Structure Prediction of the Second Extracellular Loop in G-Protein-Coupled Receptors

G-protein-coupled receptors (GPCRs) play key roles in living organisms. Therefore, it is important to determine their functional structures. The second extracellular loop (ECL2) is a functionally important region of GPCRs, which poses significant challenge for computational structure prediction methods. In this work, we evaluated CABS, a well-established protein modeling tool for predicting ECL2 structure in 13 GPCRs. The ECL2s (with between 13 and 34 residues) are predicted in an environment of other extracellular loops being fully flexible and the transmembrane domain fixed in its x-ray conformation. The modeling procedure used theoretical predictions of ECL2 secondary structure and experimental constraints on disulfide bridges. Our approach yielded ensembles of low-energy conformers and the most populated conformers that contained models close to the available x-ray structures. The level of similarity between the predicted models and x-ray structures is comparable to that of other state-of-the-art computational methods. Our results extend other studies by including newly crystallized GPCRs.     

Structure Prediction of the Second Extracellular Loop in G-Protein-Coupled Receptors

G-protein-coupled receptors (GPCRs) play key roles in living organisms. Therefore, it is important to determine their functional structures. The second extracellular loop (ECL2) is a functionally important region of GPCRs, which poses significant challenge for computational structure prediction methods. In this work, we evaluated CABS, a well-established protein modeling tool for predicting ECL2 structure in 13 GPCRs. The ECL2s (with between 13 and 34 residues) are predicted in an environment of other extracellular loops being fully flexible and the transmembrane domain fixed in its x-ray conformation. The modeling procedure used theoretical predictions of ECL2 secondary structure and experimental constraints on disulfide bridges. Our approach yielded ensembles of low-energy conformers and the most populated conformers that contained models close to the available x-ray structures. The level of similarity between the predicted models and x-ray structures is comparable to that of other state-of-the-art computational methods. Our results extend other studies by including newly crystallized GPCRs.     

Binding mode of ecdysone agonists to the receptor: comparative modeling and docking studies

Three-dimensional structure models of the ligand-binding domain of the ecdysone receptor of Heliothis virescens were built by the homology modeling technique from the crystal structures of nuclear receptors. Two models were created based both on known ligand-binding domain structures of the receptors with the highest sequence identity to the ecdysone receptor, and on those of steroid hormone receptors. The latter model, which was found to have better stereochemical quality and be in good agreement with the binding of the steroidal framework of the endogenous agonist 20-hydroxyecdysone, was used for docking studies. The docking of 20-hydroxyecdysone to the receptor model revealed that the ligand molecule can interact with the receptor in a similar manner to other steroid hormone-receptor complexes. The docking of a dibenzoylhydrazine agonist, chromafenozide, was performed based on the correspondences between the molecule and 20-dydroxyecdysone expected by molecular comparison. The interactions of the ligands with the receptor in the complexes modeled were investigated and found to be consistent with known structure-activity relationships.     

Comparative modeling without implicit sequence alignments

MOTIVATION: The number of known protein sequences is about thousand times larger than the number of experimentally solved 3D structures. For more than half of the protein sequences a close or distant structural analog could be identified. The key starting point in a classical comparative modeling is to generate the best possible sequence alignment with a template or templates. With decreasing sequence similarity, the number of errors in the alignments increases and these errors are the main causes of the decreasing accuracy of the molecular models generated. Here we propose a new approach to comparative modeling, which does not require the implicit alignment - the model building phase explores geometric, evolutionary and physical properties of a template (or templates). RESULTS: The proposed method requires prior identification of a template, although the initial sequence alignment is ignored. The model is built using a very efficient reduced representation search engine CABS to find the best possible superposition of the query protein onto the template represented as a 3D multi-featured scaffold. The criteria used include: sequence similarity, predicted secondary structure consistency, local geometric features and hydrophobicity profile. For more difficult cases, the new method qualitatively outperforms existing schemes of comparative modeling. The algorithm unifies de novo modeling, 3D threading and sequence-based methods. The main idea is general and could be easily combined with other efficient modeling tools as Rosetta, UNRES and others.     

Structural and posttranslational analysis of human calcium-binding protein,spermatid-associated 1

Recently, we detected a novel biomarker in human saliva called calcium-binding protein, spermatid-associated 1 (CABS1). CABS1 protein had previously been described only in testis, and little was known of its characteristics other than it was considered a structurally disordered protein. Levels of human CABS1 (hCABS1) in saliva correlate with stress, whereas smaller sized forms of hCABS1 in saliva are associated with resilience to stress. Interestingly, hCABS1 also has an anti-inflammatory peptide sequence near its carboxyl terminus, similar to that of a rat prohormone, submandibular rat 1. We performed phylogenetic and sequence analysis of hCABS1. We found that from 72 CABS1 sequences currently annotated in the National Center for Biotechnology Information protein database, only 14 contain the anti-inflammatory domain “TxIFELL,” all of which are primates. We performed structural unfoldability analysis using PONDER and FoldIndex and discovered three domains that are highly disordered. Predictions of three-dimensional structure of hCABS1 using RaptorX, IonCom, and I-TASSER software agreed with these findings. Predicted neutrophil elastase cleavage density also correlated with hCABS1 regions of high structural disorder. Ligand binding prediction identified Ca²⁺, Mg²⁺, Zn²⁺, leucine, and thiamine pyrophosphate, a pattern observed in enzymes associated with energy metabolism and mitochondrial localization. These new observations on hCABS1 raise intriguing questions about the interconnection between the autonomic nervous system, stress, and the immune system. However, the precise molecular mechanisms involved in the complex biology of hCABS1 remain unclear. We provide a detailed in silico analysis of relevant aspects of the structure and function of hCABS1 and postulate extracellular and intracellular roles.     

Automated prediction of ligand-binding sites in proteins

We present a method, termed AutoLigand, for the prediction of ligand-binding sites in proteins of known structure. The method searches the space surrounding the protein and finds the contiguous envelope with the specified volume of atoms, which has the largest possible interaction energy with the protein. It uses a full atomic representation, with atom types for carbon, hydrogen, oxygen, nitrogen and sulfur (and others, if desired), and is designed to minimize the need for artificial geometry. Testing on a set of 187 diverse protein-ligand complexes has shown that the method is successful in predicting the location and approximate volume of the binding site in 73% of cases. Additional testing was performed on a set of 96 protein-ligand complexes with crystallographic structures of apo and holo forms, and AutoLigand was able to predict the binding site in 80% of the apo structures.     

Distance restraints from crosslinking mass spectrometry: Mining a molecular dynamics simulation database to evaluate lysine–lysine distances

Integrative structural biology attempts to model the structures of protein complexes that are challenging or intractable by classical structural methods (due to size, dynamics, or heterogeneity) by combining computational structural modeling with data from experimental methods. One such experimental method is chemical crosslinking mass spectrometry (XL‐MS), in which protein complexes are crosslinked and characterized using liquid chromatography‐mass spectrometry to pinpoint specific amino acid residues in close structural proximity. The commonly used lysine‐reactive N‐hydroxysuccinimide ester reagents disuccinimidylsuberate (DSS) and bis(sulfosuccinimidyl)suberate (BS³) have a linker arm that is 11.4 Å long when fully extended, allowing C_α (alpha carbon of protein backbone) atoms of crosslinked lysine residues to be up to ～24 Å apart. However, XL‐MS studies on proteins of known structure frequently report crosslinks that exceed this distance. Typically, a tolerance of ～3 Å is added to the theoretical maximum to account for this observation, with limited justification for the chosen value. We used the Dynameomics database, a repository of high‐quality molecular dynamics simulations of 807 proteins representative of diverse protein folds, to investigate the relationship between lysine–lysine distances in experimental starting structures and in simulation ensembles. We conclude that for DSS/BS³, a distance constraint of 26–30 Å between C_α atoms is appropriate. This analysis provides a theoretical basis for the widespread practice of adding a tolerance to the crosslinker length when comparing XL‐MS results to structures or in modeling. We also discuss the comparison of XL‐MS results to MD simulations and known structures as a means to test and validate experimental XL‐MS methods.     

Structure prediction of a complex between the chromosomal protein HMG-D and DNA

Non-histone chromosomal proteins are an important part of nuclear structure and function due to their ability to interact with DNA to form and modulate chromatin structure and regulate gene expression. However, the understanding of the function of chromosomal proteins at the molecular level has been hampered by the lack of structures of chromosomal protein–DNA complexes. We have carried out a molecular dynamics modeling study to provide insight into the mode of DNA binding to the chromosomal HMG-domain protein, HMG-D. Three models of a complex of HMG-D bound to DNA were derived through docking the protein to two different DNA fragments of known structure. Molecular dynamics simulations of the complexes provided data indicating the most favorable model. This model was further refined by molecular dynamics simulation and extensively analyzed. The structure of the corresponding HMG-D-DNA complex exhibits many features seen in the NMR structures of the sequence-specific HMG-domain-DNA complexes, lymphoid enhancer factor 1 (LEF-1) and testis determining factor (SRY). The model reveals differences from these known structures that suggest how chromosomal proteins bind to many different DNA sequences with comparable affinity. Proteins 30:113–135, 1998. © 1998 Wiley-Liss, Inc.     

Protein models: The Grand Challenge of protein docking

Characterization of life processes at the molecular level requires structural details of protein–protein interactions (PPIs). The number of experimentally determined protein structures accounts only for a fraction of known proteins. This gap has to be bridged by modeling, typically using experimentally determined structures as templates to model related proteins. The fraction of experimentally determined PPI structures is even smaller than that for the individual proteins, due to a larger number of interactions than the number of individual proteins, and a greater difficulty of crystallizing protein–protein complexes. The approaches to structural modeling of PPI (docking) often have to rely on modeled structures of the interactors, especially in the case of large PPI networks. Structures of modeled proteins are typically less accurate than the ones determined by X‐ray crystallography or nuclear magnetic resonance. Thus the utility of approaches to dock these structures should be assessed by thorough benchmarking, specifically designed for protein models. To be credible, such benchmarking has to be based on carefully curated sets of structures with levels of distortion typical for modeled proteins. This article presents such a suite of models built for the benchmark set of the X‐ray structures from the Dockground resource ( http://dockground.bioinformatics.ku.edu ) by a combination of homology modeling and Nudged Elastic Band method. For each monomer, six models were generated with predefined C^α root mean square deviation from the native structure (1, 2, …, 6 Å). The sets and the accompanying data provide a comprehensive resource for the development of docking methodology for modeled proteins. Proteins 2014; 82:278–287. © 2013 Wiley Periodicals, Inc.     

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

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

Nucleocytoplasmic transport enters the atomic age

Nucleocytoplasmic transport occurs through nuclear pore complexes (NPCs) and is mediated by saturable transport receptors that shuttle between the nucleus and cytoplasm. Our understanding of the molecular interactions underlying this process has improved dramatically as a result of the elucidation of the crystal structures of several nuclear transport factors either alone or in a complex with other components of the nuclear transport machinery. Furthermore, a conserved family of proteins, which is distinct from the well characterized family of importin beta-like nuclear export receptors, is implicated in the export of messenger RNA to the cytoplasm.     

A flexible docking approach for prediction of T cell receptor–peptide–MHC complexes

T cell receptors (TCRs) are immune proteins that specifically bind to antigenic molecules, which are often foreign peptides presented by major histocompatibility complex proteins (pMHCs), playing a key role in the cellular immune response. To advance our understanding and modeling of this dynamic immunological event, we assembled a protein–protein docking benchmark consisting of 20 structures of crystallized TCR/pMHC complexes for which unbound structures exist for both TCR and pMHC. We used our benchmark to compare predictive performance using several flexible and rigid backbone TCR/pMHC docking protocols. Our flexible TCR docking algorithm, TCRFlexDock, improved predictive success over the fixed backbone protocol, leading to near‐native predictions for 80% of the TCR/pMHC cases among the top 10 models, and 100% of the cases in the top 30 models. We then applied TCRFlexDock to predict the two distinct docking modes recently described for a single TCR bound to two different antigens, and tested several protein modeling scoring functions for prediction of TCR/pMHC binding affinities. This algorithm and benchmark should enable future efforts to predict, and design of uncharacterized TCR/pMHC complexes.     

Purification of the vertebrate nuclear pore complex by biochemical criteria

The nuclear pore is a large and complex biological machine, mediating all signal-directed transport between the nucleus and the cytoplasm. The vertebrate pore has a mass of ∼120 million daltons or 30 times the size of a ribosome. The large size of the pore, coupled to its tight integration in the nuclear lamina, has hampered the isolation of pore complexes from vertebrate sources. We have now developed a strategy for the purification of nuclear pores from in vitro assembled annulate lamellae (AL), a cytoplasmic mimic of the nuclear envelope that lacks a lamina, nuclear matrix, and chromatin-associated proteins. We find that purified pore complexes from annulate lamellae contain every nuclear pore protein tested. In addition, immunoblotting reveals the presence of soluble transport receptors and factors known to play important roles in the transport of macromolecules through the pore. While transport factors such as Ran and NTF2 show only transient interaction with the pores, a number of soluble transport receptors, including importin β, show a tight association with the purified pores. In summary, we report that we have purified the vertebrate pore by biochemical criteria; silver staining reveals ∼40–50 distinct protein bands.     

Structural templates for comparative protein docking

Structural characterization of protein‐protein interactions is important for understanding life processes. Because of the inherent limitations of experimental techniques, such characterization requires computational approaches. Along with the traditional protein‐protein docking (free search for a match between two proteins), comparative (template‐based) modeling of protein‐protein complexes has been gaining popularity. Its development puts an emphasis on full and partial structural similarity between the target protein monomers and the protein‐protein complexes previously determined by experimental techniques (templates). The template‐based docking relies on the quality and diversity of the template set. We present a carefully curated, nonredundant library of templates containing 4950 full structures of binary complexes and 5936 protein‐protein interfaces extracted from the full structures at 12 Å distance cut‐off. Redundancy in the libraries was removed by clustering the PDB structures based on structural similarity. The value of the clustering threshold was determined from the analysis of the clusters and the docking performance on a benchmark set. High structural quality of the interfaces in the template and validation sets was achieved by automated procedures and manual curation. The library is included in the Dockground resource for molecular recognition studies at http://dockground.bioinformatics.ku.edu . Proteins 2015; 83:1563–1570. © 2014 Wiley Periodicals, Inc.     

Reconstruction of low-resolution molecular structures from simulated atomic force microscopy images

BackgroundAtomic Force Microscopy (AFM) is an experimental technique to study structure-function relationship of biomolecules. AFM provides images of biomolecules at nanometer resolution. High-speed AFM experiments produce a series of images following dynamics of biomolecules. To further understand biomolecular functions, information on three-dimensional (3D) structures is beneficial.MethodWe aim to recover 3D information from an AFM image by computational modeling. The AFM image includes only low-resolution representation of a molecule; therefore we represent the structures by a coarse grained model (Gaussian mixture model). Using Monte-Carlo sampling, candidate models are generated to increase similarity between AFM images simulated from the models and target AFM image.ResultsThe algorithm was tested on two proteins to model their conformational transitions. Using a simulated AFM image as reference, the algorithm can produce a low-resolution 3D model of the target molecule. Effect of molecular orientations captured in AFM images on the 3D modeling performance was also examined and it is shown that similar accuracy can be obtained for many orientations.ConclusionsThe proposed algorithm can generate 3D low-resolution protein models, from which conformational transitions observed in AFM images can be interpreted in more detail.General significanceHigh-speed AFM experiments allow us to directly observe biomolecules in action, which provides insights on biomolecular function through dynamics. However, as only partial structural information can be obtained from AFM data, this new AFM based hybrid modeling method would be useful to retrieve 3D information of the entire biomolecule.     

The composite nature of the interaction between nuclear receptors EcR and DHR38

Ecdysteroids coordinate essential biological processes in Drosophila through a complex of two nuclear receptors, the ecdysteroid receptor (EcR) and the ultraspiracle protein (Usp). Biochemical experiments have shown that, in contrast to Usp, the EcR molecule is characterized by high intramolecular plasticity. To investigate whether this plasticity is sufficient to form EcR complexes with nuclear receptors other than Usp, we studied the interaction of EcR with the DHR38 nuclear receptor. Previous in vitro experiments suggested that DHR38 can form complexes with Usp and thus disrupt Usp-EcR interaction with the specific hsp27pal response element. This article provides the experimental evidence that EcR is able to form complexes with DHR38 as well. The recombinant DNA-binding domains (DBDs) of EcR and DHR38 interact specifically on hsp27pal. However, the interaction between the receptors is not restricted to their isolated DBDs. We pre\xadsent data that indicate that the full-length EcR and DHR38 can also form specific complexes within the nuclei of living cells. This interaction is mediated by the hinge region of EcR, which was recently classified as an intrinsically disordered region. Our results indicate that DHR38 might modulate the activity of the Usp-EcR heterodimer by forming complexes with both of its components.     

Effects of Charcoal on Dissociation Kinetics of Nuclear and Cytosolic Steroid-Receptor Complexes from Hen Oviduct

Abstract

The observed rate of dissociation of radioactive estradiol from nuclear estrogen-receptor complexes from hen oviduct has been shown to depend to a large extent on the method used to initiate dissociation. The present study indicates that nuclear progesterone receptors display the same pattern of behavior. Dissociation kinetics of nuclear progesterone receptor extracted from hen oviducts were affected by the method of initiation of dissociation; the rate of dissociation at 25°C when dissociation was initiated with unlabeled steroid was three times that observed when dissociation was initiated by addition of a charcoal/dextran suspension. In contrast to nuclear receptors, both estrogen and progesterone receptors prepared from cytosol displayed only a single rate of dissociation, no matter what the method of initiation of dissociation. These results strengthen the idea that nuclear receptors contain a factor or subunit which may be removed by charcoal, which alters the rate of dissociation of steroid from the complex.     

How inaccuracies in protein structure models affect estimates of protein-ligand interactions: computational analysis of HIV-I protease inhibitor binding

The influence of possible inaccuracies that can arise during homology modeling of protein structures used for ligand binding studies were investigated with the molecular mechanics generalized Born surface area (MM-GBSA) method. For this, a family of well-characterized HIV-I protease-inhibitor complexes was used. Validation of MM-GBSA led to a correlation coefficient ranging from 0.72 to 0.93 between calculated and experimental binding free energies DeltaG. All calculated DeltaG values were based on molecular dynamics simulations with explicit solvent. Errors introduced into the protein structure through misplacement of side-chains during rotamer modeling led to a correlation coefficient between DeltaG(calc) and DeltaG(exp) of 0.75 compared with 0.90 for the correctly placed side chains. This is in contrast to homology models for members of the retroviral protease family with template structures ranging in sequence identity between 32% and 51%. For these protein models, the correlation coefficients vary between 0.84 and 0.87, which is considerably closer to the original protein (0.90). It is concluded that HIV-I low sequence identity with the template structure still allows creating sufficiently reliable homology models to be used for ligand-binding studies, although placement of the rotamers is a critical step during the modeling.