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This results from the current implementation of Phyre which uses one template for homology modeling per protein sequence.
To this day, homology modeling methods represent one of the most reliable approache to generate a structural model for a protein sequence [5], when at least one suitable template is available.
Comparative modeling calculates a 3D model of a given protein sequence from the previously determined structures of related proteins.
Results: We present a novel protein threading method, CNFpred, which achieves much more accurate sequence template alignment by employing a probabilistic graphical model called a Conditional Neural Field (CNF), which aligns one protein sequence to its remote template using a non-linear scoring function.
To build a structure model for a target protein sequence, the TBM process consists of four major steps: identification of structural templates, alignment of target sequence to structural templates (or sequence-structure alignment), model building, and model quality evaluation.
Nucleic acid MSAs were performed with DAMBE [28] using the protein sequence alignment as a template.
Then the templates are selected to build the structure models for the query protein sequence using MODELLER [28].
The percentage similarity between template and protein sequence was 24%.
Protein sequence trees were constructed from template CLUSTALX tree files (.ph) generated during MCOFFEE alignment.
For the organisms in the priority set, we performed a large-scale homology modeling of all protein sequences for which we found valid structural templates as explained in the Methods Section.
The model quality of TBM depends on sequence-template alignment and template selection, both of which are challenging when only distantly related templates are available for a protein sequence under prediction.
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