Protein-ligand Binding Sites Research Articles

SitesBase: a database for structure-based protein-ligand binding site comparisons

There are many components which govern the function of a protein within a cell. Here, we focus on the molecular recognition of small molecules and the prediction of common recognition by similarity between protein–ligand binding sites. SitesBase is an easily accessible database which is simple to use and holds information about structural similarities between known ligand binding sites found in the Protein Data Bank. These similarities are presented to the wider community enabling full analysis of molecular recognition and potentially protein structure–function relationships. SitesBase is accessible at .

A Searchable Database for Comparing Protein−Ligand Binding Sites for the Analysis of Structure−Function Relationships

The rapid expansion of structural information for protein-ligand binding sites is potentially an important source of information in structure-based drug design and in understanding ligand cross reactivity and toxicity. We have developed a large database of ligand binding sites extracted automatically from the Protein Data Bank. This has been combined with a method for calculating binding site similarity based on geometric hashing to create a relational database for the retrieval of site similarity and binding site superposition. It contains an all-against-all comparison of binding sites and holds known protein-ligand binding sites, which are made accessible to data mining. Here we demonstrate its utility in two structure-based applications: in determining site similarity and in aiding the derivation of a receptor-based pharmacophore model. The database is available from http://www.bioinformatics.leeds.ac.uk/sb/.

Fold Independent Structural Comparisons of Protein–Ligand Binding Sites for Exploring Functional Relationships

The rapid growth in protein structural data and the emergence of structural genomics projects have increased the need for automatic structure analysis and tools for function prediction. Small molecule recognition is critical to the function of many proteins; therefore, determination of ligand binding site similarity is important for understanding ligand interactions and may allow their functional classification. Here, we present a binding sites database (SitesBase) that given a known protein-ligand binding site allows rapid retrieval of other binding sites with similar structure independent of overall sequence or fold similarity. However, each match is also annotated with sequence similarity and fold information to aid interpretation of structure and functional similarity. Similarity in ligand binding sites can indicate common binding modes and recognition of similar molecules, allowing potential inference of function for an uncharacterised protein or providing additional evidence of common function where sequence or fold similarity is already known. Alternatively, the resource can provide valuable information for detailed studies of molecular recognition including structure-based ligand design and in understanding ligand cross-reactivity. Here, we show examples of atomic similarity between superfamily or more distant fold relatives as well as between seemingly unrelated proteins. Assignment of unclassified proteins to structural superfamiles is also undertaken and in most cases substantiates assignments made using sequence similarity. Correct assignment is also possible where sequence similarity fails to find significant matches, illustrating the potential use of binding site comparisons for newly determined proteins.

Sequence variation in ligand binding sites in proteins

BackgroundThe recent explosion in the availability of complete genome sequences has led to the cataloging of tens of thousands of new proteins and putative proteins. Many of these proteins can be structurally or functionally categorized from sequence conservation alone. In contrast, little attention has been given to the meaning of poorly-conserved sites in families of proteins, which are typically assumed to be of little structural or functional importance.ResultsRecently, using statistical free energy analysis of tetratricopeptide repeat (TPR) domains, we observed that positions in contact with peptide ligands are more variable than surface positions in general. Here we show that statistical analysis of TPRs, ankyrin repeats, Cys2His2 zinc fingers and PDZ domains accurately identifies specificity-determining positions by their sequence variation. Sequence variation is measured as deviation from a neutral reference state, and we present probabilistic and information theory formalisms that improve upon recently suggested methods such as statistical free energies and sequence entropies.ConclusionSequence variation has been used to identify functionally-important residues in four selected protein families. With TPRs and ankyrin repeats, protein families that bind highly diverse ligands, the effect is so pronounced that sequence "hypervariation" alone can be used to predict ligand binding sites.

Effects of continuous administration of paroxetine on ligand binding site and expression of serotonin transporter protein in mouse brain

Selective serotonin reuptake inhibitors (SSRIs), such as paroxetine, are utilized in the treatment of depression and anxiety disorders. Although SSRIs potently interfere with the activity of brain serotonin transporter (SERT) after acute treatment, clinical improvement of psychiatric diseases is observed only after the repeated administration for several weeks (2–6 weeks). The present study was undertaken to investigate the effects of continuous administration of paroxetine on specific [ 3H]paroxetine binding sites and expression of SERT protein in mouse brain. Mice continuously and subcutaneously received paroxetine at doses of 2.67 or 13.3 μmol/kg/day for 21 days by using osmotic minipumps, and the steady-state plasma drug levels were within the range of reported concentrations in the clinical therapy. Continuous administration of paroxetine at theses doses produced significant (25–46%) reduction of [ 3H]paroxetine binding in each brain region (cerebral cortex, striatum, hippocampus, thalamus, midbrain) of mice. In Western blot analysis, expression levels of SERT protein in the thalamus and midbrain of mice were significantly (51% and 61%, respectively) decreased on day 21 after the implantation of minipumps at the higher dose. In conclusion, this study has firstly shown that continuous administration of paroxetine induces significant reduction of not only ligand binding sites of SERT but the protein expression level in mouse brain. Such down-regulation of SERT may partly underlie the therapeutic effect of long-term treatment with SSRIs in human.

Computational prediction of native protein ligand-binding and enzyme active site sequences

Recent studies reveal that the core sequences of many proteins were nearly optimized for stability by natural evolution. Surface residues, by contrast, are not so optimized, presumably because protein function is mediated through surface interactions with other molecules. Here, we sought to determine the extent to which the sequences of protein ligand-binding and enzyme active sites could be predicted by optimization of scoring functions based on protein ligand-binding affinity rather than structural stability. Optimization of binding affinity under constraints on the folding free energy correctly predicted 83% of amino acid residues (94% similar) in the binding sites of two model receptor-ligand complexes, streptavidin-biotin and glucose-binding protein. To explore the applicability of this methodology to enzymes, we applied an identical algorithm to the active sites of diverse enzymes from the peptidase, beta-gal, and nucleotide synthase families. Although simple optimization of binding affinity reproduced the sequences of some enzyme active sites with high precision, imposition of additional, geometric constraints on side-chain conformations based on the catalytic mechanism was required in other cases. With these modifications, our sequence optimization algorithm correctly predicted 78% of residues from all of the enzymes, with 83% similar to native (90% correct, with 95% similar, excluding residues with high variability in multiple sequence alignments). Furthermore, the conformations of the selected side chains were often correctly predicted within crystallographic error. These findings suggest that simple selection pressures may have played a predominant role in determining the sequences of ligand-binding and active sites in proteins.

Pocketome via Comprehensive Identification and Classification of Ligand Binding Envelopes

We developed a new computational algorithm for the accurate identification of ligand binding envelopes rather than surface binding sites. We performed a large scale classification of the identified envelopes according to their shape and physicochemical properties. The predicting algorithm, called PocketFinder, uses a transformation of the Lennard-Jones potential calculated from a three-dimensional protein structure and does not require any knowledge about a potential ligand molecule. We validated this algorithm using two systematically collected data sets of ligand binding pockets from complexed (bound) and uncomplexed (apo) structures from the Protein Data Bank, 5616 and 11,510, respectively. As many as 96.8% of experimental binding sites were predicted at better than 50% overlap level. Furthermore 95.0% of the asserted sites from the apo receptors were predicted at the same level. We demonstrate that conformational differences between the apo and bound pockets do not dramatically affect the prediction results. The algorithm can be used to predict ligand binding pockets of uncharacterized protein structures, suggest new allosteric pockets, evaluate feasibility of protein-protein interaction inhibition, and prioritize molecular targets. Finally the data base of the known and predicted binding pockets for the human proteome structures, the human pocketome, was collected and classified. The pocketome can be used for rapid evaluation of possible binding partners of a given chemical compound.

The Architecture of Protein–Ligand Binding Sites Revealed through Template‐Assisted Intramolecular Peptide–Peptide Interactions

The Architecture of Protein–Ligand Binding Sites Revealed through Template‐Assisted Intramolecular Peptide–Peptide Interactions

Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites

Identifying the location of ligand binding sites on a protein is of fundamental importance for a range of applications including molecular docking, de novo drug design and structural identification and comparison of functional sites. Here, we describe a new method of ligand binding site prediction called Q-SiteFinder. It uses the interaction energy between the protein and a simple van der Waals probe to locate energetically favourable binding sites. Energetically favourable probe sites are clustered according to their spatial proximity and clusters are then ranked according to the sum of interaction energies for sites within each cluster. There is at least one successful prediction in the top three predicted sites in 90% of proteins tested when using Q-SiteFinder. This success rate is higher than that of a commonly used pocket detection algorithm (Pocket-Finder) which uses geometric criteria. Additionally, Q-SiteFinder is twice as effective as Pocket-Finder in generating predicted sites that map accurately onto ligand coordinates. It also generates predicted sites with the lowest average volumes of the methods examined in this study. Unlike pocket detection, the volumes of the predicted sites appear to show relatively low dependence on protein volume and are similar in volume to the ligands they contain. Restricting the size of the pocket is important for reducing the search space required for docking and de novo drug design or site comparison. The method can be applied in structural genomics studies where protein binding sites remain uncharacterized since the 86% success rate for unbound proteins appears to be only slightly lower than that of ligand-bound proteins. Both Q-SiteFinder and Pocket-Finder have been made available online at http://www.bioinformatics.leeds.ac.uk/qsitefinder and http://www.bioinformatics.leeds.ac.uk/pocketfinder

A novel statistical ligand-binding site predictor: application to ATP-binding sites

Structural genomics initiatives are leading to rapid growth in newly determined protein 3D structures, the functional characterization of which may still be inadequate. As an attempt to provide insights into the possible roles of the emerging proteins whose structures are available and/or to complement biochemical research, a variety of computational methods have been developed for the screening and prediction of ligand-binding sites in raw structural data, including statistical pattern classification techniques. In this paper, we report a novel statistical descriptor (the Oriented Shell Model) for protein ligand-binding sites, which utilizes the distance and angular position distribution of various structural and physicochemical features present in immediate proximity to the center of a binding site. Using the support vector machine (SVM) as the classifier, our model identified 69% of the ATP-binding sites in whole-protein scanning tests and in eukaryotic proteins the accuracy is particularly high. We propose that this feature extraction and machine learning procedure can screen out ligand-binding-capable protein candidates and can yield valuable biochemical information for individual proteins.

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Method for computing protein binding affinity

A Monte Carlo method is given to compute the binding affinity of a ligand to a protein. The method involves extending configuration space by a discrete variable indicating whether the ligand is bound to the protein and a special Monte Carlo move, which allows transitions between the unbound and bound states. Provided that an accurate protein structure is given, that the protein-ligand binding site is known, and that an accurate chemical force field together with a continuum solvation model is used, this method provides a quantitative estimate of the free energy of binding.

Modelling and simulation: a computational perspective in anticancer drug discovery.

The availability of high-quality molecular graphics tools in the public domain is changing the way macromolecular structure is perceived by researchers, educators and students alike. Computational methods have become increasingly important in a number of areas such as comparative or homology modelling, functional site location, characterization of ligand-binding sites in proteins, docking of small molecules into protein binding sites, protein-protein docking, and molecular dynamics simulations. The results obtained yield information that sometimes is beyond current experimental possibilities and can be used to guide and improve a vast array of experiments. On the basis of our improved level of understanding of molecular recognition and the widespread availability of target structures, it is reasonable to assume that computational methods will continue aiding not only in the design and interpretation of hypothesis-driven experiments in the field of cancer research but also in the rapid generation of new hypotheses.

Biosynthesis of heparan sulfate – how regulated does it need to be?

Heparan sulfate proteoglycans (HSPGs) are ubiquitous in animals. The functional significance of the structural variability exhibited by the constituent HS chains remains a fundamental question in cell and developmental biology. The polysaccharides influence cell behaviour, by modulating the activities of signalling proteins or through interactions in the extracellular matrix. HS is synthesized as a linear polymer of alternating glucuronate (GlcA) and N‐acetylglucosamine (GlcNAc) units. The resultant [GlcA‐GlcNAc]n polymer is partially modified through a series of N‐deacetylation/N‐sulfation, GlcA C5‐epimerization and O‐sulfation reactions (Esko & Lindahl 2001) and may be further modified by selective removal of O‐sulfate groups (Ai et al. 2003). Owing to the variable extent of these reactions in different cells and tissues, and at different developmental stages, the mature HS products display different structures, typically expressed through sulfated domains of variable length and composition (Esko & Lindahl 2001; Casu & Lindahl 2001). These domains provide binding sites for protein ligands and thus constitute the structural basis for the diverse functional roles of HS. The regulated diversity of HS structure is demonstrated through compositional analysis of HS from various organs as well as by immunohistochemical recognition of HS epitopes (van Kuppevelt, T. H et al. 1998). So far, a precise structure–function relation has been defined only for the antithrombin‐binding pentasaccharide sequence (Casu & Lindahl 2001).HS is essential throughout development, as mouse embryos devoid of HS‐polymerizing enzymes fail in gastrulation (Gallagher 2001). By contrast, targeted disruption of genes encoding polymer‐modifying enzymes is associated with surprisingly mild phenotypes. Embryos lacking N‐deacetylase/N‐sulfotransferase‐1, 2‐O‐sulfotransferase (Gallagher 2001) or GlcA C5‐epimerase (Li et al. 2003), thus show major defects incompatible with postnatal life, but also apparently normal organ systems known to rely on HS‐binding morphogens or growth factors for their development. Moreover, transgenic mice overexpressing heparanase appear essentially normal (Zcharia et al. 2004), in spite of an overall drastic reduction in HS chain size. How stringent are structure/function relations in HS–protein interactions?

First Principles Predictions of the Structure and Function of G-Protein-Coupled Receptors: Validation for Bovine Rhodopsin

G-protein-coupled receptors (GPCRs) are involved in cell communication processes and with mediating such senses as vision, smell, taste, and pain. They constitute a prominent superfamily of drug targets, but an atomic-level structure is available for only one GPCR, bovine rhodopsin, making it difficult to use structure-based methods to design receptor-specific drugs. We have developed the MembStruk first principles computational method for predicting the three-dimensional structure of GPCRs. In this article we validate the MembStruk procedure by comparing its predictions with the high-resolution crystal structure of bovine rhodopsin. The crystal structure of bovine rhodopsin has the second extracellular (EC-II) loop closed over the transmembrane regions by making a disulfide linkage between Cys-110 and Cys-187, but we speculate that opening this loop may play a role in the activation process of the receptor through the cysteine linkage with helix 3. Consequently we predicted two structures for bovine rhodopsin from the primary sequence (with no input from the crystal structure)—one with the EC-II loop closed as in the crystal structure, and the other with the EC-II loop open. The MembStruk-predicted structure of bovine rhodopsin with the closed EC-II loop deviates from the crystal by 2.84 Å coordinate root mean-square (CRMS) in the transmembrane region main-chain atoms. The predicted three-dimensional structures for other GPCRs can be validated only by predicting binding sites and energies for various ligands. For such predictions we developed the HierDock first principles computational method. We validate HierDock by predicting the binding site of 11- cis-retinal in the crystal structure of bovine rhodopsin. Scanning the whole protein without using any prior knowledge of the binding site, we find that the best scoring conformation in rhodopsin is 1.1 Å CRMS from the crystal structure for the ligand atoms. This predicted conformation has the carbonyl O only 2.82 Å from the N of Lys-296. Making this Schiff base bond and minimizing leads to a final conformation only 0.62 Å CRMS from the crystal structure. We also used HierDock to predict the binding site of 11- cis-retinal in the MembStruk-predicted structure of bovine rhodopsin (closed loop). Scanning the whole protein structure leads to a structure in which the carbonyl O is only 2.85 Å from the N of Lys-296. Making this Schiff base bond and minimizing leads to a final conformation only 2.92 Å CRMS from the crystal structure. The good agreement of the ab initio-predicted protein structures and ligand binding site with experiment validates the use of the MembStruk and HierDock first principles’ methods. Since these methods are generic and applicable to any GPCR, they should be useful in predicting the structures of other GPCRs and the binding site of ligands to these proteins.

Semiempirical calculations of binding enthalpy for protein–ligand complexes

AbstractA systematic semiempirical quantum mechanical study of the interactions between proteins and ligands has been performed to determine the ability of this approach for the accurate estimation of the enthalpic contribution to the binding free energy of the protein–ligand systems. This approach has been applied for eight test protein–ligand complexes with experimentally known binding enthalpies. The calculations were performed using the semiempirical PM3 approach incorporated in the MOPAC 97, ZAVA originally elaborated in Algodign, and MOPAC 2002 with MOZYME facility packages. Special attention was paid to take into account structural water molecules, which were located in the protein–ligand binding site. It was shown that the results of binding enthalpy calculations fit experimental data within ∼2 kcal/mol in the presented approach. © 2003 Wiley Periodicals, Inc. Int J Quantum Chem, 2004

An assessment of protein-ligand binding site polarizability.

Electronic polarizability, an important physical property of biomolecules, is currently ignored in most biomolecular calculations. Yet, it is widely believed that polarization could account for a substantial fraction of the total nonbonded energy of a system. This belief is supported by studies of small complexes in vacuum. This perception is driving the development of a new class of polarizable force fields for biomolecular calculations. However, the quantification of this term for protein-ligand complexes has never been attempted. Here we explore the polarizable nature of protein-ligand complexes in order to evaluate the importance of this effect. We introduce two indexes describing the polarizability of protein binding sites. These we apply to a large range of pharmaceutically relevant complexes. We offer a recommendation of particular complexes as test systems with which to determine the effects of polarizability and as test cases with which to test the new generation of force fields. Additionally, we provide a tabulation of the amino acid composition of these binding sites and show that composition can be specific for certain classes of proteins. We also show that the relative abundance of some amino acids is different in binding sites than elsewhere in a protein's structure.

Probing protein conformation with a minimal photochemical reagent.

3H-diazirine (3H-DZN), a photoreactive gas similar in size to water, was used to probe the topography of the surface and inner space of proteins. On photolysis 3H-DZN generates 3H-methylene carbene, which reacts unselectively with its molecular cage, inserting even into C-H bonds. Labeling of bovine alpha-lactalbumin (alpha-LA, MW: 14,200) with 1 mM (3)H-DZN yielded 0.0041 mol CH2/mol of protein, in agreement with the expectation for an unspecific surface-labeling phenomenon. The cooperative urea-induced unfolding of alpha-LA, as monitored by the extent of 3H-methylene labeling, agrees with that measured by circular dichroism spectroscopy in the far and near ultraviolet regions. At 8 M urea, the unfolded state U was labeled 25-30% more than the native state N primarily because of the increase in the accessible surface area (ASA) of the protein occurring upon unfolding. However, this result lies below the approximately 100% increment expected from theoretical estimates of ASA of state U. Among other factors, most likely the existence of a residual structure in U, that involves helices H2 and H4 of the alpha subdomain, might account for this fact, as shown by a comparative analysis of peptide labeling patterns of N and U samples. In this paper, we demonstrate the usefulness of the 3H-methylene labeling method to monitor conformational transitions and map solvent accessibility along the polypeptide sequence, thus opening the possibility of outlining structural features of nonnative states (i.e., denatured states, molten globule). We anticipate that this technique also would help to identify ligand binding and oligomerization sites in proteins.

Insight to structural subsite recognition in plant thiol protease-inhibitor complexes : Understanding the basis of differential inhibition and the role of water

BackgroundThis work represents an extensive MD simulation / water-dynamics studies on a series of complexes of inhibitors (leupeptin, E-64, E-64-C, ZPACK) and plant cysteine proteases (actinidin, caricain, chymopapain, calotropin DI) of papain family to understand the various interactions, water binding mode, factors influencing it and the structural basis of differential inhibition.ResultsThe tertiary structure of the enzyme-inhibitor complexes were built by visual interactive modeling and energy minimization followed by dynamic simulation of 120 ps in water environment. DASA study with and without the inhibitor revealed the potential subsite residues involved in inhibition. Though the interaction involving main chain atoms are similar, critical inspection of the complexes reveal significant differences in the side chain interactions in S2-P2 and S3-P3 pairs due to sequence differences in the equivalent positions of respective subsites leading to differential inhibition.ConclusionThe key finding of the study is a conserved site of a water molecule near oxyanion hole of the enzyme active site, which is found in all the modeled complexes and in most crystal structures of papain family either native or complexed. Conserved water molecules at the ligand binding sites of these homologous proteins suggest the structural importance of the water, which changes the conventional definition of chemical geometry of inhibitor binding domain, its shape and complimentarity. The water mediated recognition of inhibitor to enzyme subsites (Pn...H2O....Sn) of leupeptin acetyl oxygen to caricain, chymopapain and calotropinDI is an additional information and offer valuable insight to potent inhibitor design.

Calcium transport across the sarcoplasmic reticulum: structure and function of Ca2+-ATPase and the ryanodine receptor.

Contraction of striated muscle results from a rise in cytoplasmic calcium concentration in a process termed excitation/contraction coupling. Most of this calcium moves back and forth across the sarcoplasmic-reticulum membrane in cycles of contraction and relaxation. The channel responsible for release from the sarcoplasmic reticulum is the ryanodine receptor, whereas Ca2+-ATPase effects reuptake in an ATP-dependent manner. The structures of these two molecules have been studied by cryoelectron microscopy, with helical crystals in the case of Ca2+-ATPase and as isolated tetramers in the case of ryanodine receptor. Structures of Ca2+-ATPase at 8-A resolution reveal the packing of transmembrane helices and have allowed fitting of a putative ATP-binding domain among the cytoplasmic densities. Comparison of ATPases in different conformations gives hints about the conformational changes that accompany the reaction cycle. Structures of ryanodine receptor at 30-A resolution reveal a multitude of isolated domains in the cytoplasmic portion, as well as a distinct transmembrane assembly. Binding sites for various protein ligands have been determined and conformational changes induced by ATP, calcium and ryanodine have been characterized. Both molecules appear to use large conformational changes to couple interactions in their cytoplasmic domains with calcium transport through their membrane domains, and future studies at higher resolution will focus on the mechanisms for this coupling.