Three-dimensional Topological and Geometrical Analysis for the Investigation of Topological Features in Experimental Results of Macromolecular Modeling and Drug Design Projects
Topological analysis of macromolecules is a new powerful concept for the analysis of protein structure. This concept is based on the analysis of geometric structures of three-dimensional shapes. The analysis is based on topological
interpretations of shapes rather than on the classical geometric ones. Topological properties of molecules, like size, mass, shape, volume, conformational changes etc. can be determined by the topological
properties of the molecule. If we can estimate a geometrical point with any shape, then we can calculate the topological properties of the point. Hence the topological properties of the molecule can be estimated.
Topological analysis is used to study biological macromolecules like DNA, RNA, proteins, glycoproteins and immunoglobulins. Topological properties of macromolecules like hydrophobicity, flexibility, steric properties etc. can be estimated
using topological analysis methods. The molecule can be visualized in several perspectives including van der Waals, Eisenberg, TPSSh, Connolly, Connolly-Barrow etc.
As a result of topological analysis, the molecule has some distinct properties that help to understand its function.
KEYMACRO Description:
High-Resolution X-ray Diffraction Data Analysis of Protein Crystal Structures
High-resolution X-ray diffraction (XRD) is a technique used for determination of three-dimensional structures of proteins and DNA. Data analysis of X-ray diffraction experiments is crucial for the correct identification of X-ray
data and evaluation of their accuracy. It is a time consuming task and requires strong computing resources and expertise.
A new software was developed to perform automated data analysis of X-ray diffraction data, including estimation of the crystal structure solution and refinement.
KEYMACRO Description:
Estimation of functional consequences of sequence variants
in OMIM-patients
The growing number of sequence variants and high-throughput sequencing technologies demand methods that make a prediction of the potential pathogenicity of sequence variants.
An interactive approach, using inheritance, clinical data and analysis of sequence variants, is presented for variant prioritization. The approach is based on a calculation of residual disease susceptibility
for the patient’s genotype.
KEYMACRO Description:
Development and implementation of a new method for detection of gene 70238732e0
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