Study of P53 protein.
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For the negative set, protein variants that were never found (693 variants) or found only once( 323 variants) in human cancer have been selected (no_cancer p53 variants)
[TP53_PROF:a machine learning model to predict impact of missense mutations inTP53]
A diagram of the calculated values for each set of p53 protein mutations, which we will further analyze.

Fechner Correlation

The FECHNER CORRELATION command calculates the Fechner signs correlation coefficient between all the pairs of variables. Fechner correlation coefficient is used to check relationship for small samples.

How To
Select the variables you want to correlate.
 Pairwise deletion is default for missing values removal (use the MISSING VALUES option in the PREFERENCES window to force casewise deletion).
Matrix with Fechner correlation coefficients between each pair of variables is calculated.
Fechner correlation coefficient is defined by
The fact is that the yi values for Negative Set practically coincide with the obtained average value; as a result of the difference between the average and yi values, we get a very small value tending to zero.
Difference in calculated characteristics for Positive and Negative sets of P53 protein mutations.
To determine the correlation coefficient, we use Boolean variables and the Fechner coefficient.
rb(integr) is a Fechner coefficient
Сalculated data obtained for two sets of mutations. Plot of differential entropy changes for two data sets. The graphs show Boolean variables and the final Fechner coefficient.
The graphs for the derivatives of the ddG value are shown on the graph on the left, the graph on the right shows an area with less data scatter. As can be seen from the graph on the left, the spread of points from the Positive data set is much more significant than from the Negative data set.
In 2018 an estimated 1.7 million patients in the US will be diagnosed with cancer, of these roughly 1.5% will have the p53(Y220C) mutation, or >25,000 patients per year.
Carbazole alkaloids natural products are mostly isolated from higher plants of Rutaceae family and major components of the Clausena genus. With the isolation of carbazole core from coal tar in 1872 and the description of the antimicrobial murrayanine in 1965, the interest on these alkaloids began. Since then, natural-occurring carbazole alkaloids have been reported to exhibit a broad pharmacological profile
Rutaceae family
Over 50% of p53 proteins present missense mutations, generating a defective protein in high levels in cells due to the impairment of MDM2 mediated negative feedback, which is responsible for p53 degradation The tumor cell growth inhibitory potential of aminocarbazoles was ascertained in human colon adenocarcinoma HCT116 and melanoma A375 cell lines expressing wild-type (wt) p53
PhiKan 083
PhiKan083, an amino derivative of the carbazole, emerged from an in silico screening and was reported as a small molecule for restoration of wild-type like p53 conformation by targeting Y220 mutation. This derivative 15 established electrostatic and hydrogen bonding interactions with residues of Y220 which gave additional stability to Y220 mutant p53. This particular mutation creates a druggable surface crevice and PhiKan083 binds to this crevice and stabilizes the structure of this mutant p53.

PK083 binds to the Y220C pocket with a dissociation constant (Kd) of 140 μM.

PhiKan 083 binds to the surface cavity and stabilizes Y220C (a p53 mutant), with a Kd of 167 μM.

PhiKan 083 (100 μM) combined with doxorubicin (1 μM) enhances the pro-apoptotic activity in all variants of Ln229 cells (p53wt, p53Y220C, p53G245S, p53R282W).

Can binds to a mutant form increasing the melting
temperature of the protein to slow down its rate of
Structure of the p53 core domain mutant Y220C bound to the stabilizing small-molecule drug PhiKan083
Comparative calculated graphs of the measure of change in differential entropy for various structures of the P53 protein, taking into account Positive mutations
Enlarged area of the comparison graph in the area of greatest change
Calculation graphs for various physical quantities taking into account mutations in the p53 protein
Three-dimensional structure of the p53 protein indicating the amino acid residues, the replacement of which significantly affects the change in the calculated physical parameters
Our research team is interested in Positive mutations that exhibit higher affinity for a small molecule inhibitor.
We will select Positive mutations for which the calculated physical quantities will be as follows:
a decrease in the values of Kd and lg(cond(W)), as well as a negative entropy value TdH
The second important aspect of the study is the analysis of structure changes by analyzing the calculated data for various mutations.
PK9318, one of the most potent binders, restored p53 signaling in the liver cancer cell line HUH-7 with homozygous Y220C mutation.
PK9318 significantly slowed down aggregation in a concentration-dependent manner, with an approximately sixfold lower initial aggregation rate at a compound concentration of 30 μM, corresponding to a 1:10 protein–ligand ratio

The highest affinity in this second-generation series was observed with a C2-linked furan (PK9320) or thiophene (PK9318) moiety, with KDs of 4.0 and 2.6 μM, respectively. Improved affinities were accompanied by a substantial increase in protein
p53 cancer mutant Y220C in complex with small-molecule stabilizer Pk9318
PK9328, one of the most potent binders, restored p53 signaling in the liver cancer cell line HUH-7 with homozygous Y220C mutation.
PK9328 binds to the Y220C pocket with high affinity
(Kd = 2 μM) and induces a thermal shift (ΔTm) to the protein melting temperature of over 3°C (250 μM [ligand]). It also reduces p53 aggregation in vitro and induces selective cell viability reduction of cancer cell lines HUH-7 (p53-Y220C) and NUGC-3 (p53-Y220C) versus controls HUH7-F1 p53-Y220C KO) and NUGC-4 (p53-WT), although only within a narrow concentration range
Structure of the p53 cancer mutant Y220C in complex with small-molecule stabilizer PK9328
No ZN atom
Calculation diagram of a monomer with one chemical molecule
The three-dimensional diagram of the P53 protein contains the indicated amino acid residues with the largest difference in the calculated data for two similar small chemical molecules
the introduction of a bromine in the first step
already significantly increased binding affinity ca. tenfold, from 125 to 14 μM, for the bromocarbazole PK9284
the Y220C-PK9284 complex shows that adding a bromine results in new hydrophobic interactions
in subsite two while retaining the overall binding mode of the carbazole
Curiosity about life in all its aspects, I think, is still the secret of great creative people.
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The calculated graphs represent the difference obtained for calculations made with and without taking into account the zinc atom in the P53 protein structure
Significant differences in the calculated data are observed for mutations in the region where the zinc atom is located
ZN atom
Calculation diagram of a monomer with two chemical small molecules.
P53 monomer
Benzothiazoles (BTAs) are an important class of bicyclic heterocycles that play a key role in the design of biologically active compounds. At the moment, due to the threat of outbreaks of epidemics associated with the emergence and spread of various viruses (Zika, Lassa, SARS-Cov, etc.), modern research and development in medicinal chemistry and pharmacology based on benzothiazole derivatives have become especially relevant.

Mb710, an aminobenzothiazole derivative, is a stabilizer of oncogenic p53 mutation Y220C. MB710 binds tightly to the Y220C pocket and stabilizes p53-Y220C, with a Kd of 4.1 μM. MB710 shows anticancer activity in p53-Y220C cell lines.

Binds tightly to the pocket of Y220C mutant and
stabilizes p53-Y220C in vitro

p53 cancer mutant Y220C in complex with compound Mb710
calculated data: TdH
Between the p53 Core Domain with small inhibitors
Iodophenol derivative
2-Iodophenol (o-iodophenol) is an aromatic organic compound with the formula IC6H4OH. It is a pale yellow solid that melts near room temperature. It undergoes a variety of coupling reactions in which the iodine substituent is replaced by a new carbon group ortho to the hydroxy group of the phenol, which can be followed by cyclization to form heterocycles

Pk5196 , which displays a Kd of 10 μM and raises the Tm of the protein by almost 4 °C under saturating conditions

Structure of the p53 core domain mutant Y220C bound to the stabilizing small molecule PhiKan5196
It has been demonstrated that PK5174, a related substance, can stop Y220C from aggregating,inhibit p53 aggregation via increasing thermal stability and preventing protein unfolding.
PK5174 is a noteworthy compound with good affinity for the Y220C mutant p53 that inhibits its aggregation by acting on specific points in the p53 core domain . Interestingly, in this compound the ethynyl group is a nonclassical bioisostere to iodine, forming halogen bonds within the protein pocket [Recent Synthetic Approaches towards Small Molecule Reactivators of p53]

Structure of the p53 core domain mutant Y220C bound to the stabilizing small molecule PhiKan5174
Comparison of the results obtained for various small chemical molecules when binding to the P53 protein
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  • The body converts inorganic arsenic into the breakdown product (metabolite) called dimethylarsinic acid (DMA). DMA is also found in such foods as fish, poultry, fruits and grains. NHANES results found DMA and arsenobetaine to be the major components of urinary total arsenic levels. Arsenobetaine is a non-toxic inorganic arsenic form that comes from fish and seafood.
Finding measurable amounts of arsenic in urine does not mean those levels cause an adverse health effect. Biomonitoring studies on levels of arsenic provide physicians and public health officials with reference values. These reference values help experts determine if people have been exposed to higher levels of arsenic than are found in the general population. Biomonitoring data can also help scientists plan and conduct research on exposure and health effects.

PDB: 7V97
Arsenic-bound p53 DNA-binding domain mutant V272M

iASPP, a member of the ASPP (Ankyrin repeat domain, SH3 domain and Proline rich sequence containing Protein) family of proteins , binds the DNA binding domain of p53 and regulates its target selective transcription. In vitro and xenograft studies have shown that iASPP has pro-proliferative and chemoresistant properties. These observations led to the hypothesis that iASPP deficiency would enhance WT p53 activity to inhibit tumorigenesis


Графики полученные для позитивного и негативного набора Р53 мутаций.
Графики наглядно представляют полученную разницу для негативного набора и позитивного набора р53 мутаций при расчете различных физических параметров.
Graph of physical quantities for two sets of mutations in the P53 protein: a negative set of mutations and a positive set of mutations.

Different physical characteristics have different probabilities in determining the nature of the mutation and its subsequent impact on the cellular response.

Correlation between calculated data and RNA expression without dividing into gene groups.

На графике представлен уровень корреляции РНК экспрессии генов при мутациях в Р53 белке и расчетными параметрами, такими, как lg(cond(W)), Wd, lg(Kd), dP. Поскольку экспериментальные данные не разделены на типы генов и содержат общую сумму для общего уровня экспрессии генов, то и какую либо тенденцию выделить среди данных достаточно сложно.

The experimental data obtained earlier provide information about the level of RNA expression in various P53 mutations and the addition of various concentrations of the PAT compound.

The U937 cell library was treated with 0-, 5- and 10-mM PAT for 7 days at 37C, after which the abundance of p53 variants was determined using NGS. PAT treatment preferentially the cells with TS p53 mutations such as V272M but not other mutations such as R273H.

Корреляция между РНК экспрессией и расчетными физическими данными для группы мутаций, выполненных для каждого аминокислотного остатка Р53 белка.

Сводная итоговая таблица для корреляции РНК экспрессии, указывающая прямую и обратную корреляции между РНК экспрессией и расчетными данными для Р53 белка при мутациях в оном.

p53 mutations RNA expressions

More detailed graphs grouped by amino acid residues.

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