The FunFOLD2 server for the prediction of protein-ligand interactions

The FunFOLD2 server is a new independent server that integrates our novel protein–ligand binding site and quality assessment protocols for the prediction of protein function (FN) from sequence via structure. Our guiding principles were, first, to provide a simple unified resource to make our function prediction software easily accessible to all via a simple web interface and, second, to produce integrated output for predictions that can be easily interpreted. The server provides a clean web interface so that results can be viewed on a single page and interpreted by non-experts at a glance. The output for the prediction is an image of the top predicted tertiary structure annotated to indicate putative ligand-binding site residues. The results page also includes a list of the most likely binding site residues and the types of predicted ligands and their frequencies in similar structures. The protein–ligand interactions can also be interactively visualized in 3D using the Jmol plug-in. The raw machine readable data are provided for developers, which comply with the Critical Assessment of Techniques for Protein Structure Prediction data standards for FN predictions. The FunFOLD2 webserver is freely available to all at the following web site: http://www.reading.ac.uk/bioinf/FunFOLD/FunFOLD_form_2_0.html.

Protein-ligand docking study: diterpenes from Juniperus brevifolia as anticancer and antimicrobial agentes

REDCAT: Natural Products and related Redox Catalysts: Basic Research and Applications in Medicine and Agriculture, Aveiro, 25-27 Novembro de 2012.

Peroxisome proliferator-activated receptor structures: ligand specificity, molecular switch and interactions with regulators.

Peroxisome proliferator-activated receptors (PPARs) compose a family of nuclear receptors that mediate the effects of lipidic ligands at the transcriptional level. In this review, we highlight advances in the understanding of the PPAR ligand binding domain (LBD) structure at the atomic level. The overall structure of PPARs LBD is described, and important protein ligand interactions are presented. Structure-activity relationships between isotypes structures and ligand specificity are addressed. It is shown that the numerous experimental three-dimensional structures available, together with in silico simulations, help understanding the role played by the activating function-2 (AF-2) in PPARs activation and its underlying molecular mechanism. The relation between the PPARs constitutive activity and the intrinsic stability of the active conformation is discussed. Finally, the interactions of PPARs LBD with co-activators or co-repressors, as well as with the retinoid X receptor (RXR) are described and considered in relation to PPARs activation.

Structural analysis of TCR-ligand interactions studied on H-2Kd-restricted cloned CTL specific for a photoreactive peptide derivative.

To study the interaction of the TCR with its ligand, the complex of a MHC molecule and an antigenic peptide, we modified a TCR contact residue of a H-2Kd-restricted antigenic peptide with photoreactive 4-azidobenzoic acid. The photoreactive group was a critical component of the epitope recognized by CTL clones derived from mice immunized with such a peptide derivative. The majority of these clones expressed V beta 1-encoded beta chains that were paired with J alpha TA28-encoded alpha chains. For one of these TCR, the photoaffinity labeled sites were mapped on the alpha chain as a J alpha TA28-encoded tryptophan and on the beta chain as a residue of the C' strand of V beta 1. Molecular modeling of this TCR suggested the presence of a hydrophobic pocket that harbors this tryptophan as well as a tyrosine on the C' strand of V beta 1 between which the photoreactive side chain inserts. It is concluded that this avid binding principle may account for the preferential selection of V beta 1 and J alpha TA28-encoded TCR.

CD8 modulation of T-cell antigen receptor-ligand interactions on living cytotoxic T lymphocytes.

Thymocytes and class I major histocompatibility complex (MHC)-restricted cytotoxic T lymphocytes express predominantly heterodimeric alpha/beta CD8. By interacting with non-polymorphic regions of MHC class I molecules CD8 can mediate adhesion or by binding the same MHC molecules that interact with the T-cell antigen receptor (TCR) function as coreceptor in TCR-ligand binding and T-cell activation. Using TCR photoaffinity labelling with a soluble, monomeric photoreactive H-2Kd-peptide derivative complex, we report here that the avidity of TCR-ligand interactions on cloned cytotoxic T cells is very greatly strengthened by CD8. This is primarily explained by coordinate binding of ligand molecules by CD8 and TCR, because substitution of Asp 227 of Kd with Lys severely impaired the TCR-ligand binding on CD8+, but not CD8- cells. Kinetic studies on CD8+ and CD8- cells further showed that CD8 imposes distinct dynamics and a remarkable temperature dependence on TCR-ligand interactions. We propose that the ability of CD8 to act as coreceptor can be modulated by CD8-TCR interactions.

T cell receptor-ligand interactions: a conformational preequilibrium or an induced fit.

Kinetic parameters of T cell receptor (TCR) interactions with its ligand have been proposed to control T cell activation. Analysis of kinetic data obtained has so far produced conflicting insights; here, we offer a consideration of this problem. As a model system, association and dissociation of a soluble TCR (sT1) and its specific ligand, an azidobenzoic acid derivative of the peptide SYIPSAEK-(ABA)I (residues 252-260 from Plasmodium berghei circumsporozoite protein), bound to class I MHC H-2K(d)-encoded molecule (MHCp) were studied by surface plasmon resonance. The association time courses exhibited biphasic patterns. The fast and dominant phase was assigned to ligand association with the major fraction of TCR molecules, whereas the slow component was attributed to the presence of traces of TCR dimers. The association rate constant derived for the fast phase, assuming a reversible, single-step reaction mechanism, was relatively slow and markedly temperature-dependent, decreasing from 7.0 x 10(3) at 25 degrees C to 1.8 x 10(2) M(-1).s(-1) at 4 degrees C. Hence, it is suggested that these observed slow rate constants are the result of unresolved elementary steps of the process. Indeed, our analysis of the kinetic data shows that the time courses of TCR-MHCp interaction fit well to two different, yet closely related mechanisms, where an induced fit or a preequilibrium of two unbound TCR conformers are operational. These mechanisms may provide a rationale for the reported conformational flexibility of the TCR and its unusual ligand recognition properties, which combine high specificity with considerable crossreactivity.

Blind docking of 260 protein-ligand complexes with EADock 2.0.

Molecular docking softwares are one of the important tools of modern drug development pipelines. The promising achievements of the last 10 years emphasize the need for further improvement, as reflected by several recent publications (Leach et al., J Med Chem 2006, 49, 5851; Warren et al., J Med Chem 2006, 49, 5912). Our initial approach, EADock, showed a good performance in reproducing the experimental binding modes for a set of 37 different ligand-protein complexes (Grosdidier et al., Proteins 2007, 67, 1010). This article presents recent improvements regarding the scoring and sampling aspects over the initial implementation, as well as a new seeding procedure based on the detection of cavities, opening the door to blind docking with EADock. These enhancements were validated on 260 complexes taken from the high quality Ligand Protein Database [LPDB, (Roche et al., J Med Chem 2001, 44, 3592)]. Two issues were identified: first, the quality of the initial structures cannot be assumed and a manual inspection and/or a search in the literature are likely to be required to achieve the best performance. Second the description of interactions involving metal ions still has to be improved. Nonetheless, a remarkable success rate of 65% was achieved for a large scale blind docking assay, when considering only the top ranked binding mode and a success threshold of 2 A RMSD to the crystal structure. When looking at the five-top ranked binding modes, the success rate increases up to 76%. In a standard local docking assay, success rates of 75 and 83% were obtained, considering only the top ranked binding mode, or the five top binding modes, respectively.

VAP-1 as drug target in inflammation : structural features determining ligand interactions

Vascular adhesion protein-1 (VAP-1), which belongs to the copper amine oxidases (CAOs), is a validated drug target in inflammatory diseases. Inhibition of VAP-1 blocks the leukocyte trafficking to sites of inflammation and alleviates inflammatory reactions. In this study, a novel set of potent pyridazinone inhibitors is presented together with their X-ray structure complexes with VAP-1. The crystal structure of serum VAP-1 (sVAP-1) revealed an imidazole binding site in the active site channel and, analogously, the pyridazinone inhibitors were designed to bind into the channel. This is the first time human VAP-1 has been crystallized with a reversible inhibitor and the structures reveal detailed information of the binding mode on the atomic level. Similarly to some earlier studied inhibitors of human VAP-1, the designed pyridazinone inhibitors bind rodent VAP-1 with a lower affinity than human VAP-1. Therefore, we made homology models of rodent VAP-1 and compared human and rodent enzymes to determine differences that might affect the inhibitor binding. The comparison of the crystal structures of the human VAP-1 and the mouse VAP-1 homology model revealed key differences important for the species specific binding properties. In general, the channel in mouse VAP-1 is more narrow and polar than the channel in human VAP-1, which is wider and more hydrophobic. The differences are located in the channel leading to the active site, as well as, in the entrance to the active site channel. The information obtained from these studies is of great importance for the development and design of drugs blocking the activity of human VAP-1, as rodents are often used for in vivo testing of candidate drugs. In order to gain more insight into the selective binding properties of the different CAOs in one species a comprehensive evolutionary study of mammalian CAOs was performed. We found that CAOs can be classified into sub-families according to the residues X1 and X2 of the Thr/Ser-X1-X2-Asn-Tyr-Asp active site motif. In the phylogenetic tree, CAOs group into diamine oxidase, retina specific amine oxidase and VAP-1/serum amine oxidase clades based on the residue in the position X2. We also found that VAP-1 and SAO can be further differentiated based on the residue in the position X1. This is the first large-scale comparison of CAO sequences, which explains some of the reasons for the unique substrate specificities within the CAO family.

FunFOLDQA: a quality assessment tool for protein-ligand binding site residue predictions

The estimation of prediction quality is important because without quality measures, it is difficult to determine the usefulness of a prediction. Currently, methods for ligand binding site residue predictions are assessed in the function prediction category of the biennial Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment, utilizing the Matthews Correlation Coefficient (MCC) and Binding-site Distance Test (BDT) metrics. However, the assessment of ligand binding site predictions using such metrics requires the availability of solved structures with bound ligands. Thus, we have developed a ligand binding site quality assessment tool, FunFOLDQA, which utilizes protein feature analysis to predict ligand binding site quality prior to the experimental solution of the protein structures and their ligand interactions. The FunFOLDQA feature scores were combined using: simple linear combinations, multiple linear regression and a neural network. The neural network produced significantly better results for correlations to both the MCC and BDT scores, according to Kendall’s τ, Spearman’s ρ and Pearson’s r correlation coefficients, when tested on both the CASP8 and CASP9 datasets. The neural network also produced the largest Area Under the Curve score (AUC) when Receiver Operator Characteristic (ROC) analysis was undertaken for the CASP8 dataset. Furthermore, the FunFOLDQA algorithm incorporating the neural network, is shown to add value to FunFOLD, when both methods are employed in combination. This results in a statistically significant improvement over all of the best server methods, the FunFOLD method (6.43%), and one of the top manual groups (FN293) tested on the CASP8 dataset. The FunFOLDQA method was also found to be competitive with the top server methods when tested on the CASP9 dataset. To the best of our knowledge, FunFOLDQA is the first attempt to develop a method that can be used to assess ligand binding site prediction quality, in the absence of experimental data.

In silico identification and characterization of protein-ligand binding sites

Protein–ligand binding site prediction methods aim to predict, from amino acid sequence, protein–ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein–ligand interactions has become extremely important to help determine a protein’s functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein–ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein–ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein–ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.

Computational study of ligand binding in lipid transfer proteins: Structures, interfaces, and free energies of protein-lipid complexes

Plant nonspecific lipid transfer proteins (nsLTPs) bind a wide variety of lipids, which allows them to perform disparate functions. Recent reports on their multifunctionality in plant growth processes have posed new questions on the versatile binding abilities of these proteins. The lack of binding specificity has been customarily explained in qualitative terms on the basis of a supposed structural flexibility and nonspecificity of hydrophobic protein-ligand interactions. We present here a computational study of protein-ligand complexes formed between five nsLTPs and seven lipids bound in two different ways in every receptor protein. After optimizing geometries inmolecular dynamics calculations, we computed Poisson- Boltzmann electrostatic potentials, solvation energies, properties of the protein-ligand interfaces, and estimates of binding free energies of the resulting complexes. Our results provide the first quantitative information on the ligand abilities of nsLTPs, shed new light into protein-lipid interactions, and reveal new features which supplement commonly held assumptions on their lack of binding specificity.

CD40-CD40 ligand interactions in experimental allergic encephalomyelitis and multiple sclerosis.

We investigated the role of CD40-CD40 ligand (CD40L) interactions in multiple sclerosis (MS) and experimental allergic encephalomyelitis (EAE). Activated helper T cells expressing CD40L (gp39) surface protein were found in MS patient brain sections, but not in brain tissue sections of normal controls or patients with other neurological disease. CD40L-positive cells were co-localized with CD40-bearing cells in active lesions (perivascular infiltrates). Most of these CD40-bearing cells proved to be of the monocytic lineage (macrophages or microglial cells), and relatively few were B cells. To functionally evaluate CD40-CD40L interactions, EAE was elicited in mice by means of proteolipid-peptide immunization. Treatment with anti-CD40L monoclonal antibody completely prevented the development of disease. Furthermore, administration of anti-CD40L monoclonal antibody, even after disease onset, shortly before maximum disability score was reached led to dramatic disease reduction. The presence of helper T cells expressing CD40L in brain tissue of MS patients and EAE animals, together with the functional evidence provided by successful experimental prevention and therapy in an animal model, indicates that blockade of CD40-CD40L-mediated cellular interactions may be a method for interference in active MS.

Development and Application of Covalent-Labeling Strategies for the Large-Scale Thermodynamic Analysis of Protein Folding and Ligand Binding

Thermodynamic stability measurements on proteins and protein-ligand complexes can offer insights not only into the fundamental properties of protein folding reactions and protein functions, but also into the development of protein-directed therapeutic agents to combat disease. Conventional calorimetric or spectroscopic approaches for measuring protein stability typically require large amounts of purified protein. This requirement has precluded their use in proteomic applications. Stability of Proteins from Rates of Oxidation (SPROX) is a recently developed mass spectrometry-based approach for proteome-wide thermodynamic stability analysis. Since the proteomic coverage of SPROX is fundamentally limited by the detection of methionine-containing peptides, the use of tryptophan-containing peptides was investigated in this dissertation. A new SPROX-like protocol was developed that measured protein folding free energies using the denaturant dependence of the rate at which globally protected tryptophan and methionine residues are modified with dimethyl (2-hydroxyl-5-nitrobenzyl) sulfonium bromide and hydrogen peroxide, respectively. This so-called Hybrid protocol was applied to proteins in yeast and MCF-7 cell lysates and achieved a ~50% increase in proteomic coverage compared to probing only methionine-containing peptides. Subsequently, the Hybrid protocol was successfully utilized to identify and quantify both known and novel protein-ligand interactions in cell lysates. The ligands under study included the well-known Hsp90 inhibitor geldanamycin and the less well-understood omeprazole sulfide that inhibits liver-stage malaria. In addition to protein-small molecule interactions, protein-protein interactions involving Puf6 were investigated using the SPROX technique in comparative thermodynamic analyses performed on wild-type and Puf6-deletion yeast strains. A total of 39 proteins were detected as Puf6 targets and 36 of these targets were previously unknown to interact with Puf6. Finally, to facilitate the SPROX/Hybrid data analysis process and minimize human errors, a Bayesian algorithm was developed for transition midpoint assignment. In summary, the work in this dissertation expanded the scope of SPROX and evaluated the use of SPROX/Hybrid protocols for characterizing protein-ligand interactions in complex biological mixtures.

Distinct conformational properties determined by implicit and explicit representation of protein-solvent interactions. An analytical and computer simulation study

In the protein folding problem, solvent-mediated forces are commonly represented by intra-chain pairwise contact energy. Although this approximation has proven to be useful in several circumstances, it is limited in some other aspects of the problem. Here we show that it is possible to achieve two models to represent the chain-solvent system. one of them with implicit and other with explicit solvent, such that both reproduce the same thermodynamic results. Firstly, lattice models treated by analytical methods, were used to show that the implicit and explicitly representation of solvent effects can be energetically equivalent only if local solvent properties are time and spatially invariant. Following, applying the same reasoning Used for the lattice models, two inter-consistent Monte Carlo off-lattice models for implicit and explicit solvent are constructed, being that now in the latter the solvent properties are allowed to fluctuate. Then, it is shown that the chain configurational evolution as well as the globule equilibrium conformation are significantly distinct for implicit and explicit solvent systems. Actually, strongly contrasting with the implicit solvent version, the explicit solvent model predicts: (i) a malleable globule, in agreement with the estimated large protein-volume fluctuations; (ii) thermal conformational stability, resembling the conformational hear resistance of globular proteins, in which radii of gyration are practically insensitive to thermal effects over a relatively wide range of temperatures; and (iii) smaller radii of gyration at higher temperatures, indicating that the chain conformational entropy in the unfolded state is significantly smaller than that estimated from random coil configurations. Finally, we comment on the meaning of these results with respect to the understanding of the folding process. (C) 2009 Elsevier B.V. All rights reserved.

Synthesis of an analog of the thyroid hormone-binding protein transthyretin via regioselective chemical ligation

Transthyretin is an essential protein responsible for the transport of thyroid hormones and retinol in human serum and is also implicated in the amyloid diseases familial amyloidotic polyneuropathy and senile systemic amyloidosis. Its folding properties and stabilization by ligands are of current interest due to their importance in understanding and combating these diseases, Here we report the solid phase synthesis of the monomeric unit of a transthyretin analog (equivalent to 127 amino acids) using t-Boc chemistry and peptide ligation and its folding to form a functional 54-kDa tetramer, The monomeric unit of the protein was chemically synthesized in three parts (positions 1-51, 54-99, and 102-127) and ligated using a chemoselective thioether ligation chemistry. The synthetic protein was folded and assembled to a tetrameric structure in the presence of transthyretin's native ligand, thyroxine, as shown by gel filtration chromatography, native gel electrophoresis, transthyretin antibody recognition, and thyroid hormone binding. Other folding products included a high molecular weight aggregate as well as a transient dimeric species. This represents one of the largest macromolecules chemically synthesized to date and demonstrates the potential of protein chemical synthesis for investigations of protein-ligand interactions.