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For unbound proteins, the structural alignment between query and template is implemented to map the ligands in bound proteins to the unbound proteins.
Different from traditional dynamic programming algorithm and Monte Carlo algorithm, CE algorithm defines continuous residues in the sequence as aligned fragment pairs (AFPs), which is used in local alignment between query and template.
The Needleman-Wunsch dynamic programming algorithm [ 30] is used to find the best match between query and template sequences.
For the peptide-MHC and peptide-TCR interaction, the scoring function is defined as (2) E T o t a l = E v d W + E S F + E s i m where E vdW is the van der Waal's energy; E SF is the special energy (i.e. hydrogen-bond energy and electrostatic energy); and E sim refers to the peptide similarity score between query and template.
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(b) Matching between query and templates.
The structural alignment between query and templates in bSiteFinder is implemented by using Combinatorial Extension (CE) algorithm, which is provided by Biojava [28].
Sn1 is the raw score S normalized by the length of alignment including gaps between the query and template sequences.
(iii) If a homology model exists, we then check for sequence identity (S.I). between the query and template structures and the completeness of the homologous structure.
Q indicates the query fingerprint, D*1, D*2, D*3 indicate the similarity distance between the query and templates, and D*cindicates the distance between the query and the centroid.
Finally, three alignments were generated between query (OR83b) and template (PDB Structure).
We add the distance into the set which is constituted by the distance between the query and templates.
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