Using surface envelopes to constrain molecular modeling

Molecular density information (as measured by electron microscopic reconstructions or crystallographic density maps) can be a powerful source of information for molecular modeling. Molecular density constrains models by specifying where atoms should and should not be. Low-resolution density information can often be obtained relatively quickly, and there is a need for methods that use it effectively. We have previously described a method for scoring molecular models with surface envelopes to discriminate between plausible and implausible fits. We showed that we could successfully filter out models with the wrong shape based on this discrimination power. Ideally, however, surface information should be used during the modeling process to constrain the conformations that are sampled. In this paper, we describe an extension of our method for using shape information during computational modeling. We use the envelope scoring metric as part of an objective function in a global optimization that also optimizes distances and angles while avoiding collisions. We systematically tested surface representations of proteins (using all nonhydrogen heavy atoms) with different abundance of distance information and showed that the root mean square deviation (RMSD) of models built with envelope information is consistently improved, particularly in data sets with relatively small sets of short-range distances.     

Using molecular dynamics for the refinement of atomistic models of GPCRs by homology modeling

Despite GPCRs sharing a common seven helix bundle, analysis of the diverse crystallographic structures available reveal specific features that might be relevant for ligand design. Despite the number of crystallographic structures of GPCRs steadily increasing, there are still challenges that hamper the availability of new structures. In the absence of a crystallographic structure, homology modeling remains one of the important techniques for constructing 3D models of proteins. In the present study we investigated the use of molecular dynamics simulations for the refinement of GPCRs models constructed by homology modeling. Specifically, we investigated the relevance of template selection, ligand inclusion as well as the length of the simulation on the quality of the GPCRs models constructed. For this purpose we chose the crystallographic structure of the rat muscarinic M3 receptor as reference and constructed diverse atomistic models by homology modeling, using different templates. Specifically, templates used in the present work include the human muscarinic M2; the more distant human histamine H1 and the even more distant bovine rhodopsin as shown in the GPCRs phylogenetic tree. We also investigated the use or not of a ligand in the refinement process. Hence, we conducted the refinement process of the M3 model using the M2 muscarinic as template with tiotropium or NMS docked in the orthosteric site and compared with the results obtained with a model refined without any ligand bound.     

Identification of natural compound inhibitors against PfDXR: A hybrid structure-based molecular modeling approach and molecular dynamics simulation studies

In the present contribution, multicomplex-based pharmacophore studies were carried out on the structural proteome of Plasmodium falciparum 1-deoxy-D -xylulose-5-phosphate reductoisomerase. Among the constructed models, a representative model with complementary features, accountable for the inhibition was used as a primary filter for the screening of database molecules. Auxiliary evaluations of the screened molecules were performed via drug-likeness and molecular docking studies. Subsequently, the stability of the docked inhibitors was envisioned by molecular dynamics simulations, principle component analysis, and molecular mechanics-Poisson-Boltzmann surface area-based free binding energy calculations. The stability assessment of the hits was done by comparing with the reference (beta-substituted fosmidomycin analog, LC5) to prioritize more potent candidates. All the complexes showed stable dynamic behavior while three of them displayed higher binding free energy compared with the reference. The work resulted in the identification of the compounds with diverse scaffolds, which could be used as initial leads for the design of novel PfDXR inhibitors.     

Investigations of the thermostability of rubredoxin models using molecular dynamics simulations.

The affects of differences in amino acid sequence on the temperature stability of the three-dimensional structure of the small beta-sheet protein, rubredoxin (Rd), was revealed when a set of homology models was subjected to molecular dynamics simulations at relatively high temperatures. Models of Rd from the hyperthermophile, Pyrococcus furiosus (Pf), an organism that grows optimally at 100 degrees C, were compared to three mesophilic Rds of known X-ray crystal structure. Simulations covering the limits of known Rd thermostabilities were carried out at temperatures of 300 K, 343 K, 373 K, and 413 K. They suggest that Rd stability is correlated with structural dynamics. Because the dynamic behavior of three Pf Rd models was consistently different from the dynamic behavior of the three mesophilic Rd structures, detailed analysis of the temperature-dependent dynamic behavior was carried out. The major differences between the models of the protein from the hyperthermophile and the others were: (1) an obvious temperature-dependent transition in the mesophilic structures not seen with the Pf Rd models, (2) consistent AMBER energy for the Pf Rd due to differences in nonbonded interaction terms, (3) less variation in the average conformations for the Pf Rd models with temperature, and (4) the presence of more extensive secondary structure for the Pf Rd models. These unsolvated dynamics simulations support a simple, general hypothesis to explain the hyperthermostability of Pf Rd. Its structure simplifies the conformational space to give a single minimum accessible over an extreme range of temperatures, whereas the mesophilic proteins sample a more complex conformational space with two or more minima over the same temperature range.     

Identification of protein functions from a molecular surface database,eF-site

A bioinformatics method was developed to identify the protein surface around the functional site and to estimate the biochemical function, using a newly constructed molecular surface database named the eF-site (electrostatic surface of Functional site. Molecular surfaces of protein molecules were computed based on the atom coordinates, and the eF-site database was prepared by adding the physical properties on the constructed molecular surfaces. The electrostatic potential on each molecular surface was individually calculated solving the Poisson–Boltzmann equation numerically for the precise continuum model, and the hydrophobicity information of each residue was also included. The eF-site database is accessed by the internet (http://pi.protein.osaka-u.ac.jp/eF-site/). We have prepared four different databases, eF-site/antibody, eF-site/prosite, eF-site/P-site, and eF-site/ActiveSite, corresponding to the antigen binding sites of antibodies with the same orientations, the molecular surfaces for the individual motifs in PROSITE database, the phosphate binding sites, and the active site surfaces for the representatives of the individual protein family, respectively. An algorithm using the clique detection method as an applied graph theory was developed to search of the eF-site database, so as to recognize and discriminate the characteristic molecular surfaces of the proteins. The method identifies the active site having the similar function to those of the known proteins.     

Identification of protein biochemical functions by similarity search using the molecular surface database eF-site

The identification of protein biochemical functions based on their three-dimensional structures is strongly required in the post-genome-sequencing era. We have developed a new method to identify and predict protein biochemical functions using the similarity information of molecular surface geometries and electrostatic potentials on the surfaces. Our prediction system consists of a similarity search method based on a clique search algorithm and the molecular surface database eF-site (electrostatic surface of functional-site in proteins). Using this system, functional sites similar to those of phosphoenoylpyruvate carboxy kinase were detected in several mononucleotide-binding proteins, which have different folds. We also applied our method to a hypothetical protein, MJ0226 from Methanococcus jannaschii, and detected the mononucleotide binding site from the similarity to other proteins having different folds.     

Inferring functional relationships of proteins from local sequence and spatial surface patterns

We describe a novel approach for inferring functional relationship of proteins by detecting sequence and spatial patterns of protein surfaces. Well-formed concave surface regions in the form of pockets and voids are examined to identify similarity relationship that might be directly related to protein function. We first exhaustively identify and measure analytically all 910,379 surface pockets and interior voids on 12,177 protein structures from the Protein Data Bank. The similarity of patterns of residues forming pockets and voids are then assessed in sequence, in spatial arrangement, and in orientational arrangement. Statistical significance in the form of E and p-values is then estimated for each of the three types of similarity measurements. Our method is fully automated without human intervention and can be used without input of query patterns. It does not assume any prior knowledge of functional residues of a protein, and can detect similarity based on surface patterns small and large. It also tolerates, to some extent, conformational flexibility of functional sites. We show with examples that this method can detect functional relationship with specificity for members of the same protein family and superfamily, as well as remotely related functional surfaces from proteins of different fold structures. We envision that this method can be used for discovering novel functional relationship of protein surfaces, for functional annotation of protein structures with unknown biological roles, and for further inquiries on evolutionary origins of structural elements important for protein function.     

Analytical shape computation of macromolecules: I. molecular area and volume through alpha shape

The size and shape of macromolecules such as proteins and nucleic acids play an important role in their functions. Prior efforts to quantify these properties have been based on various discretization or tessellation procedures involving analytical or numerical computations. In this article, we present an analytically exact method for computing the metric properties of macromolecules based on the alpha shape theory. This method uses the duality between alpha complex and the weighted Voronoi decomposition of a molecule. We describe the intuitive ideas and concepts behind the alpha shape theory and the algorithm for computing areas and volumes of macromolecules. We apply our method to compute areas and volumes of a number of protein systems. We also discuss several difficulties commonly encountered in molecular shape computations and outline methods to overcome these problems. Proteins 33:1–17, 1998. © 1998 Wiley-Liss, Inc.     

Protein surface analysis for function annotation in high-throughput structural genomics pipeline

Structural genomics (SG) initiatives are expanding the universe of protein fold space by rapidly determining structures of proteins that were intentionally selected on the basis of low sequence similarity to proteins of known structure. Often these proteins have no associated biochemical or cellular functions. The SG success has resulted in an accelerated deposition of novel structures. In some cases the structural bioinformatics analysis applied to these novel structures has provided specific functional assignment. However, this approach has also uncovered limitations in the functional analysis of uncharacterized proteins using traditional sequence and backbone structure methodologies. A novel method, named pvSOAR (pocket and void Surface of Amino Acid Residues), of comparing the protein surfaces of geometrically defined pockets and voids was developed. pvSOAR was able to detect previously unrecognized and novel functional relationships between surface features of proteins. In this study, pvSOAR is applied to several structural genomics proteins. We examined the surfaces of YecM, BioH, and RpiB from Escherichia coli as well as the CBS domains from inosine-5'-monosphate dehydrogenase from Streptococcus pyogenes, conserved hypothetical protein Ta549 from Thermoplasm acidophilum, and CBS domain protein mt1622 from Methanobacterium thermoautotrophicum with the goal to infer information about their biochemical function.     

Refining homology models by combining replica-exchange molecular dynamics and statistical potentials

A protocol is presented for the global refinement of homology models of proteins. It combines the advantages of temperature-based replica-exchange molecular dynamics (REMD) for conformational sampling and the use of statistical potentials for model selection. The protocol was tested using 21 models. Of these 14 were models of 10 small proteins for which high-resolution crystal structures were available, the remainder were targets of the recent CASPR exercise. It was found that REMD in combination with currently available force fields could sample near-native conformational states starting from high-quality homology models. Conformations in which the backbone RMSD of secondary structure elements (SSE-RMSD) was lower than the starting value by 0.5-1.0 A were found for 15 out of the 21 cases (average 0.82 A). Furthermore, when a simple scoring function consisting of two statistical potentials was used to rank the structures, one or more structures with SSE-RMSD of at least 0.2 A lower than the starting value was found among the five best ranked structures in 11 out of the 21 cases. The average improvement in SSE-RMSD for the best models was 0.42 A. However, none of the scoring functions tested identified the structures with the lowest SSE-RMSD as the best models although all identified the native conformation as the one with lowest energy. This suggests that while the proposed protocol proved effective for the refinement of high-quality models of small proteins scoring functions remain one of the major limiting factors in structure refinement. This and other aspects by which the methodology could be further improved are discussed.     

Structural analysis and molecular modeling of two antitrichosanthin IgE clones from phage antibody library

Recently we constructed a murine IgE phage surface display library and screened out two IgE (Fab) clones with specific binding activity to Trichosanthin (TCS).In this work,the Vε and Vκ genes of the two clones were sequenced and their putative germline gene usages were studied.On the basis of the known 3D structure of Trichosanthin and antibody,molecular modeling was carried out to study the antigen-antibody interaction.The possible antigenic determinant sites on the surface of TCS recognized by both the clones were analyzed,and the reaction forces between TCS and two Fab fragments were also analyzed respectively.     

Automatic procedure for using models of proteins in molecular replacement

In a crystallography experiment, a crystal is irradiated with X-rays whose diffracted waves are collected and measured. The reconstruction of the structure of the molecule in the crystal requires knowledge of the phase of the diffracted waves, information that is lost in the passage from the three-dimensional structure of the molecule to its diffraction pattern. It can be recovered using experimental methods such as heavy-atom isomorphous replacement and anomalous scattering or by molecular replacement, which relies on the availability of an atomic model of the target structure. This can be the structure of the target protein itself, if a previous structure determination is available, or a computational model or, in some cases, the structure of a homologous protein. It is not straightforward to predict beforehand whether or not a computational model will work in a molecular replacement experiment, although some rules of thumb exist. The consensus is that even minor differences in the quality of the model, which are rather difficult to estimate a priori, can have a significant effect on the outcome of the procedure. We describe here a method for quickly assessing whether a protein structure can be solved by molecular replacement. The procedure consists in submitting the sequence of the target protein to a selected list of freely available structure prediction servers, cluster the resulting models, select the representative structures of each cluster and use them as search models in an automatic phasing procedure. We tested the procedure using the structure factors of newly released proteins of known structure downloaded from the Protein Data Bank as soon as they were made available. Using our automatic procedure we were able to obtain an interpretable electron density map in more than half the cases.     

Free energy surface for rotamers of cis-enol malonaldehyde in aqueous solution studied by molecular dynamics calculations

Two-dimensional free energy surfaces for four rotamers of cis-enol malonaldehyde in water have been investigated by umbrella sampling molecular dynamics (MD) calculations. Biasing potential used in the umbrella sampling calculation was adopted to be the minus of conformational free energy preliminary obtained by the thermodynamic integration MD calculations for the rigid malonaldehyde whose stretching and bending were all fixed. The calculated free energy surface shows that, in water, a rotamer that has an intramolecular hydrogen bond is most stable among the rotamers. This is the same as that in vacuum, while order of relative stability of the other three rotamers is different in water and in vacuum. Inclusion of intramolecular vibrations changed the free energy surface little, i.e. at most 2.6 kJ/mol, which is much smaller than the solvation free energy. Free energy barriers from the most stable intramolecular hydrogen bonded rotamer to the others are lowered by hydration but they are still very high, >50 kJ/mol, such that the malonaldehyde molecule spends most of its time in water taking this conformation. Thus, reaction coordinate for intramolecular proton transfer reaction in water may be constructed assuming this rotamer.     

Using multilevel models to quantify heterogeneity in resource selection

Models of resource selection are being used increasingly to predict or model the effects of management actions rather than simply quantifying habitat selection. Multilevel, or hierarchical, models are an increasingly popular method to analyze animal resource selection because they impose a relatively weak stochastic constraint to model heterogeneity in habitat use and also account for unequal sample sizes among individuals. However, few studies have used multilevel models to model coefficients as a function of predictors that may influence habitat use at different scales or quantify differences in resource selection among groups. We used an example with white-tailed deer (Odocoileus virginianus) to illustrate how to model resource use as a function of distance to road that varies among deer by road density at the home range scale. We found that deer avoidance of roads decreased as road density increased. Also, we used multilevel models with sika deer (Cervus nippon) and white-tailed deer to examine whether resource selection differed between species. We failed to detect differences in resource use between these two species and showed how information-theoretic and graphical measures can be used to assess how resource use may have differed. Multilevel models can improve our understanding of how resource selection varies among individuals and provides an objective, quantifiable approach to assess differences or changes in resource selection. © 2011 The Wildlife Society.     

A molecular dynamics investigation of chiral discrimination complexes as chiral stationary-phase models: Methyl N-(2-naphthyl)alaninate with N-(3,5-dinitrobenzoyl)leucine n-propylamide

Molecular dynamics simulations were performed on complexes of (S)-methyl N-(2-naphthyl)alaninate (NAP) with the enantiomers of N-(3,5-dinitrobenzoyl)leucine n-propylamide (DNB), which are used as models for chiral stationary-phase systems developed by Pirkle and co-workers. These studies were undertaken to qualitatively examine (pictorially) the role of entropic effects in these systems. The results of the dynamics calculations were used to refine the search for low-energy conformers. The structures were refined by the use of BioDesign's molecular mechanics method implemented in Biograf. The results of the structural refinements support our previous observation that the SR complex can achieve the same three primary interactions which are observed in the SS structure (i.e., two intermolecular hydrogen bonds and pi stacking) without a significant increase in energy. In addition, these primary interactions are conserved during molecular dynamics simulations with the occurrence of conformations which differ only in the rotational states of the alkyl side chains and ester group (which bears two potential hydrogen bond acceptors utilized in both the homo- and heterochiral complexes). The major difference in the two complexes is the relative position of the sec-butyl group and hydrogen atom on DNB's chiral center, both of which are outside the primary interaction region. All other local minima which have different relative pi orientations (“front–back,” “back–back,” and “back–front” as defined herein) are not sufficiently populated to make more than a negligible contribution to the statistical (time- or energy-averaged) analysis of the (SS)- and (SR)-NAP–DNB complexes. Thus the entropic effects observed in this study (e.g., alkyl side chain or ester group rotations) do not show evidence of qualitative differential effects on the maintenance of the same three primary interactions by both the homo- and heterochiral complexes. The reliability of the present study, which provides pictorial representations of the entropic effects, is not sufficient to determine whether the entropic effects observed herein are sufficient to achieve enantiomeric discrimination alone or in conjunction with other factors (e.g., conformational strain energy). Thus, all of the computational studies we have performed to date (i.e., our previous studies, which include strain energy and through-space field effects, and the present study, which includes entropic effects) show no evidence of any qualitative difference in the homo- and heterochiral complexes in terms of maintaining the same three “contact points”.     

Novel mutations of the lipoprotein lipase gene associated with hypertriglyceridemia in members of type 2 diabetic pedigrees

Increased plasma triglyceride and free fatty acid levels are frequently associated with type 2 diabetes mellitus (T2DM). To test the hypothesis that LPL gene mutations contribute to the hypertriglyceridemia observed in members of T2DM pedigrees, we screened the LPL gene in 53 hypertriglyceridemic members of 26 families. Four known and three novel mutations were identified. All three novel mutations, Lys312insC, Thr361insA, and double mutation Lys312insC + Asn291Ser, are clinically associated with hypertriglyceridemia. In vitro mutagenesis and expression studies confirm that these variants are associated with a significant reduction in LPL activity. The modeled structures displaying the Lys312insC and Thr361insA mutations showed loss of the activity-related C-terminal domain in the LPL protein. Another novel double mutation, Lys312insC + Asn291Ser, resulted in the loss of the catalytic ability of LPL attributable to the complete loss of the C-terminal domain and alteration in the heparin association site. Thus, these novel mutations of the LPL gene contribute to the hypertriglyceridemia observed in members of type 2 diabetic pedigrees.     

Calculation of the surface tension of planar interfaces by molecular simulations: from Lennard-Jones fluids to binary mixtures

The relative longevity of the research in the field of the molecular simulations of the liquid–vapour interfaces of Lennard-Jones (LJ) particles can be explained by the dependence of the surface tension on many methodological factors. After a few illustrations on the parameters that can impact the results of surface tension on the LJ interfaces, we establish the ability of the current methodologies to quantitatively predict the surface tension of various liquid–vapour interfaces of pure components at different temperatures. We also show that the methods perform very well for the reproduction of the interfacial tension of binary mixtures in a wide range of pressures.