B2B. Cost -saving technologies for laboratory experiments
We have developed a Biophysical Software to reduce the cost for antibody experiments in the fields of antibody-antigen, peptide-protein interaction, protein-protein interaction via data science.
This method is innovative in the field of molecular biology and our development team is looking for collaboration with university laboratories, pharmacological companies, manufacturing platforms

Affinity Maturation

Algorithm for determining the direction of change in affinity when replacing amino acid residues in the antibody-antigen complex.

Biophysics of the affinity of the antibody-antigen biocomplex
Our method will include modification of flexible chains of immunoglobults, stepwise testing of each antibody to antigen, determination of key amino acid residues, range of changes in affinity.
The method developed by our group makes it possible to determine the direction of the change in affinity upon substitutions of amino acid residues in flexible chains of an antibody upon binding to an antigen.

The purpose of this research work is to develop software that will allow determining the direction in the change in affinity when replacing amino acid residues in polypeptide chains, in this case, an antibody or antigen. Previously, we have successfully tested the developed software package for assessing the direction of change in affinity upon substitution of amino acid residues in the polypeptide chains of proteins of the Bax-Bcl-2 complex. This work is a continuation of previous research and in this work we are expanding our research to tetrameric antibody-antigen complexes.

To do this, we will use a ready-made three-dimensional structure of the complex, which is a biological complex consisting of six units. We will use 4 units for our calculations: two CD20 molecules and two Fab molecules. The structure of such a computational complex is shown in Fig.1.

In this work, we present a completely new method for determining the direction of change in affinity for complex biological complexes consisting of 4 molecules: CD20 and CD20, Fab light and Fab heavy. The three-dimensional structure of such a tetramer is shown in Fig.3-4.To calculate the effect of amino acid substitutions on the affinity of the tetramer, we compiled a block matrix shown in Fig.2
Fig.1.Numerical results of amino acid residue substitutions in Rituximab upon binding to CD20.
Let's move on to the main result obtained in our work. As mentioned above, the goal of our project is to develop a method that would allow determining the range of changes in the affinity of a biological complex upon substitutions of amino acid residues in polypeptide chains. In this work, 5 substitutions of amino acid residues in the heavy and flexible chains of Retuximab were performed. The initial value corresponds to the interaction of the wild type, from which the subsequent counting is carried out. Recall that the larger the value of log(cond (W)), the lower the stability of the tetrameric complex. The graph is shown in Fig. 1, arrows indicate the results obtained during the experimental study of these substitutions for the affinity of the biological complex [Structure of CD20 in complex with the therapeutic monoclonal antibody rituximab].
The cells of such a matrix are filled with the values of the potential energy of electrostatic interaction, and we left the diagonal elements that are responsible for the interaction of identical amino acid residues at zero.
Fig.2.Assembly diagram of a block matrix when calculating a tetramer a) and a three-dimensional structure of a tetramer b)

For the convenience of further visual representation, we have developed three-dimensional maps of the potential energy of electrostatic interaction between pairwise taken amino acid residues of different units. The three-dimensional reconstructed map of the potential energy of interaction is partially shown in Fig. 3 and 4.

Figure 3. shows a three-dimensional region of interaction between CD20 and Fab heavy in the region of the region of interaction between polypeptide chains. A three-dimensional map of the interaction potential of this area is shown in Fig. 4. In this figure, there are two amino acid residues that we will replace in the Fab heavy molecule. These will be replacements for the Y97F and G99K. As can be seen on the presented map, these amino acid residues are characterized by low values of potential energy. Thus, the interaction of Y97 Fab heavy interacts with E174 CD20 with a value of -1.8E-27 J. The interaction of W102 Fab heavy with A170 CD20 is characterized by more significant values, the value of this interaction was 4.47E-26 J
Fig.3.Section of the three-dimensional map of the potential energy of interaction between CD20 and Fab heavy a) and the three-dimensional structure of the interaction section Fab heavy and CD20 b)
The second area we are considering is shown in Fig. 4, as well as the values of the potential energy of interaction between pairwise taken amino acid residues. As can be seen in Fig. 4, the values of the interaction energy are much less than in the previous interaction section. Thus, we can estimate the contribution of each site to the stabilization of the macromolecular complex by analyzing the values of the energy interaction between a.a. two polypeptide chains, despite the close spatial arrangement. Thus, a.a. D56 Fab heavy is characterized by very low energies of interaction with a.a. from the CD20 side in this section. Two adjacent a.a. THR57 and GLY55 on the Fab heavy side are characterized by much higher energy values of 4.45U-26J and 4.13E-26 J with ALA150 on the CD20 side, respectively. Amino acid residue ASP56 Fab heavy interacts with N176 and P172 with values of 6.2E-29J and -1.7E-28 J, respectively.

The main innovation of our method is the determination of the change in the stability of the tetrameric complex by analyzing the changes in the values of the potential interaction energy during the replacement of amino acid residues in the polypeptide chain. Thus, the value lg(cond (W)) proposed by us, which we use as a criterion for assessing the change in stability, allows us to obtain a numerical estimate of such a change.
Fig.4.three-dimensional structure of the interaction area Fab heavy and CD20 a) and the corresponding area of the three-dimensional map of the potential energy of interaction between CD20 and Fab heavy b)
As the third interaction site under consideration, we chose the area between CD20 and Fab light. At this site, we will carry out the replacement of the amino acid residue Ser28ASP Fab light and the subsequent analysis of the change in the stability of the entire tetrameric complex during such a replacement, graphical representation in Fig. 5. We present a detailed analysis of the change in the three-dimensional energy map when replacing CYS167 with ALA (Fig.5b) and ARG (Fig.5c).
In this case, hydrophilic interactions are indicated in green, hydrophobic interactions are indicated in blue, and the interaction of charged amino acid residues is indicated in red. Also, above each card, the corresponding values of potential energy are given. The largest changes in energy interactions are observed with the replacement CYS167ALA (fig.5c).
Figure 5: 3D maps of the potential energy of electrostatic interaction between Fab light and CD20 in the interaction of wild-type CD20 a), with the replacement of CYS167ALA in CD20 b), with the replacement of CYS167ARG in CD20 c)
Thus, a three-dimensional map of the potential energy of interaction allows you to clearly see the energy peaks attributable to the interactions of certain amino acid residues. Varying the magnitude of this energy interaction will lead to noticeable changes in the affinity of the biological complex, in this case the tetrameric complex.

Our group developed an innovative method in biology for antibody-antigen development

During the first half of the 20th century, a series of scientific discoveries resolved that antibody-mediated immunity is the cornerstone of the specific immune response. Since their first use as immunolabeling research tools in the early 1970s, antibody technologies have vastly improved, and antibodies have become critical tools for most areas of life science research. The basic principle of any immunochemical technique is that a specific antibody will combine with its specific antigen to generate an exclusive antibody-antigen complex.
Our group has developed an innovative research technique for such a complex using Data Science

We passionately believe that medicine antibody development shouldn't be done alone - collaboration is essential for antibody-antigen development. That's why we are open for work with other innovators across the health landscape including academic scientists, patient organisations, governments, other bio-pharmaceutical companies and healthcare professionals.
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 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 a wrong setup of the 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 [1-2].

How to determine the affinity of a biocomplex before performing an experiment?

What is antibody?
An antibody (Ab), also known as an immunoglobulin (Ig), is a large, Y-shaped protein produced mainly by plasma cells that is used by the immune system to neutralize pathogens such as pathogenic bacteria and viruses.Antibody development is the procedure of creating and characterizing an antibody.
Antibody development
Antibody development is the procedure of creating and characterizing an antibody. Below is a diagram of the biophysical model developed by us, which allows us to determine various parameters of the physical interaction of molecules and thus predict the change in the affinity and stability of the molecular complex thereby reducing the amount of costs for the experiment, increasing its informativeness.
We offer
Development of therapeutic antibodies. Antibody development is a multi-faceted process and an experiment in itself. We propose to reduce the number of test experiments conducted to determine the affinity of an antibody to an antigen by modifying flexible chains of immunoglobulins using our software.
1. Barbas, C.F., Hu, D., Dunlop, N., Sawyer, L., Cababa, D., Hendry, R.M., Nara, P.L., and Burton, D.R. (1994) In vitro evolution of a neutralizing human antibody to human immunodeficiency virus type 1 to enhance affinity and broaden strain cross-reactivity. Proc. Natl. Acad. Sci., 91, 3809–3813.
2. Nelson, J.D., Brunel, F.M., Jensen, R., Crooks, E.T., Cardoso, R.M.F., Wang, M., Hessell, A., Wilson, I.A., Binley, J.M., Dawson, P.E. et al. (2007) An affinity-enhanced neutralizing antibody against the membrane-proximal external region of human immunodeficiency virus type 1 gp41 recognizes

How to measure and improve antibody-antigen affinity?

You do not need to perform preliminary expensive experiments to test different antibody modifications. You can use the software developed by us to determine the affinity of the antibody-antigen complex and its various modifications in case of missense mutations
Procedure for finding suitable immunoglobulins
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1.Determination of three-dimensional complex of the target protein with antibody flexible chain, which is subject to further modification. This should be at least one file with the extension of the PDB obtained by the method of X-ray diffraction analysis.
2.To control the received data, you can choose either of two options:
- you can use the additional structure of the PDB of antibody-antigen.
-take advantage of previously available data on the mutations performed, alanine scanning of one of the participants of the antibody-antigen complex

3.Our experts check files, adapt them for computational manipulations using Soft Development and Data Science.
4. Our specialists perform the necessary calculations: obtain data, numerically calculate the results in the form of graphs and diagrams, determine
-key amino acid residues of antibody,
-interaction energies of antibody-antigen complex,
-changes in affinity and stability of antibody-antigen complex,
-change in entropy for each replacement of the amino acid residue in the flexible chain of immunoglobulin.
5. Performing a verification series of calculations in accordance with paragraph 2
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Additional Information

How to predict antigen-antibody binding interface?

Whenever the X-ray crystallofraphic of structure of an antigen-antibody complex is available, knowledge of the paratope-epitope interaction provides the opportunity for a rational approachto affinity maturation.Site-directed mutagenesis can be used to introduced: Site-directed mutagenesis can be used to introduce amino acid exchanged that are supposed to be beneficial for the setup of the interface of antigen and antibody. But at present, it remains nearly impossible to predict the antigen-antibody binding interface reliably. To overcome this drawback, we developed a rational mutation design
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[Crystal Structure of Human Antibody 2909 Reveals Conserved Features of Quaternary Structure-Specific Antibodies That Potently Neutralize HIV-1]
Because most therapeutic mAbs would require affinities better than those of antibodies recovered directly from in vitro antibody display systems, large efforts have been undertaken to develop efficient in vitro means to mimic the in vivo affinity maturation process. The screening procedures may be manipulated to recover variable regions with selective improvements in kon and/or in koff, something not feasible with affinity maturation in vivo. As typical for the in vivo process, iterative rounds of in vitro mutagenesis and selection are employed to recover and incrementally improve selected variants. In this way, antibodies with affinities <10E−9 –10E−10 mol L−1 and occasionally greater can be routinely generated through in vitro processes. These processes, and with advancements such as utilization of combinations of in vitro procedures that complement deficiencies inherent in each (phage plus either ribosome display or yeast display) and improvements in operational efficiencies that allow for both parallel-processing of multiple starting V region templates and screening of larger pools of variants, have yielded antibodies with picomolar and femtomolar affinities (Schier et al. 1995; Boder et al. 2000; Hanes et al. 2000; Zahnd et al. 2004; Hoet et al. 2005; Rathanaswami et al. 2005).
The naive cells ( Naïve T cells are continually generated in the thymus, where each cell undergoes DNA rearrangement to generate a unique T-cell receptor) in the human body have the ability to express, in principle, more than 10E+11 different B-cell receptors with only about 23 000 genes.

During the process of clonal selection (Clonal selection is a process proposed to explain how a single B or T cell that recognizes an antigen that enters the body is selected from the pre-existing cell pool of differing antigen specificities and then reproduced to generate a clonal cell population that eliminates the antigen), high-affinity antibodies are generated owing to the humoral response to a repeated antigen challenge. Two processes of positive selection are responsible for the affinity maturation (affinity maturation is the process by which TFH cell-activated B cells produce antibodies with increased affinity for antigen during the course of an immune response) that takes place in different compartments of the germinal center (the germinal center (GC) is a specialized microstructure that forms in secondary lymphoid tissues, producing long-lived antibody secreting plasma cells and memory B cells, which can provide protection against reinfection) in secondary lymphoid organs. Antibody diversity is considrably increased by somatic hypermutations, which introdused point mutations as well as insertions and deletions in the V(D)J regions in the variable genes of activated B cells. The improvment by hypermutation and clonal deletion is a stepwise process that may lead to an increase of up to a million-fold in the affinity with respect to the deduced antibody with germline sequences from the naive gene repertoire.

Affinity maturation, in principle, be confirmed in a study where pacient were immunized with titanus toxin and the antibody generated by single B cell clones were analyzed. The antibodies developed by the patients had an average affinity of 1,0x10E-9 M at 37C and 3,4x10E-10 M at 25C but with a number of antibodies showing higher affinity than the proposed 10E-10 M. In addition, transgenic hyperimmunized mouse that contains the human antibody repertoire produced antibodies with even sub-picomolar affinities.

As the mutations that occur during the affinity maturation are inserted randomly in the V genes, some of the resulting B-cell receptor (BCRs) may arise with Kd values beyond the 10E-10 barrier.

Somatic hypermutation leads to an accumulation of beneficial amino acid exchanges mainly in the complementary determining regions (CDRs). Mutations in the framework regions occur at much lower frequency but are supposed to be no less important for the maturation process: mutations that occur at the antigen binding sites may lead to a decrease of the thermodinamic stability of the antibody. The destabilizing effect can be conpensated by additional somatic mutations located on surface loops distal to the antigen binding site.
Overall structure of 2909 Fab. The 2909 crystal structure reveals a combining region dominated by a protruding, acidic CDR H3 loop. (A) Ribbon representation of the 2909 Fab structure is shown, with heavy and light chains colored in blue and green, respectively. The CDR H3 loop is highlighted in red, while other CDR loops (as defined by Kabat [19]) are depicted in yellow. (B) Surface representation of the 2909 Fab is shown in the same orientation as in panel A (left) or rotated 180° about the y axis (right). The surfaces are colored by electrostatic potential (−10 to +10 kT/e), with positively and negatively charged regions shown in blue and red, respectively. [Crystal Structure of Human Antibody 2909 Reveals Conserved Features of Quaternary Structure-Specific Antibodies That Potently Neutralize HIV-1]
In vitro antibody selection systems have been adopted to generate high-affinity binders. Error-prone polymerase ( error-prone polymerases are sometimes used in circumstances where the capacity to make errors has a selective advantage) chain reactions (PCRs) can be used to introduce amino acid exchanges randomly, either scattered over the whole Fv fragments or only in the CDRs [35]. The mutated DNA is subcloned into an appropriate expression vector for construction of an antibody library that is screened for high-affinity binders under modified panning conditions that allow enrichment of affinity-matured binders. Of course, the insertion of mutations in the Fv fragments with error-prone PCR cannot provide the whole theoretical diversity in these mutation libraries as this would exceed the possible library size. But the nucleic acid amino sequence diversity can be estimated using appropriate computer programs [36]. Nevertheless, screening of mutation libraries is widely used for the identification of beneficial amino acid exchanges not only in the CDRs but also in regions that are not directly involved in antigen binding.
Antigen Affinity - Affinity Measurement
The strength of antibody-antigen binding is enhanced by a fast association rate, which is proportional to the association rate constant (kon or ka), and by a slow dissociation rate, which is proportional to the dissociation rate constant (koff or kd). The value of affi nity is most frequently described by the equilibrium dissociation constant (KD). The KD, which is readily calculated by koff divided by kon, is the concentration of antibody-binding sites that will bind 50% of the antigen-binding sites when the concentration of antigen is much less than the KD. This simple defi nition of KD assumes that all antibody-binding sites are accessible to all antigen-binding sites and that no avid interactions occur. Avidity refl ects the strength of binding when multivalent binding results in a cooperative antigen– antibody interaction. An example of an interaction is when both antibodybinding sites simultaneously bind an antigen on a surface, or form cyclic or lattice immune complexes. In such cases, the avidity may be much stronger (by several orders of magnitude) than reflected by the 1 : 1 site binding KD. The values of KD, kon, and koff can be determined experimentally.
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Development and testing of new antibodies using our biophysical software can significantly save money on laboratory research
Another approach tries to resemble the in vivo affinity maturation. There, germline hot spots for mutations are identified in the CDRs and randomly mutagenized instead of introducing mutations in the whole Fv or CDR regions. The resulting antibody libraries can subsequently be screened for binders with higher affinities. Using this approach, moderate affinity improvements were obtained up to 10-fold[1-2] possibly due to the lack of beneficial effects from alterations in the FRs. In order to mimic the in vivo affinity maturation in B cells, a combination of a mammalian display-based screening system that is coupled to in vitro somatic hypermutation by coexpression of the activation-induced cytidine deaminase (AID) was developed[3-4]
Look-through mutagenesis makes use of a library, in which only the amino acids in the CDRs are exchanged: Nine representatives of the different major chemical functionalities (small, nucleophilic, hydrophobic, aromatic, acidic, amine, and basic) are randomly introduced at all CDR positions. Using this method and subsequently combining the beneficial mutations in a second maturation and screening step lead to an affinity increase of an anti-TNFα scFv of 500- to 870-fold [5].

1.Ho, M., Kreitman, R.J., Onda, M., and Pastan, I. (2005) In vitro antibody evolution targeting germline hot spots
to increase activity of an anti-CD22 immunotoxin. J. Biol. Chem., 280, 607–617.,
2. Beers, R., Chowdhury, P., Bigner, D., and Pastan, I. (2000) Immunotoxins with increased activity against epidermal growth factor receptor vIIIexpressing cells produced by antibody phage display. Clin. Cancer Res., 6, 2835–2843.
3. Bowers, P.M., Horlick, R.A., Kehry, M.R., Neben, T.Y., Tomlinson, G.L., Altobell, L., Zhang, X., Macomber, J.L., Krapf, I.P., Wu, B.F. et al. (2014) Mammalian cell display for the discovery and optimization of antibody therapeutics. Methods, 65, 44–56.
4. McConnell, A.D., Do, M., Neben, T.Y., Spasojevic, V., MacLaren, J., Chen, A.P., Altobell, L., Macomber, J.L., Berkebile, A.D., Horlick, R.A. et al. (2012) High affinity humanized antibodies without making hybridomas; immunization paired with mammalian cell display and in vitro somatic hypermutation. PLoS ONE, 7, e49458.
5. Rajpal, A., Beyaz, N., Haber, L., Cappuccilli, G., Yee, H., Bhatt, R.R., Takeuchi, T., Lerner, R.A., and Crea, R. (2005) A general method for greatly improving the affinity of antibodies by using combinatorial libraries. Proc. Natl. Acad. Sci. U.S.A., 102, 8466–8471.

The transfer of in vitro data into an in vivo system in respect of efficacy is a difficult task: in vitro assays are performed under conditions that o not consider the antigen turnover or the addition or elimination of the antibody. Formation of an immune complex of antigen and antibody may also influence the pharmacokinetics of both molecules [64–66]. In principle, a soluble antigen adopts the pharmacokinetic of the antibody when the complex is formed. In case of a cell-bound antigen, the antibody is eliminated by internalization of the antigen, which may result in a dramatic decrease of antibody concentration in the tumor vicinity.
Despite the complexity of the antibody and antigen kinetics in vivo, the effect of affinity on antibody potency is similar to that observed in vitro.
From kinetic observations, a simple relationship between affinity and binding potency emerges. For any given antigen concentration, an antibody affinity exists beyond which further improvements in affinity will not enhance antigen binding. This potency ceiling for affinity occurs when KD of the antibody falls to approximately 1/10th the antigen concentration, this relationship holds in vitro and in vivo.
For more detailed information you can read: "Handbook of Therapeutic Antibodies" Edited by Stefan Dubel and Janice M. Reichert
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