PRIMO: an interactive homology modeling pipeline

The development of automated servers to predict the three-dimensional structure of proteins has seen much progress over the years. These servers make calculations simpler, but largely exclude users from the process. In this study, we present the PRotein Interactive MOdeling (PRIMO) pipeline for homology modeling of protein monomers. The pipeline eases the multi-step modeling process, and reduces the workload required by the user, while still allowing engagement from the user during every step. Default parameters are given for each step, which can either be modified or supplemented with additional external input. PRIMO has been designed for users of varying levels of experience with homology modeling. The pipeline incorporates a user-friendly interface that makes it easy to alter parameters used during modeling

The development of computational biology in South Africa: successes achieved and lessons learnt

Bioinformatics is now a critical skill in many research and commercial environments as biological data are increasing in both size and complexity. South African researchers recognized this need in the mid-1990s and responded by working with the government as well as international bodies to develop initiatives to build bioinformatics capacity in the country. Significant injections of support from these bodies provided a springboard for the establishment of computational biology units at multiple universities throughout the country, which took on teaching, basic research and support roles. Several challenges were encountered, for example with unreliability of funding, lack of skills, and lack of infrastructure. However, the bioinformatics community worked together to overcome these, and South Africa is now arguably the leading country in bioinformatics on the African continent. Here we discuss how the discipline developed in the country, highlighting the challenges, successes, and lessons learnt

The global distribution and diversity of protein vaccine candidate antigens in the highly virulent Streptococcus pnuemoniae serotype 1

Serotype 1 is one of the most common causes of pneumococcal disease worldwide. Pneumococcal protein vaccines are currently being developed as an alternate intervention strategy to pneumococcal conjugate vaccines. Pre-requisites for an efficacious pneumococcal protein vaccine are universal presence and minimal variation of the target antigen in the pneumococcal population, and the capability to induce a robust human immune response. We used in silico analysis to assess the prevalence of seven protein vaccine candidates (CbpA, PcpA, PhtD, PspA, SP0148, SP1912, SP2108) among 445 serotype 1 pneumococci from 26 different countries, across four continents. CbpA (76%), PspA (68%), PhtD (28%), PcpA (11%) were not universally encoded in the study population, and would not provide full coverage against serotype 1. PcpA was widely present in the European (82%), but not in the African (2%) population. A multi-valent vaccine incorporating CbpA, PcpA, PhtD and PspA was predicted to provide coverage against 86% of the global population. SP0148, SP1912 and SP2108 were universally encoded and we further assessed their predicted amino acid, antigenic and structural variation. Multiple allelic variants of these proteins were identified, different allelic variants dominated in different continents; the observed variation was predicted to impact the antigenicity and structure of two SP0148 variants, one SP1912 variant and four SP2108 variants, however these variants were each only present in a small fraction of the global population (<2%). The vast majority of the observed variation was predicted to have no impact on the efficaciousness of a protein vaccine incorporating a single variant of SP0148, SP1912 and/or SP2108 from S. pneumoniae TIGR4. Our findings emphasise the importance of taking geographic differences into account when designing global vaccine interventions and support the continued development of SP0148, SP1912 and SP2108 as protein vaccine candidates against this important pneumococcal serotype

The value of spreader grafts in rhinoplasty: a critical review

The value of spreader grafts in rhinoplasty cannot be underestimated. Various studies have demonstrated that they play a valuable role in the restoration of nasal dorsum aesthetics, provide support for the nasal valve and maintain the straightened position of the corrected deviated cartilaginous septal dorsum. However, there is still controversy on the extent of its value in nasal patency. This study reviews the literature and describes the values and limitations of spreader grafts in rhinoplasty and the alternatives to classic spreader grafts

Prediction of HIV-1 virus-host protein interactions using virus and host sequence motifs

<p>Abstract</p> <p>Background</p> <p>Host protein-protein interaction networks are altered by invading virus proteins, which create new interactions, and modify or destroy others. The resulting network topology favors excessive amounts of virus production in a stressed host cell network. Short linear peptide motifs common to both virus and host provide the basis for host network modification.</p> <p>Methods</p> <p>We focused our host-pathogen study on the binding and competing interactions of HIV-1 and human proteins. We showed that peptide motifs conserved across 70% of HIV-1 subtype B and C samples occurred in similar positions on HIV-1 proteins, and we documented protein domains that interact with these conserved motifs. We predicted which human proteins may be targeted by HIV-1 by taking pairs of human proteins that may interact via a motif conserved in HIV-1 and the corresponding interacting protein domain.</p> <p>Results</p> <p>Our predictions were enriched with host proteins known to interact with HIV-1 proteins ENV, NEF, and TAT (p-value < 4.26E-21). Cellular pathways statistically enriched for our predictions include the T cell receptor signaling, natural killer cell mediated cytotoxicity, cell cycle, and apoptosis pathways. Gene Ontology molecular function level 5 categories enriched with both predicted and confirmed HIV-1 targeted proteins included categories associated with phosphorylation events and adenyl ribonucleotide binding.</p> <p>Conclusion</p> <p>A list of host proteins highly enriched with those targeted by HIV-1 proteins can be obtained by searching for host protein motifs along virus protein sequences. The resulting set of host proteins predicted to be targeted by virus proteins will become more accurate with better annotations of motifs and domains. Nevertheless, our study validates the role of linear binding motifs shared by virus and host proteins as an important part of the crosstalk between virus and host.</p

GOBLET: the Global Organisation for Bioinformatics Learning, Education and Training

In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy--paradoxically, many are actually closing "niche" bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all

GOBLET: The Global Organisation for Bioinformatics Learning, Education and Training

In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy—paradoxically, many are actually closing “niche” bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all

Structural similarity-based predictions of protein interactions between HIV-1 and Homo sapiens

Abstract Background In the course of infection, viruses such as HIV-1 must enter a cell, travel to sites where they can hijack host machinery to transcribe their genes and translate their proteins, assemble, and then leave the cell again, all while evading the host immune system. Thus, successful infection depends on the pathogen's ability to manipulate the biological pathways and processes of the organism it infects. Interactions between HIV-encoded and human proteins provide one means by which HIV-1 can connect into cellular pathways to carry out these survival processes. Results We developed and applied a computational approach to predict interactions between HIV and human proteins based on structural similarity of 9 HIV-1 proteins to human proteins having known interactions. Using functional data from RNAi studies as a filter, we generated over 2000 interaction predictions between HIV proteins and 406 unique human proteins. Additional filtering based on Gene Ontology cellular component annotation reduced the number of predictions to 502 interactions involving 137 human proteins. We find numerous known interactions as well as novel interactions showing significant functional relevance based on supporting Gene Ontology and literature evidence. Conclusions Understanding the interplay between HIV-1 and its human host will help in understanding the viral lifecycle and the ways in which this virus is able to manipulate its host. The results shown here provide a potential set of interactions that are amenable to further experimental manipulation as well as potential targets for therapeutic intervention

No evidence for association with APOL1 kidney disease risk alleles and Human African Trypanosomiasis in two Ugandan populations:

Human African trypanosomiasis (HAT) manifests as an acute form caused by Trypanosoma brucei rhodesiense (Tbr) and a chronic form caused by Trypanosoma brucei gambiense (Tbg). Previous studies have suggested a host genetic role in infection outcomes, particularly for APOL1. We have undertaken a candidate gene association studies (CGAS) in a Ugandan Tbr and a Tbg HAT endemic area, to determine whether polymorphisms in IL10, IL8, IL4, HLAG, TNFA, TNX4LB, IL6, IFNG, MIF, APOL1, HLAA, IL1B, IL4R, IL12B, IL12R, HP, HPR, and CFH have a role in HAT