Benchmarking of protein descriptor sets in proteochemometric modeling (part 1): comparative study of 13 amino acid descriptor sets
By G. Westen, Remco F. Swier, Jörg Kurt Wegner, Adriaan P. IJzerman, H. V. Vlijmen, Andreas Bender. 2013
113 citations recorded by the source corpus.
BackgroundWhile a large body of work exists on comparing and benchmarking of descriptors of molecular structures, a similar comparison of protein descriptor sets is lacking. Hence, in the current work a total of 13 different protein descriptor sets have been compared with respect to their behavior in perceiving similarities between amino acids. The descriptor sets included in the study are Z-scales (3 variants), VHSE, T-scales, ST-scales, MS-WHIM, FASGAI and BLOSUM, and a novel protein descriptor set termed ProtFP (4 variants). We investigate to which extent descriptor sets show collinear as well as orthogonal behavior via principal component analysis (PCA).ResultsIn describing amino acid similarities, MSWHIM, T-scales and ST-scales show related behavior, as do the VHSE, FASGAI, and ProtFP (PCA3) descriptor sets. Conversely, the ProtFP (PCA5), ProtFP (PCA8), Z-Scales (Binned), and BLOSUM descriptor sets show behavior that is distinct from one another as well as both of the clusters above. Generally, the use of more principal components (>3 per amino acid, per descriptor) leads to a significant differences in the way amino acids are described, despite that the later principal components capture less variation per component of the original input data.ConclusionIn this work a comparison is provided of how similar (and differently) currently available amino acids descriptor sets behave when converting structure to property space. The results obtained enable molecular modelers to select suitable amino acid descriptor sets for structure-activity analyses, e.g. those showing complementary behavior.
Subfields: Computational Theory and Mathematics, Molecular Biology
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In Molecular Biology
- Albert J. Kooistra
- Gáspár Pándy-Szekeres
- David E. Gloriam
- Alibek Mamyrbekov
- György M. Keserü
- Christian Munk
- Stefan Mordalski
- Mauricio Esguerra
Citations in the corpus
- GPCRdb in 2021: integrating GPCR sequence, structure and function (2020, background): “These amino acid groups for residue property conservation, like ligand-based pharmacophores and many previous amino acid descriptors (28), were designed to correlate common sequence features with the ability to mediate a shared molecular interaction and function, such as the binding of a ligand or G”
- Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases (2018, background): “In another study, van Westen and colleagues [36] compared the performances of 13 different types of amino acid descriptors (i.”