On the accuracy of homology modeling and sequence alignment methods applied to membrane proteins.

By L. Forrest, Christopher Tang, Barry Honig. 2006

242 citations recorded by the source corpus.

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In Molecular Biology

Citations in the corpus

MRFalign: Protein Homology Detection through Alignment of Markov Random Fields (2014, background): “Sequence-based protein alignment and homology detection has been extensively studied and widely applied to many biological problems such as homology modeling [1-4], phylogeny inference [5-7] and protein function prediction [8-10].”
Memoir: template-based structure prediction for membrane proteins (2013, unknown): “Fortunately, structural constraints imposed on the protein by its biological membrane are thought to make membrane protein models more accurate than similarly remote globular protein models (3).”
Accurate multiple sequence alignment of transmembrane proteins with PSI-Coffee (2012, background): “The problem of generating multiple sequence alignments (MSAs) of TMPs was first addressed by [3], and over the last years several packages have been published, specifically designed for that task [4-6].”
Modern homology modeling of G-protein coupled receptors: which structural template to use? (2009, methodology): “However, the data for transmembrane proteins (without considering loops) can be represented by a linear relationship in the SI range between 30 − 100% 25 .”
The SLC2 (GLUT) Family of Membrane Transporters (2013, unknown): “However, the accuracy of this model is uncertain because the protein used as the template structure, the E. coli glycerol-3-P antiporter, shares little if any significant sequence identity with GLUT1, making it impossible to evaluate the accuracy of the sequence alignment (Forrest et al., 2006).”