Cargando…
Prediction of protein-mannose binding sites using random forest
Mannose is an abundant cell surface monosaccharide and has an important role in many biochemical processes. It binds to a great diversity of receptor proteins. In this study we have employed Random Forest for prediction of mannose binding sites. Mannosebinding site is taken to be a sphere around the...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Biomedical Informatics
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3530872/ https://www.ncbi.nlm.nih.gov/pubmed/23275720 http://dx.doi.org/10.6026/97320630081202 |
_version_ | 1782254074995933184 |
---|---|
author | Khare, Harshvardan Ratnaparkhi, Vivek Chavan, Sonali Jayraman, Valadi |
author_facet | Khare, Harshvardan Ratnaparkhi, Vivek Chavan, Sonali Jayraman, Valadi |
author_sort | Khare, Harshvardan |
collection | PubMed |
description | Mannose is an abundant cell surface monosaccharide and has an important role in many biochemical processes. It binds to a great diversity of receptor proteins. In this study we have employed Random Forest for prediction of mannose binding sites. Mannosebinding site is taken to be a sphere around the centroid of the ligand and the sphere is subdivided into different layers and atom wise and residue wise features were extracted for each layer. The method achieves 95.59 % of accuracy using Random Forest with 10 fold cross validation. Prediction of mannose binding site analysis will be quite useful in drug design. |
format | Online Article Text |
id | pubmed-3530872 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Biomedical Informatics |
record_format | MEDLINE/PubMed |
spelling | pubmed-35308722012-12-28 Prediction of protein-mannose binding sites using random forest Khare, Harshvardan Ratnaparkhi, Vivek Chavan, Sonali Jayraman, Valadi Bioinformation Hypothesis Mannose is an abundant cell surface monosaccharide and has an important role in many biochemical processes. It binds to a great diversity of receptor proteins. In this study we have employed Random Forest for prediction of mannose binding sites. Mannosebinding site is taken to be a sphere around the centroid of the ligand and the sphere is subdivided into different layers and atom wise and residue wise features were extracted for each layer. The method achieves 95.59 % of accuracy using Random Forest with 10 fold cross validation. Prediction of mannose binding site analysis will be quite useful in drug design. Biomedical Informatics 2012-12-08 /pmc/articles/PMC3530872/ /pubmed/23275720 http://dx.doi.org/10.6026/97320630081202 Text en © 2012 Biomedical Informatics This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited. |
spellingShingle | Hypothesis Khare, Harshvardan Ratnaparkhi, Vivek Chavan, Sonali Jayraman, Valadi Prediction of protein-mannose binding sites using random forest |
title | Prediction of protein-mannose binding sites using random forest |
title_full | Prediction of protein-mannose binding sites using random forest |
title_fullStr | Prediction of protein-mannose binding sites using random forest |
title_full_unstemmed | Prediction of protein-mannose binding sites using random forest |
title_short | Prediction of protein-mannose binding sites using random forest |
title_sort | prediction of protein-mannose binding sites using random forest |
topic | Hypothesis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3530872/ https://www.ncbi.nlm.nih.gov/pubmed/23275720 http://dx.doi.org/10.6026/97320630081202 |
work_keys_str_mv | AT khareharshvardan predictionofproteinmannosebindingsitesusingrandomforest AT ratnaparkhivivek predictionofproteinmannosebindingsitesusingrandomforest AT chavansonali predictionofproteinmannosebindingsitesusingrandomforest AT jayramanvaladi predictionofproteinmannosebindingsitesusingrandomforest |