SuperLooper--a prediction server for the modeling of loops in globular and membrane proteins

Comprehensive assessment of protein loop modeling programs on large-scale datasets: prediction accuracy and efficiency

Protein loops play a critical role in the dynamics of proteins and are essential for numerous biological functions, and various computational approaches to loop modeling have been proposed over the past decades. However, a comprehensive understanding of the strengths and weaknesses of each method is lacking. In this work, we constructed two high-quality datasets (i.e. the General dataset and the CASP dataset) and systematically evaluated the accuracy and efficiency of 13 commonly used loop modeling approaches from the perspective of loop lengths, protein classes and residue types. The results indicate that the knowledge-based method FREAD generally outperforms the other tested programs in most cases, but encountered challenges when predicting loops longer than 15 and 30 residues on the CASP and General datasets, respectively. The ab initio method Rosetta NGK demonstrated exceptional modeling accuracy for short loops with four to eight residues and achieved the highest success rate on the CASP dataset. The well-known AlphaFold2 and RoseTTAFold require more resources for better performance, but they exhibit promise for predicting loops longer than 16 and 30 residues in the CASP and General datasets. These observations can provide valuable insights for selecting suitable methods for specific loop modeling tasks and contribute to future advancements in the field.

Protein Loop Modeling Using AlphaFold2

The functions of proteins are largely determined by their three-dimensional (3D) structures. Loop modeling tries to predict the conformation of a relatively short stretch of protein backbone and sidechain. It is a difficult problem due to conformational variability. Recently, AlphaFold2 has achieved outstanding results in 3-D protein structure prediction and is expected to perform well on loop modeling. In this paper, we investigate the performances of AlphaFold2 variants on popular loop modeling benchmark datasets and propose an efficient protocol of using AlphaFold2 for loop modeling, called IAFLoop. To predict the structure of a loop region, IAFLoop gives a moderately extended segment of the target loop region as input to AlphaFold2, runs a fast version of AlphaFold2 using a reduced database without ensembling, and uses RMSD based consensus scores to select the final output models. Our experimental results on benchmark datasets show that IAFLoop generated highly accurate loop models. It achieves comparable performance to the original application of AlphaFold2 in terms of RMSD error, and achieving much better results on some targets, while only using half of the time. Compared to the best previous methods, IAFLoop reduces the RMSD error by almost half on the 8-residual loop dataset, and more than 70% on the 12-residual loop dataset.

Backbone amides are determinants of Cl- selectivity in CLC ion channels

Chloride homeostasis is regulated in all cellular compartments. CLC-type channels selectively transport Cl- across biological membranes. It is proposed that side-chains of pore-lining residues determine Cl- selectivity in CLC-type channels, but their spatial orientation and contributions to selectivity are not conserved. This suggests a possible role for mainchain amides in selectivity. We use nonsense suppression to insert α-hydroxy acids at pore-lining positions in two CLC-type channels, CLC-0 and bCLC-k, thus exchanging peptide-bond amides with ester-bond oxygens which are incapable of hydrogen-bonding. Backbone substitutions functionally degrade inter-anion discrimination in a site-specific manner. The presence of a pore-occupying glutamate side chain modulates these effects. Molecular dynamics simulations show backbone amides determine ion energetics within the bCLC-k pore and how insertion of an α-hydroxy acid alters selectivity. We propose that backbone-ion interactions are determinants of Cl- specificity in CLC channels in a mechanism reminiscent of that described for K+ channels.

Accurate Structure Prediction for Protein Loops Based on Molecular Dynamics Simulations with RSFF2C

Protein loops, connecting the α-helices and β-strands, are involved in many important biological processes. However, due to their conformational flexibility, it is still challenging to accurately determine three-dimensional (3D) structures of long loops experimentally and computationally. Herein, we present a systematic study of the protein loop structure prediction via a total of ∼850 μs molecular dynamics (MD) simulations. For a set of 15 long (10-16 residues) and solvent-exposed loops, we first evaluated the performance of four state-of-the-art loop modeling algorithms, DaReUS-Loop, Sphinx, Rosetta-NGK, and MODELLER, on each loop, and none of them could accurately predict the structures for most loops. Then, temperature replica exchange molecular dynamics (REMD) simulations were conducted with three recent force fields, RSFF2C with TIP3P water model, CHARMM36m with CHARMM-modified TIP3P, and AMBER ff19SB with OPC. We found that our recently developed residue-specific force field RSFF2C performed the best and successfully predicted 12 out of 15 loops with a root-mean-square deviation (RMSD) < 1.5 Å. As an alternative with lower computational cost, normal MD simulations at high temperatures (380, 500, and 620 K) were investigated. Temperature-dependent performance was observed for each force field, and, for RSFF2C+TIP3P, we found that three independent 100-ns MD simulations at 500 K gave comparable results with REMD simulations. These results suggest that MD simulations, especially with enhanced sampling techniques such as replica exchange, with the RSFF2C force field could be useful for accurate loop structure prediction.

Putative ligand binding sites of two functionally characterized bark beetle odorant receptors

BACKGROUND

Bark beetles are major pests of conifer forests, and their behavior is primarily mediated via olfaction. Targeting the odorant receptors (ORs) may thus provide avenues towards improved pest control. Such an approach requires information on the function of ORs and their interactions with ligands, which is also essential for understanding the functional evolution of these receptors. Hence, we aimed to identify a high-quality complement of ORs from the destructive spruce bark beetle Ips typographus (Coleoptera, Curculionidae, Scolytinae) and analyze their antennal expression and phylogenetic relationships with ORs from other beetles. Using 68 biologically relevant test compounds, we next aimed to functionally characterize ecologically important ORs, using two systems for heterologous expression. Our final aim was to gain insight into the ligand-OR interaction of the functionally characterized ORs, using a combination of computational and experimental methods.

RESULTS

We annotated 73 ORs from an antennal transcriptome of I. typographus and report the functional characterization of two ORs (ItypOR46 and ItypOR49), which are responsive to single enantiomers of the common bark beetle pheromone compounds ipsenol and ipsdienol, respectively. Their responses and antennal expression correlate with the specificities, localizations, and/or abundances of olfactory sensory neurons detecting these enantiomers. We use homology modeling and molecular docking to predict their binding sites. Our models reveal a likely binding cleft lined with residues that previously have been shown to affect the responses of insect ORs. Within this cleft, the active ligands are predicted to specifically interact with residues Tyr84 and Thr205 in ItypOR46. The suggested importance of these residues in the activation by ipsenol is experimentally supported through site-directed mutagenesis and functional testing, and hydrogen bonding appears key in pheromone binding.

CONCLUSIONS

The emerging insight into ligand binding in the two characterized ItypORs has a general importance for our understanding of the molecular and functional evolution of the insect OR gene family. Due to the ecological importance of the characterized receptors and widespread use of ipsenol and ipsdienol in bark beetle chemical communication, these ORs should be evaluated for their potential use in pest control and biosensors to detect bark beetle infestations.

Putative ligand binding sites of two functionally characterized bark beetle odorant receptors

BACKGROUND

Bark beetles are major pests of conifer forests, and their behavior is primarily mediated via olfaction. Targeting the odorant receptors (ORs) may thus provide avenues towards improved pest control. Such an approach requires information on the function of ORs and their interactions with ligands, which is also essential for understanding the functional evolution of these receptors. Hence, we aimed to identify a high-quality complement of ORs from the destructive spruce bark beetle Ips typographus (Coleoptera, Curculionidae, Scolytinae) and analyze their antennal expression and phylogenetic relationships with ORs from other beetles. Using 68 biologically relevant test compounds, we next aimed to functionally characterize ecologically important ORs, using two systems for heterologous expression. Our final aim was to gain insight into the ligand-OR interaction of the functionally characterized ORs, using a combination of computational and experimental methods.

RESULTS

We annotated 73 ORs from an antennal transcriptome of I. typographus and report the functional characterization of two ORs (ItypOR46 and ItypOR49), which are responsive to single enantiomers of the common bark beetle pheromone compounds ipsenol and ipsdienol, respectively. Their responses and antennal expression correlate with the specificities, localizations, and/or abundances of olfactory sensory neurons detecting these enantiomers. We use homology modeling and molecular docking to predict their binding sites. Our models reveal a likely binding cleft lined with residues that previously have been shown to affect the responses of insect ORs. Within this cleft, the active ligands are predicted to specifically interact with residues Tyr84 and Thr205 in ItypOR46. The suggested importance of these residues in the activation by ipsenol is experimentally supported through site-directed mutagenesis and functional testing, and hydrogen bonding appears key in pheromone binding.

CONCLUSIONS

The emerging insight into ligand binding in the two characterized ItypORs has a general importance for our understanding of the molecular and functional evolution of the insect OR gene family. Due to the ecological importance of the characterized receptors and widespread use of ipsenol and ipsdienol in bark beetle chemical communication, these ORs should be evaluated for their potential use in pest control and biosensors to detect bark beetle infestations.

Efficient Sampling of Protein Loop Regions Using Conformational Hashing Complemented with Random Coordinate Descent

De novo construction of loop regions is an important problem in computational structural biology. Compared to regions with well-defined secondary structure, loops tend to exhibit significant conformational heterogeneity. As a result, their structures are often ambiguous when determined using experimental data obtained by crystallography, cryo-EM, or NMR. Although structurally diverse models could provide a more relevant representation of proteins in their native states, obtaining large numbers of biophysically realistic and physiologically relevant loop conformations is a resource-consuming task. To address this need, we developed a novel loop construction algorithm, Hash/RCD, that combines knowledge-based conformational hashing with random coordinate descent (RCD). This hybrid approach achieved a closure rate of 100% on a benchmark set of 195 loops in 29 proteins that range from 3 to 31 residues. More importantly, the use of templates allows Hash/RCD to maintain the accuracy of state-of-the-art coordinate descent methods while reducing sampling time from over 400 to 141 ms. These results highlight how the integration of coordinate descent with knowledge-based sampling overcomes barriers inherent to either approach in isolation. This method may facilitate the identification of native-like loop conformations using experimental data or full-atom scoring functions by allowing rapid sampling of large numbers of loops. In this manuscript, we investigate and discuss the advantages, bottlenecks, and limitations of combining conformational hashing with RCD. By providing a detailed technical description of the Hash/RCD algorithm, we hope to facilitate its implementation by other researchers.

Structural basis of BMP-2 and BMP-7 interactions with antagonists Gremlin-1 and Noggin in Glioblastoma tumors

In Glioblastoma (GBM) brain tumors, both Gremlin-1 and Noggin are reported to bind to BMP and inhibit BMP-signaling, thereby allowing the cell to maintain tumorous morphology. Enlisting the interfacial residues important for protein-protein complex formation between BMPs (BMP-2 and BMP-7) and antagonists (Gremlin-1 and Noggin), we analyzed the structural basis of their interactions. We found possible key mutations that destabilize these complexes, which may prevent GBM development. It was also observed that when the interfacial residues were either mutated to histidine or tryptophan, it led to higher destabilization energy values. Besides, our study of the Noggin interactive model of BMP-2 suggested preferential binding at binding site II over binding site I. In the case of Gremlin-1 and BMPs, our research, along with few previous studies, indicates a close-ended cis-trans interactive model.

Interdomain Flexibility within NADPH Oxidase Suggested by SANS Using LMNG Stealth Carrier

Small angle neutron scattering (SANS) provides a method to obtain important low-resolution information for integral membrane proteins (IMPs), challenging targets for structural determination. Specific deuteration furnishes a "stealth" carrier for the solubilized IMP. We used SANS to determine a structural envelope of SpNOX, the Streptococcus pneumoniae NADPH oxidase (NOX), a prokaryotic model system for exploring structure and function of eukaryotic NOXes. SpNOX was solubilized in the detergent lauryl maltose neopentyl glycol, which provides optimal SpNOX stability and activity. Using deuterated solvent and protein, the lauryl maltose neopentyl glycol was experimentally undetected in SANS. This affords a cost-effective SANS approach for obtaining novel structural information on IMPs. Combining SANS data with molecular modeling provided a first, to our knowledge, structural characterization of an entire NOX enzyme. It revealed a distinctly less compact structure than that predicted from the docking of homologous crystal structures of the separate transmembrane and dehydrogenase domains, consistent with a flexible linker connecting the two domains.

DaReUS-Loop: a web server to model multiple loops in homology models

Loop regions in protein structures often have crucial roles, and they are much more variable in sequence and structure than other regions. In homology modeling, this leads to larger deviations from the homologous templates, and loop modeling of homology models remains an open problem. To address this issue, we have previously developed the DaReUS-Loop protocol, leading to significant improvement over existing methods. Here, a DaReUS-Loop web server is presented, providing an automated platform for modeling or remodeling loops in the context of homology models. This is the first web server accepting a protein with up to 20 loop regions, and modeling them all in parallel. It also provides a prediction confidence level that corresponds to the expected accuracy of the loops. DaReUS-Loop facilitates the analysis of the results through its interactive graphical interface and is freely available at http://bioserv.rpbs.univ-paris-diderot.fr/services/DaReUS-Loop/.

Simple Selection Procedure to Distinguish between Static and Flexible Loops

Loops are the most variable and unorganized elements of the secondary structure of proteins. Their ability to shift their shape can play a role in the binding of small ligands, enzymatic catalysis, or protein–protein interactions. Due to the loop flexibility, the positions of their residues in solved structures show the largest B-factors, or in a worst-case scenario can be unknown. Based on the loops’ movements’ timeline, they can be divided into slow (static) and fast (flexible). Although most of the loops that are missing in experimental structures belong to the flexible loops group, the computational tools for loop reconstruction use a set of static loop conformations to predict the missing part of the structure and evaluate the model. We believe that these two loop types can adopt different conformations and that using scoring functions appropriate for static loops is not sufficient for flexible loops. We showed that common model evaluation methods, are insufficient in the case of flexible solvent-exposed loops. Instead, we recommend using the potential energy to evaluate such loop models. We provide a novel model selection method based on a set of geometrical parameters to distinguish between flexible and static loops without the use of molecular dynamics simulations. We have also pointed out the importance of water network and interactions with the solvent for the flexible loop modeling.

A network of phosphatidylinositol 4,5-bisphosphate binding sites regulates gating of the Ca2+-activated Cl- channel ANO1 (TMEM16A)

ANO1 (TMEM16A) is a Ca²⁺-activated Cl^- channel that regulates diverse cellular functions including fluid secretion, neuronal excitability, and smooth muscle contraction. ANO1 is activated by elevation of cytosolic Ca²⁺ and modulated by phosphatidylinositol 4,5-bisphosphate [PI(4,5)P₂]. Here, we describe a closely concerted experimental and computational study, including electrophysiology, mutagenesis, functional assays, and extended sampling of lipid-protein interactions with molecular dynamics (MD) to characterize PI(4,5)P₂ binding modes and sites on ANO1. ANO1 currents in excised inside-out patches activated by 270 nM Ca²⁺ at +100 mV are increased by exogenous PI(4,5)P₂ with an EC₅₀ = 1.24 µM. The effect of PI(4,5)P₂ is dependent on membrane voltage and Ca²⁺ and is explained by a stabilization of the ANO1 Ca²⁺-bound open state. Unbiased atomistic MD simulations with 1.4 mol% PI(4,5)P₂ in a phosphatidylcholine bilayer identified 8 binding sites with significant probability of binding PI(4,5)P₂ Three of these sites captured 85% of all ANO1-PI(4,5)P₂ interactions. Mutagenesis of basic amino acids near the membrane-cytosol interface found 3 regions of ANO1 critical for PI(4,5)P₂ regulation that correspond to the same 3 sites identified by MD. PI(4,5)P₂ is stabilized by hydrogen bonding between amino acid side chains and phosphate/hydroxyl groups on PI(4,5)P₂ Binding of PI(4,5)P₂ alters the position of the cytoplasmic extension of TM6, which plays a crucial role in ANO1 channel gating, and increases the accessibility of the inner vestibule to Cl^- ions. We propose a model consisting of a network of 3 PI(4,5)P₂ binding sites at the cytoplasmic face of the membrane allosterically regulating ANO1 channel gating.

GPCR-SSFE 2.0-a fragment-based molecular modeling web tool for Class A G-protein coupled receptors

G-protein coupled receptors (GPCRs) are key players in signal transduction and therefore a large proportion of pharmaceutical drugs target these receptors. Structural data of GPCRs are sparse yet important for elucidating the molecular basis of GPCR-related diseases and for performing structure-based drug design. To ameliorate this problem, GPCR-SSFE 2.0 (http://www.ssfa-7tmr.de/ssfe2/), an intuitive web server dedicated to providing three-dimensional Class A GPCR homology models has been developed. The updated web server includes 27 inactive template structures and incorporates various new functionalities. Uniquely, it uses a fingerprint correlation scoring strategy for identifying the optimal templates, which we demonstrate captures structural features that sequence similarity alone is unable to do. Template selection is carried out separately for each helix, allowing both single-template models and fragment-based models to be built. Additionally, GPCR-SSFE 2.0 stores a comprehensive set of pre-calculated and downloadable homology models and also incorporates interactive loop modeling using the tool SL2, allowing knowledge-based input by the user to guide the selection process. For visual analysis, the NGL viewer is embedded into the result pages. Finally, blind-testing using two recently published structures shows that GPCR-SSFE 2.0 performs comparably or better than other state-of-the art GPCR modeling web servers.

Binding site comparisons for target-centered drug discovery

INTRODUCTION

The success of binding site comparisons in drug discovery is based on the recognized fact that many different proteins have similar binding sites. Indeed, binding site comparisons have found many uses in drug development and have the potential to dramatically cut the cost and shorten the time necessary for the development of new drugs. Areas covered: The authors review recent methods for comparing protein binding sites and their use in drug repurposing and polypharmacology. They examine emerging fields including the use of binding site comparisons in precision medicine, the prediction of structured water molecules, the search for targets of natural compounds, and their application in the development of protein-based drugs by loop modeling and for comparison of RNA binding sites. Expert opinion: Binding site comparisons have produced many interesting results in drug development, but relatively little work has been done on protein-protein interaction sites, which are particularly relevant in view of the success of biological drugs. Growth of protein loop modeling for modulating biological drugs is anticipated. The fusion of currently distinct methods for the comparison of RNA and protein binding sites into a single comprehensive approach could allow the search for new selective ribosomal antibiotics and initiate pharmaceutical research into other nucleoproteins.

Direct protein-lipid interactions shape the conformational landscape of secondary transporters

Secondary transporters undergo structural rearrangements to catalyze substrate translocation across the cell membrane – yet how such conformational changes happen within a lipid environment remains poorly understood. Here, we combine hydrogen-deuterium exchange mass spectrometry (HDX-MS) with molecular dynamics (MD) simulations to understand how lipids regulate the conformational dynamics of secondary transporters at the molecular level. Using the homologous transporters XylE, LacY and GlpT from Escherichia coli as model systems, we discover that conserved networks of charged residues act as molecular switches that drive the conformational transition between different states. We reveal that these molecular switches are regulated by interactions with surrounding phospholipids and show that phosphatidylethanolamine interferes with the formation of the conserved networks and favors an inward-facing state. Overall, this work provides insights into the importance of lipids in shaping the conformational landscape of an important class of transporters.

Secondary transporters catalyse substrate translocation across the cell membrane but the role of lipids during the transport cycle remains unclear. Here authors used hydrogen-deuterium exchange mass spectrometry and molecular dynamics simulations to understand how lipids regulate the conformational dynamics of secondary transporters.

DaReUS-Loop: accurate loop modeling using fragments from remote or unrelated proteins

Despite efforts during the past decades, loop modeling remains a difficult part of protein structure modeling. Several approaches have been developed in the framework of crystal structures. However, for homology models, the modeling of loops is still far from being solved. We propose DaReUS-Loop, a data-based approach that identifies loop candidates mining the complete set of experimental structures available in the Protein Data Bank. Candidate filtering relies on local conformation profile-profile comparison, together with physico-chemical scoring. Applied to three different template-based test sets, DaReUS-Loop shows significant increase in the number of high-accuracy loops, and significant enhancement for modeling long loops. A special advantage is that our method proposes a prediction confidence score that correlates well with the expected accuracy of the loops. Strikingly, over 50% of successful loop models are derived from unrelated proteins, indicating that fragments under similar constraints tend to adopt similar structure, beyond mere homology.

FragFit: a web-application for interactive modeling of protein segments into cryo-EM density maps

Cryo-electron microscopy (cryo-EM) is a standard method to determine the three-dimensional structures of molecular complexes. However, easy to use tools for modeling of protein segments into cryo-EM maps are sparse. Here, we present the FragFit web-application, a web server for interactive modeling of segments of up to 35 amino acids length into cryo-EM density maps. The fragments are provided by a regularly updated database containing at the moment about 1 billion entries extracted from PDB structures and can be readily integrated into a protein structure. Fragments are selected based on geometric criteria, sequence similarity and fit into a given cryo-EM density map. Web-based molecular visualization with the NGL Viewer allows interactive selection of fragments. The FragFit web-application, accessible at http://proteinformatics.de/FragFit, is free and open to all users, without any login requirements.

The Role of the Active Site Flap in Streptavidin/Biotin Complex Formation

Obtaining a detailed description of how active site flap motion affects substrate or ligand binding will advance structure-based drug design (SBDD) efforts on systems including the kinases, HSP90, HIV protease, ureases, etc. Through this understanding, we will be able to design better inhibitors and better proteins that have desired functions. Herein we address this issue by generating the relevant configurational states of a protein flap on the molecular energy landscape using an approach we call MT_Flex-b and then following this with a procedure to estimate the free energy associated with the motion of the flap region. To illustrate our overall workflow, we explored the free energy changes in the streptavidin/biotin system upon introducing conformational flexibility in loop_3-4 in the biotin unbound ( apo) and bound ( holo) state. The free energy surfaces were created using the Movable Type free energy method, and for further validation, we compared them to potential of mean force (PMF) generated free energy surfaces using MD simulations employing the FF99SBILDN and FF14SB force fields. We also estimated the free energy thermodynamic cycle using an ensemble of closed-like and open-like end states for the ligand unbound and bound states and estimated the binding free energy to be approximately -16.2 kcal/mol (experimental -18.3 kcal/mol). The good agreement between MT_Flex-b in combination with the MT method with experiment and MD simulations supports the effectiveness of our strategy in obtaining unique insights into the motions in proteins that can then be used in a range of biological and biomedical applications.

Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction

Motivation

Loops are often vital for protein function, however, their irregular structures make them difficult to model accurately. Current loop modelling algorithms can mostly be divided into two categories: knowledge-based, where databases of fragments are searched to find suitable conformations and ab initio, where conformations are generated computationally. Existing knowledge-based methods only use fragments that are the same length as the target, even though loops of slightly different lengths may adopt similar conformations. Here, we present a novel method, Sphinx, which combines ab initio techniques with the potential extra structural information contained within loops of a different length to improve structure prediction.

Results

We show that Sphinx is able to generate high-accuracy predictions and decoy sets enriched with near-native loop conformations, performing better than the ab initio algorithm on which it is based. In addition, it is able to provide predictions for every target, unlike some knowledge-based methods. Sphinx can be used successfully for the difficult problem of antibody H3 prediction, outperforming RosettaAntibody, one of the leading H3-specific ab initio methods, both in accuracy and speed.

Availability and Implementation

Sphinx is available at http://opig.stats.ox.ac.uk/webapps/sphinx.

Supplementary information

Supplementary data are available at Bioinformatics online.

A fragment based method for modeling of protein segments into cryo-EM density maps

BACKGROUND

Single-particle analysis of electron cryo-microscopy (cryo-EM) is a key technology for elucidation of macromolecular structures. Recent technical advances in hardware and software developments significantly enhanced the resolution of cryo-EM density maps and broadened the applicability and the circle of users. To facilitate modeling of macromolecules into cryo-EM density maps, fast and easy to use methods for modeling are now demanded.

RESULTS

Here we investigated and benchmarked the suitability of a classical and well established fragment-based approach for modeling of segments into cryo-EM density maps (termed FragFit). FragFit uses a hierarchical strategy to select fragments from a pre-calculated set of billions of fragments derived from structures deposited in the Protein Data Bank, based on sequence similarly, fit of stem atoms and fit to a cryo-EM density map. The user only has to specify the sequence of the segment and the number of the N- and C-terminal stem-residues in the protein. Using a representative data set of protein structures, we show that protein segments can be accurately modeled into cryo-EM density maps of different resolution by FragFit. Prediction quality depends on segment length, the type of secondary structure of the segment and local quality of the map.

CONCLUSION

Fast and automated calculation of FragFit renders it applicable for implementation of interactive web-applications e.g. to model missing segments, flexible protein parts or hinge-regions into cryo-EM density maps.

A comprehensive structural model for the human KCNQ1/KCNE1 ion channel

The voltage-gated KCNQ1/KCNE1 potassium ion channel complex, forms the slow delayed rectifier (I_Ks) current in the heart, which plays an important role in heart signaling. The importance of KCNQ1/KCNE1 channel's function is further implicated by the linkage between loss-of-function and gain-of-function mutations in KCNQ1 or KCNE1, and long QT syndromes, congenital atrial fibrillation, and short QT syndrome. Also, KCNQ1/KCNE1 channels are an off-target for many non-cardiovascular drugs, leading to fatal cardiac irregularities. One solution to address and study the mentioned aspects of KCNQ1/KNCE1 channel would be the structural studies using a validated and accurate model. Along the same line in this study, we have used several top-notch modeling approaches to build a structural model for the open state of KCNQ1 protein, which is both accurate and compatible with available experimental data. Next, we included the KCNE1 protein components using data-driven protein-protein docking simulations, encompassing a 4:2 stoichiometry to complete the picture of the channel complex formed by these two proteins. All the protein systems generated through these processes were refined by long Molecular Dynamics simulations. The refined models were analyzed extensively to infer data about the interaction of KCNQ1 channel with its accessory KCNE1 beta subunits.

Lipids and ions traverse the membrane by the same physical pathway in the nhTMEM16 scramblase

From bacteria to mammals, different phospholipid species are segregated between the inner and outer leaflets of the plasma membrane by ATP-dependent lipid transporters. Disruption of this asymmetry by ATP-independent phospholipid scrambling is important in cellular signaling, but its mechanism remains incompletely understood. Using MD simulations coupled with experimental assays, we show that the surface hydrophilic transmembrane cavity exposed to the lipid bilayer on the fungal scramblase nhTMEM16 serves as the pathway for both lipid translocation and ion conduction across the membrane. Ca²⁺ binding stimulates its open conformation by altering the structure of transmembrane helices that line the cavity. We have identified key amino acids necessary for phospholipid scrambling and validated the idea that ions permeate TMEM16 Cl^- channels via a structurally homologous pathway by showing that mutation of two residues in the pore region of the TMEM16A Ca²⁺-activated Cl^- channel convert it into a robust scramblase.

Interpretation of Seemingly Contradictory Data: Low NMR S2 Order Parameters Observed in Helices and High NMR S2 Order Parameters in Disordered Loops of the Protein hGH at Low pH

At low pH, human growth hormone (hGH) adopts a partially folded state, in which the native helices are maintained, but the long loop regions and side-chain packing become disordered. Some of the S² order parameters for backbone N-H vectors derived from NMR relaxation measurements on hGH at low pH initially seem contradictory. Three isolated residues (15, 20, and 171) in helices A and D exhibit low order parameter values (<0.5) indicating flexibility, whereas residue 143 in the centre of a long flexible loop region has a high order parameter (0.82). Using S² order parameter restraining MD simulations, this paradox has been resolved. Low S² values in helices are due to the presence of a mixture of 3₁₀ -helical and α-helical hydrogen bonds. High S² values in relatively disordered parts of a protein may be due to fluctuating networks of hydrogen bonds between the backbone and the side chains, which restrict the motion of N-H bond vectors.

Antibody H3 Structure Prediction

Antibodies are proteins of the immune system that are able to bind to a huge variety of different substances, making them attractive candidates for therapeutic applications. Antibody structures have the potential to be useful during drug development, allowing the implementation of rational design procedures. The most challenging part of the antibody structure to experimentally determine or model is the H3 loop, which in addition is often the most important region in an antibody's binding site. This review summarises the approaches used so far in the pursuit of accurate computational H3 structure prediction.

Molecular Modeling of Transporters: From Low Resolution Cryo-Electron Microscopy Map to Conformational Exploration. The Example of TSPO

This chapter describes a protocol to establish a three-dimensional (3D) model of a protein and to explore its conformational landscape. It combines predictions from up-to-date bioinformatics methods with low-resolution experimental data. It also proposes to examine rapidly the dynamics of the protein using molecular dynamics simulations with a coarse-grained force field. Tools for analyzing these trajectories are suggested as well as those for constructing all-atoms models. Thus, starting from a protein sequence and using free software, the user can get important conformational information, which might improve the knowledge about the protein function.

The Framework of Computational Protein Design

Computational protein design (CPD) has established itself as a leading field in basic and applied science with a strong coupling between the two. Proteins are computationally designed from the level of amino acids to the level of a functional protein complex. Design targets range from increased thermo- (or other) stability to specific requested reactions such as protein-protein binding, enzymatic reactions, or nanotechnology applications. The design scheme may encompass small regions of the proteins or the entire protein. In either case, the design may aim at the side-chains or at the full backbone conformation. Herein, the main framework for the process is outlined highlighting key elements in the CPD iterative cycle. These include the very definition of CPD, the diverse goals of CPD, components of the CPD protocol, methods for searching sequence and structure space, scoring functions, and augmenting the CPD with other optimization tools. Taken together, this chapter aims to introduce the framework of CPD.

Microscopic Characterization of Membrane Transporter Function by In Silico Modeling and Simulation

Membrane transporters mediate one of the most fundamental processes in biology. They are the main gatekeepers controlling active traffic of materials in a highly selective and regulated manner between different cellular compartments demarcated by biological membranes. At the heart of the mechanism of membrane transporters lie protein conformational changes of diverse forms and magnitudes, which closely mediate critical aspects of the transport process, most importantly the coordinated motions of remotely located gating elements and their tight coupling to chemical processes such as binding, unbinding and translocation of transported substrate and cotransported ions, ATP binding and hydrolysis, and other molecular events fueling uphill transport of the cargo. An increasing number of functional studies have established the active participation of lipids and other components of biological membranes in the function of transporters and other membrane proteins, often acting as major signaling and regulating elements. Understanding the mechanistic details of these molecular processes require methods that offer high spatial and temporal resolutions. Computational modeling and simulations technologies empowered by advanced sampling and free energy calculations have reached a sufficiently mature state to become an indispensable component of mechanistic studies of membrane transporters in their natural environment of the membrane. In this article, we provide an overview of a number of major computational protocols and techniques commonly used in membrane transporter modeling and simulation studies. The article also includes practical hints on effective use of these methods, critical perspectives on their strengths and weak points, and examples of their successful applications to membrane transporters, selected from the research performed in our own laboratory.

SL2: an interactive webtool for modeling of missing segments in proteins

SuperLooper2 (SL2) (http://proteinformatics.charite.de/sl2) is the updated version of our previous web-server SuperLooper, a fragment based tool for the prediction and interactive placement of loop structures into globular and helical membrane proteins. In comparison to our previous version, SL2 benefits from both a considerably enlarged database of fragments derived from high-resolution 3D protein structures of globular and helical membrane proteins, and the integration of a new protein viewer. The database, now with double the content, significantly improved the coverage of fragment conformations and prediction quality. The employment of the NGL viewer for visualization of the protein under investigation and interactive selection of appropriate loops makes SL2 independent of third-party plug-ins and additional installations.

Structural modeling of G-protein coupled receptors: An overview on automatic web-servers

Despite the significant efforts and discoveries during the last few years in G protein-coupled receptor (GPCR) expression and crystallization, the receptors with known structures to date are limited only to a small fraction of human GPCRs. The lack of experimental three-dimensional structures of the receptors represents a strong limitation that hampers a deep understanding of their function. Computational techniques are thus a valid alternative strategy to model three-dimensional structures. Indeed, recent advances in the field, together with extraordinary developments in crystallography, in particular due to its ability to capture GPCRs in different activation states, have led to encouraging results in the generation of accurate models. This, prompted the community of modelers to render their methods publicly available through dedicated databases and web-servers. Here, we present an extensive overview on these services, focusing on their advantages, drawbacks and their role in successful applications. Future challenges in the field of GPCR modeling, such as the predictions of long loop regions and the modeling of receptor activation states are presented as well.

Role of Structural Dynamics at the Receptor G Protein Interface for Signal Transduction

GPCRs catalyze GDP/GTP exchange in the α-subunit of heterotrimeric G proteins (Gαßγ) through displacement of the Gα C-terminal α5 helix, which directly connects the interface of the active receptor (R*) to the nucleotide binding pocket of G. Hydrogen-deuterium exchange mass spectrometry and kinetic analysis of R* catalysed G protein activation have suggested that displacement of α5 starts from an intermediate GDP bound complex (R*•GGDP). To elucidate the structural basis of receptor-catalysed displacement of α5, we modelled the structure of R*•GGDP. A flexible docking protocol yielded an intermediate R*•GGDP complex, with a similar overall arrangement as in the X-ray structure of the nucleotide free complex (R*•Gempty), however with the α5 C-terminus (GαCT) forming different polar contacts with R*. Starting molecular dynamics simulations of GαCT bound to R* in the intermediate position, we observe a screw-like motion, which restores the specific interactions of α5 with R* in R*•Gempty. The observed rotation of α5 by 60° is in line with experimental data. Reformation of hydrogen bonds, water expulsion and formation of hydrophobic interactions are driving forces of the α5 displacement. We conclude that the identified interactions between R* and G protein define a structural framework in which the α5 displacement promotes direct transmission of the signal from R* to the GDP binding pocket.

BCSearch: fast structural fragment mining over large collections of protein structures

Resources to mine the large amount of protein structures available today are necessary to better understand how amino acid variations are compatible with conformation preservation, to assist protein design, engineering and, further, the development of biologic therapeutic compounds. BCSearch is a versatile service to efficiently mine large collections of protein structures. It relies on a new approach based on a Binet-Cauchy kernel that is more discriminative than the widely used root mean square deviation criterion. It has statistics independent of size even for short fragments, and is fast. The systematic mining of large collections of structures such as the complete SCOPe protein structural classification or comprehensive subsets of the Protein Data Bank can be performed in few minutes. Based on this new score, we propose four innovative applications: BCFragSearch and BCMirrorSearch, respectively, search for fragments similar and anti-similar to a query and return information on the diversity of the sequences of the hits. BCLoopSearch identifies candidate fragments of fixed size matching the flanks of a gaped structure. BCSpecificitySearch analyzes a complete protein structure and returns information about sites having few similar fragments. BCSearch is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/BCSearch.

Identification of STAT1 and STAT3 specific inhibitors using comparative virtual screening and docking validation

Signal transducers and activators of transcription (STATs) facilitate action of cytokines, growth factors and pathogens. STAT activation is mediated by a highly conserved SH2 domain, which interacts with phosphotyrosine motifs for specific STAT-receptor contacts and STAT dimerization. The active dimers induce gene transcription in the nucleus by binding to a specific DNA-response element in the promoter of target genes. Abnormal activation of STAT signaling pathways is implicated in many human diseases, like cancer, inflammation and auto-immunity. Searches for STAT-targeting compounds, exploring the phosphotyrosine (pTyr)-SH2 interaction site, yielded many small molecules for STAT3 but sparsely for other STATs. However, many of these inhibitors seem not STAT3-specific, thereby questioning the present modeling and selection strategies of SH2 domain-based STAT inhibitors. We generated new 3D structure models for all human (h)STATs and developed a comparative in silico docking strategy to obtain further insight into STAT-SH2 cross-binding specificity of a selection of previously identified STAT3 inhibitors. Indeed, by primarily targeting the highly conserved pTyr-SH2 binding pocket the majority of these compounds exhibited similar binding affinity and tendency scores for all STATs. By comparative screening of a natural product library we provided initial proof for the possibility to identify STAT1 as well as STAT3-specific inhibitors, introducing the ‘STAT-comparative binding affinity value’ and ‘ligand binding pose variation’ as selection criteria. In silico screening of a multi-million clean leads (CL) compound library for binding of all STATs, likewise identified potential specific inhibitors for STAT1 and STAT3 after docking validation. Based on comparative virtual screening and docking validation, we developed a novel STAT inhibitor screening tool that allows identification of specific STAT1 and STAT3 inhibitory compounds. This could increase our understanding of the functional role of these STATs in different diseases and benefit the clinical need for more drugable STAT inhibitors with high specificity, potency and excellent bioavailability.

Expanding the horizons of G protein-coupled receptor structure-based ligand discovery and optimization using homology models

We show the key role of structural homology models in GPCR structure-based lead discovery and optimization, highlighting methodological aspects, recent progress and future directions.

Identification of Plant Homologues of Dual Specificity Yak1-Related Kinases

Currently, Dual Specificity YAK1-Related Kinases (MNB/DYRK) were found in slime molds, protista, fungi, and animals, but the existence of plant homologues is still unclear. In the present study, we have identified 14 potential plant homologues with the previously unknown functions, based on the strong sequence similarity. The results of bioinformatics analysis revealed their correspondence to DYRK1A, DYRK1B, DYRK3, and DYRK4. For two plant homologues of animal DYRK1A from Physcomitrella patens and Arabidopsis thaliana spatial structures of catalytic domains were predicted, as well as their complexes with ADP and selective inhibitor d15. Comparative analysis of 3D-structures of the human DYRK1A and plant homologues, their complexes with the specific inhibitors, and results of molecular dynamics confirm their structural and functional similarity with high probability. Preliminary data indicate the presence of potential MNB/DYRK specific phosphorylation sites in such proteins associated with plant cytoskeleton as plant microtubule-associated proteins WVD2 and WDL1, and FH5 and SCAR2 involved in the organization and polarity of the actin cytoskeleton and some kinesin-like microtubule motor proteins.

Regulation of the mammalian elongation cycle by subunit rolling: a eukaryotic-specific ribosome rearrangement

The extent to which bacterial ribosomes and the significantly larger eukaryotic ribosomes share the same mechanisms of ribosomal elongation is unknown. Here, we present subnanometer resolution cryoelectron microscopy maps of the mammalian 80S ribosome in the posttranslocational state and in complex with the eukaryotic eEF1A⋅Val-tRNA⋅GMPPNP ternary complex, revealing significant differences in the elongation mechanism between bacteria and mammals. Surprisingly, and in contrast to bacterial ribosomes, a rotation of the small subunit around its long axis and orthogonal to the well-known intersubunit rotation distinguishes the posttranslocational state from the classical pretranslocational state ribosome. We term this motion "subunit rolling." Correspondingly, a mammalian decoding complex visualized in substates before and after codon recognition reveals structural distinctions from the bacterial system. These findings suggest how codon recognition leads to GTPase activation in the mammalian system and demonstrate that in mammalia subunit rolling occurs during tRNA selection.

Fast protein loop sampling and structure prediction using distance-guided sequential chain-growth Monte Carlo method

Loops in proteins are flexible regions connecting regular secondary structures. They are often involved in protein functions through interacting with other molecules. The irregularity and flexibility of loops make their structures difficult to determine experimentally and challenging to model computationally. Conformation sampling and energy evaluation are the two key components in loop modeling. We have developed a new method for loop conformation sampling and prediction based on a chain growth sequential Monte Carlo sampling strategy, called Distance-guided Sequential chain-Growth Monte Carlo (DISGRO). With an energy function designed specifically for loops, our method can efficiently generate high quality loop conformations with low energy that are enriched with near-native loop structures. The average minimum global backbone RMSD for 1,000 conformations of 12-residue loops is 1:53 A° , with a lowest energy RMSD of 2:99 A° , and an average ensembleRMSD of 5:23 A° . A novel geometric criterion is applied to speed up calculations. The computational cost of generating 1,000 conformations for each of the x loops in a benchmark dataset is only about 10 cpu minutes for 12-residue loops, compared to ca 180 cpu minutes using the FALCm method. Test results on benchmark datasets show that DISGRO performs comparably or better than previous successful methods, while requiring far less computing time. DISGRO is especially effective in modeling longer loops (10-17 residues).

LoopWeaver: loop modeling by the weighted scaling of verified proteins

Modeling loops is a necessary step in protein structure determination, even with experimental nuclear magnetic resonance (NMR) data, it is widely known to be difficult. Database techniques have the advantage of producing a higher proportion of predictions with subangstrom accuracy when compared with ab initio techniques, but the disadvantage of also producing a higher proportion of clashing or highly inaccurate predictions. We introduce LoopWeaver, a database method that uses multidimensional scaling to achieve better, clash-free placement of loops obtained from a database of protein structures. This allows us to maintain the above-mentioned advantage while avoiding the disadvantage. Test results show that we achieve significantly better results than all other methods, including Modeler, Loopy, SuperLooper, and Rapper, before refinement. With refinement, our results (LoopWeaver and Loopy consensus) are better than ROSETTA, with 0.42 Å RMSD on average for 206 length 6 loops, 0.64 Å local RMSD for 168 length 7 loops, 0.81Å RMSD for 117 length 8 loops, and 0.98 Å RMSD for length 9 loops, while ROSETTA has 0.55, 0.79, 1.16, 1.42, respectively, at the same average time limit (3 hours). When we allow ROSETTA to run for over a week, it approaches, but does not surpass, our accuracy.

Cloud-based simulations on Google Exacycle reveal ligand modulation of GPCR activation pathways

Simulations can provide tremendous insight into the atomistic details of biological mechanisms, but micro- to millisecond timescales are historically only accessible on dedicated supercomputers. We demonstrate that cloud computing is a viable alternative that brings long-timescale processes within reach of a broader community. We used Google's Exacycle cloud-computing platform to simulate two milliseconds of dynamics of a major drug target, the G-protein-coupled receptor β2AR. Markov state models aggregate independent simulations into a single statistical model that is validated by previous computational and experimental results. Moreover, our models provide an atomistic description of the activation of a G-protein-coupled receptor and reveal multiple activation pathways. Agonists and inverse agonists interact differentially with these pathways, with profound implications for drug design.

ArchDB 2014: structural classification of loops in proteins

The function of a protein is determined by its three-dimensional structure, which is formed by regular (i.e. β-strands and α-helices) and non-periodic structural units such as loops. Compared to regular structural elements, non-periodic, non-repetitive conformational units enclose a much higher degree of variability—raising difficulties in the identification of regularities, and yet represent an important part of the structure of a protein. Indeed, loops often play a pivotal role in the function of a protein and different aspects of protein folding and dynamics. Therefore, the structural classification of protein loops is an important subject with clear applications in homology modelling, protein structure prediction, protein design (e.g. enzyme design and catalytic loops) and function prediction. ArchDB, the database presented here (freely available at http://sbi.imim.es/archdb), represents such a resource and has been an important asset for the scientific community throughout the years. In this article, we present a completely reworked and updated version of ArchDB. The new version of ArchDB features a novel, fast and user-friendly web-based interface, and a novel graph-based, computationally efficient, clustering algorithm. The current version of ArchDB classifies 149,134 loops in 5739 classes and 9608 subclasses.

Fragment-based modeling of membrane protein loops: successes, failures, and prospects for the future

Membrane proteins (MPs) have become a major focus in structure prediction, due to their medical importance. There is, however, a lack of fast and reliable methods that specialize in the modeling of MP loops. Often methods designed for soluble proteins (SPs) are applied directly to MPs. In this article, we investigate the validity of such an approach in the realm of fragment-based methods. We also examined the differences in membrane and soluble protein loops that might affect accuracy. We test our ability to predict soluble and MP loops with the previously published method FREAD. We show that it is possible to predict accurately the structure of MP loops using a database of MP fragments (0.5-1 Å median root-mean-square deviation). The presence of homologous proteins in the database helps prediction accuracy. However, even when homologues are removed better results are still achieved using fragments of MPs (0.8-1.6 Å) rather than SPs (1-4 Å) to model MP loops. We find that many fragments of SPs have shapes similar to their MP counterparts but have very different sequences; however, they do not appear to differ in their substitution patterns. Our findings may allow further improvements to fragment-based loop modeling algorithms for MPs. The current version of our proof-of-concept loop modeling protocol produces high-accuracy loop models for MPs and is available as a web server at http://medeller.info/fread.

Construction and validation of a homology model of the human voltage-gated proton channel hHV1

The topological similarity of voltage-gated proton channels (H_V1s) to the voltage-sensing domain (VSD) of other voltage-gated ion channels raises the central question of whether H_V1s have a similar structure. We present the construction and validation of a homology model of the human H_V1 (hH_V1). Multiple structural alignment was used to construct structural models of the open (proton-conducting) state of hH_V1 by exploiting the homology of hH_V1 with VSDs of K⁺ and Na⁺ channels of known three-dimensional structure. The comparative assessment of structural stability of the homology models and their VSD templates was performed using massively repeated molecular dynamics simulations in which the proteins were allowed to relax from their initial conformation in an explicit membrane mimetic. The analysis of structural deviations from the initial conformation based on up to 125 repeats of 100-ns simulations for each system reveals structural features consistently retained in the homology models and leads to a consensus structural model for hH_V1 in which well-defined external and internal salt-bridge networks stabilize the open state. The structural and electrostatic properties of this open-state model are compatible with proton translocation and offer an explanation for the reversal of charge selectivity in neutral mutants of Asp¹¹². Furthermore, these structural properties are consistent with experimental accessibility data, providing a valuable basis for further structural and functional studies of hH_V1. Each Arg residue in the S4 helix of hH_V1 was replaced by His to test accessibility using Zn²⁺ as a probe. The two outermost Arg residues in S4 were accessible to external solution, whereas the innermost one was accessible only to the internal solution. Both modeling and experimental data indicate that in the open state, Arg²¹¹, the third Arg residue in the S4 helix in hH_V1, remains accessible to the internal solution and is located near the charge transfer center, Phe¹⁵⁰.

Functional diversity and structural disorder in the human ubiquitination pathway

The ubiquitin-proteasome system plays a central role in cellular regulation and protein quality control (PQC). The system is built as a pyramid of increasing complexity, with two E1 (ubiquitin activating), few dozen E2 (ubiquitin conjugating) and several hundred E3 (ubiquitin ligase) enzymes. By collecting and analyzing E3 sequences from the KEGG BRITE database and literature, we assembled a coherent dataset of 563 human E3s and analyzed their various physical features. We found an increase in structural disorder of the system with multiple disorder predictors (IUPred – E1: 5.97%, E2: 17.74%, E3: 20.03%). E3s that can bind E2 and substrate simultaneously (single subunit E3, ssE3) have significantly higher disorder (22.98%) than E3s in which E2 binding (multi RING-finger, mRF, 0.62%), scaffolding (6.01%) and substrate binding (adaptor/substrate recognition subunits, 17.33%) functions are separated. In ssE3s, the disorder was localized in the substrate/adaptor binding domains, whereas the E2-binding RING/HECT-domains were structured. To demonstrate the involvement of disorder in E3 function, we applied normal modes and molecular dynamics analyses to show how a disordered and highly flexible linker in human CBL (an E3 that acts as a regulator of several tyrosine kinase-mediated signalling pathways) facilitates long-range conformational changes bringing substrate and E2-binding domains towards each other and thus assisting in ubiquitin transfer. E3s with multiple interaction partners (as evidenced by data in STRING) also possess elevated levels of disorder (hubs, 22.90% vs. non-hubs, 18.36%). Furthermore, a search in PDB uncovered 21 distinct human E3 interactions, in 7 of which the disordered region of E3s undergoes induced folding (or mutual induced folding) in the presence of the partner. In conclusion, our data highlights the primary role of structural disorder in the functions of E3 ligases that manifests itself in the substrate/adaptor binding functions as well as the mechanism of ubiquitin transfer by long-range conformational transitions.

Virtual and biophysical screening targeting the γ-tubulin complex--a new target for the inhibition of microtubule nucleation

Microtubules are the main constituents of mitotic spindles. They are nucleated in large amounts during spindle assembly, from multiprotein complexes containing γ-tubulin and associated γ-tubulin complex proteins (GCPs). With the aim of developing anti-cancer drugs targeting these nucleating complexes, we analyzed the interface between GCP4 and γ-tubulin proteins usually located in a multiprotein complex named γ-TuRC (γ-Tubulin Ring Complex). 10 ns molecular dynamics simulations were performed on the heterodimers to obtain a stable complex in silico and to analyze the residues involved in persistent protein-protein contacts, responsible for the stability of the complex. We demonstrated in silico the existence of a binding pocket at the interface between the two proteins upon complex formation. By combining virtual screening using a fragment-based approach and biophysical screening, we found several small molecules that bind specifically to this pocket. Sub-millimolar fragments have been experimentally characterized on recombinant proteins using differential scanning fluorimetry (DSF) for validation of these compounds as inhibitors. These results open a new avenue for drug development against microtubule-nucleating γ-tubulin complexes.

Novel VEGFR-2 kinase inhibitors identified by the back-to-front approach

We report a novel VEGFR-2 inhibitor, developed by the back-to-front approach. Docking experiments indicated that the 3-chloromethylphenylurea motif of the lead compound occupied the back pocket of VEGFR-2 kinase. An attempt was made to enhance the binding affinity of 1 by expanding the structure to access the front pocket using a triazole linker. A library of 1,4-(disubstituted)-1H-1,2,3-triazoles were screened in silico, and one compound (VH02) was identified with an IC50 against VEGFR-2 of 0.56μM. VH02 showed antiangiogenic effects, inhibiting tube formation in HUVEC cells (EA.hy926) at 0.3μM, 13 times lower than its cytotoxic dose. These enzymatic and cellular activities suggest that VH02 has potential as a lead for further optimization.

patGPCR: a multitemplate approach for improving 3D structure prediction of transmembrane helices of G-protein-coupled receptors

The structures of the seven transmembrane helices of G-protein-coupled receptors are critically involved in many aspects of these receptors, such as receptor stability, ligand docking, and molecular function. Most of the previous multitemplate approaches have built a "super" template with very little merging of aligned fragments from different templates. Here, we present a parallelized multitemplate approach, patGPCR, to predict the 3D structures of transmembrane helices of G-protein-coupled receptors. patGPCR, which employs a bundle-packing related energy function that extends on the RosettaMem energy, parallelizes eight pipelines for transmembrane helix refinement and exchanges the optimized helix structures from multiple templates. We have investigated the performance of patGPCR on a test set containing eight determined G-protein-coupled receptors. The results indicate that patGPCR improves the TM RMSD of the predicted models by 33.64% on average against a single-template method. Compared with other homology approaches, the best models for five of the eight targets built by patGPCR had a lower TM RMSD than that obtained from SWISS-MODEL; patGPCR also showed lower average TM RMSD than single-template and multiple-template MODELLER.

Towards improved quality of GPCR models by usage of multiple templates and profile-profile comparison

G-protein coupled receptors (GPCRs) are targets of nearly one third of the drugs at the current pharmaceutical market. Despite their importance in many cellular processes the crystal structures are available for less than 20 unique GPCRs of the Rhodopsin-like class. Fortunately, even though involved in different signaling cascades, this large group of membrane proteins has preserved a uniform structure comprising seven transmembrane helices that allows quite reliable comparative modeling. Nevertheless, low sequence similarity between the GPCR family members is still a serious obstacle not only in template selection but also in providing theoretical models of acceptable quality. An additional level of difficulty is the prediction of kinks and bulges in transmembrane helices. Usage of multiple templates and generation of alignments based on sequence profiles may increase the rate of success in difficult cases of comparative modeling in which the sequence similarity between GPCRs is exceptionally low. Here, we present GPCRM, a novel method for fast and accurate generation of GPCR models using averaging of multiple template structures and profile-profile comparison. In particular, GPCRM is the first GPCR structure predictor incorporating two distinct loop modeling techniques: Modeller and Rosetta together with the filtering of models based on the Z-coordinate. We tested our approach on all unique GPCR structures determined to date and report its performance in comparison with other computational methods targeting the Rhodopsin-like class. We also provide a database of precomputed GPCR models of the human receptors from that class.

AVAILABILITY

GPCRM SERVER AND DATABASE: http://gpcrm.biomodellab.eu.