ArticleActa crystallographica. Section D, Structural biology2017
Approaches to ab initio molecular replacement of α-helical transmembrane proteins.
Article in Acta crystallographica. Section D, Structural biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- TMKit: a Python interface for computational analysis of transmembrane proteins.Briefings in bioinformatics · 2023Article
- Machine learning in computational modelling of membrane protein sequences and structures: From methodologies to applications.Computational and structural biotechnology journal · 2023Review
- Computational Study on the Inhibitory Effect of Natural Compounds against the SARS-CoV-2 Proteins.Bioinorganic chemistry and applications · 2022Article
- Helical ensembles outperform ideal helices in molecular replacement.Acta crystallographica. Section D, Structural biology · 2020Article
- Recent developments in MrBUMP: better search-model preparation, graphical interaction with search models, and solution improvement and assessment.Acta crystallographica. Section D, Structural biology · 2018Article
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Authors and funding
7 authors.
Funding
Abstract
α-Helical transmembrane proteins are a ubiquitous and important class of proteins, but present difficulties for crystallographic structure solution. Here, the effectiveness of the AMPLE molecular replacement pipeline in solving α-helical transmembrane-protein structures is assessed using a small library of eight ideal helices, as well as search models derived from ab initio models generated both with and without evolutionary contact information. The ideal helices prove to be surprisingly effective at solving higher resolution structures, but ab initio-derived search models are able to solve structures that could not be solved with the ideal helices. The addition of evolutionary contact information results in a marked improvement in the modelling and makes additional solutions possible.
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