A biochemical model of matrix metalloproteinase 9 activation and inhibition

Matrix metalloproteinases (MMPs) are a class of extracellular and membrane-bound proteases involved in an array of physiological processes, including angiogenesis. We present a detailed computational model of MMP9 activation and inhibition. Our model is validated to existing biochemical experimental data. We determine kinetic rate constants for the processes of MMP9 activation by MMP3, MMP10, MMP13, and trypsin; inhibition by the tissue inhibitors of metalloproteinases (TIMPs) 1 and 2; and MMP9 deactivation. This computational approach allows us to investigate discrepancies in our understanding of the interaction of MMP9 with TIMP1. Specifically, we find that inhibition due to a single binding event cannot describe MMP9 inhibition by TIMP1. Temporally accurate biphasic inhibition requires either an additional isomerization step or a second lower affinity isoform of MMP9. We also theoretically characterize the MMP3/TIMP2/pro-MMP9 and MMP3/TIMP1/pro-MMP9 systems. We speculate that these systems differ significantly in their time scales of activation and inhibition such that MMP9 is able to temporarily overshoot its final equilibrium value in the latter. Our numerical simulations suggest that the ability of pro-MMP9 to complex TIMP1 increases this overshoot. In all, our analysis serves as a summary of existing kinetic data for MMP9 and a foundation for future models utilizing MMP9 or other MMPs under physiologically well defined microenvironments.     

Computational design of antibody-affinity improvement beyond in vivo maturation

Antibodies are used extensively in diagnostics and as therapeutic agents. Achieving high-affinity binding is important for expanding detection limits, extending dissociation half-times, decreasing drug dosages and increasing drug efficacy. However, antibody-affinity maturation in vivo often fails to produce antibody drugs of the targeted potency, making further affinity maturation in vitro by directed evolution or computational design necessary. Here we present an iterative computational design procedure that focuses on electrostatic binding contributions and single mutants. By combining multiple designed mutations, a tenfold affinity improvement to 52 pM was engineered into the anti-epidermal growth factor receptor drug cetuximab (Erbitux), and a 140-fold improvement in affinity to 30 pM was obtained for the anti-lysozyme model antibody D44.1. The generality of the methods was further demonstrated through identification of known affinity-enhancing mutations in the therapeutic antibody bevacizumab (Avastin) and the model anti-fluorescein antibody 4-4-20. These results demonstrate computational capabilities for enhancing and accelerating the development of protein reagents and therapeutics.     

Structural Model for the Interaction of a Designed Ankyrin Repeat Protein with the Human Epidermal Growth Factor Receptor 2

Designed Ankyrin Repeat Proteins are a class of novel binding proteins that can be selected and evolved to bind to targets with high affinity and specificity. We are interested in the DARPin H10-2-G3, which has been evolved to bind with very high affinity to the human epidermal growth factor receptor 2 (HER2). HER2 is found to be over-expressed in 30% of breast cancers, and is the target for the FDA-approved therapeutic monoclonal antibodies trastuzumab and pertuzumab and small molecule tyrosine kinase inhibitors. Here, we use computational macromolecular docking, coupled with several interface metrics such as shape complementarity, interaction energy, and electrostatic complementarity, to model the structure of the complex between the DARPin H10-2-G3 and HER2. We analyzed the interface between the two proteins and then validated the structural model by showing that selected HER2 point mutations at the putative interface with H10-2-G3 reduce the affinity of binding up to 100-fold without affecting the binding of trastuzumab. Comparisons made with a subsequently solved X-ray crystal structure of the complex yielded a backbone atom root mean square deviation of 0.84–1.14 Ångstroms. The study presented here demonstrates the capability of the computational techniques of structural bioinformatics in generating useful structural models of protein-protein interactions.     

Computational Assessment of Protein–protein Binding Affinity by Reversely Engineering the Energetics in Protein Complexes

The cellular functions of proteins are maintained by forming diverse complexes. The stability of these complexes is quantified by the measurement of binding affinity, and mutations that alter the binding affinity can cause various diseases such as cancer and diabetes. As a result, accurate estimation of the binding stability and the effects of mutations on changes of binding affinity is a crucial step to understanding the biological functions of proteins and their dysfunctional consequences. It has been hypothesized that the stability of a protein complex is dependent not only on the residues at its binding interface by pairwise interactions but also on all other remaining residues that do not appear at the binding interface. Here, we computationally reconstruct the binding affinity by decomposing it into the contributions of interfacial residues and other non-interfacial residues in a protein complex. We further assume that the contributions of both interfacial and non-interfacial residues to the binding affinity depend on their local structural environments such as solvent-accessible surfaces and secondary structural types. The weights of all corresponding parameters are optimized by Monte-Carlo simulations. After cross-validation against a large-scale dataset, we show that the model not only shows a strong correlation between the absolute values of the experimental and calculated binding affinities, but can also be an effective approach to predict the relative changes of binding affinity from mutations. Moreover, we have found that the optimized weights of many parameters can capture the first-principle chemical and physical features of molecular recognition, therefore reversely engineering the energetics of protein complexes. These results suggest that our method can serve as a useful addition to current computational approaches for predicting binding affinity and understanding the molecular mechanism of protein–protein interactions.     

Combining different design strategies for rational affinity maturation of the MICA-NKG2D interface

We redesigned residues on the surface of MICA, a protein that binds the homodimeric immunoreceptor NKG2D, to increase binding affinity with a series of rational, incremental changes. A fixed-backbone RosettaDesign protocol scored a set of initial mutations, which we tested by surface plasmon resonance for thermodynamics and kinetics of NKG2D binding, both singly and in combination. We combined the best four mutations at the surface with three affinity-enhancing mutations below the binding interface found with a previous design strategy. After curating design scores with three cross-validated tests, we found a linear relationship between free energy of binding and design score, and to a lesser extent, enthalpy and design score. Multiple mutants bound with substantial subadditivity, but in at least one case full additivity was observed when combining distant mutations. Altogether, combining the best mutations from the two strategies into a septuple mutant enhanced affinity by 50-fold, to 50 nM, demonstrating a simple, effective protocol for affinity enhancement.     

Designed Loop Extension Followed by Combinatorial Screening Confers High Specificity to a Broad Matrix Metalloproteinase Inhibitor

Matrix metalloproteinases (MMPs) are key drivers of various diseases, including cancer. Development of probes and drugs capable of selectively inhibiting the individual members of the large MMP family remains a persistent challenge. The inhibitory N-terminal domain of tissue inhibitor of metalloproteinases-2 (N-TIMP2), a natural broad MMP inhibitor, can provide a scaffold for protein engineering to create more selective MMP inhibitors. Here, we pursued a unique approach harnessing both computational design and combinatorial screening to confer high binding specificity toward a target MMP in preference to an anti-target MMP. We designed a loop extension of N-TIMP2 to allow new interactions with the non-conserved MMP surface and generated an efficient focused library for yeast surface display, which was then screened for high binding to the target MMP-14 and low binding to anti-target MMP-3. Deep sequencing analysis identified the most promising variants, which were expressed, purified, and tested for selectivity of inhibition. Our best N-TIMP2 variant exhibited 29 pM binding affinity to MMP-14 and 2.4 µM affinity to MMP-3, revealing 7500-fold greater specificity than WT N-TIMP2. High-confidence structural models were obtained by including NGS data in the AlphaFold multiple sequence alignment. The modeling together with experimental mutagenesis validated our design predictions, demonstrating that the loop extension packs tightly against non-conserved residues on MMP-14 and clashes with MMP-3. This study demonstrates how introduction of loop extensions in a manner guided by target protein conservation data and loop design can offer an attractive strategy to achieve specificity in design of protein ligands.     

Combinatorial and Computational Approaches to Identify Interactions of Macrophage Colony-stimulating Factor (M-CSF) and Its Receptor c-FMS

The molecular interactions between macrophage colony-stimulating factor (M-CSF) and the tyrosine kinase receptor c-FMS play a key role in the immune response, bone metabolism, and the development of some cancers. Because no x-ray structure is available for the human M-CSF·c-FMS complex, the binding epitope for this complex is largely unknown. Our goal was to identify the residues that are essential for binding of the human M-CSF to c-FMS. For this purpose, we used a yeast surface display (YSD) approach. We expressed a combinatorial library of monomeric M-CSF (M-CSF_M) single mutants and screened this library to isolate variants with reduced affinity for c-FMS using FACS. Sequencing yielded a number of single M-CSF_M variants with mutations both in the direct binding interface and distant from the binding site. In addition, we used computational modeling to map the identified mutations onto the M-CSF_M structure and to classify the mutations into three groups as follows: those that significantly decrease protein stability; those that destroy favorable intermolecular interactions; and those that decrease affinity through allosteric effects. To validate the YSD and computational data, M-CSF_M and three variants were produced as soluble proteins; their affinity and structure were analyzed; and very good correlations with both YSD data and computational predictions were obtained. By identifying the M-CSF_M residues critical for M-CSF·c-FMS interactions, we have laid down the basis for a deeper understanding of the M-CSF·c-FMS signaling mechanism and for the development of target-specific therapeutic agents with the ability to sterically occlude the M-CSF·c-FMS binding interface.     

Distinct modes of collagen type I proteolysis by matrix metalloproteinase (MMP) 2 and membrane type I MMP during the migration of a tip endothelial cell: insights from a computational model

Matrix metalloproteinases (MMPs) are a family of enzymes responsible for the proteolytic processing of extracellular matrix (ECM) structural proteins under physiological and pathological conditions. During sprouting angiogenesis, the MMPs expressed by a single "tip" endothelial cell exhibit proteolytic activity that allows the cells of the sprouting vessel bud to migrate into the ECM. Membrane type I matrix metalloproteinase (MT1-MMP) and the diffusible matrix metalloproteinase MMP2, in the presence of the tissue inhibitor of metalloproteinases TIMP2, constitute a system of proteins that play an important role during the proteolysis of collagen type I matrices. Here, we have formulated a computational model to investigate the proteolytic potential of such a tip endothelial cell. The cell expresses MMP2 in its proenzyme form, pro-MMP2, as well as MT1-MMP and TIMP2. The interactions of the proteins are described by a biochemically detailed reaction network. Assuming that the rate-limiting step of the migration is the ability of the tip cell to carry out proteolysis, we have estimated cell velocities for matrices of different collagen content. The estimated velocities of a few microns per hour are in agreement with experimental data. At high collagen content, proteolysis was carried out primarily by MT1-MMP and localized to the cell leading edge, whereas at lower concentrations, MT1-MMP and MMP2 were found to act in parallel, causing proteolysis in the vicinity of the leading edge. TIMP2 is a regulator of the proteolysis localization because it can shift the activity of MT1-MMP from its enzymatic toward its activatory mode, suggesting a tight mechanosensitive regulation of the enzymes and inhibitor expression. The model described here provides a foundation for quantitative studies of angiogenesis in extracellular matrices of different compositions, both in vitro and in vivo. It also identifies critical parameters whose values are not presently available and which should be determined in future experiments.     

Computational design of calmodulin mutants with up to 900-fold increase in binding specificity

Calmodulin (CaM) is a ubiquitous second messenger protein that regulates a variety of structurally and functionally diverse targets in response to changes in Ca²⁺ concentration. CaM-dependent protein kinase II (CaMKII) and calcineurin (CaN) are the prominent CaM targets that play an opposing role in many cellular functions including synaptic regulation. Since CaMKII and CaN compete for the available Ca²⁺/CaM, the differential affinity of these enzymes for CaM is crucial for achieving a balance in Ca²⁺ signaling. We used the computational protein design approach to modify CaM binding specificity for these two targets. Starting from the X-ray structure of CaM in complex with the CaM-binding domain of CaMKII, we optimized CaM interactions with CaMKII by introducing mutations into the CaM sequence. CaM optimization was performed with a protein design program, ORBIT, using a modified energy function that emphasized intermolecular interactions in the sequence selection procedure. Several CaM variants were experimentally constructed and tested for binding to the CaMKII and CaN peptides using the surface plasmon resonance technique. Most of our CaM mutants demonstrated small increase in affinity for the CaMKII peptide and substantial decrease in affinity for the CaN peptide compared to that of wild-type CaM. Our best CaM design exhibited an about 900-fold increase in binding specificity towards the CaMKII peptide, becoming the highest specificity switch achieved in any protein-protein interface through the computational protein design approach. Our results show that computational redesign of protein-protein interfaces becomes a reliable method for altering protein binding affinity and specificity.     

Constraining specificity in the N-domain of tissue inhibitor of metalloproteinases-1; gelatinase-selective inhibitors

The tissue inhibitors of metalloproteinases (TIMPs) are endogenous inhibitors of the matrix metalloproteinases (MMPs). Since unregulated MMP activities are linked to arthritis, cancer, and atherosclerosis, TIMP variants that are selective inhibitors of disease-related MMPs have potential therapeutic value. The structures of TIMP/MMP complexes reveal that most interactions with the MMP involve the N-terminal pentapeptide of TIMP and the C-D beta-strand connector which occupy the primed and unprimed regions of the active site. The loop between beta-strands A and B forms a secondary interaction site for some MMPs, ranging from multiple contacts in the TIMP-2/membrane type-1 (MT1)-MMP complex to none in the TIMP-1/MMP-1 complex. TIMP-1 and its inhibitory domain, N-TIMP-1, are weak inhibitors of MT1-MMP; inhibition is not improved by grafting the longer AB loop from TIMP-2 into N-TIMP-1, but this change impairs binding to MMP-3 and MMP-7. Mutational studies with N-TIMP-1 suggest that its weak inhibition of MT1-MMP, as compared to other N-TIMPs, arises from multiple (>3) sequence differences in the interaction site. Substitutions for Thr2 of N-TIMP-1 strongly influence MMP selectivity; Arg and Gly, that generally reduce MMP affinity, have less effect on binding to MMP-9. When the Arg mutation is added to the N-TIMP-1(AB2) mutant, it produces a gelatinase-specific inhibitor with Ki values of 2.8 and 0.4 nM for MMP-2 and -9, respectively. Interestingly, the Gly mutant has a Ki of 2.1 nM for MMP-9 and >40 muM for MMP-2, indicating that engineered TIMPs can discriminate between MMPs in the same subfamily.     

Computational Assessment of Protein–protein Binding Affinity by Reversely Engineering the Energetics in Protein Complexes

The cellular functions of proteins are maintained by forming diverse complexes. The stability of these complexes is quantified by the measurement of binding affinity, and mutations that alter the binding affinity can cause various diseases such as cancer and diabetes. As a result, accurate estimation of the binding stability and the effects of mutations on changes of binding affinity is a crucial step to understanding the biological functions of proteins and their dysfunctional consequences. It has been hypothesized that the stability of a protein complex is dependent not only on the residues at its binding interface by pairwise interactions but also on all other remaining residues that do not appear at the binding interface. Here, we computationally reconstruct the binding affinity by decomposing it into the contributions of interfacial residues and other non-interfacial residues in a protein complex. We further assume that the contributions of both interfacial and non-interfacial residues to the binding affinity depend on their local structural environments such as solvent-accessible surfaces and secondary structural types. The weights of all corresponding parameters are optimized by Monte-Carlo simulations. After cross-validation against a large-scale dataset, we show that the model not only shows a strong correlation between the absolute values of the experimental and calculated binding affinities, but can also be an effective approach to predict the relative changes of binding affinity from mutations. Moreover, we have found that the optimized weights of many parameters can capture the first-principle chemical and physical features of molecular recognition, therefore reversely engineering the energetics of protein complexes. These results suggest that our method can serve as a useful addition to current computational approaches for predicting binding affinity and understanding the molecular mechanism of protein–protein interactions.     

Expression of bone morphogenetic proteins, matrix metalloproteinases and inhibitors of matrix metalloproteinases in lung cancers and their prognostic significance

Matrix metalloproteinases (MMP) and their tissue inhibitors (TIMP) are one of the molecules that have become a topic of great interest among scientists studying lung cancers. There is a distinct tendency toward higher expression of selected MMP and TIMP in tumor lung tissue. Furthermore, there is a significant correlation between high expression of TIMP-1 or MMP-2 in lung cancer and shortened survival and between high expression of TIMP-1 or MMP-7 in lung cancer and higher stage of disease. There have been only a few articles about the role of bone morphogenetic proteins (BMP) in lung cancer pathogenesis published so far in which BMP-2 or BMP-4 were overexpressed. It was also shown that BMP-2 stimulates tumor growth while BMP-4 inhibits it. This article is mainly concentrated on the expression of MMP, TIMP and BMP in lung cancers, but also it shows the significance of these proteins.     

Action-at-a-distance interactions enhance protein binding affinity

The identification of protein mutations that enhance binding affinity may be achieved by computational or experimental means, or by a combination of the two. Sources of affinity enhancement may include improvements to the net balance of binding interactions of residues forming intermolecular contacts at the binding interface, such as packing and hydrogen-bonding interactions. Here we identify noncontacting residues that make substantial contributions to binding affinity and that also provide opportunities for mutations that increase binding affinity of the TEM1 beta-lactamase (TEM1) to the beta-lactamase inhibitor protein (BLIP). A region of BLIP not on the direct TEM1-binding surface was identified for which changes in net charge result in particularly large increases in computed binding affinity. Some mutations to the region have previously been characterized, and our results are in good correspondence with this results of that study. In addition, we propose novel mutations to BLIP that were computed to improve binding significantly without contacting TEM1 directly. This class of noncontacting electrostatic interactions could have general utility in the design and tuning of binding interactions.     

Elevated membrane-type matrix metalloproteinases in gliomas revealed by profiling proteases and inhibitors in human cancer cells

Matrix metalloproteinases (MMPs) and tissue inhibitors of metalloproteinases (TIMPs) regulate proteolysis of the extracellular matrix and other extracellular proteins, including growth factors and their receptors. The aberrant expression of these genes is common in most cancers. We profiled the RNA levels of every human MMP and TIMP in a variety of cell types (fibroblast, endothelial, hematopoietic, carcinoma, melanoma, and glioma) using quantitative PCR, with the aim of identifying novel expression patterns. Almost all members of the membrane-type (MT-) MMP and TIMP families were elevated in glioma lines compared to carcinomas. In clinical glioma specimens, there were positive correlations between glioma grade and RNA levels of MT-1, MT-2, and MT-6 MMP, TIMP-1 and TIMP-2, and for several growth factors and receptors. These findings suggest that advanced malignant gliomas have elevated levels of membrane-associated MMPs and TIMPs, which may potentially regulate vascularization and invasion. Concurrent elevation of signaling molecules suggests potential bidirectional relationships that enhance tumor aggressiveness.     

Matrix metalloproteinase 9 (MMP9) expression in preeclamptic decidua and MMP9 induction by tumor necrosis factor alpha and interleukin 1 beta in human first trimester decidual cells

Extravillous trophoblasts (EVTs) invade human decidua via sequential integrin-mediated binding and proteolysis of basement membrane proteins in the extracellular matrix (ECM). In preeclampsia, shallow EVT invasion impairs spiral artery and arteriole remodeling to reduce uteroplacental blood flow. Excess decidual cell-expressed matrix metalloproteinases (MMPs) 2 and 9, in response to preeclampsia-related interleukin 1 beta (IL1B) and tumor necrosis factor alpha (TNF), may inappropriately degrade these basement membrane proteins and impede EVT invasion. This study found significantly higher immunohistochemical MMP9 levels in decidual cells and adjacent interstitial trophoblasts in placental sections of preeclamptic versus gestational age-matched control women. In contrast, immunostaining for MMP2 and tissue inhibitor of matrix metalloproteinases 1 and 2 (TIMP1 and TIMP2) were similar in preeclamptic and control groups. First-trimester decidual cells were incubated with estradiol (E(2)) or E(2) + medroxyprogesterone acetate (MPA), with or without TNF or IL1B. As measured by ELISA, both cytokines elicited concentration-dependent increases in secreted MMP9 levels that were unaffected by MPA. In contrast, secreted levels of MMP2, TIMP1, and TIMP2 were unchanged in all treatment groups. Substrate gel zymography and Western blotting confirmed that each cytokine increased secreted levels of MMP9 but not MMP2. Similarly, quantitative RT-PCR found that TNF and IL1B enhanced MMP9, but not MMP2, mRNA levels. At the implantation site, inflammatory cytokine-enhanced MMP9 may promote preeclampsia by disrupting the decidual ECM to interfere with normal stepwise EVT invasion.     

Determination of binding affinity upon mutation for type I dockerin–cohesin complexes from Clostridium thermocellum and Clostridium cellulolyticum using deep sequencing

The comprehensive sequence determinants of binding affinity for type I cohesin toward dockerin from Clostridium thermocellum and Clostridium cellulolyticum was evaluated using deep mutational scanning coupled to yeast surface display. We measured the relative binding affinity to dockerin for 2970 and 2778 single point mutants of C. thermocellum and C. cellulolyticum, respectively, representing over 96% of all possible single point mutants. The interface ΔΔG for each variant was reconstructed from sequencing counts and compared with the three independent experimental methods. This reconstruction results in a narrow dynamic range of ?0.8–0.5 kcal/mol. The computational software packages FoldX and Rosetta were used to predict mutations that disrupt binding by more than 0.4 kcal/mol. The area under the curve of receiver operator curves was 0.82 for FoldX and 0.77 for Rosetta, showing reasonable agreements between predictions and experimental results. Destabilizing mutations to core and rim positions were predicted with higher accuracy than support positions. This benchmark dataset may be useful for developing new computational prediction tools for the prediction of the mutational effect on binding affinities for protein–protein interactions. Experimental considerations to improve precision and range of the reconstruction method are discussed. Proteins 2016; 84:1914–1928. © 2016 Wiley Periodicals, Inc.     

Transmembrane domain helix packing stabilizes integrin alphaIIbbeta3 in the low affinity state

Regulated changes in the affinity of integrin adhesion receptors ("activation") play an important role in numerous biological functions including hemostasis, the immune response, and cell migration. Physiological integrin activation is the result of conformational changes in the extracellular domain initiated by the binding of cytoplasmic proteins to integrin cytoplasmic domains. The conformational changes in the extracellular domain are likely caused by disruption of intersubunit interactions between the alpha and beta transmembrane (TM) and cytoplasmic domains. Here, we reasoned that mutation of residues contributing to alpha/beta interactions that stabilize the low affinity state should lead to integrin activation. Thus, we subjected the entire intracellular domain of the beta3 integrin subunit to unbiased random mutagenesis and selected it for activated mutants. 25 unique activating mutations were identified in the TM and membrane-proximal cytoplasmic domain. In contrast, no activating mutations were identified in the more distal cytoplasmic tail, suggesting that this region is dispensable for the maintenance of the inactive state. Among the 13 novel TM domain mutations that lead to integrin activation were several informative point mutations that, in combination with computational modeling, suggested the existence of a specific TM helix-helix packing interface that maintains the low affinity state. The interactions predicted by the model were used to identify additional activating mutations in both the alpha and beta TM domains. Therefore, we propose that helical packing of the alpha and beta TM domains forms a clasp that regulates integrin activation.     

Engineering of tissue inhibitor of metalloproteinases TIMP-1 for fine discrimination between closely related stromelysins MMP-3 and MMP-10

Matrix metalloproteinases (MMPs) have long been known as key drivers in the development and progression of diseases, including cancer and neurodegenerative, cardiovascular, and many other inflammatory and degenerative diseases, making them attractive potential drug targets. Engineering selective inhibitors based upon tissue inhibitors of metalloproteinases (TIMPs), endogenous human proteins that tightly yet nonspecifically bind to the family of MMPs, represents a promising new avenue for therapeutic development. Here, we used a counter-selective screening strategy for directed evolution of yeast-displayed human TIMP-1 to obtain TIMP-1 variants highly selective for the inhibition of MMP-3 in preference over MMP-10. As MMP-3 and MMP-10 are the most similar MMPs in sequence, structure, and function, our results thus clearly demonstrate the capability for engineering full-length TIMP proteins to be highly selective MMP inhibitors. We show using protein crystal structures and models of MMP-3-selective TIMP-1 variants bound to MMP-3 and counter-target MMP-10 how structural alterations within the N-terminal and C-terminal TIMP-1 domains create new favorable and selective interactions with MMP-3 and disrupt unique interactions with MMP-10. While our MMP-3-selective inhibitors may be of interest for future investigation in diseases where this enzyme drives pathology, our platform and screening strategy can be employed for developing selective inhibitors of additional MMPs implicated as therapeutic targets in disease.     

Dissecting cooperative and additive binding energetics in the affinity maturation pathway of a protein-protein interface

When two proteins associate they form a molecular interface that is a structural and energetic mosaic. Within such interfaces, individual amino acid residues contribute distinct binding energies to the complex. In combination, these energies are not necessarily additive, and significant positive or negative cooperative effects often exist. The basis of reliable algorithms to predict the specificities and energies of protein-protein interactions depends critically on a quantitative understanding of this cooperativity. We have used a model protein-protein system defined by an affinity maturation pathway, comprising variants of a T cell receptor Vbeta domain that exhibit an overall affinity range of approximately 1500-fold for binding to the superantigen staphylococcal enterotoxin C3, in order to dissect the cooperative and additive energetic contributions of residues within an interface. This molecular interaction has been well characterized previously both structurally, by x-ray crystallographic analysis, and energetically, by scanning alanine mutagenesis. Through analysis of group and individual maturation and reversion mutations using surface plasmon resonance spectroscopy, we have identified energetically important interfacial residues, determined their cooperative and additive energetic properties, and elucidated the kinetic and thermodynamic bases for molecular evolution in this system. The summation of the binding free energy changes associated with the individual mutations that define this affinity maturation pathway is greater than that of the fully matured variant, even though the affinity gap between the end point variants is relatively large. Two mutations in particular, both located in the complementarity determining region 2 loop of the Vbeta domain, exhibit negative cooperativity.