Computational alanine scanning of protein-protein interfaces

Molecular dynamics-solvated interaction energy studies of protein-protein interactions: the MP1-p14 scaffolding complex

Using the MP1-p14 scaffolding complex from the mitogen-activated protein kinase signaling pathway as model system, we explored a structure-based computational protocol to probe and characterize binding affinity hot spots at protein-protein interfaces. Hot spots are located by virtual alanine-scanning consensus predictions over three different energy functions and two different single-structure representations of the complex. Refined binding affinity predictions for select hot-spot mutations are carried out by applying first-principle methods such as the molecular mechanics generalized Born surface area (MM-GBSA) and solvated interaction energy (SIE) to the molecular dynamics (MD) trajectories for mutated and wild-type complexes. Here, predicted hot-spot residues were actually mutated to alanine, and crystal structures of the mutated complexes were determined. Two mutated MP1-p14 complexes were investigated, the p14(Y56A)-mutated complex and the MP1(L63A,L65A)-mutated complex. Alternative ways to generate MD ensembles for mutant complexes, not relying on crystal structures for mutated complexes, were also investigated. The SIE function, fitted on protein-ligand binding affinities, gave absolute binding affinity predictions in excellent agreement with experiment and outperformed standard MM-GBSA predictions when tested on the MD ensembles of Ras-Raf and Ras-RalGDS protein-protein complexes. For wild-type and mutant MP1-p14 complexes, SIE predictions of relative binding affinities were supported by a yeast two-hybrid assay that provided semiquantitative relative interaction strengths. Results on the MP1-mutated complex suggested that SIE predictions deteriorate if mutant MD ensembles are approximated by just mutating the wild-type MD trajectory. The SIE data on the p14-mutated complex indicated feasibility for generating mutant MD ensembles from mutated wild-type crystal structure, despite local structural differences observed upon mutation. For energetic considerations, this would circumvent costly needs to produce and crystallize mutated complexes. The sensitized protein-protein interface afforded by the p14(Y56A) mutation identified here has practical applications in screening-based discovery of first-generation small-molecule hits for further development into specific modulators of the mitogen-activated protein kinase signaling pathway.

A new twist in TCR diversity revealed by a forbidden alphabeta TCR

We report crystal structures of a negatively selected T cell receptor (TCR) that recognizes two I-A(u)-restricted myelin basic protein peptides and one of its peptide/major histocompatibility complex (pMHC) ligands. Unusual complementarity-determining region (CDR) structural features revealed by our analyses identify a previously unrecognized mechanism by which the highly variable CDR3 regions define ligand specificity. In addition to the pMHC contact residues contributed by CDR3, the CDR3 residues buried deep within the V alpha/V beta interface exert indirect effects on recognition by influencing the V alpha/V beta interdomain angle. This phenomenon represents an additional mechanism for increasing the potential diversity of the TCR repertoire. Both the direct and indirect effects exerted by CDR residues can impact global TCR/MHC docking. Analysis of the available TCR structures in light of these results highlights the significance of the V alpha/V beta interdomain angle in determining specificity and indicates that TCR/pMHC interface features do not distinguish autoimmune from non-autoimmune class II-restricted TCRs.

Restricted mobility of conserved residues in protein-protein interfaces in molecular simulations

Conserved residues in protein-protein interfaces correlate with residue hot-spots. To obtain insight into their roles, we have studied their mobility. We have performed 39 explicit solvent simulations of 15 complexes and their monomers, with the interfaces varying in size, shape, and function. The dynamic behavior of conserved residues in unbound monomers illustrates significantly lower flexibility as compared to their environment, suggesting that already before binding they are constrained in a boundlike configuration. To understand this behavior, we have analyzed the inter- and intrachain hydrogen-bond residence-time in the interfaces. We find that conserved residues are not involved significantly in hydrogen bonds across the interface as compared to nonconserved. However, the monomer simulations reveal that conserved residues contribute dominantly to hydrogen-bond formation before binding. Packing of conserved residues across the trajectories is significantly higher before and after the binding, rationalizing their lower mobility. Backbone torsional angle distributions show that conserved residues assume restricted regions of space and the most visited conformations in the bound and unbound trajectories are similar, suggesting that conserved residues are preorganized. Combined with previous studies, we conclude that conserved residues, hot spots, anchor, and interface-buried residues may be similar residues, fulfilling similar roles.

Determinants of protein abundance and translation efficiency in S. cerevisiae

The translation efficiency of most Saccharomyces cerevisiae genes remains fairly constant across poor and rich growth media. This observation has led us to revisit the available data and to examine the potential utility of a protein abundance predictor in reinterpreting existing mRNA expression data. Our predictor is based on large-scale data of mRNA levels, the tRNA adaptation index, and the evolutionary rate. It attains a correlation of 0.76 with experimentally determined protein abundance levels on unseen data and successfully cross-predicts protein abundance levels in another yeast species (Schizosaccharomyces pombe). The predicted abundance levels of proteins in known S. cerevisiae complexes, and of interacting proteins, are significantly more coherent than their corresponding mRNA expression levels. Analysis of gene expression measurement experiments using the predicted protein abundance levels yields new insights that are not readily discernable when clustering the corresponding mRNA expression levels. Comparing protein abundance levels across poor and rich media, we find a general trend for homeostatic regulation where transcription and translation change in a reciprocal manner. This phenomenon is more prominent near origins of replications. Our analysis shows that in parallel to the adaptation occurring at the tRNA level via the codon bias, proteins do undergo a complementary adaptation at the amino acid level to further increase their abundance.

Statistical analysis of physical-chemical properties and prediction of protein-protein interfaces

We have developed a fully automated method, InterProSurf, to predict interacting amino acid residues on protein surfaces of monomeric 3D structures. Potential interacting residues are predicted based on solvent accessible surface areas, a new scale for interface propensities, and a cluster algorithm to locate surface exposed areas with high interface propensities. Previous studies have shown the importance of hydrophobic residues and specific charge distribution as characteristics for interfaces. Here we show differences in interface and surface regions of all physical chemical properties of residues as represented by five quantitative descriptors. In the current study a set of 72 protein complexes with known 3D structures were analyzed to obtain interface propensities of residues, and to find differences in the distribution of five quantitative descriptors for amino acid residues. We also investigated spatial pair correlations of solvent accessible residues in interface and surface areas, and compared log-odds ratios for interface and surface areas. A new scoring method to predict potential functional sites on the protein surface was developed and tested for a new dataset of 21 protein complexes, which were not included in the original training dataset. Empirically we found that the algorithm achieves a good balance in the accuracy of precision and sensitivity by selecting the top eight highest scoring clusters as interface regions. The performance of the method is illustrated for a dimeric ATPase of the hyperthermophile, Methanococcus jannaschii, and the capsid protein of Human Hepatitis B virus. An automated version of the method can be accessed from our web server at http://curie.utmb.edu/prosurf.html.

Spatial chemical conservation of hot spot interactions in protein-protein complexes

Background

Conservation of the spatial binding organizations at the level of physico-chemical interactions is important for the formation and stability of protein-protein complexes as well as protein and drug design. Due to the lack of computational tools for recognition of spatial patterns of interactions shared by a set of protein-protein complexes, the conservation of such interactions has not been addressed previously.

Results

We performed extensive spatial comparisons of physico-chemical interactions common to different types of protein-protein complexes. We observed that 80% of these interactions correspond to known hot spots. Moreover, we show that spatially conserved interactions allow prediction of hot spots with a success rate higher than obtained by methods based on sequence or backbone similarity. Detection of spatially conserved interaction patterns was performed by our novel MAPPIS algorithm. MAPPIS performs multiple alignments of the physico-chemical interactions and the binding properties in three dimensional space. It is independent of the overall similarity in the protein sequences, folds or amino acid identities. We present examples of interactions shared between complexes of colicins with immunity proteins, serine proteases with inhibitors and T-cell receptors with superantigens. We unravel previously overlooked similarities, such as the interactions shared by the structurally different RNase-inhibitor families.

Conclusion

The key contribution of MAPPIS is in discovering the 3D patterns of physico-chemical interactions. The detected patterns describe the conserved binding organizations that involve energetically important hot spot residues and are crucial for the protein-protein associations.

Characterization of protomer interfaces in HslV protease; the bacterial homologue of 20S proteasome

HslVU, a two-component proteasome-related prokaryotic system is composed of HslV protease and HslU ATPase. HslV protomers assemble in a dodecamer of two-stacked hexameric rings that form a complex with HslU hexamers. The intra- and inter-ring protomer interfaces in the HslV dodecamer underpin the integrity and functionality of HslVU. Structural characterization of HslV from different bacteria illustrated considerable differences in interacting residues, accessible surface and gap volumes at the intra-ring interface that is primarily stabilized by polar interactions. Amino acid residues Lys28, Arg83 and Asp111 have envisaged as hot spots at this HslU-interacting interface. The inter-ring interfaces that are made up of side chain packing of hydrophobic residues are structurally conserved. Hyperthermostable bacterium T. maritima HslV has extensively networked polar/nonpolar interactions and highly packed environment at all interfaces. Present data demonstrates that HslV protomer interfaces perform distinct functions; whereas intra-ring interface participates in HslV:HslU interaction resulting in allosteric activation of HslV protease by HslU, the inter-ring interfaces uphold the oligomeric form of HslV.

Protein-protein interaction hotspots carved into sequences

Protein-protein interactions, a key to almost any biological process, are mediated by molecular mechanisms that are not entirely clear. The study of these mechanisms often focuses on all residues at protein-protein interfaces. However, only a small subset of all interface residues is actually essential for recognition or binding. Commonly referred to as "hotspots," these essential residues are defined as residues that impede protein-protein interactions if mutated. While no in silico tool identifies hotspots in unbound chains, numerous prediction methods were designed to identify all the residues in a protein that are likely to be a part of protein-protein interfaces. These methods typically identify successfully only a small fraction of all interface residues. Here, we analyzed the hypothesis that the two subsets correspond (i.e., that in silico methods may predict few residues because they preferentially predict hotspots). We demonstrate that this is indeed the case and that we can therefore predict directly from the sequence of a single protein which residues are interaction hotspots (without knowledge of the interaction partner). Our results suggested that most protein complexes are stabilized by similar basic principles. The ability to accurately and efficiently identify hotspots from sequence enables the annotation and analysis of protein-protein interaction hotspots in entire organisms and thus may benefit function prediction and drug development. The server for prediction is available at http://www.rostlab.org/services/isis.

RRM Proteins Interacting with the Cap Region of Topoisomerase I

RNA recognition motif (RRM) domains bind both nucleic acids and proteins. Several proteins that contain two closely spaced RRM domains were previously found in protein complexes formed by the cap region of human topoisomerase I, a nuclear enzyme responsible for DNA relaxation or phosphorylation of SR splicing proteins. To obtain molecular insight into specific interactions between the RRM proteins and the cap region of topo I we examined their binary interactions using the yeast two-hybrid system. The interactions were established for hnRNP A1, p54(nrb) and SF2/ASF, but not for hnRNP L or HuR. To identify the amino acid pattern responsible for binding, experimental mutagenesis was employed and computational modelling of these processes was carried out. These studies revealed that two RRM domains and six residues of the consensus sequence are required for the binding to the cap region. On the basis of the above data, a structural model for the hnRNP A1-topoisomerase I complex was proposed. The main component of the hnRNP A1 binding site is a hydrophobic pocket on the beta-surface of the first RRM domain, similar to that described for Y14 protein interacting with Mago. We demonstrated that the interaction between RRM domains and the cap region was important for the kinase reaction catalyzed by topoisomerase I. Together with the previously described inhibitory effect of RRM domains of SF2/ASF on DNA cleavage, the above suggests that the binding of RRM proteins could regulate the activity of topoisomerase I.

EhPAK2, a novel p21-activated kinase, is required for collagen invasion and capping in Entamoeba histolytica

p21-activated kinases (PAKs) are a highly conserved family of enzymes that are activated by Rho GTPases. All PAKs contain an N-terminal Cdc42/Rac interacting binding (CRIB) domain, which confers binding to these GTPases, and a C-terminal kinase domain. In addition, some PAKs such as Cla4p, Skm1p and Pak2p contain an N-terminal pleckstrin homology (PH) domain and form a distinct group of PAK proteins involved in cell morphology, cell-cycle and gene transcription. Here, we describe a novel p21-activated kinase, denominated EhPAK2, on the parasitic protozoan Entamoeba histolytica. This is the first reported Entamoeba PAK member that contains a N-terminal PH domain and a highly conserved CRIB domain. EhPAK2 CRIB domain shares 29% of amino acid identity and 53% of amino acid homology with these of DdPAKC from Dictyostelium discoideum and Cla4p from Saccharomyces cerevisiae and binds in vitro and in vivo to EhRacA GTPase. This domain also possesses the conserved residues His123, Phe134 and Trp141, which are important for the interaction with the effector loop and strand beta2 of the GTPase; and the residues Met121 and Phe145, which are specific for the interaction of EhPAK2 with EhRacA. Functional studies of EhPAK2 showed that its C-terminal kinase domain had activity toward myelin basic protein. Cellular studies showed that Entamoeba trophozoites transfected with the vector pExEhNeo/kinase-myc, had a 90% decrease in the ability to invade a collagen matrix as well as severe defects in capping, suggesting the involvement of EhPAK2 in these cellular processes.

From monomeric to homodimeric endonucleases and back: engineering novel specificity of LAGLIDADG enzymes

Monomeric homing endonucleases of the LAGLIDADG family recognize DNA in a bipartite manner, reflecting the underlying structural assembly of two protein domains (A and B) related by pseudo 2-fold symmetry. This architecture allows for changes in DNA specificity via the distinct combination of these half-site domains. The key to engineering such hybrid proteins lies in the LAGLIDADG two-helix bundle that forms both the domain interface and the endonuclease active site. In this study, we utilize domain A of the monomeric I-DmoI to demonstrate the feasibility of generating functional homodimeric endonucleases that recognize palindromic DNA sequences derived from the original, non-palindromic target. Wild-type I-DmoI domain A is capable of forming a homodimer (H-DmoA) that binds tightly to, but does not cleave efficiently, its anticipated DNA target. Partial restoration of DNA cleavage ability was obtained by re-engineering the LAGLIDADG dimerization interface (H-DmoC). Upon fusing two copies of H-DmoC via a short peptide linker, a novel, site-specific DNA endonuclease was created (H-DmoC2). Like I-DmoI, H-DmoC2 is thermostable and cleaves the new target DNA to generate the predicted 4 nt 3'-OH overhangs but, unlike I-DmoI, H-DmoC2 retains stringent cleavage specificity when substituting Mn2+ for Mg2+ as co-factor. This novel endonuclease allows speculation regarding specificity of monomeric LAGLIDADG proteins, while it supports the evolutionary genesis of these proteins by a gene duplication event.

Molecular simulation of the binding of nerve growth factor peptide mimics to the receptor tyrosine kinase A

Nerve growth factor (NGF) mimics play an important role for therapies that target the receptor tyrosine kinase A (trkA). The N-terminal fragment of the NGF (N-term@NGF) was previously demonstrated to be an important determinant for affinity and specificity in the binding to trkA. Here we use a variety of computational tools (contact surface analysis and free energy predictions) to identify residues playing a key role for the binding to the receptor. Molecular dynamics simulations are then used to investigate the stability of complexes between trkA and peptides mimicking N-term@NGF. Steered molecular dynamics calculations are finally performed to investigate the process of detaching the peptide from the receptor. Three disruptive events are observed, the first involving the breaking of all intermolecular interactions except two salt bridges, which break subsequently.

Identification of hot spot residues at protein-protein interface

It is known that binding free energy of protein-protein interaction is mainly contributed by hot spot (high energy) interface residues. Here, we investigate the characteristics of hot spots by examining inter-atomic sidechain-sidechain interactions using a dataset of 296 alanine-mutated interface residues. Results show that hot spots participate in strong and energetically favorable sidechain-sidechain interactions. Subsequently, we describe a novel, yet simple 'hot spot' prediction model with an accuracy that is similar to many available approaches. The model is also shown to efficiently distinguish specific protein-protein interactions from non-specific interactions.

High-resolution protein-protein docking

The high-resolution prediction of protein-protein docking can now create structures with atomic-level accuracy. This progress arises from both improvements in the rapid sampling of conformations and increased accuracy of binding free energy calculations. Consequently, the quality of models submitted to the blind prediction challenge CAPRI (Critical Assessment of PRedicted Interactions) has steadily increased, including complexes predicted from homology structures of one binding partner and complexes with atomic accuracy at the interface. By exploiting experimental information, docking has created model structures for real applications, even when confronted with challenges such as moving backbones and uncertain monomer structures. Work remains to be done in docking large or flexible proteins, ranking models consistently, and producing models accurate enough to allow computational design of higher affinities or specificities.

Molecular insight into pseudolysin inhibition using the MM-PBSA and LIE methods

Pseudolysin, the extracellullar elastase of Pseudomonas aeruginosa (EC: 3.4.24.26) plays an important role in the pathogenesis of P. aeruginosa infections. In the present study, molecular dynamics simulations and theoretical affinity predictions were used to gain molecular insight into pseudolysin inhibition. Four low molecular weight inhibitors were docked at their putative binding sites and molecular dynamics (MD) simulations were performed for 5.0 ns, and the free energy of binding was calculated by the linear interaction energy method. The number and the contact surface area of stabilizing hydrophobic, aromatic, and hydrogen bonding interactions appears to reflect the affinity differences between the inhibitors. The proteinaceous inhibitor, Streptomyces metalloproteinase inhibitor (SMPI) was docked in three different binding positions and MD simulations were performed for 3.0 ns. The MD trajectories were used for molecular mechanics-Poisson-Boltzmann surface area analysis of the three binding positions. Computational alanine scanning of the average pseudolysin-SMPI complexes after MD revealed residues at the pseudolysin-SMPI interface giving the main contribution to the free energy of binding. The calculations indicated that SMPI interacts with pseudolysin via the rigid active site loop, but that also contact sites outside this loop contribute significantly to the free energy of association.

A Binding Free Energy Hot Spot in the Ankyrin Repeat Protein GABPβ Mediated Protein–Protein Interaction

The frequently observed ankyrin repeat motif represents a structural scaffold evolved for mediating protein-protein interactions. As such, these repeats modulate a diverse range of cellular functions. We thermodynamically characterized the heterodimeric GA-binding protein (GABP) alphabeta complex and focused specifically on the interaction mediated by the ankyrin repeat domain of the GABPbeta. Our isothermal titration calorimetric analysis of the interaction between the GABP subunits determined an association constant (K(A)) of 6.0 x 10(8) M(-1) and that the association is favorably driven by a significant change in enthalpy (DeltaH) and a minor change in entropy (-TDeltaS). A total of 16 GABPbeta interface residues were chosen for alanine scanning mutagenesis. The calorimetrically measured differences in the free energy of binding were compared to computationally calculated values resulting in a correlation coefficient r = 0.71. We identified three spatially contiguous hydrophobic and aromatic residues that form a binding free energy hot spot (DeltaDeltaG > 2.0 kcal/mol). One residue provides structural support to the hot spot residues. Three non-hot spot residues are intermediate contributors (DeltaDeltaG approximately 1.0 kcal/mol) and create a canopy-like structure over the hot spot residues to possibly occlude solvent and orientate the subunits. The remaining interface residues are located peripherally and have weak contributions. Finally, our mutational analysis revealed a significant entropy-enthalpy compensation for this interaction.

Gain and loss of channel function by alanine substitutions in the transmembrane segments of the rat ATP-gated P2X2 receptor

ATP opens ionotropic P2X channels through a process that is poorly understood. We made an array of mutant rat P2X2 channels containing unique alanine substitutions in the transmembrane segments with the goal of identifying possible secondary structure and mapping gating domains in the pore. Alteration of channel function was measured as a change in ATP potency, 2'-3'-O-(4-benzoylbenzoyl)ATP (BzATP) efficacy, and deactivation kinetics. Four mutants (V45A, Y47A, V51A, and D349A) failed to respond to ATP. Seven (H33A, Q37A, I40A, L41A, Y43A, F44A, and I50A) of 22 mutations in the first transmembrane segment (TM1) produced channels with altered potencies, and two mutants (Y43A and F44A) were active in the absence of agonist. The pattern of hits was consistent with a helical secondary structure. In contrast, nine (I328A, P329A, N333A, L338A, T339A, S340A, G342A, G344A, and S345A) of 24 mutations in the second transmembrane segment (TM2) resulted in a change in potency, but no regular pattern of impact was apparent. Many of the same mutations that altered ATP potency also changed the relative efficacy of the partial agonist BzATP. Together, these data suggest that both TM1 and TM2 participate in the conformational changes that occur during receptor activation and help to define domains involved in conformational switching within or near the pore.

Protein structure prediction and analysis using the Robetta server

The Robetta server (http://robetta.bakerlab.org) provides automated tools for protein structure prediction and analysis. For structure prediction, sequences submitted to the server are parsed into putative domains and structural models are generated using either comparative modeling or de novo structure prediction methods. If a confident match to a protein of known structure is found using BLAST, PSI-BLAST, FFAS03 or 3D-Jury, it is used as a template for comparative modeling. If no match is found, structure predictions are made using the de novo Rosetta fragment insertion method. Experimental nuclear magnetic resonance (NMR) constraints data can also be submitted with a query sequence for RosettaNMR de novo structure determination. Other current capabilities include the prediction of the effects of mutations on protein-protein interactions using computational interface alanine scanning. The Rosetta protein design and protein-protein docking methodologies will soon be available through the server as well.