NMR-SBA

AUTOMATED NMR STRUCTURE-BASED ASSIGNMENTS

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 Obiettivo del progetto (Objective)

'While automation is revolutionizing many aspects of biology, the determination of three-dimensional protein structure remains a long, hard, and expensive task. Novel algorithms and computational methods in biomolecular NMR are necessary to apply modern techniques such as structure-based drug design on a much larger scale. The goal of this project is to address a key computational bottleneck in NMR structural biology, resonance assignments. We will accelerate protein NMR assignment by exploiting a priori structural information. By analogy, in X-ray crystallography, the molecular replacement (MR) technique allows solution of the crystallographic phase problem when a “close” or homologous structural model is known, thereby facilitating rapid structure determination. In contrast, a key bottleneck in NMR structural biology is the assignment problem. An automated procedure for rapidly determining NMR assignments given an homologous structure, will similarly accelerate structure determination. Moreover, even when the structure has already been determined by crystallography or computational homology modeling, NMR assignments are valuable because NMR can be used to probe protein-protein interactions and protein-ligand binding (e.g. via chemical shift mapping), and dynamics (via, e.g., nuclear spin relaxation). We will develop an MR-like approach for structure-based assignment of resonances and NOEs, to be applied when a homologous protein is known. The tool that we develop will accept both CH- and NH- RDCs, and 4-D NOESY data, and will implement a Bayesian scoring function for structure-based assignments. It will provide the user the option to use only NH RDCs or NH and CH RDCs and will be tested on real proteins. The source code will be released as open source with the user manual.'

Introduzione (Teaser)

Scientists need many tools to combat diseases such as cancer and cardiovascular disease. An EU-funded project developed software to refine one tool designed to analyse proteins.

Descrizione progetto (Article)

The project 'Automated NMR structure-based assignments' (NMR-SBA) focused on problems in reading the spectra from nuclear magnetic resonance (NMR) studies. Researchers addressed this task by developing automated NMR structure-based assignment software.

To reach this goal, several milestones had to be reached. These included developing algorithms for analysing proteins of various sizes and testing the algorithms to determine the best parameters for their use. In addition, the team incorporated new types of NMR data into the software to increase its usability. They also extracted more data from existing sources to enhance the performance of the algorithms.

The team developed three algorithms and corresponding software to tackle the assignment of proteins in the presence of a template. Researchers used algorithms based on an existing framework called nuclear vector replacement (NVR). The first of these approaches, NVR-BIP, used binary integer programming (BIP) to find the exact solution for minimizing the size of the proteins.

This technique improved the assignment accuracy of the NVR tool significantly. However, it didn't solve the problem for large proteins. Therefore, the team developed two other algorithms for these large proteins. In addition, new data, which previously had to be set manually, have been incorporated into the software.

Researchers used data from public databases, as well as data provided by the team's collaborators, to test the software. If a particular data type was not available, they used synthetic data.

Toward the end of the project, the team received a grant to work with high-profile scientists on new therapeutic avenues. The software will contribute to the study of large proteins for the development of new antibiotics against antibiotic-resistant gram-negative bacteria.

This is one of many ways that scientists can take advantage of this software. Many more will probably be discovered in the future.