High‑affinity chromatography delivers powerful selectivity, but it comes with cost, robustness, and format‑specific limitations. Typical pain points include harsh elution conditions, ligand/metal leachables, tag‑related artifacts, co‑purification of interactors, scale‑up sensitivity.
BinomLabs platform has developed a method for selecting impurities from high-molecular complexes: determination of the concentrations ratios for all participating chemical compounds
BinomLabs platform has developed a method for selecting impurities from high-molecular complexes: determination of the concentrations ratios for all participating chemical compounds
Protein Purification System
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Why is agarose used in Affinity Chromatography?
Affinity chromatography is a method for selective purification of a molecule or group of molecules from complex mixtures based on highly specific biological interaction between the two molecules. The interaction is typically reversible and purification is achieved through two phases, with one of the molecules (the ligand) immobilized to a surface while its partner (the target) is in a mobile phase as part of a complex mixture. The capture step is generally followed by washing and elution, resulting in recovery of highly purified protein. Highly selective interactions allow for a fast, often single step, process, with potential for purification in the order of several hundred to thousand-fold. -
Why is agarose used in Ion Exchange Chromatography?
Ion exchange chromatography (IEX) is used to separate molecules based on the strength of their overall ionic interaction with either negatively or positively charged groups on a resin. By manipulating buffer conditions, such as pH and ionic strength, molecules of greater or lesser ionic character can be bound to or dissociated from the solid phase material. IEX supports may either be positively charged (anion binding), or negatively charged (cation binding). -
Does size matter?
Agarose resins come with different particle sizes and size distributions. These have an impact on the physical properties of the purification matrix.- Pressure - the smaller the beads, and the narrower the size distribution, the higher the pressure-resistance of the beads. In comparison, the larger the beads, the faster the flow rate in batch and FPLC experiments.
- Binding capacity - the smaller the beads, the higher the ratio of surface to volume, and the higher the binding capacity of the beads. Although binding capacity is also dependent on other factors such as the type and size of ligand, and density of ligand coupling.
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Particle size distribution
A narrow particle size distribution offers improved performance characteristics. The more uniform the beads, the more consistently the resin will perform, whether that be when packing the column or running your process.
Most agarose-based resins on the market are produced using Batch Emulsification technology, first utilized around 50 years ago. This produces a relatively wide particle size distribution. -
Advantages of using agarose for chromatography include:
- Extremely hydrophilic – minimal unspecific binding
- Low matrix volume (4-8%) – possible to achieve high capacity
- Easy to conjugate
- Very stable under alkaline conditions
BinomLabs platform has developed a method
for selecting impurities from
high-molecular complexes affinity:
for selecting impurities from
high-molecular complexes affinity:
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Data Collection:
- Compiling a report of all possible high-molecular and low-molecular formations
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Calculations and analysis:
- Determining the affinity and measure of entropy change during the formation of each biocomplex from the list,
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- Determining the most and least stable molecular complexes,
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- Determining the effect of modifications, mutations of participating molecules,
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Data processing:
- Determining the ratio of concentrations of the formed biocomplexes,
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- Separation and separation of contaminants and impurities in the eluate
Affinity & epitope insight: Predicts ΔG/Kd changes for mutations, domain swaps, or CDR edits—so you express/purify fewer, better variants.
Scores deamidation, isomerization, oxidation, glycation hotspots; proposes stabilizing edits before you head to column.
PPI/context awareness: Maps protein–protein interfaces that may trap contaminants or ligands and recommends buffer additives to keep them off your product.
Assay planning synergy: Aligns purification choices with ELISA/ELISpot/flow or activity assays so fractions elute in conditions friendly to function tests Affinity & epitope insight: Predicts ΔG/Kd changes for mutations, domain swaps, or CDR edits—so you express/purify fewer, better variants.
Scores deamidation, isomerization, oxidation, glycation hotspots; proposes stabilizing edits before you head to column.
PPI/context awareness: Maps protein–protein interfaces that may trap contaminants or ligands and recommends buffer additives to keep them off your product.
Assay planning synergy: Aligns purification choices with ELISA/ELISpot/flow or activity assays so fractions elute in conditions friendly to function tests Affinity & epitope insight: Predicts ΔG/Kd changes for mutations, domain swaps, or CDR edits—so you express/purify fewer, better variants.
Pharma and biotech spend tens of billions each year on in‑vitro work, where variability and low first‑try success increse cost and timelines. BinomLabs applies state‑of‑the‑art ML to deliver experiment prognoses that align with lab data up to R = 0.93, demonstrated on real in‑vitro studies.
With this guidance, teams typically reduce ~10 experiments to 3–4, lifting the proportion of successful first attempts and freeing capital for the highest‑value questions. We enhance expert judgment—turning every scientist into a faster, more precise decision‑maker.
With this guidance, teams typically reduce ~10 experiments to 3–4, lifting the proportion of successful first attempts and freeing capital for the highest‑value questions. We enhance expert judgment—turning every scientist into a faster, more precise decision‑maker.
Are you part of a biochemical or pharmacological laboratory and looking for highly effective results?
Join our free pilot program featuring an advanced AI platform that predicts experimental data with 70%-90% correlation, reducing the number of required experiments by 60%!
Benefits:
Save time and resources.
Enhance research efficiency.
Focus on breakthroughs while AI handles the heavy lifting.
📩 Apply now to explore this game-changing technology and collaborate with us!
Join our free pilot program featuring an advanced AI platform that predicts experimental data with 70%-90% correlation, reducing the number of required experiments by 60%!
Benefits:
Save time and resources.
Enhance research efficiency.
Focus on breakthroughs while AI handles the heavy lifting.
📩 Apply now to explore this game-changing technology and collaborate with us!
🚨 We’re Hiring Pilot Projects! 🚨 FREE PILOT project for biochemistry labs!
Are you part of a biochemical or pharmacological laboratory and looking for highly effective results?
Join our free pilot program featuring an advanced AI platform that predicts experimental data with 70%-90% correlation, reducing the number of required experiments by 60%!
Benefits:
Save time and resources.
Enhance research efficiency.
Focus on breakthroughs while AI handles the heavy lifting.
📩 Apply now to explore this game-changing technology and collaborate with us!
Join our free pilot program featuring an advanced AI platform that predicts experimental data with 70%-90% correlation, reducing the number of required experiments by 60%!
Benefits:
Save time and resources.
Enhance research efficiency.
Focus on breakthroughs while AI handles the heavy lifting.
📩 Apply now to explore this game-changing technology and collaborate with us!
🚨 We’re Hiring Pilot Projects! 🚨 FREE PILOT project for biochemistry labs!
Reduce in vitro cost
phone nomber: 053-382-60-75
koshlan.tetiana@gmail.com
koshlan.tetiana@gmail.com
- Enzyme properties and the effect of substrate concentration
- Protein assay and standard curve generation
- Thin-layer chromatography
- ELISA.
- DNA/RNA Sequencing.
- Nutrition.
- Gel Electrophoresis.
- Antibodies & Antigens.
- Blotting Methods.
Benefit from modern AI-BinomLab technologies:
AI Platform for Accurate Experimental Data Prediction:
- activity of the complex,
- cell growth,
- affinity, IС50, Kd,
- survival,
- toxicity,
- drug efficacy,
- effect of protein modification and drug addition,
- structural changes,
- unfolding,
- denaturation,
- molecular weight of the complex, aggregation
- entropy change,
- enthalpy change,
- numerical stability parameter,
- potential energy,
- calculated Kd,
- heat maps,
- numerical values
- monomers, dimers,
- trimers, tetramers,
- protein-protein interaction
- peptides,
- protein+inhibitors+atoms,
- Antibody-Antigen
- RNA molecules
AI Platform for Predicting Structure, Composition, and Chemical Reactions of Substances
Suitable for the following molecules:
You will receive the following set of calculated data:
records data, and studies the functions, chemical processes
New! Tubulin Inhibitors: Decades of controversy.
In the last decade, conflicting data on the effectiveness of Rigosertib have accumulated. We make a Comparative numerical analysis: Rigosertib/ ON01500?
Let us conduct a comparative computational analysis for tubulin tetramers containing small chemical molecules (inhibitors): GTP, Rig, oN015000
Arrows indicate the calculated values of the movement of biochemical processes within the framework of the given formations.
The system is in search of molecular formations that meet the above conditions of thermodynamic equilibrium. Learn More
In the last decade, conflicting data on the effectiveness of Rigosertib have accumulated. We make a Comparative numerical analysis: Rigosertib/ ON01500?
Let us conduct a comparative computational analysis for tubulin tetramers containing small chemical molecules (inhibitors): GTP, Rig, oN015000
Arrows indicate the calculated values of the movement of biochemical processes within the framework of the given formations.
The system is in search of molecular formations that meet the above conditions of thermodynamic equilibrium. Learn More
Comparative numerical analysis: Rigosertib/ ON01500?
How much does it cost to use AI in biochemical experiments?
Modern technologies will allow you to get a large set of preliminary data for the price of 2.49 Euros for each small protein or peptide when ordering a study on a hundred similar amino acid sequences.
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