Identifying protein-protein interfacial residues in heterocomplexes using residue conservation scores

Identifying protein–protein interfaces is crucial for structural biology. Because of the constraints in wet experiments, many computational methods have been proposed. Without knowing any information about the partner chains, a new method of predicting protein–protein interaction interface residues purely based on evolutionary information in heterocomplexes is proposed here. Unlike traditional approaches using multiple sequence alignment profiles to represent the conservation level for each residue, we make predictions based on the concept of residue conservation scores so that the dimension of the feature vector for each residue can be drastically reduced, at least 20 times less than conventional methods. Based on the representation approach, a simple linear discriminant function is used to make predictions, so the computational complexity of the whole prediction procedure can also be greatly decreased. By testing our approach on 69 heterocomplex chains, experimental results demonstrate the performance of our approach is indeed superior to current existing methods.     

Comparing interfacial dynamics in protein-protein complexes: an elastic network approach

Background  

The transient, or permanent, association of proteins to form organized complexes is one of the most common mechanisms of regulation of biological processes. Systematic physico-chemical studies of the binding interfaces have previously shown that a key mechanism for the formation/stabilization of dimers is the steric and chemical complementarity of the two semi-interfaces. The role of the fluctuation dynamics at the interface of the interacting subunits, although expectedly important, proved more elusive to characterize. The aim of the present computational study is to gain insight into salient dynamics-based aspects of protein-protein interfaces.     

Protein-protein interfaces: analysis of amino acid conservation in homodimers

Evolutionary information derived from the large number of available protein sequences and structures could powerfully guide both analysis and prediction of protein-protein interfaces. To test the relevance of this information, we assess the conservation of residues at protein-protein interfaces compared with other residues on the protein surface. Six homodimer families are analyzed: alkaline phosphatase, enolase, glutathione S-transferase, copper-zinc superoxide dismutase, Streptomyces subtilisin inhibitor, and triose phosphate isomerase. For each family, random simulation is used to calculate the probability (P value) that the level of conservation observed at the interface occurred by chance. The results show that interface conservation is higher than expected by chance and usually statistically significant at the 5% level or better. The effect on the P values of using different definitions of the interface and of excluding active site residues is discussed.     

Determination of the interfacial water content in protein-protein complexes from free energy simulations

The question as to how many tightly or weakly bound water molecules are located in interfaces between protein-protein complex constituents is addressed from a phase equilibrium point of view by developing a theory in the canonical ensemble. A fast method based on free energy simulations is described for computing the number of water molecules in the interface regions. Results are given for 211 interfacial cavities of 26 antigen-antibody complexes for which experimentally determined structures are found in the Protein Data Bank. The accuracy of the method is assessed and the computational water content is compared with experimental data, revealing the amount of water molecules not resolved by experimental approaches.     

A dominant conformational role for amino acid diversity in minimalist protein-protein interfaces

Recent studies have shown that highly simplified interaction surfaces consisting of combinations of just two amino acids, Tyr and Ser, exhibit high affinity and specificity. The high functional levels of such minimalist interfaces might thus indicate small contributions of greater amino acid diversity seen in natural interfaces. Toward addressing this issue, we have produced a pair of binding proteins built on the fibronectin type III scaffold, termed “monobodies.” One monobody contains the Tyr/Ser binary-code interface (termed YS) and the other contains an expanded amino acid diversity interface (YSX), but both bind to an identical target, maltose-binding protein. The YSX monobody bound with higher affinity, a slower off rate and a more favorable enthalpic contribution than the YS monobody. High-resolution X-ray crystal structures revealed that both proteins bound to an essentially identical epitope, providing a unique opportunity to directly investigate the role of amino acid diversity in a protein interaction interface. Surprisingly, Tyr still dominates the YSX paratope and the additional amino acid types are primarily used to conformationally optimize contacts made by tyrosines. Scanning mutagenesis showed that while all contacting Tyr side chains are essential in the YS monobody, the YSX interface was more tolerant to mutations. These results suggest that the conformational, not chemical, diversity of additional types of amino acids provided higher functionality and evolutionary robustness, supporting the dominant role of Tyr and the importance of conformational diversity in forming protein interaction interfaces.     

Micropatterning for quantitative analysis of protein-protein interactions in living cells

We present a method to identify and characterize interactions between a fluorophore-labeled protein ('prey') and a membrane protein ('bait') in live mammalian cells. Cells are plated on micropatterned surfaces functionalized with antibodies to the bait extracellular domain. Bait-prey interactions are assayed through the redistribution of the fluorescent prey. We used the method to characterize the interaction between human CD4, the major co-receptor in T-cell activation, and human Lck, the protein tyrosine kinase essential for early T-cell signaling. We measured equilibrium associations by quantifying Lck redistribution to CD4 micropatterns and studied interaction dynamics by photobleaching experiments and single-molecule imaging. In addition to the known zinc clasp structure, the Lck membrane anchor in particular had a major impact on the Lck-CD4 interaction, mediating direct binding and further stabilizing the interaction of other Lck domains. In total, membrane anchorage increased the interaction lifetime by two orders of magnitude.     

A tri-functional amino acid enables mapping of binding sites for posttranslational-modification-mediated protein-protein interactions

1. Download : Download high-res image (167KB)
2. Download : Download full-size image

     

Validation of a reversed-phase HPLC method for quantitative amino acid analysis.

A semi-automated method for amino acid derivatization and analysis has been validated for use in analysis of protein biopharmaceuticals. The method includes protein hydrolysis, o-phthalaldehyde derivatization, and reversed-phase high-performance liquid chromatography analysis in a general-purpose UV-visible high-performance liquid chromatography system. Amino-acid derivatization is performed automatically by the high-performance liquid chromatography autosampler right before injection. The required validation parameters, i.e., specificity, linearity, accuracy, precision, limit of detection, and limit of quantification, were studied for bovine serum albumin and for a recombinant human Fab fragment. The method can be employed as an absolute quantification method for determination of extinction coefficients of recombinant proteins.     

Correlating amino acid conservation with function in tyrosyl-tRNA synthetase

Sequence comparisons have been combined with mutational and kinetic analyses to elucidate how the catalytic mechanism of Bacillus stearothermophilus tyrosyl-tRNA synthetase evolved. Catalysis of tRNA(Tyr) aminoacylation by tyrosyl-tRNA synthetase involves two steps: activation of the tyrosine substrate by ATP to form an enzyme-bound tyrosyl-adenylate intermediate, and transfer of tyrosine from the tyrosyl-adenylate intermediate to tRNA(Tyr). Previous investigations indicate that the class I conserved KMSKS motif is involved in only the first step of the reaction (i.e. tyrosine activation). Here, we demonstrate that the class I conserved HIGH motif also is involved only in the tyrosine activation step. In contrast, one amino acid that is conserved in a subset of the class I aminoacyl-tRNA synthetases, Thr40, and two amino acids that are present only in tyrosyl-tRNA synthetases, Lys82 and Arg86, stabilize the transition states for both steps of the tRNA aminoacylation reaction. These results imply that stabilization of the transition state for the first step of the reaction by the class I aminoacyl-tRNA synthetases preceded stabilization of the transition state for the second step of the reaction. This is consistent with the hypothesis that the ability of aminoacyl-tRNA synthetases to catalyze the activation of amino acids with ATP preceded their ability to catalyze attachment of the amino acid to the 3' end of tRNA. We propose that the primordial aminoacyl-tRNA synthetases replaced a ribozyme whose function was to promote the reaction of amino acids and other small molecules with ATP.     

Antitumor activity of titanocene amino acid complexes

Seven ionic titanocene -amino acid (aa) complexes [(C₅H₅)₂Ti(aa)₂]²⁺[X]₂ ^– with aa = glycine,l-alanine, 2-methylalanine,d-l-phenylalanine,d,l-4-fluorophenylalanine and X = Cl or AsF₆, were investigated for antitumor activity against fluid Ehrlich ascites tumor growing in CF1 mice. These complexes are the first stable model compounds of titanocene units with protein components, synthesized from a water-like, methanolic medium. All titanocene amino acid complexes induced antitumor activity which was manifested by maximum cure rates ranging from 30 to 70% and increases in life span from 78 to 276% in comparison with untreated control animals. The complexes containing chloride as anion X were more effective than the hexafluoroarsenate derivatives, which surprisingly showed a low substance toxicity. In all cases, the antitumor activity of the ionic titanocene amino acid complexes tested was less pronounced than that of the neutral parent compound [(C₅H₅)₂TiCl₂].     

Computational prediction of protein-protein complexes

ABSTRACT: BACKGROUND: Protein-protein interactions form the core of several biological processes. With protein-protein interfaces being considered as drug targets, studies on their interactions and molecular mechanisms are gaining ground. As the number of protein complexes in databases is scarce as compared to a spectrum of independent protein molecules, computational approaches are being considered for speedier model derivation and assessment of a plausible complex. In this study, a good approach towards in silico generation of protein-protein heterocomplex and identification of the most probable complex among thousands of complexes thus generated is documented. This approach becomes even more useful in the event of little or no binding site information between the interacting protein molecules. FINDINGS: A plausible protein-protein hetero-complex was fished out from 10 docked complexes which are a representative set of complexes obtained after clustering of 2000 generated complexes using protein-protein docking softwares. The interfacial area for this complex was predicted by two hotspot prediction programs employing different algorithms. Further, this complex had the lowest energy and most buried surface area of all the complexes with the same interfacial residues. CONCLUSIONS: For the generation of a plausible protein heterocomplex, various software tools were employed. Prominent are the protein-protein docking methods, prediction of 'hotspots' which are the amino acid residues likely to be in an interface and measurement of buried surface area of the complexes. Consensus generated in their predictions lends credence to the use of the various softwares used.     

Sequence and structural features of binding site residues in protein-protein complexes: comparison with protein-nucleic acid complexes

Background

Protein-protein interactions are important for several cellular processes. Understanding the mechanism of protein-protein recognition and predicting the binding sites in protein-protein complexes are long standing goals in molecular and computational biology.

Methods

We have developed an energy based approach for identifying the binding site residues in protein–protein complexes. The binding site residues have been analyzed with sequence and structure based parameters such as binding propensity, neighboring residues in the vicinity of binding sites, conservation score and conformational switching.

Results

We observed that the binding propensities of amino acid residues are specific for protein-protein complexes. Further, typical dipeptides and tripeptides showed high preference for binding, which is unique to protein-protein complexes. Most of the binding site residues are highly conserved among homologous sequences. Our analysis showed that 7% of residues changed their conformations upon protein-protein complex formation and it is 9.2% and 6.6% in the binding and non-binding sites, respectively. Specifically, the residues Glu, Lys, Leu and Ser changed their conformation from coil to helix/strand and from helix to coil/strand. Leu, Ser, Thr and Val prefer to change their conformation from strand to coil/helix.

Conclusions

The results obtained in this study will be helpful for understanding and predicting the binding sites in protein-protein complexes.

     

A quantitative investigation of the chemical space surrounding amino acid alphabet formation

To date, explanations for the origin and emergence of the alphabet of amino acids encoded by the standard genetic code have been largely qualitative and speculative. Here, with the help of computational chemistry, we present the first quantitative exploration of nature's “choices” set against various models for plausible alternatives. Specifically, we consider the chemical space defined by three fundamental biophysical properties (size, charge, and hydrophobicity) to ask whether the amino acids that entered the genetic code exhibit a higher diversity than random samples of similar size drawn from several different definitions of amino acid possibility space.We found that in terms of the properties studied, the full, standard set of 20 biologically encoded amino acids is indeed significantly more diverse than an equivalently sized group drawn at random from the set of plausible, prebiotic alternatives (using the Murchison meteorite as a model for pre-biotic plausibility). However, when the set of possible amino acids is enlarged to include those that are produced by standard biosynthetic pathways (reflecting the widespread idea that many members of the standard alphabet were recruited in this way), then the genetically encoded amino acids can no longer be distinguished as more diverse than a random sample. Finally, if we turn to consider the overlap between biologically encoded amino acids and those that are prebiotically plausible, then we find that the biologically encoded subset are no more diverse as a group than would be expected from a random sample, unless the definition of “random sample” is adjusted to reflect possible prebiotic abundance (again, using the contents of the Murchison meteorite as our estimator). This final result is contingent on the accuracy of our computational estimates for amino acid properties, and prebiotic abundances, and an exploration of the likely effect of errors in our estimation reveals that our results should be treated with caution. We thus present this work as a first step in quantifying and thus testing various origin-of-life hypotheses regarding the origin and evolution of life's amino acid alphabet, and advocate the progress that would add valuable information in the future.     

Electrostatic properties of protein-protein complexes

Statistical electrostatic analysis of 37 protein-protein complexes extracted from the previously developed database of protein complexes (ProtCom, http://www.ces.clemson.edu/compbio/protcom) is presented. It is shown that small interfaces have a higher content of charged and polar groups compared to large interfaces. In a vast majority of the cases the average pKa shifts for acidic residues induced by the complex formation are negative, indicating that complex formation stabilizes their ionizable states, whereas the histidines are predicted to destabilize the complex. The individual pKa shifts show the same tendency since 80% of the interfacial acidic groups were found to lower their pKas, whereas only 25% of histidines raise their pKa upon the complex formation. The interfacial groups have been divided into three sets according to the mechanism of their pKa shift, and statistical analysis of each set was performed. It was shown that the optimum pH values (pH of maximal stability) of the complex tend to be the same as the optimum pH values of the complex components. This finding can be used in the homology-based prediction of the 3D structures of protein complexes, especially when one needs to evaluate and rank putative models. It is more likely for a model to be correct if both components of the model complex and the entire complex have the same or at least similar values of the optimum pH.     

Optimization of electrostatic interactions in protein-protein complexes

In this article, we present a statistical analysis of the electrostatic properties of 298 protein-protein complexes and 356 domain-domain structures extracted from the previously developed database of protein complexes (ProtCom, http://www.ces.clemson.edu/compbio/protcom). For each structure in the dataset we calculated the total electrostatic energy of the binding and its two components, Coulombic and reaction field energy. It was found that in a vast majority of the cases (>90%), the total electrostatic component of the binding energy was unfavorable. At the same time, the Coulombic component of the binding energy was found to favor the complex formation while the reaction field component of the binding energy opposed the binding. It was also demonstrated that the components in a wild-type (WT) structure are optimized/anti-optimized with respect to the corresponding distributions, arising from random shuffling of the charged side chains. The degree of this optimization was assessed through the Z-score of WT energy in respect to the random distribution. It was found that the Z-scores of Coulombic interactions peak at a considerably negative value for all 654 cases considered while the Z-score of the reaction field energy varied among different types of complexes. All these findings indicate that the Coulombic interactions within WT protein-protein complexes are optimized to favor the complex formation while the total electrostatic energy predominantly opposes the binding. This observation was used to discriminate WT structures among sets of structural decoys and showed that the electrostatic component of the binding energy is not a good discriminator of the WT; while, Coulombic or reaction field energies perform better depending upon the decoy set used.     

Relative von Neumann entropy for evaluating amino acid conservation

The Shannon entropy is a common way of measuring conservation of sites in multiple sequence alignments, and has also been extended with the relative Shannon entropy to account for background frequencies. The von Neumann entropy is another extension of the Shannon entropy, adapted from quantum mechanics in order to account for amino acid similarities. However, there is yet no relative von Neumann entropy defined for sequence analysis. We introduce a new definition of the von Neumann entropy for use in sequence analysis, which we found to perform better than the previous definition. We also introduce the relative von Neumann entropy and a way of parametrizing this in order to obtain the Shannon entropy, the relative Shannon entropy and the von Neumann entropy at special parameter values. We performed an exhaustive search of this parameter space and found better predictions of catalytic sites compared to any of the previously used entropies.     

iPfam: visualization of protein-protein interactions in PDB at domain and amino acid resolutions

SUMMARY: There are many resources that contain information about binary interactions between proteins. However, protein interactions are defined by only a subset of residues in any protein. We have implemented a web resource that allows the investigation of protein interactions in the Protein Data Bank structures at the level of Pfam domains and amino acid residues. This detailed knowledge relies on the fact that there are a large number of multidomain proteins and protein complexes being deposited in the structure databases. The resource called iPfam is hosted within the Pfam UK website. Most resources focus on the interactions between proteins; iPfam includes these as well as interactions between domains in a single protein. AVAILABILITY: iPfam is available on the Web for browsing at http://www.sanger.ac.uk/Software/Pfam/iPfam/; the source-data for iPfam is freely available in relational tables via the ftp site ftp://ftp.sanger.ac.uk/pub/databases/Pfam/database_files/.