in
the juxtamembrane domain of the receptor occur in 25% of AML cases.
Previously, we have shown that these mutations activate the receptor and
induce leukemic transformation. In this study, we performed genome-wide
parallel expression analyses of 32Dcl3 cells stably transfected with either wild-
type or 3 different ITD isoforms of Flt3. Comparison of microarray expression
analyses revealed that 767 of 6586 genes differed in expression between
FLT3-WT- and FLT3-ITD-expressing cell lines. The target genes of mutationally
activated Flt3 resembled more closely those of the interleukin 3 (IL-3)
receptor than those of ligand-activated Flt3. The serine-threonine kinase Pim-
2 was up-regulated on the mRNA and the protein level in Flt3-ITD-expressing
cells. Further experiments indicated that Pim-2 function was important for
clonal growth of 32D cells. Several genes repressed by the mutations were
found to be involved in myeloid gene regulation. Pu.1 and C/EBPalpha, both
induced by ligand-activation of wild-type Flt3, were suppressed in theirexpression and function by the Flt3 mutations. In conclusion, internal tandem
duplication mutations of Flt3 activate transcriptional programs that partially
mimic IL-3 activity. Interestingly, other parts of the transcriptional program
involve novel, IL-3-independent pathways that antagonize differentiation-
inducing effects of wild-type Flt3. The identification of the transcriptional
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program induced by ITD mutations should ease the development of specific
therapies.
Steffen et-al, 2005 reported the description of the molecular pathogenesis of
acute myeloid leukemias (AML) has seen dramatic progress over the last
years. Two major types of genetic events have been described that are crucial
for leukemic transformation: alterations in myeloid transcription factors
governing hematopoietic differentiation and activating mutations of signal
transduction intermediates. These processes are highly interdependent, since
the molecular events changing the transcriptional control in hematopoietic
progenitor cells modify the composition of signal transduction molecules
available for growth factor receptors, while the activating mutations in signal
transduction molecules induce alterations in the activity and expression of
several transcription factors that are crucial for normal myeloid differentiation.
The purpose of this article is to review the current literature describing these
genetic events, their biological consequences and their clinical implications. As
the article will show, the recent description of several critical transforming
mutations in AML may soon give rise to more efficient and less toxic
molecularly targeted therapies of this deadly disease.
Schessl ,et-al, 2005 work showed that The molecular characterization of
leukemia has demonstrated that genetic alterations in the leukemic clone
frequently fall into 2 classes, those affecting transcription factors (e.g., AML1-
ETO) and mutations affecting genes involved in signal transduction (e.g.,
activating mutations of FLT3 and KIT). This finding has favored a model of
leukemogenesis in which the collaboration of these 2 classes of genetic
alterations is necessary for the malignant transformation of hematopoietic
progenitor cells. The model is supported by experimental data indicating that
AML1-ETO and FLT3 length mutation (FLT3-LM), 2 of the most frequent
genetic alterations in AML, are both insufficient on their own to cause leukemia
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in animal models. Here we report that AML1-ETO collaborates with FLT3-LM in
inducing acute leukemia in a murine BM transplantation model. Moreover, in a
series of 135 patients with AML1-ETO-positive AML, the most frequently
identified class of additional mutations affected genes involved in signal
transduction pathways including FLT3-LM or mutations of KIT and NRAS.
These data support the concept of oncogenic cooperation between AML1-ETO
and a class of activating mutations, recurrently found in patients with t(8;21),
and provide a rationale for therapies targeting signal transduction pathways in
AML1-ETO-positive leukemias.
Stirewalt DL and Radich JP., 2003 work showed Normal haematopoietic
cells use complex systems to control proliferation, differentiation and cell
death. The control of proliferation is, in part, accomplished through the ligand-
induced stimulation of receptor tyrosine kinases, which signal to downstream
effectors through the RAS pathway. Recently, mutations in the FMS-like
tyrosine kinase 3 (FLT3) gene, which encodes a receptor tyrosine kinase, have
been found to be the most common genetic lesion in acute myeloid leukaemia
(AML), occurring in approximately 25% of cases. Exploring the mechanism by
which these FLT3 mutations cause uncontrolled proliferation might lead to a
better understanding of how cells become cancerous and provide insights for
the development of new drugs.
Mizuki et-al, 2000, Their studies were performed to Somatic mutations of
the receptor tyrosine kinase Flt3 consisting of internal tandem duplications
(ITD) occur in 20% of patients with acute myeloid leukemia. They are
associated with a poor prognosis of the disease. In this study, wecharacterized the oncogenic potential and signaling properties of Flt3
mutations. We constructed chimeric molecules that consisted of the murine
Flt3 backbone and a 510-base pair human Flt3 fragment, which contained
either 4 different ITD mutants or the wild-type coding sequence. Flt3
isoforms containing ITD mutations (Flt3-ITD) induced factor-independent
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growth and resistance to radiation-induced apoptosis in 32D cells. Cells
containing Flt3-ITD, but not those containing wild-type Flt3 (Flt3-WT),
formed colonies in methylcellulose. Injection of 32D/Flt3-ITD induced rapid
development of a leukemia-type disease in syngeneic mice. Flt3-ITD
mutations exhibited constitutive autophosphorylation of the immature form
of the Flt3 receptor. Analysis of the involved signal transduction pathways
revealed that Flt3-ITD only slightly activated the MAP kinases Erk1 and 2 and
the protein kinase B (Akt) in the absence of ligand and retained ligand-
induced activation of these enzymes. However, Flt3-ITD led to strong factor-
independent activation of STAT5. The relative importance of the STAT5 and
Ras pathways for ITD-induced colony formation was assessed by transfection
of dominant negative (dn) forms of these proteins: transfection of dnSTAT5
inhibited colony formation by 50%. Despite its weak constitutive activation
by Flt3-ITD, dnRas also strongly inhibited Flt3-ITD-mediated colony
formation. Taken together, Flt3-ITD mutations induce factor-independent
growth and leukemogenesis of 32D cells that are mediated by the Ras and
STAT5 pathways.
Quentmeier et-al, 2003 estimated Internal tandem duplications (ITD) and
D835 point mutations of the receptor tyrosine kinase (RTK) FLT3 are found in
a high proportion of cases with acute myeloid leukemia (AML). These genetic
aberrations may lead to the constitutive activation of the receptor, thus
providing the molecular basis for a persisting growth stimulus. We have
screened 69 AML-derived cell lines for FLT3 mutations. Four of these cell lines
showed ITD of the FLT3 gene, none carried a D835 point mutation. Two cell
lines (MUTZ-11 and MV4-11) expressed exclusively the mutated allele, the
other two cell lines (MOLM-13 and PL-21) displayed a mutated and the wild-
type version of the gene. Although mutationally activated FLT3 is supposed to
substitute for the stimulatory signal of a growth factor, one of these cell lines
(MUTZ-11) was strictly cytokine-dependent. FLT3 transcripts were found in all
four cell lines, but the constitutively phosphorylated receptor protein was
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clearly detectable only in cell line MV4-11, possibly explaining why MUTZ-11
cells were growth-factor dependent. Thus, not all FLT3 ITD-positive cells
express high levels of the active receptor protein, a finding that might be of
relevance for a possible future application of a kinase inhibitor as therapeutic
agent. It had been described that STAT-5 phosphorylation was part of the
FLT3 signalling chain and that STAT-5 molecules were constitutively
phosphorylated in FLT3 ITD-positive cells. Although we observed the
constitutive phosphorylation of STAT-5 molecules in FLT3-mutant cells, FLT3
ligand (FL) did not induce STAT-5 phosphorylation in FLT3 wild-type cells.
These results suggest that the signalling mechanisms of the mutated FL
receptor differ at least to some extent from those conferred by wild-type FLT3.
In conclusion, (1) not all cells with FLT3 ITD express significant amounts of
the mutated receptor protein; (2) signals downstream from wild-type and
mutant FLT3 receptors are not 100% identical; and (3) MV4-11 represents a
model cell line for FLT3 ITD signalling.
Choudhary et-al, 2005 sujjested that Activating mutations of Fms-like
tyrosine kinase 3 (Flt3) are the most common genetic lesions in acute
myeloid leukemia (AML) and are present in approximately one third of AML
patients. The 2 classes of Flt3 mutations are internal tandem duplications in
the juxtamembrane domain and point mutations in the tyrosine kinase
domain. In normal hematopoietic progenitor cells, Flt3 ligand induces the
activation of several downstream signal-transduction mediators, including
phosphoinositol 3-kinases, Src kinases, mitogen-activated protein kinases,
and the phosphorylation of several adaptor proteins. Oncogenic mutations in
Flt3 result in ligand-independent constitutive and deregulated activation of
these signaling pathways. In addition, however, oncogenic mutations of Flt3
also result in the activation of aberrant signaling pathways, including strong
activation of STAT5, induction of STAT target genes, and repression of
myeloid transcription factors c/EBP-3 and Pu.1. Aberrant activation of these
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signaling pathways by oncogenic Flt3 may play a critical role in mutant Flt3-
mediated leukemic transformation.
Moore, et-al, 2007 worked on human leukemogenesis by transduction of
human hematopoietic stem cells (HSC) with genes associated with leukemia
and expressed in leukemic stem cells. METHODS: Constitutive activation of
Flt3 (Flt3-ITD) has been reported in 25 to 30% of patients with acute
myeloid leukemia (AML). Retroviral vectors expressing constitutively
activated Flt3 and STAT5A were used to transduce human cord blood
CD34(+) cells and HSC cell self-renewal and differentiation were evaluated.
RESULTS: We have demonstrated that retroviral transduction of Flt3
mutations into CD34(+) cells enhanced HSC self-renewal as measured in
vitro in competitive stromal coculture and limiting-dilution week-2
cobblestone (CAFC) assays. Enhanced erythropoiesis and decreased
myelopoiesis were noted together with strong activation of STAT5A.
Consequently, transduction studies were undertaken with a constitutively
active mutant of STAT5A (STAT5A[1( *)6]) and here also a marked, selective
expansion of transduced CD34(+) cells was noted, with a massive increase in
self-renewing CAFC detectable at both 2 and 5 weeks of stromal coculture.
Differentiation was biased to erythropoiesis, including erythropoietin
independence, with myeloid maturation inhibition. The observed phenotypic
changes correlated with differential gene expression, with a number of genes
differentially regulated by both the Flt3 and STAT5A mutants. These included
upregulation of genes involved in erythropoiesis and downregulation of genes
involved in myelopoiesis. The phenotype of week-2 self-renewing CAFC also
characterized primary Flt3-ITD(+) AML bone marrow samples. Isolation of
leukemic stem cells (LSC) with a CD34(+), CD38(-), HLA-DR(-) phenotype
was undertaken with Flt3-ITD(+) AML samples resulting in co-purification of
early CAFC. Gene expression of LSC relative to the bulk leukemic population
revealed upregulation of homeobox genes (HOXA9, HOXA5) implicated in
leukemogenesis, and hepatic leukemia factor (HLF) involved in stem cell
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proliferation. CONCLUSION: Myeloid leukemogenesis is a multi-stage process
that can involve constitutively activated receptors and downstream pathways
involving STAT5, HOX genes, and HLF.
Spiekermann, et-al, 2003 indicated that Activating length mutations in the
juxtamembrane domain (FLT3-LM) and mutations in the tyrosine kinase
domain (FLT3-TKD) of FLT3 represent the most frequent genetic alterations
in acute myeloid leukemia (AML). However, the functional role of active FLT3
mutants in primary AML blast cells is not well characterized. EXPERIMENTAL
DESIGN: We analyzed the transforming potential and the signaling of FLT3-
ITD mutants in Ba/F3 cells and in primary AML blasts. RESULTS: FLT3-ITD
mutants induce an autophosphorylation of the receptor, interleukin 3-
independent growth in Ba/F3 cells, and a strong STAT5 and mitogen-
activated protein kinase (MAPK) activation. In contrast to the FLT3-ITD
mutants, the ligand-stimulated FLT3-WT receptor was unable to transduce a
fully proliferative response in Ba/F3 and monocytic OCI-AML5 cells. The
ligand-stimulated FLT3-WT receptor activated AKT and MAPK, but not STAT5.
In primary blast cells from 60 patients with AML, FLT3 was expressed in
91.9% of patients carrying a FLT3-LM/TKD mutation compared with 77.8% in
FLT3-LM/TKD-negative patients. STAT3 and STAT5 were constitutively
activated in 76 and 63% of patients, respectively. In accordance with the
results in Ba/F3 cells, a high FLT3 expression and the presence of a FLT3-LM
was strongly associated with the STAT5 but not with the STAT3 activation in
primary AML blast cells. Moreover, the constitutive tyrosine phosphorylation
of STAT5 was efficiently down-regulated by a FLT3 protein tyrosine kinase
inhibitor in AML cells expressing an active FLT3 mutant. CONCLUSIONS:
Active FLT3 receptor mutants have transforming potential in hematopoietic
cells and induce a strong activation of STAT5 in primary AML cells. The FLT3-
STAT5 pathway contributes to the malignant phenotype and represents a
promising molecular therapeutic target structure in AML.
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MATERIALS AND METHODS
Retrieval of Protein Sequence of Flt3 in Homo sapiens:
Protein sequence of Flt3 in Homo sapiens was done from National Center OfBiotechnology information(www.ncbi.nlm.nih.gov/). The sequence of
protein was in FASTA format :
>gi|406323|emb|CAA81393.1| FLT3 receptor tyrosine kinase precursor
[Homo sapiens]
MPALARDGGQLPLLVVFSAMIFGTITNQDLPVIKCVLINHKNNDSSVGKSSSYPMVSESPEDLGCALRPQ
SSGTVYERAAVEVDVSASITLQVLVDAPGNISCLWVFKHSSLNCQPHFDLQNRGVVSMVILKMTETQAGE
YLLFIQSEATNYTILFTVSIRNTLLYTLRRPYFRKMENQDALVCISESVPEPIVEWVLCDSQGESCKEES
PAVVKKEEKVLHELFGMDIRCCARNELGRECTRLFTIDLNQTPQTTLPQLFLKVGEPLWIRCKAVHVNHG
FGLTWELENKALEEGNYFEMSTYSTNRTMIRILFAFVSSVARNDTGYYTCSSSKHPSQSALVTIVEKGFI
NATNSSEDYEIDQYEEFCFSVRFKAYPQIRCTWTFSRKSFPCEQKGLDNGYSISKFCNHKHQPGEYIFHAENDDAQFTKMFTLNIRRKPQVLAEASASQASCFSDGYPLPSWTWKKCSDKSPNCTEEITEGVWNRKANRK
VFGQWVSSSTLNMSEAIKGFLVKCCAYNSLGTSCETILLNSPGPFPFIQDNISFYATIGVCLLFIVVLTL
LICHKYKKQFRYESQLQMVQVTGSSDNEYFYVDFREYEYDLKWEFPRENLEFGKVLGSGAFGKVMNATAY
GISKTGVSIQVAVKMLKEKADSSEREALMSELKMMTQLGSHENIVNLLGACTLSGPIYLIFEYCCYGDLL
NYLRSKREKFHRTWTEIFKEHNFSFYPTFQSHPNSSMPGSREVQIHPDSDQISGLHGNSFHSEDEIEYEN
QKRLEEEEDLNVLTFEDLLCFAYQVAKGMEFLEFKSCVHRDLAARNVLVTHGKVVKICDFGLARDIMSDS
NYVVRGNARLPVKWMAPESLFEGIYTIKSDVWSYGILLWEIFSLGVNPYPGIPVDANFYKLIQNGFKMDQ
PFYATEEIYIIMQSCWAFDSRKRPSFPNLTSFLGCQLADAEEAMYQNVDGRVSECPHTYQNRRPFSREMD
LGLLSPQAQVEDS
Homology Modelling :
Homology modelling is required when the exact structure of the protein is not
available. The structure of Flt3 was also unavailable, so homology modeling
was required. It is also known as comperative modelling. Here we model the
molecule (protein) from amino acid sequence by following a protocol to
model.The amino acid sequence is query or target sequence. Homology
modeling techniques depend on identificatiction of one or more stuctures
known as template, which resembles the sructure of query sequence. The
sequence alignment and template stucture are used to produce a structural
model of the target. Usually sequence similarity corresponds to high
structural similarity.
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Different softwares are used for Homology Modelling such as SWISS MODEL
SERVER.,CPH MODEL SERVER.,MODELLER etc. In this project Swiss
Model server is used for Homology Modelling. The methodology for
homology modeling with Swiss Model Server is:
BLAST
BLAST (Basic Local Alignment Search Tool),(www.ncbi.nlm.nih.gov/BLAST)is a tool
by which we can find alignment between our query in form of nucleotide or
protein sequence, against the database of BLAST. The results show us the
extent to which our query sequence matches the sequences stored in theBLAST database.In case our sequence is a novel entry ,it does not show any
results. Here I carried out protein-protein BLAST of my query sequence,
against pdb (protein data bank);which consists of amino acid sequences of
the proteins submitted in pdb .The results generated by BLAT were furthur
used for the modeling of the protein. After we get BLAST results we carry out
CLUSTAL W.
CLUSTAL W
CLUSTAL-W (www.ebi.ac.uk/clustalw/) is a multiple sequence alignment
programme for DNA or proteins. It provides multiple sequence alignment
forgiven sequence. It gives the match between the query sequences and
allows us to have the idea of best match between our target sequence and
template. This informationis furthur used in swiss model. Evolutionaryrelationships can be viewed by cladograms or phylograms.
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Swiss Model:
It is totally automated protein structure homology modeling server,
accessible via ExPASy web server or from swiss pdb viewer.
(www.swissmodel.expasy.org//SWISS-MODEL.html).
SWISS MODEL SERVER: It is used for final modeling of protein, using
results of CLUSTAL-W. Basically there are three moes os SWISS MODEL,
which are:
1. First approach mode: it only requires a single amino acid sequence
information as input data. The server automatically selects suitable template.
However the user may specify up to five template structures either fromExPDB library, or opload co-ordinate files. The process starts if atleast one
template sequence has a identity of more than 25% with submitted target
sequence. The reliability of model decreases as sequence identity decreases.
2. Alignment Mode: it is done by submitting a sequence alignment. The ser
predicts the target sequence and the one, which is structurally known protein
FROM ExPDB library. The server builds yhe model according to given
alignment.
3. Project Mode: here user submits a manually optimized modeling request
to SWISS MODEL server The starting moe is a Deep View project file. It
contains superposed template structures and alignment between target and
template. It allows template selection or gap placement in the alignment. It
can also be used to improve the output of first approach mode.
Here alignment mode of SWISS MODEL was used to predict structure of Flt3model.
There are certain steps to be followed in this process, which are:
Retrieval of protein seuence from NCBI in FASTA format.
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Protein BLAST of protein sequence obyained in last step against
pdb(protein data bank).
Selecting the second, third, fourth match results and obtaining their
FASTA format of sequence.
Puting the results obtained in last step alongwith target protein
sequence of protein in a notepad. The sequences obtained in last steo
are pot\entail te,plates.
Open CLUSTAL W page and paste the sequence obtained in last step in
window displayed and submit.
Open SWISS MODEL SERVER page and paste the sequence in window
and submit.
The results are obtained, asve the result file with (.pdb) extension, to
save a pdb file.
Open the saved file with rasmol viewer to view 3-D image of the
modeled protein.
Retrieval of inhibitor against Flt3:
Inhibitor against Flt3 protein retrieved through two major sources.
1. BRENDA (www.brenda.uni-koeln.de) is the main collection of enzyme
functional data available to the scientific community. BRENDA is maintainedand developed at the institute of Biochemistry at the University of Cologne
2. NCBI Pubchem Compound: PubChem Structure Search allows
PubChem Compound Database to be queried using a chemical structure.
Chemical structure queries may be sketched using the PubChem Sketcher.
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You may also specify the structural query input by PubChem Compound
Identifier (CID), SMILES, SMARTS, InChI, Molecular Formula, or by upload of
a supported structure file format.
This standardizing allows NCBI to compute chemical parameters and
similarity relationships between compounds. The compounds are grouped
into levels of chemical similarity from most general to most specific: same
bonding connectivity and any tautomer; same bonding connectivity; same
stereochemistry; same isotopes; and same stereochemistry and isotopes.
PubChem Compound also indexes these chemicals using 34 fields, many of
which represent computed chemical properties such as the number of chiral
centers, the number of hydrogen bond donors/acceptors, molecular formula
and weight, total formal charge, and octanol-water partition coefficients
(XlogP). These groups are provided as Entrez links that allow similar
compounds to be retrieved quickly.
Building of 3d structure (PDB file) of Inhibitors:
2D structure of potent inhibitors are obtained by submitting the CID no tothe NCBIs Pubchem compound and convert it into SDF format then convert it
into PDB format to get the 3D-structure.
Procedure of converting 2D-structure into 3D-structure
1) To select SDF format from NCBI.
Open google and enter NCBI home page.
Choose pubchem compound from search drop-down menu.
Type CID no.
When answers come ,Change display format to SDFand save it .
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To retrieve PDB file of Inhibitors:
2-D structure of protein has been obtained by put the specific CID no. in the
pubchem compound it retrieved the 2-D or SDF file of inhibitor we save it &
will convert this 2-D file in the 3-D file i.e. in the form of PDB file, using
software Babel.
Babel Molecule format Converter:
Babel is a cross-platform program designed to interconvert between many
file formats used in molecular modeling and computational chemistry and
related areas. Babel is a chemical toolbox designed to allowing anyone,
convert, analyze, or store data from molecular modeling, chemistry, solid-
state materials, biochemistry, or related areas.
Procedure to convert the 2-D file in the 3-D file or PDB file
First of all open the Babel page.
Set the parameter for input and output file i.e. SDF for input file
& PDF for output file.
Paste the data of 2-D file in the input section or upload the SDF
file.
Click on the convert file.
The result will show in the output section in the form of PDF file, copy thatdata and paste in the word pad and save that file with (.pdb) extension.
COMPND 1248
HETATM 1 O1 LIG 1 5.411 0.262 0.000 1.00 0.00 O
HETATM 2 O2 LIG 1 8.160 -1.543 0.000 1.00 0.00 O
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HETATM 3 O3 LIG 1 8.160 -3.152 0.000 1.00 0.00 O
HETATM 4 O4 LIG 1 3.579 2.966 0.000 1.00 0.00 O
HETATM 5 O5 LIG 1 2.000 2.653 0.000 1.00 0.00 O
HETATM 6 O6 LIG 1 5.717 2.011 0.000 1.00 0.00 O
HETATM 7 N7 LIG 1 3.682 -1.827 0.000 1.00 0.00 N
HETATM 8 C8 LIG 1 4.588 -1.313 0.000 1.00 0.00 C
HETATM 9 C9 LIG 1 3.682 -2.868 0.000 1.00 0.00 C
HETATM 10 C10 LIG 1 4.600 -0.313 0.000 1.00 0.00 C
HETATM 11 C11 LIG 1 5.482 -1.847 0.000 1.00 0.00 C
HETATM 12 C12 LIG 1 4.588 -3.382 0.000 1.00 0.00 C
HETATM 13 C13 LIG 1 5.482 -2.847 0.000 1.00 0.00 C
HETATM 14 C14 LIG 1 2.682 -1.823 0.000 1.00 0.00 C
HETATM 15 C15 LIG 1 3.185 -0.959 0.000 1.00 0.00 C
HETATM 16 C16 LIG 1 3.802 0.280 0.000 1.00 0.00 C
HETATM 17 C17 LIG 1 6.348 -1.347 0.000 1.00 0.00 C
HETATM 18 C18 LIG 1 6.348 -3.347 0.000 1.00 0.00 C
HETATM 19 C19 LIG 1 4.123 1.227 0.000 1.00 0.00 C
HETATM 20 C20 LIG 1 7.214 -1.847 0.000 1.00 0.00 C
HETATM 21 C21 LIG 1 5.117 1.211 0.000 1.00 0.00 C
HETATM 22 C22 LIG 1 7.214 -2.847 0.000 1.00 0.00 C
HETATM 23 C23 LIG 1 2.821 0.085 0.000 1.00 0.00 C
HETATM 24 C24 LIG 1 3.464 1.979 0.000 1.00 0.00 C
HETATM 25 C25 LIG 1 2.483 1.784 0.000 1.00 0.00 C
HETATM 26 C26 LIG 1 2.162 0.837 0.000 1.00 0.00 C
HETATM 27 C27 LIG 1 8.744 -2.347 0.000 1.00 0.00 C
HETATM 28 C28 LIG 1 2.676 3.382 0.000 1.00 0.00 C
HETATM 29 H8 LIG 1 4.054 -0.998 0.000 1.00 0.00 H
HETATM 30 1H9 LIG 1 3.071 -2.762 0.000 1.00 0.00 H
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HETATM 31 2H9 LIG 1 3.473 -3.452 0.000 1.00 0.00 H
HETATM 32 H10 LIG 1 5.149 -0.601 0.000 1.00 0.00 H
HETATM 33 1H12 LIG 1 4.194 -3.861 0.000 1.00 0.00 H
HETATM 34 2H12 LIG 1 4.993 -3.852 0.000 1.00 0.00 H
HETATM 35 1H14 LIG 1 2.680 -2.443 0.000 1.00 0.00 H
HETATM 36 2H14 LIG 1 2.062 -1.820 0.000 1.00 0.00 H
HETATM 37 3H14 LIG 1 2.684 -1.203 0.000 1.00 0.00 H
HETATM 38 1H15 LIG 1 2.647 -1.266 0.000 1.00 0.00 H
HETATM 39 2H15 LIG 1 2.877 -0.421 0.000 1.00 0.00 H
HETATM 40 3H15 LIG 1 3.724 -0.651 0.000 1.00 0.00 H
HETATM 41 H17 LIG 1 6.348 -0.727 0.000 1.00 0.00 H
HETATM 42 H18 LIG 1 6.348 -3.967 0.000 1.00 0.00 H
HETATM 43 H23 LIG 1 2.621 -0.502 0.000 1.00 0.00 H
HETATM 44 H26 LIG 1 1.554 0.716 0.000 1.00 0.00 H
HETATM 45 1H27 LIG 1 9.205 -2.762 0.000 1.00 0.00 H
HETATM 46 2H27 LIG 1 9.205 -1.933 0.000 1.00 0.00 H
HETATM 47 1H28 LIG 1 2.993 3.915 0.000 1.00 0.00 H
HETATM 48 2H28 LIG 1 2.179 3.753 0.000 1.00 0.00 H
TER 49 LIG 1
CONECT 1 10 21
CONECT 2 20 27
CONECT 3 22 27
CONECT 4 24 28
CONECT 5 25 28
CONECT 6 21 21
CONECT 7 8 9 14 15
CONECT 8 7 10 11 29
CONECT 9 7 12 30 31
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CONECT 10 1 8 16 32
CONECT 11 8 13 17 17
CONECT 12 9 13 33 34
CONECT 13 11 12 18 18
CONECT 14 7 35 36 37
CONECT 15 7 38 39 40
CONECT 16 10 19 19 23
CONECT 17 11 11 20 41
CONECT 18 13 13 22 42
CONECT 19 16 16 21 24
CONECT 20 2 17 22 22
CONECT 21 1 6 6 19
CONECT 22 3 18 20 20
CONECT 23 16 26 26 43
CONECT 24 4 19 25 25
CONECT 25 5 24 24 26
CONECT 26 23 23 25 44
CONECT 27 2 3 45 46
CONECT 28 4 5 47 48
CONECT 29 8
CONECT 30 9
CONECT 31 9
CONECT 32 10
CONECT 33 12
CONECT 34 12
CONECT 35 14
CONECT 36 14
CONECT 37 14
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CONECT 38 15
CONECT 39 15
CONECT 40 15
CONECT 41 17
CONECT 42 18
CONECT 43 23
CONECT 44 26
CONECT 45 27
CONECT 46 27
CONECT 47 28
CONECT 48 28
END
Docking Of Flexible Ligands to the Receptors
For docking the flexible ligands to the receptors following softwares can be used which
are listed below:
SN Name License Term Platform Keyword
1 Autodock Commercial UNIX,LINUX,SGI GA/LGA,MC
2 Affinity Commercial SGI Monte Carlo
method
3 Dock Vision Commercial LINUX.IRIS MC,GA
4 DOT(Daughter
of Turnip)
Free Supercomputers,UNIX
5 Flex X Commercial UNIX Fragnent Based
6 Shape E-mail request UNIX Structure andchemistry of
molecular surface
7 LEAPFROG Commercial SGI ligand design
8 Q site Commercial UNIX,LINUX,SGI Mixed
quantum and
molecular
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mechanics
9 HINT Commercial Windows
2000,SGI,LINUX
Hydropathic
interaction
10 GOLD Free evaluation UNIX GA
Cygwin: It is a collection of free software tools originally developed from
Cygnus solutionsto allow various versions of Microsoft windows to act
similarto a Linux operating system.As Autodock is programmed to run on
Linux operating system,so for those systems which run on windows,cygwin is
a must.It can be freely downloaded from the internet.
AUTODOCK: Autodock is a suite of automated docking tools. It is designed
to predict how small molecules, such as substrates or drug candidates, bind
to a receptor of known 3D structure.AutoDockactually consists of two main
programs: AutoDock performs the docking of the ligand to a set of grids
describing the target protein; Auto Grid pre-calculates these grids. In
additions to using them for docking, the atomic affinity grids can be
visualized. This can help, for example, to guide organic synthetic chemistsdesign better binders.
1.Autogrid.
2.Autodock.
AUTOGRID:
A. Peparing a Ligand for Autodock:
In autodock page,go to ligand and in it click on input.
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In input click on open AD3.
Go to your folder and open the (.pdb) file of the inhibitor.
Go to Ligand again in autodock window and in it Torsion Tree andclick ondetect route.
In Ligand select Torsion Tree and click on Choose Torsionand click
on done.
Go to Ligand again and select Torsion Tree and select Set number
Of Torsions.The number of torsions
Set number of torsions less than or equal to 6 and click on Dismiss.
Go to Logand and in it to Output and then click on Save As
PDBQ.Then go to your folder a save your this file as (inhibitor
name.out.pdbq).
B. Preparing A Macromolecule For Autodock:
Go to Grid and in it click on Macromolecule and in it click on OpenAG3.
Open the (.pdb) file from your folder and click on OK.
Now save this file as protein name.pdbqs.
Come back to autodock window and press shift key+n to visualize the
protein on screen.
C. Preparing The Grid Parameter File:
Go to Grid and select Set Map Types and in it select Choose Ligand
AG3.
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Now select the inhibitor file.
Now click on Ligand and then click on Accept.
Go to Grid and selectGrid Box.
On the window that opens,set x,y,z co-ordinate axes so that the
macromolecule is completely covered.You can rotate the molecule by
pressing shift+right click of mouse.
On the same window,click on File and there click on Saving CurrentSetting.
Go to Grid again and in it go to Output,then click on SaveGPF(AG3)
Save this file in your folder as protein name.gpf.
Go to Grid and in it go to Edit Grid and clik it,then click on Accept.
Go to your folder and copy the path of your folder eg(C:\probir) and
open the (.gpf) file in your folder wit wordpad and paste this path
followed by \ on left of wherever you find protein name in this file.It
is to be noted that there should not be any gap between path and
protein name.
Click on Save in this window after you finish.
AUTODOCK:
A. Startimg Autodogrid:
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Go to Run and in it click on Run Autogrid.
On the window that opens on the first Browse option click and select
autogrid.exe file.
Then in second Browse option click and go to your folder and open
the (.gpf) file.
Back to autogrid, select the entire bottom line(i.e. the path) of the
Browse window and press cntrl+c.
Open Cygwin and in it go to Edit and Paste the path copied and
press Enter.
B. Preparing A docking Parameter For Autodock:
Click on Docking on the the autodock window.
In it select on Macromolecule and in it click on Choose AD3.
Select your protein in the window that opens and click on OK.
Click on Select Macromolecule and click on window that opens twice.
Go to Docking and in it go to Ligand and in it click on Choose
(AD3).
On the window that opens click and select the ligand.
Click on Select Ligand and click on Accept on the window.
Go to docking again and selectSearch Parameterand in it click on
Genetic Algorithm.Click Accept on yhe window that opens.
Go to Docking again and in it click on Docking Parameters.Click on
Accept on the window that opens.
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Go to Docking again and in it select Output and in it click on
Lamarkian GA(AD3).Then go to your folder and save the file as
(inhibitor name.dpf).
Go to your folder and copy the path of (.dpf) file.
Open this (.dpf) file in wordpad and paste the copied path
everywhere you find inhibitor name,followed by \ i.e.path+\,on left
of the inhibitor name.Continue till you reach on yhe line with move
and here do the same.
Save the page.
C. Starting Autodock:
Back to autodock,click on Run and in it click on Run Autodock.
On the window that opens on first Browse option,click it and open the
autodock.exe file.
On the second Browse option,click and go to your folder and open the
the (.dpf) file.
Come back to Browse window and copy the path at the bottom by
selecting it and then pressing cntrl+c.
Open Cygwin and go to Edit and click on Paste .
Press Enter to run Autodock.
D. Analysing Autodock Results:
Click on Analyse on the autodock window and in it click on Docking.
Go to your folder and open the (.dlg) file. And click ok.
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Now go to Macromolecule in Analyse and go to your folder and open
the (.pdbqs) file of the target.
Press Shift+n to visualize the macromolecule on the screen.
Go to Conformation in Analyse and in it click on Load,a box
appears.
Go to Conformation again and click on Play,another window opens.
In the Play window,click on (&) sign ,a new window opens.
Now on the first window that came on pressing Load go to its second
line and click
It shows the docking energy and various other docking
parameters.Note it.The more negative dock energy,the better inhibitor
is;positive dock energies(if found) are neglected as it is not a proper
result.
Now go to the window which came in Play,in it click on the direction
buttons to analyse each of the ten active sites.It gives information
about various parameters on a particular active site.Here we also
search for hydrogen bonds which are shown on the bottom of that
window and we can also find the amino acid to which the ligand binds.
Expand the bottom of the box which we got on clicking Load.
Click on Write Current Coords and go to your folder and save this file
as (inhibitor.docked.pdbq).
Record the results.
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PMV (Python Molecular Viewer):
Python Molecular Viewer is a tool to view the binding of hydrogen bonds in
the target molecule.It helps to visualise and analyse the hudrogen bonds.The
process of operation of PMV is enlisted below:
Procedure For Operation Of PMV:
Open PMV.
Go to File and click on Browse Command.
In the window that opens,click on pmv
In the adjacent window click on trace command,then click on
Load.Again in the adjacent window of pmv click on hbond command
and load this too.
Go to file in PMV and click on Read Molecule nad go to your folder and
open (protein name.pdbqs) file.
Go to Compute and in it go to Trace.
Here click on Compute Extrude Trace.
Go to color and click on choose color.
In the that opens click on CAT race and click ok.
In the next window which opens, choose any color of your choice and
click on Dismiss.
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Go to Display of PMV and click on Display.
In the next window click on undisplay and click ok.
Go to Select and I it click on Select From String.
In the window that opens in the box where Residue Number is written
enter the residue with its number which was noted from Analyse of
autodock. In the place where atom type is given type *.
Click on Add.
Click on Dismiss.
Go to Display and in it click on cpk.
In the window that opens adjust the Scale Factor to 0.7 and Sphere
Quality to 15,by moving the mouse across the wheels.
Click ok.
Go to Color and click on By Atom Type.
Click cpk in the window that opens.
Click ok.
Go to File and in it go to Read Molecule.
By last step go to your folder and open the (inhibitor.docked.pdbq) file
and open it.
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Go to Select and in it click on Direct Select.
In the window that opens click on Molecule and in it click on your
macromolecule.
Click on Molecule again and now click on the ligand or the inhibitor.
Click on Dismiss.
Go to Display.
In it click on Stick and Balls.
In the window that opens set Stick Quality to 15 and set Ball
Quality to 15.
Click ok.
Go to Color and click on By Atom Type.
In the next window click on Stick and Balls.
Click ok.
Go to Hydrogen Bond.
In it go to Build.
In it click on Set Parms+Build.
In the window that opens click on specify two sets.
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In the next window click on,in the top list under Molecule List click it
and select macromolecule.
I the bottom Molecule List,click it and select the ligand.
Click ok.
Go to H bond and in it click on Display.
In it click on as lines.
Click Dismiss in the window that opens.
Again go to Display and click on Cylinders.
In the window that opens adjust bond length and bond radius of the
hydrogen bond by using mouse,to a suitable size.
Go to Dj vu GUI and click on camera in the lower window.
On the window which lengthens, click on Set Background Color.
Click on SW and then click on S.
Go to File of PMV and click on save as.
In the window that opens click on Browse and go to your folder and
save the picture as (protein.tif).
RESULTS AND DISCUSSION
Retrieval of protein sequence of Flt3
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>gi|406323|emb|CAA81393.1| FLT3 receptor tyrosine kinase precursor
[Homo sapiens]
MPALARDGGQLPLLVVFSAMIFGTITNQDLPVIKCVLINHKNNDSSVGKSSSYPMVSESPEDLGCALRPQ
SSGTVYERAAVEVDVSASITLQVLVDAPGNISCLWVFKHSSLNCQPHFDLQNRGVVSMVILKMTETQAGE
YLLFIQSEATNYTILFTVSIRNTLLYTLRRPYFRKMENQDALVCISESVPEPIVEWVLCDSQGESCKEES
PAVVKKEEKVLHELFGMDIRCCARNELGRECTRLFTIDLNQTPQTTLPQLFLKVGEPLWIRCKAVHVNHG
FGLTWELENKALEEGNYFEMSTYSTNRTMIRILFAFVSSVARNDTGYYTCSSSKHPSQSALVTIVEKGFI
NATNSSEDYEIDQYEEFCFSVRFKAYPQIRCTWTFSRKSFPCEQKGLDNGYSISKFCNHKHQPGEYIFHA
ENDDAQFTKMFTLNIRRKPQVLAEASASQASCFSDGYPLPSWTWKKCSDKSPNCTEEITEGVWNRKANRK
VFGQWVSSSTLNMSEAIKGFLVKCCAYNSLGTSCETILLNSPGPFPFIQDNISFYATIGVCLLFIVVLTL
LICHKYKKQFRYESQLQMVQVTGSSDNEYFYVDFREYEYDLKWEFPRENLEFGKVLGSGAFGKVMNATAY
GISKTGVSIQVAVKMLKEKADSSEREALMSELKMMTQLGSHENIVNLLGACTLSGPIYLIFEYCCYGDLL
NYLRSKREKFHRTWTEIFKEHNFSFYPTFQSHPNSSMPGSREVQIHPDSDQISGLHGNSFHSEDEIEYEN
QKRLEEEEDLNVLTFEDLLCFAYQVAKGMEFLEFKSCVHRDLAARNVLVTHGKVVKICDFGLARDIMSDS
NYVVRGNARLPVKWMAPESLFEGIYTIKSDVWSYGILLWEIFSLGVNPYPGIPVDANFYKLIQNGFKMDQ
PFYATEEIYIIMQSCWAFDSRKRPSFPNLTSFLGCQLADAEEAMYQNVDGRVSECPHTYQNRRPFSREMD
LGLLSPQAQVEDS
Retrieval of structure of FLT3 protein.
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BLAST Result:-
Distribution of 174 Blast Hits on the Query Sequence
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Fig4.1: BLAST RESULT
ClustalW Results:
Results of search
Number of sequences 4
434
http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#6435671http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#6435671http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#119389607http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#119389607http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158431054http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158431054http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#126030689http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#126030689http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#88192844http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#88192844http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#109157762http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#109157762http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#30749935http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#30749935http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#93279684http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#93279684http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#126030685http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#126030685http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#30749934http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#30749934http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#126030694http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#126030694http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#149241245http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#149241245http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#114794378http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#114794378http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158431485http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158431485http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#109157754http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#109157754http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158430354http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158430354http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#10835731http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#10835731http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#30750130http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#17943043http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#146386625http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#20663951http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#28373614http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#114794791http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#114794791http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#34811267http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#40889699http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#114794793http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#114794793http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#2780855http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#114794789http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#114794789http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#157831492http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#13399500http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#145580114http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#15988250http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158429514http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158429514http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#22218646http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#22218646http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158429549http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158429549http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158429593http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158429593http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158429562http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158429562http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158429508http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158429587http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158429510http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158429233http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158429233http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158429585http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#50513700http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#50513700http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#50513701http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#50513701http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#34810084http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#34810084http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#119390020http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#119390020http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#126031591http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#126031591http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#2392334http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#158429479http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#7546569http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#75765648http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#145580440http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#145580439http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#71041982http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#119390010http://www.ncbi.nlm.nih.gov/blast/Blast.cgi#425435658/8/2019 Leukemia Project
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gi|119390010|pdb|2I0V|A --------------------------------------------------
gi|71041982|pdb|1Y6A|A --------------------------------------------------
gi|406323|emb|CAA81393.1| QTPQTTLPQLFLKVGEPLWIRCKAVHVNHGFGLTWELENKALEEGNYFEM 300
gi|42543565|pdb|1RJB|A --------------------------------------------------
gi|119390010|pdb|2I0V|A --------------------------------------------------
gi|71041982|pdb|1Y6A|A --------------------------------------------------
gi|406323|emb|CAA81393.1| STYSTNRTMIRILFAFVSSVARNDTGYYTCSSSKHPSQSALVTIVEKGFI 350
gi|42543565|pdb|1RJB|A --------------------------------------------------
gi|119390010|pdb|2I0V|A --------------------------------------------------
gi|71041982|pdb|1Y6A|A --------------------------------------------------
gi|406323|emb|CAA81393.1| NATNSSEDYEIDQYEEFCFSVRFKAYPQIRCTWTFSRKSFPCEQKGLDNG 400
gi|42543565|pdb|1RJB|A --------------------------------------------------
gi|119390010|pdb|2I0V|A --------------------------------------------------
gi|71041982|pdb|1Y6A|A --------------------------------------------------
gi|406323|emb|CAA81393.1| YSISKFCNHKHQPGEYIFHAENDDAQFTKMFTLNIRRKPQVLAEASASQA 450
gi|42543565|pdb|1RJB|A --------------------------------------------------
gi|119390010|pdb|2I0V|A --------------------------------------------------
gi|71041982|pdb|1Y6A|A --------------------------------------------------
gi|406323|emb|CAA81393.1| SCFSDGYPLPSWTWKKCSDKSPNCTEEITEGVWNRKANRKVFGQWVSSST 500
gi|42543565|pdb|1RJB|A --------------------------------------------------
gi|119390010|pdb|2I0V|A --------------------------------------------------
gi|71041982|pdb|1Y6A|A --------------------------------------------------
gi|406323|emb|CAA81393.1| LNMSEAIKGFLVKCCAYNSLGTSCETILLNSPGPFPFIQDNISFYATIGV 550
gi|42543565|pdb|1RJB|A --------------------------------------------------
gi|119390010|pdb|2I0V|A --------------------------------------------------
gi|71041982|pdb|1Y6A|A --------------------------------------------------
gi|406323|emb|CAA81393.1| CLLFIVVLTLLICHKYKKQFRYESQLQMVQVTGSSDNEYFYVDFREYEYD 600
gi|42543565|pdb|1RJB|A -------------HKYKKQFRYESQLQMVQVTGSSDNEYFYVDFREYEYD 37
gi|119390010|pdb|2I0V|A ----------GVDYKYKQKPKYQVRWKIIESYEG--NSYTFIDPTQLPYN 38gi|71041982|pdb|1Y6A|A --------------MDPDELPLDEHCERLPYDAS---------------- 20
.: : : : : .
gi|406323|emb|CAA81393.1| LKWEFPRENLEFGKVLGSGAFGKVMNATAYGISKTGVSIQVAVKMLKEKA 650
gi|42543565|pdb|1RJB|A LKWEFPRENLEFGKVLGSGAFGKVMNATAYGISKTGVSIQVAVKMLKEKA 87
gi|119390010|pdb|2I0V|A EKWEFPRNNLQFGKTLGAGAFGKVVEATAFGLGKEDAVLKVAVKMLKSTA 88
gi|71041982|pdb|1Y6A|A -KWEFPRDRLKLGKPLGRGAFGQVIEADAFGIDKTATCRTVAVKMLKEGA 69
******:.*::** ** ****:*::* *:*:.* . *******. *
gi|406323|emb|CAA81393.1| DSSEREALMSELKMMTQLGSHENIVNLLGACT-LSGPIYLIFEYCCYGDL 699
gi|42543565|pdb|1RJB|A DSSEREALMSELKMMTQLGSHENIVNLLGACT-LSGPIYLIFEYCCYGDL 136
gi|119390010|pdb|2I0V|A HADEKEALMSELKIMSHLGQHENIVNLLGACT-HGGPVLVITEYCCYGDL 137
gi|71041982|pdb|1Y6A|A THSEHRALMSELKILIHIGHHLNVVNLLGACTKPGGPLMVIVEFCKFGNL 119
.*:.*******:: ::* * *:******** .**: :* *:* :*:*
gi|406323|emb|CAA81393.1| LNYLRSKREKFHRTWTEIFKEHNFSFYPTFQSHPNSSMPGSREVQIHPDS 749
gi|42543565|pdb|1RJB|A LNYLRSKREKFS-------------------------------------- 148gi|119390010|pdb|2I0V|A LNFLRRKR------------------------------------------ 145
gi|71041982|pdb|1Y6A|A STYLRSKRNEFVPYKTKGARFRQGKDYVGAIPVDLKRRLDSITSSQSSAS 169
.:** **
gi|406323|emb|CAA81393.1| DQISGLHGNSFHSEDEIEYENQKRLEEEEDLNVLTFEDLLCFAYQVAKGM 799
gi|42543565|pdb|1RJB|A -------------EDEIEYENQKRLEEEEDLNVLTFEDLLCFAYQVAKGM 185
gi|119390010|pdb|2I0V|A -------------PPGLEYSYNPSHNPEE---QLSSRDLLHFSSQVAQGM 179
gi|71041982|pdb|1Y6A|A SG--------FVEEKSLSDVEEEEAPEDLYKDFLTLEHLICYSFQVAKGM 211
:. : : *: ..*: :: ***:**
gi|406323|emb|CAA81393.1| EFLEFKSCVHRDLAARNVLVTHGKVVKICDFGLARDIMSDSNYVVRGNAR 849
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gi|42543565|pdb|1RJB|A EFLEFKSCVHRDLAARNVLVTHGKVVKICDFGLARDIMSDSNYVVRGNAR 235
gi|119390010|pdb|2I0V|A AFLASKNCIHRDVAARNVLLTNGHVAKIGDFGLARDIMNDSNYIVKGNAR 229
gi|71041982|pdb|1Y6A|A EFLASRKCIHRDLAARNILLSEKNVVKICDFGLARDIYKDPDYVRKGDAR 261
** :.*:***:****:*::. :*.** ******** .*.:*: :*:**
gi|406323|emb|CAA81393.1| LPVKWMAPESLFEGIYTIKSDVWSYGILLWEIFSLGVNPYPGIPVDANFY 899
gi|42543565|pdb|1RJB|A LPVKWMAPESLFEGIYTIKSDVWSYGILLWEIFSLGVNPYPGIPVDANFY 285
gi|119390010|pdb|2I0V|A LPVKWMAPESIFDCVYTVQSDVWSYGILLWEIFSLGLNPYPGILVNSKFY 279
gi|71041982|pdb|1Y6A|A LPLKWMAPETIFDRVYTIQSDVWSFGVLLWEIFSLGASPYPGVKIDEEFC 311
**:******::*: :**::*****:*:********* .****: :: :*
gi|406323|emb|CAA81393.1| KLIQNGFKMDQPFYATEEIYIIMQSCWAFDSRKRPSFPNLTSFLGCQLAD 949
gi|42543565|pdb|1RJB|A KLIQNGFKMDQPFYATEEIYIIMQSCWAFDSRKRPSFPNLTSFLGCQLAD 335
gi|119390010|pdb|2I0V|A KLVKDGYQMAQPAFAPKNIYSIMQACWALEPTHRPTFQQICSFLQEQAQE 329
gi|71041982|pdb|1Y6A|A RRLKEGTRMRAPDYTTPEMYQTMLDCWHGEPSQRPTFSELVEHLGNLLQA 361
: :::* :* * ::. ::* * ** :. :**:* :: ..*
gi|406323|emb|CAA81393.1| AEEAMYQNVDGRVSECPHTYQNRRPFSREMDLGLLSPQAQVEDS 993
gi|42543565|pdb|1RJB|A AEEAMYQNV----------------------------------- 344
gi|119390010|pdb|2I0V|A DRRERD-------------------------------------- 335
gi|71041982|pdb|1Y6A|A NAQQD--------------------------------------- 366
SWISS MODEL Result: _________________
CLUSTAL W(1.81) multiple sequence alignment
Target/1-495 MRGARGAWDFLCVLLLLLRVQTGSSQPSVSPGEPSPPSIHPGKSDLIVRVGDEIRLLCTD
Template/1-495 ------------------------------------------------------------
Target/1-495 PGFVKWTFEILDETNENKQNEWITEKAEATNTGKYTCTNKHGLSNSIYVFVRDPAKLFLV
Template/1-495 ---------------------------------------YESQLQMVQVTGSSDNEYFYV
.. : : * . : * *
Target/1-495 DRSLYGKEDNDTLVRCPLTDPEVTNYSLKGCQGKPLPKDLRFIPDPKAGIMIKSVKRAYH
Template/1-495 DFREYEYDLKWEFPRENLEFGKVLGSGAFGKVMNATAYGISKTGVSIQVAVKMLKER---
* * : : : * * :* . . * :. . .: . : :*
Target/1-495 RLCLHCSVDQEGKSVLSEKFILKVRPAFKAVPVVS-VSKASYLLREGEEFTVTCTIKDVS
Template/1-495 ---EALMSELKMMTQLGSHENIVN-----------LLGACTLSGPIYLIFEYCCYGDLLN
: : : *..: : :. .: * * . :.
Target/1-495 SSVYSTWKRENSQTKLQEKYNSWHHGDFNYERQATLTISSARVNDSGVFMCYANNTFGSA
Template/1-495 YLRSKREKFL---------------------TFEDLLCFAYQVAKGMEFLEFKS--CVHR
. * * : :* .. *: : .
Target/1-495 NVTTTLEVVDKGFINIFPMINTTVFVNDGENVDLIVEYEAFPKPEHQQWIYMNRTFTDKW
Template/1-495 DLAARNVLVTHGKVVKICDFGLARDIMS-DSNYVVRGNARLPVKWMAPESLFEGIYTIKS
:::: :* :* : : :. : : . :. :: :* :: :* *
Target/1-495 EDYPKSENESNIRYVSELHLTRLKGTEGGTYTFLVSNSDVNAAIAFNVYVNTKPEILTYD
Template/1-495 DVWSYG---------------------------------ILLWEIFSLGVNPYP------
: :. . : *.: **. *
Target/1-495 RLVNGMLQCVAAGFPEPTIDWYFCPGTEQRCSASVLPVDVQTLNSSGPPFGKLVVQSSID
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TARGET 398 DVNAAIAFNV YVNTKPEILT YDRLVNGMLQ CVAAGFPEPT IDWYFCPGTE
1rjbA 876 -illweifsl gvnpyp---- ---------- ----gipvda nfykliqngf
TARGET hhhhh sss sss hhhhh
1rjbA hhhhhhh hhhhhhhh
TARGET 448 QRCSASVLPV DVQTLNSSGP PFGKLVVQSS IDSSAFKHNG TVECKAY
1rjbA 907 kmdqpfyate eiyiimqscw afdsrkrpsf pnltsflg-- ----cql-
TARGET h hhhhhhhh h hhhhhhh
1rjbA h hhhhhhhhh h hhhhhhhh hh
INHIBITOR TABLE:
Table 4.1 : List of inhibitors against Flt3 protein
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Inhibi
torname
Chemical
formula
Molecul
arweight
Chemical structure IUPAC
name
Ag1296
C16H14N2O2 266.29456g/mol
6,7-dimethoxy-2-phenylquinoxaline
Cep701
C26H21N3O4 439.46264g/mol
Cep701.
Mln518
C31H42N6O4 562.70298g/mol
4-(6-methoxy-7-(3-piperidin-1-ylpropoxy)quinazolin-4-yl)piperazine-1-carboxylic acid(4-isopropoxyphenyl)amide
494
http://%20void%20window.open%28%27../image/structurefly.cgi?cid=3038522&width=400&height=400%27,%20%27StructureFly%27,%20%27resizable=yes,%20scrollbars=yes,%20WIDTH=620,%20HEIGHT%20=%20620%27)http://%20void%20window.open%28%27../image/structurefly.cgi?cid=126565&width=400&height=400%27,%20%27StructureFly%27,%20%27resizable=yes,%20scrollbars=yes,%20WIDTH=620,%20HEIGHT%20=%20620%27)http://%20void%20window.open%28%27../image/structurefly.cgi?cid=2049&width=400&height=400%27,%20%27StructureFly%27,%20%27resizable=yes,%20scrollbars=yes,%20WIDTH=620,%20HEIGHT%20=%20620%27)8/8/2019 Leukemia Project
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Pkc412
C35H30N4O4
570.637g/mol
Pkc412
Su5614
C15H13ClN2O 272.72952
g/mol
5-Chloro-3-[(3,5-
dimethylpyrrol-2-yl)methylene]-2-
indolinone
Sui C21H20NO6+
382.3866
g/mol
6-(6,6-
dimethyl-7,8-dihydro-5H-[1,3]dioxolo[4,5-g]isoquinolin-6-ium-5-yl)-6H-furo[4,3-g][1,3]benzodioxol-8-one
Table4.4 shows the chemical formula, molecular weight, chemical structure and IUPAC
name of different inhibitors which show interaction with Flt3 protein. The IUPAC name
of the inhibitor is further used in making pdb file of that inhibitor.
Docking of Ligand to Receptor
505
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Fig :Docking result Between Flt3 Proteins Active Site and Inhibitor AG1296
Python Molecular Viewer (PMV) Results:
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Fig :Docking result Between Flt3 Proteins Active Site and Inhibitor CEP701
Python Molecular Viewer (PMV) Results:
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Fig : Docking result Between Flt3 Proteins Active Site and Inhibitor MLN518
Python Molecular Viewer (PMV) Results:
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Fig4:Docking result Between Flt3 Proteins Active Site and Inhibitor PKC412.
Python Molecular Viewer (PMV) Results:
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Fig:Docking result Between Flt3 Proteins Active Site and Inhibitor Su5614.
Python Molecular Viewer (PMV) Results:
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Rational Drug Designing Strategies reduce a lot of time, money and energy
as compared to other hit and trial methods.According to recent trends
mathematical modelling has become very valuable.The use of sophasticated
softwares and tools greatly help in this process, helping furthur development
in research and development in this field. The main concern in AutoDock is
computation of docking energy, which essentially should be less than
zero.The more negative the docking energy, the better it is.
Graphical Representation of Autodoc Result
Fig : Shows the relative docked energies of various inhibitors with the target protein.
From the figure we can conclude that Su5614 has the minimum docked energy,hence
the best inhibitor.
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CONCLUSION
After the project work on rational drug design for flt3,the conclusion is that
out of all the inhibitors chosen for the docking,su5614 emerged to be be the
best inhibitor for the protein flt3.The precise reason for it was its docking
energy which was the lowest(docked energy=-14.74),among all other
inhibitors used.Hence the conclusion is that su5614 is the best inhibitor,for
flt3.Hence the task was completed successfully.
Cancer is a major threat to the worlds health. There are many reasons and
factors responsible for induction of cancer. flt3 is also one of those factors
responsible for the induction of cancer.Basically flt3 is an enzyme present inour body which is an integral part of the inflamatory responses of our
immune system.If due to any reason the secretion of this enzyme crosses a
perticular threshold,it can cause tumor formation.This tumor may under the
influence of mitogens and other carcinogens can cause cancer.The threat if
cancer being cause by flt3 has spread globally and many bio-pharma giants
have launched several medicines eg: Standard induction therapy for acute
myeloid leukemia includes two drugs: An anthracycline (such as daunorubicin
or idarubicin) in combination with the nucleoside analogue, cytosine
arabinoside. The main concern is to reduce the over-expression of flt3 and
not to terminate its secretion completely.There are many inhibitors which are
used for the inhibition of over secretion of flt3.Out of many inhibitors,some
are rejected due to their side effects,as the chemotherapy drugs(such as
daunorubicin or idarubicin) will kill normal bone marrow and leukemic cells
equally, so the most significant side effects besides nausea and vomiting are
a temporary reduction of normal white blood cells, red blood cells, and
platelets. The lack of white cells results in lowered immunity and a high
likelihood of infections. A low platelet count may result in easy bruisability
and spontaneous bleeding. A decrease in the red cell count, termed anemia,
may result in fatigue, shortness of breath, and lack of energy.However there
is no inhibihitor which is fully perfect and without any
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sideeffects.Nevertheless we try to reduce the burden on the general health of
the patient to the maximum extent possible.Hence ,newer drugs are required
which have the same efficacy as the older one but are having fewer side
effects.The intial phase of discovering a new drug nowadays is by using
CADD.This method has greately reduced the time ,energy and money
involved in the traditional methods.After a drug has been designined in-
silico,its furthur verification is done,as stated earlier in laoratories.This
method of using computer to design the drugs has indeed hastened the
process of drug discovery.
Rational Drug Designing Strategies reduce a lot of time ,money and energy
as compared to other hit and trial methods.According to recent trends
mathematical modelling has become very valuable recently.The use of
sophasticated softwares and tools greatly help in this process,helping furthur
development in research and development in this field.
In my project I found su5614 (docking energy= -14.74) as to be the best