H2020Индивидуална стипендия2018–2020

LikelyStructures · Accounting for correlated errors with maximum likelihood in crystallography and cryo-EM

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2018-06-01 → 2020-05-31
Финансиране от ЕС: 183 455 €
Участници: 1
Схема: MSCA-IF-EF-ST

Линиите свързват координатора с партньорите.

Накратко на български

Структурите на протеините се анализират чрез нови софтуерни методи, които поправят грешки при използването на сходни молекулни модели. Това помага за по-точно определяне на формата на биомолекулите чрез кристалография и електронна микроскопия.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Accounting for correlated errors with maximum likelihood in crystallography and cryo-EM

Macromolecular Crystallography is a gold standard experimental technique to determine the structures of proteins and other macromolecules. As only partial information is directly measured in the experiment, it is usually necessary to use computational methods to derive the missing information. Molecular Replacement (MR) bootstraps the final structure from the initial partial information given by other molecules that share a certain degree of similarity with the unknown structure. In particular, the Phaser MR software uses a statistical approach based on maximum likelihood that is able to exploit even low signal from such remote models, and it is today the most-used software worldwide to accomplish such a task. Over the years the mathematical foundations of the software have been strengthened and the algorithms have become more sophisticated, but limitations remain because of uncertainties in the quality of models and in assumptions about the data themselves. In this project, we tried to address some of those uncertainties by building an automatic, easy to use, graphical pipeline that will prepare both the data and the models prior to and specifically for the molecular replacement task. The findings in this procedure can be exploited and applied also to emergent techniques such as Cryo-EM and EM-Tomography. Our main goal is to build a unified framework that can tackle structural biology problems from different points of view and exploiting prior information combined with machine learning approaches.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

Proper understanding of the biological processes related to complex macromolecular entities depends on the detailed description of their 3D structures. For 100 years X-Ray Crystallography has been the main player in revealing high resolution structures. In the last decade, Bayesian statistics has yielded a breakthrough for solving challenging structures thanks to the integration of specialised error models essential to extract a weak signal from noisy data. Developed on such statistical methods, the program PHASER implements (along with experimental phasing) the Molecular Replacement technique in which the unknown phases, associated with the experimentally recorded intensities, are estimated from a homologous protein structure. Exploiting a deep new understanding of the link between model, data and phasing success, this technique will be decisively extended by the analysis of multiple models collected into ensembles optimised for likelihood calculations. Recent dramatic improvements in cryo-EM hardware have brought it into the high resolution realm and it is bound to become the main structural technique for the kind of challenging structures at the forefront. The leap from qualitative into quantitative Cryo-EM has already involved algorithmic approaches based on Maximum Likelihood. Generalising its full potential requires new methods that will lead to higher resolution reconstructions. The proposed integration of all sources of error is imperative for difficult samples. In this project, advances in both X-ray crystallography and cryo-EM data-analysis methods are planned, focusing on transferring experience acquired over many years in the first field into the second. Central to this project, the personal development of the experienced researcher will broaden his field of expertise in structural biology through advanced statistics with the aim of preparing, mentoring and leading him to an independent future research career in the development of methods.

Оригинален текст от CORDIS (на английски).

Участници

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