The impact of protein flexibility on protein-protein docking

Accounting for protein flexibility in protein-protein docking algorithms is challenging, and most algorithms therefore treat proteins as rigid bodies or permit side-chain motion only. While the consequences are obvious when there are large conformational changes upon binding, the situation is less clear for the modest conformational changes that occur upon formation of most protein-protein complexes. We have therefore studied the impact of local protein flexibility on protein-protein association by means of rigid body and torsion angle dynamics simulation. The binding of barnase and barstar was chosen as a model system for this study, because the complexation of these 2 proteins is well-characterized experimentally, and the conformational changes accompanying binding are modest. On the side-chain level, we show that the orientation of particular residues at the interface (so-called hotspot residues) have a crucial influence on the way contacts are established during docking from short protein separations of approximately 5 A. However, side-chain torsion angle dynamics simulations did not result in satisfactory docking of the proteins when using the unbound protein structures. This can be explained by our observations that, on the backbone level, even small (2 A) local loop deformations affect the dynamics of contact formation upon docking. Complementary shape-based docking calculations confirm this result, which indicates that both side-chain and backbone levels of flexibility influence short-range protein-protein association and should be treated simultaneously for atomic-detail computational docking of proteins.     

The relationship between the flexibility of proteins and their conformational states on forming protein-protein complexes with an application to protein-protein docking

We investigate the extent to which the conformational fluctuations of proteins in solution reflect the conformational changes that they undergo when they form binary protein-protein complexes. To do this, we study a set of 41 proteins that form such complexes and whose three-dimensional structures are known, both bound in the complex and unbound. We carry out molecular dynamics simulations of each protein, starting from the unbound structure, and analyze the resulting conformational fluctuations in trajectories of 5 ns in length, comparing with the structure in the complex. It is found that fluctuations take some parts of the molecules into regions of conformational space close to the bound state (or give information about it), but at no point in the simulation does each protein as whole sample the complete bound state. Subsequent use of conformations from a clustered MD ensemble in rigid-body docking is nevertheless partially successful when compared to docking the unbound conformations, as long as the unbound conformations are themselves included with the MD conformations and the whole globally rescored. For one key example where sub-domain motion is present, a ribonuclease inhibitor, principal components analysis of the MD was applied and was also able to produce conformations for docking that gave enhanced results compared to the unbound. The most significant finding is that core interface residues show a tendency to be less mobile (by size of fluctuation or entropy) than the rest of the surface even when the other binding partner is absent, and conversely the peripheral interface residues are more mobile. This surprising result, consistent across up to 40 of the 41 proteins, suggests different roles for these regions in protein recognition and binding, and suggests ways that docking algorithms could be improved by treating these regions differently in the docking process.     

Conformational entropy changes upon lactose binding to the carbohydrate recognition domain of galectin-3

The conformational entropy of proteins can make significant contributions to the free energy of ligand binding. NMR spin relaxation enables site-specific investigation of conformational entropy, via order parameters that parameterize local reorientational fluctuations of rank-2 tensors. Here we have probed the conformational entropy of lactose binding to the carbohydrate recognition domain of galectin-3 (Gal3), a protein that plays an important role in cell growth, cell differentiation, cell cycle regulation, and apoptosis, making it a potential target for therapeutic intervention in inflammation and cancer. We used ¹⁵N spin relaxation experiments and molecular dynamics simulations to monitor the backbone amides and secondary amines of the tryptophan and arginine side chains in the ligand-free and lactose-bound states of Gal3. Overall, we observe good agreement between the experimental and computed order parameters of the ligand-free and lactose-bound states. Thus, the ¹⁵N spin relaxation data indicate that the molecular dynamics simulations provide reliable information on the conformational entropy of the binding process. The molecular dynamics simulations reveal a correlation between the simulated order parameters and residue-specific backbone entropy, re-emphasizing that order parameters provide useful estimates of local conformational entropy. The present results show that the protein backbone exhibits an increase in conformational entropy upon binding lactose, without any accompanying structural changes.     

The Effect of Different Force Applications on the Protein-Protein Complex Barnase-Barstar

Steered molecular dynamics simulations are a tool to examine the energy landscape of protein-protein complexes by applying external forces. Here, we analyze the influence of the velocity and geometry of the probing forces on a protein complex using this tool. With steered molecular dynamics, we probe the stability of the protein-protein complex Barnase-Barstar. The individual proteins are mechanically labile. The Barnase-Barstar binding site is more stable than the folds of the individual proteins. By using different force protocols, we observe a variety of responses of the system to the applied tension.     

Influence of electrostatic forces on the association kinetics and conformational ensemble of an intrinsically disordered protein

Recent work has revealed that the association of a disordered region of a protein with a folded binding partner can occur as rapidly as association between two folded proteins. This is the case for the phosphatase calcineurin (CaN) and its association with its activator calmodulin. Calmodulin binds to the intrinsically disordered regulatory domain of CaN. Previous studies have shown that electrostatic steering can accelerate the binding of folded proteins with disordered ligands. Given that electrostatic forces are strong determinants of disordered protein ensembles, the relationship between electrostatics, conformational ensembles, and quaternary interactions is unclear. Here, we employ experimental approaches to explore the impact of electrostatic interactions on the association of calmodulin with the disordered regulatory region of CaN. We find that estimated association rate constants of calmodulin with our chosen calmodulin-substrates are within the diffusion-limited regime. The association rates are dependent on the ionic strength, indicating that favorable electrostatic forces increase the rate of association. Further, we show that charged amino acids outside the calmodulin-binding site modulate the binding rate. Conformational ensembles obtained from computer simulations suggest that electrostatic interactions within the regulatory domain might bias the conformational ensemble such that the calmodulin binding region is readily accessible. Given the prevalence of charged residues in disordered protein chains, our findings are likely relevant to many protein-protein interactions.     

Discrete Molecular Dynamics Can Predict Helical Prestructured Motifs in Disordered Proteins

Intrinsically disordered proteins (IDPs) lack a stable tertiary structure, but their short binding regions termed Pre-Structured Motifs (PreSMo) can form transient secondary structure elements in solution. Although disordered proteins are crucial in many biological processes and designing strategies to modulate their function is highly important, both experimental and computational tools to describe their conformational ensembles and the initial steps of folding are sparse. Here we report that discrete molecular dynamics (DMD) simulations combined with replica exchange (RX) method efficiently samples the conformational space and detects regions populating α-helical conformational states in disordered protein regions. While the available computational methods predict secondary structural propensities in IDPs based on the observation of protein-protein interactions, our ab initio method rests on physical principles of protein folding and dynamics. We show that RX-DMD predicts α-PreSMos with high confidence confirmed by comparison to experimental NMR data. Moreover, the method also can dissect α-PreSMos in close vicinity to each other and indicate helix stability. Importantly, simulations with disordered regions forming helices in X-ray structures of complexes indicate that a preformed helix is frequently the binding element itself, while in other cases it may have a role in initiating the binding process. Our results indicate that RX-DMD provides a breakthrough in the structural and dynamical characterization of disordered proteins by generating the structural ensembles of IDPs even when experimental data are not available.     

A fast empirical approach to binding free energy calculations based on protein interface information

Three useful variables from the interfaces of 20 protein-protein complexes were investigated. These variables are the side-chain accessible number (N(b)), the number of hydrophilic pairs (N(pair)) and buried a polar solvent accessible surface areas (DeltaDeltaASA(apol)). An empirical model based on the three variables was developed to describe the free energy of protein associations. As the results show, the side-chain accessible numbers characterize the loss of side-chain conformational entropy of protein interactions and the effective empirical function presented here has great capability for estimating the binding free energy. It was found that the variables of interface information capture most of the significant features of protein-protein association. Also, we applied the model based on the variables as a rescoring function to docking simulations and found that it has the potential to distinguish the 'true' binding mode. It is clear that the simple and empirical scale developed here is an attractive target function for calculating binding free energy for various biological processes to rational protein design.     

Coarse-grained simulations of protein-protein association: an energy landscape perspective

Understanding protein-protein association is crucial in revealing the molecular basis of many biological processes. Here, we describe a theoretical simulation pipeline to study protein-protein association from an energy landscape perspective. First, a coarse-grained model is implemented and its applications are demonstrated via molecular dynamics simulations for several protein complexes. Second, an enhanced search method is used to efficiently sample a broad range of protein conformations. Third, multiple conformations are identified and clustered from simulation data and further projected on a three-dimensional globe specifying protein orientations and interacting energies. Results from several complexes indicate that the crystal-like conformation is favorable on the energy landscape even if the landscape is relatively rugged with metastable conformations. A closer examination on molecular forces shows that the formation of associated protein complexes can be primarily electrostatics-driven, hydrophobics-driven, or a combination of both in stabilizing specific binding interfaces. Taken together, these results suggest that the coarse-grained simulations and analyses provide an alternative toolset to study protein-protein association occurring in functional biomolecular complexes.     

Accounting for conformational entropy in predicting binding free energies of protein-protein interactions

Protein-protein interactions are governed by the change in free energy upon binding, ΔG = ΔH - TΔS. These interactions are often marginally stable, so one must examine the balance between the change in enthalpy, ΔH, and the change in entropy, ΔS, when investigating known complexes, characterizing the effects of mutations, or designing optimized variants. To perform a large-scale study into the contribution of conformational entropy to binding free energy, we developed a technique called GOBLIN (Graphical mOdel for BiomoLecular INteractions) that performs physics-based free energy calculations for protein-protein complexes under both side-chain and backbone flexibility. Goblin uses a probabilistic graphical model that exploits conditional independencies in the Boltzmann distribution and employs variational inference techniques that approximate the free energy of binding in only a few minutes. We examined the role of conformational entropy on a benchmark set of more than 700 mutants in eight large, well-studied complexes. Our findings suggest that conformational entropy is important in protein-protein interactions--the root mean square error (RMSE) between calculated and experimentally measured ΔΔGs decreases by 12% when explicit entropic contributions were incorporated. GOBLIN models all atoms of the protein complex and detects changes to the binding entropy along the interface as well as positions distal to the binding interface. Our results also suggest that a variational approach to entropy calculations may be quantitatively more accurate than the knowledge-based approaches used by the well-known programs FOLDX and Rosetta--GOBLIN's RMSEs are 10 and 36% lower than these programs, respectively.     

A Brownian dynamics study: the effect of a membrane environment on an electron transfer system

During the past few years, three-dimensional crystal structures of many of the important integral membrane proteins responsible for the bioenergetic processes of photosynthesis and respiration have been determined. Moreover, a few crystal structures of protein-protein complexes have become available that characterize the interaction between those membrane proteins and the electron carrier protein cytochrome c. Here, we address the association kinetics for binding of cytochrome c to cytochrome c oxidase (COX) from Paracoccus denitrificans by Brownian dynamics simulations. The effects of ionic strength and protein mutations were studied for two different cytochrome c species: the positively charged, dipolar horse heart cytochrome c and the negatively charged physiological electron transfer partner cytochrome c(552). We studied association toward "naked" COX and toward membrane-embedded COX where the membrane is represented as an uncharged DPPC bilayer modeled in atomistic detail. For the nonnatural association toward "naked" COX, the association rates are >100 times larger for horse heart cytochrome c than for cytochrome c(552). Interestingly, the presence of the lipid bilayer leads to a dramatic decrease of the association rate of horse heart cytochrome c, but slightly enhances association of cytochrome c(552), leading to very similar association rates of both proteins to membrane-embedded COX. This finding from computational modeling studies may reflect the optimization of surface patches and of the total net charge on electron transfer pairs in nature.     

Side-chain conformational entropy at protein-protein interfaces

Protein-protein interactions are the key to many biological processes. How proteins selectively and correctly associate with their required protein partner(s) is still unclear. Previous studies of this "protein-docking problem" have found that shape complementarity is a major determinant of interaction, but the detailed balance of energy contributions to association remains unclear. This study estimates side-chain conformational entropy (per unit solvent accessible area) for various protein surface regions, using a self-consistent mean field calculation of rotamer probabilities. Interfacial surface regions were less flexible than the rest of the protein surface for calculations with monomers extracted from homodimer datasets in 21 of 25 cases, and in 8 of 9 for the large protomer from heterodimer datasets. In surface patch analysis, based on side-chain conformational entropy, 68% of true interfaces were ranked top for the homodimer set and 66% for the large protomer/heterodimer set. The results indicate that addition of a side-chain entropic term could significantly improve empirical calculations of protein-protein association.     

Calorimetric dissection of colicin DNase--immunity protein complex specificity

We explore the thermodynamic strategies used to achieve specific, high-affinity binding within a family of conserved protein-protein complexes. Protein-protein interactions are often stabilized by a conserved interfacial hotspot that serves as the anchor for the complex, with neighboring variable residues providing specificity. A key question for such complexes is the thermodynamic basis for specificity given the dominance of the hotspot. We address this question using, as our model, colicin endonuclease (DNase)-immunity (Im) protein complexes. In this system, cognate and noncognate complexes alike share the same mechanism of association and binding hotspot, but cognate complexes (K(d) approximately 10(-)(14) M) are orders of magnitude more stable than noncognate complexes (10(6)-10(10)-fold discrimination), largely because of a much slower rate of dissociation. Using isothermal titration calorimetry (ITC), we investigated the changes in enthalpy (DeltaH), entropy (-TDeltaS), and heat capacity (DeltaC(p)) accompanying binding of each Im protein (Im2, Im7, Im8, and Im9) to the DNase domains of colicins E2, E7, E8, and E9, in the context of both cognate and noncognate complexes. The data show that specific binding to the E2, E7, and E8 DNases is enthalpically driven but entropically driven for the E9 DNase. Analysis of DeltaC(p), a measure of the change in structural fluctuation upon complexation, indicates that E2, E7, and E8 DNase specificity is coupled to structural changes within cognate complexes that are consistent with a reduction in the conformational dynamics of these complexes. In contrast, E9 DNase specificity appears coupled to the exclusion of water molecules, consistent with the nonpolar nature of the interface of this complex. The work highlights that although protein-protein interactions may be centered on conserved structural epitopes the thermodynamic mechanism underpinning binding specificity can vary considerably.     

Identification of protein-protein interaction sites from docking energy landscapes

Protein recognition is one of the most challenging and intriguing problems in structural biology. Despite all the available structural, sequence and biophysical information about protein-protein complexes, the physico-chemical patterns, if any, that make a protein surface likely to be involved in protein-protein interactions, remain elusive. Here, we apply protein docking simulations and analysis of the interaction energy landscapes to identify protein-protein interaction sites. The new protocol for global docking based on multi-start global energy optimization of an all-atom model of the ligand, with detailed receptor potentials and atomic solvation parameters optimized in a training set of 24 complexes, explores the conformational space around the whole receptor without restrictions. The ensembles of the rigid-body docking solutions generated by the simulations were subsequently used to project the docking energy landscapes onto the protein surfaces. We found that highly populated low-energy regions consistently corresponded to actual binding sites. The procedure was validated on a test set of 21 known protein-protein complexes not used in the training set. As much as 81% of the predicted high-propensity patch residues were located correctly in the native interfaces. This approach can guide the design of mutations on the surfaces of proteins, provide geometrical details of a possible interaction, and help to annotate protein surfaces in structural proteomics.     

Electrostatic control of calcineurin's intrinsically-disordered regulatory domain binding to calmodulin

Calcineurin (CaN) is a serine/threonine phosphatase that regulates a variety of physiological and pathophysiological processes in mammalian tissue. The calcineurin (CaN) regulatory domain (RD) is responsible for regulating the enzyme's phosphatase activity, and is believed to be highly-disordered when inhibiting CaN, but undergoes a disorder-to-order transition upon diffusion-limited binding with the regulatory protein calmodulin (CaM). The prevalence of polar and charged amino acids in the regulatory domain (RD) suggests electrostatic interactions are involved in mediating calmodulin (CaM) binding, yet the lack of atomistic-resolution data for the bound complex has stymied efforts to probe how the RD sequence controls its conformational ensemble and long-range attractions contribute to target protein binding. In the present study, we investigated via computational modeling the extent to which electrostatics and structural disorder facilitate CaM/CaN association kinetics. Specifically, we examined several RD constructs that contain the CaM binding region (CAMBR) to characterize the roles of electrostatics versus conformational diversity in controlling diffusion-limited association rates, via microsecond-scale molecular dynamics (MD) and Brownian dynamic (BD) simulations. Our results indicate that the RD amino acid composition and sequence length influence both the dynamic availability of conformations amenable to CaM binding, as well as long-range electrostatic interactions to steer association. These findings provide intriguing insight into the interplay between conformational diversity and electrostatically-driven protein-protein association involving CaN, which are likely to extend to wide-ranging diffusion-limited processes regulated by intrinsically-disordered proteins.     

Compromise in competition between free energy and binding effect of intrinsically disordered protein p53 C-terminal domain

The C-terminal domain (CTD) of tumour suppressor p53 is an intrinsically disordered protein which has been shown to be able to bind multiple partner proteins and exercise diverse physiological functions in the cell. In this study, we performed molecular dynamics simulations on the isolated p53 CTD, as well as three regulatory binding complexes to investigate the conformational ensemble of isolated p53 CTD and its dynamic structures when different binding partner present. The results demonstrate that the isolated p53 CTD resembles a molten globule rather than extended structure. It mainly adopts random coil conformations with some tendency to form helical structures, which is consistent with experimental observations. For isolated p53 CTD, the dynamics is exclusively dominated by the intrinsic free energy and the p53 CTD could not folded spontaneously to each binding competent state which is located in high free energy region. However, when the binding partners present, the dynamics of p53 CTD are dominated by two mechanisms, the p53 CTD tending to adopt the structure with minimum free energy as isolate existed and the binding energy from partner protein tending to minimum. Each of them has an extreme tendency and corresponds to a possible characteristic state, the random coil state and each binding competent state. The compromise in competition between these two mechanisms results in alternate realisation of different characteristic states, while the relative strength of each mechanism determines the sampling frequency of each characteristic state.     

Predicting large-scale conformational changes in proteins using energy-weighted normal modes

We report the development of a method to improve the sampling of protein conformational space in molecular simulations. It is shown that a principal component analysis of energy-weighted normal modes in Cartesian coordinates can be used to extract vectors suitable for describing the dynamics of protein substructures. The method can operate with either atomistic or user-defined coarse-grained models of protein structure. An implicit reverse coarse-graining allows the dynamics of all-atoms to be recovered when a coarse-grained model is used. For an external test set of four proteins, it is shown that the new method is more successful than normal mode analysis in describing the large-scale conformational changes observed on ligand binding. The method has potential applications in protein-ligand and protein-protein docking and in biasing molecular dynamics simulations.     

Molecular principles of the interactions of disordered proteins

Thorough knowledge of the molecular principles of protein-protein recognition is essential to our understanding of protein function at the cellular level. Whereas interactions of ordered proteins have been analyzed in great detail, complexes of intrinsically unstructured/disordered proteins (IUPs) have hardly been addressed so far. Here, we have collected a database of 39 complexes of experimentally verified IUPs, and compared their interfaces with those of 72 complexes of ordered, globular proteins. The characteristic differences found between the two types of complexes suggest that IUPs represent a distinct molecular implementation of the principles of protein-protein recognition. The interfaces do not differ in size, but those of IUPs cover a much larger part of the surface of the protein than for their ordered counterparts. Moreover, IUP interfaces are significantly more hydrophobic relative to their overall amino acid composition, but also in absolute terms. They rely more on hydrophobic-hydrophobic than on polar-polar interactions. Their amino acids in the interface realize more intermolecular contacts, which suggests a better fit with the partner due to induced folding upon binding that results in a better adaptation to the partner. The two modes of interaction also differ in that IUPs usually use only a single continuous segment for partner binding, whereas the binding sites of ordered proteins are more segmented. Probably, all these features contribute to the increased evolutionary conservation of IUP interface residues. These noted molecular differences are also manifested in the interaction energies of IUPs. Our approximation of these by low-resolution force-fields shows that IUPs gain much more stabilization energy from intermolecular contacts, than from folding, i.e. they use their binding energy for folding. Overall, our findings provide a structural rationale to the prior suggestions that many IUPs are specialized for functions realized by protein-protein interactions.