Protein-protein interaction: a genetic selection for compensating mutations at the barnase-barstar interface

Single-Molecule Observation of Competitive Protein-Protein Interactions Utilizing a Nanopore

Two or more protein ligands may compete against each other to interact transiently with a protein receptor. While this is a ubiquitous phenomenon in cell signaling, existing technologies cannot identify its kinetic complexity because specific subpopulations of binding events of different ligands are hidden in the averaging process in an ensemble. In addition, the limited time resolution of prevailing methods makes detecting and discriminating binding events among diverse interacting partners challenging. Here, we utilize a genetically encoded nanopore sensor to disentangle competitive protein-protein interactions (PPIs) in a one-on-one and label-free fashion. Our measurements involve binary mixtures of protein ligands of varying binding affinity against the same receptor, which was externally immobilized on the nanopore tip. We use the resistive-pulse technique to monitor the kinetics and dynamics of reversible PPIs without the nanopore confinement, with a high-time bandwidth, and at titratable ligand concentrations. In this way, we systematically evaluate how individual protein ligands take their turn to reside on the receptor's binding site. Further, our single-molecule determinations of these interactions are quantitatively compared with data generated by a two-ligand, one-receptor queuing model. The outcomes of this work provide a fundamental basis for future developments aimed at a better mechanistic understanding of competitive PPIs. Moreover, they may also form a platform in drug development pipelines targeting high-complexity PPIs mediated by protein hubs.

Interpreting the effect of mutations to protein binding sites from large-scale genomic screens

Predicting the functionality of missense mutations is extremely difficult. Large-scale genomic screens are commonly performed to identify mutational correlates or drivers of disease and treatment resistance, but interpretation of how these mutations impact protein function is limited. One such consequence of mutations to a protein is to impact its ability to bind and interact with partners or small molecules such as ATP, thereby modulating its function. Multiple methods exist for predicting the impact of a single mutation on protein-protein binding energy, but it is difficult in the context of a genomic screen to understand if these mutations with large impacts on binding are more common than statistically expected. We present a methodology for taking mutational data from large-scale genomic screens and generating functional and statistical insights into their role in the binding of proteins both with each other and their small molecule ligands. This allows a quantitative and statistical analysis to determine whether mutations impacting protein binding or ligand interactions are occurring more or less frequently than expected by chance. We achieve this by calculating the potential impact of any possible mutation and comparing an expected distribution to the observed mutations. This method is applied to examples demonstrating its ability to interpret mutations involved in protein-protein binding, protein-DNA interactions, and the evolution of therapeutic resistance.

Analysis of Protein-Protein Interactions for Intermolecular Bond Prediction

Protein-protein interactions often involve a complex system of intermolecular interactions between residues and atoms at the binding site. A comprehensive exploration of these interactions can help reveal key residues involved in protein-protein recognition that are not obvious using other protein analysis techniques. This paper presents and extends DiffBond, a novel method for identifying and classifying intermolecular bonds while applying standard definitions of bonds in chemical literature to explain protein interactions. DiffBond predicted intermolecular bonds from four protein complexes: Barnase-Barstar, Rap1a-raf, SMAD2-SMAD4, and a subset of complexes formed from three-finger toxins and nAChRs. Based on validation through manual literature search and through comparison of two protein complexes from the SKEMPI dataset, DiffBond was able to identify intermolecular ionic bonds and hydrogen bonds with high precision and recall, and identify salt bridges with high precision. DiffBond predictions on bond existence were also strongly correlated with observations of Gibbs free energy change and electrostatic complementarity in mutational experiments. DiffBond can be a powerful tool for predicting and characterizing influential residues in protein-protein interactions, and its predictions can support research in mutational experiments and drug design.

DiffBond: A Method for Predicting Intermolecular Bond Formation

Many tools that explore models of protein complexes are also able to analyze interactions between specific residues and atoms. A comprehensive exploration of these interactions can often uncover aspects of protein-protein recognition that are not obvious using other protein analysis techniques. This paper describes DiffBond, a novel method for searching for intermolecular interactions between protein complexes while differentiating between three different types of interaction: hydrogen bonds, ionic bonds, and salt bridges. DiffBond incorporates textbook definitions of these three interactions while contending with uncertainties that are inherent in computational models of interacting proteins. We used it to examine the barnase-barstar, Rap1a-raf, and Smad2-Smad4 complexes, as well as a subset of protein complexes formed between three-finger toxins and nAChRs. Based on electrostatic interactions established by previous experimental studies, DiffBond was able to identify ionic and hydrogen bonds with high precision and recall, and identify salt bridges with high precision. In combination with other electrostatic analysis methods, DiffBond can be a useful tool in helping predict influential amino acids in protein-protein interactions and characterizing the type of interaction.

Molecular Mechanism for the Hofmeister Effect Derived from NMR and DSC Measurements on Barnase

The effects of sodium thiocyanate, sodium chloride, and sodium sulfate on the ribonuclease barnase were studied using differential scanning calorimetry (DSC) and NMR. Both measurements reveal specific and saturable binding at low anion concentrations (up to 250 mM), which produces localized conformational and energetic effects that are unrelated to the Hofmeister series. The binding of sulfate slows intramolecular motions, as revealed by peak broadening in ¹³C heteronuclear single quantum coherence spectroscopy. None of the anions shows significant binding to hydrophobic groups. Above 250 mM, the DSC results are consistent with the expected Hofmeister effects in that the chaotropic anion thiocyanate destabilizes barnase. In this higher concentration range, the anions have approximately linear effects on protein NMR chemical shifts, with no evidence for direct interaction of the anions with the protein surface. We conclude that the effects of the anions on barnase are mediated by solvent interactions. The results are not consistent with the predictions of the preferential interaction, preferential hydration, and excluded volume models commonly used to describe Hofmeister effects. Instead, they suggest that the Hofmeister anion effects on both stability and solubility of barnase are due to the way in which the protein interacts with water molecules, and in particular with water dipoles, which are more ordered around sulfate anions and less ordered around thiocyanate anions.

Identification of human TERT elements necessary for telomerase recruitment to telomeres

Human chromosomes terminate in telomeres, repetitive DNA sequences bound by the shelterin complex. Shelterin protects chromosome ends, prevents recognition by the DNA damage machinery, and recruits telomerase. A patch of amino acids, termed the TEL-patch, on the OB-fold domain of the shelterin component TPP1 is essential to recruit telomerase to telomeres. In contrast, the site on telomerase that interacts with the TPP1 OB-fold is not well defined. In this study, we identify separation-of-function mutations in the TEN-domain of human telomerase reverse transcriptase (hTERT) that disrupt the interaction of telomerase with TPP1 in vivo and in vitro but have very little effect on the catalytic activity of telomerase. Suppression of a TEN-domain mutation with a compensatory charge-swap mutation in the TEL-patch indicates that their association is direct. Our findings define the interaction interface required for telomerase recruitment to telomeres, an important step towards developing modulators of this interaction as therapeutics for human disease.

DOI:http://dx.doi.org/10.7554/eLife.03563.001

In the nucleus of a cell, the DNA that contains the cell's genetic information is packaged into long structures called chromosomes. Every time a cell divides, its chromosomes are duplicated. However, the proteins that are responsible for copying the DNA cannot reach the very end of the DNA strand, causing the chromosomes to progressively shorten. To ensure that this does not cause genetic information to be lost, each chromosome ends in a repetitive stretch of DNA called a telomere. Though the end of the telomere is lost whenever the DNA is copied, an enzyme called telomerase replaces the sequence that has been lost and counteracts the shortening of the telomeres.

Shelterin is a protein complex that binds to telomeres to protect them and also helps telomerase to work correctly. Shelterin contains a specific site that attaches to telomerase, but exactly how the human versions of these two molecules bind to each other is unknown. A possible interaction site had been identified on the telomerase, which, when mutated, stops the telomerase working properly. However, as this region is also involved in lengthening the telomeres after the chromosomes have duplicated, it is not certain that these problems result from the telomerase failing to bind to shelterin.

The enzyme telomerase is unusual; it has both RNA and protein components. Like all other proteins, the telomerase protein is made up of strings of amino acids. Schmidt et al. discovered that replacing two specific amino acids in human telomerase prevents its binding to shelterin. Cells that produced the modified form of the telomerase had chromosomes with shortened telomeres. However, if the cells also produced modified versions of the shelterin complex that were designed to bind to the modified telomerase, telomere length was normal. This indicates that the telomerase interacts directly with shelterin, rather than through a ‘bridging’ molecule.

Mutations in the genes coding for both shelterin and the telomerase enzyme cause a number of human diseases, and cancers rely on the activity of telomerases to grow. Knowing how shelterin and telomerase interact could therefore help to design drugs that may either restore or disrupt the interaction and therefore can be used to treat these diseases.

DOI:http://dx.doi.org/10.7554/eLife.03563.002

Electrostatic interactions in the binding pathway of a transient protein complex studied by NMR and isothermal titration calorimetry

Much of our knowledge of protein binding pathways is derived from extremely stable complexes that interact very tightly, with lifetimes of hours to days. Much less is known about weaker interactions and transient complexes because these are challenging to characterize experimentally. Nevertheless, these types of interactions are ubiquitous in living systems. The combination of NMR relaxation dispersion Carr-Purcell-Meiboom-Gill (CPMG) experiments and isothermal titration calorimetry allows the quantification of rapid binding kinetics for complexes with submillisecond lifetimes that are difficult to study using conventional techniques. We have used this approach to investigate the binding pathway of the Src homology 3 (SH3) domain from the Fyn tyrosine kinase, which forms complexes with peptide targets whose lifetimes are on the order of about a millisecond. Long range electrostatic interactions have been shown to play a critical role in the binding pathways of tightly binding complexes. The role of electrostatics in the binding pathways of transient complexes is less well understood. Similarly to previously studied tight complexes, we find that SH3 domain association rates are enhanced by long range electrostatics, whereas short range interactions are formed late in the docking process. However, the extent of electrostatic association rate enhancement is several orders of magnitudes less, whereas the electrostatic-free basal association rate is significantly greater. Thus, the SH3 domain is far less reliant on electrostatic enhancement to achieve rapid association kinetics than are previously studied systems. This suggests that there may be overall differences in the role played by electrostatics in the binding pathways of extremely stable versus transient complexes.

Covariation of branch lengths in phylogenies of functionally related genes

Recent studies have shown evidence for the coevolution of functionally-related genes. This coevolution is a result of constraints to maintain functional relationships between interacting proteins. The studies have focused on the correlation in gene tree branch lengths of proteins that are directly interacting with each other. We here hypothesize that the correlation in branch lengths is not limited only to proteins that directly interact, but also to proteins that operate within the same pathway. Using generalized linear models as a basis of identifying correlation, we attempted to predict the gene ontology (GO) terms of a gene based on its gene tree branch lengths. We applied our method to a dataset consisting of proteins from ten prokaryotic species. We found that the degree of accuracy to which we could predict the function of the proteins from their gene tree varied substantially with different GO terms. In particular, our model could accurately predict genes involved in translation and certain ribosomal activities with the area of the receiver-operator curve of up to 92%. Further analysis showed that the similarity between the trees of genes labeled with similar GO terms was not limited to genes that physically interacted, but also extended to genes functioning within the same pathway. We discuss the relevance of our findings as it relates to the use of phylogenetic methods in comparative genomics.

rRNA mutations that inhibit transfer-messenger RNA activity on stalled ribosomes

In eubacteria, stalled ribosomes are rescued by a conserved quality-control mechanism involving transfer-messenger RNA (tmRNA) and its protein partner, SmpB. Mimicking a tRNA, tmRNA enters stalled ribosomes, adds Ala to the nascent polypeptide, and serves as a template to encode a short peptide that tags the nascent protein for destruction. To further characterize the tagging process, we developed two genetic selections that link tmRNA activity to cell death. These negative selections can be used to identify inhibitors of tagging or to identify mutations in key residues essential for ribosome rescue. Little is known about which ribosomal elements are specifically required for tmRNA activity. Using these selections, we isolated rRNA mutations that block the rescue of ribosomes stalled at rare Arg codons or at the inefficient termination signal Pro-opal. We found that deletion of A1150 in the 16S rRNA blocked tagging regardless of the stalling sequence, suggesting that it inhibits tmRNA activity directly. The C889U mutation in 23S rRNA, however, lowered tagging levels at Pro-opal and rare Arg codons, but not at the 3' end of an mRNA lacking a stop codon. We concluded that the C889U mutation does not inhibit tmRNA activity per se but interferes with an upstream step intermediate between stalling and tagging. C889 is found in the A-site finger, where it interacts with the S13 protein in the small subunit (forming intersubunit bridge B1a).

Antitumor activity and toxicity of anti-HER2 immunoRNase scFv 4D5-dibarnase in mice bearing human breast cancer xenografts

Ribonucleases (RNases) are a non-mutagenic alternative to harmful DNA-damaging anticancer drugs. Targeting of RNases with antibodies to surface antigens that are selectively expressed on tumor cells endows specificity to the cytotoxic actions of RNases. Barnase, a ribonuclease from Bacillus amyloliquefaciens, is a promising candidate for targeted delivery to cancer cells because of its insusceptibility to the ubiquitous cytoplasmic ribonuclease inhibitor, and its high stability and catalytic activity. Here, we characterized in vitro and in vivo an immunoRNase, scFv 4D5-dibarnase, which consists of two barnase molecules that are fused serially to the single-chain variable fragment (scFv) of humanized 4D5 antibody. The latter is directed against the extracellular domain of human epidermal growth factor receptor 2 (HER2), a cancer marker that is overexpressed in many human carcinomas. The scFv 4D5-dibarnase exerted a specific cytotoxic effect on HER2-overexpressing SKBR-3 and BT-474 human breast carcinoma cells (IC(50) = 4.1 and 2.4 nM, respectively) via induction of apoptosis. Ten doses of 0.7 mg/kg scFv 4D5-dibarnase to BALB/c nude mice that bore SKBR-3 human breast cancer xenografts resulted in a 76% reduction in tumor growth. A single injection of scFv 4D5-dibarnase at a total course dose of 7 mg/kg did not cause severe side effects in BALB/c nude or BDF1 mice. The cytotoxicity and selectivity of scFv 4D5-dibarnase merit consideration of this immunoRNase as a potent anticancer agent.

Binding mechanism of an SH3 domain studied by NMR and ITC

Complexes between Src-homology 3 domains and proline-rich target peptides can have lifetimes on the order of milliseconds, making them too short-lived for kinetic characterization by conventional methods. Nuclear magnetic resonance (NMR) dynamics experiments are ideally suited to study such rapid binding equilibria, and additionally provide information on partly bound intermediate states. We used NMR together with isothermal titration calorimetry (ITC) to characterize the interaction of the SH3 domain from the Fyn tyrosine kinase with a 12-residue peptide at temperatures between 10 and 50 degrees C. NMR data at all temperatures are consistent with an effectively two-state binding reaction, such that any intermediates are either very weakly populated or exchange extremely rapidly with the free or bound forms. Dissociation rate constants, determined by CPMG and ZZ-exchange NMR experiments, range from k(off)(10 degrees C) = 4.5 s(-1) to k(off)(50 degrees C) = 331 s(-1). ITC data at all temperatures follow a simple two-state interaction model. Binding is favored enthalpically, with a dissociation enthalpy, DeltaH(D)(30 degrees C) = 15.4 kcal mol(-1), and disfavored entropically, with a dissociation entropy, DeltaS(D)(30 degrees C) = 20.0 cal mol(-1) K(-1). The free protein and peptide have significantly higher heat capacity than the bound complex, DeltaC(p) = 352 cal mol(-1) K(-1), which is consistent with the largely hydrophobic character of the binding interface. An Eyring plot of k(off) values gives an activation enthalpy of dissociation, DeltaH(D)(double dagger)(30 degrees C) = 19.3 kcal mol(-1) and exhibits slight curvature consistent with the ITC-derived value of DeltaC(p). The curvature suggests that nonpolar residues of the hydrophobic interface are solvated in the transition state for dissociation. Association rate constants were calculated as k(on) = k(off)/K(D), and range from k(on)(10 degrees C) = 1.03 x 10(8) M(-1) s(-1) to k(on)(50 degrees C) = 2.0 x 10(8) M(-1) s(-1), with an apparent activation enthalpy, DeltaH(A)(double dagger) = 3.4 kcal mol(-1). Both the magnitudes and temperature dependence of k(on) values are consistent with a diffusion-limited association mechanism. The combination of NMR and ITC data sheds light on how the Fyn tyrosine kinase is activated by binding to proline-rich targets, and represents a powerful approach for characterizing transient protein/ligand interactions.

PINAT1.0: protein interaction network analysis tool

Cellular processes are regulated by interaction of various proteins i.e. multiprotein complexes and absences of these interactions are often the cause of disorder or disease. Such type of protein interactions are of great interest for drug designing. In host­parasite diseases like Tuberculosis, non-homologous proteins as drug target are first preference. Most potent drug target can be identifying among large number of non-homologous protein through protein interaction network analysis. Drug target should be those non-homologous protein which is associated with maximum number of functional proteins i.e. has highest number of interactants, so that maximum harm can be caused to pathogen only. In present work, Protein Interaction Network Analysis Tool (PINAT) has been developed to identification of potential protein interaction for drug target identification. PINAT is standalone, GUI application software made for protein-protein interaction (PPI) analysis and network building by using co­evolutionary profile. PINAT is very useful for large data PPI study with easiest handling among available softwares. PINAT provides excellent facilities for the assembly of data for network building with visual presentation of the results and interaction score. The software is written in JAVA and provides reliability through transparency with user.

Barnase as a new therapeutic agent triggering apoptosis in human cancer cells

Background

RNases are currently studied as non-mutagenic alternatives to the harmful DNA-damaging anticancer drugs commonly used in clinical practice. Many mammalian RNases are not potent toxins due to the strong inhibition by ribonuclease inhibitor (RI) presented in the cytoplasm of mammalian cells.

Methodology/Principal Findings

In search of new effective anticancer RNases we studied the effects of barnase, a ribonuclease from Bacillus amyloliquefaciens, on human cancer cells. We found that barnase is resistant to RI. In MTT cell viability assay, barnase was cytotoxic to human carcinoma cell lines with half-inhibitory concentrations (IC₅₀) ranging from 0.2 to 13 µM and to leukemia cell lines with IC₅₀ values ranging from 2.4 to 82 µM. Also, we characterized the cytotoxic effects of barnase-based immunoRNase scFv 4D5-dibarnase, which consists of two barnase molecules serially fused to the single-chain variable fragment (scFv) of humanized antibody 4D5 that recognizes the extracellular domain of cancer marker HER2. The scFv 4D5-dibarnase specifically bound to HER2-positive cells and was internalized via receptor-mediated endocytosis. The intracellular localization of internalized scFv 4D5-dibarnase was determined by electronic microscopy. The cytotoxic effect of scFv 4D5-dibarnase on HER2-positive human ovarian carcinoma SKOV-3 cells (IC₅₀ = 1.8 nM) was three orders of magnitude greater than that of barnase alone. Both barnase and scFv 4D5-dibarnase induced apoptosis in SKOV-3 cells accompanied by internucleosomal chromatin fragmentation, membrane blebbing, the appearance of phosphatidylserine on the outer leaflet of the plasma membrane, and the activation of caspase-3.

Conclusions/Significance

These results demonstrate that barnase is a potent toxic agent for targeting to cancer cells.

Discovering implicit protein-protein interactions in the cell cycle using bioinformatics approaches

The cell division control protein (Cdc2) kinase is a catalytic subunit of a protein kinase complex, called the M phase promoting factor, which induces entry into mitosis and is universal among eukaryotes. This protein is believed to play a major role in cell division and control. The lives of biological cells are controlled by proteins interacting in metabolic and signaling pathways, in complexes that replicate genes and regulate gene activity, and in the assembly of the cytoskeletal infrastructure. Our knowledge of protein-protein (P-P) interactions has been accumulated from biochemical and genetic experiments, including the widely used yeast two-hybrid test. In this paper we examine if P-P interactions in regenerating tissues and cells of the anuran Xenopus laevis can be discovered from biomedical literature using computational and literature mining techniques. Using literature mining techniques, we have identified a set of implicitly interacting proteins in regenerating tissues and cells of Xenopus laevis that may interact with Cdc2 to control cell division. Genome sequence based bioinformatics tools were then applied to validate a set of proteins that appear to interact with the Cdc2 protein. Pathway analysis of these proteins suggests that Myc proteins function as the regulator of M phase initiation by controlling expression of the Akt1 molecule that ultimately inhibits the Cdc2-cyclin B complex in cells. P-P interactions that are implicitly appearing in literature can be effectively discovered using literature mining techniques. By applying evolutionary principles on the P-P interacting pairs, it is possible to quantitatively analyze the significance of the associations with biological relevance. The developed BioMap system allows discovering implicit P-P interactions from large quantity of biomedical literature data. The unique similarities and differences observed within the interacting proteins can lead to the development of the new hypotheses that can be used to design further laboratory experiments.

Prediction of protein-protein association rates from a transition-state theory

We recently developed a theory for the rates of protein-protein association. The theory is based on the concept of a transition state, which separates the bound state, with numerous short-range interactions but restricted translational and rotational freedom, and the unbound state, with, at most, a small number of interactions but expanded configurational freedom. When not accompanied by large-scale conformational changes, protein-protein association becomes diffusion limited. The association rate is then predicted as k(a)=k(a)(0)exp(-DeltaG(el)(double dagger)/k(B)T), where DeltaG(el)(double dagger) is the electrostatic interaction free energy in the transition state, k(a)(0) is the rate in the absence of electrostatic interactions, and k(B)T is thermal energy. Here, this transition-state theory is used to predict the association rates of four protein complexes. The predictions for the wild-type complexes and 23 mutants are found to agree closely with experimental data over wide ranges of ionic strength.

Correlated mutations: advances and limitations. A study on fusion proteins and on the Cohesin-Dockerin families

Correlated mutations have been repeatedly exploited for intramolecular contact map prediction. Over the last decade these efforts yielded several methods for measuring correlated mutations. Nevertheless, the application of correlated mutations for the prediction of intermolecular interactions has not yet been explored. This gap is due to several obstacles, such as 3D complexes availability, paralog discrimination, and the availability of sequence pairs that are required for inter- but not intramolecular analyses. Here we selected for analysis fusion protein families that bypass some of these obstacles. We find that several correlated mutation measurements yield reasonable accuracy for intramolecular contact map prediction on the fusion dataset. However, the accuracy level drops sharply in intermolecular contacts prediction. This drop in accuracy does not occur always. In the Cohesin-Dockerin family, reasonable accuracy is achieved in the prediction of both intra- and intermolecular contacts. The Cohesin-Dockerin family is well suited for correlated mutation analysis. Because, however, this family constitutes a special case (it has radical mutations, has domain repeats, within each species each Dockerin domain interacts with each Cohesin domain, see below), the successful prediction in this family does not point to a general potential in using correlated mutations for predicting intermolecular contacts. Overall, the results of our study indicate that current methodologies of correlated mutations analysis are not suitable for large-scale intermolecular contact prediction, and thus cannot assist in docking. With current measurements, sequence availability, sequence annotations, and underdeveloped sequence pairing methods, correlated mutations can yield reasonable accuracy only for a handful of families.

How do biomolecular systems speed up and regulate rates?

The viability of a biological system depends upon careful regulation of the rates of various processes. These rates have limits imposed by intrinsic chemical or physical steps (e.g., diffusion). These limits can be expanded by interactions and dynamics of the biomolecules. For example, (a) a chemical reaction is catalyzed when its transition state is preferentially bound to an enzyme; (b) the folding of a protein molecule is speeded up by specific interactions within the transition-state ensemble and may be assisted by molecular chaperones; (c) the rate of specific binding of a protein molecule to a cellular target can be enhanced by mechanisms such as long-range electrostatic interactions, nonspecific binding and folding upon binding; (d) directional movement of motor proteins is generated by capturing favorable Brownian motion through intermolecular binding energy; and (e) conduction and selectivity of ions through membrane channels are controlled by interactions and the dynamics of channel proteins. Simple physical models are presented here to illustrate these processes and provide a unifying framework for understanding speed attainment and regulation in biomolecular systems.

ADVICE: Automated Detection and Validation of Interaction by Co-Evolution

ADVICE (Automated Detection and Validation of Interaction by Co-Evolution) is a web tool for predicting and validating protein-protein interactions using the observed co-evolution between interacting proteins. Interacting proteins are known to share similar evolutionary histories since they undergo coordinated evolutionary changes to preserve interactions and functionalities. The web tool automates a commonly adopted methodology to quantify the similarities in proteins' evolutionary histories for postulating potential protein-protein interactions. ADVICE can also be used to validate experimental data against spurious protein interactions by identifying those that have few similarities in their evolutionary histories. The web tool accepts a list of protein sequences or sequence pairs as input and retrieves orthologous sequences to compute the similarities in the proteins' evolutionary histories. To facilitate hypothesis generation, detected co-evolved proteins can be visualized as a network at the website. ADVICE is available at http://advice.i2r.a-star.edu.sg.

Highly Discriminating Protein–Protein Interaction Specificities in the Context of a Conserved Binding Energy Hotspot

We explore the thermodynamic basis for high affinity binding and specificity in conserved protein complexes using colicin endonuclease-immunity protein complexes as our model system. We investigated the ability of each colicin-specific immunity protein (Im2, Im7, Im8 and Im9) to bind the endonuclease (DNase) domains of colicins E2, E7 and E8 in vitro and compared these to the previously studied colicin E9. We find that high affinity binding (Kd < or = 10(-14) M) is a common feature of cognate colicin DNase-Im protein complexes as are non-cognate protein-protein associations, which are generally 10(6)-10(8)-fold weaker. Comparative alanine scanning of Im2 and Im9 residues involved in binding the E2 DNase revealed similar behaviour to that of the two proteins binding the E9 DNase; helix III forms a conserved binding energy hotspot with specificity residues from helix II only contributing favourably in a cognate interaction, a combination we have termed as "dual recognition". Significant differences are seen, however, in the number and side-chain chemistries of specificity sites that contribute to cognate binding. In Im2, Asp33 from helix II dominates colicin E2 specificity, whereas in Im9 several hydrophobic residues, including position 33 (leucine), help define its colicin specificity. A similar distribution of specificity sites was seen using phage display where, with Im2 as the template, a library of randomised sequences was generated in helix II and the library panned against either the E2 or E9 DNase. Position 33 was the dominant specificity site recovered in all E2 DNase-selected clones, whereas a number of Im9 specificity sites were recovered in E9 DNase-selected clones, including position 33. In order to probe the relationship between biological specificity and in vitro binding affinity we compared the degree of protection afforded to bacteria against colicin E9 toxicity by a set of immunity proteins whose affinities for the E9 DNase differed by up to ten orders of magnitude. This analysis indicated that the Kd required for complete biological protection is <10(-10)M and that the "affinity window" over which the selection of novel immunity protein specificities likely evolves is 10(-6)-10(-10)M. This comprehensive survey of colicin DNase-immunity protein complexes illustrates how high affinity protein-protein interactions can be very discriminating even though binding is dominated by a conserved hotspot, with single or multiple specificity sites modulating the overall binding free energy. We discuss these results in the context of other conserved protein complexes and suggest that they point to a generic specificity mechanism in divergently evolved protein-protein interactions.

Comparison of calculation and experiment implicates significant electrostatic contributions to the binding stability of barnase and barstar

The contributions of electrostatic interactions to the binding stability of barnase and barstar were studied by the Poisson-Boltzmann model with three different protocols: a), the dielectric boundary specified as the van der Waals (vdW) surface of the protein along with a protein dielectric constant (epsilon (p)) of 4; b), the dielectric boundary specified as the molecular (i.e., solvent-exclusion (SE)) surface along with epsilon (p) = 4; and c), "SE + epsilon (p) = 20." The "vdW + epsilon (p) = 4" and "SE + epsilon (p) = 20" protocols predicted an overall electrostatic stabilization whereas the "SE + epsilon (p) = 4" protocol predicted an overall electrostatic destabilization. The "vdW + epsilon (p) = 4" protocol was most consistent with experiment. It quantitatively reproduced the observed effects of 17 mutations neutralizing charged residues lining the binding interface and the measured coupling energies of six charge pairs across the interface and reasonably rationalized the experimental ionic strength and pH dependences of the binding constant. In contrast, the "SE + epsilon (p) = 4" protocol predicted significantly larger coupling energies of charge pairs whereas the "SE + epsilon (p) = 20" protocol did not predict any pH dependence. This study calls for further scrutiny of the different Poisson-Boltzmann protocols and demonstrates potential danger in drawing conclusions on electrostatic contributions based on a particular calculation protocol.

Effect of the protein import machinery at the mitochondrial surface on precursor stability

Many biological processes require proteins to undergo conformational changes at the surface of membranes. For example, some precursor proteins unfold at the surface of mitochondria and chloroplasts before translocation into the organelles, and toxins such as colicin A unfold to the molten globule state at bacterial surfaces before inserting into the cell membrane. It is commonly thought that the membrane surfaces and the associated protein machinery destabilize the substrate proteins and that this effect is required for membrane insertion or translocation. One of the best characterized translocation processes is protein import into mitochondria. By measuring the contributions of individual interactions within a model protein to its stability at the mitochondrial surface and in free solution, we show here that the mitochondrial surface neither induces the molten globule state in this protein nor preferentially destabilizes any type of interaction (e.g., hydrogen bonds, nonpolar, etc.) within the protein. Because it is not possible to measure absolute protein stability at the surface of mitochondria, we determined the stability of a tightly associated protein-protein complex at the mitochondrial import site as a model of the stability of a protein. We found the binding constants of the protein-protein complex at the mitochondrial surface and in free solution to be identical. Our results demonstrate that the mitochondrial surface does not destabilize importing precursor proteins in its vicinity.

Allele-specific suppression as a tool to study protein-protein interactions in bacteria

Suppression analysis is well suited to study the interactions of gene products. It offers the advantage of simplicity for any organism for which a convenient genetic system has been developed, which holds for a wide spectrum of bacteria and an ever-increasing number of unicellular as well as complex eukaryotes. No other method provides as much information about the functional relationships of biological macromolecules. The intrinsic value of suppression analysis is enhanced by advances in genomics and in biophysical techniques for investigating the properties of nucleic acids and proteins, such as X-ray crystallography, liquid and solid-state nuclear magnetic resonance, electron spin labeling, and isothermal calorimetry. These approaches confirm and complement whatever is revealed by genetics. Despite these sterling qualities, suppression analysis has its dangers, less in execution than in conceptualization of experiments and interpretation of data. A consistent nomenclature is essential for a uniform and widespread understanding of the results. Familiarity with the genetic background and idiosyncracies of the organism studied is critical in avoiding extraneous phenomena that can affect the outcome. Finally, it is imperative not to underestimate potentially bizarre and improbable consequences that can transpire when rigorous genetic selection is maintained for an appreciable length of time. The article begins with a somewhat pedagogical discussion of genetic terminology. It then moves on to the necessary precautions to observe while planning and conducting suppression analysis. The remainder of the article considers different manifestations of suppression: bypass suppression; gradients of suppression; suppression by relaxed specificity; allele-specific "suppression at a distance"; and true conformational suppression. The treatment is not exhaustive, but representative examples have been gleaned from the recent bacterial literature.

Guiding a docking mode by phage display: selection of correlated mutations at the staphylokinase-plasmin interface

During co-evolution of interacting proteins, functionally disruptive mutations on one side of the interface may be compensated by local amino acid changes on the other to restore binding affinity. This information can be useful for geometry-based docking approaches by reducing the translational and rotational space available to the proteins. Here, we demonstrate that correlated mutations at a protein-protein interface can be rapidly identified by selecting a phage-displayed library of a randomly mutated component of the complex for complementation of mutations that decreased binding in the interacting partner. This approach was used to deduce the binding mode of staphylokinase (Sak), a 15.5 kDa "indirect" plasminogen activator on microplasmin (microPli), the 28 kDa serine protease domain of plasmin. Biopanning indicated that residues Arg94 and Gly174 in microPli are located in close proximity to Glu75 and the Glu88:Ile128 pair in Sak, respectively. The coupled mutations Glu94<-->Lys75 reversed and Gly174<-->Lys88:Val128 introduced a salt bridge, whereby the binding affinities (with coupling energies of 1.8 to 2.3 kcal mol-1, respectively) and the plasminogen activation ability of the mutated complexes were partially restored. These findings suggested a unique docking mode of Sak at the western rim of the active-site cleft of microPli, that is in agreement with the structure of the Sak-microPli complex as recently derived by other methods.

X-ray structural analysis of compensating mutations at the barnase-barstar interface

The crystal structure of the barstar mutants (Y29P) and (Y29D, Y30W) as well as that of the complexes of barstar(Y29P) with wild-type barnase and barnase(H102K) have been determined. These barstar mutants compensate for the dramatic loss of barnase-barstar interaction energy caused by a single mutation of the barnase active site His-102 to a lysine. The latter introduces an uncompensated charge in the pocket at the surface of barstar where Lys-102 is located. The analysis of the structures suggests a mechanism for this compensation based on the solvation of the charge of Lys-102. Additional compensation occurs through the formation of a hydrogen bond.

Progress toward the evolution of an organism with an expanded genetic code

Several significant steps have been completed toward a general method for the site-specific incorporation of unnatural amino acids into proteins in vivo. An "orthogonal" suppressor tRNA was derived from Saccharomyces cerevisiae tRNA2Gln. This yeast orthogonal tRNA is not a substrate in vitro or in vivo for any Escherichia coli aminoacyl-tRNA synthetase, including E. coli glutaminyl-tRNA synthetase (GlnRS), yet functions with the E. coli translational machinery. Importantly, S. cerevisiae GlnRS aminoacylates the yeast orthogonal tRNA in vitro and in E. coli, but does not charge E. coli tRNAGln. This yeast-derived suppressor tRNA together with yeast GlnRS thus represents a completely orthogonal tRNA/synthetase pair in E. coli suitable for the delivery of unnatural amino acids into proteins in vivo. A general method was developed to select for mutant aminoacyl-tRNA synthetases capable of charging any ribosomally accepted molecule onto an orthogonal suppressor tRNA. Finally, a rapid nonradioactive screen for unnatural amino acid uptake was developed and applied to a collection of 138 amino acids. The majority of glutamine and glutamic acid analogs under examination were found to be uptaken by E. coli. Implications of these results are discussed.

Use of altered specificity mutants to probe a specific protein-protein interaction in differentiation: the GATA-1:FOG complex

GATA-1 and FOG (Friend of GATA-1) are each essential for erythroid and megakaryocyte development. FOG, a zinc finger protein, interacts with the amino (N) finger of GATA-1 and cooperates with GATA-1 to promote differentiation. To determine whether this interaction is critical for GATA-1 action, we selected GATA-1 mutants in yeast that fail to interact with FOG but retain normal DNA binding, as well a compensatory FOG mutant that restores interaction. These novel GATA-1 mutants do not promote erythroid differentiation of GATA-1- erythroid cells. Differentiation is rescued by the second-site FOG mutant. Thus, interaction of FOG with GATA-1 is essential for the function of GATA-1 in erythroid differentiation. These findings provide a paradigm for dissecting protein-protein associations involved in mammalian development.

Amino acid-amino acid contacts at the cooperativity interface of the bacteriophage lambda and P22 repressors

The bacteriophage lambda repressor and its relatives bind cooperatively to adjacent as well as artificially separated operator sites. This cooperativity is mediated by a protein-protein interaction between the DNA-bound dimers. Here we use a genetic approach to identify two pairs of amino acids that interact at the dimer-dimer interface. One of these pairs is nonconserved in the aligned sequences of the lambda and P22 repressors; we show that a lambda repressor variant bearing the P22 residues at these two positions interacts specifically with the P22 repressor. The other pair consists of a conserved ion pair; we reverse the charges at these two positions and demonstrate that, whereas the individual substitutions abolish the interaction of the DNA-bound dimers, these changes in combination restore the interaction of both lambdacI and P22c2 dimers.

A new method to characterize hydrophobic organization of proteins: application to rational protein engineering of barnase

We present a new algorithm for characterization of protein spatial structure basing on the molecular hydrophobicity potential approach. The method is illustrated by the analysis of three-dimensional structure of barnase and barnase-barstar complex. Current approach enables identification of amino acid residues situated in unfavorable environment (these residues may be "active" for binding), and to map quantitatively hydrophobic, hydrophilic and unfavorable hydrophobic-hydrophilic intra- and inter-molecular contacts involving backbone and side-chain segments of amino acid residues. Calculation of individual contributions of amino acid residues to such contacts permits identification of structurally-important residues. The contact plots obtained with molecular hydrophobicity potential calculations, provide easy rules to choose sites for mutations, which can increase a strength of intra- or inter-molecular hydrophobic interactions. The unfavorable hydrophobic-hydrophilic contact can be mutated to favorable hydrophobic, and already existing weak hydrophobic contact can be strengthen by increasing hydrophobicity of residues in contact. Basing on the analysis of the contact plots, we suggest several mutations of barnase which are supposed to increase intramolecular hydrophobic interactions, and thus might lead to increased stability of the protein. Part of these mutations was studied previously experimentally, and indeed stabilized barnase. The other of predicted mutations were not studied experimentally yet. Several new mutations of barnase and barstar are also proposed to enhance the hydrophobic interactions on their binding interface.

The kinetics of protein-protein recognition

We examine a simple kinetic model for association that incorporates the basic features of protein-protein recognition within the rigid body approximation, that is, when no large conformation change occurs. Association starts with random collision at the rate k(coll) predicted by the Einstein-Smoluchowski equation. This creates an encounter pair that can evolve into a stable complex if and only if the two molecules are correctly oriented and positioned, which has a probability p(r). In the absence of long-range interactions, the bimolecular rate of association is p(r) k(coll). Long-range electrostatic interactions affect both k(coll) and p(r). The collision rate is multiplied by q(t), a factor larger than 1 when the molecules carry net charges of opposite sign as coulombic attraction makes collisions more frequent, and less than 1 in the opposite case. The probability p(r) is multiplied by a factor q(r) that represents the steering effect of electric dipoles, which preorient the molecules before they collide. The model is applied to experimental data obtained by Schreiber and Fersht (Nat. Struct. Biol. 3:427-431, 1996) on the kinetics of barnase-barstar association. When long-range electrostatic interactions are fully screened or mutated away, q(t)q(r) approximately 1, and the observed rate of productive collision is p(r) k(coll) approximately 10(5) M(-1) x s(-1). Under these conditions, p(r) approximately 1.5 x 10(-5) is determined by geometric constraints corresponding to a loss of rotational freedom. Its value is compatible with computer docking simulations and implies a rotational entropy loss deltaS(rot) approximately 22 e.u. in the transition state. At low ionic strength, long-range electrostatic interactions accelerate barnase-barstar association by a factor q(t)q(r) of up to 10(5) as favorable charge-charge and charge-dipole interactions work together to make it much faster than free diffusion would allow.

Simulation of the diffusional association of barnase and barstar

The rate of protein association places an upper limit on the response time due to protein interactions, which, under certain circumstances, can be diffusion-controlled. Simulations of model proteins show that diffusion-limited association rates are approximately 10(6)-10(7) M-1 s-1 in the absence of long-range forces (Northrup, S. H., and H. P. Erickson. 1992. Kinetics of protein-protein association explained by Brownian dynamics computer simulations. Proc. Natl. Acad. Sci. U.S.A. 89:3338-3342). The measured association rates of barnase and barstar are 10(8)-10(9) M-1 s-1 at 50 mM ionic strength, and depend on ionic strength (Schreiber, G., and A. R. Fersht. 1996. Rapid, electrostatically assisted association of proteins. Nat. Struct. Biol. 3:427-431), implying that their association is electrostatically facilitated. We report Brownian dynamics simulations of the diffusional association of barnase and barstar to compute association rates and their dependence on ionic strength and protein mutation. Crucial to the ability to reproduce experimental rates is the definition of encounter complex formation at the endpoint of diffusional motion. Simple definitions, such as a required root mean square (RMS) distance to the fully bound position, fail to explain the large influence of some mutations on association rates. Good agreement with experiments could be obtained if satisfaction of two intermolecular residue contacts was required for encounter complex formation. In the encounter complexes, barstar tends to be shifted from its position in the bound complex toward the guanine-binding loop on barnase.