Estimation of changes in side chain configurational entropy in binding and folding: general methods and application to helix formation

A cell-free antigen processing system informs HIV-1 epitope selection and vaccine design

Distinct CD4+ T cell epitopes have been associated with spontaneous control of HIV-1 replication, but analysis of antigen-dependent factors that influence epitope selection is lacking. To examine these factors, we used a cell-free antigen processing system that incorporates soluble HLA-DR (DR1), HLA-DM (DM), cathepsins, and full-length protein antigens for epitope identification by LC-MS/MS. HIV-1 Gag, Pol, Env, Vif, Tat, Rev, and Nef were examined using this system. We identified 35 novel epitopes, including glycopeptides. Epitopes from smaller HIV-1 proteins mapped to regions of low protein stability and higher solvent accessibility. HIV-1 antigens associated with limited CD4+ T cell responses were processed efficiently, while some protective epitopes were inefficiently processed. 55% of epitopes obtained from cell-free processing induced memory CD4+ T cell responses in HIV-1+ donors, including eight of 19 novel epitopes tested. Thus, an in vitro processing system utilizing the components of Class II processing reveals factors influencing epitope selection of HIV-1 and represents an approach to understanding epitope selection from non-HIV-1 antigens.

Kinematic Vibrational Entropy Assessment and Analysis of SARS CoV-2 Main Protease

The three-dimensional conformations of a protein influence its function and select for the ligands it can interact with. The total free energy change during protein-ligand complex formation includes enthalphic and entropic components, which together report on the binding affinity and conformational states of the complex. However, determining the entropic contribution is computationally burdensome. Here, we apply kinematic flexibility analysis (KFA) to efficiently estimate vibrational frequencies from static protein and protein-ligand structures. The vibrational frequencies, in turn, determine the vibrational entropies of the structures and their complexes. Our estimates of the vibrational entropy change caused by ligand binding compare favorably to values obtained from a dynamic Normal Mode Analysis (NMA). Higher correlation factors can be achieved by increasing the distance cutoff in the potential energy model. Furthermore, we apply our new method to analyze the entropy changes of the SARS CoV-2 main protease when binding with different ligand inhibitors, which is relevant for the design of potential drugs.

In vitro and in vivo inhibition of malaria parasite infection by monoclonal antibodies against Plasmodium falciparum circumsporozoite protein (CSP)

Plasmodium falciparum malaria contributes to a significant global disease burden. Circumsporozoite protein (CSP), the most abundant sporozoite stage antigen, is a prime vaccine candidate. Inhibitory monoclonal antibodies (mAbs) against CSP map to either a short junctional sequence or the central (NPNA)_n repeat region. We compared in vitro and in vivo activities of six CSP-specific mAbs derived from human recipients of a recombinant CSP vaccine RTS,S/AS01 (mAbs 317 and 311); an irradiated whole sporozoite vaccine PfSPZ (mAbs CIS43 and MGG4); or individuals exposed to malaria (mAbs 580 and 663). RTS,S mAb 317 that specifically binds the (NPNA)_n epitope, had the highest affinity and it elicited the best sterile protection in mice. The most potent inhibitor of sporozoite invasion in vitro was mAb CIS43 which shows dual-specific binding to the junctional sequence and (NPNA)_n. In vivo mouse protection was associated with the mAb reactivity to the NANPx6 peptide, the in vitro inhibition of sporozoite invasion activity, and kinetic parameters measured using intact mAbs or their Fab fragments. Buried surface area between mAb and its target epitope was also associated with in vivo protection. Association and disconnects between in vitro and in vivo readouts has important implications for the design and down-selection of the next generation of CSP based interventions.

Structural and Energetic Characterization of the Denatured State from the Perspectives of Peptides, the Coil Library, and Intrinsically Disordered Proteins

The α and polyproline II (PPII) basins are the two most populated regions of the Ramachandran map when constructed from the protein coil library, a widely used denatured state model built from the segments of irregular structure found in the Protein Data Bank. This indicates the α and PPII conformations are dominant components of the ensembles of denatured structures that exist in solution for biological proteins, an observation supported in part by structural studies of short, and thus unfolded, peptides. Although intrinsic conformational propensities have been determined experimentally for the common amino acids in short peptides, and estimated from surveys of the protein coil library, the ability of these intrinsic conformational propensities to quantitatively reproduce structural behavior in intrinsically disordered proteins (IDPs), an increasingly important class of proteins in cell function, has thus far proven elusive to establish. Recently, we demonstrated that the sequence dependence of the mean hydrodynamic size of IDPs in water and the impact of heat on the coil dimensions, provide access to both the sequence dependence and thermodynamic energies that are associated with biases for the α and PPII backbone conformations. Here, we compare results from peptide-based studies of intrinsic conformational propensities and surveys of the protein coil library to those of the sequence-based analysis of heat effects on IDP hydrodynamic size, showing that a common structural and thermodynamic description of the protein denatured state is obtained.

Entropy Hotspots for the Binding of Intrinsically Disordered Ligands to a Receptor Domain

Proline-rich motifs (PRMs) are widely used for mediating protein-protein interactions with weak binding affinities. Because they are intrinsically disordered when unbound, conformational entropy plays a significant role for the binding. However, residue-level differences of the entropic contribution in the binding of different ligands remain not well understood. We use all-atom molecular dynamics simulation and the maximal information spanning tree formalism to analyze conformational entropy associated with the binding of two PRMs, one from the Abl kinase and the other from the nonstructural protein 1 of the 1918 Spanish influenza A virus, to the N-terminal SH3 (nSH3) domain of the CrkII protein. Side chains of the stably folded nSH3 experience more entropy change upon ligand binding than the backbone, whereas PRMs involve comparable but heterogeneous entropy changes among the backbone and side chains. In nSH3, two conserved nonpolar residues forming contacts with the PRM experience the largest side-chain entropy loss. In contrast, the C-terminal charged residues of PRMs that form polar contacts with nSH3 experience the greatest side-chain entropy loss, although their "fuzzy" nature is attributable to the backbone that remains relatively flexible. Thus, residues that form high-occupancy contacts between nSH3 and PRM do not reciprocally contribute to entropy loss. Furthermore, certain surface residues of nSH3 distal to the interface with PRMs gain entropy, indicating a nonlocal effect of ligand binding. Comparing between the PRMs from cAbl and nonstructural protein 1, the latter involves a larger side-chain entropy loss and forms more contacts with nSH3. Consistent with experiments, this indicates stronger binding of the viral ligand at the expense of losing the flexibility of side chains, whereas the backbone experiences less entropy loss. The entropy "hotspots" as identified in this study will be important for tuning the binding affinity of various ligands to a receptor.

Impact of Heat on Coil Hydrodynamic Size Yields the Energetics of Denatured State Conformational Bias

Conformational equilibria in the protein denatured state have key roles regulating folding, stability, and function. The extent of conformational bias in the protein denatured state under folding conditions, however, has thus far proven elusive to quantify, particularly with regard to its sequence dependence and energetic character. To better understand the structural preferences of the denatured state, we analyzed both the sequence dependence to the mean hydrodynamic size of disordered proteins in water and the impact of heat on the coil dimensions, showing that the sequence dependence and thermodynamic energies associated with intrinsic biases for the α and polyproline II (PPII) backbone conformations can be obtained. Experiments that evaluate how the hydrodynamic size changes with compositional changes in the protein reveal amino acid specific preferences for PPII that are in good quantitative agreement with calorimetry-measured values from unfolded peptides and those inferred by survey of the protein coil library. At temperatures above 25 °C, the denatured state follows the predictions of a PPII-dominant ensemble. Heat effects on coil hydrodynamic size indicate the α bias is comparable to the PPII bias at cold temperatures. Though historically thought to give poor resolution to structural details, the hydrodynamic size of the unfolded state is found to be an effective reporter on the extent of the biases for the α and PPII backbone conformations.

Sequence Reversal Prevents Chain Collapse and Yields Heat-Sensitive Intrinsic Disorder

Sequence patterns of charge, hydrophobicity, hydrogen bonding, and other amino acid physicochemical properties contribute to mechanisms of protein folding, but how sequence composition and patterns influence the conformational dynamics of the denatured state ensemble is not fully understood. To investigate structure-sequence relationships in the denatured state, we reversed the sequence of staphylococcal nuclease and characterized its structure, thermodynamic character, and hydrodynamic radius using circular dichroism spectroscopy, dynamic light scattering, analytical ultracentrifugation, and size-exclusion chromatography as a function of temperature. The macromolecular size of "Retro-nuclease" is highly expanded in solution with characteristics similar to biological intrinsically disordered proteins. In contradistinction to a disordered state, Retro-nuclease exhibits a broad sigmoid transition of its hydrodynamic dimensions as temperature is increased, indicating a thermodynamically controlled compaction. Counterintuitively, the magnitude of these temperature-induced hydrodynamic changes exceed that observed from thermal denaturation of folded unaltered staphylococcal nuclease. Undetectable by calorimetry and intrinsic tryptophan fluorescence, the lack of heat capacity or fluorescence changes throughout the thermal transition indicate canonical hydrophobic collapse did not drive the Retro-nuclease structural transitions. Temperature-dependent circular dichroism spectroscopy performed on Retro-nuclease and computer simulations correlate to temperature sensitivity in the intrinsic sampling of backbone conformations for polyproline II and α-helix. The experimental results indicate a role for sequence direction in mediating the collapse of the polypeptide chain, whereas the simulation trends illustrate the generality of the observed heat effects on disordered protein structure.

Improving the thermostability of Serratia marcescens B4A chitinase via G191V site-directed mutagenesis

Chitinases with high thermostability are important for many industrial and biotechnological applications. This study was conducted to enhance the stability of Serratia marcescens B4A chitinase by site directed mutagenesis of G191 V. Further characterization showed that the thermal stability of the mutant showed marked increase of about 5 and 15 fold at 50 and 60 °C respectively, while the optimum temperature and pH was retained. Kinetic analysis showed decreased K_m and V_max of the mutant in comparison with the wild type chitinase of about 1.3 and 3 fold, respectively. Based on structural prediction, it was speculated that this replacement shortened an important loop concomitant with the extension of adjacent β sheets. Accordingly, a higher thermostability of G191 V up to 90 °C supporting the decreased flexibility of unfolded state was also indicated. Finally, a practical proof of kinetic and thermal stabilization of chitinase was provided through decreased flexibility and entropic stabilization of its surface loops.

Structural Stability of the Coiled-Coil Domain of Tumor Susceptibility Gene (TSG)-101

The tumor susceptibility gene-101 coiled coil domain (TSG101cc) is an integral component of the endosomal maturation machinery and cytokinesis, and also interacts with several transcription factors. The TSG101cc has been crystallized as a homotetramer but is known to interact with two of its binding partners as a heterotrimer. To investigate this apparent discrepancy, we examined the solution thermodynamics of the TSG101cc. Here, we use circular dichroism, differential scanning calorimetry, analytical ultracentrifugation, fluorescence, and structural thermodynamic analysis to investigate the structural stability and the unfolding of the TSG101cc. We demonstrate that TSG101cc exists in solution primarily as a tetramer, which unfolds in a two-state manner. Surprisingly, no homodimeric or homotrimeric species were detected. Structural thermodynamic analysis of the homotetrameric structure and comparison with known oligomeric coiled-coils suggests that the TSG101cc homotetramer is comparatively unstable on a per residue basis. Furthermore, the homotrimeric coiled-coil is predicted to be much less stable than the functional heterotrimeric coiled-coil in the endosomal sorting complex required for transport 1 (ESCRT1). These results support a model whereby the tetramer–monomer equilibrium of TSG101 serves as the cellular reservoir of TSG101, which is effectively outcompeted when its binding partners are present and the heteroternary complex can form.

Are induced fit protein conformational changes caused by ligand-binding predictable? A molecular dynamics investigation

In this work, the ability of molecular dynamics simulations (MD) to prospectively predict regions of ligand binding sites that could undergo induced fit effects was investigated. Conventional MD was run on 39 apo structures (no ligand), and the resulting trajectories were compared to a set of 147 holo X-ray structures (ligand-bound). It was observed from the simulations, in the absence of the ligands, that structures exhibiting large residue conformational changes indicated higher likelihood of induced fit effects. Nevertheless, the simulation results did not perform better than using the normalized crystallographic structural factors as predictors of active-site rigid residues (87% predictive power) and mobile residues (47% predictive power). While the simulations could not produce full active sites conformations similar to holo-like states, it was found that the simulations could reproduce bound state conformations of individual residues. These results suggest potential issues in the use of unligated simulation frames directly for drug design applications such as ligand docking, and an overall caution in the use of protein flexibility in docking protocols should be emphasized. © 2017 Wiley Periodicals, Inc.

Knowledge-based entropies improve the identification of native protein structures

Evaluating protein structures requires reliable free energies with good estimates of both potential energies and entropies. Although there are many demonstrated successes from using knowledge-based potential energies, computing entropies of proteins has lagged far behind. Here we take an entirely different approach and evaluate knowledge-based conformational entropies of proteins based on the observed frequencies of contact changes between amino acids in a set of 167 diverse proteins, each of which has two alternative structures. The results show that charged and polar interactions break more often than hydrophobic pairs. This pattern correlates strongly with the average solvent exposure of amino acids in globular proteins, as well as with polarity indices and the sizes of the amino acids. Knowledge-based entropies are derived by using the inverse Boltzmann relationship, in a manner analogous to the way that knowledge-based potentials have been extracted. Including these new knowledge-based entropies almost doubles the performance of knowledge-based potentials in selecting the native protein structures from decoy sets. Beyond the overall energy-entropy compensation, a similar compensation is seen for individual pairs of interacting amino acids. The entropies in this report have immediate applications for 3D structure prediction, protein model assessment, and protein engineering and design.

Effect of the Crystal Environment on Side-Chain Conformational Dynamics in Cyanovirin-N Investigated through Crystal and Solution Molecular Dynamics Simulations

Side chains in protein crystal structures are essential for understanding biochemical processes such as catalysis and molecular recognition. However, crystal packing could influence side-chain conformation and dynamics, thus complicating functional interpretations of available experimental structures. Here we investigate the effect of crystal packing on side-chain conformational dynamics with crystal and solution molecular dynamics simulations using Cyanovirin-N as a model system. Side-chain ensembles for solvent-exposed residues obtained from simulation largely reflect the conformations observed in the X-ray structure. This agreement is most striking for crystal-contacting residues during crystal simulation. Given the high level of correspondence between our simulations and the X-ray data, we compare side-chain ensembles in solution and crystal simulations. We observe large decreases in conformational entropy in the crystal for several long, polar and contacting residues on the protein surface. Such cases agree well with the average loss in conformational entropy per residue upon protein folding and are accompanied by a change in side-chain conformation. This finding supports the application of surface engineering to facilitate crystallization. Our simulation-based approach demonstrated here with Cyanovirin-N establishes a framework for quantitatively comparing side-chain ensembles in solution and in the crystal across a larger set of proteins to elucidate the effect of the crystal environment on protein conformations.

Intrinsic α helix propensities compact hydrodynamic radii in intrinsically disordered proteins

Proteins that lack tertiary stability under normal conditions, known as intrinsically disordered, exhibit a wide range of biological activities. Molecular descriptions for the biology of intrinsically disordered proteins (IDPs) consequently rely on disordered structural models, which in turn require experiments that assess the origins to structural features observed. For example, while hydrodynamic size is mostly insensitive to sequence composition in chemically denatured proteins, IDPs show strong sequence-specific effects in the hydrodynamic radius (R_h ) when measured under normal conditions. To investigate sequence-modulation of IDP R_h , disordered ensembles generated by a hard sphere collision model modified with a structure-based parameterization of the solution energetics were used to parse the contributions of net charge, main chain dihedral angle bias, and excluded volume on hydrodynamic size. Ensembles for polypeptides 10-35 residues in length were then used to establish power-law scaling relationships for comparison to experimental R_h from 26 IDPs. Results showed the expected outcomes of increased hydrodynamic size from increases in excluded volume and net charge, and compaction from chain-solvent interactions. Chain bias representing intrinsic preferences for α helix and polyproline II (PP_II ), however, modulated R_h with intricate dependence on the simulated propensities. PP_II propensities at levels expected in IDPs correlated with heightened R_h sensitivity to even weak α helix propensities, indicating bias for common (φ, ψ) are important determinants of hydrodynamic size. Moreover, data show that IDP R_h can be predicted from sequence with good accuracy from a small set of physicochemical properties, namely intrinsic conformational propensities and net charge. Proteins 2017; 85:296-311. © 2016 Wiley Periodicals, Inc.

Hydrodynamic Radii of Intrinsically Disordered Proteins Determined from Experimental Polyproline II Propensities

The properties of disordered proteins are thought to depend on intrinsic conformational propensities for polyproline II (PP_II) structure. While intrinsic PP_II propensities have been measured for the common biological amino acids in short peptides, the ability of these experimentally determined propensities to quantitatively reproduce structural behavior in intrinsically disordered proteins (IDPs) has not been established. Presented here are results from molecular simulations of disordered proteins showing that the hydrodynamic radius (R_h) can be predicted from experimental PP_II propensities with good agreement, even when charge-based considerations are omitted. The simulations demonstrate that R_h and chain propensity for PP_II structure are linked via a simple power-law scaling relationship, which was tested using the experimental R_h of 22 IDPs covering a wide range of peptide lengths, net charge, and sequence composition. Charge effects on R_h were found to be generally weak when compared to PP_II effects on R_h. Results from this study indicate that the hydrodynamic dimensions of IDPs are evidence of considerable sequence-dependent backbone propensities for PP_II structure that qualitatively, if not quantitatively, match conformational propensities measured in peptides.

Molecular models of disordered protein structures are needed to elucidate the functional mechanisms of intrinsically disordered proteins, a class of proteins implicated in many disease pathologies and human health issues. Several studies have measured intrinsic conformational propensities for polyproline II helix, a key structural motif of disordered proteins, in short peptides. Whether or not these experimental polyproline II propensities, which vary by amino acid type, reproduce structural behavior in intrinsically disordered proteins has yet to be demonstrated. Presented here are simulation results showing that polyproline II propensities from short peptides accurately describe sequence-dependent variability in the hydrodynamic dimensions of intrinsically disordered proteins. Good agreement was observed from a simple molecular model even when charge-based considerations were ignored, predicting that global organization of disordered protein structure is strongly dependent on intrinsic conformational propensities and, for many intrinsically disordered proteins, modulated only weakly by coulombic effects.

Clusters of isoleucine, leucine, and valine side chains define cores of stability in high-energy states of globular proteins: Sequence determinants of structure and stability

Measurements of protection against exchange of main chain amide hydrogens (NH) with solvent hydrogens in globular proteins have provided remarkable insights into the structures of rare high-energy states that populate their folding free-energy surfaces. Lacking, however, has been a unifying theory that rationalizes these high-energy states in terms of the structures and sequences of their resident proteins. The Branched Aliphatic Side Chain (BASiC) hypothesis has been developed to explain the observed patterns of protection in a pair of TIM barrel proteins. This hypothesis supposes that the side chains of isoleucine, leucine, and valine (ILV) residues often form large hydrophobic clusters that very effectively impede the penetration of water to their underlying hydrogen bond networks and, thereby, enhance the protection against solvent exchange. The linkage between the secondary and tertiary structures enables these ILV clusters to serve as cores of stability in high-energy partially folded states. Statistically significant correlations between the locations of large ILV clusters in native conformations and strong protection against exchange for a variety of motifs reported in the literature support the generality of the BASiC hypothesis. The results also illustrate the necessity to elaborate this simple hypothesis to account for the roles of adjacent hydrocarbon moieties in defining stability cores of partially folded states along folding reaction coordinates.

An integrative structure-based framework for predicting biological effects mediated by antipeptide antibodies

A general framework is presented for predicting quantitative biological effects mediated by antipeptide antibodies, primarily on the basis of antigen structure (possibly featuring intrinsic disorder) analyzed to estimate epitope-paratope binding affinities, which in turn is considered within the context of dose-response relationships as regards antibody concentration. This is illustrated mainly using an approach based on protein structural energetics, whereby expected amounts of solvent-accessible surface area buried upon epitope-paratope binding are related to the corresponding binding affinity, which is estimated from putative B-cell epitope structure with implicit treatment of paratope structure, for antipeptide antibodies either reacting with peptides or cross-reacting with cognate protein antigens. Key methods described are implemented in SAPPHIRE/SUITE (Structural-energetic Analysis Program for Predicting Humoral Immune Response Epitopes/SAPPHIRE User Interface Tool Ensemble; publicly accessible via http://freeshell.de/~badong/suite.htm). Representative results thus obtained are compared with published experimental data on binding affinities and quantitative biological effects, with special attention to loss of paratope sidechain conformational entropy (neglected in previous analyses) and in light of key in-vivo constraints on antigen-antibody binding affinity and antibody-mediated effects. Implications for further refinement of B-cell epitope prediction methods are discussed as regards envisioned biomedical applications including the development of prophylactic and therapeutic antibodies, peptide-based vaccines and immunodiagnostics.

Inferring the microscopic surface energy of protein-protein interfaces from mutation data

Mutations at protein-protein recognition sites alter binding strength by altering the chemical nature of the interacting surfaces. We present a simple surface energy model, parameterized with empirical ΔΔG values, yielding mean energies of -48 cal mol(-1) Å(-2) for interactions between hydrophobic surfaces, -51 to -80 cal mol(-1) Å(-2) for surfaces of complementary charge, and 66-83 cal mol(-1) Å(-2) for electrostatically repelling surfaces, relative to the aqueous phase. This places the mean energy of hydrophobic surface burial at -24 cal mol(-1) Å(-2) . Despite neglecting configurational entropy and intramolecular changes, the model correlates with empirical binding free energies of a functionally diverse set of rigid-body interactions (r = 0.66). When used to rerank docking poses, it can place near-native solutions in the top 10 for 37% of the complexes evaluated, and 82% in the top 100. The method shows that hydrophobic burial is the driving force for protein association, accounting for 50-95% of the cohesive energy. The model is available open-source from http://life.bsc.es/pid/web/surface_energy/ and via the CCharpPPI web server http://life.bsc.es/pid/ccharppi/.

Loss of conformational entropy in protein folding calculated using realistic ensembles and its implications for NMR-based calculations

The loss of conformational entropy is a major contribution in the thermodynamics of protein folding. However, accurate determination of the quantity has proven challenging. We calculate this loss using molecular dynamic simulations of both the native protein and a realistic denatured state ensemble. For ubiquitin, the total change in entropy is TΔSTotal = 1.4 kcal⋅mol(-1) per residue at 300 K with only 20% from the loss of side-chain entropy. Our analysis exhibits mixed agreement with prior studies because of the use of more accurate ensembles and contributions from correlated motions. Buried side chains lose only a factor of 1.4 in the number of conformations available per rotamer upon folding (ΩU/ΩN). The entropy loss for helical and sheet residues differs due to the smaller motions of helical residues (TΔShelix-sheet = 0.5 kcal⋅mol(-1)), a property not fully reflected in the amide N-H and carbonyl C=O bond NMR order parameters. The results have implications for the thermodynamics of folding and binding, including estimates of solvent ordering and microscopic entropies obtained from NMR.

Using the COREX/BEST server to model the native-state ensemble

Protein structures under normal conditions exist as ensembles of interconverting, transient microstates. A computer algorithm known as COREX/BEST (Biology using Ensemble-based Structural Thermodynamics) was developed to model microstate structures and describe the native ensembles of proteins in statistical thermodynamic terms. This algorithm has been tested extensively and validated through experimental comparisons examining a range of biophysical and functional phenomena, such as structural cooperativity, pH-dependent stability, and cold denaturation. Here, we describe a Web-based implementation of the COREX/BEST algorithm, called the COREX/BEST Server, and demonstrate how to use this online resource to characterize the structural and thermodynamic properties of the native protein ensemble.

Temperature effects on the hydrodynamic radius of the intrinsically disordered N-terminal region of the p53 protein

Intrinsically disordered proteins (IDPs) are often characterized in terms of the hydrodynamic radius, Rh . The Rh of IDPs are known to depend on fractional proline content and net charge, where increased numbers of proline residues and increased net charge cause larger Rh . Though sequence and charge effects on the Rh of IDPs have been studied, the temperature sensitivity has been noted only briefly. Reported here are Rh measurements in the temperature range of 5-75°C for the intrinsically disordered N-terminal region of the p53 protein, p53(1-93). Of note, the Rh of this protein fragment was highly sensitive to temperature, decreasing from 35 Å at 5°C to 26 Å at 75°C. Computer generated simulations of conformationally dynamic and disordered polypeptide chains were performed to provide a hypothesis for the heat-induced compaction of p53(1-93) structure, which was opposite to the heat-induced increase in Rh observed for a model folded protein. The simulations demonstrated that heat caused Rh to trend toward statistical coil values for both proteins, indicating that the effects of heat on p53(1-93) structure could be interpreted as thermal denaturation. The simulation data also predicted that proline content contributed minimally to the native Rh of p53(1-93), which was confirmed by measuring Rh for a substitution variant that had all 22 proline residues changed for glycine.

Molecular recognition in a diverse set of protein-ligand interactions studied with molecular dynamics simulations and end-point free energy calculations

End-point free energy calculations using MM-GBSA and MM-PBSA provide a detailed understanding of molecular recognition in protein-ligand interactions. The binding free energy can be used to rank-order protein-ligand structures in virtual screening for compound or target identification. Here, we carry out free energy calculations for a diverse set of 11 proteins bound to 14 small molecules using extensive explicit-solvent MD simulations. The structure of these complexes was previously solved by crystallography and their binding studied with isothermal titration calorimetry (ITC) data enabling direct comparison to the MM-GBSA and MM-PBSA calculations. Four MM-GBSA and three MM-PBSA calculations reproduced the ITC free energy within 1 kcal·mol(-1) highlighting the challenges in reproducing the absolute free energy from end-point free energy calculations. MM-GBSA exhibited better rank-ordering with a Spearman ρ of 0.68 compared to 0.40 for MM-PBSA with dielectric constant (ε = 1). An increase in ε resulted in significantly better rank-ordering for MM-PBSA (ρ = 0.91 for ε = 10), but larger ε significantly reduced the contributions of electrostatics, suggesting that the improvement is due to the nonpolar and entropy components, rather than a better representation of the electrostatics. The SVRKB scoring function applied to MD snapshots resulted in excellent rank-ordering (ρ = 0.81). Calculations of the configurational entropy using normal-mode analysis led to free energies that correlated significantly better to the ITC free energy than the MD-based quasi-harmonic approach, but the computed entropies showed no correlation with the ITC entropy. When the adaptation energy is taken into consideration by running separate simulations for complex, apo, and ligand (MM-PBSAADAPT), there is less agreement with the ITC data for the individual free energies, but remarkably good rank-ordering is observed (ρ = 0.89). Interestingly, filtering MD snapshots by prescoring protein-ligand complexes with a machine learning-based approach (SVMSP) resulted in a significant improvement in the MM-PBSA results (ε = 1) from ρ = 0.40 to ρ = 0.81. Finally, the nonpolar components of MM-GBSA and MM-PBSA, but not the electrostatic components, showed strong correlation to the ITC free energy; the computed entropies did not correlate with the ITC entropy.

The entropic nature of protein thermal stabilization

We performed thermodynamic analysis of temperature-induced unfolding of mesophilic and thermophilic proteins. It was shown that the variability in protein thermostability associated with pH-dependent unfolding or linked to the substitution of amino acid residues on the protein surface is evidence of the governing role of the entropy factor. Numerical values of conformational components in enthalpy, entropy and free energy which characterize protein unfolding in the "gas phase" were obtained. Based on the calculated absolute values of entropy and free energy, a model of protein unfolding is proposed in which the driving force is the conformational entropy of native protein, as an energy of the heat motion (T·S(NC)) increasing with temperature and acting as an factor devaluating the energy of intramolecular weak bonds in the transition state.

Side-chain rotamer changes upon ligand binding: common, crucial, correlate with entropy and rearrange hydrogen bonding

Motivation: Protein movements form a continuum from large domain rearrangements (including folding and restructuring) to side-chain rotamer changes and small rearrangements. Understanding side-chain flexibility upon binding is important to understand molecular recognition events and predict ligand binding.

Methods: In the present work, we developed a well-curated non-redundant dataset of 188 proteins in pairs of structures in the Apo (unbound) and Holo (bound) forms to study the extent and the factors that guide side-chain rotamer changes upon binding.

Results: Our analysis shows that side-chain rotamer changes are widespread with only 10% of binding sites displaying no conformational changes. Overall, at most five rotamer changes account for the observed movements in 90% of the cases. Furthermore, rotamer changes are essential in 32% of flexible binding sites. The different amino acids have a 11-fold difference in their probability to undergo changes. Side-chain flexibility represents an intrinsic property of amino acids as it correlates well with configurational entropy differences. Furthermore, on average b-factors and solvent accessible surface areas can discriminate flexible side-chains in the Apo form. Finally, there is a rearrangement of the hydrogen-bonding network upon binding primarily with a loss of H-bonds with water molecules and a gain of H-bonds with protein residues for flexible residues. Interestingly, only 25% of side chains capable of forming H-bonds do so with the ligand upon binding. In terms of drug design, this last result shows that there is a large number of potential interactions that may be exploited to modulate the specificity and sensitivity of inhibitors.

Contact:rafael.najmanovich@usherbrooke.ca

Structural modeling of HCV NS3/4A serine protease drug-resistance mutations using end-point continuum solvation and side-chain flexibility calculations

Computational methods of modeling protein-ligand interactions have gained widespread application in modern drug discovery. In continuum solvation-based methods of binding affinity estimation, limited description of solvent environment and protein flexibility is traded for a time scale that fits medicinal chemistry test cycles. The results of this speed-accuracy trade-off have been promising in terms of modeling structure-activity relationships of ligand series against protein targets. The potential of these approaches in recapitulating structural and energetic effects of resistance mutations, which involve large changes in binding affinity, remains relatively unexplored. We used continuum solvation binding affinity predictions and graph theory-based flexibility calculations to model thirteen drug resistance mutations in HCV NS3/4A serine protease, against three small-molecule inhibitors, with a 2-fold objective: quantitative assessment of binding energy predictions against experimental data and elucidation of structural/energetic determinants of resistance. The results show statistically significant correlation between predicted and experimental binding affinities, with R(2) and predictive index of up to 0.83 and 0.91, respectively. The level of accuracy was consistent with what has been reported for the inverse problem of binding affinity estimation of congeneric ligands against the same target. The quality of predictions was poor for mutations involving induced-fit effects, primarily, because of the lack of entropy terms. Flexibility analysis explained this discrepancy by indicating characteristic changes in side-chain mobility of a key binding site residue. The combined results from two approaches provide novel insights regarding the molecular mechanism of resistance. NS3/4A inhibitors, with large P2 substituents, derive high affinity with optimal van der Waals interactions in the S2 subsite, in order to overcome unfavorable desolvation and entropic cost of induced-fit effects. High-level resistance mutations tend to increase the desolvation and/or entropic barrier to ligand binding. The lead optimization strategies should, therefore, address the balance of these opposing energetic contributions in both the wild-type and mutant target.

Recognition of human tumor necrosis factor α (TNF-α) by therapeutic antibody fragment: energetics and structural features

Human tumor necrosis factor α (TNF-α) exists in its functional state as a homotrimeric protein and is involved in inflammation processes and immune response of a human organism. Overproduction of TNF-α results in the development of chronic autoimmune diseases that can be successfully treated by inhibitors such as monoclonal antibodies. However, the nature of antibody-TNF-α recognition remains elusive due to insufficient understanding of its molecular driving forces. Therefore, we studied the energetics of binding of a therapeutic antibody fragment (Fab) to the native and non-native forms of TNF-α by employing calorimetric and spectroscopic methods. Global thermodynamic analysis of data obtained from the corresponding binding and urea-induced denaturation experiments has been supported by structural modeling. We demonstrate that the observed high affinity binding of Fab to TNF-α is an enthalpy-driven process due mainly to specific noncovalent interactions taking place at the TNF-α-Fab binding interface. It is coupled to entropically unfavorable conformational changes and accompanied by entropically favorable solvation contributions. Moreover, the three-state model analysis of TNF-α unfolding shows that at physiological concentrations, TNF-α may exist not only as a biologically active trimer but also as an inactive monomer. It further suggests that even small changes of TNF-α concentration could have a considerable effect on the TNF-α activity. We believe that this study sets the energetic basis for understanding of TNF-α inhibition by antibodies and its unfolding linked with the concentration-dependent activity regulation.

Trinuclear ruthenium clusters as bivalent electrochemical probes for ligand-receptor binding interactions

Despite their popularity, electrochemical biosensors often suffer from low sensitivity. One possible approach to overcome low sensitivity in protein biosensors is to utilize multivalent ligand-receptor interactions. Controlling the spatial arrangement of ligands on surfaces is another crucial aspect of electrochemical biosensor design. We have synthesized and characterized five biotinylated trinuclear ruthenium clusters as potential new biosensor platforms: [Ru(3)O(OAc)(6)CO(4-BMP)(py)](0) (3), [Ru(3)O(OAc)(6)CO(4-BMP)(2)](0) (4), [Ru(3)O(OAc)(6)L(4-BMP)(py)](+) (8), [Ru(3)O(OAc)(6)L(4-BMP)(2)](+) (9), and [Ru(3)O(OAc)(6)L(py)(2)](+) (10) (OAc = acetate, 4-BMP = biotin aminomethylpyridine, py = pyridine, L = pyC16SH). HABA/avidin assays and isothermal titration calorimetry were used to evaluate the avidin binding properties of 3 and 4. The binding constants were found to range from (6.5-8.0) × 10(6) M(-1). Intermolecular protein binding of 4 in solution was determined by native gel electrophoresis. QM, MM, and MD calculations show the capability for the bivalent cluster, 4, to intramolecularly bind to avidin. Electrochemical measurements in solution of 3a and 4a show shifts in E(1/2) of -58 and -53 mV in the presence of avidin, respectively. Self-assembled monolayers formed with 8-10 were investigated as a model biosensor system. Diluent/cluster ratio and composition were found to have a significant effect on the ability of avidin to adequately bind to the cluster. Complexes 8 and 10 showed negligible changes in E(1/2), while complex 9 showed a shift in E(1/2) of -43 mV upon avidin addition. These results suggest that multivalent interactions can have a positive impact on the sensitivity of electrochemical protein biosensors.

Quantitative assessment of protein structural models by comparison of H/D exchange MS data with exchange behavior accurately predicted by DXCOREX

Peptide amide hydrogen/deuterium exchange mass spectrometry (DXMS) data are often used to qualitatively support models for protein structure. We have developed and validated a method (DXCOREX) by which exchange data can be used to quantitatively assess the accuracy of three-dimensional (3-D) models of protein structure. The method utilizes the COREX algorithm to predict a protein's amide hydrogen exchange rates by reference to a hypothesized structure, and these values are used to generate a virtual data set (deuteron incorporation per peptide) that can be quantitatively compared with the deuteration level of the peptide probes measured by hydrogen exchange experimentation. The accuracy of DXCOREX was established in studies performed with 13 proteins for which both high-resolution structures and experimental data were available. The DXCOREX-calculated and experimental data for each protein was highly correlated. We then employed correlation analysis of DXCOREX-calculated versus DXMS experimental data to assess the accuracy of a recently proposed structural model for the catalytic domain of a Ca(2+)-independent phospholipase A(2). The model's calculated exchange behavior was highly correlated with the experimental exchange results available for the protein, supporting the accuracy of the proposed model. This method of analysis will substantially increase the precision with which experimental hydrogen exchange data can help decipher challenging questions regarding protein structure and dynamics.

Mutational analysis of m-values as a strategy to identify cold-resistant substructures of the protein ensemble

Characterizing the native ensemble of protein is an important yet difficult objective of structural biology. The structural dynamics of protein macromolecules play key roles in biological function, but the short lifetimes and low population of near-native states of the protein ensemble limit their ability to be studied directly. In part to address such issues, it was shown recently that the cooperative substructures that populate a protein ensemble could be ascertained by NMR methods performed at very cold temperatures. What is presented here is an argument that these same substructures can also be determined by denaturant-induced unfolding studies performed on protein at room temperature. Data supporting this argument are given for Staphylococcal nuclease, chymotrypsin inhibitor 2, and ubiquitin. The observation of an agreement between the thermodynamics of the protein ensemble simulated under very cold temperatures to the apparent sensitivity of the ensemble to chemical denaturants at room temperature also suggests that the overall structural-thermodynamic character of an ensemble is surprisingly robust and preserved even in the presence of strong denaturing conditions.

Structure, energetics, and dynamics of binding coactivator peptide to the human retinoid X receptor α ligand binding domain complex with 9-cis-retinoic acid

Retinoid X receptors (RXRs) are ligand-dependent nuclear receptors, which are activated by the potent agonist 9-cis-retinoic acid (9cRA). 9cRA binds to the ligand binding domain (LBD) of RXRs and recruits coactivator proteins for gene transcription. Using isothermal titration calorimetry, the binding of a 13-mer coactivator peptide, GRIP-1, to the hRXRα-LBD homodimer complex containing 9cRA (hRXRα-LBD:9cRA:GRIP-1) is reported between 20 and 37 °C. ΔG is temperature independent (-8.5 kcal/mol), and GRIP-1 binding is driven by ΔH (-9.2 kcal/mol) at 25 °C. ΔC(p) is large and negative (-401 cal mol(-1) K(-1)). The crystal structure of hRXRα-LBD:9cRA:GRIP-1 is reported at 2.05 Å. When the structures of hRXRα-LBD:9cRA:GRIP-1 and hRXRα-LBD:9cRA ( 1FBY ) homodimers are compared, E453 and E456 on helix 12 bury and form ionic interactions with GRIP-1. R302 on helix 4 realigns to form new salt bridges to both E453 and E456. F277 (helix 3), F437 (helix 11), and F450 (helix 12) move toward the hydrophobic interior. The changes in the near-UV spectrum at 260 nm of the hRXRα-LBD:9cRA:GRIP-1 support this structural change. Helix 11 tilts toward helix 12 by ≈1 Å, modifying the ring conformation of 9cRA. Hydrogen-deuterium exchange mass spectroscopy indicates GRIP-1 binding to hRXRα-LBD:9cRA significantly decreases the exchange rates for peptides containing helices 3 (F277), 4 (R302), 11 (F437), and 12 (E453, E456). The structural changes and loss of dynamics of the GRIP-1-bound structure are used to interpret the energetics of coactivator peptide binding to the agonist-bound hRXRα-LBD.

Salt bridges: geometrically specific, designable interactions

Salt bridges occur frequently in proteins, providing conformational specificity and contributing to molecular recognition and catalysis. We present a comprehensive analysis of these interactions in protein structures by surveying a large database of protein structures. Salt bridges between Asp or Glu and His, Arg, or Lys display extremely well-defined geometric preferences. Several previously observed preferences are confirmed, and others that were previously unrecognized are discovered. Salt bridges are explored for their preferences for different separations in sequence and in space, geometric preferences within proteins and at protein-protein interfaces, co-operativity in networked salt bridges, inclusion within metal-binding sites, preference for acidic electrons, apparent conformational side chain entropy reduction on formation, and degree of burial. Salt bridges occur far more frequently between residues at close than distant sequence separations, but, at close distances, there remain strong preferences for salt bridges at specific separations. Specific types of complex salt bridges, involving three or more members, are also discovered. As we observe a strong relationship between the propensity to form a salt bridge and the placement of salt-bridging residues in protein sequences, we discuss the role that salt bridges might play in kinetically influencing protein folding and thermodynamically stabilizing the native conformation. We also develop a quantitative method to select appropriate crystal structure resolution and B-factor cutoffs. Detailed knowledge of these geometric and sequence dependences should aid de novo design and prediction algorithms.

Strategies for the thermodynamic characterization of linked binding/local folding reactions within the native state application to the LID domain of adenylate kinase from Escherichia coli

Conformational fluctuations in proteins have emerged as an important aspect of biological function, having been linked to processes ranging from molecular recognition and catalysis to allostery and signal transduction. In spite of the realization of their importance, however, the connections between fluctuations and function have largely been empirical, even when they have been quantitative. Part of the problem in understanding the role of fluctuations in function is the fact that the mere existence of fluctuations complicates the interpretation of classic mutagenesis approaches. Namely, mutagenesis, which is typically targeted to an internal position (to elicit an effect), will change the fluctuations as well as the structure of the native state. Decoupling these effects is essential to an unambiguous understanding of the role of fluctuations in function. Here, we use a mutation strategy that targets surface-exposed sites in flexible parts of the molecule for mutation to glycine. Such mutations leave the ground-state structure unaffected. As a result, we can assess the nature of the fluctuations, develop a quantitative model relating fluctuations to function (in this case, molecular recognition), and unambiguously resolve the probabilities of the fluctuating states. We show that when this approach is applied to Escherichia coli adenylate kinase (AK), unique thermodynamic and structural insights are obtained, even when classic mutagenesis approaches targeted to the same region yield ambiguous results.

Helix propensities calculations for amino acids in alanine based peptides using Jarzynski's equality

Jarzynski's equality (Jarzynski, Phys Rev E 1997; 56:5018 and Jarzynski, Phys Rev Lett 1997; 78:2690) relates equilibrium free energy differences between two states A and B to the work done when the system is driven repeatedly and irreversibly from an equilibrium state A to equilibrium state B. We present calculations of helix propensities using a novel procedure based on this equality. In particular, a work probability distribution is built based on combinations of multi-step trajectories that give representative work distributions without requiring computing an unreasonable large number of trajectories between states. A small number of trajectories (15) are used to construct a distribution that contains millions of work values. This distribution is used to calculate DeltaG(AB) using Jarsynski's equation. To apply and test this method, we used as a model system a dodeca-alanine helix, analyzing its extension using mechanical force. This helix was used as the basis of a host guest system in which two of the 12 residues are substituted by some other amino acid (as the guests). The differences between the unfolding free energies of the substituted peptides and the all-alanine peptide provided values for DeltaDeltaG that can be interpreted as the helix propensities of each amino acid. Results show good correlation with the experimental measurements of Baldwin and coworkers (Chakrabartty et al., Protein Sci 1994; 3:843-852).

Contribution of asparagine residues to the stabilization of a proteinaceous antigen-antibody complex, HyHEL-10-hen egg white lysozyme

Many germ line antibodies have asparagine residues at specific sites to achieve specific antigen recognition. To study the role of asparagine residues in the stabilization of antigen-antibody complexes, we examined the interaction between hen egg white lysozyme (HEL) and the corresponding HyHEL-10 variable domain fragment (Fv). We introduced Ala and Asp substitutions into the Fv side chains of L-Asn-31, L-Asn-32, and L-Asn-92, which interact directly with residues in HEL via hydrogen bonding in the wild-type Fv-HEL complex, and we investigated the interactions between these mutant antibodies and HEL. Isothermal titration calorimetric analysis showed that all the mutations decreased the negative enthalpy change and decreased the association constants of the interaction. Structural analyses showed that the effects of the mutations on the structure of the complex could be compensated for by conformational changes and/or by gains in other interactions. Consequently, the contribution of two hydrogen bonds was minor, and their abolition by mutation resulted in only a slight decrease in the affinity of the antibody for its antigen. By comparison, the other two hydrogen bonds buried at the interfacial area had large enthalpic advantage, despite entropic loss that was perhaps due to stiffening of the interface by the bonds, and were crucial to the strength of the interaction. Deletion of these strong hydrogen bonds could not be compensated for by other structural changes. Our results suggest that asparagine can provide the two functional groups for strong hydrogen bond formation, and their contribution to the antigen-antibody interaction can be attributed to their limited flexibility and accessibility at the complex interface.

Role of interfacial water molecules in proline-rich ligand recognition by the Src homology 3 domain of Abl

The interaction of Abl-Src homology 3 domain (SH3) with the high affinity peptide p41 is the most notable example of the inconsistency existing between the currently accepted description of SH3 complexes and their binding thermodynamic signature. We had previously hypothesized that the presence of interfacial water molecules is partially responsible for this thermodynamic behavior. We present here a thermodynamic, structural, and molecular dynamics simulation study of the interaction of p41 with Abl-SH3 and a set of mutants designed to alter the water-mediated interaction network. Our results provide a detailed description of the dynamic properties of the interfacial water molecules and a molecular interpretation of the thermodynamic effects elicited by the mutations in terms of the modulation of the water-mediated hydrogen bond network. In the light of these results, a new dual binding mechanism is proposed that provides a better description of proline-rich ligand recognition by Abl-SH3 and that has important implications for rational design.

Thermodynamics of Protein–Ligand Interactions: History, Presence, and Future Aspects

The understanding of molecular recognition processes of small ligands and biological macromolecules requires a complete characterization of the binding energetics and correlation of thermodynamic data with interacting structures involved. A quantitative description of the forces that govern molecular associations requires determination of changes of all thermodynamic parameters, including free energy of binding (deltaG), enthalpy (deltaH), and entropy (deltaS) of binding and the heat capacity change (deltaCp). A close insight into the binding process is of significant and practical interest, since it provides the fundamental know-how for development of structure-based molecular design-strategies. The only direct method to measure the heat change during complex formation at constant temperature is provided by isothermal titration calorimetry (ITC). With this method one binding partner is titrated into a solution containing the interaction partner, thereby generating or absorbing heat. This heat is the direct observable that can be quantified by the calorimeter. The use of ITC has been limited due to the lack of sensitivity, but recent developments in instrument design permit to measure heat effects generated by nanomol (typically 10-100) amounts of reactants. ITC has emerged as the primary tool for characterizing interactions in terms of thermodynamic parameters. Because heat changes occur in almost all chemical and biochemical processes, ITC can be used for numerous applications, e.g., binding studies of antibody-antigen, protein-peptide, protein-protein, enzyme-inhibitor or enzyme-substrate, carbohydrate-protein, DNA-protein (and many more) interactions as well as enzyme kinetics. Under appropriate conditions data analysis from a single experiment yields deltaH, K(B), the stoichiometry (n), deltaG and deltaS of binding. Moreover, ITC experiments performed at different temperatures yield the heat capacity change (deltaCp). The informational content of thermodynamic data is large, and it has been shown that it plays an important role in the elucidation of binding mechanisms and, through the link to structural data, also in rational drug design. In this review we will present a comprehensive overview to ITC by giving some historical background to calorimetry, outline some critical experimental and data analysis aspects, discuss the latest developments, and give three recent examples of studies published with respect to macromolecule-ligand interactions that have utilized ITC technology.

Functional aspects of protein flexibility

Proteins are dynamic entities, and they possess an inherent flexibility that allows them to function through molecular interactions within the cell, among cells and even between organisms. Appreciation of the non-static nature of proteins is emerging, but to describe and incorporate this into an intuitive perception of protein function is challenging. Flexibility is of overwhelming importance for protein function, and the changes in protein structure during interactions with binding partners can be dramatic. The present review addresses protein flexibility, focusing on protein-ligand interactions. The thermodynamics involved are reviewed, and examples of structure-function studies involving experimentally determined flexibility descriptions are presented. While much remains to be understood about protein flexibility, it is clear that it is encoded within their amino acid sequence and should be viewed as an integral part of their structure.

Driving forces of gyrase recognition by the addiction toxin CcdB

Gyrase, an essential bacterial topoisomerase, is the target of several antibiotics (e.g. quinolones) as well as of bacterial toxin CcdB. This toxin, encoded by Escherichia coli toxin-antitoxin module ccd, poisons gyrase by causing inhibition of both transcription and replication. Because the molecular driving forces of gyrase unfolding and CcdB-gyrase binding were unknown, the nature of the CcdB-gyrase recognition remained elusive. Therefore, we performed a detailed thermodynamic analysis of CcdB binding to several fragments of gyrase A subunit (GyrA) that contain the CcdB-binding site. Binding of CcdB to the shorter fragments was studied directly by isothermal titration calorimetry. Its binding to the longer GyrA59 fragment in solution is kinetically limited and was therefore investigated via urea induced unfolding of the GyrA59-CcdB complex and unbound GyrA59 and CcdB, monitored by circular dichroism spectroscopy. Model analysis of experimental data, in combination with the relevant structural information, indicates that CcdB binding to gyrase is an enthalpic process driven mainly by specific interactions between CcdB and the highly stable dimerization domain of the GyrA. The dissection of binding energetics indicates that CcdB-gyrase recognition is accompanied by opening of the tower and catalytic domain of GyrA. Such extensive structural rearrangements appear to be crucial driving forces for the functioning of the ccd toxin-antitoxin module.

Characterizing the role of ensemble modulation in mutation-induced changes in binding affinity

Protein conformational fluctuations are key contributors to biological function, mediating important processes such as enzyme catalysis, molecular recognition, and allosteric signaling. To better understand the role of conformational fluctuations in substrate/ligand recognition, we analyzed, experimentally and computationally, the binding reaction between an SH3 domain and the recognition peptide of its partner protein. The fluctuations in this SH3 domain were enumerated by using an algorithm based on the hard sphere collision model, and the binding energetics resulting from these fluctuations were calculated using a structure-based energy function parametrized to solvent accessible surface areas. Surprisingly, this simple model reproduced the effects of mutations on the experimentally determined SH3 binding energetics, within the uncertainties of the measurements, indicating that conformational fluctuations in SH3, and in particular the RT loop region, are structurally diverse and are well-approximated by the randomly configured states. The mutated positions in SH3 were distant to the binding site and involved Ala and Gly substitutions of solvent exposed positions in the RT loop. To characterize these fluctuations, we applied principal coordinate analysis to the computed ensembles, uncovering the principal modes of conformational variation. It is shown that the observed differences in binding affinity between each mutant, and thus the apparent coupling between the mutated sites, can be described in terms of the changes in these principal modes. These results indicate that dynamic loops in proteins can populate a broad conformational ensemble and that a quantitative understanding of molecular recognition requires consideration of the entire distribution of states.

Between-species variation in the kinetic stability of TIM proteins linked to solvation-barrier free energies

Theoretical, computational, and experimental studies have suggested the existence of solvation barriers in protein unfolding and denaturation processes. These barriers are related to the finite size of water molecules and can be envisioned as arising from the asynchrony between water penetration and breakup of internal interactions. Solvation barriers have been proposed to play roles in protein cooperativity and kinetic stability; therefore, they may be expected to be subject to natural selection. We study the thermal denaturation, in the presence and in the absence of chemical denaturants, of triosephosphate isomerases (TIMs) from three different species: Trypanosoma cruzi, Trypanosoma brucei, and Leishmania mexicana. In all cases, denaturation was irreversible and kinetically controlled. Surprisingly, however, we found large differences between the kinetic denaturation parameters, with T. cruzi TIM showing a much larger activation energy value (and, consequently, much lower room-temperature, extrapolated denaturation rates). This disparity cannot be accounted for by variations in the degree of exposure to solvent in transition states (as measured by kinetic urea m values) and is, therefore, to be attributed mainly to differences in solvation-barrier contributions. This was supported by structure-energetics analyses of the transition states and by application of a novel procedure to estimate from experimental data the solvation-barrier impact at the entropy and free-energy levels. These analyses were actually performed with an extended protein set (including six small proteins plus seven variants of lipase from Thermomyces lanuginosus and spanning a wide range of activation parameters), allowing us to delineate the general trends of the solvation-barrier contributions. Overall, this work supports that proteins sharing the same structure and function but belonging to different organisms may show widely different solvation barriers, possibly as a result of different levels of the selection pressure associated with cooperativity, kinetic stability, and related factors.

Exploring the impact of polyproline II (PII) conformational bias on the binding of peptides to the SEM-5 SH3 domain

The left-handed polyproline II helical structure (P(II)) is observed to be a dominant conformation in the disordered states of protein and small polypeptide chains, even when no prolines are present in the sequence. Recently, in work by Ferreon and Hilser, the energetics associated with Ala and Gly substitutions at a surface exposed proline site were determined calorimetrically by measuring the binding energetics of Sos peptide variants to the C-terminal Src Homology 3 domain of SEM-5. The results were interpreted as a significant conformational bias toward the bound conformation (i.e., P(II)), even when the ligand is unbound. That study was not able to determine, however, whether the conformational bias of the peptides could be explained in terms other than that of a P(II) preference. Here, we test, using a computer algorithm based on the hard sphere collision (HSC) model, the notion of whether a bias in the unbound states of the peptide ligands is specific for the P(II) conformation, or if a bias to any other region of (phi, psi) space can also result in the same observed binding energetics. The results of these computer simulations indicate that, of the regions of (phi, psi) modeled for bias in the small peptides, only the bias to the P(II) conformation, and at rates of bias similar to the experimentally observed rates, quantitatively reproduced the experimental binding energetics.

Structural basis of the differential binding of the SH3 domains of Grb2 adaptor to the guanine nucleotide exchange factor Sos1

Grb2-Sos1 interaction, mediated by the canonical binding of N-terminal SH3 (nSH3) and C-terminal SH3 (cSH3) domains of Grb2 to a proline-rich sequence in Sos1, provides a key regulatory switch that relays signaling from activated receptor tyrosine kinases to downstream effector molecules such as Ras. Here, using isothermal titration calorimetry in combination with site-directed mutagenesis, we show that the nSH3 domain binds to a Sos1-derived peptide containing the proline-rich consensus motif PPVPPR with an affinity that is nearly threefold greater than that observed for the binding of cSH3 domain. We further demonstrate that such differential binding of nSH3 domain relative to the cSH3 domain is largely due to the requirement of a specific acidic residue in the RT loop of the beta-barrel fold to engage in the formation of a salt bridge with the arginine residue in the consensus motif PPVPPR. While this role is fulfilled by an optimally positioned D15 in the nSH3 domain, the chemically distinct and structurally non-equivalent E171 substitutes in the case of the cSH3 domain. Additionally, our data suggest that salt tightly modulates the binding of both SH3 domains to Sos1 in a thermodynamically distinct manner. Our data further reveal that, while binding of both SH3 domains to Sos1 is under enthalpic control, the nSH3 binding suffers from entropic penalty in contrast to entropic gain accompanying the binding of cSH3, implying that the two domains employ differential thermodynamic mechanisms for Sos1 recognition. Our new findings are rationalized in the context of 3D structural models of SH3 domains in complex with the Sos1 peptide. Taken together, our study provides structural basis of the differential binding of SH3 domains of Grb2 to Sos1 and a detailed thermodynamic profile of this key protein-protein interaction pertinent to cellular signaling and cancer.

Denatured-state energy landscapes of a protein structural database reveal the energetic determinants of a framework model for folding

Position-specific denatured-state thermodynamics were determined for a database of human proteins by use of an ensemble-based model of protein structure. The results of modeling denatured protein in this manner reveal important sequence-dependent thermodynamic properties in the denatured ensembles as well as fundamental differences between the denatured and native ensembles in overall thermodynamic character. The generality and robustness of these results were validated by performing fold-recognition experiments, whereby sequences were matched with their respective folds based on amino acid propensities for the different energetic environments in the protein, as determined through cluster analysis. Correlation analysis between structure and energetic information revealed that sequence segments destined for beta-sheet in the final native fold are energetically more predisposed to a broader repertoire of states than are sequence segments destined for alpha-helix. These results suggest that within the subensemble of mostly unstructured states, the energy landscapes are dominated by states in which parts of helices adopt structure, whereas structure formation for sequences destined for beta-strand is far less probable. These results support a framework model of folding, which suggests that, in general, the denatured state has evolutionarily evolved to avoid low-energy conformations in sequences that ultimately adopt beta-strand. Instead, the denatured state evolved so that sequence segments that ultimately adopt alpha-helix and coil will have a high intrinsic structure formation capability, thus serving as potential nucleation sites.

Ligand effects on the protein ensemble: unifying the descriptions of ligand binding, local conformational fluctuations, and protein stability

Detailed description of the structural and physical basis of allostery, cooperativity, and other manifestations of long-range communication between binding sites in proteins remains elusive. Here we describe an ensemble-based structural-thermodynamic model capable of treating explicitly the coupling between ligand binding reactions, local fluctuations in structure, and global conformational transitions. The H(+) binding reactions of staphylococcal nuclease and the effects of pH on its stability were used to illustrate the properties of proteins that can be described quantitatively with this model. Each microstate in the native ensemble was modeled to have dual structural character; some regions were treated as folded and retained the same atomic geometry as in the crystallographic structure while other regions were treated thermodynamically as if they were unfolded. Two sets of pK(a) values were used to describe the affinity of each H(+) binding site. One set, calculated with a standard continuum electrostatics method, describes H(+) binding to sites in folded parts of the protein. A second set of pK(a) values, obtained from model compounds in water, was used to describe H(+) binding to sites in unfolded regions. An empirical free energy function, parameterized to reproduce folding thermodynamics measured by differential scanning calorimetry, was used to calculate the probability of each microstate. The effects of pH on the distribution of microstates were determined by the H(+) binding properties of each microstate. The validity of the calculations was established by comparison with a number of different experimental observables.

Prediction of Solvation Sites at the Interface of Src SH2 Domain Complexes Using Molecular Dynamics Simulations

Src Homology 2 (SH2) domains are approximately 100 amino acid domains that mediate recognition of tyrosine-phosphorylated sites by signalling proteins. Structures of SH2 domains with bound ligands indicate a potentially important role of water in influencing the binding thermodynamics. In this study, we used molecular dynamics (MD) simulation methods to evaluate solvation sites at the binding interface of the Src SH2 domain. We designed a software, WaRP (Water Residency Potential), to compute the positions of hydration sites from coordinates data of MD simulations and studied the impact of the computed positions on the prediction of the thermodynamics of Src SH2 domain binding to phosphorylated peptides using a method based on accessible surface area buried upon association. Two dually phosphorylated ligands and one monophosphorylated ligand were studied. We showed that the software predicted between 70% and 85% of the crystallographic water molecules depending on complexes. Comparison of the predicted water structures of both the bound and unbound binding partners led to a thorough evaluation of water behaviour during the binding reaction. We also showed that the predicted water structures of all ligand-SH2 domain structures investigated may be used to derive the entropy change provided that the heat capacity change is known. This study is the first to examine the dynamics of the water structure around the SH2 domain binding interface and contributes to our understanding of binding thermodynamics in SH2 domains.

Prediction of side-chain conformations on protein surfaces

An approach is described that improves the prediction of the conformations of surface side chains in crystal structures, given the main-chain conformation of a protein. A key element of the methodology involves the use of the colony energy. This phenomenological term favors conformations found in frequently sampled regions, thereby approximating entropic effects and serving to smooth the potential energy surface. Use of the colony energy significantly improves prediction accuracy for surface side chains with little additional computational cost. Prediction accuracy was quantified as the percentage of side-chain dihedral angles predicted to be within 40 degrees of the angles measured by X-ray diffraction. Use of the colony energy in predictions for single side chains improved the prediction accuracy for chi(1) and chi(1+2) from 65 and 40% to 74 and 59%, respectively. Several other factors that affect prediction of surface side-chain conformations were also analyzed, including the extent of conformational sampling, details of the rotamer library employed, and accounting for the crystallographic environment. The prediction of conformations for polar residues on the surface was generally found to be more difficult than those for hydrophobic residues, except for polar residues participating in hydrogen bonds with other protein groups. For surface residues with hydrogen-bonded side chains, the prediction accuracy of chi(1) and chi(1+2) was 79 and 63%, respectively. For surface polar residues, in general (all side-chain prediction), the accuracy of chi(1) and chi(1+2) was only 73 and 56%, respectively. The most accurate results were obtained using the colony energy and an all-atom description that includes neighboring molecules in the crystal (protein chains and hetero atoms). Here, the accuracy of chi(1) and chi(1+2) predictions for surface side chains was 82 and 73%, respectively. The root mean square deviations obtained for hydrogen-bonding surface side chains were 1.64 and 1.81 A, with and without consideration of crystal packing effects, respectively.

Compensating Enthalpic and Entropic Changes Hinder Binding Affinity Optimization

A common strategy to improve the potency of drug candidates is to introduce chemical functionalities, like hydrogen bond donors or acceptors, at positions where they are able to establish strong interactions with the target. However, it is often observed that the added functionalities do not necessarily improve potency even if they form strong hydrogen bonds. Here, we explore the thermodynamic and structural basis for those observations. KNI-10033 is a potent experimental HIV-1 protease inhibitor with picomolar affinity against the wild-type enzyme (K(d) = 13 pm). The potency of the inhibitor is the result of favorable enthalpic (DeltaH = -8.2 kcal/mol) and entropic (-TDeltaS = -6.7 kcal/mol) interactions. The replacement of the thioether group in KNI-10033 by a sulfonyl group (KNI-10075) results in a strong hydrogen bond with the amide of Asp 30B of the HIV-1 protease. This additional hydrogen bond improves the binding enthalpy by 3.9 kcal/mol; however, the enthalpy gain is completely compensated by an entropy loss, resulting in no affinity change. Crystallographic and thermodynamic analysis of the inhibitor/protease complexes indicates that the entropy losses are due to a combination of conformational and solvation effects. These results provide a set of practical guidelines aimed at overcoming enthalpy/entropy compensation and improve binding potency.