The HADDOCK2.4 web server for integrative modeling of biomolecular complexes.

Interactions between macromolecules, such as proteins and nucleic acids, are essential for cellular functions. Experimental methods can fail to provide all the information required to fully model biomolecular complexes at atomic resolution, particularly for large and heterogeneous assemblies. Integrative computational approaches have, therefore, gained popularity, complementing traditional experimental methods in structural biology. Here, we introduce HADDOCK2.4, an integrative modeling platform, and its updated web interface ( https://wenmr.science.uu.nl/haddock2.4 ). The platform seamlessly integrates diverse experimental and theoretical data to generate high-quality models of macromolecular complexes. The user-friendly web server offers automated parameter settings, access to distributed computing resources, and pre- and post-processing steps that enhance the user experience. To present the web server's various interfaces and features, we demonstrate two different applications: (i) we predict the structure of an antibody-antigen complex by using NMR data for the antigen and knowledge of the hypervariable loops for the antibody, and (ii) we perform coarse-grained modeling of PRC1 with a nucleosome particle guided by mutagenesis and functional data. The described protocols require some basic familiarity with molecular modeling and the Linux command shell. This new version of our widely used HADDOCK web server allows structural biologists and non-experts to explore intricate macromolecular assemblies encompassing various molecule types.

Robust detection of translocations in lymphoma FFPE samples using targeted locus capture-based sequencing.

In routine diagnostic pathology, cancer biopsies are preserved by formalin-fixed, paraffin-embedding (FFPE) procedures for examination of (intra-) cellular morphology. Such procedures inadvertently induce DNA fragmentation, which compromises sequencing-based analyses of chromosomal rearrangements. Yet, rearrangements drive many types of hematolymphoid malignancies and solid tumors, and their manifestation is instructive for diagnosis, prognosis, and treatment. Here, we present FFPE-targeted locus capture (FFPE-TLC) for targeted sequencing of proximity-ligation products formed in FFPE tissue blocks, and PLIER, a computational framework that allows automated identification and characterization of rearrangements involving selected, clinically relevant, loci. FFPE-TLC, blindly applied to 149 lymphoma and control FFPE samples, identifies the known and previously uncharacterized rearrangement partners. It outperforms fluorescence in situ hybridization (FISH) in sensitivity and specificity, and shows clear advantages over standard capture-NGS methods, finding rearrangements involving repetitive sequences which they typically miss. FFPE-TLC is therefore a powerful clinical diagnostics tool for accurate targeted rearrangement detection in FFPE specimens.

An overview of data-driven HADDOCK strategies in CAPRI rounds 38-45.

Our information-driven docking approach HADDOCK has demonstrated a sustained performance since the start of its participation to CAPRI. This is due, in part, to its ability to integrate data into the modeling process, and to the robustness of its scoring function. We participated in CAPRI both as server and manual predictors. In CAPRI rounds 38-45, we have used various strategies depending on the available information. These ranged from imposing restraints to a few residues identified from literature as being important for the interaction, to binding pockets identified from homologous complexes or template-based refinement/CA-CA restraint-guided docking from identified templates. When relevant, symmetry restraints were used to limit the conformational sampling. We also tested for a large decamer target a new implementation of the MARTINI coarse-grained force field in HADDOCK. Overall, we obtained acceptable or better predictions for 13 and 11 server and manual submissions, respectively, out of the 22 interfaces. Our server performance (acceptable or higher-quality models when considering the top 10) was better (59%) than the manual (50%) one, in which we typically experiment with various combinations of protocols and data sources. Again, our simple scoring function based on a linear combination of intermolecular van der Waals and electrostatic energies and an empirical desolvation term demonstrated a good performance in the scoring experiment with a 63% success rate across all 22 interfaces. An analysis of model quality indicates that, while we are consistently performing well in generating acceptable models, there is room for improvement for generating/identifying higher quality models.

Surveillance guidelines based on recurrence patterns for upper tract urothelial carcinoma.

INTRODUCTION: Upper tract urothelial carcinoma (UTUC) accounts for 5% of all urothelial tumours. Due to its rarity, evidence regarding postoperative surveillance is lacking. The objective of this study was to develop a post-radical nephroureterectomy (RNU) surveillance protocol based on recurrence patterns in a large, multi-institutional cohort of patients. METHODS: Retrospective clinical and pathological data were collected from 1029 patients undergoing RNU over a 15-year period (1994-2009) at 10 Canadian academic institutions. A multivariable model was used to identify prognostic clinicopathological factors, which were then used to define risk categories. Risk-based surveillance guidelines were proposed based on actual recurrence patterns. RESULTS: Overall, 555 (49.9%) patients developed recurrence, including 289 (25.9%) in the urothelium and 266 (23.9%) with loco-regional and distant recurrences. Based on multivariable analysis, three risk groups were identified: 1) low-risk patients with pTa-T1, pN0 disease, and no adverse histological features (high tumour grade, lymphovascular invasion [LVI], tumour multifocality); 2) intermediate-risk patients with pTa-T1, pN0 disease with one or more of the adverse histological features; and 3) high-risk patients with a ≥pT2 tumour and/or nodal involvement. Low-, intermediate-, and high-risk patients were free of urothelial recurrence at three years in 72%, 66%, and 63%, respectively, and free of regional/distant recurrence in 93%, 87%, and 62%, respectively. The risks of loco-regional and distant recurrences (p<0.0001) and time to death (p<0.0001) were significantly different between the low-, intermediate-, and high-risk patients. CONCLUSIONS: Based on recurrence patterns in a large, multicentre patient cohort, we have proposed an evidence-based, risk-adapted post-RNU surveillance protocol.

Performance of HADDOCK and a simple contact-based protein-ligand binding affinity predictor in the D3R Grand Challenge 2.

We present the performance of HADDOCK, our information-driven docking software, in the second edition of the D3R Grand Challenge. In this blind experiment, participants were requested to predict the structures and binding affinities of complexes between the Farnesoid X nuclear receptor and 102 different ligands. The models obtained in Stage1 with HADDOCK and ligand-specific protocol show an average ligand RMSD of 5.1 Å from the crystal structure. Only 6/35 targets were within 2.5 Å RMSD from the reference, which prompted us to investigate the limiting factors and revise our protocol for Stage2. The choice of the receptor conformation appeared to have the strongest influence on the results. Our Stage2 models were of higher quality (13 out of 35 were within 2.5 Å), with an average RMSD of 4.1 Å. The docking protocol was applied to all 102 ligands to generate poses for binding affinity prediction. We developed a modified version of our contact-based binding affinity predictor PRODIGY, using the number of interatomic contacts classified by their type and the intermolecular electrostatic energy. This simple structure-based binding affinity predictor shows a Kendall's Tau correlation of 0.37 in ranking the ligands (7th best out of 77 methods, 5th/25 groups). Those results were obtained from the average prediction over the top10 poses, irrespective of their similarity/correctness, underscoring the robustness of our simple predictor. This results in an enrichment factor of 2.5 compared to a random predictor for ranking ligands within the top 25%, making it a promising approach to identify lead compounds in virtual screening.

Application of a simplified method of chloroplast enrichment to small amounts of tissue for chloroplast genome sequencing.

PREMISE OF THE STUDY: High-throughput sequencing of genomic DNA can recover complete chloroplast genome sequences, but the sequence data are usually dominated by sequences from nuclear/mitochondrial genomes. To overcome this deficiency, a simple enrichment method for chloroplast DNA from small amounts of plant tissue was tested for eight plant species including a gymnosperm and various angiosperms. METHODS: Chloroplasts were enriched using a high-salt isolation buffer without any step gradient procedures, and enriched chloroplast DNA was sequenced by multiplexed high-throughput sequencing. RESULTS: Using this simple method, significant enrichment of chloroplast DNA-derived reads was attained, allowing deep sequencing of chloroplast genomes. As an example, the chloroplast genome of the conifer Callitris sulcata was assembled, from which polymorphic microsatellite loci were isolated successfully. DISCUSSION: This chloroplast enrichment method from small amounts of plant tissue will be particularly useful for studies that use sequencers with relatively small throughput and that cannot use large amounts of tissue (e.g., for endangered species).

dMM-PBSA: A New HADDOCK Scoring Function for Protein-Peptide Docking.

Molecular-docking programs coupled with suitable scoring functions are now established and very useful tools enabling computational chemists to rapidly screen large chemical databases and thereby to identify promising candidate compounds for further experimental processing. In a broader scenario, predicting binding affinity is one of the most critical and challenging components of computer-aided structure-based drug design. The development of a molecular docking scoring function which in principle could combine both features, namely ranking putative poses and predicting complex affinity, would be of paramount importance. Here, we systematically investigated the performance of the MM-PBSA approach, using two different Poisson-Boltzmann solvers (APBS and DelPhi), in the currently rising field of protein-peptide interactions (PPIs), identifying the correct binding conformations of 19 different protein-peptide complexes and predicting their binding free energies. First, we scored the decoy structures from HADDOCK calculation via the MM-PBSA approach in order to assess the capability of retrieving near-native poses in the best-scoring clusters and of evaluating the corresponding free energies of binding. MM-PBSA behaves well in finding the poses corresponding to the lowest binding free energy, however the built-in HADDOCK score shows a better performance. In order to improve the MM-PBSA-based scoring function, we dampened the MM-PBSA solvation and coulombic terms by 0.2, as proposed in the HADDOCK score and LIE approaches. The new dampened MM-PBSA (dMM-PBSA) outperforms the original MM-PBSA and ranks the decoys structures as the HADDOCK score does. Second, we found a good correlation between the dMM-PBSA and HADDOCK scores for the near-native clusters of each system and the experimental binding energies, respectively. Therefore, we propose a new scoring function, dMM-PBSA, to be used together with the built-in HADDOCK score in the context of protein-peptide docking simulations.

Enhancers reside in a unique epigenetic environment during early zebrafish development.

BACKGROUND: Enhancers, not promoters, are the most dynamic in their DNA methylation status throughout development and differentiation. Generally speaking, enhancers that are primed to or actually drive gene expression are characterized by relatively low levels of DNA methylation (hypo-methylation), while inactive enhancers display hyper-methylation of the underlying DNA. The direct functional significance of the DNA methylation state of enhancers is, however, unclear for most loci. RESULTS: In contrast to conventional epigenetic interactions at enhancers, we find that DNA methylation status and enhancer activity during early zebrafish development display very unusual correlation characteristics: hypo-methylation is a unique feature of primed enhancers whereas active enhancers are generally hyper-methylated. The hypo-methylated enhancers that we identify (hypo-enhancers) are enriched close to important transcription factors that act later in development. Interestingly, hypo-enhancers are de-methylated shortly before the midblastula transition and reside in a unique epigenetic environment. Finally, we demonstrate that hypo-enhancers do become active at later developmental stages and that they are physically associated with the transcriptional start site of target genes, irrespective of target gene activity. CONCLUSIONS: We demonstrate that early development in zebrafish embodies a time window characterized by non-canonical DNA methylation-enhancer relationships, including global DNA hypo-methylation of inactive enhancers and DNA hyper-methylation of active enhancers.

Hidden in plain view: Cryptic diversity in the emblematic Araucaria of New Caledonia.

PREMISE OF THE STUDY: Cryptic species represent a conservation challenge, because distributions and threats cannot be accurately assessed until species are recognized and defined. Cryptic species are common in diminutive and morphologically simple organisms, but are rare in charismatic and/or highly visible groups such as conifers. New Caledonia, a small island in the southern Pacific is a hotspot of diversity for the emblematic conifer genus Araucaria (Araucariaceae, Monkey Puzzle trees) where 13 of the 19 recognized species are endemic. METHODS: We sampled across the entire geographical distribution of two closely related species (Araucaria rulei and A. muelleri) and screened them for genetic variation at 12 nuclear and 14 plastid microsatellites and one plastid minisatellite; a subset of the samples was also examined using leaf morphometrics. KEY RESULTS: The genetic data show that populations of the endangered A. muelleri fall into two clearly distinct genetic groups: one corresponding to montane populations, the other corresponding to trees from lower elevation populations from around the Goro plateau. These Goro plateau populations are more closely related to A. rulei, but are sufficiently genetically and morphological distinct to warrant recognition as a new species. CONCLUSIONS: Our study shows the presence of a previously unrecognized species in this flagship group, and that A. muelleri has 30% fewer individuals than previously thought. Combined, this clarification of species diversity and distributions provides important information to aid conservation planning for New Caledonian Araucaria.

Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment.

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.

Molecular dynamics characterization of the conformational landscape of small peptides: A series of hands-on collaborative practical sessions for undergraduate students.

Molecular modelling and simulations are nowadays an integral part of research in areas ranging from physics to chemistry to structural biology, as well as pharmaceutical drug design. This popularity is due to the development of high-performance hardware and of accurate and efficient molecular mechanics algorithms by the scientific community. These improvements are also benefitting scientific education. Molecular simulations, their underlying theory, and their applications are particularly difficult to grasp for undergraduate students. Having hands-on experience with the methods contributes to a better understanding and solidification of the concepts taught during the lectures. To this end, we have created a computer practical class, which has been running for the past five years, composed of several sessions where students characterize the conformational landscape of small peptides using molecular dynamics simulations in order to gain insights on their binding to protein receptors. In this report, we detail the ingredients and recipe necessary to establish and carry out this practical, as well as some of the questions posed to the students and their expected results. Further, we cite some examples of the students' written reports, provide statistics, and share their feedbacks on the structure and execution of the sessions. These sessions were implemented alongside a theoretical molecular modelling course but have also been used successfully as a standalone tutorial during specialized workshops. The availability of the material on our web page also facilitates this integration and dissemination and lends strength to the thesis of open-source science and education.

Development of nuclear and chloroplast microsatellite markers for the endangered conifer Callitris sulcata (Cupressaceae).

PREMISE OF THE STUDY: Microsatellite markers were developed for Callitris sulcata (Cupressaceae), an endangered conifer species in New Caledonia. METHODS AND RESULTS: Using sequencing by synthesis (SBS) of an RNA-Seq library, 15 polymorphic nuclear and chloroplast microsatellite markers were developed. When evaluated with 48 individuals, these markers showed genetic variations ranging from two to 15 alleles and expected heterozygosity ranging from 0 to 0.881. CONCLUSIONS: These markers will be useful for examining the genetic diversity and structure of remaining wild populations and improving the genetic status of ex situ populations.

The LxxxA motif in the third transmembrane helix of the maize aquaporin ZmPIP2;5 acts as an ER export signal.

The subcellular localization of aquaporins belonging to the plasma membrane intrinsic protein (PIP) subfamily is highly regulated. In maize (Zea mays), ZmPIP1s are retained in the endoplasmic reticulum (ER) whereas ZmPIP2s are able to reach the plasma membrane (PM). We recently identified a new sorting determinant which is buried within the third transmembrane domain (TM3) of ZmPIP2;5. The Leu127 and Ala131 are required for the localization of ZmPIP2;5 in the PM and for its exit from the ER. However, when inserted into ZmPIP1;2, these amino acids were not sufficient to export the protein out of the ER. Here, we show that, when inserted into a truncated version of ZmPIP1;2 consisting only of its TM3 region, Leu127 and Ala131 of ZmPIP2;5 are able to partially bring the protein to the PM, demonstrating the active anterograde sorting function of this motif.

Integrative Modeling of Biomolecular Complexes: HADDOCKing with Cryo-Electron Microscopy Data.

Protein-protein interactions play a central role in all cellular processes. Insight into their atomic architecture is therefore of paramount importance. Cryo-electron microscopy (cryo-EM) is capable of directly imaging large macromolecular complexes. Unfortunately, the resolution is usually not sufficient for a direct atomic interpretation. To overcome this, cryo-EM data are often combined with high-resolution atomic structures. However, current computational approaches typically do not include information from other experimental sources nor a proper physico-chemical description of the interfaces. Here we describe the integration of cryo-EM data into our data-driven docking program HADDOCK and its performance on a benchmark of 17 complexes. The approach is demonstrated on five systems using experimental cryo-EM data in the range of 8.5-21 Å resolution. For several cases, cryo-EM data are integrated with additional interface information, e.g. mutagenesis and hydroxyl radical footprinting data. The resulting models have high-quality interfaces, revealing novel details of the interactions.

Information-driven modeling of protein-peptide complexes.

Despite their biological importance in many regulatory processes, protein-peptide recognition mechanisms are difficult to study experimentally at the structural level because of the inherent flexibility of peptides and the often transient interactions on which they rely. Complementary methods like biomolecular docking are therefore required. The prediction of the three-dimensional structure of protein-peptide complexes raises unique challenges for computational algorithms, as exemplified by the recent introduction of protein-peptide targets in the blind international experiment CAPRI (Critical Assessment of PRedicted Interactions). Conventional protein-protein docking approaches are often struggling with the high flexibility of peptides whose short sizes impede protocols and scoring functions developed for larger interfaces. On the other side, protein-small ligand docking methods are unable to cope with the larger number of degrees of freedom in peptides compared to small molecules and the typically reduced available information to define the binding site. In this chapter, we describe a protocol to model protein-peptide complexes using the HADDOCK web server, working through a test case to illustrate every steps. The flexibility challenge that peptides represent is dealt with by combining elements of conformational selection and induced fit molecular recognition theories.

Trafficking of plant plasma membrane aquaporins: multiple regulation levels and complex sorting signals.

Aquaporins are small channel proteins which facilitate the diffusion of water and small neutral molecules across biological membranes. Compared with animals, plant genomes encode numerous aquaporins, which display a large variety of subcellular localization patterns. More specifically, plant aquaporins of the plasma membrane intrinsic protein (PIP) subfamily were first described as plasma membrane (PM)-resident proteins, but recent research has demonstrated that the trafficking and subcellular localization of these proteins are complex and highly regulated. In the past few years, PIPs emerged as new model proteins to study subcellular sorting and membrane dynamics in plant cells. At least two distinct sorting motifs (one cytosolic, the other buried in the membrane) are required to direct PIPs to the PM. Hetero-oligomerization and interaction with SNAREs (soluble N-ethylmaleimide-sensitive factor protein attachment protein receptors) also influence the subcellular trafficking of PIPs. In addition to these constitutive processes, both the progression of PIPs through the secretory pathway and their dynamics at the PM are responsive to changing environmental conditions.

Expression and characterization of plasma membrane aquaporins in stomatal complexes of Zea mays.

Stomata, the microscopic pores on the surface of the aerial parts of plants, are bordered by two specialized cells, known as guard cells, which control the stomatal aperture according to endogenous and environmental signals. Like most movements occurring in plants, the opening and closing of stomata are based on hydraulic forces. During opening, the activation of plasma membrane and tonoplast transporters results in solute accumulation in the guard cells. To re-establish the perturbed osmotic equilibrium, water follows the solutes into the cells, leading to their swelling. Numerous studies have contributed to the understanding of the mechanism and regulation of stomatal movements. However, despite the importance of transmembrane water flow during this process, only a few studies have provided evidence for the involvement of water channels, called aquaporins. Here, we microdissected Zea mays stomatal complexes and showed that members of the aquaporin plasma membrane intrinsic protein (PIP) subfamily are expressed in these complexes and that their mRNA expression generally follows a diurnal pattern. The substrate specificity of two of the expressed ZmPIPs, ZmPIP1;5 and ZmPIP1;6, was investigated by heterologous expression in Xenopus oocytes and yeast cells. Our data show that both isoforms facilitate transmembrane water diffusion in the presence of the ZmPIP2;1 isoform. In addition, both display CO2 permeability comparable to that of the CO2 diffusion facilitator NtAQP1. These data indicate that ZmPIPs may have various physiological roles in stomatal complexes.

A new LxxxA motif in the transmembrane Helix3 of maize aquaporins belonging to the plasma membrane intrinsic protein PIP2 group is required for their trafficking to the plasma membrane.

Aquaporins play important roles in maintaining plant water status under challenging environments. The regulation of aquaporin density in cell membranes is essential to control transcellular water flows. This work focuses on the maize (Zea mays) plasma membrane intrinsic protein (ZmPIP) aquaporin subfamily, which is divided into two sequence-related groups (ZmPIP1s and ZmPIP2s). When expressed alone in mesophyll protoplasts, ZmPIP2s are efficiently targeted to the plasma membrane, whereas ZmPIP1s are retained in the endoplasmic reticulum (ER). A protein domain-swapping approach was utilized to demonstrate that the transmembrane domain3 (TM3), together with the previously identified N-terminal ER export diacidic motif, account for the differential localization of these proteins. In addition to protoplasts, leaf epidermal cells transiently transformed by biolistic particle delivery were used to confirm and refine these results. By generating artificial proteins consisting of a single transmembrane domain, we demonstrated that the TM3 of ZmPIP1;2 or ZmPIP2;5 discriminates between ER and plasma membrane localization, respectively. More specifically, a new LxxxA motif in the TM3 of ZmPIP2;5, which is highly conserved in plant PIP2s, was shown to regulate its anterograde routing along the secretory pathway, particularly its export from the ER.

Insight into cyanobacterial circadian timing from structural details of the KaiB-KaiC interaction.

Circadian timing in cyanobacteria is determined by the Kai system consisting of KaiA, KaiB, and KaiC. Interactions between Kai proteins change the phosphorylation status of KaiC, defining the phase of circadian timing. The KaiC-KaiB interaction is crucial for the circadian rhythm to enter the dephosphorylation phase but it is not well understood. Using mass spectrometry to characterize Kai complexes, we found that KaiB forms monomers, dimers, and tetramers. The monomer is the unit that interacts with KaiC, with six KaiB monomers binding to one KaiC hexamer. Hydrogen-deuterium exchange MS reveals structural changes in KaiC upon binding of KaiB in both the CI and CII domains, showing allosteric coupling upon KaiB binding. Based on this information we propose a model of the KaiB-KaiC complex and hypothesize that the allosteric changes observed upon complex formation relate to coupling KaiC ATPase activity with KaiB binding and to sequestration of KaiA dimers into KaiCBA complexes.

Blind prediction of interfacial water positions in CAPRI.

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.