We have developed a biophysical method to reduce the cost for antibody experiments in the fields of antibody-antigen, peptide-protein interaction, protein-protein interaction via data science.
Our method include:
-modification of antibody flexible chains,
-stepwise testing of each antibody to antigen,
-determination of key amino acid residues,
-range of changes in affinity.
-modification of antibody flexible chains,
-stepwise testing of each antibody to antigen,
-determination of key amino acid residues,
-range of changes in affinity.
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B2B. Cost -saving technologies for laboratory experiments
Biophysics of the affinity of the antibody-antigen biocomplex.
High lifescience innovations
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.
Antibody discovery and development has two main stages.
The first one is to discover antibodies that bind the target of interest. The second, is to optimize the antibody to make a better drug. This challenge is about the second step. The starting point is a functional antibody that modulate the desired target. We offer to build a computational platform that delivers the sequence of a modified antibody sequence. Modifications are required at multiple levels:
• Antibodies differ in their level of solubility, aggregation during purification, proper folding and more.
• Physiological properties: pharmacokinetic and pharmacodynamics.
The above list of properties required is not complete. The goal is not to optimize for a specific antibody property but rather to suggest a process to optimize to any property.
The first one is to discover antibodies that bind the target of interest. The second, is to optimize the antibody to make a better drug. This challenge is about the second step. The starting point is a functional antibody that modulate the desired target. We offer to build a computational platform that delivers the sequence of a modified antibody sequence. Modifications are required at multiple levels:
• Antibodies differ in their level of solubility, aggregation during purification, proper folding and more.
• Physiological properties: pharmacokinetic and pharmacodynamics.
The above list of properties required is not complete. The goal is not to optimize for a specific antibody property but rather to suggest a process to optimize to any property.
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.
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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].
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
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. Instead you can use the software developed by our team to determine the affinity of the antibody-antigen complex and affinity of its various modifications.
1. The fraction of non-dissociated molecules after the reaction and concentration protein-ligand complex
2. Entropy Change. The case of one-dimensional normal distribution
3. Entropy Change. The case of multinormal normal distribution
4. Dissociation Constant: Kd, M/L
5. Enthalpy change: delta (P), J
6. The thermal dissociation
7. Potential energy of electrostatic interaction between all amino acid residues taken in pairs: Wp, J
8. Potential energy of the lower vibrational level: Wp1, J
9. Potential energy ofthe upper vibrational level: Wp2, J
10. Step-by-step verification of the PDB file structure.
2. Entropy Change. The case of one-dimensional normal distribution
3. Entropy Change. The case of multinormal normal distribution
4. Dissociation Constant: Kd, M/L
5. Enthalpy change: delta (P), J
6. The thermal dissociation
7. Potential energy of electrostatic interaction between all amino acid residues taken in pairs: Wp, J
8. Potential energy of the lower vibrational level: Wp1, J
9. Potential energy ofthe upper vibrational level: Wp2, J
10. Step-by-step verification of the PDB file structure.
Additional calculated parameters:
What do we have for obtaining information about the antibody-antigen affinity?
Each antibody-antigen complex has its own physical parameters that determine the interaction
Main calculated parameters:
Procedure for finding suitable immunoglobulins
STEP ONE
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 or using molecular docking programs.
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.
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 or using molecular docking programs.
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.
STEP TWO
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
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
6. Analysis of the array of data obtained, selection of the most suitable replacements using soft and Data Science, report generation.
7.Sending the received data to the customer.
7.Sending the received data to the customer.
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Additional Information
How to predict antigen-antibody binding interface?
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 approach to affinity maturation.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
[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.
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.
[The hidden world of drug interactions in anesthesia]
[The hidden world of drug interactions in anesthesia]
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].
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.
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.
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
