How to choose templates for modeling of protein complexes: Insights from benchmarking template-based docking

Comparative docking is based on experimentally determined structures of protein-protein complexes (templates), following the paradigm that proteins with similar sequences and/or structures form similar complexes. Modeling utilizing structure similarity of target monomers to template complexes significantly expands structural coverage of the interactome. Template-based docking by structure alignment can be performed for the entire structures or by aligning targets to the bound interfaces of the experimentally determined complexes. Systematic benchmarking of docking protocols based on full and interface structure alignment showed that both protocols perform similarly, with top 1 docking success rate 26%. However, in terms of the models' quality, the interface-based docking performed marginally better. The interface-based docking is preferable when one would suspect a significant conformational change in the full protein structure upon binding, for example, a rearrangement of the domains in multidomain proteins. Importantly, if the same structure is selected as the top template by both full and interface alignment, the docking success rate increases 2-fold for both top 1 and top 10 predictions. Matching structural annotations of the target and template proteins for template detection, as a computationally less expensive alternative to structural alignment, did not improve the docking performance. Sophisticated remote sequence homology detection added templates to the pool of those identified by structure-based alignment, suggesting that for practical docking, the combination of the structure alignment protocols and the remote sequence homology detection may be useful in order to avoid potential flaws in generation of the structural templates library.     

New benchmark metrics for protein-protein docking methods

With the development of many computational methods that predict the structural models of protein-protein complexes, there is a pressing need to benchmark their performance. As was the case for protein monomers, assessing the quality of models of protein complexes is not straightforward. An effective scoring scheme should be able to detect substructure similarity and estimate its statistical significance. Here, we focus on characterizing the similarity of the interfaces of the complex and introduce two scoring functions. The first, the interfacial Template Modeling score (iTM-score), measures the geometric distance between the interfaces, while the second, the Interface Similarity score (IS-score), evaluates their residue-residue contact similarity in addition to their geometric similarity. We first demonstrate that the IS-score is more suitable for assessing docking models than the iTM-score. The IS-score is then validated in a large-scale benchmark test on 1562 dimeric complexes. Finally, the scoring function is applied to evaluate docking models submitted to the Critical Assessment of Prediction of Interactions (CAPRI) experiments. While the results according to the new scoring scheme are generally consistent with the original CAPRI assessment, the IS-score identifies models whose significance was previously underestimated.     

Distribution of single‐nucleotide variants on protein–protein interaction sites and its relationship with minor allele frequency

Recent advances in DNA sequencing techniques have identified rare single‐nucleotide variants with less than 1% minor allele frequency. Despite the growing interest and physiological importance of rare variants in genome sciences, less attention has been paid to the allele frequency of variants in protein sciences. To elucidate the characteristics of genetic variants on protein interaction sites, from the viewpoints of the allele frequency and the structural position of variants, we mapped about 20,000 human SNVs onto protein complexes. We found that variants are less abundant in protein interfaces, and specifically the core regions of interfaces. The tendency to “avoid” the interfacial core is stronger among common variants than rare variants. As amino acid substitutions, the trend of mutating amino acids among rare variants is consistent in different interfacial regions, reflecting the fact that rare variants result from random mutations in DNA sequences, whereas amino acid changes of common variants vary between the interfacial core and rim regions, possibly due to functional constraints on proteins. This study illustrated how the allele frequency of variants relates to the protein structural regions and the functional sites in general and will lead to deeper understanding of the potential deleteriousness of rare variants at the structural level. Exceptional cases of the observed trends will shed light on the limitations of structural approaches to evaluate the functional impacts of variants.     

Identification of protein interaction partners and protein-protein interaction sites

Rigid-body docking has become quite successful in predicting the correct conformations of binary protein complexes, at least when the constituent proteins do not undergo large conformational changes upon binding. However, determining whether two given proteins interact is a more difficult problem. Successful docking procedures often give equally good scores for proteins that do not interact experimentally. This is the case for the multiple minimization approach we use here. An analysis of the results where all proteins within a set are docked with all other proteins (complete cross-docking) shows that the predictions can be greatly improved if the location of the correct binding interface on each protein is known, since the experimental complexes are much more likely to bring these two interfaces into contact, at the same time as yielding good interaction energy scores. While various methods exist for identifying binding interfaces, it is shown that simply studying the interaction of all potential protein pairs within a data set can itself help to identify the correct interfaces.     

Beauty Is in the Eye of the Beholder: Proteins Can Recognize Binding Sites of Homologous Proteins in More than One Way

Understanding the mechanisms of protein–protein interaction is a fundamental problem with many practical applications. The fact that different proteins can bind similar partners suggests that convergently evolved binding interfaces are reused in different complexes. A set of protein complexes composed of non-homologous domains interacting with homologous partners at equivalent binding sites was collected in 2006, offering an opportunity to investigate this point. We considered 433 pairs of protein–protein complexes from the ABAC database (AB and AC binary protein complexes sharing a homologous partner A) and analyzed the extent of physico-chemical similarity at the atomic and residue level at the protein–protein interface. Homologous partners of the complexes were superimposed using Multiprot, and similar atoms at the interface were quantified using a five class grouping scheme and a distance cut-off. We found that the number of interfacial atoms with similar properties is systematically lower in the non-homologous proteins than in the homologous ones. We assessed the significance of the similarity by bootstrapping the atomic properties at the interfaces. We found that the similarity of binding sites is very significant between homologous proteins, as expected, but generally insignificant between the non-homologous proteins that bind to homologous partners. Furthermore, evolutionarily conserved residues are not colocalized within the binding sites of non-homologous proteins. We could only identify a limited number of cases of structural mimicry at the interface, suggesting that this property is less generic than previously thought. Our results support the hypothesis that different proteins can interact with similar partners using alternate strategies, but do not support convergent evolution.     

A physical reference state unifies the structure-derived potential of mean force for protein folding and binding

Extracting knowledge-based statistical potential from known structures of proteins is proved to be a simple, effective method to obtain an approximate free-energy function. However, the different compositions of amino acid residues at the core, the surface, and the binding interface of proteins prohibited the establishment of a unified statistical potential for folding and binding despite the fact that the physical basis of the interaction (water-mediated interaction between amino acids) is the same. Recently, a physical state of ideal gas, rather than a statistically averaged state, has been used as the reference state for extracting the net interaction energy between amino acid residues of monomeric proteins. Here, we find that this monomer-based potential is more accurate than an existing all-atom knowledge-based potential trained with interfacial structures of dimers in distinguishing native complex structures from docking decoys (100% success rate vs. 52% in 21 dimer/trimer decoy sets). It is also more accurate than a recently developed semiphysical empirical free-energy functional enhanced by an orientation-dependent hydrogen-bonding potential in distinguishing native state from Rosetta docking decoys (94% success rate vs. 74% in 31 antibody-antigen and other complexes based on Z score). In addition, the monomer potential achieved a 93% success rate in distinguishing true dimeric interfaces from artificial crystal interfaces. More importantly, without additional parameters, the potential provides an accurate prediction of binding free energy of protein-peptide and protein-protein complexes (a correlation coefficient of 0.87 and a root-mean-square deviation of 1.76 kcal/mol with 69 experimental data points). This work marks a significant step toward a unified knowledge-based potential that quantitatively captures the common physical principle underlying folding and binding. A Web server for academic users, established for the prediction of binding free energy and the energy evaluation of the protein-protein complexes, may be found at http://theory.med.buffalo.edu.     

Interaction of c(60)-fullerene and carboxyfullerene with proteins: docking and binding site alignment

The unique properties of fullerenes have raised the interest of using them for biomedical applications. Within this framework, the interactions of fullerenes with proteins have been an exciting research target, yet little is known about how native proteins can bind fullerenes, and what is the nature of these interactions. Moreover, though some proteins have been shown to interact with fullerenes, up to date, no crystal structure of such complexes was obtained. Here we report docking studies aimed at examining the interactions of fullerene in two forms (C60 nonsubstituted fullerene and carboxyfullerene) with four proteins that are known to bind fullerene derivatives: HIV protease, fullerene-specific antibody, human serum albumin, and bovine serum albumin. Our work provides docking models with detailed binding pockets information, which closely match available experimental data. We further compare the predicted binding sites using a novel multiple binding site alignment method. A high similarity between the physicochemical properties and surface geometry was found for fullerene's binding sites of HIV protease and the human and bovine serum albumins.     

Immunospecificity of antisera against nonhistone nuclear proteins of human lymphoid cells grown in culture

Rabbit antibodies were obtained to nonhistone protein--DNA complexes (dehistonized chromatin) prepared from two human lymphoblastoid cell lines: the Conception line from an American Burkitt lymphoma and NC-37 from a nonmalignant source. Both antisera showed a high degree of specificity for nuclear proteins of their respective cell lines. This specificity was evident in the reactivity of both whole chromatin and dehistonized chromatin using a quantitative micro-complement fixation assay. The results presented here suggest that DNA present in the antigen is necessary for maintaining the structure of the antigenic site.     

Accuracy of Protein-Protein Binding Sites in High-Throughput Template-Based Modeling

The accuracy of protein structures, particularly their binding sites, is essential for the success of modeling protein complexes. Computationally inexpensive methodology is required for genome-wide modeling of such structures. For systematic evaluation of potential accuracy in high-throughput modeling of binding sites, a statistical analysis of target-template sequence alignments was performed for a representative set of protein complexes. For most of the complexes, alignments containing all residues of the interface were found. The full interface alignments were obtained even in the case of poor alignments where a relatively small part of the target sequence (as low as 40%) aligned to the template sequence, with a low overall alignment identity (<30%). Although such poor overall alignments might be considered inadequate for modeling of whole proteins, the alignment of the interfaces was strong enough for docking. In the set of homology models built on these alignments, one third of those ranked 1 by a simple sequence identity criteria had RMSD<5 Å, the accuracy suitable for low-resolution template free docking. Such models corresponded to multi-domain target proteins, whereas for single-domain proteins the best models had 5 Å<RMSD<10 Å, the accuracy suitable for less sensitive structure-alignment methods. Overall, ∼50% of complexes with the interfaces modeled by high-throughput techniques had accuracy suitable for meaningful docking experiments. This percentage will grow with the increasing availability of co-crystallized protein-protein complexes.     

Scoring protein interaction decoys using exposed residues (SPIDER): a novel multibody interaction scoring function based on frequent geometric patterns of interfacial residues

Accurate prediction of the structure of protein-protein complexes in computational docking experiments remains a formidable challenge. It has been recognized that identifying native or native-like poses among multiple decoys is the major bottleneck of the current scoring functions used in docking. We have developed a novel multibody pose-scoring function that has no theoretical limit on the number of residues contributing to the individual interaction terms. We use a coarse-grain representation of a protein-protein complex where each residue is represented by its side chain centroid. We apply a computational geometry approach called Almost-Delaunay tessellation that transforms protein-protein complexes into a residue contact network, or an undirectional graph where vertex-residues are nodes connected by edges. This treatment forms a family of interfacial graphs representing a dataset of protein-protein complexes. We then employ frequent subgraph mining approach to identify common interfacial residue patterns that appear in at least a subset of native protein-protein interfaces. The geometrical parameters and frequency of occurrence of each "native" pattern in the training set are used to develop the new SPIDER scoring function. SPIDER was validated using standard "ZDOCK" benchmark dataset that was not used in the development of SPIDER. We demonstrate that SPIDER scoring function ranks native and native-like poses above geometrical decoys and that it exceeds in performance a popular ZRANK scoring function. SPIDER was ranked among the top scoring functions in a recent round of CAPRI (Critical Assessment of PRedicted Interactions) blind test of protein-protein docking methods.     

Resonant recognition model and protein topography. Model studies with myoglobin, hemoglobin and lysozyme

This study describes the further extension of the resonant recognition model for the analysis and prediction of protein--protein and protein--DNA structure/function dependencies. The model is based on the significant correlation between spectra of numerical presentations of the amino acid or nucleotide sequences of proteins and their coded biological activity. According to this physico-mathematical method, it is possible to define amino acids in the sequence which are predicted to be the most critical for protein function. Using sperm whale myoglobin, human hemoglobin and hen egg white lysozyme as model protein examples, sets of predicted amino acids, or so-called 'hot spots', have been identified within the tertiary structure. It was found for each protein that the predicted 'hot spots', which are distributed along the primary sequence, are spatially grouped in a dome-like arrangement over the active site. The identified amino acids did not correspond to the amino acid residues which are involved in the chemical reaction site of these proteins. It is thus proposed that the resonant recognition model helps to identify amino acid residues which are important for the creation of the molecular structure around the catalytic active site and also the associated physical field conditions required for biorecognition, docking of the specific substrate and full biological activity.     

Substitution rates in α-helical transmembrane proteins

It has been shown previously that some membrane proteins have a conserved core of amino acid residues. This idea not only serves to orient helices during model building exercises but may also provide insight into the structural role of residues mediating helix-helix interactions. Using experimentally determined high-resolution structures of alpha-helical transmembrane proteins we show that, of the residues within the hydrophobic transmembrane spans, the residues at lipid and subunit interfaces are more evolutionarily variable than those within the lipid-inaccessible core of a polypeptide's transmembrane domain. This supports the idea that helix-helix interactions within the same polypeptide chain and those at the interface between different polypeptide chains may arise in distinct ways. To show this, we use a new method to estimate the substitution rate of an amino acid residue given an alignment and phylogenetic tree of closely related proteins. This method gives better sensitivity in the otherwise-conserved transmembrane domains than a conventional similarity analysis and is relatively insensitive to the sequences used.     

Sequence-specific positioning of core histones on an 860 base-pair DNA. Experiment and theory

Previous experiments have shown that the locations of the histone octamer on DNA molecules of 140 to 240 base-pairs (bp) are influenced strongly by the nucleotide sequence. Here we have studied the locations of the histone octamer on a relatively long DNA molecule of 860 bp, using two different nucleases, micrococcal and DNAase I. Data were obtained from both the protein--DNA complexes and from the naked DNA at single-bond resolution, and then were analyzed by densitometry to yield plots of differential cleavage, which show clearly the changes in cutting due to the addition of protein. Our results show that the placement of core histones on the 860 bp molecule is definitely non-random. The digestion data provide evidence for five nucleosome cores, the centers of which lie in defined locations. In all but one of these protein--DNA complexes, the DNA adopts a unique, highly preferred rotational setting with respect to the protein surface. Another protein--DNA complex is unusual in that it protects 200 bp from digestion, yet is cut in its very center as if it were split into two parts. The apparent average twist of the DNA within all of these protein--DNA complexes is 10.2(+/- 0.1) bp, as measured by the periodicity of DNAase I digestion. This value is in excellent agreement with the twist of 10.21(+/- 0.05) bp deduced from the periodicity of sequence content in chicken nucleosome core DNA. In addition, we observe a discontinuity in the periodic cutting by DNAase I of about -1 to -3 bonds in going from any nucleosome core to the next. The most plausible interpretation of this discontinuity is that it reflects the angle by which adjacent protein--DNA complexes are aligned. Thus, any nucleosome may be related to its neighbor by a left-handed rotation in space of -1/10.2 to -3/10.2 helix turns, or -35 degrees to -105 degrees. Repeated many times, this operation would build a long, left-handed helix of nucleosomes similar to that described by many workers for the packing of nucleosomes in chromatin. In order to look for any long-range influences on the positioning of the histone octamer in the 860 bp molecule (as would be expected if the nucleosomes have to fit into some higher-order structure), we have examined the locations of the histone octamer on five different isolated short fragments of the 860-mer, all of nucleosomal length.(ABSTRACT TRUNCATED AT 400 WORDS)     

Protein Docking by the Interface Structure Similarity: How Much Structure Is Needed?

The increasing availability of co-crystallized protein-protein complexes provides an opportunity to use template-based modeling for protein-protein docking. Structure alignment techniques are useful in detection of remote target-template similarities. The size of the structure involved in the alignment is important for the success in modeling. This paper describes a systematic large-scale study to find the optimal definition/size of the interfaces for the structure alignment-based docking applications. The results showed that structural areas corresponding to the cutoff values <12 Å across the interface inadequately represent structural details of the interfaces. With the increase of the cutoff beyond 12 Å, the success rate for the benchmark set of 99 protein complexes, did not increase significantly for higher accuracy models, and decreased for lower-accuracy models. The 12 Å cutoff was optimal in our interface alignment-based docking, and a likely best choice for the large-scale (e.g., on the scale of the entire genome) applications to protein interaction networks. The results provide guidelines for the docking approaches, including high-throughput applications to modeled structures.     

Optimal contact map alignment of protein-protein interfaces

The long-standing problem of constructing protein structure alignments is of central importance in computational biology. The main goal is to provide an alignment of residue correspondences, in order to identify homologous residues across chains. A critical next step of this is the alignment of protein complexes and their interfaces. Here, we introduce the program CMAPi, a two-dimensional dynamic programming algorithm that, given a pair of protein complexes, optimally aligns the contact maps of their interfaces: it produces polynomial-time near-optimal alignments in the case of multiple complexes. We demonstrate the efficacy of our algorithm on complexes from PPI families listed in the SCOPPI database and from highly divergent cytokine families. In comparison to existing techniques, CMAPi generates more accurate alignments of interacting residues within families of interacting proteins, especially for sequences with low similarity. While previous methods that use an all-atom based representation of the interface have been successful, CMAPi's use of a contact map representation allows it to be more tolerant to conformational changes and thus to align more of the interaction surface. These improved interface alignments should enhance homology modeling and threading methods for predicting PPIs by providing a basis for generating template profiles for sequence-structure alignment.     

Interaction of transmembrane helices by a knobs-into-holes packing characteristic of soluble coiled coils

Membrane-embedded protein domains frequently exist as α-helical bundles, as exemplified by photosynthetic reaction centers, bacteriorhodopsin, and cytochrome C oxidase. The sidechain packing between their transmembrane helices was investigated by a nearest-neighbor analysis which identified sets of interfacial residues for each analyzed helix–helix interface. For the left-handed helix–helix pairs, the interfacial residues almost exclusively occupy positions a, d, e, or g within a heptad motif (abcdefg) which is repeated two to three times for each interacting helical surface. The connectivity between the interfacial residues of adjacent helices conforms to the knobs-into-holes type of sidechain packing known from soluble coiled coils. These results demonstrate on a quantitative basis that the geometry of sidechain packing is similar for left-handed helix–helix pairs embedded in membranes and coiled coils of soluble proteins. The transmembrane helix–helix interfaces studied are somewhat less compact and regular as compared to soluble coiled coils and tolerate all hydrophobic amino acid types to similar degrees. The results are discussed with respect to previous experimental findings which demonstrate that specific interactions between transmembrane helices are important for membrane protein folding and/or oligomerization. Proteins 31:150–159, 1998. © 1998 Wiley-Liss, Inc.     

Modelling repressor proteins docking to DNA

The docking of repressor proteins to DNA starting from the unbound protein and model-built DNA coordinates is modeled computationally. The approach was evaluated on eight repressor/DNA complexes that employed different modes for protein/ DNA recognition. The global search is based on a protein-protein docking algorithm that evaluates shape and electrostatic complementarity, which was modified to consider the importance of electrostatic features in DNA-protein recognition. Complexes were then ranked by an empirical score for the observed amino acid /nucleotide pairings (i.e., protein-DNA pair potentials) derived from a database of 20 protein/DNA complexes. A good prediction had at least 65% of the correct contacts modeled. This approach was able to identify a good solution at rank four or better for three out of the eight complexes. Predicted complexes were filtered by a distance constraint based on experimental data defining the DNA footprint. This improved coverage to four out of eight complexes having a good model at rank four or better. The additional use of amino acid mutagenesis and phylogenetic data defining residues on the repressor resulted in between 2 and 27 models that would have to be examined to find a good solution for seven of the eight test systems. This study shows that starting with unbound coordinates one can predict three-dimensional models for protein/DNA complexes that do not involve gross conformational changes on association. Proteins 33:535–549, 1998. © 1998 Wiley-Liss, Inc.