Assessing protein kinase selectivity with molecular dynamics and mm-pbsa binding free energy calculations

Investigation of the Inhibition Mechanism of Xanthine Oxidoreductase by Oxipurinol: A Computational Study

Xanthine oxidoreductase (XOR) is an enzyme found in various organisms. It converts hypoxanthine to xanthine and urate, which are crucial steps in purine elimination in humans. Elevated uric acid levels can lead to conditions like gout and hyperuricemia. Therefore, there is significant interest in developing drugs that target XOR for treating these conditions and other diseases. Oxipurinol, an analogue of xanthine, is a well-known inhibitor of XOR. Crystallographic studies have revealed that oxipurinol directly binds to the molybdenum cofactor (MoCo) in XOR. However, the precise details of the inhibition mechanism are still unclear, which would be valuable for designing more effective drugs with similar inhibitory functions. In this study, molecular dynamics and quantum mechanics/molecular mechanics calculations are employed to investigate the inhibition mechanism of XOR by oxipurinol. The study examines the structural and dynamic effects of oxipurinol on the pre-catalytic structure of the metabolite-bound system. Our results provide insights on the reaction mechanism catalyzed by the MoCo center in the active site, which aligns well with experimental findings. Furthermore, the results provide insights into the residues surrounding the active site and propose an alternative mechanism for developing alternative covalent inhibitors.

Computational Characterization of the Inhibition Mechanism of Xanthine Oxidoreductase by Topiroxostat

Xanthine oxidase (XO) is a member of the molybdopterin-containing enzyme family. It interconverts xanthine to uric acid as the last step of purine catabolism in the human body. The high uric acid concentration in the blood directly leads to human diseases like gout and hyperuricemia. Therefore, drugs that inhibit the biosynthesis of uric acid by human XO have been clinically used for many years to decrease the concentration of uric acid in the blood. In this study, the inhibition mechanism of XO and a new promising drug, topiroxostat (code: FYX-051), is investigated by employing molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) calculations. This drug has been reported to act as both a noncovalent and covalent inhibitor and undergoes a stepwise inhibition by all its hydroxylated metabolites, which include 2-hydroxy-FYX-051, dihydroxy-FYX-051, and trihydroxy-FYX-051. However, the detailed mechanism of inhibition of each metabolite remains elusive and can be useful for designing more effective drugs with similar inhibition functions. Hence, herein we present the computational investigation of the structural and dynamical effects of FYX-051 and the calculated reaction mechanism for all of the oxidation steps catalyzed by the molybdopterin center in the active site. Calculated results for the proposed reaction mechanisms for each metabolite's inhibition reaction in the enzyme's active site, binding affinities, and the noncovalent interactions with the surrounding amino acid residues are consistent with previously reported experimental findings. Analysis of the noncovalent interactions via energy decomposition analysis (EDA) and noncovalent interaction (NCI) techniques suggests that residues L648, K771, E802, R839, L873, R880, R912, F914, F1009, L1014, and A1079 can be used as key interacting residues for further hybrid-type inhibitor development.

Assessing the Performance of Screening MM/PBSA in Protein-Ligand Interactions

Accurate calculation of the binding free energies between a protein and a ligand is the primary objective of structure-based drug design, but it still remains a challenging problem. In this work, we apply the screening molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) method to calculate the binding affinity of protein-ligand interactions. Our results show that the performance of the screening MM/PBSA is better than that of the standard MM/PBSA, especially in a charged-ligand system. In addition, we also investigate the effect of the solute dielectric constant on the results, and find that the optimal solute dielectric constants are different between the neutral-ligand system and the charged-ligand system. Moreover, we also evaluate the effect of the atomic-charge methods on the performance of the screening MM/PBSA. The present study demonstrates that the screening MM/PBSA should be a reliable method for calculating binding energy of biosystems.

Calculation of Crystal-Solution Dissociation Constants

The calculation of dissociation constants is an important problem in molecular biophysics. For such a calculation, it is important to correctly calculate both terms of the binding free energy; that is, the enthalpy and entropy of binding. Both these terms can be computed using molecular dynamics simulations, but this approach is very computationally expensive, and entropy calculations are especially slow. We develop an alternative very fast method of calculating the binding entropy and dissociation constants. The main part of our approach is based on the evaluation of movement ranges of molecules in the bound state. Then, the range of molecular movements in the bound state (here, in molecular crystals) is used for the calculation of the binding entropies and, then (using, in addition, the experimentally measured sublimation enthalpies), the crystal-to-vapor dissociation constants. Previously, we considered the process of the reversible sublimation of small organic molecules from crystals to vapor. In this work, we extend our approach by considering the dissolution of molecules, in addition to their sublimation. Similar to the sublimation case, our method shows a good correlation with experimentally measured dissociation constants at the dissolution of crystals.

Divide-and-link peptide docking: a fragment-based peptide docking protocol

Protein-peptide interactions are crucial for various important cellular regulations, and are also a basis for understanding protein-protein interactions, protein folding and peptide drug design. Due to the limited structural data obtained using experimental methods, it is necessary to predict protein-peptide interaction modes using computational methods. In the present work, we designed a fragment-based docking protocol, Divide-and-Link Peptide Docking (DLPepDock), to predict protein-peptide binding modes. This protocol contains the following steps: dividing the peptide into fragments and separately docking the fragments using a third-party small molecular docking tool, linking the docked fragmental poses to form the whole peptide conformations via fragmental coordinate transformation using our in-house program, removing unreasonable poses according to several geometrical filters, extracting representative conformations after clustering for further minimization using the steepest descent and conjugation gradient methods based on a full-atom molecular force field and finally scoring using the MM/PBSA binding energy calculation implemented in Amber. When tested on the LEADS-PEP benchmark data set of 26 diverse complexes with peptides of 6-12 residues, FlexPepDock ab initio and AutoDock CrankPep achieved superior results. DLPepDock performed better than the other 15 docking protocols implemented in nine docking programs (HPepDock, DockThor, rDock, Glide, LeDock, AutoDock, AutoDock Vina, Surflex, and GOLD). The Linux scripts to call the third-party tools and run all the calculations.

Assessing the performance of MM/PBSA and MM/GBSA methods. 9. Prediction reliability of binding affinities and binding poses for protein-peptide complexes

A significant number of protein-protein interactions (PPIs) are mediated through the interactions between proteins and peptide segments, and therefore determination of protein-peptide interactions (PpIs) is critical to gain an in-depth understanding of the PPI network and even design peptides or small molecules capable of modulating PPIs. Computational approaches, especially molecular docking, provide an efficient way to model PpIs, and a reliable scoring function that can recognize the correct binding conformations for protein-peptide complexes is one of the most important components in protein-peptide docking. The end-point binding free energy calculation methods, such as MM/GBSA and MM/PBSA, are theoretically more rigorous than most empirical and semi-empirical scoring functions designed for protein-peptide docking, but their performance in predicting binding affinities and binding poses for protein-peptide systems has not been systematically assessed. In this study, we first evaluated the capability of MM/GBSA and MM/PBSA with different solvation models, interior dielectric constants (εin) and force fields to predict the binding affinities for 53 protein-peptide complexes. For the 19 short peptides with 5-12 residues, MM/PBSA based on the minimized structures in explicit solvent with the ff99 force field and εin = 2 yields the best correlation between the predicted binding affinities and the experimental data (rp = 0.748), while for the 34 medium-size peptides with 20-25 residues, MM/GBSA based on 1 ns of molecular dynamics (MD) simulations in implicit solvent with the ff03 force field, the GBOBC1 model and a low interior dielectric constant (εin = 1) yields the best accuracy (rp = 0.735). Then, we assessed the rescoring capability of MM/PBSA and MM/GBSA to distinguish the correct binding conformations from the decoys for 112 protein-peptide systems. The results illustrate that MM/PBSA based on the minimized structures with the ff99 or ff14SB force field and MM/GBSA based on the minimized structures with the ff03 force field show excellent capability to recognize the near-native binding poses for the short and medium-size peptides, respectively, and they outperform the predictions given by two popular protein-peptide docking algorithms (pepATTRACT and HPEPDOCK). Therefore, MM/PBSA and MM/GBSA are powerful tools to predict the binding affinities and identify the correct binding poses for protein-peptide systems.

Assessing the performance of MM/PBSA and MM/GBSA methods. 8. Predicting binding free energies and poses of protein-RNA complexes

Molecular docking provides a computationally efficient way to predict the atomic structural details of protein-RNA interactions (PRI), but accurate prediction of the three-dimensional structures and binding affinities for PRI is still notoriously difficult, partly due to the unreliability of the existing scoring functions for PRI. MM/PBSA and MM/GBSA are more theoretically rigorous than most scoring functions for protein-RNA docking, but their prediction performance for protein-RNA systems remains unclear. Here, we systemically evaluated the capability of MM/PBSA and MM/GBSA to predict the binding affinities and recognize the near-native binding structures for protein-RNA systems with different solvent models and interior dielectric constants (ε_in). For predicting the binding affinities, the predictions given by MM/GBSA based on the minimized structures in explicit solvent and the GB^GBn1 model with ε_in = 2 yielded the highest correlation with the experimental data. Moreover, the MM/GBSA calculations based on the minimized structures in implicit solvent and the GB^GBn1 model distinguished the near-native binding structures within the top 10 decoys for 117 out of the 148 protein-RNA systems (79.1%). This performance is better than all docking scoring functions studied here. Therefore, the MM/GBSA rescoring is an efficient way to improve the prediction capability of scoring functions for protein-RNA systems.

Sublimation Entropy and Dissociation Constants Prediction by Quantitative Evaluation of Molecular Mobility in Crystals

Prediction of binding free energies (or dissociation constants) is a crucial challenge for computational biochemistry. One of the main problems here consists in fast and accurate evaluation of binding entropy, which is far more time-consuming than evaluation of binding enthalpy. Here, we offer a fast and rather accurate approach to evaluate the sublimation entropy (i.e., entropy of binding of a vapor molecule to a crystal, taken with the opposite sign) from the average range of molecular movements in the solid state. To estimate this range (and the corresponding amplitude), we considered equilibrium sublimation of small organic molecules from molecular crystals. The calculations were based on experimental data on the sublimation enthalpy, pressure of saturated vapor, and structural characteristics of the molecule in question. The resulting average amplitude (0.17 ± 0.01 Å) of molecular movements in crystals was used to predict sublimation entropies and dissociation constants for sublimation of 28 molecular crystals. The results of these predictions are in close agreement with experimental values.

Potential inhibitory effect of indolizine derivatives on the two enzymes: nicotinamide phosphoribosyltransferase and beta lactamase, a molecular dynamics study

Nicotinamide phosphoribosyl-transferases (NAMPT) are enzymes that play a role in targeting cancer metabolism, while beta lactamases are involved in bacterial resistance to beta-lactam antibiotics. Many protein inhibitors exhibit such property which is often correlated with their cellular potency. In order to understand such a phenomenon, the present article conducts an analysis of the dynamic behavior of complexes formed by the inhibitors, that is indolizine derivatives, with the studied enzymes. Both docking and molecular dynamics led to identification of their interactions and showed the mechanism of inhibition of the two studied enzymes. The differences in the behavior of ligand at the active sites of beta lactamases and nicotinamide phosphoribosyl-transferases are indicated by structural and enthalpy values.

Assessing the performance of MM/PBSA and MM/GBSA methods. 4. Accuracies of MM/PBSA and MM/GBSA methodologies evaluated by various simulation protocols using PDBbind data set

By using different evaluation strategies, we systemically evaluated the performance of Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) and Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) methodologies based on more than 1800 protein-ligand crystal structures in the PDBbind database. The results can be summarized as follows: (1) for the one-protein-family/one-binding-ligand case which represents the unbiased protein-ligand complex sampling, both MM/GBSA and MM/PBSA methodologies achieve approximately equal accuracies at the interior dielectric constant of 4 (with rp = 0.408 ± 0.006 of MM/GBSA and rp = 0.388 ± 0.006 of MM/PBSA based on the minimized structures); while for the total dataset (1864 crystal structures), the overall best Pearson correlation coefficient (rp = 0.579 ± 0.002) based on MM/GBSA is better than that of MM/PBSA (rp = 0.491 ± 0.003), indicating that biased sampling may significantly affect the accuracy of the predicted result (some protein families contain too many instances and can bias the overall predicted accuracy). Therefore, family based classification is needed to evaluate the two methodologies; (2) the prediction accuracies of MM/GBSA and MM/PBSA for different protein families are quite different with rp ranging from 0 to 0.9, whereas the correlation and ranking scores (an averaged rp/rs over a list of protein folds and also representing the unbiased sampling) given by MM/PBSA (rp-score = 0.506 ± 0.050 and rs-score = 0.481 ± 0.052) are comparable to those given by MM/GBSA (rp-score = 0.516 ± 0.047 and rs-score = 0.463 ± 0.047) at the fold family level; (3) for the overall prediction accuracies, molecular dynamics (MD) simulation may not be quite necessary for MM/GBSA (rp-minimized = 0.579 ± 0.002 and rp-1ns = 0.564 ± 0.002), but is needed for MM/PBSA (rp-minimized = 0.412 ± 0.003 and rp-1ns = 0.491 ± 0.003). However, for the individual systems, whether to use MD simulation is depended. (4) both MM/GBSA and MM/PBSA may be unable to give successful predictions for the ligands with high formal charges, with the Pearson correlation coefficient ranging from 0.621 ± 0.003 (neutral ligands) to 0.125 ± 0.142 (ligands with a formal charge of 5). Therefore, it can be summarized that, although MM/GBSA and MM/PBSA perform similarly in the unbiased dataset, for the currently available crystal structures in the PDBbind database, compared with MM/GBSA, which may be used in multi-target comparisons, MM/PBSA is more sensitive to the investigated systems, and may be more suitable for individual-target-level binding free energy ranking. This study may provide useful guidance for the post-processing of docking based studies.

The impact of molecular dynamics on drug design: applications for the characterization of ligand-macromolecule complexes

Among all tools available to design new drugs, molecular dynamics (MD) simulations have become an essential technique. Initially developed to investigate molecular models with a limited number of atoms, computers now enable investigations of large macromolecular systems with a simulation time reaching the microsecond range. The reviewed articles cover four years of research to give an overview on the actual impact of MD on the current medicinal chemistry landscape with a particular emphasis on studies of ligand-protein interactions. With a special focus on studies combining computational approaches with data gained from other techniques, this review shows how deeply embedded MD simulations are in drug design strategies and articulates what the future of this technique could be.

Binding of pyrazole-based inhibitors to Mycobacterium tuberculosis pantothenate synthetase: docking and MM-GB(PB)SA analysis

Recently, the search for new drugs against tuberculosis (TB) has been a hot topic and the search for new inhibitors against validated drug targets and pathways other than those currently targeted by known drugs is suggested to be the most promising way forward. Mycobacterium tuberculosis pantothenate synthetase (MTBPS) happens to be one of such targets. In a quest to carry out virtual screening for active inhibitors against MTBPS and to get ideas for the design of new inhibitors against this target, we have docked a set of pyrazole-based inhibitors to the active site of this enzyme. The docking solutions were post processed using the MM-PB(GB)SA method and molecular dynamic simulations in order to analyze and validate the two previously proposed binding modes. The results show that both the MM-PBSA and MM-GBSA were able to discriminate between active and inactive compounds. Moreover, the pharmacophore-based scoring method proved efficient in discriminating the active compounds from inactives. From this work a protocol for screening of potential inhibitors of the enzyme from commercially available databases has been devised.

Structural and dynamic investigation of bovine folate receptor alpha (FOLR1), and role of ultra-high temperature processing on conformational and thermodynamic characteristics of FOLR1-folate complex

The folate receptor alpha (FOLR1) present in milk has widely been studied to investigate the effects of pasteurization, ultra-high temperature (UHT) processing and fermentation on net folate concentration. However, the folate binding mechanism with FOLR1, and effect of temperature on FOLR1-folate complex is poorly explored till now in bovine milk which is a chief resource of folate. Despite of enormous importance of folic acid and the routine intake of bovine milk, folic acid deficiency diseases are common in human race. To understand the folate deficiency in milk after processing, in absence of experimental structure, 3D model of bovine FOLR1 (bvFOLR1) was built followed by 40ns molecular dynamics (MD) simulation. The folate and its derivatives binding sites in bvFOLR1 were anticipated by molecular docking using AutoDock 4.2. Essential MD studies suggested the presence of a longer signal peptide (22 residues) and a short propeptide (7 residues) at the C-terminus that may cleaved during post-translational modification. MD analysis of bvFOLR1-folate complex at 298, 323, 353, 373 and 408K followed by binding energy (BE) calculation showed maximum binding affinity at ∼353K. However, at 373K and UHT (408K), the folate BE is significantly decreased with substantial conformational alteration. Heating at UHT followed by cooling within 298-408K range demoed no structural reformation with temperature reduction, and the folate was displaced from the active site. This study presented the disintegration of folate from bvFOLR1 during high temperature processing and revealed a lower folate concentration in UHT milk and dairy products.

UNDERSTANDING THE MOLECULAR MECHANISM OF BINDING MODES OF AURORA A INHIBITORS BY LONG TIME SCALE GPU DYNAMICS

Inhibition of Aurora A kinase interaction is considered to be a promising approach for the discovery of new molecularly targeted cancer therapeutics. In this study, the binding mechanisms of two different inhibitors with a contrasting binding affinity to Aurora A were investigated by long time scale GPU molecular dynamics (MD) simulations coupled with molecular mechanics-Poisson–Boltzmann/generalized Born surface area (MM-PB/GBSA) method. The results showed that the predicted binding free energies of these two complexes were consistent with the experimental data. Through analyzing the individual energy components of binding free energy, we found that the van der Waals contribution was the main force to drive the inhibitor–protein binding and the electrostatic contribution was also a crucial factor for the inhibitor–Aurora A binding. The structural analysis demonstrated that the inhibitor HPM could produce more hydrophobic interaction contacts with Aurora A than that of 2JZ, and the loss of key hydrogen bonds between the inhibitor and residue Arg137 in the hinge region of Aurora A was another important reason for the weaker binding affinity of 2JZ to Aurora A. This study sheds more light on the development of the efficient inhibitors targeting the Aurora A.

Differences in the binding affinities of ErbB family: heterogeneity in the prediction of resistance mutants

The pressure exerted by drugs targeted to a protein in any therapy inevitably leads to the emergence of drug resistance. One major mechanism of resistance involves the mutation of key residues in the target protein. Drugs that competitively replace a natural substrate are often made ineffective by mutations that reduce the drug’s affinity relative to that of the natural substrate. Hence atomic level understanding of the mechanisms that underlie this behavior is of utmost importance in efforts to design new drugs that can target such mutant proteins. Methods that can predict these mutations before they appear in clinic would be a major advance in the selection of the appropriate treatment strategy in patients. The present computational approach aims to model this emergence in EGFR and ErbB2 after treatment with the drug lapatinib, by investigating the structural, dynamic and energetic effects on these kinases when bound to the natural substrate ATP and to lapatinib. The study reveals binding modes and subpopulations that are presumably normally cryptic and these have been analyzed extensively here with respect to sites that are predicted to be hotspots for resisting mutations. These positions are compared in the context of currently available data from laboratory-based experiments and mechanistic details, at the atomistic level, of the origin of resistance are developed. The prediction of novel mutations, if validated by their emergence in the clinic, will make these methods as a powerful predictive tool which can be used in the design of new kinase inhibitors.

In silico design: extended molecular dynamic simulations of a new series of dually acting inhibitors against EGFR and HER2

Based on the hit structures that have been identified in our previous studies against EGFR and HER2, new potential inhibitors that share the same scaffold of the hit structures are designed and screened in silico. Insights into understanding the potential inhibitory effect of the new inhibitors against both EGFR and HER2 receptors is obtained using extended molecular dynamics (MD) simulations and different scoring techniques. The binding mechanisms and dynamics are detailed with respect to two approved inhibitors against EGFR (lapatinib) and HER2 (SYR127063). The best scoring inhibitor (T9) is chosen for additional in silico investigation against both the wild-type and T790M mutant strain of EGFR and the wild-type HER2. The results reveal that certain substitution patterns increase the stability and assure stronger binding and higher H-bond occupancy of the conserved water molecule that is commonly observed with kinase crystal structures. Furthermore, the new inhibitor (T9) forms stable interactions with the mutant strain as a direct consequence of the enhanced ability to form additional hydrogen bonding interactions with binding site residues.

Exploring PHD fingers and H3K4me0 interactions with molecular dynamics simulations and binding free energy calculations: AIRE-PHD1, a comparative study

PHD fingers represent one of the largest families of epigenetic readers capable of decoding post-translationally modified or unmodified histone H3 tails. Because of their direct involvement in human pathologies they are increasingly considered as a potential therapeutic target. Several PHD/histone-peptide structures have been determined, however relatively little information is available on their dynamics. Studies aiming to characterize the dynamic and energetic determinants driving histone peptide recognition by epigenetic readers would strongly benefit from computational studies. Herein we focus on the dynamic and energetic characterization of the PHD finger subclass specialized in the recognition of histone H3 peptides unmodified in position K4 (H3K4me0). As a case study we focused on the first PHD finger of autoimmune regulator protein (AIRE-PHD1) in complex with H3K4me0. PCA analysis of the covariance matrix of free AIRE-PHD1 highlights the presence of a "flapping" movement, which is blocked in an open conformation upon binding to H3K4me0. Moreover, binding free energy calculations obtained through Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) methodology are in good qualitative agreement with experiments and allow dissection of the energetic terms associated with native and alanine mutants of AIRE-PHD1/H3K4me0 complexes. MM/PBSA calculations have also been applied to the energetic analysis of other PHD fingers recognizing H3K4me0. In this case we observe excellent correlation between computed and experimental binding free energies. Overall calculations show that H3K4me0 recognition by PHD fingers relies on compensation of the electrostatic and polar solvation energy terms and is stabilized by non-polar interactions.

Exploring the inter-molecular interactions in amyloid-β protofibril with molecular dynamics simulations and molecular mechanics Poisson-Boltzmann surface area free energy calculations

Aggregation of amyloid-β (Aβ) peptides correlates with the pathology of Alzheimer's disease. However, the inter-molecular interactions between Aβ protofibril remain elusive. Herein, molecular mechanics Poisson-Boltzmann surface area analysis based on all-atom molecular dynamics simulations was performed to study the inter-molecular interactions in Aβ(17-42) protofibril. It is found that the nonpolar interactions are the important forces to stabilize the Aβ(17-42) protofibril, while electrostatic interactions play a minor role. Through free energy decomposition, 18 residues of the Aβ(17-42) are identified to provide interaction energy lower than -2.5 kcal/mol. The nonpolar interactions are mainly provided by the main chain of the peptide and the side chains of nine hydrophobic residues (Leu17, Phe19, Phe20, Leu32, Leu34, Met35, Val36, Val40, and Ile41). However, the electrostatic interactions are mainly supplied by the main chains of six hydrophobic residues (Phe19, Phe20, Val24, Met35, Val36, and Val40) and the side chains of the charged residues (Glu22, Asp23, and Lys28). In the electrostatic interactions, the overwhelming majority of hydrogen bonds involve the main chains of Aβ as well as the guanidinium group of the charged side chain of Lys28. The work has thus elucidated the molecular mechanism of the inter-molecular interactions between Aβ monomers in Aβ(17-42) protofibril, and the findings are considered critical for exploring effective agents for the inhibition of Aβ aggregation.

Molecular mechanism of the effects of salt and pH on the affinity between protein A and human immunoglobulin G1 revealed by molecular simulations

Protein A from the bacterium Staphylococcus aureus (SpA) has been widely used as an affinity ligand for purification of immunoglobulin G (IgG). The affinity between SpA and IgG is affected differently by salt and pH, but their molecular mechanisms still remain unclear. In this work, molecular dynamics simulations and molecular mechanics Poisson-Boltzmann surface area analysis were performed to investigate the salt (NaCl) and pH effects on the affinity between SpA and human IgG1 (hIgG1). It is found that salt and pH affect the interactions of the hot spots of SpA by different mechanisms. In the salt solution, the compensations between helices I and II of SpA as well as between the nonpolar and electrostatic energies make the binding free energy independent of salt concentration. At pH 3.0, the unfavorable electrostatic interactions increase greatly and become the driving force for dissociation of the SpA-hIgG1 complex. They mainly come from the strong electrostatic repulsions between positively charged residues (H137, R146, and K154) of SpA and the positively charged residues of hIgG1. It is considered to be the molecular basis for hIgG1 elution from SpA-based affinity adsorbents at pH 3.0. The dissociation mechanism is then used to refine the binding model of SpA to hIgG1. The model is expected to help design high-affinity peptide ligands of IgG.