8
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Inter-Species/Host-Parasite Protein Interaction Predictions Reviewed

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Host-parasite protein interactions (HPPI) are those interactions occurring between a parasite and its host. Host-parasite protein interaction enhances the understanding of how parasite can infect its host. The interaction plays an important role in initiating infections, although it is not all host-parasite interactions that result in infection. Identifying the protein-protein interactions (PPIs) that allow a parasite to infect its host has a lot do in discovering possible drug targets. Such PPIs, when altered, would prevent the host from being infected by the parasite and in some cases, result in the parasite inability to complete specific stages of its life cycle and invariably lead to the death of such parasite. It therefore becomes important to understand the workings of host-parasite interactions which are the major causes of most infectious diseases.

          Objective

          Many studies have been conducted in literature to predict HPPI, mostly using computational methods with few experimental methods. Computational method has proved to be faster and more efficient in manipulating and analyzing real life data. This study looks at various computational methods used in literature for host-parasite/inter-species protein-protein interaction predictions with the hope of getting a better insight into computational methods used and identify whether machine learning approaches have been extensively used for the same purpose.

          Methods

          The various methods involved in host-parasite protein interactions were reviewed with their individual strengths. Tabulations of studies that carried out host-parasite/inter-species protein interaction predictions were performed, analyzing their predictive methods, filters used, potential protein-protein interactions discovered in those studies and various validation measurements used as the case may be. The commonly used measurement indexes for such studies were highlighted displaying the various formulas. Finally, future prospects of studies specific to human-plasmodium falciparum PPI predictions were proposed.

          Result

          We discovered that quite a few studies reviewed implemented machine learning approach for HPPI predictions when compared with methods such as sequence homology search and protein structure and domain-motif. The key challenge well noted in HPPI predictions is getting relevant information.

          Conclusion

          This review presents useful knowledge and future directions on the subject matter.

          Related collections

          Most cited references 47

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Evaluation of time profile reconstruction from complex two-color microarray designs

          Background As an alternative to the frequently used "reference design" for two-channel microarrays, other designs have been proposed. These designs have been shown to be more profitable from a theoretical point of view (more replicates of the conditions of interest for the same number of arrays). However, the interpretation of the measurements is less straightforward and a reconstruction method is needed to convert the observed ratios into the genuine profile of interest (e.g. a time profile). The potential advantages of using these alternative designs thus largely depend on the success of the profile reconstruction. Therefore, we compared to what extent different linear models agree with each other in reconstructing expression ratios and corresponding time profiles from a complex design. Results On average the correlation between the estimated ratios was high, and all methods agreed with each other in predicting the same profile, especially for genes of which the expression profile showed a large variance across the different time points. Assessing the similarity in profile shape, it appears that, the more similar the underlying principles of the methods (model and input data), the more similar their results. Methods with a dye effect seemed more robust against array failure. The influence of a different normalization was not drastic and independent of the method used. Conclusion Including a dye effect such as in the methods lmbr_dye, anovaFix and anovaMix compensates for residual dye related inconsistencies in the data and renders the results more robust against array failure. Including random effects requires more parameters to be estimated and is only advised when a design is used with a sufficient number of replicates. Because of this, we believe lmbr_dye, anovaFix and anovaMix are most appropriate for practical use.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Genetic diversity among Plasmodium falciparum field isolates in Pakistan measured with PCR genotyping of the merozoite surface protein 1 and 2

            Background The genetic diversity of Plasmodium falciparum has been extensively studied in various parts of the world. However, limited data are available from Pakistan. This study aimed to establish molecular characterization of P. falciparum field isolates in Pakistan measured with two highly polymorphic genetic markers, i.e. the merozoite surface protein 1 (msp-1)and 2 (msp-2). Methods Between October 2005 and October 2007, 244 blood samples from patients with symptomatic blood-slide confirmed P. falciparum mono-infections attending the Aga Khan University Hospital, Karachi, or its collection units located in Sindh and Baluchistan provinces, Pakistan were collected. The genetic diversity of P. falciparum was analysed by length polymorphism following gel electrophoresis of DNA products from nested polymerase chain reactions (PCR) targeting block 2 of msp-1 and block 3 of msp-2, including their respective allelic families KI, MAD 20, RO33, and FC27, 3D7/IC. Results A total of 238/244 (98%) patients had a positive PCR outcome in at least one genetic marker; the remaining six were excluded from analysis. A majority of patients had monoclonal infections. Only 56/231 (24%) and 51/236 (22%) carried multiple P. falciparum genotypes in msp-1 and msp-2, respectively. The estimated total number of genotypes was 25 msp-1 (12 KI; 8 MAD20; 5 RO33) and 33 msp-2 (14 FC27; 19 3D7/IC). Conclusions This is the first report on molecular characterization of P. falciparum field isolates in Pakistan with regards to multiplicity of infection. The genetic diversity and allelic distribution found in this study is similar to previous reports from India and Southeast Asian countries with low malaria endemicity.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Protein-Protein Interaction Detection: Methods and Analysis

               V Rao,  K Srinivas,  G. Sujini (2014)
              Protein-protein interaction plays key role in predicting the protein function of target protein and drug ability of molecules. The majority of genes and proteins realize resulting phenotype functions as a set of interactions. The in vitro and in vivo methods like affinity purification, Y2H (yeast 2 hybrid), TAP (tandem affinity purification), and so forth have their own limitations like cost, time, and so forth, and the resultant data sets are noisy and have more false positives to annotate the function of drug molecules. Thus, in silico methods which include sequence-based approaches, structure-based approaches, chromosome proximity, gene fusion, in silico 2 hybrid, phylogenetic tree, phylogenetic profile, and gene expression-based approaches were developed. Elucidation of protein interaction networks also contributes greatly to the analysis of signal transduction pathways. Recent developments have also led to the construction of networks having all the protein-protein interactions using computational methods for signaling pathways and protein complex identification in specific diseases.
                Bookmark

                Author and article information

                Journal
                Curr Bioinform
                Curr Bioinform
                CBIO
                Current Bioinformatics
                Bentham Science Publishers
                1574-8936
                2212-392X
                August 2018
                August 2018
                : 13
                : 4
                : 396-406
                Affiliations
                [1 ]Department of Computer Science, The Federal Polytechnic, Ilaro, Nigeria;
                [2 ]Department of Computer & Information Sciences, Covenant University, Ota, Nigeria and
                [3 ]Covenant University Bioinformatics Research (CUBRe), Ota, Nigeria
                Author notes
                [* ]Address correspondence to this author at the Department of Computer and Information Sciences, College of Science and Technology, Covenant University, Ota, Nigeria; Tel: +234 803 575 5778;, E-mail: ola.oyelade@ 123456covenantuniversity.edu.ng
                [#]

                Joint Authors

                Article
                CBIO-13-396
                10.2174/1574893613666180108155851
                6691774
                © 2018 Bentham Science Publishers

                This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) ( https://creativecommons.org/licenses/by-nc/4.0/legalcode), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

                Categories
                Article

                Comments

                Comment on this article