Biochemistry Software | Clinical Chemistry

Software that allows you to get preliminary results before conducting a laboratory experiment!

Biochemical Analysis Software

This section provides and describes in detail a numerical method for determining the effect of mutations on binding to small chemical molecules. The method we have developed makes it possible to numerically determine such a parameter as the stability of a complex molecular complex consisting of a protein and a small molecule. Changes in the stability parameter for various oncogenic mutations in proteins upon binding to small chemicals molecules indicates the direction of the change in affinity and can serve as a good predictor, since it will allow the selection of small chemical molecules that increase the affinity for the selected oncogenic mutations in proteins.
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Examples using small molecules are given below

The originality of this article is that the developed biophysical model makes it possible:

To determine the key amino acid residues in the protein complex, which correspond to the maximum values of the potential energy of electrostatic interaction.
To determine the effect of point mutations in peptides on the stability of the resulting biological complexes with protein. To qualitatively determine the range of variation of Kd during point mutations, when peptides bind to the active protein site.
Identifying the change in the physical parameters of binding upon modification of the polypeptide chain of the protein
Taking into account mutations in proteins, the effect of mutations on binding to small chemical molecules, as well as on binding to an antibody
Analyzing the joint binding of two small chemical molecules, thus allowing the resulting complex biological effect of the influences of two chemical molecules on protein binding by observing allosteric binding or competitive inhibition

The method can be used to obtain preliminary results for the following cases:

Identification of key amino acid residues
Alanine scan
Amyloid peptides

Why choose us?

Our software allows you to determine the direction of change in affinity, so you can significantly save on the following experimental methods:
Gel-shift assays
Aanalytical ultracentrifugation
Surface plasmon resonance
Spectroscopic assays
Affinity electrophoresis
Isothermal Calorimetry


Prediction of protein interactions is a very important task for modern proteomics, since such interactions determine the functions of proteins at levels from the cell to the whole organism. For proteins whose structure is known, the search for intermolecular interactions according to known data on the conformation of their tertiary structure reduces to the problem of searching for geometric complementarity of the sections of two interacting molecular surfaces and modelling their contacts, the so-called molecular docking[1].

The problem of molecular docking is the task of a conformational search algorithm, which reduces to a search for the conformational space of the formed biological complex due to the variation of the torsion angles of protein molecules. Modern conformational search algorithms in most cases find conformations that are generally close to the experimentally found structures in a relatively short time. However, there are factors that also have a significant impact on the success of the docking, which are often not taken into account in standard algorithms. One such factor is the conformational mobility of the target protein. The mobility range can be different - beginning with a small "adjustment" of the side chains and ending with scale domain movements [2]. These movements play an important role. At first glance, the most logical solution to this problem is to take into account the mobility of the protein in a docking program. Unfortunately, modern computational tools do not allow such modelling to be performed in an acceptable time frame since a protein molecule is very large, and allowing for mobility over all degrees of freedom can lead to a so-called "combinatorial explosion" (an astronomical increase in the number of possible variants). Only in some programs is there limited mobility of protein binding sites (usually at the level of a small adaptation of conformations of the side chains of the active centre residues).

Another approach to this issue consists in docking the same protein in several conformations, and then selecting the best solutions from each docking run.

The third approach is to find a universal structure of the target protein in which docking would produce fairly good results for different classes of ligands. In this case, the number of "missed" (but correct) solutions decreases, but the number of incorrect options [3] also increases significantly.

It should also be noted that most programs for the theoretical docking of proteins work according to the following principle: one protein is fixed in space, and the second is rotated around it in a variety of ways. At the same time, for each rotation configuration, estimates are made for the evaluation function.

In contrast to the above computer simulation algorithms, mathematical algorithms have been developed in this article that allow determination the stability of different regions of protein complexes by analyzing the potential energy matrix of pairwise electrostatic interaction between different sites of the biological complex.

We applied the method we developed to the following small chemical molecules: erlotinib, gefitinib, CO-1686, imatinib, naquatinib, and as well as the antibody-antigen complex [Fab]2-CD20.
The physically grounded mathematical approach developed in this article, in addition to work on molecular dynamics, will theoretically predict the passage of the biochemical reaction in the selected direction with the given amino acid sequences and identify the stability of different areas of protein complexes by analyzing the potential energy matrix of electrostatic interaction between different sites of the biological complex. In the future, it will allow us to solve fundamental and applied problems of medicine, for example, to develop new drugs and to study the processes occurring in the development of diseases, which are actual problems.
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There are many ways to measure binding affinity and dissociation constants,
such as
- ELISAs gel-shift assays
- analytical ultracentrifugation
- surface plasmon resonance
- spectroscopic assays affinity
- electrophoresis isothermal calorimetry.

You can also measure binding affinity when modifying a molecule as a way to see how changing its binding properties relates to the pathway or process you are studying. Our developed software allows us to determine the direction of the change in affinity during the mutations of amino acid chains during interaction with small chemical molecules.

In this study, we will show how it is possible to determine the range of changes in the affinity of small chemical molecules only using information about the three-dimensional structure of such a complex.

The calculated data, which was obtained using our developed software package and is given in graphs, directly enables us to obtain information about the nature and direction of changes in affinity. Fig.1 shows a joint representation of the experimental graph and the graph of the values of lg(cond(W)), each of which demonstrates the direction of change in the affinity of the dimer complex during mutations in the protein when it binds to a small chemical molecule. In this case, the affinity changes for the two graphs coincide in their direction:
the decrease in affinity is characterized by higher estimated/ experimental values, while the increase in the affinity of the dimer complex is characterized by a lower range of values of both the experimental and calculated values of lg(cond(W)).

Thus, in order to determine the direction of the change in the affinity of the
dimer complex during a mutation in a protein, a laboratory experiment may be conducted, or our developed software package may be used, to obtain the numerical values of the value lg(cond(W)).
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At the moment, it is necessary to conduct a biological experiment each time in order to determine how the effect of an oncogenic mutation on the affinity for a small molecule, it is necessary to experimentally investigate the cellular response and determine the concentration for the half-inhibition of the enzyme.

The goal of our project is to develop a method that allows one to determine the stability of a molecular complex using the local three-dimensional structures of interacting reagents, which in turn affects the affinity of the components, which is reflected in the cellular response.

The results of applying our technique can be of good help for the pre-experimental determination of such quantities as the affinity expressed by the dissociation constant or the half maximal inhibitory concentration (IC50).

Technical information

Numerical determination of the stability of the biocomplex taking into account
mutations in the protein

The document below provides a mathematical background. Thus, to express the conformational mobility of a polyatomic molecule in the IR region, one can use a formula of the form (43). At the same time, for correct use, it should be understood that the greater value (43) in comparison with the rest of the values will indicate that not large vibrations of individual chain links of a polyatomic molecule should be understood so that not the basic vibrations of an individual links protein complex can lead to a shift in the rest of the chain links of the polyatomic molecule and, as a consequence, to the exit from the state of equilibrium and transition to the state of the entire molecule.
Modeling the impact of point mutations on the stability of proteins. EXAMPLE 1 BIOLOGICAL SOFT
Thanks to the use of the software developed by us, you can determine the affinity of the biological complex before carry out the biological experiment. Binomial Soft will allow you to determine the range of variation of the experimental values in biological research. The purpose of our software development is to determine the affinity of a biological complex, which is comparable to such experimental values as Kd (a specific type of equilibrium constant), IC50 (the half maximal inhibitory concentration ), ΔH, potential energy of interaction. Moreover, we want to share our method with other people how to use methods by other laboratories around the world, as this will significantly accelerate the development of drugs against other diseases.
Video instruction for using the software package
Our next example examines the effect of mutations in the heavy and light chains of Rituximab on binding to CD20. The figure shows a tetramer consisting of two CD20 transmembrane proteins and two FABs, heavy and light chains We will introduce five mutations in turn into the active binding site with CD20 and analyze the change in stability. The graph on the right presents the obtained numerical results on a logarithmic scale of the change in the value of lg (cond (W)). We have rotated the graph by 90 degrees for convenience of presentation, opposite each mutation the observed biological effect is shown, as well as the change in affinity in multiples.
Determination of antibody-antigen interaction using biological software

Additional information on small chemical molecules which are given as examples

A number of structures in the Protein Data Bank (PDB) contain adenosine 5′-(β,γ-imido)triphosphate (AMPPNP), a nonhydrolysable analog of ATP in which the bridging O atom between the two terminal phosphate groups is substituted by the imido function. Under mild conditions imides do not have acidic properties and thus the imide nitrogen should be protonated. However, an analysis of protein structures containing AMPPNP reveals that the imide group is deprotonated in certain complexes if the negative charges of the phosphate moieties in AMPPNP are in part neutralized by coordinating divalent metals or a guanidinium group of an arginine.
[Deprotonated imidodiphosphate in AMPPNP-­containing protein structures ]
Tumor cell turnover modulates the speed of selection against drug resistance by amplifying the effects of competition and resistance costs
Adenylylimidodiphosphate: effect of contaminants on adenylate cyclase activity
ATP analogue adenylyl-imidodiphosphate (AMP-PNP)
Gefitinib is an anilinoquinazoline with antineoplastic activity. Gefitinib inhibits the catalytic activity of numerous tyrosine kinases including the epidermal growth factor receptor (EGFR), which may result in inhibition of tyrosine kinase-dependent tumor growth. Specifically, this agent competes with the binding of ATP to the tyrosine kinase domain of EGFR, thereby inhibiting receptor autophosphorylation and resulting in inhibition of signal transduction. Patients with advanced epidermal growth factor receptor (EGFR) mutated non–small- cell lung cancer (NSCLC) treated with tyrosine kinase inhibitors (TKIs), such as gefitinib, erlotinib, and afatinib, show improved progression-free survival (PFS) compared with standard chemo- therapy as first-line therapy.
Cancer researchers are medical scientists research on carcinoma (cancer)
Gefitinib (Iressa®) is a selective small-molecule epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (EGFR TKI) indicated for the treatment of adults with locally advanced or metastatic non-small cell lung cancer (NSCLC) with activating mutations of EGFR tyrosine kinase.
Gefitinib (Iressa) is an orally active TK inhibitor
(TKI) that blocks signal transduction pathways implicated
in cancers. The structures of the L858R and G719S mutants complexed with either AMPPNP or the inhibitors, gefitinib and AEE788, revealed that the overall conformation and ligand-binding modes are very similar to those of the wild-type EGFR-TK in the active
cancer treatment research medicine software
CH7233163 as having the potential to overcome EGFR-Del19/T790M/C797S. CH7233163 showed potent antitumor activities against tumor with EGFR-Del19/T790M/C797S in vitro and in vivo. In addition to EGFR-Del19/T790M/C797S, the characterization assays showed that CH7233163 more selectively inhibits various types of EGFR mutants (e.g., L858R/T790M/C797S, L858R/T790M, Del19/T790M, Del19, and L858R) over wild type.
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Rociletinib (CO-1686) is an irreversible, mutant-selective EGFR inhibitor[52]. It is a medication developed to treat non-small cell lung carcinomas with a specific mutation. It is a third-generation epidermal growth factor receptor tyrosine kinase inhibitor. It was being developed by Clovis Oncology as a potential treatment for non-small-cell lung cancer [53]
Cancer. Medicine. software oncology research
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