Conformational transitions upon ligand binding: holo-structure prediction from apo conformations

Identification of a novel putative inhibitor of the Plasmodium falciparum purine nucleoside phosphorylase: exploring the purine salvage pathway to design new antimalarial drugs

Malaria, a tropical parasitic disease caused by Plasmodium spp., continues to place a heavy social burden, with almost 200 million cases and more than 580,000 deaths per year. Plasmodium falciparum purine nucleoside phosphorylase (PfPNP) can be targeted for antimalarial drug design since its inhibition kills malaria parasites both in vitro and in vivo. Although the currently known inhibitors of PfPNP, immucillins, are orally available and of low toxicity to animals and humans, to the best of our knowledge, none of these compounds has entered clinical trials for the treatment of malaria. Using a pharmacophore-based virtual screening coupled to a consensual molecular docking approach, we identified 59 potential PfPNP inhibitors that are predicted to be orally absorbed in a Caco-2 cell model. Although most of these compounds are predicted to have high plasma protein binding levels, poor water solubility (except for compound 25) and CYP3A4 metabolic stability (except for 4, 7 and 8), four structures (4, 7, 8 and 25) remain as potential leads because of their plausible interaction with a specific hydrophobic pocket of PfPNP, which would confer them higher selectivity for PfPNP over human PNP. Additionally, both predicted Gibbs free energies for binding and molecular dynamics suggest that compound 4 may form a more stable complex with PfPNP than 5[Formula: see text]-methylthio-immucillin-H, a potent and selective inhibitor of PfPNP.

Dynamical persistence of active sites identified in maltose-binding protein

This study identifies dynamical properties of maltose-binding protein (MBP) useful in unveiling active site residues susceptible to ligand binding. The described methodology has been previously used in support of novel topological techniques of persistent homology and statistical inference in complex, multi-scale, high-dimensional data often encountered in computational biophysics. Here we outline a computational protocol that is based on the anisotropic elastic network models of 14 all-atom three-dimensional protein structures. We introduce the notion of dynamical distance matrices as a measure of correlated interactions among 370 amino acid residues that constitute a single protein. The dynamical distance matrices serve as an input for a persistent homology suite of codes to further distinguish a small subset of residues with high affinity for ligand binding and allosteric activity. In addition, we show that ligand-free closed MBP structures require lower deformation energies than open MBP structures, which may be used in categorization of time-evolving molecular dynamics structures. Analysis of the most probable allosteric coupling pathways between active site residues and the protein exterior is also presented.

Modeling and Design of Peptidomimetics to Modulate Protein-Protein Interactions

We describe a modular approach to identify and inhibit protein-protein interactions (PPIs) that are mediated by protein secondary and tertiary structures with rationally designed peptidomimetics. Our analysis begins with entries of high-resolution complexes in the Protein Data Bank and utilizes conformational sampling, scoring, and design capabilities of advanced biomolecular modeling software to develop peptidomimetics.

An efficient perturbation method to predict the functionally key sites of glutamine binding protein

Glutamine-Binding Protein (GlnBP) of Escherichia coli, an important member of the periplasmic binding protein family, is responsible for the first step in the active transport of glutamine across the cytoplasmic membrane. In this work, the functionally key regulation sites of GlnBP were identified by utilizing a perturbation method proposed by our group, in which the residues whose perturbations markedly change the binding free energy between GlnBP and glutamine are considered to be functionally key residues. The results show that besides the substrate binding sites, some other residues distant from the binding pocket, including the ones in the hinge regions between the two domains, the front- and back- door channels and the exposed region, are important for the function of glutamine binding and transport. The predicted results are well consistent with the theoretical and experimental data, which indicates that our method is an effective approach to identify the key residues important for both ligand binding and long-range allosteric signal transmission. This work can provide some insights into the function performance of GlnBP and the physical mechanism of its allosteric regulation.

In Silico Template Selection of Short Antimicrobial Peptide Viscotoxin for Improving Its Antimicrobial Efficiency in Development of Potential Therapeutic Drugs

Rapid increase in antibiotic resistance has posed a worldwide threat, due to increased mortality, morbidity, and expenditure caused by antibiotic-resistant microbes. Recent development of the antimicrobial peptides like viscotoxin (Vt) has been successfully comprehended as a substitute for classical antibiotics. A structurally stable peptide, Vt can enhance antimicrobial property and can be used for various developmental purposes. Thus, structural stability among the antimicrobial peptides, Vt A1 (3C8P), A2 (1JMN), A3 (1ED0), B (1JMP), and C (1ORL) of Viscus album was computationally analyzed. In specific, the static confirmation of VtA3 showed high number of intramolecular interactions, along with an increase in hydrophobicity than others comparatively. Further, conformational sampling was used to analyze various geometrical parameters such as root mean square deviation, root mean square fluctuation, radius of gyration, and ovality which also revealed the structural stability of VtA3. Moreover, the statistically validated contours of surface area, lipophilicity, and distance constraints of disulfide bonds also supported the priority of VtA3 with respect to stability. Finally, the functional activity of peptides was accessed by computing their free energy of membrane association and membrane interactions, which defined VtA3 as functionally stable. Currently, peptide-based antibiotics and nanoparticles have attracted the pharmaceutical industries for their potential therapeutic applications. Thereby, it is proposed that viscotoxin A3 (1ED0) could be used as a preeminent template for scaffolding potentially efficient antimicrobial peptide-based drugs and nanomaterials in future.

Plate-based diversity subset screening generation 2: an improved paradigm for high-throughput screening of large compound files

High-throughput screening (HTS) is an effective method for lead and probe discovery that is widely used in industry and academia to identify novel chemical matter and to initiate the drug discovery process. However, HTS can be time consuming and costly and the use of subsets as an efficient alternative to screening entire compound collections has been investigated. Subsets may be selected on the basis of chemical diversity, molecular properties, biological activity diversity or biological target focus. Previously, we described a novel form of subset screening: plate-based diversity subset (PBDS) screening, in which the screening subset is constructed by plate selection (rather than individual compound cherry-picking), using algorithms that select for compound quality and chemical diversity on a plate basis. In this paper, we describe a second-generation approach to the construction of an updated subset: PBDS2, using both plate and individual compound selection, that has an improved coverage of the chemical space of the screening file, whilst only selecting the same number of plates for screening. We describe the validation of PBDS2 and its successful use in hit and lead discovery. PBDS2 screening became the default mode of singleton (one compound per well) HTS for lead discovery in Pfizer.

Dissecting the Influence of Protein Flexibility on the Location and Thermodynamic Profile of Explicit Water Molecules in Protein-Ligand Binding

Explicit water molecules in the binding site of proteins play a crucial role for protein-ligand association. Recent advances in computer-aided drug discovery methodology allow for an accurate prediction of the localized position and thermodynamic profile of water molecules (i.e., hydration sites) in the binding site. The underlying calculations are based on MD simulations of explicit water molecules in a restrained protein structure. However, the ligand-binding process is typically associated with protein conformational change that influences the position and thermodynamic properties of the hydration site. In this manuscript, we present the developments of two methods to incorporate the influence of protein conformational change on hydration sites either by following the conformational transition step-by-step (method I) or to match the hydration sites of the two transition end states using local coordinate systems (method II). Using these methods, we highlight the difference in the estimated protein desolvation free energy with and without inclusion of protein flexibility. To the best of our knowledge, this is the first study that explicitly studies the influence of protein conformational change on the position and thermodynamic profiles of water molecules and provides methodology to incorporate protein flexibility into the estimation of the desolvation free energy.

Ligand Docking to Intermediate and Close-To-Bound Conformers Generated by an Elastic Network Model Based Algorithm for Highly Flexible Proteins

Incorporating receptor flexibility in small ligand-protein docking still poses a challenge for proteins undergoing large conformational changes. In the absence of bound structures, sampling conformers that are accessible by apo state may facilitate docking and drug design studies. For this aim, we developed an unbiased conformational search algorithm, by integrating global modes from elastic network model, clustering and energy minimization with implicit solvation. Our dataset consists of five diverse proteins with apo to complex RMSDs 4.7-15 Å. Applying this iterative algorithm on apo structures, conformers close to the bound-state (RMSD 1.4-3.8 Å), as well as the intermediate states were generated. Dockings to a sequence of conformers consisting of a closed structure and its "parents" up to the apo were performed to compare binding poses on different states of the receptor. For two periplasmic binding proteins and biotin carboxylase that exhibit hinge-type closure of two dynamics domains, the best pose was obtained for the conformer closest to the bound structure (ligand RMSDs 1.5-2 Å). In contrast, the best pose for adenylate kinase corresponded to an intermediate state with partially closed LID domain and open NMP domain, in line with recent studies (ligand RMSD 2.9 Å). The docking of a helical peptide to calmodulin was the most challenging case due to the complexity of its 15 Å transition, for which a two-stage procedure was necessary. The technique was first applied on the extended calmodulin to generate intermediate conformers; then peptide docking and a second generation stage on the complex were performed, which in turn yielded a final peptide RMSD of 2.9 Å. Our algorithm is effective in producing conformational states based on the apo state. This study underlines the importance of such intermediate states for ligand docking to proteins undergoing large transitions.

The Phylogenetic Signature Underlying ATP Synthase c-Ring Compliance

The proton-driven ATP synthase (FOF1) is comprised of two rotary, stepping motors (FO and F1) coupled by an elastic power transmission. The elastic compliance resides in the rotor module that includes the membrane-embedded FO c-ring. Proton transport by FO is firmly coupled to the rotation of the c-ring relative to other FO subunits (ab2). It drives ATP synthesis. We used a computational method to investigate the contribution of the c-ring to the total elastic compliance. We performed principal component analysis of conformational ensembles built using distance constraints from the bovine mitochondrial c-ring x-ray structure. Angular rotary twist, the dominant ring motion, was estimated to show that the c-ring accounted in part for the measured compliance. Ring rotation was entrained to rotation of the external helix within each hairpin-shaped c-subunit in the ring. Ensembles of monomer and dimers extracted from complete c-rings showed that the coupling between collective ring and the individual subunit motions was independent of the size of the c-ring, which varies between organisms. Molecular determinants were identified by covariance analysis of residue coevolution and structural-alphabet-based local dynamics correlations. The residue coevolution gave a readout of subunit architecture. The dynamic couplings revealed that the hinge for both ring and subunit helix rotations was constructed from the proton-binding site and the adjacent glycine motif (IB-GGGG) in the midmembrane plane. IB-GGGG motifs were linked by long-range couplings across the ring, while intrasubunit couplings connected the motif to the conserved cytoplasmic loop and adjacent segments. The correlation with principal collective motions shows that the couplings underlie both ring rotary and bending motions. Noncontact couplings between IB-GGGG motifs matched the coevolution signal as well as contact couplings. The residue coevolution reflects the physiological importance of the dynamics that may link proton transfer to ring compliance.

Protein Binding Pocket Dynamics

The dynamics of protein binding pockets are crucial for their interaction specificity. Structural flexibility allows proteins to adapt to their individual molecular binding partners and facilitates the binding process. This implies the necessity to consider protein internal motion in determining and predicting binding properties and in designing new binders. Although accounting for protein dynamics presents a challenge for computational approaches, it expands the structural and physicochemical space for compound design and thus offers the prospect of improved binding specificity and selectivity. A cavity on the surface or in the interior of a protein that possesses suitable properties for binding a ligand is usually referred to as a binding pocket. The set of amino acid residues around a binding pocket determines its physicochemical characteristics and, together with its shape and location in a protein, defines its functionality. Residues outside the binding site can also have a long-range effect on the properties of the binding pocket. Cavities with similar functionalities are often conserved across protein families. For example, enzyme active sites are usually concave surfaces that present amino acid residues in a suitable configuration for binding low molecular weight compounds. Macromolecular binding pockets, on the other hand, are located on the protein surface and are often shallower. The mobility of proteins allows the opening, closing, and adaptation of binding pockets to regulate binding processes and specific protein functionalities. For example, channels and tunnels can exist permanently or transiently to transport compounds to and from a binding site. The influence of protein flexibility on binding pockets can vary from small changes to an already existent pocket to the formation of a completely new pocket. Here, we review recent developments in computational methods to detect and define binding pockets and to study pocket dynamics. We introduce five different classes of protein pocket dynamics: (1) appearance/disappearance of a subpocket in an existing pocket; (2) appearance/disappearance of an adjacent pocket on the protein surface in the direct vicinity of an already existing pocket; (3) pocket breathing, which may be caused by side-chain fluctuations or backbone or interdomain vibrational motion; (4) opening/closing of a channel or tunnel, connecting a pocket inside the protein with solvent, including lid motion; and (5) the appearance/disappearance of an allosteric pocket at a site on a protein distinct from an already existing pocket with binding of a ligand to the allosteric binding site affecting the original pocket. We suggest that the class of pocket dynamics, as well as the type and extent of protein motion affecting the binding pocket, should be factors considered in choosing the most appropriate computational approach to study a given binding pocket. Furthermore, we examine the relationship between pocket dynamics classes and induced fit, conformational selection, and gating models of ligand binding on binding kinetics and thermodynamics. We discuss the implications of protein binding pocket dynamics for drug design and conclude with potential future directions for computational analysis of protein binding pocket dynamics.

CCProf: exploring conformational change profile of proteins

In many biological processes, proteins have important interactions with various molecules such as proteins, ions or ligands. Many proteins undergo conformational changes upon these interactions, where regions with large conformational changes are critical to the interactions. This work presents the CCProf platform, which provides conformational changes of entire proteins, named conformational change profile (CCP) in the context. CCProf aims to be a platform where users can study potential causes of novel conformational changes. It provides 10 biological features, including conformational change, potential binding target site, secondary structure, conservation, disorder propensity, hydropathy propensity, sequence domain, structural domain, phosphorylation site and catalytic site. All these information are integrated into a well-aligned view, so that researchers can capture important relevance between different biological features visually. The CCProf contains 986 187 protein structure pairs for 3123 proteins. In addition, CCProf provides a 3D view in which users can see the protein structures before and after conformational changes as well as binding targets that induce conformational changes. All information (e.g. CCP, binding targets and protein structures) shown in CCProf, including intermediate data are available for download to expedite further analyses.

Database URL: http://zoro.ee.ncku.edu.tw/ccprof/

Adaptive BP-Dock: An Induced Fit Docking Approach for Full Receptor Flexibility

We present an induced fit docking approach called Adaptive BP-Dock that integrates perturbation response scanning (PRS) with the flexible docking protocol of RosettaLigand in an adaptive manner. We first perturb the binding pocket residues of a receptor and obtain a new conformation based on the residue response fluctuation profile using PRS. Next, we dock a ligand to this new conformation by RosettaLigand, where we repeat these steps for several iterations. We test this approach on several protein test sets including difficult unbound docking cases such as HIV-1 reverse transcriptase and HIV-1 protease. Adaptive BP-Dock results show better correlation with experimental binding affinities compared to other docking protocols. Overall, the results imply that Adaptive BP-Dock can easily capture binding induced conformational changes by simultaneous sampling of protein and ligand conformations. This can provide faster and efficient docking of novel targets for rational drug design.

PDBFlex: exploring flexibility in protein structures

The PDBFlex database, available freely and with no login requirements at http://pdbflex.org, provides information on flexibility of protein structures as revealed by the analysis of variations between depositions of different structural models of the same protein in the Protein Data Bank (PDB). PDBFlex collects information on all instances of such depositions, identifying them by a 95% sequence identity threshold, performs analysis of their structural differences and clusters them according to their structural similarities for easy analysis. The PDBFlex contains tools and viewers enabling in-depth examination of structural variability including: 2D-scaling visualization of RMSD distances between structures of the same protein, graphs of average local RMSD in the aligned structures of protein chains, graphical presentation of differences in secondary structure and observed structural disorder (unresolved residues), difference distance maps between all sets of coordinates and 3D views of individual structures and simulated transitions between different conformations, the latter displayed using JSMol visualization software.

Molecular Dynamics: New Frontier in Personalized Medicine

The field of drug discovery has witnessed infinite development over the last decade with the demand for discovery of novel efficient lead compounds. Although the development of novel compounds in this field has seen large failure, a breakthrough in this area might be the establishment of personalized medicine. The trend of personalized medicine has shown stupendous growth being a hot topic after the successful completion of Human Genome Project and 1000 genomes pilot project. Genomic variant such as SNPs play a vital role with respect to inter individual's disease susceptibility and drug response. Hence, identification of such genetic variants has to be performed before administration of a drug. This process requires high-end techniques to understand the complexity of the molecules which might bring an insight to understand the compounds at their molecular level. To sustenance this, field of bioinformatics plays a crucial role in revealing the molecular mechanism of the mutation and thereby designing a drug for an individual in fast and affordable manner. High-end computational methods, such as molecular dynamics (MD) simulation has proved to be a constitutive approach to detecting the minor changes associated with an SNP for better understanding of the structural and functional relationship. The parameters used in molecular dynamic simulation elucidate different properties of a macromolecule, such as protein stability and flexibility. MD along with docking analysis can reveal the synergetic effect of an SNP in protein-ligand interaction and provides a foundation for designing a particular drug molecule for an individual. This compelling application of computational power and the advent of other technologies have paved a promising way toward personalized medicine. In this in-depth review, we tried to highlight the different wings of MD toward personalized medicine.

WONKA: objective novel complex analysis for ensembles of protein-ligand structures

WONKA is a tool for the systematic analysis of an ensemble of protein-ligand structures. It makes the identification of conserved and unusual features within such an ensemble straightforward. WONKA uses an intuitive workflow to process structural co-ordinates. Ligand and protein features are summarised and then presented within an interactive web application. WONKA's power in consolidating and summarising large amounts of data is described through the analysis of three bromodomain datasets. Furthermore, and in contrast to many current methods, WONKA relates analysis to individual ligands, from which we find unusual and erroneous binding modes. Finally the use of WONKA as an annotation tool to share observations about structures is demonstrated. WONKA is freely available to download and install locally or can be used online at http://wonka.sgc.ox.ac.uk.

A Quantitative Measure of Conformational Changes in Apo, Holo and Ligand-Bound Forms of Enzymes

Determination of the native geometry of the enzymes and ligand complexes is a key step in the process of structure-based drug designing. Enzymes and ligands show flexibility in structural behavior as they come in contact with each other. When ligand binds with active site of the enzyme, in the presence of cofactor some structural changes are expected to occur in the active site. Motivation behind this study is to determine the nature of conformational changes as well as regions where such changes are more pronounced. To measure the structural changes due to cofactor and ligand complex, enzyme in apo, holo and ligand-bound forms is selected. Enzyme data set was retrieved from protein data bank. Fifteen triplet groups were selected for the analysis of structural changes based on selection criteria. Structural features for selected enzymes were compared at the global as well as local region. Accessible surface area for the enzymes in entire triplet set was calculated, which describes the change in accessible surface area upon binding of cofactor and ligand with the enzyme. It was observed that some structural changes take place during binding of ligand in the presence of cofactor. This study will helps in understanding the level of flexibility in protein-ligand interaction for computer-aided drug designing.

Nullspace Sampling with Holonomic Constraints Reveals Molecular Mechanisms of Protein Gαs

Proteins perform their function or interact with partners by exchanging between conformational substates on a wide range of spatiotemporal scales. Structurally characterizing these exchanges is challenging, both experimentally and computationally. Large, diffusional motions are often on timescales that are difficult to access with molecular dynamics simulations, especially for large proteins and their complexes. The low frequency modes of normal mode analysis (NMA) report on molecular fluctuations associated with biological activity. However, NMA is limited to a second order expansion about a minimum of the potential energy function, which limits opportunities to observe diffusional motions. By contrast, kino-geometric conformational sampling (KGS) permits large perturbations while maintaining the exact geometry of explicit conformational constraints, such as hydrogen bonds. Here, we extend KGS and show that a conformational ensemble of the α subunit Gαs of heterotrimeric stimulatory protein Gs exhibits structural features implicated in its activation pathway. Activation of protein Gs by G protein-coupled receptors (GPCRs) is associated with GDP release and large conformational changes of its α-helical domain. Our method reveals a coupled α-helical domain opening motion while, simultaneously, Gαs helix α5 samples an activated conformation. These motions are moderated in the activated state. The motion centers on a dynamic hub near the nucleotide-binding site of Gαs, and radiates to helix α4. We find that comparative NMA-based ensembles underestimate the amplitudes of the motion. Additionally, the ensembles fall short in predicting the accepted direction of the full activation pathway. Taken together, our findings suggest that nullspace sampling with explicit, holonomic constraints yields ensembles that illuminate molecular mechanisms involved in GDP release and protein Gs activation, and further establish conformational coupling between key structural elements of Gαs.

Features of large hinge-bending conformational transitions. Prediction of closed structure from open state

We performed a detailed analysis of conformational transition pathways for a set of 10 proteins, which undergo large hinge-bending-type motions with 4-12 Å RMSD (root mean-square distance) between open and closed crystal structures. Anisotropic network model-Monte Carlo (ANM-MC) algorithm generates a targeted pathway between two conformations, where the collective modes from the ANM are used for deformation at each iteration and the conformational energy of the deformed structure is minimized via an MC algorithm. The target structure was approached successfully with an RMSD of 0.9-4.1 Å when a relatively low cutoff radius of 10 Å was used in ANM. Even though one predominant mode (first or second) directed the open-to-closed conformational transition, changes in the dominant mode character were observed for most cases along the transition. By imposing radius of gyration constraint during mode selection, it was possible to predict the closed structure for eight out of 10 proteins (with initial 4.1-7.1 Å and final 1.7-2.9 Å RMSD to target). Deforming along a single mode leads to most successful predictions. Based on the previously reported free energy surface of adenylate kinase, deformations along the first mode produced an energetically favorable path, which was interestingly facilitated by a change in mode shape (resembling second and third modes) at key points. Pathway intermediates are provided in our database of conformational transitions (http://safir.prc.boun.edu.tr/anmmc/method/1).

Discovery of small molecule CD40-TRAF6 inhibitors

The CD154-CD40 receptor complex plays a pivotal role in several inflammatory pathways. Attempts to inhibit the formation of this complex have resulted in systemic side effects. Downstream inhibition of the CD40 signaling pathway therefore seems a better way to ameliorate inflammatory disease. To relay a signal, the CD40 receptor recruits adapter proteins called tumor necrosis factor receptor-associated factors (TRAFs). CD40-TRAF6 interactions are known to play an essential role in several inflammatory diseases. We used in silico, in vitro, and in vivo experiments to identify and characterize compounds that block CD40-TRAF6 interactions. We present in detail our drug docking and optimization pipeline and show how we used it to find lead compounds that reduce inflammation in models of peritonitis and sepsis. These compounds appear to be good leads for drug development, given the observed absence of side effects and their demonstrated efficacy for peritonitis and sepsis in mouse models.

Synthesis and in vitro bioactivity evaluation of new glucose and xylitol ester derivatives of 5-aminosalicylic acid

Synthesis,in vitroanti-bacterial, anti-inflammatory and anti-cancer activity evaluations andin silicostudy of monosaccharide derivatives of mesalazine in comparison with parent drug.

SPILLO-PBSS: detecting hidden binding sites within protein 3D-structures through a flexible structure-based approach

The study reports a flexible structure-based approach aimed at identifying binding sites within target proteins starting from a well-defined reference binding site. The method, named SPILLO potential binding sites searcher (SPILLO-PBSS), includes a suitably designed tolerance which allows an efficient recognition of the potential binding sites regardless of both involved residues and protein conformation. Hence, the proposed method overcomes the rigidity which affects the available approaches and which prevents a proper analysis of distorted binding sites. We apply SPILLO-PBSS to several test cases, including the search for the guanosine diphosphate binding site in distorted H-Ras proteins and the identification of acetylcholine binding proteins from among a library of heterogeneous resolved proteins. Tests are also performed to compare SPILLO-PBSS with other related and available methods. The encouraging results confirm the notable potentialities of this approach and lay the foundation for its use to analyze and predict target proteins on a proteome-wide scale.

Ligand-receptor affinities computed by an adapted linear interaction model for continuum electrostatics and by protein conformational averaging

Accurate calculations of free energies involved in small-molecule binding to a receptor are challenging. Interactions between ligand, receptor, and solvent molecules have to be described precisely, and a large number of conformational microstates has to be sampled, particularly for ligand binding to a flexible protein. Linear interaction energy models are computationally efficient methods that have found considerable success in the prediction of binding free energies. Here, we parametrize a linear interaction model for implicit solvation with coefficients adapted by ligand and binding site relative polarities in order to predict ligand binding free energies. Results obtained for a diverse series of ligands suggest that the model has good predictive power and transferability. We also apply implicit ligand theory and propose approximations to average contributions of multiple ligand-receptor poses built from a protein conformational ensemble and find that exponential averages require proper energy discrimination between plausible binding poses and false-positives (i.e., decoys). The linear interaction model and the averaging procedures presented can be applied independently of each other and of the method used to obtain the receptor structural representation.

Mechanistic details for anthraniloyl transfer in PqsD: the initial step in HHQ biosynthesis

PqsD mediates the conversion of anthraniloyl-coenzyme A (ACoA) to 2-heptyl-4-hydroxyquinoline (HHQ), a precursor of the Pseudomonas quinolone signal (PQS) molecule. Due to the role of the quinolone signaling pathway of Pseudomonas aeruginosa in the expression of several virulence factors and biofilm formation, PqsD is a potential target for controlling this nosocomial pathogen, which exhibits a low susceptibility to standard antibiotics. PqsD belongs to the β-ketoacyl-ACP synthase family and is similar in structure to homologous FabH enzymes in E. coli and Mycobacterium tuberculosis. Here, we used molecular dynamics simulations to obtain the structural position of the substrate ACoA in the binding pocket of PqsD, and semiempirical molecular orbital calculations to study the reaction mechanism for the catalytic cleavage of ACoA. Our findings suggest a nucleophilic attack of the deprotonated sulfur of Cys112 at the carbonyl carbon of ACoA and a switch in the protonation pattern of His257 whereby Nδ is protonated and the proton of Nε is shifted to the sulfur of CoA during the reaction. This is in agreement with the experimentally determined decreased catalytic activity of the Cys112Ser mutant, whereas the Cys112Ala, His257Phe, and Asn287Ala mutants are all inactive. ESI mass-spectrometric measurements of the Asn287Ala mutant show that anthraniloyl remains covalently bound to Cys112, thus further supporting the inference from our computed mechanism that Asn287 does not take part in the cleavage of ACoA. Since this mutant is inactive, we suggest instead that Asn287 must play an essential role in the subsequent formation of HHQ in vitro.

Specific non-local interactions are not necessary for recovering native protein dynamics

The elastic network model (ENM) is a widely used method to study native protein dynamics by normal mode analysis (NMA). In ENM we need information about all pairwise distances, and the distance between contacting atoms is restrained to the native value. Therefore ENM requires O(N²) information to realize its dynamics for a protein consisting of N amino acid residues. To see if (or to what extent) such a large amount of specific structural information is required to realize native protein dynamics, here we introduce a novel model based on only O(N) restraints. This model, named the ‘contact number diffusion’ model (CND), includes specific distance restraints for only local (along the amino acid sequence) atom pairs, and semi-specific non-local restraints imposed on each atom, rather than atom pairs. The semi-specific non-local restraints are defined in terms of the non-local contact numbers of atoms. The CND model exhibits the dynamic characteristics comparable to ENM and more correlated with the explicit-solvent molecular dynamics simulation than ENM. Moreover, unrealistic surface fluctuations often observed in ENM were suppressed in CND. On the other hand, in some ligand-bound structures CND showed larger fluctuations of buried protein atoms interacting with the ligand compared to ENM. In addition, fluctuations from CND and ENM show comparable correlations with the experimental B-factor. Although there are some indications of the importance of some specific non-local interactions, the semi-specific non-local interactions are mostly sufficient for reproducing the native protein dynamics.

Coevolutionary signals across protein lineages help capture multiple protein conformations

A long-standing problem in molecular biology is the determination of a complete functional conformational landscape of proteins. This includes not only proteins' native structures, but also all their respective functional states, including functionally important intermediates. Here, we reveal a signature of functionally important states in several protein families, using direct coupling analysis, which detects residue pair coevolution of protein sequence composition. This signature is exploited in a protein structure-based model to uncover conformational diversity, including hidden functional configurations. We uncovered, with high resolution (mean ~1.9 Å rmsd for nonapo structures), different functional structural states for medium to large proteins (200-450 aa) belonging to several distinct families. The combination of direct coupling analysis and the structure-based model also predicts several intermediates or hidden states that are of functional importance. This enhanced sampling is broadly applicable and has direct implications in protein structure determination and the design of ligands or drugs to trap intermediate states.

Rapid identification of ligand-binding sites by using an assignment-free NMR approach

In this study, we developed an assignment-free approach for rapid identification of ligand-binding sites in target proteins by using NMR. With a sophisticated cell-free stable isotope-labeling procedure that introduces (15)N- or (13)C-labels to specific atoms of target proteins, this approach requires only a single series of ligand titrations with labeled targets. Using titration data, ligand-binding sites in the target protein can be identified without time-consuming assignment procedures. We demonstrated the feasibility of this approach by using structurally well-characterized interactions between mitogen-activated protein (MAP) kinase p38α and its inhibitor 2-amino-3-benzyloxypyridine. Furthermore, we confirmed the recently proposed fatty acid binding to p38α and confirmed the fatty acid-binding site in the MAP kinase insert region.

Interaction of multimicrobial synthetic inhibitor 1,2-bis(2-benzimidazolyl)-1,2-ethanediol with serum albumin: spectroscopic and computational studies

The molecule, 1,2-Bis(2-benzimidazolyl)-1,2-ethanediol (BBE) is known to act as a selective inhibitor of poliovirus, rhinovirus, Candida albicans, several bacterial species, and is easily synthesized by Phillips reaction. The interaction of BBE with BSA and the effects of its binding on the conformation and unfolding/refolding pathways of the protein were investigated using multispectroscopic techniques and molecular modeling. The binding studies indicate that BSA has one high affinity BBE binding site with association constant 6.02±0.05×10(4) M(-1) at 298 K. By measuring binding at different temperatures, we determined the changes in enthalpy (ΔH = -15.13±2.15 kJ mol(-1)), entropy (ΔS = 40.87±7.25 J mol(-1) K(-1)) and free energy (ΔG( = )26.78±1.02) of interaction, which indicate that the binding was spontaneous and both enthalpically and entropically driven. Based on molecular modeling and thermodynamic parameters, we proposed that the complex formation involved mainly hydrophilic interaction such as hydrogen bonding between hydroxyl groups of ethane-1,2-diol fragment with Tyr410 and benzimidazole sp(2) nitrogen atom with Ser488 and hydrophobic interaction between phenyl ring of one benzimidazole of the ligand and hydrophobic residues namely, Ile387, Cys391, Phe402, Val432 and Cys437. The sequential unfolding mechanism of BSA, site-specific marker displacement experiments and molecular modeling showed that the molecule preferably binds in subdomain IIIA. The BBE binding to BSA was found to cause both secondary and tertiary structural alterations in the protein as studied by intrinsic fluorescence, near-UV and far-UV circular dichroism results. The unfolding/refolding study showed that BBE stabilized native to intermediate states (N⇌I) transition of the protein by ∼2 kJ mol(-1) without affecting the intermediate to unfolded states (I⇌U) transition and general mechanism of unfolding of BSA.

Molecular recognition in the case of flexible targets

A protein's flexibility is well recognized to underlie its capacity to engage in critical functions, such as signal transduction, biomolecular transport and biochemical reactivity. Molecular recognition is also tightly linked to the dynamics of the binding partners, yet protein flexibility has largely been ignored by the growing field of structure-based drug design (SBDD). In combination with experimentally determined structures, a number of computational methods have been proposed to model protein movements, which may be important for small molecule binding. Such techniques have the ability to expose new binding site conformations, which may in turn recognize and lead to the discovery of more potent and selective drugs through molecular docking. In this article, we discuss various methods and focus on the Relaxed Complex Scheme (RCS), which uses Molecular Dynamics (MD) simulations to model full protein flexibility and enhance virtual screening programmes. We review practical applications of the RCS and use a recent study of the HIV-1 reverse transcriptase to illustrate the various phases of the scheme. We also discuss some encouraging developments, aimed at addressing current weaknesses of the RCS.

Benchmarks for flexible and rigid transcription factor-DNA docking

BACKGROUND

Structural insight from transcription factor-DNA (TF-DNA) complexes is of paramount importance to our understanding of the affinity and specificity of TF-DNA interaction, and to the development of structure-based prediction of TF binding sites. Yet the majority of the TF-DNA complexes remain unsolved despite the considerable experimental efforts being made. Computational docking represents a promising alternative to bridge the gap. To facilitate the study of TF-DNA docking, carefully designed benchmarks are needed for performance evaluation and identification of the strengths and weaknesses of docking algorithms.

RESULTS

We constructed two benchmarks for flexible and rigid TF-DNA docking respectively using a unified non-redundant set of 38 test cases. The test cases encompass diverse fold families and are classified into easy and hard groups with respect to the degrees of difficulty in TF-DNA docking. The major parameters used to classify expected docking difficulty in flexible docking are the conformational differences between bound and unbound TFs and the interaction strength between TFs and DNA. For rigid docking in which the starting structure is a bound TF conformation, only interaction strength is considered.

CONCLUSIONS

We believe these benchmarks are important for the development of better interaction potentials and TF-DNA docking algorithms, which bears important implications to structure-based prediction of transcription factor binding sites and drug design.

Predicting protein ligand binding motions with the conformation explorer

BACKGROUND

Knowledge of the structure of proteins bound to known or potential ligands is crucial for biological understanding and drug design. Often the 3D structure of the protein is available in some conformation, but binding the ligand of interest may involve a large scale conformational change which is difficult to predict with existing methods.

RESULTS

We describe how to generate ligand binding conformations of proteins that move by hinge bending, the largest class of motions. First, we predict the location of the hinge between domains. Second, we apply an Euler rotation to one of the domains about the hinge point. Third, we compute a short-time dynamical trajectory using Molecular Dynamics to equilibrate the protein and ligand and correct unnatural atomic positions. Fourth, we score the generated structures using a novel fitness function which favors closed or holo structures. By iterating the second through fourth steps we systematically minimize the fitness function, thus predicting the conformational change required for small ligand binding for five well studied proteins.

CONCLUSIONS

We demonstrate that the method in most cases successfully predicts the holo conformation given only an apo structure.

iMod: multipurpose normal mode analysis in internal coordinates

MOTIVATION

Dynamic simulations of systems with biologically relevant sizes and time scales are critical for understanding macromolecular functioning. Coarse-grained representations combined with normal mode analysis (NMA) have been established as an alternative to atomistic simulations. The versatility and efficiency of current approaches normally based on Cartesian coordinates can be greatly enhanced with internal coordinates (IC).

RESULTS

Here, we present a new versatile tool chest to explore conformational flexibility of both protein and nucleic acid structures using NMA in IC. Consideration of dihedral angles as variables reduces the computational cost and non-physical distortions of classical Cartesian NMA methods. Our proposed framework operates at different coarse-grained levels and offers an efficient framework to conduct NMA-based conformational studies, including standard vibrational analysis, Monte-Carlo simulations or pathway exploration. Examples of these approaches are shown to demonstrate its applicability, robustness and efficiency.

CONTACT

pablo@chaconlab.org

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Ligand-induced conformational change of a protein reproduced by a linear combination of displacement vectors obtained from normal mode analysis

The conformational change of a protein upon ligand binding was examined by normal mode analysis (NMA) based on an elastic-network model (ENM) for a full-atom system using dihedral angles as independent variables. Specifically, we investigated the extent to which conformational change vectors of atoms from an apo form to a holo form of a protein can be represented by a linear combination of the displacement vectors of atoms in the apo form calculated for the lowest-frequency m normal modes (m=1, 2,…, 20). In this analysis, the latter vectors were best fitted to the former ones by the least-squares method. Twenty-two paired proteins in the holo and apo forms, including three dimer pairs, were examined. The results showed that, in most cases, the conformational change vectors were reproduced well by a linear combination of the displacement vectors of a small number of low-frequency normal modes. The conformational change around an active site was reproduced as well as the entire conformational change, except for some proteins that only undergo significant conformational changes around active sites. The weighting factors for 20 normal modes optimized by the least-squares fitting characterize the conformational changes upon ligand binding for these proteins. The conformational changes sampled around the apo form of a protein by the linear combination of the displacement vectors obtained by ENM-based NMA may help solve the flexible-docking problem of a protein with another molecule because the results presented herein suggest that they have a relatively high probability of being involved in an actual conformational change.