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Using AI and machine learning methods to obtain preliminary results in experimental biochemical studies.
Mutagenesis, missense mutations, point mutations
Which type of data is qualitative data?
Examples of direct and inverse correlation between experimental and calculated data.
Let me remind you that dependencies may not always be linear.But it is precisely linear correlation dependencies that are the most visual, understandable and easy to obtain and process data.
Analysis data science
Use AI preliminary research to obtain Experiment data Prognosis.
The level of correlation between the forecast and the results is shown in the graphs.
The level of correlation between the forecast and the results is shown in the graphs.
Data Table of Calculated and Experimental Data for Several Mutations in Alpha Synuclein, with Correlation Levels Indicated.
First example
The obtained correlation graphs for p53 protein.
Correlation graphs between experimental and calculated dates.
Correlation graphs between experimental and calculated dates.
Additional example
Experimental and calculated date
You will receive a preliminary data meaning with a description and value of the quantities, their physical interpretation for a given molecular biological entity.
What should we do first to get a forecast for the experimental data?
Below are some intermediate results. First of all, this is the calculation of the potential energy of interaction between amino acid residues, visually this can be represented as a heat map or Excel tables.
Next, the calculation of the physical parameters of interaction, which are listed below in the figures, is the
In addition, you can also take into account the experimental conditions:
Next, the calculation of the physical parameters of interaction, which are listed below in the figures, is the
- entropy change,
- enthalpy change,
- stability criterion,
- calculated dissociation constants
In addition, you can also take into account the experimental conditions:
- temperature,
- salt solutions,
- denaturing solutions.
Heat map of the potential energy of electrostatic interaction between pairwise amino acid
residues of the wild-type monomeric p53 protein
residues of the wild-type monomeric p53 protein
(b) area of the potential energy of electrostatic interaction
from 129 a.a. till 140 a.a.
from 129 a.a. till 140 a.a.
a section of the three-dimensional structure of the p53 protein (c) indicating the amino acid residues of the selected range from the table of values.
Redistribution of potential energy of interaction of amino acid residues with each other, in missense mutations, mutagenesis
How to get a preliminary analysis?
You can make an order for calculating the effect of selected mutations in the target protein on the affinity of a dimer, tetramer, binding to an antibody or inhibitor.
You are required to specify the PDB file of the protein, or only the amino acid sequence, and then we will assemble the protein from the domains ourselves, specify the numbers and names of the substitutions, list the interactions with other molecules that interest you.
If you have a list of PDB structures that interest you, then press here
If you do not have PDB structures, then you have to press here
You are required to specify the PDB file of the protein, or only the amino acid sequence, and then we will assemble the protein from the domains ourselves, specify the numbers and names of the substitutions, list the interactions with other molecules that interest you.
If you have a list of PDB structures that interest you, then press here
If you do not have PDB structures, then you have to press here
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