Title |
Benchmarking of protein descriptor sets in proteochemometric modeling (part 2): modeling performance of 13 amino acid descriptor sets
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Published in |
Journal of Cheminformatics, September 2013
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DOI | 10.1186/1758-2946-5-42 |
Pubmed ID | |
Authors |
Gerard JP van Westen, Remco F Swier, Isidro Cortes-Ciriano, Jörg K Wegner, John P Overington, Adriaan P IJzerman, Herman WT van Vlijmen, Andreas Bender |
Abstract |
While a large body of work exists on comparing and benchmarking descriptors of molecular structures, a similar comparison of protein descriptor sets is lacking. Hence, in the current work a total of 13 amino acid descriptor sets have been benchmarked with respect to their ability of establishing bioactivity models. The descriptor sets included in the study are Z-scales (3 variants), VHSE, T-scales, ST-scales, MS-WHIM, FASGAI, BLOSUM, a novel protein descriptor set (termed ProtFP (4 variants)), and in addition we created and benchmarked three pairs of descriptor combinations. Prediction performance was evaluated in seven structure-activity benchmarks which comprise Angiotensin Converting Enzyme (ACE) dipeptidic inhibitor data, and three proteochemometric data sets, namely (1) GPCR ligands modeled against a GPCR panel, (2) enzyme inhibitors (NNRTIs) with associated bioactivities against a set of HIV enzyme mutants, and (3) enzyme inhibitors (PIs) with associated bioactivities on a large set of HIV enzyme mutants. |
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Demographic breakdown
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Mendeley readers
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India | 2 | 1% |
Bulgaria | 1 | <1% |
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Iran, Islamic Republic of | 1 | <1% |
Japan | 1 | <1% |
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Researcher | 39 | 23% |
Student > Ph. D. Student | 26 | 15% |
Student > Master | 23 | 14% |
Student > Bachelor | 17 | 10% |
Student > Doctoral Student | 9 | 5% |
Other | 26 | 15% |
Unknown | 28 | 17% |
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Computer Science | 26 | 15% |
Biochemistry, Genetics and Molecular Biology | 25 | 15% |
Agricultural and Biological Sciences | 19 | 11% |
Pharmacology, Toxicology and Pharmaceutical Science | 13 | 8% |
Other | 17 | 10% |
Unknown | 29 | 17% |