Laurence Leherte

Analysis of three-dimensional protein images

A fundamental goal of research in molecular biology is to understand protein structure. Protein crystallography is currently the most successful method for determining the three-dimensional (3D) conformation of a protein, yet it remains labor intensive and relies on an experts ability to derive and evaluate a protein scene model. In this paper, the problem of protein structure determination is formulated as an exercise in scene analysis. A computational methodology is presented in which a 3D image of a protein is segmented into a graph of critical points. Bayesian and certainty factor approaches are described and used to analyze critical point graphs and identify meaningful substructures, such as α-helices and β-sheets. Results of applying the methodologies to protein images at low and medium resolution are reported. The research is related to approaches to representation, segmentation and classification in vision, as well as to top-down approaches to protein structure prediction.

Molecular Mechanical Investigation of the Energetics of Butene Sorbed in H-Ferrierite

Abstract The energetics and diffusion of the four butene isomers in a model of protonated ferrierite with Si/Al ratio of 8 is investigated using molecular mechanics, molecular dynamics, and a simple activated jump diffusion model, in order to determine the influence of the diffusion of the sorbent molecules onto the selectivity of ferrierite toward isobutene. Two main classes of adsorption sites are found, in the main 10-T channels and in cavities along 8-T channels. The magnitude of the self-diffusion coefficient mainly depends on the motions of the molecules in the 10-T channels, and it is found that isobutene diffuses more slowly than the linear isomers: at 623 K, D (isobutene) < 0.03 × 10−4 cm2/s, while D (trans-2-butene)  0.42 × 10−4 cm2/s. However, the sites in the 8-T cavities act as molecular traps for linear butenes and slow down their diffusion, while they do not influence the self-diffusion of isobutene. Therefore, the diffusion of isobutene is enhanced relative to the other isomers in ferrier...

Molecular scene analysis: the integration of direct-methods and artificial-intelligence strategies for solving protein crystal structure.

A knowledge-based approach to crystal structure determination is presented. The approach integrates direct-methods and artificial-intelligence strategies to rephrase the structure determination process as an exercise in scene analysis. A general joint probability distribution framework, which allows the incorporation of isomorphous replacement, anomalous scattering and a priori structural information, forms the basis of the direct-methods strategies. The accumulated knowledge on crystal and molecular structures is exploited through the use of artificial-intelligence strategies, which include techniques of knowledge representation, search and machine learning.

Energetics and diffusion of butene isomers in channel zeolites from molecular dynamics simulations

We have investigated the minimum energy positions and the short time self-diffusion of butene isomers in 6 zeolite structures: TON, MTT, MEL, MFI, FER, and HEU. The minimum energy positions, and the corresponding interaction energies, reflect essentially the steric interaction between the guest molecule and the host zeolite walls. It is shown that in all structures except zeolite TON, trans-2-butene diffuses faster than the other isomers, while in all cases except for TON and MTT, the diffusion of isobutene could not be followed during a 200 ps molecular dynamics run. In zeolite TON the ratio of isobutene versus linear butene self-diffusion is larger than in the other zeolites, which indicates that in this particular structure, diffusion is probably not the rate-limiting process to butene isomerization.

SELF-DIFFUSION OF WATER INTO A FERRIERITE-TYPE ZEOLITE BY MOLECULAR DYNAMICS SIMULATIONS

Previous work in our laboratory described the application of molecular dynamics (MD) to the study of water within such complex models as zeolite systems. In particular, the description of well suited interaction potentials, taking into account periodicity and long-range effects, was of relevance. In this contribution, the application of MD to the study of water inside ferrierite is extended to several systems distinguished by different water coverages. It is shown that the self-diffusion character increases for higher water coverage owing to randomization of the translational movements inside the large pores where the interactions with the framework are not too important. An increase in the self-diffusion coefficient is also observed inside small pores when the modelled Bronsted-acid groups are no longer accessible. Comparisons with available experimental neutron diffusion spectra for various hydrated zeolites show that MD is convenient for simulating the translational movements of water molecules within a porous medium, as well as their librational character.

CRITICAL-POINT ANALYSIS IN PROTEIN ELECTRON-DENSITY MAP INTERPRETATION

Publisher Summary Critical-point mapping has the potential to become an effective tool for the segmentation of protein electron-density maps and the recognition of structural motifs within the maps. Being built on a well-defined mathematical framework, it is well suited for implementation as a fully automated computer approach to map interpretation. Current efforts are focused on reimplementing the program to gain speed and to allow for the incorporation of intelligence and information. Critical-point mapping takes as input an electron–density map and produces a provisional interpretation consisting of hypothesized three-dimensional structures. The threading algorithm in turn attempts to find the most plausible ways to superimpose a given sequence onto hypothesized structures with a scoring function. Threading, thus, can be used for the evaluation and validation of map interpretation results. Furthermore, it can be used for the classification and identification of individual residues in medium-resolution electron-density maps, providing a potentially very useful tool for model building and refinement.

Molecular scene analysis: application of a topogical approach to the automated interpretation of protein electron-density maps

Methods to assist in the spatial and visual analysis of electron-density maps have been investigated as part of a project in molecular scene analysis [Fortier, Castleden, Glasgow, Conklin, Walmsley, Leherte & Allen (1993). Acta Cryst. D49, 168-178]. In particular, the usefulness of the topological approach for the segmentation of medium-resolution (3 A) maps of proteins and their interpretation in terms of structural motifs has been assessed. The approach followed is that proposed by Johnson [Johnson (1977). ORCRIT. The Oak Ridge Critical Point Network Program. Chemistry Division, Oak Ridge National Laboratory, USA] which provides a global representation of the electron-density distribution through the location, identification and linkage of its critical points. In the first part of the study, the topological approach was applied to calculated maps of three proteins of small to medium size so as to develop a methodology that could then be used for analyzing maps of medium resolution. The methodology was then applied to both calculated and experimental maps of penicillopepsin at 3 A resolution. The study shows that the networks of critical points can provide a useful segmentation of the maps, tracing the protein main chains and capturing their conformation. In addition, these networks can be parsed in terms of secondary-structure motifs, through a geometrical analysis of the critical points. The procedure adopted for secondary-structure recognition, which was phrased in terms of geometry-based rules, provides a basis for a further automated implementation of a more complete set of recognition operations through the use of artificial-intelligence techniques.

Application of multiresolution analyses to electron density maps of small molecules: Critical point representations for molecular superposition

Three different methods are applied to generate low resolution molecular electron density (ED) distribution functions: a crystallography-based formalism, an analytical approach which allows the calculation of a promolecular ED distribution in terms of a weighted summation over atomic ED distributions, and a wavelet-based multiresolution analysis approach. Critical point graph representations of the molecular ED distributions are then generated by locating points where the gradient of the density is equal to zero, and further considered for pairwise molecular superpositions of thrombin inhibitors using a Monte Carlo/Simulated Annealing technique.

On the modularity of the intrinsic flexibility of the µ opioid receptor : a computational study

The µ opioid receptor (µOR), the principal target to control pain, belongs to the G protein-coupled receptors (GPCRs) family, one of the most highlighted protein families due to their importance as therapeutic targets. The conformational flexibility of GPCRs is one of their essential characteristics as they take part in ligand recognition and subsequent activation or inactivation mechanisms. It is assessed that the intrinsic mechanical properties of the µOR, more specifically its particular flexibility behavior, would facilitate the accomplishment of specific biological functions, at least in their first steps, even in the absence of a ligand or any chemical species usually present in its biological environment. The study of the mechanical properties of the µOR would thus bring some indications regarding the highly efficient ability of the µOR to transduce cellular message. We therefore investigate the intrinsic flexibility of the µOR in its apo-form using all-atom Molecular Dynamics simulations at the sub-microsecond time scale. We particularly consider the µOR embedded in a simplified membrane model without specific ions, particular lipids, such as cholesterol moieties, or any other chemical species that could affect the flexibility of the µOR. Our analyses highlighted an important local effect due to the various bendability of the helices resulting in a diversity of shape and volume sizes adopted by the µOR binding site. Such property explains why the µOR can interact with ligands presenting highly diverse structural geometry. By investigating the topology of the µOR binding site, a conformational global effect is depicted: the correlation between the motional modes of the extra- and intracellular parts of µOR on one hand, along with a clear rigidity of the central µOR domain on the other hand. Our results show how the modularity of the µOR flexibility is related to its pre-ability to activate and to present a basal activity.

Coarse Point Charge Models For Proteins From Smoothed Molecular Electrostatic Potentials

To generate coarse electrostatic models of proteins, we developed an original approach to hierarchically locate maxima and minima in smoothed molecular electrostatic potentials. A charge-fitting program was used to assign charges to the so-obtained reduced representations. Templates are defined to easily generate coarse point charge models for protein structures, in the particular cases of the Amber99 and Gromos43A1 force fields. Applications to four small peptides and to the ion channel KcsA are presented. Electrostatic potential values generated by the reduced models are compared with the corresponding values obtained using the original sets of atomic charges.