Open-source molecular affinity calculations written in Matlab

Artificial Intelligence in Molecular Biosciences:
Protein Biochemistry

Calculated parametrs:

The fraction of non-dissociated molecules after the reaction and concentration protein-ligand complex
Entropy Change . The case of a one-dimensional normal distribution

3. Entropy Change . The case of multinormal normal distribution
4.Constant dissociation
5. Enthalpy change
6. The thermal dissociation
7. Potential energy of electrostatic interaction between all amino acid residues taken in pairs
8. Potential energy of the lower vibrational level.
9. Potential energy of the upper vibrational level.
10.Step-by-step verification of the PDB file structure.

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), mutations were taken here:
[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:

Take a look!

A visual, easy-to-understand guide to separating oncogenic and non-oncogenic P53 protein mutations among a variety of mutations.

NEW! Machine Learning and Deep Learning Methods

Zero Block

To select significant predictors(features variables), we have developed an original
software package that includes:
 a genetic algorithm,
 a stepwise regression method,
 regression trees and model trees using M5method.

3. Building regression trees and model trees using M5method
(M5 model tree is a decision tree learner for regression task which is used to predict values of numerical response variable, which is a binary decision tree having linear regression functions at the terminal (leaf) nodes, which can predict continuous numerical attributes) as well as building
ensembles of M5 trees using Bagging, Random Forests, and Extremely Randomized Trees.

The built trees can also be linearized into decision rules either directly or using the M5 method. Program accepts input variables to be continuous, binary, and categorical, as well as manages missing values. Model trees combine a conventional regression tree with the possibility of linear regression functions at the leaves. This representation usually provides higher accuracy than regression trees but preserves the advantage of clear and easy-to-interpret structure.
Thus, combining the methods GA-PLS, GA-OLS, GA-KNN, GA-RR, GA-PC, FS-PLS, FSOLS, FS-KNN, FS-RR, FS-PC and regression trees and model trees using we got a set of significant predictors for the prediction model. The described methods were implemented in the original toolbox.

At the same time, we consistently used a genetic algorithm, a decision tree to select the optimal set of features.
1. Genetic Algorithms(GA) are adaptive heuristic search algorithms that belong to the larger part of evolutionary algorithms. Genetic algorithms are based on the ideas of natural selection and genetics. These are intelligent exploitation of random search provided with historical data to direct the search into the region of better performance in solution space.
They are commonly used to generate high-quality solutions for optimization problems and search problems.
To select significant predictors, we used the following combined approaches:
 GA-PLS (partial least squares),
 GA-OLS(ordinary least squares) ,
 GA-PC(principal component),
 GA-RR(ridge regression),
Also, to improve the classification, we use
 GA-KNN( k- nearest neighbor) (KNN).In this case, instead of considering all training samples and taking k-neighbors, we used GA, which immediately takes k-neighbors, and then calculates the distance to classify the test samples.

An example program for the developed Machine Learning and Deep Learning Method for biological systems. The analysis is carried out for charged amino acid residues that are replaced (mutated) in the Spike-ACE2 dimer.
Correlation after clustering represents the dependence between calculated and experimental data

2. Stepwise regression (regression is a method of fitting regression models in which the choice of predictive variables is carried out by an automatic procedure. In each step, a variable is considered for addition to or subtraction from the set of explanatory variables based on some prespecified criterion. Usually, this takes the form of a forward, backward, or combined sequence of F-tests. The main approaches for stepwise regression is: forward selection (FS), which involves starting with no variables in the model, testing the addition of each variable using a chosen model fit criterion, adding the variable (if any) whose inclusion gives the most statistically
significant improvement of the fit, and repeating this process until none improves the model to a statistically significant extent.
 FS-PLS (partial least squares),
 FS-OLS (ordinary least squares) ,
 FS-PC (principal component),
 FS-RR (ridge regression),
 FS-KNN (k- nearest neighbor)
To select significant predictors, we choose the smallest value of RMSE(root mean square error) из GA- PLS, GA-OLS, GA-KNN, GA-RR, GA-PC, FS-PLS, FS-OLS, FS-KNN,
FS-RR, FS-PC.

An example program for the developed Machine Learning and Deep Learning Method for biological systems. The analysis is carried out for hydrophobic amino acid residues that are replaced (mutated) in the Spike-ACE2 dimer.
Correlation after clustering represents the dependence between calculated and experimental data

The main buttons in the Machine Learning program.

[Deep mutational scanning of an antibody
against epidermal growth factor receptor using
mammalian cell display and massively parallel
pyrosequencing] details of the experimental studies are described here

Absolutely for free

Hello, researcher!
We do macromolecular calculations for you!

All calculations are performed free of charge. You just need to go through a simple registration and send a technical assignment for calculations.

The purpose of our software is to obtain preliminary physical data on the interaction of biological molecules, thus the information obtained on the direction of the affinity change will reduce the number of experimental experiments performed.

Artificial intelligence (AI) is used in biochemistry for a variety of purposes, including the prediction of protein secondary structures, drug delivery, and enzyme creation.

Stages of software development in relation to various aspects of biochemical, biological and pharmacological queries.

Development of a multi-stage approach for checking the correctness of the PDB structure

Modification of antibody flexible chains,
stepwise testing of each antibody to antigen,
determination of key amino acid residues,
range of affinity changes.

Alanine scan
Mutagenesis
Identification of key amino acid residues
Stability of the
macromolecular complex
Entropy change

Determination of changes in the affinity of the test drug for the target protein in the presence of modifications, mutations in proteins

A method has been developed to increase the stability of amyloid peptides, thereby reducing their reactivity

Method for the determination
of biomarkers for clinical trials

Selection of inhibitors taking into account the high mutational volatility of viruses.

personalized medicine using AI solutions

Proteins
Interaction

PDB structure
checking

Antibody
development

Alzheimer's disease

Viruses

Drug Investigation

Biomarkers

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

1

Identification of key amino acid residues
The software package will allow you to determine the key amino acid residues in the biological complex, which account for the maximum potential energy of electrostatic interaction.
2

Mutagenesis
The software package allows you to replace amino acid residues in the polypeptide chains of proteins and get a change in the physical parameters of the interaction, such as stability, change in differential entropy, redistribution of the potential energy of electrostatic interaction. The data obtained make it possible to determine the direction of change in affinity.
3

Alanine scan
Computer alanine scanning makes it possible to obtain parameters of physical interaction when replacing amino acid residues with alanine. The data obtained are similar to those for mutagenesis given above.
4

Amyloid peptides
Stabilization of amyloid peptides at the level of dimeric complexes.
We have developed a method for increasing the stability of amyloid dimers in order to reduce their ability to enter into further biochemical reactions with the formation of toxic oligomers. The developed method is well suited for calculating the toxicity of hereditary mutations K16N, Flemish, Dutch, Italian, Iowa, L34V.
https://binomlabs.com/ad
5

Viruses
A detailed method was developed for selecting inhibitors based on modified natural peptides for the SARS-CoV protein spike glycoprotein. The selection of inhibitors is carried out by increasing the affinity of the peptide to the active center of the protein. The article also provides a step-by-step guide to the analysis of affinity of interaction by comparing 3 criteria, presents an analysis of energy interactions between the active center of a protein and the wild-type peptide interacting with it and taking into account modifications of the latter.

Physical aspects of interactions that we receive using the developed software package

Potential energy
Potential energy of interaction between all amino acid residues of the participating polypeptide sequences (as well as small molecules)
3D map of the potential energy
obtaining a map of the potential energy of interaction allows you to see the key amino acid residues at which the maximum values fall. The replacement of such amino acid residues leads to a redistribution of the potential energy of interaction, which also makes it possible to calculate the software package
Stability of the macromolecular complex
The introduced parameter of stability of biological complexes lg (cond (w)) makes it possible to determine the direction of the change in affinity upon substitutions of amino acid residues in polypeptide chains, which is also proportional to such experimental values as Kd (dissociation constant) and IC50.
Entropy change
the value of (delta)H (entropy change) obtained in the program allows identification of a sharp change in conformation when modifying polypeptide chains
Individual Approach
Our company works according to the principle of individual approach to every client. This method allows us to achieve success in problems of all levels.

metastatic breast cancer, breast cancer, colon cancer, what is colon cancer,

Our software package is designed for two types of structures:

You can choose calculations for a suitable type of structure, choose both options, or contact our specialists to clarify the details.

Linear Docking

For the case when the 3D structure of proteins is unknown, but the amino acid sequence is known, for example, using a sequence from the uniprot database Fig.1a)

3D Molecules

For cases when the 3D structure of dimeric (n-dimensional complexes) is known by the X-ray scattering method. You can also use molecular docking structures (Swiss Dock, LightDock) , but you will have to take into account the RMSD. Fig 1b)

Our software package is designed for two types of structures:

Linear Docking
For the case when the 3D structure of proteins is unknown, but the amino acid sequence is known, for example, using a sequence from the uniprot database.

3D Molecules
For cases when the 3D structure of dimeric (n-dimensional complexes) is known by the X-ray scattering method. You can also use molecular docking structures (Swiss Dock, LightDock) , but you will have to take into account the RMSD. Fig 1b)

3D structure of proteins is unknown Fig 1a)

1. Finding active sites of interaction (for cases where active sites of interaction are represented by a large number of consecutive amino acid residues, as for the cases of Nap1, Mdm2, MdmX, P53, P63, P73).
Example 1
Example 1_1
Example 1_2

2. Determination of thermal stability of individual domains with temperature changes.
Example 2

3. Determination of changes in the range of affinity of dimers upon phosphorylation of amino acid residues in one of them
Example 3

3D structure of dimeric (n-dimensional complexes) is known by the X-ray scattering method Fig 1b)
1. Determination of the direction of affinity change of dimeric (n-dimensional) complexes when replacing amino acid residues in proteins

2. Determination of the stability of amyloid complexes, the possibility of selecting polypeptide chains in order to stabilize them

3. Selection of peptide inhibitors

4. Direction of change in affinity with mutations in proteins that cause resistance to chemotherapy

5. Selection of flexible chains of immunoglobulins for antigen-antibody complexes.

Biomedical AI can help a doctor diagnose a disease, determine its optimal treatment, and predict the patient's prognosis.

Figure 1. Types of structures and types of calculations for each of them

Learn more Short Examples

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.

Guide to biological software tutorial.

Software package for determining the stability of protein molecules.

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

Antibody

Selection of amino acid residues in flexible chains to increase the antibody-antigen affinity

Viral Proteins

Determination of the direction of affinity change upon replacement of key amino acid residues

Small molecules

Determination of Suitable Small Molecules for Cancer Changes in Proteins

Amyloid peptides

Selection of peptide sequences to increase the stability of amyloid complexes

Get calculated data for your molecules.

Leave your details and make a short description of your biological complexes. Our specialists will contact you. We understand how complex biochemical studies are in setting, processing, interpreting, therefore we see the solution in the collaboration of specialists.
All calculations are made free of charge.

Short Examples
DIRECTION OF AFFINITY CHANGE (Fig.1b)

comparison of experimental (Kd, IC50)
and calculated values (lg(cond(W)), deltaH)

Erlotinib-EGFR
Erlotinib is used to treat certain types of non-small cell lung cancer that has spread to nearby tissues or to other parts of the body in patients who have already been treated with at least one other chemotherapy medication and have not gotten better. A value lg(cond(W)) that shows the stability of a biological complex and shows the direction of change in the affinity of a dimer under various mutations. 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).

THE FIRST GRAPH (RED) SHOWS THE DEPENDENCE OF THE VALUE IC50 ON THE MUTATION IN THE EGFR PROTEIN, THE SECOND GRAPH (BLUE) SHOWS THE RESULTS OF THE CALCULATIONS USING THE SOFTWARE DEVELOPED BY US, WHICH SHOWS THE DIRECTION OF THE CHANGE IN AFFINITY FOR MUTATIONS IN PROTEINS

The experimental values were taken [In vitro modeling to determine mutation specificity of EGFR tyrosine kinase inhibitors against clinically relevant EGFR mutants in non-small-cell lung cancer]

1. Thus, the numerical method developed by us makes it possible to determine the range of changes in the stability of dimeric complexes with the participation of a small chemical molecule and a protein molecule.

2. Application of our method will allow us to identify mutations that lead to a decrease in the affinity of components.

3. Numerical analysis requires a three-dimensional structure of the dimer under study, in the protein component of which substitutions of amino acid residues will be introduced.

Imatinib-PPAR
Imatinib is used to treat certain types of leukemia (cancer that begins in the white blood cells) and other cancers and disorders of the blood cells. Imatinib is also used to treat certain types of gastrointestinal stromal tumors.
Peroxisome proliferator-activated receptor (PPAR ) belongs to the thyroid hormone receptor-like nuclear receptor subfamily 1, which is one of the ligand-activated transcription factors.
Chemical structure of Imatinib-PPAR dimer with indication of key amino acid residues.

Useful application of the obtained numerical results.
The results of our studies can be applied in predicting:
1. Inhibitory potency and binding ability of small molecules
2. Inhibitor dissociation constants for the WT and mutant
kinases
3.Enzyme kinetic parameters
4. Explain the enhanced drug sensitivity of different mutants
5. Changing in the binding site caused by
the mutation on the enzyme's binding affinity for TKIs
6.Enzyme kinetic assays and IC50 determinations
7. Inhibitor binding constants, the drug resistance

Naquotinib (ASP8273)-EGFR
Naquotinib (ASP8273) is an orally available, irreversible, third-generation, mutant-selective, epidermal growth factor receptor (EGFR) inhibitor.
ASP8273 is a novel, small molecule, irreversible TKI that inhibits EGFR activity in patients with exon 19 deletions, L858R substitutions in exon 21, as well as T790M resistance mutations. Naquotinib is an orally available, irreversible, third-generation, mutant-selective, epidermal growth factor receptor (EGFR) inhibitor, with potential antineoplastic activity. Upon oral administration, ASP8273 covalently binds to and inhibits the activity of mutant forms of EGFR, including the T790M EGFR mutant, thereby preventing EGFR-mediated signaling. ASP8273 preferentially inhibits mutated forms of EGFR including T790M, a secondarily acquired resistance mutation, and may have therapeutic benefits in tumors with T790M-mediated resistance when compared to other EGFR tyrosine kinase inhibitors. As this agent is selective towards mutant forms of EGFR, its toxicity profile may be reduced as compared to non-selective EGFR inhibitors which also inhibit wild-type EGFR.

Rociletinib (CO-1686)-EGFR
Rociletinib (CO-1686) is an irreversible, mutant-selective EGFR inhibitor. 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.
A value lg(cond(W)) that shows the stability of a biological complex and shows the direction of change in the affinity of a dimer under various mutations.

Software Data Results

The results of numerical calculations of two different structures (5XDK and 5XDL) EGFR-Rociletinib (CO-1686) are in good agreement.
1. Substitution of L844V leads to a decrease in the stability of the mEGFR (L844V) - Rociletinib dimeric complex when analyzing the 5XDK and 5XDL sutures (the difference in the cond (W) value between the two mEGFR (L844V) - Rociletinib and wtEGFR-Rociletinib complexes was 300)

2. Replacement of T790M leads to increased resistance of mEGFR (T790M) - Rociletinib

3. Double substitution of T790M / L858R leads to a significant increase in the stability of the mEGFR dimer (T790M / L858R) - Rociletinib. Numerical calculations of the two structures showed similar results.

4. Replacement of L858R led to an increase in the stability of the mEGFR complex (L858R) - Rociletinib

Thus, the numerical method developed by us makes it possible to determine the range of changes in the stability of dimeric complexes with the participation of a small chemical molecule and a protein molecule. Application of our method will allow you to identify mutations that lead to a decrease in the affinity of components. Numerical analysis requires a three-dimensional structure of the dimer under study, in the protein component of which substitutions of amino acid residues will be introduced.

Mcl1-Bax BH3
Myeloid leukemia 1 (MCL-1) is an antiapoptotic protein of the BCL-2 family that prevents apoptosis by binding to the pro-apoptotic BCL-2 proteins. Overexpression of MCL-1 is frequently observed in many tumor types and is closely associated with tumorigenesis, poor prognosis and drug resistance. The central role of MCL-1 in regulating the mitochondrial apoptotic pathway makes it an attractive target for cancer therapy. Various Bax Met-74 mutants disrupt interactions between Bax and all pro-survival proteins, but these Bax mutants retain pro-apoptotic activity.

ANALYSIS OF BINDING OF BAX MET-74 MUTANT PEPTIDES TO PRO-SURVIVAL PROTEINS USING A BIACORE-BASED COMPETITION ASSAY VALUES ARE PRESENTED AS AN IC50 IN NM, AND VALUES IN BRACKETS REPRESENTS S.D.
(N =2–3 ASSAYS).

Comparing graphs a) and c), we see that the maximum value of IC50 and lg (cond (W)) falls on the replacement 74Asp. Thus, the replacement of methionine at position 74 of the Bax protein in the BH3 domain with Asp leads to the maximum decrease in resistance according to theoretical calculations and to the maximum loss of mutant peptide binding to Mcl1 protein. Thus, the maximum decrease in the stability of the Bax Bh3 (MET74ASP) -Mcl1 dimer corresponds to a significant loss of the peptide's ability to bind to the protein, according to the experimental data.
Since the first 4 results are graphically in the same range (at the bottom of the experimental and theoretical plots) compared to the maximum value of 74Asp, we decided to separately present these 4 values in plots b) and d) with an indication of the experimental error. According to the obtained theoretical and experimental data, the most stable is the wild-type wtBax BH3-Mcl1 dimer, while the wild-type Bax BH3 peptide has the greatest ability to bind to the Mcl1 protein compared to all the presented substitutions of amino acid residues in the Bax BH3 peptide.

.
Antibody-Antigen. Fab-CD20
Rituximab is a chimeric monoclonal antibody to the CD20 transmembrane antigen, expressed on the surface of B-lymphocytes and regulating lymphoid cell differentiation from an immature lymphocyte to a plasma cell. After rituximab binds to the CD20 antigen, a multi-stage complement system is activated on the surface of the B-lymphocyte, with the last stage being the formation of the C9 protein.The main innovation for the method proposed in this article is the determination of changes in the stability of the tetrameric complex, as well as the development of an original technique and the corresponding software package. These would allow researchers to determine the range of changes in the affinity of a biological complex when replacing amino acid residues in polypeptide chains; in this case, an antibody or antigen. We adapted the original method that we developed, in order to examine tetrameric antibody-antigen complexes. For this
purpose, we used a ready-made three-dimensional structure, which is a biological comprising six units, as presented in the PDB database: 6VJA

The three-dimensional structure and matrix of tetramer

Antibody affinity describes the intensity with which a single antibody molecule binds to its specific epitope in an antigen. This means that under a given concentration of antibody and antigen, a specific number of antigen-antibody complexes are formed. Consequently, antibody affinity is one of the major properties affecting the potency of therapeutic antibodies. Binders with higher affinities may allow for lower doses or longer intervals of administration during therapy. Moreover, as antibodies require sophisticated production systems and therapeutic doses, and costs of goods of antibodies are comparably high, a high affinity may affect the commercial success of a therapeutic antibody.

The process of in vivo affinity maturation is described as well as strategies for in vitro affinity maturation. Finally, the relation between affinity and efficacy and the determination of antibody affinity are reviewed. The correct determination of antibody affinity is crucial for antibody development, as wrongly set up experiments may result in the further development of the wrong candidate antibody. This can result in low in vivo efficacy, especially when high-affinity antibodies are needed; for example, for neutralizing antibodies.

Thus, there is no need to conduct expensive preliminary experiments to test different antibody modifications with our developed software package. We now have a unique opportunity to use our developed software to determine the affinity of the antibody-antigen complex and its various modifications in the case of missense mutations.

A completely new section - the calculation of DNA and RNA molecules when interacting with proteins

Today, for the first time, I performed quantum mechanical calculations for the interaction of an RNA molecule!We presented an RNA molecule as a chemical molecule and calculated the effect of mutations in the SARS-CoV-2 nucleocapsid phosphoprotein protein on the binding affinity to RNA.

The main goal

The main goal of our software is to reduce the cost of biochemical experiments by obtaining preliminary information on the interaction of chemical compounds.

Let's go!

Software tools for structure analysis of biochemical experiments:

Inhibitory potency and binding ability of small molecule

Inhibitor dissociation constants for the WT and mutant kinases

Enzyme kinetic parameters

Explain the enhanced drug sensitivity of different mutants

Inhibitor dissociation constants for the WT and mutant kinases

Changing in the binding site caused by
the mutation on the enzyme's binding affinity for TKIs

Enzyme kinetic assays and IC50 determinations

Inhibitor binding constants

The drug resistance

UP TITLE

Thanks to the use of the software developed by us,
you can determine the affinity range of the biological complex
before carry out the biological experiment.

Why choose us?

Our software allows you to determine the direction of affinity change, so you can significantly save on the following experimental methods:

ELISAs
Gel-shift assays
Aanalytical ultracentrifugation
Surface plasmon resonance
Spectroscopic assays
Affinity electrophoresis
Isothermal Calorimetry

Let's go!

FAQ.
Why are we investigating electrostatic interactions?

- we are often asked about this, because "there are many other interactions."

This part is devoted to a frequently asked question regarding electrostatic interactions, which are the main ones in our research.

Solvation (from lat. Solvo "dissolve") - electrostatic interaction between particles (ions, molecules) of a dissolved substance and a solvent. Solvation in aqueous solutions is called hydration. The molecular aggregates formed as a result of solvation are called solvates (in the case of water, hydrates)

Van der Waals forces (Van der Waals forces) are the forces of intermolecular (and interatomic) interaction with an energy of 10–20 kJ / mol. This term originally denoted all such forces, in modern science it is usually applied to the forces arising from the polarization of molecules and the formation of dipoles.

Classification of van der Waals forces:
The van der Waals interaction consists of three types of weak electromagnetic interactions:

Orientation forces, dipole-dipole attraction. It is carried out between molecules that are permanent dipoles. An example is HCl in liquid and solid state. The energy of this interaction is inversely proportional to the cube of the distance between the dipoles.

Dispersive attraction (London forces, dispersion forces). They are due to the interaction between the instantaneous and the induced dipole. The energy of this interaction is inversely proportional to the sixth power of the distance between the dipoles.

Induction attraction (polarization attraction). Interaction between permanent dipole and induced (induced). The energy of this interaction is inversely proportional to the sixth power of the distance between the dipoles.

The dipole moment is an important molecular constant that characterizes the electrical symmetry of a molecule. Knowledge of the magnitude of the dipole moment is necessary for studying the nature of chemical bonds, assessing the strength of donor-acceptor and intermolecular bonds, for quantum-chemical calculations.

Electric dipole moment is a vector physical quantity that characterizes, along with the total charge (and rarely used higher multipole moments), the electrical properties of a system of charged particles (charge distribution) in the sense of the field they create and the action of external fields on it. After the total charge and the position of the system as a whole (its radius vector), the main characteristic of the configuration of the charges of the system when observing it was published

Dispersion forces (dispersive attraction, London forces, London dispersion forces, LDF) are the forces of electrostatic attraction of instantaneous and induced (induced) dipoles of electrically neutral atoms or molecules.

A hydrogen bond is a form of association between an electronegative atom and a hydrogen atom H, covalently bonded to another electronegative atom. N, O, or F can act as electronegative atoms. Hydrogen bonds can be intermolecular or intramolecular

Donor-acceptor interaction - charge transfer between donor and acceptor molecules without the formation of a chemical bond between them (exchange mechanism); or the transfer of a lone electron pair from a donor to an acceptor, leading to the formation of a bond (donor-acceptor mechanism).

Introductory video on the practical use of our software

Using our software package you can determine the range of changes in affinity and then select only those modifications for further experimental research that meet the set objectives, for example, antibody modifications that will increase the affinity to the antigen, but will not lead to aggregation of antibodies among themselves.

Description of the software package for determining the stability of protein molecules.

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TUTORIAL BIOLOGICAL SOFT. The figures show two graphs showing the results of the effect of mutations in the BAK peptide on binding to the Bcl-xl protein. The graph on the left is from an experimental study.

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.

Below are some biological research areas to which our software package can be applied.

Molecular Therapies of Cancer

Our team has developed an innovative method for determining the stability of chemical compounds, taking into account various oncogenic mutations. Useful application of the obtained numerical results

Gefitinibe

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.

AMP

The T790M mutation of EGFR increases the ATP affinity of the G719S mutant, explaining the acquired drug resistance of the double mutant. Structural analyses of the G719S/T790M double mutant, as well as the wild type and the G719S and L858R mutants, revealed that the T790M mutation stabilizes the hydrophobic spine of the active EGFR-TK conformation.

CO-1686

Rociletinib (CO-1686) is an irreversible, mutant-selective EGFR inhibitor. 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

Imatinib

Imatinib is specific tyrosine kinase receptor inhibitor that is used in the therapy of Philadelphia chromosome-positive chronic myelogenous leukemia and gastrointestinal stromal tumors, both of which are marked by an abnormal, constitutively expressed tyrosine kinase that causes unregulated cell growth.

Imatinib Naquotinib Erlotinib

Now let's analyze, and then perform example of replacing an amino acid residue in a Bak peptide when it interacts with the whole protein Bcl xl, which leads to an increase in the affinity of the peptide to the protein. Let us consider in more detail the three-dimensional structure of this dimer. Initially, we have a 3D structure of a dimer, in which the Q77L substitution in the Bak peptide is performed. The overall structure of BAKQ77L was not significantly affected by the mutation, and the side chain of L77 is oriented identically to the wild-type glutamine at this position on the solvent-exposed surface of the (BH3) helix.

Example 2: guide to biological software

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What researches are you interested in?

Here you can ask a question, talk about the goals of your research.

Hello, researcher! We do macromolecular calculations for you!

ProteinsInteraction

Antibodydevelopment

Alzheimer's disease

Viruses

Drug Investigation

Biomarkers

Our software package is designed for two types of structures:

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

Short ExamplesDIRECTION OF AFFINITY CHANGE (Fig.1b)comparison of experimental (Kd, IC50) and calculated values (lg(cond(W)), deltaH)

Software tools for structure analysis of biochemical experiments:

FAQ.Why are we investigating electrostatic interactions?

Below are some biological research areas to which our software package can be applied.

Molecular Therapies of Cancer

Hello, researcher!
We do macromolecular calculations for you!

Proteins
Interaction

Antibody
development

Short Examples
DIRECTION OF AFFINITY CHANGE (Fig.1b)

comparison of experimental (Kd, IC50)
and calculated values (lg(cond(W)), deltaH)

FAQ.
Why are we investigating electrostatic interactions?