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Our information-driven docking approach HADDOCK is a consistent top predictor and scorer since the start of its participation in the CAPRI community-wide experiment. This sustained performance is due, in part, to its ability to integrate experimental data and/or bioinformatics information into the modelling process, and also to the overall robustness of the scoring function used to assess and rank the predictions. In the CASP-CAPRI Round 1 scoring experiment we successfully selected acceptable/medium quality models for 18/14 of the 25 targets - a top-ranking performance among all scorers. Considering that for only 20 targets acceptable models were generated by the community, our effective success rate reaches as high as 90% (18/20). This was achieved using the standard HADDOCK scoring function, which, thirteen years after its original publication, still consists of a simple linear combination of intermolecular van der Waals and Coulomb electrostatics energies and an empirically derived desolvation energy term. Despite its simplicity, this scoring function makes sense from a physico-chemical perspective, encoding key aspects of biomolecular recognition. In addition to its success in the scoring experiment, the HADDOCK server takes the first place in the server prediction category, with 16 successful predictions. Much like our scoring protocol, because of the limited time per target, the predictions relied mainly on either an ab initio center-of-mass and symmetry restrained protocol, or on a template-based approach whenever applicable. These results underline the success of our simple but sensible prediction and scoring scheme. Proteins 2017; 85:417-423. © 2016 Wiley Periodicals, Inc., (© 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.)

Protein docking procedures carry out the task of predicting the structure of a protein-protein complex starting from the known structures of the individual protein components. More often than not, however, the structure of one or both components is not known, but can be derived by homology modeling on the basis of known structures of related proteins deposited in the Protein Data Bank (PDB). Thus, the problem is to develop methods that optimally integrate homology modeling and docking with the goal of predicting the structure of a complex directly from the amino acid sequences of its component proteins. One possibility is to use the best available homology modeling and docking methods. However, the models built for the individual subunits often differ to a significant degree from the bound conformation in the complex, often much more so than the differences observed between free and bound structures of the same protein, and therefore additional conformational adjustments, both at the backbone and side chain levels need to be modeled to achieve an accurate docking prediction. In particular, even homology models of overall good accuracy frequently include localized errors that unfavorably impact docking results. The predicted reliability of the different regions in the model can also serve as a useful input for the docking calculations. Here we present a benchmark dataset that should help to explore and solve combined modeling and docking problems. This dataset comprises a subset of the experimentally solved 'target' complexes from the widely used Docking Benchmark from the Weng Lab (excluding antibody-antigen complexes). This subset is extended to include the structures from the PDB related to those of the individual components of each complex, and hence represent potential templates for investigating and benchmarking integrated homology modeling and docking approaches. Template sets can be dynamically customized by specifying ranges in sequence similarity and in PDB release dates, or using other filtering options, such as excluding sets of specific structures from the template list. Multiple sequence alignments, as well as structural alignments of the templates to their corresponding subunits in the target are also provided. The resource is accessible online or can be downloaded at http://cluspro.org/benchmark, and is updated on a weekly basis in synchrony with new PDB releases. Proteins 2016; 85:10-16. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. Proteins 2016; 84(Suppl 1):323-348. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

Protein-protein interactions control a plethora of cellular processes, including cell proliferation, differentiation, apoptosis, and signal transduction. Understanding how and why proteins interact will inevitably lead to novel structure-based drug design methods, as well as design of de novo binders with preferred interaction properties. At a structural and molecular level, interface and rim regions are not enough to fully account for the energetics of protein-protein binding, even for simple lock-and-key rigid binders. As we have recently shown, properties of the global surface might also play a role in protein-protein interactions. Here, we report on molecular dynamics simulations performed to understand solvent effects on protein-protein surfaces. We compare properties of the interface, rim, and non-interacting surface regions for five different complexes and their free components. Interface and rim residues become, as expected, less mobile upon complexation. However, non-interacting surface appears more flexible in the complex. Fluctuations of polar residues are always lower compared with charged ones, independent of the protein state. Further, stable water molecules are often observed around polar residues, in contrast to charged ones. Our analysis reveals that (a) upon complexation, the non-interacting surface can have a direct entropic compensation for the lower interface and rim entropy and (b) the mobility of the first hydration layer, which is linked to the stability of the protein-protein complex, is influenced by the local chemical properties of the surface. These findings corroborate previous hypotheses on the role of the hydration layer in shielding protein-protein complexes from unintended protein-protein interactions., (© 2014 Wiley Periodicals, Inc.)

We report the first assessment of blind predictions of water positions at protein-protein interfaces, performed as part of the critical assessment of predicted interactions (CAPRI) community-wide experiment. Groups submitting docking predictions for the complex of the DNase domain of colicin E2 and Im2 immunity protein (CAPRI Target 47), were invited to predict the positions of interfacial water molecules using the method of their choice. The predictions-20 groups submitted a total of 195 models-were assessed by measuring the recall fraction of water-mediated protein contacts. Of the 176 high- or medium-quality docking models-a very good docking performance per se-only 44% had a recall fraction above 0.3, and a mere 6% above 0.5. The actual water positions were in general predicted to an accuracy level no better than 1.5 Å, and even in good models about half of the contacts represented false positives. This notwithstanding, three hotspot interface water positions were quite well predicted, and so was one of the water positions that is believed to stabilize the loop that confers specificity in these complexes. Overall the best interface water predictions was achieved by groups that also produced high-quality docking models, indicating that accurate modelling of the protein portion is a determinant factor. The use of established molecular mechanics force fields, coupled to sampling and optimization procedures also seemed to confer an advantage. Insights gained from this analysis should help improve the prediction of protein-water interactions and their role in stabilizing protein complexes., (Copyright © 2013 Wiley Periodicals, Inc.)

Information-driven docking is currently one of the most successful approaches to obtain structural models of protein interactions as demonstrated in the latest round of CAPRI. While various experimental and computational techniques can be used to retrieve information about the binding mode, the availability of three-dimensional structures of the interacting partners remains a limiting factor. Fortunately, the wealth of structural information gathered by large-scale initiatives allows for homology-based modeling of a significant fraction of the protein universe. Defining the limits of information-driven docking based on such homology models is therefore highly relevant. Here we show, using previous CAPRI targets, that out of a variety of measures, the global sequence identity between template and target is a simple but reliable predictor of the achievable quality of the docking models. This indicates that a well-defined overall fold is critical for the interaction. Furthermore, the quality of the data at our disposal to characterize the interaction plays a determinant role in the success of the docking. Given reliable interface information we can obtain acceptable predictions even at low global sequence identity. These results, which define the boundaries between trustworthy and unreliable predictions, should guide both experts and nonexperts in defining the limits of what is achievable by docking. This is highly relevant considering that the fraction of the interactome amenable for docking is only bound to grow as the number of experimentally solved structures increases., (Copyright © 2013 Wiley Periodicals, Inc.)

Community-wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community-wide assessment of methods to predict the effects of mutations on protein-protein interactions. Twenty-two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side-chain sampling and backbone relaxation, evaluated packing, electrostatic, and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large-scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of both existing and new prediction methodologies., (© 2013 Wiley Periodicals, Inc.)

HADDOCK is one of the few docking programs that can explicitly account for water molecules in the docking process. Its solvated docking protocol starts from hydrated molecules and a fraction of the resulting interfacial waters is subsequently removed in a biased Monte Carlo procedure based on water-mediated contact probabilities. The latter were derived from an analysis of water contact frequencies from high-resolution crystal structures. Here, we introduce a simple water-mediated amino acid-amino acid contact probability scale derived from the Kyte-Doolittle hydrophobicity scale and assess its performance on the largest high-resolution dataset developed to date for solvated docking. Both scales yield high-quality docking results. The novel and simple hydrophobicity scale, which should reflect better the physicochemical principles underlying contact propensities, leads to a performance improvement of around 10% in ranking, cluster quality and water recovery at the interface compared with the statistics-based original solvated docking protocol., (Copyright © 2012 Wiley Periodicals, Inc.)

Inaccuracies in computational molecular modeling methods are often counterweighed by brute-force generation of a plethora of putative solutions. These are then typically sieved via structural clustering based on similarity measures such as the root mean square deviation (RMSD) of atomic positions. Albeit widely used, these measures suffer from several theoretical and technical limitations (e.g., choice of regions for fitting) that impair their application in multicomponent systems (N > 2), large-scale studies (e.g., interactomes), and other time-critical scenarios. We present here a simple similarity measure for structural clustering based on atomic contacts--the fraction of common contacts--and compare it with the most used similarity measure of the protein docking community--interface backbone RMSD. We show that this method produces very compact clusters in remarkably short time when applied to a collection of binary and multicomponent protein-protein and protein-DNA complexes. Furthermore, it allows easy clustering of similar conformations of multicomponent symmetrical assemblies in which chain permutations can occur. Simple contact-based metrics should be applicable to other structural biology clustering problems, in particular for time-critical or large-scale endeavors., (Copyright © 2012 Wiley Periodicals, Inc.)

Despite recent advances in the modeling of protein-protein complexes by docking, additional information is often required to identify the best solutions. For this purpose, NMR data deliver valuable restraints that can be used in the sampling and/or the scoring stage, like in the data-driven docking approach HADDOCK that can make use of NMR chemical shift perturbation (CSP) data to define the binding site on each protein and drive the docking. We show here that a quantitative use of chemical shifts (CS) in the scoring stage can help to resolve ambiguities. A quantitative CS-RMSD score based on (1) H(α) ,(13) C(α) , and (15) N chemical shifts ranks the best solutions always at the top, as demonstrated on a small benchmark of four complexes. It is implemented in a new docking protocol, CS-HADDOCK, which combines CSP data as ambiguous interaction restraints in the sampling stage with the CS-RMSD score in the final scoring stage. This combination of qualitative and quantitative use of chemical shifts increases the reliability of data-driven docking for the structure determination of complexes from limited NMR data., (Copyright © 2011 Wiley-Liss, Inc.)

The recent CAPRI rounds have introduced new docking challenges in the form of protein-RNA complexes, multiple alternative interfaces, and an unprecedented number of targets for which homology modeling was required. We present here the performance of HADDOCK and its web server in the CAPRI experiment and discuss the strengths and weaknesses of data-driven docking. HADDOCK was successful for 6 out of 9 complexes (6 out of 11 targets) and accurately predicted the individual interfaces for two more complexes. The HADDOCK server, which is the first allowing the simultaneous docking of generic multi-body complexes, was successful in 4 out of 7 complexes for which it participated. In the scoring experiment, we predicted the highest number of targets of any group. The main weakness of data-driven docking revealed from these last CAPRI results is its vulnerability for incorrect experimental data related to the interface or the stoichiometry of the complex. At the same time, the use of experimental and/or predicted information is also the strength of our approach as evidenced for those targets for which accurate experimental information was available (e.g., the 10 three-stars predictions for T40!). Even when the models show a wrong orientation, the individual interfaces are generally well predicted with an average coverage of 60% ± 26% over all targets. This makes data-driven docking particularly valuable in a biological context to guide experimental studies like, for example, targeted mutagenesis., (© 2010 Wiley-Liss, Inc.)

In nature, some proteins partially unfold under specific environmental conditions. These unfolded states typically consist of a large ensemble of conformations; their proper description is therefore a challenging problem. NMR spectroscopy is particularly well suited for this task: information on conformational preferences can be derived, for example, from chemical shifts or residual dipolar couplings. This information, which is measured as a time- and ensemble-average, can be used to model these states by generating large ensembles of conformations. The challenge is then to select a minimum representative set of conformations out of a large ensemble to represent the unfolded state. We have developed for this purpose an algorithm called MINOES (MINimum Optimal Ensemble Selection), which is based on an iterative procedure based on a driven expansion/contraction selection process. MINOES aims at selecting an optimal and minimal ensemble of conformations that, on average, maximizes the agreement between back-calculated and experimental (NMR) data, without any a-priori assumption about the required ensemble size. This approach is demonstrated by modeling the partially unfolded state of a deletion mutant of the Photoactive Yellow Protein, Delta25-PYP, which has been previously characterized by NMR (Bernard et al., Structure 2005;13:953-962).

The human LINE-1 endonuclease (L1-EN) contributes in defining the genomic integration sites of the abundant human L1 and Alu retrotransposons. LINEs have been considered as possible vehicles for gene delivery and understanding the mechanism of L1-EN could help engineering them as genetic tools. We tested the in vitro activity of point mutants in three L1-EN residues--Asp145, Arg155, Ile204--that are key for DNA cleavage, and determined their crystal structures. The L1-EN structure remains overall unaffected by the mutations, which change the enzyme activity but leave DNA cleavage sequence specificity mostly unaffected. To better understand the mechanism of L1-EN, we performed molecular dynamics simulations using as model the structures of wild type EN-L1, of two betaB6-betaB5 loop exchange mutants we have described previously to be important for DNA recognition, of the R155A mutant from this study, and of the homologous TRAS1 endonuclease: all confirm a rigid scaffold. The simulations crucially indicate that the betaB6-betaB5 loop shows an anticorrelated motion with the surface loops betaA6-betaA5 and betaB3-alphaB1. The latter loop harbors N118, a residue that alters DNA cleavage specificity in homologous endonucleases, and implies that the plasticity and correlated motion of these loops has a functional importance in DNA recognition and binding. To further explore how these loops are possibly involved in DNA binding, we docked computationally two DNA substrates to our structure, one involving a flipped-out nucleotide downstream the scissile phosphodiester; and one not. The models for both scenarios are feasible and agree with the hypotheses derived from the dynamic simulations. The reduced cleavage activity we have observed for the I204Y mutant above however, favors the flipped out nucleotide model.

Skeletal alpha-tropomyosin (Tm) is a dimeric coiled-coil protein that forms linear assemblies under low ionic strength conditions in vitro through head-to-tail interactions. A previously published NMR structure of the Tm head-to-tail complex revealed that it is formed by the insertion of the N-terminal coiled-coil of one molecule into a cleft formed by the separation of the helices at the C-terminus of a second molecule. To evaluate the contribution of charged residues to complex stability, we employed single and double-mutant Tm fragments in which specific charged residues were changed to alanine in head-to-tail binding assays, and the effects of the mutations were analyzed by thermodynamic double-mutant cycles and protein-protein docking. The results show that residues K5, K7, and D280 are essential to the stability of the complex. Though D2, K6, D275, and H276 are exposed to the solvent and do not participate in intermolecular contacts in the NMR structure, they may contribute to head-to-tail complex stability by modulating the stability of the helices at the Tm termini.

Here we present version 2.0 of HADDOCK, which incorporates considerable improvements and new features. HADDOCK is now able to model not only protein-protein complexes but also other kinds of biomolecular complexes and multi-component (N > 2) systems. In the absence of any experimental and/or predicted information to drive the docking, HADDOCK now offers two additional ab initio docking modes based on either random patch definition or center-of-mass restraints. The docking protocol has been considerably improved, supporting among other solvated docking, automatic definition of semi-flexible regions, and inclusion of a desolvation energy term in the scoring scheme. The performance of HADDOCK2.0 is evaluated on the targets of rounds 4-11, run in a semi-automated mode using the original information we used in our CAPRI submissions. This enables a direct assessment of the progress made since the previous versions. Although HADDOCK performed very well in CAPRI (65% and 71% success rates, overall and for unbound targets only, respectively), a substantial improvement was achieved with HADDOCK2.0., ((c) 2007 Wiley-Liss, Inc.)

Chicken liver bile acid binding protein (cL-BABP) is involved in bile acid transport in the liver cytosol. A detailed study of the mechanism of binding and selectivity of bile acids binding proteins towards the physiological pool of bile salts is a key issue for the complete understanding of the role of these proteins and their involvement in cholesterol homeostasis. In the present study, we modeled the ternary complex of cL-BABP with two molecules of bile salts using the data driven docking program HADDOCK on the basis of NMR and mass spectrometry data. Docking resulted in good 3D models, satisfying the majority of experimental restraints. The docking procedure represents a necessary step to help in the structure determination and in functional analysis of such systems, in view of the high complexity of the 3D structure determination of a ternary complex with two identical ligands. HADDOCK models show that residues involved in binding are mainly located in the C-terminal end of the protein, with two loops, CD and EF, playing a major role in ligand binding. A spine, comprising polarresidues pointing toward the protein interior and involved in motion communication, has a prominent role in ligand interaction. The modeling approach has been complemented with NMR interaction and competition studies of cL-BABP with chenodeoxycholic and cholic acids. A higher affinity for chenodeoxycholic acid was observed and a Kd upper limit estimate was obtained. The binding is highly cooperative and no site selectivity was detected for the different bile salts, thus indicating that site selectivity and cooperativity are not correlated. Differences in physiological pathways and bile salt pools in different species is discussed in light of the binding results thus enlarging the body of knowledge of BABPs biological functions., (2007 Wiley-Liss, Inc.)

Protein-protein interactions play a key role in biological processes. Identifying the interacting residues is a first step toward understanding these interactions at a structural level. In this study, the interface prediction program WHISCY is presented. It combines surface conservation and structural information to predict protein-protein interfaces. The accuracy of the predictions is more than three times higher than a random prediction. These predictions have been combined with another interface prediction program, ProMate [Neuvirth et al. J Mol Biol 2004;338:181-199], resulting in an even more accurate predictor. The usefulness of the predictions was tested using the data-driven docking program HADDOCK [Dominguez et al. J Am Chem Soc 2003;125:1731-1737] in an unbound docking experiment, with the goal of generating as many near-native structures as possible. Unrefined rigid body docking solutions within 10 A ligand RMSD from the true structure were generated for 22 out of 25 docked complexes. For 18 complexes, more than 100 of the 8000 generated models were correct. Our results demonstrates the potential of using interface predictions to drive protein-protein docking., ((c) 2006 Wiley-Liss, Inc.)

When classical, Nuclear Overhauser Effect (NOE)-based approaches fail, it is possible, given high-resolution structures of the free molecules, to model the structure of a complex in solution based solely on chemical shift perturbation (CSP) data in combination with orientational restraints from residual dipolar couplings (RDCs) when available. RDCs can be incorporated into the docking following various strategies: as direct restraints and/or as intermolecular intervector projection angle restraints (Meiler et al., J Biomol NMR 2000;16:245-252). The advantage of the latter for docking is that they directly define the relative orientation of the molecules. A combined protocol in which RDCs are first introduced as intervector projection angle restraints and at a later stage as direct restraints is shown here to give the best performance. This approach, implemented in our information-driven docking approach HADDOCK (Dominguez et al., J Am Chem Soc 2003;125:1731-1737), is used to determine the solution structure of the Lys48-linked di-ubiquitin, for which chemical shift mapping, RDCs, and (15)N-relaxation data have been previously obtained (Varadan et al., J Mol Biol 2002;324:637-647). The resulting structures, derived from CSP and RDC data, are cross-validated using (15)N-relaxation data. The solution structure differs from the crystal structure by a 20 degrees rotation of the two ubiquitin units relative to each other., ((c) 2005 Wiley-Liss, Inc.)

We have shown previously that given high-resolution structures of the unbound molecules, structure determination of protein complexes is possible by including biochemical and/or biophysical data as highly ambiguous distance restraints in a docking approach. We applied this method, implemented in the HADDOCK (High Ambiguity Driven DOCKing) package (Dominguez et al., J Am Chem Soc 2003;125:1731-1737), to the targets in the fourth and fifth rounds of CAPRI. Here we describe our results and analyze them in detail. Special attention is given to the role of flexibility in our docking method and the way in which this improves the docking results. We describe extensions to our approach that were developed as a direct result of our participation in CAPRI. In addition to experimental information, we also included interface residue predictions from PPISP (Protein-Protein Interaction Site Predictor; Zhou and Shan, Proteins 2001;44:336-343), a neural network method. Using HADDOCK we were able to generate acceptable structures for 6 of the 8 targets, and to submit at least 1 acceptable structure for 5 of them. Of these 5 submissions, 3 were of medium quality (Targets 10, 11, and 15) and 2 of high quality (Targets 13 and 14). In all cases, predictions were obtained containing at least 40% of the correct epitope at the interface for both ligand and receptor simultaneously.

State-of-the-art methods based on CNS and CYANA were used to recalculate the nuclear magnetic resonance (NMR) solution structures of 500+ proteins for which coordinates and NMR restraints are available from the Protein Data Bank. Curated restraints were obtained from the BioMagResBank FRED database. Although the original NMR structures were determined by various methods, they all were recalculated by CNS and CYANA and refined subsequently by restrained molecular dynamics (CNS) in a hydrated environment. We present an extensive analysis of the results, in terms of various quality indicators generated by PROCHECK and WHAT_CHECK. On average, the quality indicators for packing and Ramachandran appearance moved one standard deviation closer to the mean of the reference database. The structural quality of the recalculated structures is discussed in relation to various parameters, including number of restraints per residue, NOE completeness and positional root mean square deviation (RMSD). Correlations between pairs of these quality indicators were generally low; for example, there is a weak correlation between the number of restraints per residue and the Ramachandran appearance according to WHAT_CHECK (r = 0.31). The set of recalculated coordinates constitutes a unified database of protein structures in which potential user- and software-dependent biases have been kept as small as possible. The database can be used by the structural biology community for further development of calculation protocols, validation tools, structure-based statistical approaches and modeling. The RECOORD database of recalculated structures is publicly available from http://www.ebi.ac.uk/msd/recoord.

Several studies have shown that biomolecular NMR structures are often of lower quality when compared to crystal structures, and consequently they are often excluded from structural analyses. We present a publicly available database of re-refined NMR structures, exhibiting significantly improved quality. This database (available at http://www.cmbi.kun.nl/dress/) presents a uniformly refined and validated set of structural models that improves the value of these NMR structures as input for experimental and theoretical studies in many fields of research., (Copyright 2004 Wiley-Liss, Inc.)

The entry of HIV-1 into a target cell requires gp120 and receptor CD4 as well as coreceptor CCR5/CXCR4 recognition events associated with conformational changes of the involved proteins. The binding of CD4 to gp120 is the initiation step of the whole process involving structural rearrangements that are crucial for subsequent pathways. Despite the wealth of knowledge about the gp120/CD4 interactions, details of the conformational changes occurring at this stage remain elusive. We have performed molecular dynamics simulations in explicit solvent based on the gp120/CD4/CD4i crystal structure in conjunction with modeled V3 and V4 loops to gain insight into the dynamics of the binding process. Three differentiated interaction modes between CD4 and gp120 were found, which involve electrostatics, hydrogen bond and van der Waals networks. A "binding funnel" model is proposed based on the dynamical nature of the binding interface together with a CD4-attraction gradient centered in gp120 at the CD4-Phe43-binding cavity. Distinct dynamical behaviors of free and CD4-bound gp120 were monitored, which likely represent the ground and pre-fusogenic states, respectively. The transition between these states revealed concerted motions in gp120 leading to: i) loop contractions around the CD4-Phe43-insertion cavity; ii) stabilization of the four-stranded "bridging sheet" structure; and iii) translocation and clustering of the V3 loop and the bridging sheet leading to the formation of the coreceptor binding site. Our results provide new insight into the dynamic of the underlying molecular recognition mechanism that complements the biochemical and structural studies., (Copyright 2004 Wiley-Liss, Inc.)

We present a CPU efficient protocol for refinement of protein structures in a thin layer of explicit solvent and energy parameters with completely revised dihedral angle terms. Our approach is suitable for protein structures determined by theoretical (e.g., homology modeling or threading) or experimental methods (e.g., NMR). In contrast to other recently proposed refinement protocols, we put a strong emphasis on consistency with widely accepted covalent parameters and computational efficiency. We illustrate the method for NMR structure calculations of three proteins: interleukin-4, ubiquitin, and crambin. We show a comparison of their structure ensembles before and after refinement in water with and without a force field energy term for the dihedral angles; crambin was also refined in DMSO. Our results demonstrate the significant improvement of structure quality by a short refinement in a thin layer of solvent. Further, they show that a dihedral angle energy term in the force field is beneficial for structure calculation and refinement. We discuss the optimal weight for the energy constant for the backbone angle omega and include an extensive discussion of meaning and relevance of the calculated validation criteria, in particular root mean square Z scores for covalent parameters such as bond lengths., (Copyright 2003 Wiley-Liss, Inc.)

The structure in solution of crambin, a small protein of 46 residues, has been determined from 2D NMR data using an iterative relaxation matrix approach (IRMA) together with distance geometry, distance bound driven dynamics, molecular dynamics, and energy minimization. A new protocol based on an "ensemble" approach is proposed and compared to the more standard initial rate analysis approach and a "single structure" relaxation matrix approach. The effects of fast local motions are included and R-factor calculations are performed on NOE build-ups to describe the quality of agreement between theory and experiment. A new method for stereospecific assignment of prochiral groups, based on a comparison of theoretical and experimental NOE intensities, has been applied. The solution structure of crambin could be determined with a precision (rmsd from the average structure) of 0.7 A on backbone atoms and 1.1 A on all heavy atoms and is largely similar to the crystal structure with a small difference observed in the position of the side chain of Tyr-29 which is determined in solution by both J-coupling and NOE data. Regions of higher structural variability (suggesting higher mobility) are found in the solution structure, in particular for the loop between the two helices (Gly-20 to Pro-22).