Evaluation of direct and cooperative contributions towards the strength of buried hydrogen bonds and salt bridges

Molecular Insight into Drug Resistance Mechanism Conferred by Aberrant PIK3CD Splice Variant in African American Prostate Cancer

Targeting PI3Kδ has emerged as a promising therapy for hematologic and non-hematologic malignancies. Previously, we identified an oncogenic splice variant, PIK3CD-S, conferring Idelalisib resistance in African American (AA) prostate cancer (PCa). In the current study, we employed a comprehensive analysis combining molecular biology, biochemistry, histology, in silico simulation, and in vitro functional assays to investigate the PIK3CD-S expression profiles in PCa samples and to elucidate the drug resistance mechanism mediated by PI3Kδ-S (encoded by PIK3CD-S). The immunohistochemistry, RT-PCR, and Western blot assays first confirmed that PI3Kδ-S is highly expressed in AA PCa. Compared with PCa expressing the full-length PI3Kδ-L, PCa expressing PI3Kδ-S exhibits enhanced drug resistance properties, including a higher cell viability, more antiapoptotic and invasive capacities, and constitutively activated PI3K/AKT signaling, in the presence of PI3Kδ/PI3K inhibitors (Idelalisib, Seletalisib, Wortmannin, and Dactolisib). Molecular docking, ATP-competitive assays, and PI3 kinase assays have further indicated a drastically reduced affinity of PI3Kδ inhibitors with PI3Kδ-S vs. PI3Kδ-L, attributed to the lack of core binding residues in the PI3Kδ-S catalytic domain. Additionally, SRSF2 has been identified as a critical splicing factor mediating exon 20 skipping in PIK3CD pre-mRNA. The inhibition of the SRSF2 activity by SRPIN340 successfully sensitizes AA PCa cells to PI3Kδ inhibitors, suggesting a novel therapeutic option for Idelalisib-resistant tumors.

Understanding the Binding Transition State After the Conformational Selection Step: The Second Half of the Molecular Recognition Process Between NS1 of the 1918 Influenza Virus and Host p85β

Biomolecular recognition often involves conformational changes as a prerequisite for binding (i.e., conformational selection) or concurrently with binding (i.e., induced-fit). Recent advances in structural and kinetic approaches have enabled the detailed characterization of protein motions at atomic resolution. However, to fully understand the role of the conformational dynamics in molecular recognition, studies on the binding transition state are needed. Here, we investigate the binding transition state between nonstructural protein 1 (NS1) of the pandemic 1918 influenza A virus and the human p85β subunit of PI3K. 1918 NS1 binds to p85β via conformational selection. We present the free-energy mapping of the transition and bound states of the 1918 NS1:p85β interaction using linear free energy relationship and ϕ-value analyses. We find that the binding transition state of 1918 NS1 and p85β is structurally similar to the bound state with well-defined binding orientation and hydrophobic interactions. Our finding provides a detailed view of how protein motion contributes to the development of intermolecular interactions along the binding reaction coordinate.

Composition-dependent energetic contribution of complex salt bridges to collagen stability

Complex salt bridges, on which three or more charged residues interplay simultaneously, cannot be considered as addition of individual salt bridges. This is still an intriguing problem in protein folding and stability. Here, we used an obligated ABC-type collagen heterotrimer as a platform to study the relationship between energetic contributions and conformational details of three-body complex salt bridges anchored by positively charged residues, K and R. Eight complex salt bridges were constructed by engineering point mutations in the heterotrimer. The circular dichroism measurements showed that the K-anchored complex salt bridges were stronger than the R-anchored ones. The molecular dynamics simulation revealed that both types of salt bridges had distinct dynamic features. The energetic contribution of K-anchored salt bridges was mainly determined by strong single bridges. In the R-anchored complex salt bridges, both side-chain electrostatic interactions and side-chain-backbone hydrogen bonding were involved. An empirical equation was proposed to predict the energetic contributions with high accuracy (R² = 0.93). This work could help us take insights into the mechanisms of composition-dependent behaviors of the complex salt bridges on protein surface.

An ultra-high affinity protein-protein interface displaying sequence-robustness

Protein-protein interactions are crucial in biology and play roles in for example, the immune system, signaling pathways, and enzyme regulation. Ultra-high affinity interactions (K_d <0.1 nM) occur in these systems, however, structures and energetics behind stability of ultra-high affinity protein-protein complexes are not well understood. Regulation of the starch debranching barley limit dextrinase (LD) and its endogenous cereal type inhibitor (LDI) exemplifies an ultra-high affinity complex (K_d of 42 pM). In this study the LD-LDI complex is investigated to unveil how robust the ultra-high affinity is to LDI sequence variation at the protein-protein interface and whether alternative sequences can retain the ultra-high binding affinity. The interface of LD-LDI was engineered using computational protein redesign aiming at identifying LDI variants predicted to retain ultra-high binding affinity. These variants present a very diverse set of mutations going beyond conservative and alanine substitutions typically used to probe interfaces. Surface plasmon resonance analysis of the LDI variants revealed that high affinity of LD-LDI requires interactions of several residues at the rim of the protein interface, unlike the classical hotspot arrangement where key residues are found at the center of the interface. Notably, substitution of interface residues in LDI, including amino acids with functional groups different from the wild-type, could occur without loss of affinity. This demonstrates that ultra-high binding affinity can be conferred without hotspot residues, thus making complexes more robust to mutational drift in evolution. The present mutational analysis also demonstrates how energetic coupling can emerge between residues at large distances at the interface.

Assessment of software methods for estimating protein-protein relative binding affinities

A growing number of computational tools have been developed to accurately and rapidly predict the impact of amino acid mutations on protein-protein relative binding affinities. Such tools have many applications, for example, designing new drugs and studying evolutionary mechanisms. In the search for accuracy, many of these methods employ expensive yet rigorous molecular dynamics simulations. By contrast, non-rigorous methods use less exhaustive statistical mechanics, allowing for more efficient calculations. However, it is unclear if such methods retain enough accuracy to replace rigorous methods in binding affinity calculations. This trade-off between accuracy and computational expense makes it difficult to determine the best method for a particular system or study. Here, eight non-rigorous computational methods were assessed using eight antibody-antigen and eight non-antibody-antigen complexes for their ability to accurately predict relative binding affinities (ΔΔG) for 654 single mutations. In addition to assessing accuracy, we analyzed the CPU cost and performance for each method using a variety of physico-chemical structural features. This allowed us to posit scenarios in which each method may be best utilized. Most methods performed worse when applied to antibody-antigen complexes compared to non-antibody-antigen complexes. Rosetta-based JayZ and EasyE methods classified mutations as destabilizing (ΔΔG < -0.5 kcal/mol) with high (83-98%) accuracy and a relatively low computational cost for non-antibody-antigen complexes. Some of the most accurate results for antibody-antigen systems came from combining molecular dynamics with FoldX with a correlation coefficient (r) of 0.46, but this was also the most computationally expensive method. Overall, our results suggest these methods can be used to quickly and accurately predict stabilizing versus destabilizing mutations but are less accurate at predicting actual binding affinities. This study highlights the need for continued development of reliable, accessible, and reproducible methods for predicting binding affinities in antibody-antigen proteins and provides a recipe for using current methods.

Structure based peptide design, molecular dynamics and MM-PBSA studies for targeting C terminal dimerization of NFAT5 DNA binding domain

NFAT5 as a transcription factor with an established role in osmotic stress response, has also been revealed to be active under numerous settings, including pathological conditions such as diabetic microvascular complications, chronic arthritis and cancer. Despite these links, current strategies for downregulating NFAT5 activity only relies on indirect modulators, not directly targeting NFAT5, itself. With this study, through using a computational approach, an original peptide was explored to directly target C terminal dimerization of NFAT5 RHR, located in its DNA binding domain. At first, homodimeric NFAT5 RHR bound to its consensus DNA was used for prediction of a preliminary peptide sequence. Possible amino acid replacements for this preliminary peptide were predicted for optimization, which was followed by addition of a cell penetrating peptide sequence. These attempts yielded a small peptide library, which was further investigated for peptide affinities towards C terminal of NFAT5 RHR through molecular docking, 50 ns and 250 ns molecular dynamics simulations, followed by estimation of MM-PBSA based relative binding free energies. Results indicated that after receiving mutations on the preliminary peptide sequence for optimization, a unique peptide could target C terminal dimerization region of NFAT5 RHR through using its cell penetrating peptide sequence. In conclusion, this is the first study presenting computational evidence on identification of a novel peptide capable of directly targeting NFAT5 dimerization. Besides, future implications of these observations were also discussed in terms of methodology and possible applications.

Comparative studies on ion-pair energetic, distribution among three domains of life: Archaea, eubacteria, and eukarya

Salt-bridges play a unique role in the structural and functional stability of proteins, especially under harsh environments. How these salt-bridges contribute to the overall thermodynamic stability of protein structure and function across different domains of life is elusive still date. To address the issue, statistical analyses on the energies of salt-bridges, involved in proteins' structure and function, are performed across three domains of life, that is, archaea, eubacteria, and eukarya. Results show that although the majority of salt-bridges are stable and conserved, yet the stability of archaeal proteins (∆∆G_net = -5.06 ± 3.8) is much more than that of eubacteria (∆∆G_net = -3.7 ± 2.9) and eukarya (∆∆G_net = -3.54 ± 3.1). Unlike earlier study with archaea, in eukarya and eubacteria, not all buried salt-bridge in our dataset are stable. Buried salt-bridges play surprising role in protein stability, whose variations are clearly observed among these domains. Greater desolvation penalty of buried salt-bridges is compensated by stable network of salt-bridges apart from equal contribution of bridge and background energy terms. On the basis proteins' secondary structure, topology, and evolution, our observation shows that salt-bridges when present closer to each other in sequence tend to form a greater number. Overall, our comparative study provides insight into the role of specific electrostatic interactions in proteins from different domains of life, which we hope, would be useful for protein engineering and bioinformatics study.

Evolutionary Stability of Salt Bridges Hints Its Contribution to Stability of Proteins

The contribution of newly designed salt bridges to protein stabilization remains controversial even today. In order to solve this problem, we investigated salt bridges from two aspects: spatial distribution and evolutionary characteristics of salt bridges. Firstly, we analyzed spatial distribution of salt bridges in proteins, elucidating the basic requirements of forming salt bridges. Then, from an evolutionary point of view, the evolutionary characteristics of salt bridges as well as their neighboring residues were investigated in our study. The results demonstrate that charged residues appear more frequently than other neutral residues at certain positions of sequence even under evolutionary pressure, which are able to form electrostatic interactions that could increase the evolutionary stability of corresponding amino acid regions, enhancing their importance to stability of proteins. As a corollary, we conjectured that the newly designed salt bridges with more contribution to proteins, not only, are qualified spatial distribution of salt bridges, but also, are needed to further increase the evolutionary stability of corresponding amino acid regions. Based on analysis, the 8 mutations were accordingly constructed in the 1,4-α-glucan branching enzyme (EC 2.4.1.18, GBE) from Geobacillus thermoglucosidans STB02, of which 7 mutations improved thermostability of GBE. The enhanced thermostability of 7 mutations might be a result of additional salt bridges on residue positions that at least one of amino acids positions is conservative, improving their contribution of stabilization to proteins.

Principles of Protein Stability and Their Application in Computational Design

Proteins are increasingly used in basic and applied biomedical research. Many proteins, however, are only marginally stable and can be expressed in limited amounts, thus hampering research and applications. Research has revealed the thermodynamic, cellular, and evolutionary principles and mechanisms that underlie marginal stability. With this growing understanding, computational stability design methods have advanced over the past two decades starting from methods that selectively addressed only some aspects of marginal stability. Current methods are more general and, by combining phylogenetic analysis with atomistic design, have shown drastic improvements in solubility, thermal stability, and aggregation resistance while maintaining the protein's primary molecular activity. Stability design is opening the way to rational engineering of improved enzymes, therapeutics, and vaccines and to the application of protein design methodology to large proteins and molecular activities that have proven challenging in the past.

Quantitative tests of a reconstitution model for RNA folding thermodynamics and kinetics

Decades of study of the architecture and function of structured RNAs have led to the perspective that RNA tertiary structure is modular, made of locally stable domains that retain their structure across RNAs. We formalize a hypothesis inspired by this modularity-that RNA folding thermodynamics and kinetics can be quantitatively predicted from separable energetic contributions of the individual components of a complex RNA. This reconstitution hypothesis considers RNA tertiary folding in terms of ΔG_align, the probability of aligning tertiary contact partners, and ΔG_tert, the favorable energetic contribution from the formation of tertiary contacts in an aligned state. This hypothesis predicts that changes in the alignment of tertiary contacts from different connecting helices and junctions (ΔG_HJH) or from changes in the electrostatic environment (ΔG_+/-) will not affect the energetic perturbation from a mutation in a tertiary contact (ΔΔG_tert). Consistent with these predictions, single-molecule FRET measurements of folding of model RNAs revealed constant ΔΔG_tert values for mutations in a tertiary contact embedded in different structural contexts and under different electrostatic conditions. The kinetic effects of these mutations provide further support for modular behavior of RNA elements and suggest that tertiary mutations may be used to identify rate-limiting steps and dissect folding and assembly pathways for complex RNAs. Overall, our model and results are foundational for a predictive understanding of RNA folding that will allow manipulation of RNA folding thermodynamics and kinetics. Conversely, the approaches herein can identify cases where an independent, additive model cannot be applied and so require additional investigation.

Backbone Hydrogen Bond Strengths Can Vary Widely in Transmembrane Helices

Although backbone hydrogen bonds in transmembrane (TM) helices have the potential to be very strong due to the low dielectric and low water environment of the membrane, their strength has never been assessed experimentally. Moreover, variations in hydrogen bond strength might be necessary to facilitate the TM helix breaking and bending that is often needed to satisfy functional imperatives. Here we employed equilibrium hydrogen/deuterium fractionation factors to measure backbone hydrogen bond strengths in the TM helix of the amyloid precursor protein (APP). We find an enormous range of hydrogen bond free energies, with some weaker than water–water hydrogen bonds and some over 6 kcal/mol stronger than water–water hydrogen bonds. We find that weak hydrogen bonds are at or near preferred γ-secretase cleavage sites, suggesting that the sequence of APP and possibly other cleaved TM helices may be designed, in part, to make their backbones accessible for cleavage. The finding that hydrogen bond strengths in a TM helix can vary widely has implications for membrane protein function, dynamics, evolution, and design.

The Dependence of Carbohydrate-Aromatic Interaction Strengths on the Structure of the Carbohydrate

Interactions between proteins and carbohydrates are ubiquitous in biology. Therefore, understanding the factors that determine their affinity and selectivity are correspondingly important. Herein, we have determined the relative strengths of intramolecular interactions between a series of monosaccharides and an aromatic ring close to the glycosylation site in an N-glycoprotein host. We employed the enhanced aromatic sequon, a structural motif found in the reverse turns of some N-glycoproteins, to facilitate face-to-face monosaccharide-aromatic interactions. A protein host was used because the dependence of the folding energetics on the identity of the monosaccharide can be accurately measured to assess the strength of the carbohydrate-aromatic interaction. Our data demonstrate that the carbohydrate-aromatic interaction strengths are moderately affected by changes in the stereochemistry and identity of the substituents on the pyranose rings of the sugars. Galactose seems to make the weakest and allose the strongest sugar-aromatic interactions, with glucose, N-acetylglucosamine (GlcNAc) and mannose in between. The NMR solution structures of several of the monosaccharide-containing N-glycoproteins were solved to further understand the origins of the similarities and differences between the monosaccharide-aromatic interaction energies. Peracetylation of the monosaccharides substantially increases the strength of the sugar-aromatic interaction in the context of our N-glycoprotein host. Finally, we discuss our results in light of recent literature regarding the contribution of electrostatics to CH-π interactions and speculate on what our observations imply about the absolute conservation of GlcNAc as the monosaccharide through which N-linked glycans are attached to glycoproteins in eukaryotes.

Modeling and fitting protein-protein complexes to predict change of binding energy

It is possible to accurately and economically predict change in protein-protein interaction energy upon mutation (ΔΔG), when a high-resolution structure of the complex is available. This is of growing usefulness for design of high-affinity or otherwise modified binding proteins for therapeutic, diagnostic, industrial, and basic science applications. Recently the field has begun to pursue ΔΔG prediction for homology modeled complexes, but so far this has worked mostly for cases of high sequence identity. If the interacting proteins have been crystallized in free (uncomplexed) form, in a majority of cases it is possible to find a structurally similar complex which can be used as the basis for template-based modeling. We describe how to use MMB to create such models, and then use them to predict ΔΔG, using a dataset consisting of free target structures, co-crystallized template complexes with sequence identify with respect to the targets as low as 44%, and experimental ΔΔG measurements. We obtain similar results by fitting to a low-resolution Cryo-EM density map. Results suggest that other structural constraints may lead to a similar outcome, making the method even more broadly applicable.

Forces stabilizing proteins

The goal of this article is to summarize what has been learned about the major forces stabilizing proteins since the late 1980s when site-directed mutagenesis became possible. The following conclusions are derived from experimental studies of hydrophobic and hydrogen bonding variants. (1) Based on studies of 138 hydrophobic interaction variants in 11 proteins, burying a -CH2- group on folding contributes 1.1±0.5 kcal/mol to protein stability. (2) The burial of non-polar side chains contributes to protein stability in two ways: first, a term that depends on the removal of the side chains from water and, more importantly, the enhanced London dispersion forces that result from the tight packing in the protein interior. (3) Based on studies of 151 hydrogen bonding variants in 15 proteins, forming a hydrogen bond on folding contributes 1.1±0.8 kcal/mol to protein stability. (4) The contribution of hydrogen bonds to protein stability is strongly context dependent. (5) Hydrogen bonds by side chains and peptide groups make similar contributions to protein stability. (6) Polar group burial can make a favorable contribution to protein stability even if the polar group is not hydrogen bonded. (7) Hydrophobic interactions and hydrogen bonds both make large contributions to protein stability.

Salt-bridge energetics in halophilic proteins

Halophilic proteins have greater abundance of acidic over basic and very low bulky hydrophobic residues. Classical electrostatic stabilization was suggested as the key determinant for halophilic adaptation of protein. However, contribution of specific electrostatic interactions (i.e. salt-bridges) to overall stability of halophilic proteins is yet to be understood. To understand this, we use Adaptive-Poison-Boltzmann-Solver Methods along with our home-built automation to workout net as well as associated component energy terms such as desolvation energy, bridge energy and background energy for 275 salt-bridges from 20 extremely halophilic proteins. We then perform extensive statistical analysis on general and energetic attributes on these salt-bridges. On average, 8 salt-bridges per 150 residues protein were observed which is almost twice than earlier report. Overall contributions of salt-bridges are −3.0 kcal mol⁻¹. Majority (78%) of salt-bridges in our dataset are stable and conserved in nature. Although, average contributions of component energy terms are equal, their individual details vary greatly from one another indicating their sensitivity to local micro-environment. Notably, 35% of salt-bridges in our database are buried and stable. Greater desolvation penalty of these buried salt-bridges are counteracted by stable network salt-bridges apart from favorable equal contributions of bridge and background terms. Recruitment of extensive network salt-bridges (46%) with a net contribution of −5.0 kcal mol⁻¹ per salt-bridge, seems to be a halophilic design wherein favorable average contribution of background term (−10 kcal mol⁻¹) exceeds than that of bridge term (−7 kcal mol⁻¹). Interiors of proteins from halophiles are seen to possess relatively higher abundance of charge and polar side chains than that of mesophiles which seems to be satisfied by cooperative network salt-bridges. Overall, our theoretical analyses provide insight into halophilic signature in its specific electrostatic interactions which we hope would help in protein engineering and bioinformatics studies.

An energetic scale for equilibrium H/D fractionation factors illuminates hydrogen bond free energies in proteins

Equilibrium H/D fractionation factors have been extensively employed to qualitatively assess hydrogen bond strengths in protein structure, enzyme active sites, and DNA. It remains unclear how fractionation factors correlate with hydrogen bond free energies, however. Here we develop an empirical relationship between fractionation factors and free energy, allowing for the simple and quantitative measurement of hydrogen bond free energies. Applying our empirical relationship to prior fractionation factor studies in proteins, we find: [1] Within the folded state, backbone hydrogen bonds are only marginally stronger on average in α-helices compared to β-sheets by ∼0.2 kcal/mol. [2] Charge-stabilized hydrogen bonds are stronger than neutral hydrogen bonds by ∼2 kcal/mol on average, and can be as strong as -7 kcal/mol. [3] Changes in a few hydrogen bonds during an enzyme catalytic cycle can stabilize an intermediate state by -4.2 kcal/mol. [4] Backbone hydrogen bonds can make a large overall contribution to the energetics of conformational changes, possibly playing an important role in directing conformational changes. [5] Backbone hydrogen bonding becomes more uniform overall upon ligand binding, which may facilitate participation of the entire protein structure in events at the active site. Our energetic scale provides a simple method for further exploration of hydrogen bond free energies.

FGFR3 transmembrane domain interactions persist in the presence of its extracellular domain

Isolated receptor tyrosine kinase transmembrane (TM) domains have been shown to form sequence-specific dimers in membranes. Yet, it is not clear whether studies of isolated TM domains yield knowledge that is relevant to full-length receptors or whether the large glycosylated extracellular domains alter the interactions between the TM helices. Here, we address this question by quantifying the effect of the pathogenic A391E TM domain mutation on the stability of the fibroblast growth factor receptor 3 dimer in the presence of the extracellular domain and comparing these results to the case of the isolated TM fibroblast growth factor receptor 3 domains. We perform the measurements in plasma membrane-derived vesicles using a Förster-resonance-energy-transfer-based method. The effect of the mutation on dimer stability in both cases is the same (∼-1.5 kcal/mol), suggesting that the interactions observed in simple TM-peptide model systems are relevant in a biological context.

Effect of salt on the formation of salt-bridges in β-hairpin peptides

The formation of salt-bridges in β-hairpin peptides is measured in increasing salt concentrations, indicating a decrease in the salt-bridged population due to charge–charge screening, as well as non-cooperative salt-bridge triads.

NXO beta structure mimicry: an ultrashort turn/hairpin mimic that folds in water

An NXO building block derived tetrapeptide mimic emulates a natural proline-glycine β-turn/hairpin in polar media, including water at room temperature.

Characterizing changes in the rate of protein-protein dissociation upon interface mutation using hotspot energy and organization

Predicting the effects of mutations on the kinetic rate constants of protein-protein interactions is central to both the modeling of complex diseases and the design of effective peptide drug inhibitors. However, while most studies have concentrated on the determination of association rate constants, dissociation rates have received less attention. In this work we take a novel approach by relating the changes in dissociation rates upon mutation to the energetics and architecture of hotspots and hotregions, by performing alanine scans pre- and post-mutation. From these scans, we design a set of descriptors that capture the change in hotspot energy and distribution. The method is benchmarked on 713 kinetically characterized mutations from the SKEMPI database. Our investigations show that, with the use of hotspot descriptors, energies from single-point alanine mutations may be used for the estimation of off-rate mutations to any residue type and also multi-point mutations. A number of machine learning models are built from a combination of molecular and hotspot descriptors, with the best models achieving a Pearson's Correlation Coefficient of 0.79 with experimental off-rates and a Matthew's Correlation Coefficient of 0.6 in the detection of rare stabilizing mutations. Using specialized feature selection models we identify descriptors that are highly specific and, conversely, broadly important to predicting the effects of different classes of mutations, interface regions and complexes. Our results also indicate that the distribution of the critical stability regions across protein-protein interfaces is a function of complex size more strongly than interface area. In addition, mutations at the rim are critical for the stability of small complexes, but consistently harder to characterize. The relationship between hotregion size and the dissociation rate is also investigated and, using hotspot descriptors which model cooperative effects within hotregions, we show how the contribution of hotregions of different sizes, changes under different cooperative effects.

Selective amine recognition driven by host-guest proton transfer and salt bridge formation

The stepwise synthesis of ionizable p-tert-butylcalix[5]arenes 1a·H and 1b·H, featuring a fixed cone cavity endowed with a carboxyl moiety at the narrow rim, is described. Single-crystal X-ray analyses have shown that in the solid state 1a·H and 1b·H adopt a cone-out conformation with the carboxylic OH group pointing in, toward the bottom of the aromatic cavity, as a result of a three- or two-center hydrogen-bonding pattern between the carboxyl group and the phenolic oxygen atom(s). The affinity of amines for calix[5]arene derivatives 1a·H and 1b·H was probed by (1)H NMR spectroscopy and single-crystal X-ray diffraction studies. These carboxylcalix[5]arenes are shown to selectively recognize linear primary amines--over branched, secondary, and tertiary amines--by a two-step process involving a proton transfer from the carboxyl to the amino group to provide the corresponding alkylammonium ion, followed by binding of the latter inside the cavity of the ionized calixarene. Proton transfer occurs only with linear primary amines, that is, when the best size and shape fit between host and substrate is achieved, while the other amines remain in their noncompeting unprotonated form. The role of the solvent in the ionization/complexation process is discussed. Structural studies on the n-BuNH(2) complexes with 1a·H and 1b·H provide evidence that binding of the in situ formed n-BuNH(3)(+) substrate to the cavity of the ionized macrocycle is ultimately secured, in the case of 1a·H, by the formation of an unprecedented salt-bridge interaction.

Functionally important aromatic-aromatic and sulfur-π interactions in the D2 dopamine receptor

The recently published crystal structure of the D3 dopamine receptor shows a tightly packed region of aromatic residues on helices 5 and 6 in the space bridging the binding site and what is thought to be the origin of intracellular helical motion. This highly conserved region also makes contacts with residues on helix 3, and here we use double mutant cycle analysis and unnatural amino acid mutagenesis to probe the functional role of several residues in this region of the closely related D2 dopamine receptor. Of the eight mutant pairs examined, all show significant functional coupling (Ω > 2), with the largest coupling coefficients observed between residues on different helices, C3.36/W6.48, T3.37/S5.46, and F5.47/F6.52. Additionally, three aromatic residues examined, F5.47, Y5.48, and F5.51, show consistent trends upon progressive fluorination of the aromatic side chain. These trends are indicative of a functionally important electrostatic interaction with the face of the aromatic residue examined, which is likely attributed to aromatic-aromatic interactions between residues in this microdomain. We also propose that the previously determined fluorination trend at W6.48 is likely due to a sulfur-π interaction with the side chain of C3.36. We conclude that these residues form a tightly packed structural microdomain that connects helices 3, 5, and 6, thus forming a barrier that prevents dopamine from binding further toward the intracellular surface. Upon activation, these residues likely do not change their relative conformation, but rather act to translate agonist binding at the extracellular surface into the large intracellular movements that characterize receptor activation.

Versatility and invariance in the evolution of homologous heteromeric interfaces

Evolutionary pressures act on protein complex interfaces so that they preserve their complementarity. Nonetheless, the elementary interactions which compose the interface are highly versatile throughout evolution. Understanding and characterizing interface plasticity across evolution is a fundamental issue which could provide new insights into protein-protein interaction prediction. Using a database of 1,024 couples of close and remote heteromeric structural interologs, we studied protein-protein interactions from a structural and evolutionary point of view. We systematically and quantitatively analyzed the conservation of different types of interface contacts. Our study highlights astonishing plasticity regarding polar contacts at complex interfaces. It also reveals that up to a quarter of the residues switch out of the interface when comparing two homologous complexes. Despite such versatility, we identify two important interface descriptors which correlate with an increased conservation in the evolution of interfaces: apolar patches and contacts surrounding anchor residues. These observations hold true even when restricting the dataset to transiently formed complexes. We show that a combination of six features related either to sequence or to geometric properties of interfaces can be used to rank positions likely to share similar contacts between two interologs. Altogether, our analysis provides important tracks for extracting meaningful information from multiple sequence alignments of conserved binding partners and for discriminating near-native interfaces using evolutionary information.

Unraveling how interfaces of protein complexes coevolved is of major importance to improve our ability to predict their structures and design novel binders. Proteins whose interaction was maintained throughout evolution generally have their homologs binding in a similar manner while their sequences can have significantly diverged. Constraints holding proteins together should be captured from the growing body of available multiple sequence alignments. However, it remains unclear which features of the interfaces provide most tolerance to mutations and it is unknown whether any invariant properties may help to extract meaningful signals from sequence alignments. To solve this issue, we tackled an unprecedented large scale analysis of more than 1000 non-redundant couples of structural interologs. Structural interologs are pairs of complexes of known structure whose chains are homologs. We quantitatively measured how the networks of contacts varied between two interfaces. Although highly versatile, we found that contact networks were more conserved for residues acting as anchors and for apolar contacts when they are clustered into surface patches. Altogether, our results provide major guidelines for exploiting the wealth of evolutionary information contained in the sequences of binding partners. On those bases we developed a method to predict which residues most likely conserve their contacts.

Protein-binding dynamics imaged in a living cell

Historically, rate constants were determined in vitro and it was unknown whether they were valid for in vivo biological processes. Here, we bridge this gap by measuring binding dynamics between a pair of proteins in living HeLa cells. Binding of a β-lactamase to its protein inhibitor was initiated by microinjection and monitored by Förster resonance energy transfer. Association rate constants for the wild-type and an electrostatically optimized mutant were only 25% and 50% lower than in vitro values, whereas no change in the rate constant was observed for a slower binding mutant. These changes are much smaller than might be anticipated considering the high macromolecular crowding within the cell. Single-cell analyses of association rate constants and fluorescence recovery after photobleaching reveals a naturally occurring variation in cell density, which is translated to an up to a twofold effect on binding rate constants. The data show that for this model protein interaction the intracellular environment had only a small effect on the association kinetics, justifying the extrapolation of in vitro data to processes in the cell.

DBAC: a simple prediction method for protein binding hot spots based on burial levels and deeply buried atomic contacts

BACKGROUND

A protein binding hot spot is a cluster of residues in the interface that are energetically important for the binding of the protein with its interaction partner. Identifying protein binding hot spots can give useful information to protein engineering and drug design, and can also deepen our understanding of protein-protein interaction. These residues are usually buried inside the interface with very low solvent accessible surface area (SASA). Thus SASA is widely used as an outstanding feature in hot spot prediction by many computational methods. However, SASA is not capable of distinguishing slightly buried residues, of which most are non hot spots, and deeply buried ones that are usually inside a hot spot.

RESULTS

We propose a new descriptor called "burial level" for characterizing residues, atoms and atomic contacts. Specifically, burial level captures the depth the residues are buried. We identify different kinds of deeply buried atomic contacts (DBAC) at different burial levels that are directly broken in alanine substitution. We use their numbers as input for SVM to classify between hot spot or non hot spot residues. We achieve F measure of 0.6237 under the leave-one-out cross-validation on a data set containing 258 mutations. This performance is better than other computational methods.

CONCLUSIONS

Our results show that hot spot residues tend to be deeply buried in the interface, not just having a low SASA value. This indicates that a high burial level is not only a necessary but also a more sufficient condition than a low SASA for a residue to be a hot spot residue. We find that those deeply buried atoms become increasingly more important when their burial levels rise up. This work also confirms the contribution of deeply buried interfacial atomic contacts to the energy of protein binding hot spot.

Specificity and cooperativity at β-lactamase position 104 in TEM-1/BLIP and SHV-1/BLIP interactions

Establishing a quantitative understanding of the determinants of affinity in protein-protein interactions remains challenging. For example, TEM-1/β-lactamase inhibitor protein (BLIP) and SHV-1/BLIP are homologous β-lactamase/β-lactamase inhibitor protein complexes with disparate K(d) values (3 nM and 2 μM, respectively), and a single substitution, D104E in SHV-1, results in a 1000-fold enhancement in binding affinity. In TEM-1, E104 participates in a salt bridge with BLIP K74, whereas the corresponding SHV-1 D104 does not in the wild type SHV-1/BLIP co-structure. Here, we present a 1.6 Å crystal structure of the SHV-1 D104E/BLIP complex that demonstrates that this point mutation restores this salt bridge. Additionally, mutation of a neighboring residue, BLIP E73M, results in salt bridge formation between SHV-1 D104 and BLIP K74 and a 400-fold increase in binding affinity. To understand how this salt bridge contributes to complex affinity, the cooperativity between the E/K or D/K salt bridge pair and a neighboring hot spot residue (BLIP F142) was investigated using double mutant cycle analyses in the background of the E73M mutation. We find that BLIP F142 cooperatively stabilizes both interactions, illustrating how a single mutation at a hot spot position can drive large perturbations in interface stability and specificity through a cooperative interaction network.

Contribution of inter-subunit interactions to the thermostability of Pyrococcus furiosus citrate synthase

Using citrate synthase from the hyperthermophile Pyrococcus furiosus (PfCS) as our test molecule, we show through guanidine hydrochloride-induced unfolding that the dimer separates into folded, but inactive, monomers before individual subunit unfolding takes place. Given that forces across the dimer interface are vital for thermostability, a robust computational method was derived that uses the University of Houston Brownian Dynamics (UHBD) program to calculate both the hydrophobic and electrostatic contribution to the dimerisation energy at 100°C. The results from computational and experimental determination of the lowered stability of interface mutants were correlated, being both of the same order of magnitude and placing the mutant proteins in the same order of stability. This computational method, optimised for hyperthermophilic molecules and tested in the laboratory, after further testing on other examples, could be of widespread use in the prediction of thermostabilising mutations in other oligomeric proteins for which dissociation is the first step in unfolding.

Dissecting protein-protein interactions using directed evolution

Protein-protein interactions are essential for life. They are responsible for most cellular functions and when they go awry often lead to disease. Proteins are inherently complex. They are flexible macromolecules whose constituent amino acid components act in combinatorial and networked ways when they engage one another in binding interactions. It is just this complexity that allows them to conduct such a broad array of biological functions. Despite decades of intense study of the molecular basis of protein-protein interactions, key gaps in our understanding remain, hindering our ability to accurately predict the specificities and affinities of their interactions. Until recently, most protein-protein investigations have been probed experimentally at the single-amino acid level, making them, by definition, incapable of capturing the combinatorial nature of, and networked communications between, the numerous residues within and outside of the protein-protein interface. This aspect of protein-protein interactions, however, is emerging as a major driving force for protein affinity and specificity. Understanding a combinatorial process necessarily requires a combinatorial experimental tool. Much like the organisms in which they reside, proteins naturally evolve over time, through a combinatorial process of mutagenesis and selection, to functionally associate. Elucidating the process by which proteins have evolved may be one of the keys to deciphering the molecular rules that govern their interactions with one another. Directed evolution is a technique performed in the laboratory that mimics natural evolution on a tractable time scale that has been utilized widely to engineer proteins with novel capabilities, including altered binding properties. In this review, we discuss directed evolution as an emerging tool for dissecting protein-protein interactions.

Membrane protein folding: how important are hydrogen bonds?

Water is an inhospitable environment for protein hydrogen bonds because it is polarizable and capable of forming competitive hydrogen bonds. In contrast, the apolar core of a biological membrane seems like an ideal environment for hydrogen bonds, and it has long been assumed that hydrogen bonding should be a powerful force driving membrane protein folding. Nevertheless, while backbone hydrogen bonds may be much stronger in membrane proteins, experimental measurements indicate that side chain hydrogen bond strengths are not strikingly different in membrane and water soluble proteins. How is this possible? I argue that model compounds in apolar solvents do not adequately describe the system because the protein itself is ignored. The protein chain provides a rich source of competitive hydrogen bonds and a polarizable environment that can weaken hydrogen bonds. Thus, just like water soluble proteins, evolution can drive the creation of potent hydrogen bonds in membrane proteins where necessary, but mitigating forces in their environment must still be overcome.

Functional mapping of the anti-idiotypic antibody anti-TS1 scFv using site-directed mutagenesis and kinetic analysis

Recombinant antibodies may be engineered to obtain improved functional properties. Functional mapping of the residues in the binding surfaces is of importance for predicting alterations needed to yield the desired properties. In this investigation, 17 single mutation mutant single-chain variable fragments (scFvs) of the anti-idiotypic antibody anti-TS1 were generated in order to functionally map amino acid residues important for the interaction with its idiotype TS1. Residues in anti-TS1 determined to be very important for the interaction were identified, Y32L, K50L, K33H, and Y52H, and they were distributed adjacent to a centrally located hydrophobic area, and contributed extensively to the interaction energy (≥2.5 kcal/mol) in the interaction. Quantitative ELISA assays, BIAcore technologies and three-dimensional surface analysis by modeling were employed to visualize the consequences of the mutations. The expression levels varied between 2 - 1,800 nM as determined by ELISA. All the 17 scFvs displayed higher dissociation rates (60 - 1,300 times) and all but two of them also faster association rates (1.3 - 56 times). The decrease in affinity was determined to be 1.6 - 12,200 times. Two of the mutants displayed almost identical affinity with the wild type anti-TS1, but with a change in both association and dissociation rates. The present investigation demonstrates that it is possible to generate a large panorama of anti-idiotypic antibodies, and single out a few that might be of potential use for future clearing and pre-targeting purposes of idiotypic-anti-idiotypic interactions.

The role of amphiphilicity and negative charge in glycoprotein 41 interactions in the hydrophobic pocket

The hydrophobic pocket within the coiled coil domain of HIV-1 gp41 is considered to be a hot-spot suitable for small molecule intervention of fusion, although so far it has yielded only microM inhibitors. Previous peptide studies have identified specific hydrophobic interactions and a Lys-Asp salt bridge as contributing to binding affinity in the pocket. Negative charge appears to be critical for activity of small molecules. We have examined the role of charge and amphiphilic character in the interaction by studying a series of short pocket binding peptides differing in charge, helical content, and in the presence or absence of the Lys-Asp salt bridge, and a series of fatty acid salts with varying charge and hydrocarbon length. Quantitative binding analysis revealed that long-range electrostatic forces and a greasy nonspecific hydrophobic interaction were sufficient for microM potency. The results suggest that an extended interaction site may be necessary for higher potency. We examined a region of the coiled coil immediately C-terminal to the pocket and found that specific salt bridge and hydrogen bond networks may reside in this region. Negatively charged groups extended toward or beyond the C-terminus of the pocket could therefore result in improved low molecular weight fusion inhibitors.

Localized thermodynamic coupling between hydrogen bonding and microenvironment polarity substantially stabilizes proteins

The energetic contributions of hydrogen bonding to protein folding are still unclear, despite more than 70 years of study. This is due partly to the difficulty of extracting thermodynamic information about specific interactions from protein mutagenesis data and partly to the context dependence of hydrogen bond strengths. Herein, we test the hypothesis that hydrogen bond strengths depend on the polarity of their microenvironment, with stronger hydrogen bonds forming in nonpolar surroundings. Double-mutant cycle analysis using a combination of amide-to-ester backbone mutagenesis and traditional side chain mutagenesis revealed that hydrogen bonds can be stronger by up to 1.2 kcal mol(-1) when they are sequestered in hydrophobic surroundings than when they are solvent exposed. Such large coupling energies between hydrogen bond strengths and local polarity suggest that the context dependence of hydrogen bond strengths must be accounted for in any comprehensive account of the forces responsible for protein folding.

Empirical estimation of the energetic contribution of individual interface residues in structures of protein-protein complexes

We report a simple algorithm to scan interfaces in protein-protein complexes for identifying binding 'hot spots'. The change in side-chain solvent accessible area (DeltaASA) of interface residues has been related to change in binding energy due to mutating interface residues to Ala (DeltaDeltaG (X --> ALA)) based on two criteria-hydrogen bonding across the interface and location in the interface core-both of which are major determinants in specific, high-affinity binding. These relationships are used to predict the energetic contribution of individual interface residues. The predictions are tested against 462 experimental X --> ALA mutations from 28 interfaces with an average unsigned error of 1.04 kcal/mol. More than 80% of interface hot spots (with experimental DeltaDeltaG > or = 2 kcal/mol) could be identified as being energetically important. From the experimental values, Asp, Lys, Tyr and Trp are found to contribute most of the binding energy, burying >45 A2 on average. The method described here would be useful to understand and interfere with protein interactions by assessing the energetic importance of individual interface residues.

Exploring the mechanism of beta-amyloid toxicity attenuation by multivalent sialic acid polymers through the use of mathematical models

beta-Amyloid peptide (A beta), the primary protein component in senile plaques associated with Alzheimer's disease (AD), has been implicated in neurotoxicity associated with AD. Previous studies have shown that the A beta-neuronal membrane interaction plays a role in the mechanism of A beta toxicity. More specifically, it is thought that A beta interacts with ganglioside rich and sialic acid rich regions of cell surfaces. In light of such evidence, we have used a number of different sialic acid compounds of different valency or number of sialic acid moieties per molecule to attenuate A beta toxicity in a cell culture model. In this work, we proposed various mathematical models of A beta interaction with both the cell membrane and with the multivalent sialic acid compounds, designed to act as membrane mimics. These models allow us to explore the mechanism of action of this class of sialic acid membrane mimics in attenuating the toxicity of A beta. The mathematical models, when compared with experimental data, facilitate the discrimination between different modes of action of these materials. Understanding the mechanism of action of A beta toxicity inhibitors should provide insight into the design of the next generation of molecules that could be used to prevent A beta toxicity associated with AD.

Binding to gating transduction in nicotinic receptors: Cys-loop energetically couples to pre-M1 and M2-M3 regions

The nicotinic acetylcholine receptor (AChR) transduces binding of nerve-released ACh into opening of an intrinsic ion channel, yet the intraprotein interactions behind transduction remain to be fully elucidated. Attention has focused on the region of the AChR in which the beta1-beta2 and Cys-loops from the extracellular domain project into a cavity framed by residues preceding the first transmembrane domain (pre-M1) and the linker spanning transmembrane domains M2 and M3. Previous studies identified a principal transduction pathway in which the pre-M1 domain is coupled to the M2-M3 linker through the beta1-beta2 loop. Here we identify a parallel pathway in which the pre-M1 domain is coupled to the M2-M3 linker through the Cys-loop. Mutagenesis, single-channel kinetic analyses and thermodynamic mutant cycle analyses reveal energetic coupling among alphaLeu 210 from the pre-M1 domain, alphaPhe 135 and alphaPhe 137 from the Cys-loop, and alphaLeu 273 from the M2-M3 linker. Residues at equivalent positions of non-alpha-subunits show negligible coupling, indicating these interresidue couplings are specific to residues in the alpha-subunit. Thus, the extracellular beta1-beta2 and Cys-loops bridge the pre-M1 domain and M2-M3 linker to transduce agonist binding into channel gating.

Hot-spot residues at the E9/Im9 interface help binding via different mechanisms

Protein-protein association involves many interface interactions, but they do not contribute equally. Ala scanning experiments reveal that only a few mutations significantly lower binding affinity. These key residues, which appear to drive protein-protein association, are called hot-spot residues. Molecular dynamics simulations of the Colicin E9/Im9 complex show Im9 Glu41 and Im9 Ser50, both hot-spots, bind via different mechanisms. The results suggest that Im9 Ser50 restricts Glu41 in a conformation auspicious for salt-bridge formation across the interface. This type of model may be helpful in engineering hot-spot clusters at protein-protein interfaces and, consequently, the design of specificity.

Nicotinic receptor interloop proline anchors beta1-beta2 and Cys loops in coupling agonist binding to channel gating

Nicotinic acetylcholine receptors (AChRs) mediate rapid excitatory synaptic transmission throughout the peripheral and central nervous systems. They transduce binding of nerve-released ACh into opening of an intrinsic channel, yet the structural basis underlying transduction is not fully understood. Previous studies revealed a principal transduction pathway in which αArg 209 of the pre-M1 domain and αGlu 45 of the β1–β2 loop functionally link the two regions, positioning αVal 46 of the β1–β2 loop in a cavity formed by αPro 272 through αSer 269 of the M2–M3 loop. Here we investigate contributions of residues within and proximal to this pathway using single-channel kinetic analysis, site-directed mutagenesis, and thermodynamic mutant cycle analysis. We find that in contributing to channel gating, αVal 46 and αVal 132 of the signature Cys loop couple energetically to αPro 272. Furthermore, these residues are optimized in both their size and hydrophobicity to mediate rapid and efficient channel gating, suggesting naturally occurring substitutions at these positions enable a diverse range of gating rate constants among the Cys-loop receptor superfamily. The overall results indicate that αPro 272 functionally couples to flanking Val residues extending from the β1–β2 and Cys loops within the ACh binding to channel opening transduction pathway.

Computational redesign of the SHV-1 beta-lactamase/beta-lactamase inhibitor protein interface

Beta-lactamases are enzymes that catalyze the hydrolysis of beta-lactam antibiotics. beta-lactamase/beta-lactamase inhibitor protein (BLIP) complexes are emerging as a well characterized experimental model system for studying protein-protein interactions. BLIP is a 165 amino acid protein that inhibits several class A beta-lactamases with a wide range of affinities: picomolar affinity for K1; nanomolar affinity for TEM-1, SME-1, and BlaI; but only micromolar affinity for SHV-1 beta-lactamase. The large differences in affinity coupled with the availability of extensive mutagenesis data and high-resolution crystal structures for the TEM-1/BLIP and SHV-1/BLIP complexes make them attractive systems for the further development of computational design methodology. We used EGAD, a physics-based computational design program, to redesign BLIP in an attempt to increase affinity for SHV-1. Characterization of several of designs and point mutants revealed that in all cases, the mutations stabilize the interface by 10- to 1000-fold relative to wild type BLIP. The calculated changes in binding affinity for the mutants were within a mean absolute error of 0.87 kcal/mol from the experimental values, and comparison of the calculated and experimental values for a set of 30 SHV-1/BLIP complexes yielded a correlation coefficient of 0.77. Structures of the two complexes with the highest affinity, SHV-1/BLIP (E73M) and SHV-1/BLIP (E73M, S130K, S146M), are presented at 1.7 A resolution. While the predicted structures have much in common with the experimentally determined structures, they do not coincide perfectly; in particular a salt bridge between SHV-1 D104 and BLIP K74 is observed in the experimental structures, but not in the predicted design conformations. This discrepancy highlights the difficulty of modeling salt bridge interactions with a protein design algorithm that approximates side chains as discrete rotamers. Nevertheless, while local structural features of the interface were sometimes miscalculated, EGAD is globally successful in designing complexes with increased affinity.

Modest membrane hydrogen bonds deliver rich results

The significance of hydrogen bonds in protein structure was recognized as early as 1936 by Mirsky and Pauling, and the importance of hydrogen bonds in water-soluble proteins has since been studied extensively. Now a new paper takes an important step forward in characterizing the energetic significance of hydrogen bonds in membrane-soluble proteins.

Double mutant cycle thermodynamic analysis of the hydrophobic Cdc42-ACK protein-protein interaction

Protein-protein interactions such as those between small G proteins and their effector proteins control most cell signaling pathways and thereby govern many cellular processes in both normal and disease states. Each small G protein interacts with several effectors, some shared between similar G proteins and others unique to a single GTPase. Although there is knowledge of the structural basis of these interactions, there is limited understanding of their thermodynamic basis. This is particularly significant because of the intrinsic conformational flexibility of the interacting partners. Here we have conducted a double mutant thermodynamic cycle for two key hydrophobic interactions in the Cdc42-ACK interface: Val42Cdc42-Ile463ACK and Leu174Cdc42-Leu449ACK. Val42 and Leu174 are known to be energetically important in this complex from previous thermodynamic studies, and their respective partners were predicted from the structure of the complex. Such a study has not been hitherto performed on any hydrophobic protein-protein interaction. The results confirm that a significant proportion of the overall interaction is dependent upon these residues, but in neither case is the direct interaction between the side chains the predominant energetic force. Indeed, the interaction of the side chains of Val42 and Ile463 appears to exert an energetic penalty. Rather, the stabilization of the complex, which requires the presence of these two pairs of residues, appears to be due to conformational changes, or interactions, that are not easily visualized in the structure of the complexes. In this respect, it is noteworthy that isolated Cdc42 shows regions of disorder and isolated ACK has no stable tertiary structure, whereas the Cdc42-ACK complex has a well-defined quaternary structure. Such changes may well be critical for the known selectivity of Cdc42 and related proteins such as Rho and Rac, for their wide range of effectors.

On the dynamic nature of the transition state for protein-protein association as determined by double-mutant cycle analysis and simulation

The process of protein-protein association starts with their random collision, which may develop into an encounter complex followed by a transition state and final complex formation. Here we aim to experimentally characterize the nature of the transition state of protein-protein association for three different protein-protein interactions; Barnase-Barstar, TEM1-BLIP and IFNalpha2-IFNAR2, and use the data to model the transition state structures. To model the transition state, we determined inter-protein distance-constraints of the activated complex by using double mutant cycles (DMC) assuming that interacting residues are spatially close. Significant DeltaDeltaG(double dagger)(int) values were obtained only between residues on Barnase and Barstar. However, introducing specific mutations that optimize the charge complementarity between BLIP and TEM1 resulted in the introduction of significant DeltaDeltaG(double dagger)(int) values also between residues of these two proteins. While electrostatic interactions make major contributions towards stabilizing the transition state, we show two examples where steric hindrance exerts an effect on the transition state as well. To model the transition-state structures from the experimental DeltaDeltaG(double dagger)(int) values, we introduced a method for structure perturbation, searching for those inter-protein orientations that best support the experimental DeltaDeltaG(double dagger)(int) values. Two types of transition states were found, specific as observed for Barnase-Barstar and the electrostatically optimized TEM1-BLIP mutants, and diffusive as shown for wild-type TEM1-BLIP and IFNalpha2-IFNAR2. The specific transition states are characterized by defined inter-protein orientations, which cannot be modeled for the diffusive transition states. Mutations introduced through rational design can change the transition state from diffusive to specific. Together, these data provide a structural view of the mechanism allowing rates of association to differ by five orders of magnitude between different protein complexes.