Evaluation of the FLEXX incremental construction algorithm for protein-ligand docking

We report on a test of FLEXX, a fully automatic docking tool for flexible ligands, on a highly diverse data set of 200 protein-ligand complexes from the Protein Data Bank. In total 46.5% of the complexes of the data set can be reproduced by a FLEXX docking solution at rank 1 with an rms deviation (RMSD) from the observed structure of less than 2 A. This rate rises to 70% if one looks at the entire generated solution set. FLEXX produces reliable results for ligands with up to 15 components which can be docked in 80% of the cases with acceptable accuracy. Ligands with more than 15 components tend to generate wrong solutions more often. The average runtime of FLEXX on this test set is 93 seconds per complex on a SUN Ultra-30 workstation. In addition, we report on "cross-docking" experiments, in which several receptor structures of complexes with identical proteins have been used for docking all cocrystallized ligands of these complexes. In most cases, these experiments show that FLEXX can acceptably dock a ligand into a foreign receptor structure. Finally we report on screening runs of ligands out of a library with 556 entries against ten different proteins. In eight cases FLEXX is able to find the original inhibitor within the top 7% of the total library.     

Using protein-ligand docking to assess the chemical tractability of inhibiting a protein target

Assessing the difficulty of inhibiting a specific protein by a small molecule can be highly valuable in risk-assessment and prioritization of a new target. In particular, when the disease linkage for a number of targets is broadly similar, being able to identify the most tractable can have a significant impact on informing target selection. With an increasing focus against new and novel protein classes, being able to assess the most likely targets to yield lead-like chemical start points can guide the selection and the lead-generation strategy implemented. This study exploits protein-ligand docking studies on published protein x-ray crystal structures to provide guidance on the feasibility of identifying small molecule inhibitors against a range of targets.     

Detailed comparison of the protein-ligand docking efficiencies of GOLD, a commercial package and ArgusLab, a licensable freeware

Molecular docking and virtual screening based on molecular docking have become an integral part of many modern structure-based drug discovery efforts. Hence, it becomes a useful endeavor to evaluate existing docking programs, which can assist in the choice of the most suitable docking algorithm for any particular study. The objective of the current study was to evaluate the ability of ArgusLab 4.0, a relatively new molecular modeling package in which molecular docking is implemented, to reproduce crystallographic binding orientations and to compare its accuracy with that of a well established commercial package, GOLD. The study also aimed to evaluate the effect of the nature of the binding site and ligand properties on docking accuracy. The three dimensional structures of a carefully chosen set of 75 pharmaceutically relevant protein-ligand complexes were used for the comparative study. The study revealed that the commercial package outperforms the freely available docking engine in almost all the parameters tested. However, the study also revealed that although lagging behind in accuracy, results from ArgusLab are biologically meaningful. This taken together with the fact that ArgusLab has an easy to use graphical user interface, means that it can be employed as an effective teaching tool to demonstrate molecular docking to beginners in this area.     

Relibase: design and development of a database for comprehensive analysis of protein-ligand interactions

Knowledge discovery from the exponentially growing body of structurally characterised protein-ligand complexes as a source of information in structure-based drug design is a major challenge in contemporary drug research. Given the need for powerful data retrieval, integration and analysis tools, Relibase was developed as a database system particularly designed to handle protein-ligand related problems and tasks. Here, we describe the design and functionality of the Relibase core database system. Features of Relibase include, e.g. the detailed analysis of superimposed ligand binding sites, ligand similarity and substructure searches, and 3D searches for protein-ligand and protein-protein interaction patterns. The broad range of functions provided in Relibase and its high level of data integration, along with its flexible and intuitive interface, makes Relibase an invaluable data mining tool which can significantly enhance the drug development process. An example, illustrating a 3D query for quarternary ligand nitrogen atoms interacting with aromatic ring systems in proteins, a pattern found in pharmaceutically relevant target proteins such as, e.g. acetylcholine-esterase, is discussed.     

Model-assisted Design of Experiments as a concept for knowledge-based bioprocess development

Bioprocess and Biosystems Engineering - Design of Experiments methods offer systematic tools for bioprocess development in Quality by Design, but their major drawback is the user-defined choice of...     

Bloom forming cyanobacterial complexes co-occurring in a subtropical large reservoir: validation of dominant eco-strategies

In this study, we analyse the spatial distribution of cyanobacterial summer blooms in a large subtropical reservoir located in the Uruguay River, from 2007 to 2011; these extraordinary algal growth events are mainly represented by scum-forming and nitrogen-fixing eco-strategists of the Dolichospermum and Microcystis genera. The use of the eco-strategists approach, based on ecophysiological work and field observations, allowed us to explain the differences in the distribution pattern and temporal dynamics of both cyanobacterial complexes. Spatial differences were produced due to much higher and fluctuating cyanobacterial abundances at the right margin of the reservoir and at the littoral areas closer to the dam. Satellite imagery (LANDSAT 5 TM) clearly depicted the stronger algal development in the reservoir arms and in the section closer to the dam. The Microcystis spp. complex achieved higher density than the Dolichospermum spp. complex. We hypothesise that the hydrological cycle explains the inter-annual fluctuations of the intensity and frequency of cyanobacterial blooms, and that spatial differences in cyanobacterial presence between the reservoir arms, its margins and the main channel is mainly a response to morphometrical and hydrological characteristics.     

Strong and weak hydrogen bonds in protein-ligand complexes of kinases: a comparative study

Strong and weak hydrogen bonds between protein and ligand are analyzed in a group of 233 X-ray crystal structures of the kinase family. These kinases are from both eukaryotic and prokaryotic organisms. The dataset comprises of 44 sub-families, out of which 35 are of human origin and the rest belong to other organisms. Interaction analysis was carried out in the active sites, defined here as a sphere of 10 A radius around the ligand. A majority of the interactions are observed between the main chain of the protein and the ligand atoms. As a donor, the ligand frequently interacts with amino acid residues like Leu, Glu and His. As an acceptor, the ligand interacts often with Gly, and Leu. Strong hydrogen bonds N-H...O, O-H...O, N-H...N and weak bonds C-H...O, C-H...N are common between the protein and ligand. The hydrogen bond donor capacity of Gly in N-H...O and C-H...O interactions is noteworthy. Similarly, the acceptor capacity of main chain Glu is ubiquitous in several kinase sub-families. Hydrogen bonds between protein and ligand form characteristic hydrogen bond patterns (supramolecular synthons). These synthon patterns are unique to each sub-family. The synthon locations are conserved across sub-families due to a higher percentage of conserved sequences in the active sites. The nature of active site water molecules was studied through a novel classification scheme, based on the extent of exposure of water molecules. Water which is least exposed usually participates in hydrogen bond formation with the ligand. These findings will help structural biologists, crystallographers and medicinal chemists to design better kinase inhibitors.     

Anchoring of a large set of markers onto a BAC library for the development of a draft physical map of the grapevine genome

Five hundred and six EST-derived markers, 313 SSR markers and 26 BAC end-derived or SCAR markers were anchored by PCR on a subset of a Cabernet Sauvignon BAC library representing six genome equivalents pooled in three dimensions. In parallel, the 12,351 EST clusters of the grapevine UniGene set (build #11) from NCBI were used to design 12,125 primers pairs and perform electronic PCR on 67,543 nonredundant BAC-end sequences. This in silico experiment yielded 1,140 positive results concerning 638 different markers, among which 602 had not been already anchored by PCR. The data obtained will provide an easier access to the regulatory sequences surrounding important genes (represented by ESTs). In total, 1,731 islands of BAC clones (set of overlapping BAC clones containing at least one common marker) were obtained and 226 of them contained at least one genetically mapped anchor. These assigned islands are very useful because they will link the genetic map and the future fingerprint-based physical map and because they allowed us to indirectly place 93 ESTs on the genetic map. The islands containing two or more mapped SSR markers were also used to assess the quality of the integrated genetic map of the grapevine genome.Electronic Supplementary Material Supplementary material is available to authorised users in the online version of this article at .Didier Lamoureux and Anne Bernole contributed equally to this work.     

A multidomain flexible docking approach to deal with large conformational changes in the modeling of biomolecular complexes

Binding-induced backbone and large-scale conformational changes represent one of the major challenges in the modeling of biomolecular complexes by docking. To address this challenge, we have developed a flexible multidomain docking protocol that follows a divide-and-conquer approach to model both large-scale domain motions and small- to medium-scale interfacial rearrangements: the flexible binding partner is treated as an assembly of subparts/domains that are docked simultaneously making use of HADDOCK's multidomain docking ability. For this, the flexible molecules are cut at hinge regions predicted using an elastic network model. The performance of this approach is demonstrated on a benchmark covering an unprecedented range of conformational changes of 1.5 to 19.5 ?. We show from a statistical survey of known complexes that the cumulative sum of eigenvalues obtained from the elastic network has some predictive power to indicate the extent of the conformational change to be expected.     

A soft docking algorithm for predicting the structure of antibody-antigen complexes

An efficient soft docking algorithm is described for predicting the mode of binding between an antibody and its antigen based on the three-dimensional structures of the molecules. The basic tools are the "simplified protein" model and the docking algorithm of Wodak and Janin. The side-chain flexibility of Arg, Lys, Asp, Glu, and Met residues on the protein surface is taken into account. A combined filtering technique is used to select candidate binding modes. After energy minimization, we calculate a scoring function, which includes electrostatic and desolvation energy terms. This procedure was applied to targets 04, 05, and 06 of CAPRI, which are complexes of three different camelid antibody VHH variable domains with pig alpha-amylase. For target 06, two native-like structures with a root-mean-square deviation < 4.0 A relative to the X-ray structure were found within the five top ranking structures. For targets 04 and 05, our procedure produced models where more than half of the antigen residues forming the epitope were correctly predicted, albeit with a wrong VHH domain orientation. Thus, our soft docking algorithm is a promising tool for predicting antibody-antigen recognition.     

Validation of the use of intermolecular NOE constraints for obtaining docked structures of protein-ligand complexes

Summary The use of intermolecular NOEs for docking a small ligand molecule into its target protein has been investigated with the aim of determining the effectiveness and methodology of this type of NOE docking calculation. A high-resolution X-ray structure of a protein-ligand complex has been used to simulate loose distance constraints of varying degrees of quality, typical of those estimated from experimental NOE intensities. These simulated data were used to examine the effect of the number, distribution and representation of the experimental constraints on the precision and accuracy of the calculated structures. A standard simulated annealing protocol was used, as well as a more novel method based on rigid-body dynamics. The results showed some analogies with those from similar studies on complete protein NMR structure determinations, but it was found that more constraints per torsion angle are required to define docked structures of similar quality. The effectiveness of different NOE-constraint averaging methods was explored and the benefits of using R^–6 averaging rather than centre averaging with small sets of NOE constraints were shown. The starting protein structure used in docking calculations was obtained from previous X-ray or NMR structure studies on a related complex. The effects on the calculated conformations of introducing structural differences into the binding site of the initial protein structure were also considered.To whom correspondence should be addressed.     

AlgR-binding sites within the algD promoter make up a set of inverted repeats separated by a large intervening segment of DNA.

Activation of algD by AlgR is essential for mucoidy, a virulence factor expressed by Pseudomonas aeruginosa in cystic fibrosis. Two AlgR-binding sites, RB1 and RB2, located far upstream from the algD mRNA start site, are essential for the high-level activity of algD. However, the removal of RB1 and RB2 does not completely abolish inducibility of algD in response to environmental signals. In this work, a third binding site for AlgR, termed RB3, near the algD mRNA start site was characterized. Deletion of RB3 abrogated both the AlgR-binding ability and the residual inducibility of the algD promoter. DNase I footprinting analysis of RB3 resulted in a protection pattern spanning nucleotides -50 to -30. Eight of 10 residues encompassing a continuous region of protection within RB3 (positions -45 to -36) matched in the inverted orientation the conserved core sequence (ACCGTTCGTC) of RB1 and RB2. Quantitative binding measurements of AlgR association with RB1, RB2, and RB3 indicated that AlgR had significantly lower affinity for RB3 than for RB1 and RB2, with differences in the free energy of binding of 1.05 and 0.93 kcal/mol (4.39 and 3.89 kJ/mmol), respectively. Altering the core of RB2 to match the core of RB3 significantly reduced AlgR binding. Conversely, changing the core of RB3 to perfectly match the core of RB2 (mutant site termed RB3*) improved AlgR binding, approximating the affinity of RB2. RB3*, in the absence of the far upstream sites, showed an increase in activity, approaching the levels observed with the full-size algD promoter. Changing 4 nucleotides in two different combinations within the core of RB3 abolished the binding of AlgR to this site and resulted in a significant reduction of promoter activity in the presence of the far upstream sites. Thus, (i) the core sequence is essential for AlgR binding; (ii) the three binding sites, RB1, RB2, and RB3, are organized as an uneven palindrome with symmetrical sequences separated by 341 and 417 bp; and (iii) all three sites participate in algD activation.     

Improving the stability of an antibody variable fragment by a combination of knowledge-based approaches: validation and mechanisms

Numerous approaches have been described to obtain variable fragments of antibodies (Fv or scFv) that are sufficiently stable for their applications. Here, we combined several knowledge-based methods to increase the stability of pre-existing scFvs by design. Firstly, the consensus sequence approach was used in a non-stringent way to predict a large basic set of potentially stabilizing mutations. These mutations were then prioritized by other methods of design, mainly the formation of additional hydrogen bonds, an increase in the hydrophilicity of solvent exposed residues, and previously described mutations in other antibodies. We validated this combined method with antibody mAbD1.3, directed against lysozyme. Fourteen potentially stabilizing mutations were designed and introduced into scFvD1.3 by site-directed mutagenesis, either individually or in combinations. We characterized the effects of the mutations on the thermodynamic stability of scFvD1.3 by experiments of unfolding with urea, monitored by spectrofluorometry, and tested the additivity of their effects by double-mutant cycles. We also quantified the individual contributions of the resistance to denaturation ([urea](1/2)) and cooperativity of unfolding (m) to the variations of stability and the energy of coupling between mutations by a novel approach. Most mutations (75%) were stabilizing and none was destabilizing. The progressive recombination of the mutations into the same molecule of scFvD1.3 showed that their effects were mostly additive or synergistic, provided a large overall increase in protein stability (9.1 kcal/mol), and resulted in a highly stable scFvD1.3 derivative. The mechanisms of the mutations and of their combinations involved variations in the resistance to denaturation, cooperativity of unfolding, and likely residual structures of the denatured state, which was constrained by two disulfide bonds. This combined method should be applicable to any recombinant antibody fragment, through a single step of mutagenesis.     

ClusPro: an automated docking and discrimination method for the prediction of protein complexes

MOTIVATION: Predicting protein interactions is one of the most challenging problems in functional genomics. Given two proteins known to interact, current docking methods evaluate billions of docked conformations by simple scoring functions, and in addition to near-native structures yield many false positives, i.e. structures with good surface complementarity but far from the native. RESULTS: We have developed a fast algorithm for filtering docked conformations with good surface complementarity, and ranking them based on their clustering properties. The free energy filters select complexes with lowest desolvation and electrostatic energies. Clustering is then used to smooth the local minima and to select the ones with the broadest energy wells-a property associated with the free energy at the binding site. The robustness of the method was tested on sets of 2000 docked conformations generated for 48 pairs of interacting proteins. In 31 of these cases, the top 10 predictions include at least one near-native complex, with an average RMSD of 5 A from the native structure. The docking and discrimination method also provides good results for a number of complexes that were used as targets in the Critical Assessment of PRedictions of Interactions experiment. AVAILABILITY: The fully automated docking and discrimination server ClusPro can be found at http://structure.bu.edu     

Setting up standards and a reference map for the alkaline proteome of the Gram-positive bacterium Lactococcus lactis

Despite the fact that almost 39% of the theoretical expressed proteins of Lactococcus lactis have a predicted isoelectric point above 7, these proteins have not been studied in previous proteome analyses. In the present study, we set up a reference map of alkaline lactococcal proteins by using immobilized pH gradients (IPG) spanning pH 6 to 12 and 9 to 12, and protein identification by matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS). Different electrophoresis systems for isoelectric focusing were evaluated to optimize the first dimension. Best results were obtained by sample application using cup-loading at the anodic side and increasing the final voltage up to 8000 V for IPGs, using N,N-dimethylacrylamide as monomer. After two-dimensional gel electrophoresis of extracts obtained from exponentially growing cells, about 200 protein spots were selected for identification by peptide mass fingerprinting. With MALDI-TOF MS, 153 proteins were identified that were the products of 85 different genes. Their predicted isoelectric points range from as high as 11.31 to as low as 6.34. Ribosomal proteins, hypothetical proteins and proteins with unknown function represent the largest groups of identified proteins. For further classification, the codon adaptation index (CAI) and grand average of hydropathicity (GRAVY) for each lactococcal protein were calculated. The protein with the lowest CAI identified in this study is the manganese ABC transporter ATP-binding protein. Less than 10% of the alkaline lactococcal proteins have a smaller CAI. The highest GRAVY for an identified protein is 0.26. The complete in silico data of Lactococcus lactis as well as clickable reference maps are available at www.wzw.tum.de/proteomik/lactis.     

Combinatorial docking approach for structure prediction of large proteins and multi-molecular assemblies

Protein folding and protein binding are similar processes. In both, structural units combinatorially associate with each other. In the case of folding, we mostly handle relatively small units, building blocks or domains, that are covalently linked. In the case of multi-molecular binding, the subunits are relatively large and are associated only by non-covalent bonds. Experimentally, the difficulty in the determination of the structures of such large assemblies increases with the complex size and the number of components it contains. Computationally, the prediction of the structures of multi-molecular complexes has largely not been addressed, probably owing to the magnitude of the combinatorial complexity of the problem. Current docking algorithms mostly target prediction of pairwise interactions. Here our goal is to predict the structures of multi-unit associations, whether these are chain-connected as in protein folding, or separate disjoint molecules in the assemblies. We assume that the structures of the single units are known, either through experimental determination or modeling. Our aim is to combinatorially assemble these units to predict their structure. To address this problem we have developed CombDock. CombDock is a combinatorial docking algorithm for the structural units assembly problem. Below, we briefly describe the algorithm and present examples of its various applications to folding and to multi-molecular assemblies. To test the robustness of the algorithm, we use inaccurate models of the structural units, derived either from crystal structures of unbound molecules or from modeling of the target sequences. The algorithm has been able to predict near-native arrangements of the input structural units in almost all of the cases, suggesting that a combinatorial approach can overcome the imperfect shape complementarity caused by the inaccuracy of the models. In addition, we further show that through a combinatorial docking strategy it is possible to enhance the predictions of pairwise interactions involved in a multi-molecular assembly.     

Interaction pattern for the complex of B-DNA Fullerene compounds with a set of known replication proteins using docking study

Fullerenes have attracted considerable attention due to their unique chemical structure and potential applications which has opened wide venues for possible human exposure to various fullerene types. Therefore, in depth knowledge of how fullerene may interfere with various cellular processes becomes quite imperative. The present study was designed to investigate how the presence of fullerene affect the binding of DNA with different enzymes involved in replication process. Different fullerenes were first docked with DNA and then binding scores of different enzymes was analyzed with fullerene docked DNA. C30, C40 & C50 once docked with DNA, reduced the binding score of primase, whereas no significant change in the binding score was observed with the helicase, ssb protein, dna pol δ, dna pol ε, ligase, DNA clamp, and topoisomerases. On the contrast, the binding score of RPA14 decreases in fluctuating manner while interacting with increasing molecular weight of fullerene bound single-stranded DNA complex. The study revealed the affect of fullerene family interacting with DNA on the binding pattern of enzymes involved in replication process. Study suggests that the presence of most of fullerenes may not affect the activity of these enzymes necessary for replication process whereas C30, C40 & C50 may disrupt the activity of primase, (strating point for DNA polymerase) its docking score decreases from 13820 to 10702.     

Methods for evaluating clustering algorithms for gene expression data using a reference set of functional classes

Background  

A cluster analysis is the most commonly performed procedure (often regarded as a first step) on a set of gene expression profiles. In most cases, a post hoc analysis is done to see if the genes in the same clusters can be functionally correlated. While past successes of such analyses have often been reported in a number of microarray studies (most of which used the standard hierarchical clustering, UPGMA, with one minus the Pearson's correlation coefficient as a measure of dissimilarity), often times such groupings could be misleading. More importantly, a systematic evaluation of the entire set of clusters produced by such unsupervised procedures is necessary since they also contain genes that are seemingly unrelated or may have more than one common function. Here we quantify the performance of a given unsupervised clustering algorithm applied to a given microarray study in terms of its ability to produce biologically meaningful clusters using a reference set of functional classes. Such a reference set may come from prior biological knowledge specific to a microarray study or may be formed using the growing databases of gene ontologies (GO) for the annotated genes of the relevant species.