Electrostatically optimized Ras-binding Ral guanine dissociation stimulator mutants increase the rate of association by stabilizing the encounter complex

Energy landscape reshaped by strain-specific mutations underlies epistasis in NS1 evolution of influenza A virus

Elucidating how individual mutations affect the protein energy landscape is crucial for understanding how proteins evolve. However, predicting mutational effects remains challenging because of epistasis—the nonadditive interactions between mutations. Here, we investigate the biophysical mechanism of strain-specific epistasis in the nonstructural protein 1 (NS1) of influenza A viruses (IAVs). We integrate structural, kinetic, thermodynamic, and conformational dynamics analyses of four NS1s of influenza strains that emerged between 1918 and 2004. Although functionally near-neutral, strain-specific NS1 mutations exhibit long-range epistatic interactions with residues at the p85β-binding interface. We reveal that strain-specific mutations reshaped the NS1 energy landscape during evolution. Using NMR spin dynamics, we find that the strain-specific mutations altered the conformational dynamics of the hidden network of tightly packed residues, underlying the evolution of long-range epistasis. This work shows how near-neutral mutations silently alter the biophysical energy landscapes, resulting in diverse background effects during molecular evolution.

Influenza A virus (IAV) nonstructural protein 1 (NS1) is a multifunctional virulence factor that interacts with several host factors such as phosphatidylinositol-3-kinase (PI3K). NS1 binds specifically to the p85β regulatory subunit of PI3K and subsequently activates PI3K signaling. Here, Kim et al. show that functionally near-neutral, strain-specific NS1 mutations lead to variations in binding kinetics to p85β exhibit long-range epistatic interactions. Applying NMR they provide evidence that the structural dynamics of the NS1 hydrophobic core have evolved over time and contributed to epistasis.

Protein-Protein Binding Free Energy Predictions with the MM/PBSA Approach Complemented with the Gaussian-Based Method for Entropy Estimation

Here, we present a Gaussian-based method for estimation of protein-protein binding entropy to augment the molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) method for computational prediction of binding free energy (ΔG). The method is termed f5-MM/PBSA/E, where "E" stands for entropy and f5 for five adjustable parameters. The enthalpy components of ΔG (molecular mechanics, polar and non-polar solvation energies) are computed from a single implicit solvent generalized Born (GB) energy minimized structure of a protein-protein complex, while the binding entropy is computed using independently GB energy minimized unbound and bound structures. It should be emphasized that the f5-MM/PBSA/E method does not use snapshots, just energy minimized structures, and is thus very fast and computationally efficient. The method is trained and benchmarked in 5-fold validation test over a data set consisting of 46 protein-protein binding cases with experimentally determined dissociation constant K _d values. This data set has been used for benchmarking in recently published protein-protein binding studies that apply conventional MM/PBSA and MM/PBSA with an enhanced sampling method. The f5-MM/PBSA/E tested on the same data set achieves similar or better performance than these computationally demanding approaches, making it an excellent choice for high throughput protein-protein binding affinity prediction studies.

Specific inhibition of oncogenic RAS using cell-permeable RAS-binding domains

Oncogenic RAS proteins, common oncogenic drivers in many human cancers, have been refractory to conventional small-molecule and macromolecule inhibitors due to their intracellular localization and the lack of druggable pockets. Here, we present a feasible strategy for designing RAS inhibitors that involves intracellular delivery of RAS-binding domain (RBD), a nanomolar-affinity specific ligand of RAS. Screening of 51 different combinations of RBD and cell-permeable peptides has identified Pen-cRaf-v1 as a cell-permeable pan-RAS inhibitor capable of targeting both G12C and non-G12C RAS mutants. Pen-cRaf-v1 crosses the cell membrane via endocytosis, competitively inhibits RAS-effector interaction, and thereby exerts anticancer activity against several KRAS-mutant cancer cell lines. Moreover, Pen-cRaf-v1 exhibits excellent activity comparable with a leading pan-RAS inhibitor (BI-2852), as well as high target specificity in transcriptome analysis and alanine mutation analysis. These findings demonstrate that specific inhibition of oncogenic RAS, and possibly treatment of RAS-mutant cancer, is feasible by intracellular delivery of RBD.

A comprehensive analysis of RAS-effector interactions reveals interaction hotspots and new binding partners

RAS effectors specifically interact with GTP-bound RAS proteins to link extracellular signals to downstream signaling pathways. These interactions rely on two types of domains, called RAS-binding (RB) and RAS association (RA) domains, which share common structural characteristics. Although the molecular nature of RAS-effector interactions is well-studied for some proteins, most of the RA/RB-domain-containing proteins remain largely uncharacterized. Here, we searched through human proteome databases, extracting 41 RA domains in 39 proteins and 16 RB domains in 14 proteins, each of which can specifically select at least one of the 25 members in the RAS family. We next comprehensively investigated the sequence–structure–function relationship between different representatives of the RAS family, including HRAS, RRAS, RALA, RAP1B, RAP2A, RHEB1, and RIT1, with all members of RA domain family proteins (RASSFs) and the RB-domain-containing CRAF. The binding affinity for RAS-effector interactions, determined using fluorescence polarization, broadly ranged between high (0.3 μM) and very low (500 μM) affinities, raising interesting questions about the consequence of these variable binding affinities in the regulation of signaling events. Sequence and structural alignments pointed to two interaction hotspots in the RA/RB domains, consisting of an average of 19 RAS-binding residues. Moreover, we found novel interactions between RRAS1, RIT1, and RALA and RASSF7, RASSF9, and RASSF1, respectively, which were systematically explored in sequence–structure–property relationship analysis, and validated by mutational analysis. These data provide a set of distinct functional properties and putative biological roles that should now be investigated in the cellular context.

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

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

Quantitative mechanistic model for ultrasmall nanoparticle-protein interactions

To date, extensive effort has been devoted toward the characterization of protein interactions with synthetic nanostructures. However, much remains to be understood, particularly concerning microscopic mechanisms of interactions. Here, we have conducted a detailed investigation of the kinetics of nanoparticle-protein complexation to gain deeper insights into the elementary steps and molecular events along the pathway for complex formation. Toward that end, the binding kinetics between p-mercaptobenzoic acid-coated ultrasmall gold nanoparticles (AuMBA) and fluorescently-labeled ubiquitin was investigated at millisecond time resolution using stopped-flow spectroscopy. It was found that both the association and dissociation kinetics consisted of multiple exponential phases, hence suggesting a complex, multi-step reaction mechanism. The results fit into a picture where complexation proceeds through the formation of a weakly-bound first-encounter complex with an apparent binding affinity (KD) of ∼9 μM. Encounter complex formation is followed by unimolecular tightening steps of partial desolvation/ion removal and conformational rearrangement, which, collectively, achieve an almost 100-fold increase in affinity of the final bound state (apparent KD ∼0.1 μM). The final state is found to be weakly stabilized, displaying an average lifetime in the range of seconds. Screening of the electrostatic forces at high ionic strength weakens the AuMBA-ubiquitin interactions by destabilizing the encounter complex, whereas the average lifetime of the final bound state remains largely unchanged. Overall, our rapid kinetics investigation has revealed novel quantitative insights into the molecular-level mechanisms of ultrasmall nanoparticle-protein interactions.

ProAffiMuSeq: sequence-based method to predict the binding free energy change of protein-protein complexes upon mutation using functional classification

MOTIVATION

Protein-protein interactions are essential for the cell and mediate various functions. However, mutations can disrupt these interactions and may cause diseases. Currently available computational methods require a complex structure as input for predicting the change in binding affinity. Further, they have not included the functional class information for the protein-protein complex. To address this, we have developed a method, ProAffiMuSeq, which predicts the change in binding free energy using sequence-based features and functional class.

RESULTS

Our method shows an average correlation between predicted and experimentally determined ΔΔG of 0.73 and mean absolute error (MAE) of 0.86 kcal/mol in 10-fold cross-validation and correlation of 0.75 with MAE of 0.94 kcal/mol in the test dataset. ProAffiMuSeq was also tested on an external validation set and showed results comparable to structure-based methods. Our method can be used for large-scale analysis of disease-causing mutations in protein-protein complexes without structural information.

AVAILABILITY AND IMPLEMENTATION

Users can access the method at https://web.iitm.ac.in/bioinfo2/proaffimuseq/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A De novo Peptide from a High Throughput Peptide Library Blocks Myosin A -MTIP Complex Formation in Plasmodium falciparum

Apicomplexan parasites, through their motor machinery, produce the required propulsive force critical for host cell-entry. The conserved components of this so-called glideosome machinery are myosin A and myosin A Tail Interacting Protein (MTIP). MTIP tethers myosin A to the inner membrane complex of the parasite through 20 amino acid-long C-terminal end of myosin A that makes direct contacts with MTIP, allowing the invasion of Plasmodium falciparum in erythrocytes. Here, we discovered through screening a peptide library, a de-novo peptide ZA1 that binds the myosin A tail domain. We demonstrated that ZA1 bound strongly to myosin A tail and was able to disrupt the native myosin A tail MTIP complex both in vitro and in vivo. We then showed that a shortened peptide derived from ZA1, named ZA1S, was able to bind myosin A and block parasite invasion. Overall, our study identified a novel anti-malarial peptide that could be used in combination with other antimalarials for blocking the invasion of Plasmodium falciparum.

Insights revealed by the co-crystal structure of the Saccharomyces cerevisiae histidine phosphotransfer protein Ypd1 and the receiver domain of its downstream response regulator Ssk1

Two‐component signaling systems are the primary means by which bacteria, archaea, and certain plants and fungi react to their environments. The model yeast, Saccharomyces cerevisiae, uses the Sln1 signaling pathway to respond to hyperosmotic stress. This pathway contains a hybrid histidine kinase (Sln1) that autophosphorylates and transfers a phosphoryl group to its own receiver domain (R1). The phosphoryl group is then transferred to a histidine phosphotransfer protein (Ypd1) that finally passes it to the receiver domain (R2) of a downstream response regulator (Ssk1). Under normal conditions, Ssk1 is constitutively and preferentially phosphorylated in the phosphorelay. Upon detecting hyperosmotic stress, Ssk1 rapidly dephosphorylates and activates the high‐osmolarity glycerol (HOG) pathway, initiating a response. Despite their distinct physiological roles, both Sln1 and Ssk1 bind to Ypd1 at a common docking site. Co‐crystal structures of response regulators in complex with their phosphorelay partners are scarce, leaving many mechanistic and structural details uncharacterized for systems like the Sln1 pathway. In this work, we present the co‐crystal structure of Ypd1 and a near wild‐type variant of the receiver domain of Ssk1 (Ssk1‐R2‐W638A) at a resolution of 2.80 Å. Our structural analyses of Ypd1‐receiver domain complexes, biochemical determination of binding affinities for Ssk1‐R2 variants, in silico free energy estimates, and sequence comparisons reveal distinctive electrostatic properties of the Ypd1/Ssk1‐R2‐W638A complex that may provide insight into the regulation of the Sln1 pathway as a function of dynamic osmolyte concentration.

Potential Regulatory Role of Competitive Encounter Complexes in Paralogous Phosphotransferase Systems

There are two paralogous Escherichia coli phosphotransferase systems, one for sugar import (PTS^sugar) and one for nitrogen regulation (PTS^Ntr), that utilize proteins enzyme I^sugar (EI^sugar) and HPr, and enzyme I^Ntr (EI^Ntr) and NPr, respectively. The enzyme I proteins have similar folds, as do their substrates HPr and NPr, yet they show strict specificity for their cognate partner both in stereospecific protein-protein complex formation and in reversible phosphotransfer. Here, we investigate the mechanism of specific EI^Ntr:NPr complex formation by the study of transient encounter complexes. NMR paramagnetic relaxation enhancement experiments demonstrated transient encounter complexes of EI^Ntr not only with the expected partner, NPr, but also with the unexpected partner, HPr. HPr occupies transient sites on EI^Ntr but is unable to complete stereospecific complex formation. By occupying the non-productive transient sites, HPr promotes NPr transient interaction to productive sites closer to the stereospecific binding site and actually enhances specific complex formation between NPr and EI^Ntr. The cellular level of HPr is approximately 150 times higher than that of NPr. Thus, our finding suggests a potential mechanism for cross-regulation of enzyme activity through formation of competitive encounter complexes.

Mapping Transient Protein Interactions at the Nanoscale in Living Mammalian Cells

Protein-protein interactions (PPIs) form the basis of cellular processes, regulating cell behavior and fate. PPIs can be extremely transient in nature, which hinders their detection. In addition, traditional biochemical methods provided limited information on the spatial distribution and temporal dynamics of PPIs that is crucial for their regulation in the crowded cellular environment. Given the pivotal role of membrane micro- and nanodomains in the regulation of PPIs at the plasma membrane, the development of methods to visualize PPIs with a high spatial resolution is imperative. Here, we present a super-resolution fluorescence microscopy technique that can detect and map short-lived transient protein-protein interactions on a nanometer scale in the cellular environment. This imaging method is based on single-molecule fluorescence microscopy and exploits the effect of the difference in the mobility between cytosolic and membrane-bound proteins in the recorded fluorescence signals. After the development of the proof of concept using a model system based on membrane-bound modular protein domains and fluorescently labeled peptides, we applied this imaging approach to investigate the interactions of cytosolic proteins involved in the epidermal growth factor signaling pathway (namely, Grb2, c-Raf, and PLCγ1). The detected clusters of Grb2 and c-Raf were correlated with the distribution of the receptor at the plasma membrane. Additionally, the interactions of wild type PLCγ1 were compared with those detected with truncated mutants, which provided important information regarding the role played by specific domains in the interaction with the membrane. The results presented here demonstrate the potential of this technique to unravel the role of membrane heterogeneity in the spatiotemporal regulation of cell signaling.

The Impairment of TorsinA's Binding to and Interactions With Its Activator: An Atomistic Molecular Dynamics Study of Primary Dystonia

Primary dystonia's prolonged muscle contractions and the associated abnormal postures and twisting movements remain incurable. Genetic mutation/deletion of GAG from TorsonA's gene resulting in ΔE303 (which weakens the binding between TorsinA and its activator, such as LULL1) primarily cause this neurodegenerative disorder. We studied TorsinA-LULL1 (or TorsinAΔE303-LULL1) bindings and interactions. For the first time, we show the atomic details of TorsinA-LULL1 dynamic interactions and TorsinAΔE303-LULL1 dynamic interactions and their binding affinities. Our results show extensive effects of ΔE303 on TorsinAΔE303-LULL1 interactions, and suggest that the differences between TorsinA-LULL1 interactions and TorsinAΔE303-LULL1 interactions are non-subtle. ΔE303 significantly weakens TorsinAΔE303-LULL1's binding affinity. We present pieces of evidence proving that the effects of ΔE303 (on the differences between TorsinA-LULL1 interactions and TorsinAΔE303-LULL1 interactions) are more pronounced than previously suggested, and that the nanobody used for achieving the X-ray crystallization in the previous study attenuated the differences between TorsinA-LULL1 and TorsinAΔE303-LULL1 interactions. Our accounts of the dynamic interactions between “TorsinA and LULL1” and between “TorsinAΔE303 and LULL1” and the detailed effects of ΔE303 on TorsinA-/TorsinAΔE303-LULL1 build on previous findings and offer new insights for a better understanding of the molecular basis of Primary Dystonia. Our results have long-term potentials of guiding the development of medications for the disease.

Antibody Affinity Maturation by Computational Design

The immune systems protect our bodies from foreign molecules or antigens, where antibodies play important roles. Antibodies evolve over time upon antigen encounter by somatically mutating their genome sequences. The end result is a series of antibodies that display higher affinities and specificities to specific antigens. This process is called affinity maturation. Recent improvements in computer hardware and modeling algorithms now enable the rational design of protein structures and functions, and several works on computer-aided antibody design have been published. In this chapter, we briefly describe computational methods for antibody affinity maturation, focusing on methods for sampling antibody conformations and for scoring designed antibody variants. We also discuss lessons learned from the successful computer-aided design of antibodies.

Interaction Dynamics Determine Signaling and Output Pathway Responses

The understanding of interaction dynamics in signaling pathways can shed light on pathway architecture and provide insights into targets for intervention. Here, we explored the relevance of kinetic rate constants of a key upstream osmosensor in the yeast high-osmolarity glycerol-mitogen-activated protein kinase (HOG-MAPK) pathway to signaling output responses. We created mutant pairs of the Sln1-Ypd1 complex interface that caused major compensating changes in the association (k_on) and dissociation (k_off) rate constants (kinetic perturbations) but only moderate changes in the overall complex affinity (K_d). Yeast cells carrying a Sln1-Ypd1 mutant pair with moderate increases in k_on and k_off displayed a lower threshold of HOG pathway activation than wild-type cells. Mutants with higher k_on and k_off rates gave rise to higher basal signaling and gene expression but impaired osmoadaptation. Thus, the k_on and k_off rates of the components in the Sln1 osmosensor determine proper signaling dynamics and osmoadaptation.

The ATAD2 bromodomain binds different acetylation marks on the histone H4 in similar fuzzy complexes

Bromodomains are protein modules adopting conserved helix bundle folds. Some bromodomain-containing proteins, such as ATPase family AAA domain-containing protein 2 (ATAD2), isoform A, have attracted much interest because they are overexpressed in many types of cancer. Bromodomains bind to acetylated lysine residues on histone tails and thereby facilitate the reading of the histone code. Epigenetic regulators in general have been implicated as indicators, mediators, or causes of a large number of diseases and disorders. To interfere with or modulate these processes, it is therefore of fundamental interest to understand the molecular mechanisms by which epigenetic regulation occurs. Here, we present results from molecular dynamics simulations of a doubly acetylated histone H4 peptide bound to the bromodomain of ATAD2 (hereafter referred to as ATAD2A). These simulations revealed how the flexibility of ATAD2A's major loop, the so-called ZA loop, creates an adaptable interface that preserves the disorder of both peptide and loop in the bound state. We further demonstrate that the binding involves an almost identical average pattern of interactions irrespective of which acetyl mark is inserted into the pocket. In conjunction with a likely mechanism of electrostatically driven recruitment, our simulation results highlight how the bromodomain is built toward promiscuous binding with low specificity. In conclusion, the simulations indicate that disorder and electrostatic steering function jointly to recruit ATAD2A to the histone core and that these fuzzy interactions may promote cooperativity between nearby epigenetic marks.

Kinetic characterization of apoptotic Ras signaling through Nore1-MST1 complex formation

Ras-mediated apoptotic signaling is expected to be mediated via Rassf-MST complexes, but the system has been poorly characterized in vitro until now. Here we demonstrate that active H-Ras, Nore1A and MST1 form a stable ternary complex in vitro without other external factors, Nore1A interacting simultaneously with H-Ras and MST1 via its RBD and SARAH domain, respectively. Moreover, our data show for the first time that the SARAH domain of Nore1A plays a role in the Nore1A binding to H-Ras. Finally, we analyze the relation between the electrostatic and hydrophobic forces and kinetic constants of the Nore1A - H-Ras complex.

Accelerating the Association of the Most Stable Protein-Ligand Complex by More than Two Orders of Magnitude

The complex between the bacterial type 1 pilus subunit FimG and the peptide corresponding to the N-terminal extension (termed donor strand, Ds) of the partner subunit FimF (DsF) shows the strongest reported noncovalent molecular interaction, with a dissociation constant (KD ) of 1.5×10(-20)  m. However, the complex only exhibits a slow association rate of 330 m(-1)  s(-1) that limits technical applications, such as its use in affinity purification. Herein, a structure-based approach was used to design pairs of FimGt (a FimG variant lacking its own N-terminal extension) and DsF variants with enhanced electrostatic surface complementarity. Association of the best mutant FimGt/DsF pairs was accelerated by more than two orders of magnitude, while the dissociation rates and 3D structures of the improved complexes remained essentially unperturbed. A KD  value of 8.8×10(-22)  m was obtained for the best mutant complex, which is the lowest value reported to date for a protein/ligand complex.

Ras Conformational Ensembles, Allostery, and Signaling

Ras proteins are classical members of small GTPases that function as molecular switches by alternating between inactive GDP-bound and active GTP-bound states. Ras activation is regulated by guanine nucleotide exchange factors that catalyze the exchange of GDP by GTP, and inactivation is terminated by GTPase-activating proteins that accelerate the intrinsic GTP hydrolysis rate by orders of magnitude. In this review, we focus on data that have accumulated over the past few years pertaining to the conformational ensembles and the allosteric regulation of Ras proteins and their interpretation from our conformational landscape standpoint. The Ras ensemble embodies all states, including the ligand-bound conformations, the activated (or inactivated) allosteric modulated states, post-translationally modified states, mutational states, transition states, and nonfunctional states serving as a reservoir for emerging functions. The ensemble is shifted by distinct mutational events, cofactors, post-translational modifications, and different membrane compositions. A better understanding of Ras biology can contribute to therapeutic strategies.

Evidence for Functionally Relevant Encounter Complexes in Nitrogenase Catalysis

Nitrogenase is the only enzyme that can convert atmospheric dinitrogen (N2) into biologically usable ammonia (NH3). To achieve this multielectron redox process, the nitrogenase component proteins, MoFe-protein (MoFeP) and Fe-protein (FeP), repeatedly associate and dissociate in an ATP-dependent manner, where one electron is transferred from FeP to MoFeP per association. Here, we provide experimental evidence that encounter complexes between FeP and MoFeP play a functional role in nitrogenase catalysis. The encounter complexes are stabilized by electrostatic interactions involving a positively charged patch on the β-subunit of MoFeP. Three single mutations (βAsn399Glu, βLys400Glu, and βArg401Glu) in this patch were generated in Azotobacter vinelandii MoFeP. All of the resulting variants displayed decreases in specific catalytic activity, with the βK400E mutation showing the largest effect. As simulated by the Thorneley-Lowe kinetic scheme, this single mutation lowered the rate constant for FeP-MoFeP association 5-fold. We also found that the βK400E mutation did not affect the coupling of ATP hydrolysis with electron transfer (ET) between FeP and MoFeP. These data suggest a mechanism where FeP initially forms encounter complexes on the MoFeP β-subunit surface en route to the ATP-activated, ET-competent complex over the αβ-interface.

Binding properties of SUMO-interacting motifs (SIMs) in yeast

Small ubiquitin-like modifier (SUMO) conjugation and interaction play an essential role in many cellular processes. A large number of yeast proteins is known to interact non-covalently with SUMO via short SUMO-interacting motifs (SIMs), but the structural details of this interaction are yet poorly characterized. In the present work, sequence analysis of a large dataset of 148 yeast SIMs revealed the existence of a hydrophobic core binding motif and a preference for acidic residues either within or adjacent to the core motif. Thus the sequence properties of yeast SIMs are highly similar to those described for human. Molecular dynamics simulations were performed to investigate the binding preferences for four representative SIM peptides differing in the number and distribution of acidic residues. Furthermore, the relative stability of two previously observed alternative binding orientations (parallel, antiparallel) was assessed. For all SIMs investigated, the antiparallel binding mode remained stable in the simulations and the SIMs were tightly bound via their hydrophobic core residues supplemented by polar interactions of the acidic residues. In contrary, the stability of the parallel binding mode is more dependent on the sequence features of the SIM motif like the number and position of acidic residues or the presence of additional adjacent interaction motifs. This information should be helpful to enhance the prediction of SIMs and their binding properties in different organisms to facilitate the reconstruction of the SUMO interactome.

Deciphering the mechanisms of binding induced folding at nearly atomic resolution: The Φ value analysis applied to IDPs

The Φ value analysis is a method to analyze the structure of metastable states in reaction pathways. Such a methodology is based on the quantitative analysis of the effect of point mutations on the kinetics and thermodynamics of the probed reaction. The Φ value analysis is routinely used in protein folding studies and is potentially an extremely powerful tool to analyze the mechanism of binding induced folding of intrinsically disordered proteins. In this review we recapitulate the key equations and experimental advices to perform the Φ value analysis in the perspective of the possible caveats arising in intrinsically disordered systems. Finally, we briefly discuss some few examples already available in the literature.

The transition state structure for coupled binding and folding of disordered protein domains

Intrinsically disordered proteins are abundant in the eukaryotic proteome, and they are implicated in a range of different diseases. However, there is a paucity of experimental data on molecular details of the coupled binding and folding of such proteins. Two interacting and relatively well studied disordered protein domains are the activation domain from the p160 transcriptional co-activator ACTR and the nuclear co-activator binding domain (NCBD) of CREB binding protein. We have analyzed the transition state for their coupled binding and folding by protein engineering and kinetic experiments (Φ-value analysis) and found that it involves weak native interactions between the N-terminal helices of ACTR and NCBD, but is otherwise "disordered-like". Most native hydrophobic interactions in the interface between the two domains form later, after the rate-limiting barrier for association. Linear free energy relationships suggest a cooperative formation of native interactions, reminiscent of the nucleation-condensation mechanism in protein folding.

Mechanism of E-cadherin dimerization probed by NMR relaxation dispersion

Epithelial cadherin (E-cadherin), a member of the classical cadherin family, mediates calcium-dependent homophilic cell-cell adhesion. Crystal structures of classical cadherins reveal an adhesive dimer interface featuring reciprocal exchange of N-terminal β-strands between two protomers. Previous work has identified a putative intermediate (called the "X-dimer") in the dimerization pathway of wild-type E-cadherin EC1-EC2 domains, based on crystal structures of mutants not capable of strand swapping and on deceleration of binding kinetics by mutations at the X-dimer interface. In the present work, NMR relaxation dispersion spectroscopy is used to directly observe and characterize intermediate states without the need to disrupt the strand-swapped binding interface by mutagenesis. The results indicate that E-cadherin forms strand-swapped dimers predominantly by a mechanism in which formation of a weak and short-lived X-dimer-like state precedes the conformational changes required for formation of the mature strand-swapped dimeric structure. Disruption of this intermediate state through mutation reduces both association and dissociation rates by factors of ~10(4), while minimally perturbing affinity. The X-dimer interface lowers the energy barrier associated with strand swapping and enables E-cadherins to form strand-swapped dimers at a rate consistent with residence times in adherens junctions.

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

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

Structural basis for the interaction of the adaptor protein grb14 with activated ras

Grb14, a member of the Grb7-10-14 family of cytoplasmic adaptor proteins, is a tissue-specific negative regulator of insulin signaling. Grb7-10-14 contain several signaling modules, including a Ras-associating (RA) domain, a pleckstrin-homology (PH) domain, a family-specific BPS (between PH and SH2) region, and a C-terminal Src-homology-2 (SH2) domain. We showed previously that the RA and PH domains, along with the BPS region and SH2 domain, are necessary for downregulation of insulin signaling. Here, we report the crystal structure at 2.4-Å resolution of the Grb14 RA and PH domains in complex with GTP-loaded H-Ras (G12V). The structure reveals that the Grb14 RA and PH domains form an integrated structural unit capable of binding simultaneously to small GTPases and phosphoinositide lipids. The overall mode of binding of the Grb14 RA domain to activated H-Ras is similar to that of the RA domains of RalGDS and Raf1 but with important distinctions. The integrated RA-PH structural unit in Grb7-10-14 is also found in a second adaptor family that includes Rap1-interacting adaptor molecule (RIAM) and lamellipodin, proteins involved in actin-cytoskeleton rearrangement. The structure of Grb14 RA-PH in complex with H-Ras represents the first detailed molecular characterization of tandem RA-PH domains bound to a small GTPase and provides insights into the molecular basis for specificity.

Real-time single-molecule co-immunoprecipitation analyses reveal cancer-specific Ras signalling dynamics

Co-immunoprecipitation (co-IP) has become a standard technique, but its protein-band output provides only static, qualitative information about protein–protein interactions. Here we demonstrate a real-time single-molecule co-IP technique that generates real-time videos of individual protein–protein interactions as they occur in unpurified cell extracts. By analysing single Ras–Raf interactions with a 50-ms time resolution, we have observed transient intermediates of the protein–protein interaction and determined all the essential kinetic rates. Using this technique, we have quantified the active fraction of native Ras proteins in xenograft tumours, normal tissue and cancer cell lines. We demonstrate that the oncogenic Ras mutations selectively increase the active-Ras fraction by one order of magnitude, without affecting total Ras levels or single-molecule signalling kinetics. Our approach allows us to probe the previously hidden, dynamic aspects of weak protein–protein interactions. It also suggests a path forward towards precision molecular diagnostics at the protein–protein interaction level.

Co-immunoprecipitation provides static and qualitative information about protein–protein interactions. Lee et al. create real-time movies of single protein–protein interactions during co-immunoprecipitation, and use them to assess the dynamics of mutant Ras proteins derived from tumours.

Comparative analysis of interactions of RASSF1-10

Members of the RASSF family (RASSF1-10) have been identified as candidate tumour suppressors that are frequently downregulated by promoter hypermethylation in cancers. These proteins carry a common Ras-association (RA) and SARAH domain (RASSF1-6) that can potentially bind Ras oncoproteins and mediate protein-protein interactions with other SARAH domain proteins. However, there is a notable lack of comparative characterisation of the RASSF family, as well as molecular and structural information that facilitate their tumour suppressive functions. As part of our comparative analysis, we modelled the RA and SARAH domains of the RASSF members based on existing structures and predicted their potential interactions. These in silico predictions were compared to in vitro interaction studies with Ras and MST kinase (a SARAH domain-containing protein). Our data shows a diversity of interaction within the RASSF family RA domain, whereas the SARAH domain-mediated interactions for RASSF1-6 are consistent with the predictions. This suggests that different members, despite shared general architecture, could have distinct functional properties. Additionally, we identify a new interacting partner for MST kinase in the form of RASSF7. Current data supports an interaction model where RASSF serves as an adaptor for the assembly of multiple protein complexes and further functional interactions, involving MST kinases and other SARAH domain proteins, which could be regulated by Ras.

Predicting permanent and transient protein-protein interfaces

Protein-protein interactions (PPIs) are involved in diverse functions in a cell. To optimize functional roles of interactions, proteins interact with a spectrum of binding affinities. Interactions are conventionally classified into permanent and transient, where the former denotes tight binding between proteins that result in strong complexes, whereas the latter compose of relatively weak interactions that can dissociate after binding to regulate functional activity at specific time point. Knowing the type of interactions has significant implications for understanding the nature and function of PPIs. In this study, we constructed amino acid substitution models that capture mutation patterns at permanent and transient type of protein interfaces, which were found to be different with statistical significance. Using the substitution models, we developed a novel computational method that predicts permanent and transient protein binding interfaces (PBIs) in protein surfaces. Without knowledge of the interacting partner, the method uses a single query protein structure and a multiple sequence alignment of the sequence family. Using a large dataset of permanent and transient proteins, we show that our method, BindML+, performs very well in protein interface classification. A very high area under the curve (AUC) value of 0.957 was observed when predicted protein binding sites were classified. Remarkably, near prefect accuracy was achieved with an AUC of 0.991 when actual binding sites were classified. The developed method will be also useful for protein design of permanent and transient PBIs.

Contrasting factors on the kinetic path to protein complex formation diminish the effects of crowding agents

The crowded environment of cells poses a challenge for rapid protein-protein association. Yet, it has been established that the rates of association are similar in crowded and in dilute solutions. Here we probe the pathway leading to fast association between TEM1 β-lactamase and its inhibitor protein BLIP in crowded solutions. We show that the affinity of the encounter complex, the rate of final complex formation, and the structure of the transition state are similar in crowded solutions and in buffer. The experimental results were reproduced by calculations based on the transient-complex theory for protein association. Both experiments and calculations suggest that while crowding agents decrease the diffusion constant of the associating proteins, they also induce an effective excluded-volume attraction between them. The combination of the two opposing effects thus results in nearly identical overall association rates in diluted and crowded solutions.

Oligomerization of rab/effector complexes in the regulation of vesicle trafficking

Rabs comprise the largest member of the Ras superfamily of small GTPases with over 60 proteins in mammals and 11 proteins in yeast. Like all small GTPases, Rabs oscillate between an inactive GDP-bound conformation and an active GTP-bound state that is tethered to lipid membranes via a C-terminal prenylation site on conserved cysteine residues. In their active state, Rabs regulate various aspects of membrane trafficking, including vesicle formation, transport, docking, and fusion. The critical element of biological activity is the recruitment of cytosolic effector proteins to specific endomembranes by active Rabs. The importance of Rabs in cellular processes is apparent from their links to genetic disorders, immunodeficiency, cancer, and pathogen invasion. During the last decade, numerous structures of complexes have shed light on the molecular basis for Rab/effector specificity and their topological organization on subcellular membranes. Here, I review the known structures of Rab/effector complexes and their modes of oligomerization. This is followed by a brief discussion on the thermodynamics of effector recruitment, which has not been documented sufficiently in previous reviews. A summary of diseases associated with Rab/effector trafficking pathways concludes this chapter.

Protein-ligand interactions: fundamentals

Here are described the basic mechanisms governing the interactions between proteins and their natural or manmade ligands, together with the principles underlying their analysis. The consequences of these principles are detailed for the simplest case of one-to-one binding. The general features of experimental measurements of biomolecular interactions arise from properties of the molecules involved and, thus, are common to many methods of detection. Consequently, an understanding of these principles greatly simplifies adoption and comparison of experimental methods and provides the rationale underlying many common protocols. In seeking to understand and interpret the results of experiments or identify possible sources of error these fundamental ideas are a constant guide.

A comparison of successful and failed protein interface designs highlights the challenges of designing buried hydrogen bonds

The accurate design of new protein-protein interactions is a longstanding goal of computational protein design. However, most computationally designed interfaces fail to form experimentally. This investigation compares five previously described successful de novo interface designs with 158 failures. Both sets of proteins were designed with the molecular modeling program Rosetta. Designs were considered a success if a high-resolution crystal structure of the complex closely matched the design model and the equilibrium dissociation constant for binding was less than 10 μM. The successes and failures represent a wide variety of interface types and design goals including heterodimers, homodimers, peptide-protein interactions, one-sided designs (i.e., where only one of the proteins was mutated) and two-sided designs. The most striking feature of the successful designs is that they have fewer polar atoms at their interfaces than many of the failed designs. Designs that attempted to create extensive sets of interface-spanning hydrogen bonds resulted in no detectable binding. In contrast, polar atoms make up more than 40% of the interface area of many natural dimers, and native interfaces often contain extensive hydrogen bonding networks. These results suggest that Rosetta may not be accurately balancing hydrogen bonding and electrostatic energies against desolvation penalties and that design processes may not include sufficient sampling to identify side chains in preordered conformations that can fully satisfy the hydrogen bonding potential of the interface.

Slow, reversible, coupled folding and binding of the spectrin tetramerization domain

Many intrinsically disordered proteins (IDPs) are significantly unstructured under physiological conditions. A number of these IDPs have been shown to undergo coupled folding and binding reactions whereby they can gain structure upon association with an appropriate partner protein. In general, these systems display weaker binding affinities than do systems with association between completely structured domains, with micromolar K(d) values appearing typical. One such system is the association between α- and β-spectrin, where two partially structured, incomplete domains associate to form a fully structured, three-helix bundle, the spectrin tetramerization domain. Here, we use this model system to demonstrate a method for fitting association and dissociation kinetic traces where, using typical biophysical concentrations, the association reactions are expected to be highly reversible. We elucidate the unusually slow, two-state kinetics of spectrin assembly in solution. The advantages of studying kinetics in this regime include the potential for gaining equilibrium constants as well as rate constants, and for performing experiments with low protein concentrations. We suggest that this approach would be particularly appropriate for high-throughput mutational analysis of two-state reversible binding processes.

Structure-based design of supercharged, highly thermoresistant antibodies

Mutation of surface residues to charged amino acids increases resistance to aggregation and can enable reversible unfolding. We have developed a protocol using the Rosetta computational design package that "supercharges" proteins while considering the energetic implications of each mutation. Using a homology model, a single-chain variable fragment antibody was designed that has a markedly enhanced resistance to thermal inactivation and displays an unanticipated ≈30-fold improvement in affinity. Such supercharged antibodies should prove useful for assays in resource-limited settings and for developing reagents with improved shelf lives.

SKEMPI: a Structural Kinetic and Energetic database of Mutant Protein Interactions and its use in empirical models

MOTIVATION

Empirical models for the prediction of how changes in sequence alter protein-protein binding kinetics and thermodynamics can garner insights into many aspects of molecular biology. However, such models require empirical training data and proper validation before they can be widely applied. Previous databases contained few stabilizing mutations and no discussion of their inherent biases or how this impacts model construction or validation.

RESULTS

We present SKEMPI, a database of 3047 binding free energy changes upon mutation assembled from the scientific literature, for protein-protein heterodimeric complexes with experimentally determined structures. This represents over four times more data than previously collected. Changes in 713 association and dissociation rates and 127 enthalpies and entropies were also recorded. The existence of biases towards specific mutations, residues, interfaces, proteins and protein families is discussed in the context of how the data can be used to construct predictive models. Finally, a cross-validation scheme is presented which is capable of estimating the efficacy of derived models on future data in which these biases are not present.

AVAILABILITY

The database is available online at http://life.bsc.es/pid/mutation_database/.

Protein-protein complexation in bioluminescence

In this review we summarize the progress made towards understanding the role of protein-protein interactions in the function of various bioluminescence systems of marine organisms, including bacteria, jellyfish and soft corals, with particular focus on methodology used to detect and characterize these interactions. In some bioluminescence systems, protein-protein interactions involve an "accessory protein" whereby a stored substrate is efficiently delivered to the bioluminescent enzyme luciferase. Other types of complexation mediate energy transfer to an "antenna protein" altering the color and quantum yield of a bioluminescence reaction. Spatial structures of the complexes reveal an important role of electrostatic forces in governing the corresponding weak interactions and define the nature of the interaction surfaces. The most reliable structural model is available for the protein-protein complex of the Ca(2+)-regulated photoprotein clytin and green-fluorescent protein (GFP) from the jellyfish Clytia gregaria, solved by means of Xray crystallography, NMR mapping and molecular docking. This provides an example of the potential strategies in studying the transient complexes involved in bioluminescence. It is emphasized that structural studies such as these can provide valuable insight into the detailed mechanism of bioluminescence.

Rationalizing 5000-fold differences in receptor-binding rate constants of four cytokines

The four cytokines erythropoietin (EPO), interleukin-4 (IL4), human growth hormone (hGH), and prolactin (PRL) all form four-helix bundles and bind to type I cytokine receptors. However, their receptor-binding rate constants span a 5000-fold range. Here, we quantitatively rationalize these vast differences in rate constants by our transient-complex theory for protein-protein association. In the transient complex, the two proteins have near-native separation and relative orientation, but have yet to form the short-range specific interactions of the native complex. The theory predicts the association rate constant as k(a)=k(a0)exp(-ΔG(el)(∗)/k(B)T) where k(a0) is the basal rate constant for reaching the transient complex by random diffusion, and the Boltzmann factor captures the rate enhancement due to electrostatic attraction. We found that the vast differences in receptor-binding rate constants of the four cytokines arise mostly from the differences in charge complementarity among the four cytokine-receptor complexes. The basal rate constants (k(a0)) of EPO, IL4, hGH, and PRL were similar (5.2 × 10(5) M(-1)s(-1), 2.4 × 10(5) M(-1)s(-1), 1.7 × 10(5) M(-1)s(-1), and 1.7 × 10(5) M(-1)s(-1), respectively). However, the average electrostatic free energies (ΔG(e1)(∗)) were very different (-4.2 kcal/mol, -2.4 kcal/mol, -0.1 kcal/mol, and -0.5 kcal/mol, respectively, at ionic strength=160 mM). The receptor-binding rate constants predicted without adjusting any parameters, 6.2 × 10(8) M(-1)s(-1), 1.3 × 10(7) M(-1)s(-1), 2.0 × 10(5) M(-1)s(-1), and 7.6 × 10(4) M(-1)s(-1), respectively, for EPO, IL4, hGH, and PRL agree well with experimental results. We uncover that these diverse rate constants are anticorrelated with the circulation concentrations of the cytokines, with the resulting cytokine-receptor binding rates very close to the limits set by the half-lives of the receptors, suggesting that these binding rates are functionally relevant and perhaps evolutionarily tuned. Our calculations also reproduced well-observed effects of mutations and ionic strength on the rate constants and produced a set of mutations on the complex of hGH with its receptor that putatively enhances the rate constant by nearly 100-fold through increasing charge complementarity. To quantify charge complementarity, we propose a simple index based on the charge distribution within the binding interface, which shows good correlation with ΔG(e1)(∗). Together these results suggest that protein charges can be manipulated to tune k(a) and control biological function.

Direct visualization reveals dynamics of a transient intermediate during protein assembly

Interactions between proteins underlie numerous biological functions. Theoretical work suggests that protein interactions initiate with formation of transient intermediates that subsequently relax to specific, stable complexes. However, the nature and roles of these transient intermediates have remained elusive. Here, we characterized the global structure, dynamics, and stability of a transient, on-pathway intermediate during complex assembly between the Signal Recognition Particle (SRP) and its receptor. We show that this intermediate has overlapping but distinct interaction interfaces from that of the final complex, and it is stabilized by long-range electrostatic interactions. A wide distribution of conformations is explored by the intermediate; this distribution becomes more restricted in the final complex and is further regulated by the cargo of SRP. These results suggest a funnel-shaped energy landscape for protein interactions, and they provide a framework for understanding the role of transient intermediates in protein assembly and biological regulation.

Mapping backbone and side-chain interactions in the transition state of a coupled protein folding and binding reaction

Understanding the mechanism of protein folding requires a detailed knowledge of the structural properties of the barriers separating unfolded from native conformations. The S-peptide from ribonuclease S forms its α-helical structure only upon binding to the folded S-protein. We characterized the transition state for this binding-induced folding reaction at high resolution by determining the effect of site-specific backbone thioxylation and side-chain modifications on the kinetics and thermodynamics of the reaction, which allows us to monitor formation of backbone hydrogen bonds and side-chain interactions in the transition state. The experiments reveal that α-helical structure in the S-peptide is absent in the transition state of binding. Recognition between the unfolded S-peptide and the S-protein is mediated by loosely packed hydrophobic side-chain interactions in two well defined regions on the S-peptide. Close packing and helix formation occurs rapidly after binding. Introducing hydrophobic residues at positions outside the recognition region can drastically slow down association.

Structural determinants of affinity enhancement between GoLoco motifs and G-protein alpha subunit mutants

GoLoco motif proteins bind to the inhibitory G(i) subclass of G-protein α subunits and slow the release of bound GDP; this interaction is considered critical to asymmetric cell division and neuro-epithelium and epithelial progenitor differentiation. To provide protein tools for interrogating the precise cellular role(s) of GoLoco motif/Gα(i) complexes, we have employed structure-based protein design strategies to predict gain-of-function mutations that increase GoLoco motif binding affinity. Here, we describe fluorescence polarization and isothermal titration calorimetry measurements showing three predicted Gα(i1) point mutations, E116L, Q147L, and E245L; each increases affinity for multiple GoLoco motifs. A component of this affinity enhancement results from a decreased rate of dissociation between the Gα mutants and GoLoco motifs. For Gα(i1)(Q147L), affinity enhancement was seen to be driven by favorable changes in binding enthalpy, despite reduced contributions from binding entropy. The crystal structure of Gα(i1)(Q147L) bound to the RGS14 GoLoco motif revealed disorder among three peptide residues surrounding a well defined Leu-147 side chain. Monte Carlo simulations of the peptide in this region showed a sampling of multiple backbone conformations in contrast to the wild-type complex. We conclude that mutation of Glu-147 to leucine creates a hydrophobic surface favorably buried upon GoLoco peptide binding, yet the hydrophobic Leu-147 also promotes flexibility among residues 511-513 of the RGS14 GoLoco peptide.