Marc F. Lensink

Assessment of CAPRI predictions in rounds 3–5 shows progress in docking procedures

The current status of docking procedures for predicting protein–protein interactions starting from their three‐dimensional (3D) structure is reassessed by evaluating blind predictions, performed during 2003–2004 as part of Rounds 3–5 of the community‐wide experiment on Critical Assessment of PRedicted Interactions (CAPRI). Ten newly determined structures of protein–protein complexes were used as targets for these rounds. They comprised 2 enzyme–inhibitor complexes, 2 antigen–antibody complexes, 2 complexes involved in cellular signaling, 2 homo‐oligomers, and a complex between 2 components of the bacterial cellulosome. For most targets, the predictors were given the experimental structures of 1 unbound and 1 bound component, with the latter in a random orientation. For some, the structure of the free component was derived from that of a related protein, requiring the use of homology modeling. In some of the targets, significant differences in conformation were displayed between the bound and unbound components, representing a major challenge for the docking procedures. For 1 target, predictions could not go to completion. In total, 1866 predictions submitted by 30 groups were evaluated. Over one‐third of these groups applied completely novel docking algorithms and scoring functions, with several of them specifically addressing the challenge of dealing with side‐chain and backbone flexibility. The quality of the predicted interactions was evaluated by comparison to the experimental structures of the targets, made available for the evaluation, using the well‐agreed‐upon criteria used previously. Twenty‐four groups, which for the first time included an automatic Web server, produced predictions ranking from acceptable to highly accurate for all targets, including those where the structures of the bound and unbound forms differed substantially. These results and a brief survey of the methods used by participants of CAPRI Rounds 3–5 suggest that genuine progress in the performance of docking methods is being achieved, with CAPRI acting as the catalyst. Proteins 2005;60:150–169.

Docking and scoring protein complexes: CAPRI 3rd Edition

The performance of methods for predicting protein–protein interactions at the atomic scale is assessed by evaluating blind predictions performed during 2005–2007 as part of Rounds 6–12 of the community‐wide experiment on Critical Assessment of PRedicted Interactions (CAPRI). These Rounds also included a new scoring experiment, where a larger set of models contributed by the predictors was made available to groups developing scoring functions. These groups scored the uploaded set and submitted their own best models for assessment. The structures of nine protein complexes including one homodimer were used as targets. These targets represent biologically relevant interactions involved in gene expression, signal transduction, RNA, or protein processing and membrane maintenance. For all the targets except one, predictions started from the experimentally determined structures of the free (unbound) components or from models derived by homology, making it mandatory for docking methods to model the conformational changes that often accompany association. In total, 63 groups and eight automatic servers, a substantial increase from previous years, submitted docking predictions, of which 1994 were evaluated here. Fifteen groups submitted 305 models for five targets in the scoring experiment. Assessment of the predictions reveals that 31 different groups produced models of acceptable and medium accuracy‐but only one high accuracy submission‐for all the targets, except the homodimer. In the latter, none of the docking procedures reproduced the large conformational adjustment required for correct assembly, underscoring yet again that handling protein flexibility remains a major challenge. In the scoring experiment, a large fraction of the groups attained the set goal of singling out the correct association modes from incorrect solutions in the limited ensembles of contributed models. But in general they seemed unable to identify the best models, indicating that current scoring methods are probably not sensitive enough. With the increased focus on protein assemblies, in particular by structural genomics efforts, the growing community of CAPRI predictors is engaged more actively than ever in the development of better scoring functions and means of modeling conformational flexibility, which hold promise for much progress in the future. Proteins 2007.

Docking and scoring protein interactions: CAPRI 2009

Protein docking algorithms are assessed by evaluating blind predictions performed during 2007–2009 in Rounds 13–19 of the community‐wide experiment on critical assessment of predicted interactions (CAPRI). We evaluated the ability of these algorithms to sample docking poses and to single out specific association modes in 14 targets, representing 11 distinct protein complexes. These complexes play important biological roles in RNA maturation, G‐protein signal processing, and enzyme inhibition and function. One target involved protein–RNA interactions not previously considered in CAPRI, several others were hetero‐oligomers, or featured multiple interfaces between the same protein pair. For most targets, predictions started from the experimentally determined structures of the free (unbound) components, or from models built from known structures of related or similar proteins. To succeed they therefore needed to account for conformational changes and model inaccuracies. In total, 64 groups and 12 web‐servers submitted docking predictions of which 4420 were evaluated. Overall our assessment reveals that 67% of the groups, more than ever before, produced acceptable models or better for at least one target, with many groups submitting multiple high‐ and medium‐accuracy models for two to six targets. Forty‐one groups including four web‐servers participated in the scoring experiment with 1296 evaluated models. Scoring predictions also show signs of progress evidenced from the large proportion of correct models submitted. But singling out the best models remains a challenge, which also adversely affects the ability to correctly rank docking models. With the increased interest in translating abstract protein interaction networks into realistic models of protein assemblies, the growing CAPRI community is actively developing more efficient and reliable docking and scoring methods for everyone to use. Proteins 2010.

Docking, scoring, and affinity prediction in CAPRI

We present the fifth evaluation of docking and related scoring methods used in the community‐wide experiment on the Critical Assessment of Predicted Interactions (CAPRI). The evaluation examined predictions submitted for a total of 15 targets in eight CAPRI rounds held during the years 2010–2012. The targets represented one the most diverse set tackled by the CAPRI community so far. They included only 10 “classical” docking and scoring problems. In one of the classical targets, the new challenge was to predict the position of water molecules in the protein–protein interface. The remaining five targets represented other new challenges that involved estimating the relative binding affinity and the effect of point mutations on the stability of designed and natural protein–protein complexes. Although the 10 classical CAPRI targets included two difficult multicomponent systems, and a protein–oligosaccharide complex with which CAPRI participants had little experience, this evaluation indicates that the performance of docking and scoring methods has remained quite robust. More remarkably, we find that automatic docking servers exhibit a significantly improved performance, with some servers now performing on par with predictions done by humans. The performance of CAPRI participants in the new challenges, briefly reviewed here, was mediocre overall, but some groups did relatively well and their approaches suggested ways of improving methods for designing binders and for estimating the free energies of protein assemblies, which should impact the field of protein modeling and design as a whole. Proteins 2013; 81:2082–2095.

Blind predictions of protein interfaces by docking calculations in CAPRI

Reliable prediction of the amino acid residues involved in protein–protein interfaces can provide valuable insight into protein function, and inform mutagenesis studies, and drug design applications. A fast‐growing number of methods are being proposed for predicting protein interfaces, using structural information, energetic criteria, or sequence conservation or by integrating multiple criteria and approaches. Overall however, their performance remains limited, especially when applied to nonobligate protein complexes, where the individual components are also stable on their own. Here, we evaluate interface predictions derived from protein–protein docking calculations. To this end we measure the overlap between the interfaces in models of protein complexes submitted by 76 participants in CAPRI (Critical Assessment of Predicted Interactions) and those of 46 observed interfaces in 20 CAPRI targets corresponding to nonobligate complexes. Our evaluation considers multiple models for each target interface, submitted by different participants, using a variety of docking methods. Although this results in a substantial variability in the prediction performance across participants and targets, clear trends emerge. Docking methods that perform best in our evaluation predict interfaces with average recall and precision levels of about 60%, for a small majority (60%) of the analyzed interfaces. These levels are significantly higher than those obtained for nonobligate complexes by most extant interface prediction methods. We find furthermore that a sizable fraction (24%) of the interfaces in models ranked as incorrect in the CAPRI assessment are actually correctly predicted (recall and precision ≥50%), and that these models contribute to 70% of the correct docking‐based interface predictions overall. Our analysis proves that docking methods are much more successful in identifying interfaces than in predicting complexes, and suggests that these methods have an excellent potential of addressing the interface prediction challenge. Proteins 2010.

LigASite--a database of biologically relevant binding sites in proteins with known apo-structures.

Better characterization of binding sites in proteins and the ability to accurately predict their location and energetic properties are major challenges which, if addressed, would have many valuable practical applications. Unfortunately, reliable benchmark datasets of binding sites in proteins are still sorely lacking. Here, we present LigASite (‘LIGand Attachment SITE’), a gold-standard dataset of binding sites in 550 proteins of known structures. LigASite consists exclusively of biologically relevant binding sites in proteins for which at least one apo- and one holo-structure are available. In defining the binding sites for each protein, information from all holo-structures is combined, considering in each case the quaternary structure defined by the PQS server. LigASite is built using simple criteria and is automatically updated as new structures become available in the PDB, thereby guaranteeing optimal data coverage over time. Both a redundant and a culled non-redundant version of the dataset is available at http://www.scmbb.ulb.ac.be/Users/benoit/LigASite. The website interface allows users to search the dataset by PDB identifiers, ligand identifiers, protein names or sequence, and to look for structural matches as defined by the CATH homologous superfamilies. The datasets can be downloaded from the website as Schema-validated XML files or comma-separated flat files.

Phosphorylation by Protein Kinase CK2 Modulates the Activity of the ATP Binding Cassette A1 Transporter

In a previous characterization of the ABCA subfamily of the ATP-binding cassette (ABC) transporters, we identified potential protein kinase 2 (CK2) phosphorylation sites, which are conserved in eukaryotic and prokaryotic members of the ABCA transporters (Peelman, F., Labeur, C., Vanloo, B., Roosbeek, S., Devaud, C., Duverger, N., Denefle, P., Rosier, M., Vandekerckhove, J., and Rosseneu, M. (2003) J. Mol. Biol. 325, 259-274). These phosphorylation residues are located in the conserved cytoplamic R1 and R2 domains, downstream of the nucleotide binding domains NBD1 and NBD2. To study the possible regulation of the ABCA1 transporter by CK2, we expressed the recombinant cytoplasmic domains of ABCA1, NBD1+R1 and NBD2+R2. We demonstrated that in vitro ABCA1 NBD1+R1, and not NBD2+R2, is phosphorylated by CK2, and we identified Thr-1242, Thr-1243, and Ser-1255 as the phosphorylated residues in the R1 domain by mass spectrometry. We further investigated the functional significance of the threonine and serine phosphorylation sites in NBD1 by site-directed mutagenesis of the entire ABCA1 followed by transfection into Hek-293 Tet-Off cells. The ABCA1 flippase activity, apolipoprotein AI and AII binding, and cellular phospholipid and cholesterol efflux were enhanced by mutations preventing CK2 phosphorylation of the threonine and serine residues. This was confirmed by the effect of specific protein kinase CK2 inhibitors upon the activity of wild type and mutant ABCA1 in transfected Hek-293 Tet-Off cells. The activities of the mutants mimicking threonine phosphorylation were close to that of wild type ABCA1. Our data, therefore, suggest that besides protein kinase A and C, protein kinase CK2 might play an important role in vivo in regulating the function and transport activity of ABCA1 and possibly of other members of the ABCA subfamily.

Signal transduction in the photoactive yellow protein. I. Photon absorption and the isomerization of the chromophore

Molecular dynamics simulation techniques together with time‐dependent density functional theory calculations have been used to investigate the effect of photon absorption by a 4‐hydroxy‐cinnamic acid chromophore on the structural properties of the photoactive yellow protein (PYP) from Ectothiorodospira halophila. The calculations suggest that the protein not only modifies the absorption spectrum of the chromophore but also regulates the subsequent isomerization of the chromophore by stabilizing the isomerization transition state. Although signaling from PYP is thought to involve partial unfolding of the protein, the mechanical effects accompanying isomerization do not appear to directly destabilize the protein. Proteins 2002;48:202–211.

Homology-based modeling of 3D structures of protein-protein complexes using alignments of modified sequence profiles.

Customary practice in predicting 3D structures of protein-protein complexes is employment of various docking methods when the structures of separate monomers are known a priori. The alternative approach, i.e. the template-based prediction with pure sequence information as a starting point, is still considered as being inferior mostly due to presumption that the pool of available structures of protein-protein complexes, which can serve as putative templates, is not sufficiently large. Recently, however, several labs have developed databases containing thousands of 3D structures of protein-protein complexes, which enable statistically reliable testing of homology-based algorithms. In this paper we report the results on homology-based modeling of 3D structures of protein complexes using alignments of modified sequence profiles. The method, called HOMology-BAsed COmplex Prediction (HOMBACOP), has two distinctive features: (I) extra weight on aligning interfacial residues in the dynamical programming algorithm, and (II) increased gap penalties for the interfacial segments. The method was tested against our recently developed ProtCom database and against the Boston University protein-protein BENCHMARK. In both cases, models generated were compared to the models built on basis of customarily protein structure initiative (PSI)-BLAST sequence alignments. It was found that existence of homologous (by the means of PSI-BLAST) templates (44% of cases) enables both methods to produce models of good quality, with the profiles method outperforming the PSI-BLAST models (with respect to the percentage of correctly predicted residues on the complex interface and fraction of native interfacial contacts). The models were evaluated according to the CAPRI assessment criteria and about two thirds of the models were found to fall into acceptable and medium-quality categories. The same comparison of a larger set of 463 protein complexes showed again that profiles generate better models. We further demonstrate, using our ProtCom database, the suitability of the profile alignment algorithm in detecting remote homologues between query and template sequences, where the PSI-BLAST method fails.

Modeling protein-protein and protein-peptide complexes: CAPRI 6th edition.

We present the sixth report evaluating the performance of methods for predicting the atomic resolution structures of protein complexes offered as targets to the community‐wide initiative on the Critical Assessment of Predicted Interactions (CAPRI). The evaluation is based on a total of 20,670 predicted models for 8 protein–peptide complexes, a novel category of targets in CAPRI, and 12 protein–protein targets in CAPRI prediction Rounds held during the years 2013‐2016. For two of the protein–protein targets, the focus was on the prediction of side‐chain conformation and positions of interfacial water molecules. Seven of the protein–protein targets were particularly challenging owing to their multicomponent nature, to conformational changes at the binding site, or to a combination of both. Encouragingly, the very large multiprotein complex with the nucleosome was correctly predicted, and correct models were submitted for the protein–peptide targets, but not for some of the challenging protein–protein targets. Models of acceptable quality or better were obtained for 14 of the 20 targets, including medium quality models for 13 targets and high quality models for 8 targets, indicating tangible progress of present‐day computational methods in modeling protein complexes with increased accuracy. Our evaluation suggests that the progress stems from better integration of different modeling tools with docking procedures, as well as the use of more sophisticated evolutionary information to score models. Nonetheless, adequate modeling of conformational flexibility in interacting proteins remains an important area with a crucial need for improvement. Proteins 2017; 85:359–377.