Haiyun Lu, Shamima Rashid, Hao Li, W. Leow, Y. Liou
Studies of interactions between protein domains and ligands are important in many aspects such as cellular signaling and regulation. In this work, we applied a three-stage knowledge-guided approach of docking flexible peptide ligands to SH2 domains. The first stage of the approach search for binding pockets of SH2 domain proteins and binding motifs of peptide ligands based on known features. The knowledge of the binding sites are used in the second stage as binding constraints to align ligand's peptide backbone to the SH2 domain. The backbone-aligned ligands produced serve as good starting points to the third stage which uses a Monte Carlo method to perform the flexible docking. The experimental results show that the backbone alignment method at the second stage produces good backbone conformations which are close to the conformation in complex. The binding site information is well utilized to provide a better starting point to the next docking stage. The subsequent docking is successful or partially successful in 5 of 7 test cases. The performance is better than that of general docking methods. The presented approach can also be applied to other well characterized protein domains which bind ligands in two or more binding grooves.
{"title":"Knowledge-Guided Docking of Flexible Ligands to SH2 Domain Proteins","authors":"Haiyun Lu, Shamima Rashid, Hao Li, W. Leow, Y. Liou","doi":"10.1109/BIBE.2010.37","DOIUrl":"https://doi.org/10.1109/BIBE.2010.37","url":null,"abstract":"Studies of interactions between protein domains and ligands are important in many aspects such as cellular signaling and regulation. In this work, we applied a three-stage knowledge-guided approach of docking flexible peptide ligands to SH2 domains. The first stage of the approach search for binding pockets of SH2 domain proteins and binding motifs of peptide ligands based on known features. The knowledge of the binding sites are used in the second stage as binding constraints to align ligand's peptide backbone to the SH2 domain. The backbone-aligned ligands produced serve as good starting points to the third stage which uses a Monte Carlo method to perform the flexible docking. The experimental results show that the backbone alignment method at the second stage produces good backbone conformations which are close to the conformation in complex. The binding site information is well utilized to provide a better starting point to the next docking stage. The subsequent docking is successful or partially successful in 5 of 7 test cases. The performance is better than that of general docking methods. The presented approach can also be applied to other well characterized protein domains which bind ligands in two or more binding grooves.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130907468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-31DOI: 10.1007/978-3-642-15120-0_12
Tantan Liu, Fan Wang, G. Agrawal
{"title":"Instance Discovery and Schema Matching with Applications to Biological Deep Web Data Integration","authors":"Tantan Liu, Fan Wang, G. Agrawal","doi":"10.1007/978-3-642-15120-0_12","DOIUrl":"https://doi.org/10.1007/978-3-642-15120-0_12","url":null,"abstract":"","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133009560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nowadays, a large part of the online biological data resides in the deep web. Lately, there have been several efforts focusing on integrating and providing search functionality for biological deep web data sources. Such systems often require data access involving a large number of remote data sources and the use of various communication links. Both the servers and networking links are vulnerable to congestion and failures. This can lead to an unpredictable unavailability or inaccessibility, which can disrupt access to the information. In this paper, we propose a solution to maintain query processing capability of an integrated biological deep web search system in the presence of unavailable or inaccessible data sources. Our solution involves dynamically adapting query processing when unexpected data source unavailability or inaccessibility is detected. We exploit the data redundancy that is found across biological deep web data sources. We incrementally generate a partial new query plan by bringing in new data sources that were not in the original query plan to replace the subplan that became inaccessible.
{"title":"A Self-Healing Approach for a Domain-Specific Deep Web Search Tool","authors":"Fan Wang, G. Agrawal","doi":"10.1109/BIBE.2010.13","DOIUrl":"https://doi.org/10.1109/BIBE.2010.13","url":null,"abstract":"Nowadays, a large part of the online biological data resides in the deep web. Lately, there have been several efforts focusing on integrating and providing search functionality for biological deep web data sources. Such systems often require data access involving a large number of remote data sources and the use of various communication links. Both the servers and networking links are vulnerable to congestion and failures. This can lead to an unpredictable unavailability or inaccessibility, which can disrupt access to the information. In this paper, we propose a solution to maintain query processing capability of an integrated biological deep web search system in the presence of unavailable or inaccessible data sources. Our solution involves dynamically adapting query processing when unexpected data source unavailability or inaccessibility is detected. We exploit the data redundancy that is found across biological deep web data sources. We incrementally generate a partial new query plan by bringing in new data sources that were not in the original query plan to replace the subplan that became inaccessible.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123621739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study probes the effects of ethanol on the molecular mechanisms regulating the differentiation of embryonic stem (ES) cells towards neuroectodermal state, which may be responsible for the abnormalities observed in fetal alcohol spectrum disorders (FASD). The effects of ethanol on the early phase of ES cell differentiation have not been well characterized. Here, we investigate the stage-specific action of ethanol during early embryogenesis by an integrated experimental and computational modeling approach. Our experimental system consists of mouse ES cells and directed differentiation to neuroectodermal fate in the presence of ethanol. Experimental single-cell multiplex data on the expression of the ES core transcription factors (TFs), Sox2, Oct4 and Nanog were obtained simultaneously by multicolor flow cytometry in live cells. Singlecell flow cytometric data were analyzed by ARACNE probabilistic modeling to construct transcriptional regulatory networks and quantify the TFs interactions in a pairwisemanner. Our analysis indicates that during differentiation towards neuroectodermal fate ethanol accelerates (i) the decline of the expression levels of Sox2 and Nanog, and (ii) the decreasing strength of the correlative interactions between the core TFs which is also reflected in (iii) an advanced differentiation phenotype.
{"title":"Ethanol Effects on Transcription Factor Network Regulating Stem Cell Differentiation","authors":"R. Vadigepalli, Joshua Ogony, H. Anni","doi":"10.1109/BIBE.2010.62","DOIUrl":"https://doi.org/10.1109/BIBE.2010.62","url":null,"abstract":"This study probes the effects of ethanol on the molecular mechanisms regulating the differentiation of embryonic stem (ES) cells towards neuroectodermal state, which may be responsible for the abnormalities observed in fetal alcohol spectrum disorders (FASD). The effects of ethanol on the early phase of ES cell differentiation have not been well characterized. Here, we investigate the stage-specific action of ethanol during early embryogenesis by an integrated experimental and computational modeling approach. Our experimental system consists of mouse ES cells and directed differentiation to neuroectodermal fate in the presence of ethanol. Experimental single-cell multiplex data on the expression of the ES core transcription factors (TFs), Sox2, Oct4 and Nanog were obtained simultaneously by multicolor flow cytometry in live cells. Singlecell flow cytometric data were analyzed by ARACNE probabilistic modeling to construct transcriptional regulatory networks and quantify the TFs interactions in a pairwisemanner. Our analysis indicates that during differentiation towards neuroectodermal fate ethanol accelerates (i) the decline of the expression levels of Sox2 and Nanog, and (ii) the decreasing strength of the correlative interactions between the core TFs which is also reflected in (iii) an advanced differentiation phenotype.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"12 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123665500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
— Modular software design is a technique that increase reusability and portability of software composed from separate parts, called modules. We have designed and developed a reusable integrated software solution for robotic prostate brachytherapy procedure. The application is capable of concurrent handling of all aspects of the image-guided brachytherapy procedure: ultrasound image acquisition, anatomic delineation, target modeling, dosimetry planning and analysis, seed delivery, and visualization of all surgerical steps involved in the procedure. Based on force feedback and visual feedback, the control module of the application is capable of controlling the robotic system (i.e. motions of the ultrasound probe and the needles), supervising the flow of the procedure via built-in strategies for emergency handling and recovery, collision avoidance, manual takeover (if necessary), needle tracking and real-time dose updates. The implementation of the developed software solution to the two brachytherapy robotic systems has been presented.
{"title":"Modular Software Design for Brachytherapy Image-Guided Robotic Systems","authors":"Ivan Buzurovic, T. Podder, L. Fu, Yan Yu","doi":"10.1109/BIBE.2010.40","DOIUrl":"https://doi.org/10.1109/BIBE.2010.40","url":null,"abstract":"— Modular software design is a technique that increase reusability and portability of software composed from separate parts, called modules. We have designed and developed a reusable integrated software solution for robotic prostate brachytherapy procedure. The application is capable of concurrent handling of all aspects of the image-guided brachytherapy procedure: ultrasound image acquisition, anatomic delineation, target modeling, dosimetry planning and analysis, seed delivery, and visualization of all surgerical steps involved in the procedure. Based on force feedback and visual feedback, the control module of the application is capable of controlling the robotic system (i.e. motions of the ultrasound probe and the needles), supervising the flow of the procedure via built-in strategies for emergency handling and recovery, collision avoidance, manual takeover (if necessary), needle tracking and real-time dose updates. The implementation of the developed software solution to the two brachytherapy robotic systems has been presented.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127410511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Spectral alignment, which studies the matching of ion peaks between the investigated spectrum and theoretical spectrum of peptide in the peptide database, is a very useful topic in computational proteomics. So far, the efficient, accurate and practical spectral alignment algorithm is still urgently needed due to its important application in the PTM unrestrictive peptide identification. In this paper, a multi-stage spectral alignment algorithm called MS-SA is proposed with the following two features: (a) it provided four different levels of alignment aims according to the alignment quality which can be specified by users, (b) it provided the capability of analyzing the detail modification types and locations for spectrum with multiple PTM sites. Therefore, MS-SA is of high practicality and can be applied to different specific applications such as being a filter in the large-scale database searching, a tool for detail modification types and locations analysis in small-scale spectral alignment and so on. A large number of experiments on real MS/MS data have been done for testing the performance of MS-SA. Also, the results of MS-SA are compared with those of same type of algorithms such as SA and SPC. The results show that MS-SA possesses strong practicality and outperforms the SA and SPC algorithms on several aspects.
{"title":"A Multi-stage Spectral Alignment Strategy for Unrestrictive PTM Peptide Identification","authors":"Changyong Yu, Guoren Wang, Yuhai Zhao, Keming Mao","doi":"10.1109/BIBE.2010.11","DOIUrl":"https://doi.org/10.1109/BIBE.2010.11","url":null,"abstract":"Spectral alignment, which studies the matching of ion peaks between the investigated spectrum and theoretical spectrum of peptide in the peptide database, is a very useful topic in computational proteomics. So far, the efficient, accurate and practical spectral alignment algorithm is still urgently needed due to its important application in the PTM unrestrictive peptide identification. In this paper, a multi-stage spectral alignment algorithm called MS-SA is proposed with the following two features: (a) it provided four different levels of alignment aims according to the alignment quality which can be specified by users, (b) it provided the capability of analyzing the detail modification types and locations for spectrum with multiple PTM sites. Therefore, MS-SA is of high practicality and can be applied to different specific applications such as being a filter in the large-scale database searching, a tool for detail modification types and locations analysis in small-scale spectral alignment and so on. A large number of experiments on real MS/MS data have been done for testing the performance of MS-SA. Also, the results of MS-SA are compared with those of same type of algorithms such as SA and SPC. The results show that MS-SA possesses strong practicality and outperforms the SA and SPC algorithms on several aspects.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131740735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As a progressive, degenerative disease, ataxia telangiectasia (A-T) is caused by a gene mutation (ATM) and is a predisposition to cancer. Understanding the impaired signaling networks caused by ATM will help minimizing the damage and finding effective therapies. The goal of this work is to investigate the dynamic change of ATM-dependent signaling pathways under the treatment of different radiation dosages. A reverse-phase protein microarray (RPPM) in conjunction with quantum dots nano-crystal technology is used for the quantitative measurement. To discover the proteomic pathways affected in ATM cells, a new hill climbing algorithm is developed based on mutual information, the classical hill-climbing method, and the optimization of the local structure. More trusted biology networks are thus defined by the new approach. The study was carried out at different time points under different dosages for cell lines with and without ATM mutation. To validate the performance of the proposed algorithm, comparison experiments were also implemented using public networks.
{"title":"Learning Proteomic Network Structure by a New Hill Climbing Algorithm","authors":"Dongchul Kim, Jean X. Gao, Chin-Rang Yang","doi":"10.1109/BIBE.2010.38","DOIUrl":"https://doi.org/10.1109/BIBE.2010.38","url":null,"abstract":"As a progressive, degenerative disease, ataxia telangiectasia (A-T) is caused by a gene mutation (ATM) and is a predisposition to cancer. Understanding the impaired signaling networks caused by ATM will help minimizing the damage and finding effective therapies. The goal of this work is to investigate the dynamic change of ATM-dependent signaling pathways under the treatment of different radiation dosages. A reverse-phase protein microarray (RPPM) in conjunction with quantum dots nano-crystal technology is used for the quantitative measurement. To discover the proteomic pathways affected in ATM cells, a new hill climbing algorithm is developed based on mutual information, the classical hill-climbing method, and the optimization of the local structure. More trusted biology networks are thus defined by the new approach. The study was carried out at different time points under different dosages for cell lines with and without ATM mutation. To validate the performance of the proposed algorithm, comparison experiments were also implemented using public networks.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134546801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lin Li, J. Wang, Dheeraj Chahal, M. Eckert, Carl Lozar
In this study, we present a systematic method for early detection of mild cognitive impairment (MCI) from magnetic resonance images (MRI) using image differences and clinical features. Early detection of MCI has pivotal importance to delay or prevent the onset of Alzheimer’s disease (AD). Subjects were selected from the Open Access Series of Imaging Studies (OASIS)database and included 89 MCI subjects and 80 controls. T1 weighted MRI scans were analyzed to identify their voxel-by-voxel differences in gray matter (GM) intensity between MCI group and control group. Based on the differences, a threshold-based unseeded region growing algorithm was designed to determine multiple regions which atrophy is characteristic of MCI. A feature ranking method was then adopted to select a small number of regions that presented relatively more pronounced atrophy. Next, support vector machine (SVM) based classification was applied by using the clinical features of subjects and the features of selected regions. Our method was tested by leave-one-out cross-validation and it demonstrated high classification accuracy (90%).
{"title":"Detection of Mild Cognitive Impairment Using Image Differences and Clinical Features","authors":"Lin Li, J. Wang, Dheeraj Chahal, M. Eckert, Carl Lozar","doi":"10.1109/BIBE.2010.26","DOIUrl":"https://doi.org/10.1109/BIBE.2010.26","url":null,"abstract":"In this study, we present a systematic method for early detection of mild cognitive impairment (MCI) from magnetic resonance images (MRI) using image differences and clinical features. Early detection of MCI has pivotal importance to delay or prevent the onset of Alzheimer’s disease (AD). Subjects were selected from the Open Access Series of Imaging Studies (OASIS)database and included 89 MCI subjects and 80 controls. T1 weighted MRI scans were analyzed to identify their voxel-by-voxel differences in gray matter (GM) intensity between MCI group and control group. Based on the differences, a threshold-based unseeded region growing algorithm was designed to determine multiple regions which atrophy is characteristic of MCI. A feature ranking method was then adopted to select a small number of regions that presented relatively more pronounced atrophy. Next, support vector machine (SVM) based classification was applied by using the clinical features of subjects and the features of selected regions. Our method was tested by leave-one-out cross-validation and it demonstrated high classification accuracy (90%).","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114182918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jiang Li, A. Vadlamudi, Shao-Hui Chuang, Xiaoyan Sun, Bo Sun, F. McKenzie, L. Cazares, J. Nyalwidhe, D. Troyer, O. Semmes
We present a three-step method to predict Prostate cancer (PCa) regions on biopsy tissue samples based on high confidence, low resolution PCa regions marked by a pathologist. First, we apply a texture analysis technique on a high magnification optical image to predict PCa regions on an adjacent tissue slice. Second, we design a prediction model for the same purpose using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) tissue imaging data from the adjacent slice. Finally, we fuse those two results to obtain the PCa regions that will assist MALDI imaging biomarker identification. Experiment results show that the texture analysis based prediction is sensitive (sen. 87.45%) but not specific (spe. 75%), and the prediction based on the MALDI spectra data is specific (spe. 100%) but less sensitive (sen. 50.98%). By combining those two results, a much better prediction for PCa regions on the adjacent slice can be achieved (sen. 80.39%, spe. 93.09%).
{"title":"Combining Prostate Cancer Region Predictions from MALDI Spectra Processing and Texture Analysis","authors":"Jiang Li, A. Vadlamudi, Shao-Hui Chuang, Xiaoyan Sun, Bo Sun, F. McKenzie, L. Cazares, J. Nyalwidhe, D. Troyer, O. Semmes","doi":"10.1109/BIBE.2010.20","DOIUrl":"https://doi.org/10.1109/BIBE.2010.20","url":null,"abstract":"We present a three-step method to predict Prostate cancer (PCa) regions on biopsy tissue samples based on high confidence, low resolution PCa regions marked by a pathologist. First, we apply a texture analysis technique on a high magnification optical image to predict PCa regions on an adjacent tissue slice. Second, we design a prediction model for the same purpose using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) tissue imaging data from the adjacent slice. Finally, we fuse those two results to obtain the PCa regions that will assist MALDI imaging biomarker identification. Experiment results show that the texture analysis based prediction is sensitive (sen. 87.45%) but not specific (spe. 75%), and the prediction based on the MALDI spectra data is specific (spe. 100%) but less sensitive (sen. 50.98%). By combining those two results, a much better prediction for PCa regions on the adjacent slice can be achieved (sen. 80.39%, spe. 93.09%).","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122164392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Protein residues which contribute to bio-recognition and binding interaction between HIV Surface protein also called Glycoprotein120 (gp120) and Cluster of Differentiation4 (CD4) have been identified. However, this was with limited number of isolates. Notwithstanding, the particular HIV isolate that harbors the gp120 with the greatest binding force to the CD4 has not been investigated. In this paper, protein sequences of gp120 from 43 HIV-1 isolates, 5 isolates each from the HIV-2 and SIV as well as the CD4 of 25 HIV host organisms were analyzed using Resonant Recognition Method (RMM). The results re-confirmed that protein sequences of the HIV and CD4 share common spectral features in relation to bio-recognition and binding. From the large dataset of the HIV and SIV isolates used, MFA group M subtype B (HIV-1) isolate was found to have the greatest affinity for the CD4. Furthermore, the CD4 of the human and chimpanzee were established to possess about same level of binding force to the HIV gp120. Also the CD4 of other species offered more attractive force to another protein in such a manner that the approach taken in this study has also shown to be a useful and reliable tool for clear categorization of species. Finally, clinically experimented results were found to correlate with the computationally obtained results as the gp120 of the HIV-2 and SIV which were recognized to circumvent the CD4 during infection were found to have low peak amplitude. This low peak amplitude observed in the HIV-2 and SIV implies that they have weak affinity or attraction for the host CD4.
{"title":"Assessment of the Binding Characteristics of Human Immunodeficiency Virus Type 1 Glycoprotein120 and Host Cluster of Differentiation4 Using Digital Signal Processing","authors":"N. Nwankwo, H. Seker","doi":"10.1109/BIBE.2010.57","DOIUrl":"https://doi.org/10.1109/BIBE.2010.57","url":null,"abstract":"Protein residues which contribute to bio-recognition and binding interaction between HIV Surface protein also called Glycoprotein120 (gp120) and Cluster of Differentiation4 (CD4) have been identified. However, this was with limited number of isolates. Notwithstanding, the particular HIV isolate that harbors the gp120 with the greatest binding force to the CD4 has not been investigated. In this paper, protein sequences of gp120 from 43 HIV-1 isolates, 5 isolates each from the HIV-2 and SIV as well as the CD4 of 25 HIV host organisms were analyzed using Resonant Recognition Method (RMM). The results re-confirmed that protein sequences of the HIV and CD4 share common spectral features in relation to bio-recognition and binding. From the large dataset of the HIV and SIV isolates used, MFA group M subtype B (HIV-1) isolate was found to have the greatest affinity for the CD4. Furthermore, the CD4 of the human and chimpanzee were established to possess about same level of binding force to the HIV gp120. Also the CD4 of other species offered more attractive force to another protein in such a manner that the approach taken in this study has also shown to be a useful and reliable tool for clear categorization of species. Finally, clinically experimented results were found to correlate with the computationally obtained results as the gp120 of the HIV-2 and SIV which were recognized to circumvent the CD4 during infection were found to have low peak amplitude. This low peak amplitude observed in the HIV-2 and SIV implies that they have weak affinity or attraction for the host CD4.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114081860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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