Biomedical subjects

N L Lunina

Publications and source records attributed to N L Lunina.

5 recordsLinked to original sources

PubMed2001

Low-resolution data analysis for low-density lipoprotein particle.

The knowledge of the molecular structure of LDL, a large lipoprotein complex, is of great interest for medical investigations. Currently available LDL crystals do not diffract to high resolution and do not allow the application of standard crystallographic techniques. Additional difficulties arise because of a very dense crystal packing and the presence of several components with quite different mean densities. Several ab initio phasing methods previously reported by the authors have been successfully applied to find a crystallographic image of LDL at a resolution of 27 A. The most promising results have been obtained using direct phasing with a connectivity analysis of the electron-density maps. The current image makes it possible to discern a single particle covered by a layer of relatively high density that is asymmetrically distributed on the particle surface. It shows a partition of high and low densities inside the particle and, in particular, strips of varying density in the lipid core.

Crystallography, X-Ray↗

PubMed2000

Connectivity properties of high-density regions and ab initio phasing at low resolution.

It is expected that a correctly phased low-resolution synthesis would show a set of isolated 'blobs' located near to the centres of the macromolecules if the corresponding cut-off level is chosen properly. This is not always the case when using experimentally measured structure-factor magnitudes. Nevertheless, this property can be efficiently used as a constraint in the low-resolution ab initio phasing of structure factors. The suggested procedure consists in generating a large number of random phase sets, selecting those that together with the observed magnitudes result in the desired number of blobs in Fourier syntheses, and averaging the selected phase sets. The current paper discusses the formal definitions, analysis of low-resolution syntheses, some phasing algorithms and their application to ab initio phasing.

Chemical Phenomena↗

PubMed2000

Density constraints and low-resolution phasing.

Direct phasing needs additional information of a non-specific kind in order to select the correct phase set from all possible ones. This paper analyses the use of constraints which can be formulated in terms of electron-density values. One- and multi-dimensional histograms and connectivity properties are implemented as such constraints in density-modification procedures. These approaches usually cannot unambiguously select the best solution from a set of alternative phase variants. Nevertheless, they do allow the rejection of wrong solutions and the use of cluster analysis and averaging on the remaining variants provide a good starting point for further phase-refinement procedures.

Crystallography, X-Ray↗

PubMed2000

Low-resolution ab initio phasing: problems and advances.

If only native amplitudes are used for structure determination, then additional 'theoretical' information is necessary to determine their phases. For use in a phasing procedure, this information can be formulated as a selection criterion (figure of merit) which assigns a reliability weight to every trial phase set and distinguishes the closest ones to the true phase set. Different types of additional information may be tested as a selection criterion: electron-density histograms, connectivity properties, statistical likelihood, atomicity etc. A common feature of such criteria is that they do not unambiguously judge the phase quality at low resolution. Nevertheless, the selection of the phase sets with best criterion values increases the ratio of good phase sets in the ensemble considered. An approximate solution of the phase problem may then be found by averaging the selected phase sets. Cluster analysis of the selected phase sets and averaging within clusters allow further improvement of this solution.

Cluster Analysis↗

PubMed1998

On the ab initio solution of the phase problem or macromolecules at very low resolution. II. Generalized likelihood based approach to cluster discrimination.

The multisolution strategies for direct phasing at very low resolution, such as the few atoms model technique, result in a number of alternative phase sets, each of them arising from a cluster of closely related models. Use of a Monte-Carlo type computer procedure is suggested to choose between the possible phase sets. It consists of generating a large number of pseudo-atom models inside the mask defined by a trial phase set and the use of histograms of magnitude correlation to evaluate the masks. It is shown that the procedure may be considered as a generalization of the statistical maximum-likelihood principle and may be used as a powerful supplementary tool in the likelihood-based approaches to the phase problem solution.

Cluster Analysis↗