Phenotypic and genotypic predictors forHIV/SIV tropism are available. The genotypic predictors are more rational. However, they are sequence alignment dependent only. Regrettably, non-homologous proteins are found to display common biological functionality. This indicates that sequence-dependent predictors cannot be trusted with appropriate classification of the HIV and SIV isolates, especially if the isolates belong to same tropic group but share divergent sequence alignment. There is therefore need for genotypic predictors that will incorporate embedded intrinsic biological characteristics of the HIV and SIV isolates in the determination of HIV tropism. Secondly, more than 30 positions with at least single mutation outside the V3 domain have been found to influence HIV Tropism. Disappointingly, the available sequence alignment-based HIV genotypic predictors engage only the hyper-variable region (V3) of the HIV gp120. This has resulted in inaccurate classification of HIV and SIV strains. Finally, available HIV genotypic predictors are found to lack the ability to identify and accurately evaluate the sequences of most HIV-1 non B clades, HIV-2 and SIV. Against this background, the ability of the Digital Signal Processing (DSP) Technique called Informational Spectrum Method (ISM), which does not engage sequence similarity but the embedded bio-functionalities of the entire gp120 sequence length to predict HIV and SIV tropism is therefore investigated. 83 isolates of HIV and SIV are subjected to ISM and three other procedures. Results are generated and findings correlated. For isolates, which are analyzable by the four procedures, the results from ISM and three other procedures are found to correlate. Using 50% affinity for the host CD4 as the cut-off, the tropism of the uncategorized isolates are predicted. ISM-based technique is adjudged a better procedure. It analyzes the sequences of all HIV (HIV-1 together with non B, and HIV-2) as well as SIV isolates including those that could not be investigated by other genotypic predictors. It engages the embedded biological characteristics rather than sequence similarity and utilizes the entire HIV gp120 sequence-length instead of V3 domain. This makes ISM-based procedure a better tool for over 180,000 isolates of HIV-1, HIV-2 and SIV in the UNIPROT database. Clinical approaches are unfeasible. This study recommends ISM technique principally for viral tropism prediction as it does not discriminate against HIV/SIVcategories. It suggests that further work be done to determine a suitable cut-off (as in geno2pheno[CORECEPTOR]), and the procedure in combination with other genotypic predictors be engaged in developing an algorithm for determining viral tropism.
| Published in | Computational Biology and Bioinformatics (Volume 3, Issue 2) |
| DOI | 10.11648/j.cbb.20150302.11 |
| Page(s) | 21-30 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
CD4, Charge Rule, Digital Signal Processing, Geno2pheno, Genotypic, HIV/AIDS, HIV Surface Protein, Informational Spectrum Method, Phenotypic, Position-Specific Scoring Matrix
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APA Style
Norbert Nwankwo, Michael Adikwu, Ignatus Okafor. (2015). HIV Tropism Prediction: Digital Signal Processing-Based Bioinformatics Approach is Non-Sequence Alignment Dependent. Computational Biology and Bioinformatics, 3(2), 21-30. https://doi.org/10.11648/j.cbb.20150302.11
ACS Style
Norbert Nwankwo; Michael Adikwu; Ignatus Okafor. HIV Tropism Prediction: Digital Signal Processing-Based Bioinformatics Approach is Non-Sequence Alignment Dependent. Comput. Biol. Bioinform. 2015, 3(2), 21-30. doi: 10.11648/j.cbb.20150302.11
AMA Style
Norbert Nwankwo, Michael Adikwu, Ignatus Okafor. HIV Tropism Prediction: Digital Signal Processing-Based Bioinformatics Approach is Non-Sequence Alignment Dependent. Comput Biol Bioinform. 2015;3(2):21-30. doi: 10.11648/j.cbb.20150302.11
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Download@article{10.11648/j.cbb.20150302.11,
author = {Norbert Nwankwo and Michael Adikwu and Ignatus Okafor},
title = {HIV Tropism Prediction: Digital Signal Processing-Based Bioinformatics Approach is Non-Sequence Alignment Dependent},
journal = {Computational Biology and Bioinformatics},
volume = {3},
number = {2},
pages = {21-30},
doi = {10.11648/j.cbb.20150302.11},
url = {https://doi.org/10.11648/j.cbb.20150302.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cbb.20150302.11},
abstract = {Phenotypic and genotypic predictors forHIV/SIV tropism are available. The genotypic predictors are more rational. However, they are sequence alignment dependent only. Regrettably, non-homologous proteins are found to display common biological functionality. This indicates that sequence-dependent predictors cannot be trusted with appropriate classification of the HIV and SIV isolates, especially if the isolates belong to same tropic group but share divergent sequence alignment. There is therefore need for genotypic predictors that will incorporate embedded intrinsic biological characteristics of the HIV and SIV isolates in the determination of HIV tropism. Secondly, more than 30 positions with at least single mutation outside the V3 domain have been found to influence HIV Tropism. Disappointingly, the available sequence alignment-based HIV genotypic predictors engage only the hyper-variable region (V3) of the HIV gp120. This has resulted in inaccurate classification of HIV and SIV strains. Finally, available HIV genotypic predictors are found to lack the ability to identify and accurately evaluate the sequences of most HIV-1 non B clades, HIV-2 and SIV. Against this background, the ability of the Digital Signal Processing (DSP) Technique called Informational Spectrum Method (ISM), which does not engage sequence similarity but the embedded bio-functionalities of the entire gp120 sequence length to predict HIV and SIV tropism is therefore investigated. 83 isolates of HIV and SIV are subjected to ISM and three other procedures. Results are generated and findings correlated. For isolates, which are analyzable by the four procedures, the results from ISM and three other procedures are found to correlate. Using 50% affinity for the host CD4 as the cut-off, the tropism of the uncategorized isolates are predicted. ISM-based technique is adjudged a better procedure. It analyzes the sequences of all HIV (HIV-1 together with non B, and HIV-2) as well as SIV isolates including those that could not be investigated by other genotypic predictors. It engages the embedded biological characteristics rather than sequence similarity and utilizes the entire HIV gp120 sequence-length instead of V3 domain. This makes ISM-based procedure a better tool for over 180,000 isolates of HIV-1, HIV-2 and SIV in the UNIPROT database. Clinical approaches are unfeasible. This study recommends ISM technique principally for viral tropism prediction as it does not discriminate against HIV/SIVcategories. It suggests that further work be done to determine a suitable cut-off (as in geno2pheno[CORECEPTOR]), and the procedure in combination with other genotypic predictors be engaged in developing an algorithm for determining viral tropism.},
year = {2015}
}
TY - JOUR T1 - HIV Tropism Prediction: Digital Signal Processing-Based Bioinformatics Approach is Non-Sequence Alignment Dependent AU - Norbert Nwankwo AU - Michael Adikwu AU - Ignatus Okafor Y1 - 2015/03/28 PY - 2015 N1 - https://doi.org/10.11648/j.cbb.20150302.11 DO - 10.11648/j.cbb.20150302.11 T2 - Computational Biology and Bioinformatics JF - Computational Biology and Bioinformatics JO - Computational Biology and Bioinformatics SP - 21 EP - 30 PB - Science Publishing Group SN - 2330-8281 UR - https://doi.org/10.11648/j.cbb.20150302.11 AB - Phenotypic and genotypic predictors forHIV/SIV tropism are available. The genotypic predictors are more rational. However, they are sequence alignment dependent only. Regrettably, non-homologous proteins are found to display common biological functionality. This indicates that sequence-dependent predictors cannot be trusted with appropriate classification of the HIV and SIV isolates, especially if the isolates belong to same tropic group but share divergent sequence alignment. There is therefore need for genotypic predictors that will incorporate embedded intrinsic biological characteristics of the HIV and SIV isolates in the determination of HIV tropism. Secondly, more than 30 positions with at least single mutation outside the V3 domain have been found to influence HIV Tropism. Disappointingly, the available sequence alignment-based HIV genotypic predictors engage only the hyper-variable region (V3) of the HIV gp120. This has resulted in inaccurate classification of HIV and SIV strains. Finally, available HIV genotypic predictors are found to lack the ability to identify and accurately evaluate the sequences of most HIV-1 non B clades, HIV-2 and SIV. Against this background, the ability of the Digital Signal Processing (DSP) Technique called Informational Spectrum Method (ISM), which does not engage sequence similarity but the embedded bio-functionalities of the entire gp120 sequence length to predict HIV and SIV tropism is therefore investigated. 83 isolates of HIV and SIV are subjected to ISM and three other procedures. Results are generated and findings correlated. For isolates, which are analyzable by the four procedures, the results from ISM and three other procedures are found to correlate. Using 50% affinity for the host CD4 as the cut-off, the tropism of the uncategorized isolates are predicted. ISM-based technique is adjudged a better procedure. It analyzes the sequences of all HIV (HIV-1 together with non B, and HIV-2) as well as SIV isolates including those that could not be investigated by other genotypic predictors. It engages the embedded biological characteristics rather than sequence similarity and utilizes the entire HIV gp120 sequence-length instead of V3 domain. This makes ISM-based procedure a better tool for over 180,000 isolates of HIV-1, HIV-2 and SIV in the UNIPROT database. Clinical approaches are unfeasible. This study recommends ISM technique principally for viral tropism prediction as it does not discriminate against HIV/SIVcategories. It suggests that further work be done to determine a suitable cut-off (as in geno2pheno[CORECEPTOR]), and the procedure in combination with other genotypic predictors be engaged in developing an algorithm for determining viral tropism. VL - 3 IS - 2 ER -
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