81 research outputs found
Aminoacyl tRNA synthetases as malarial drug targets: a comparative bioinformatics study
Treatment of parasitic diseases has been challenging due to evolution of drug resistant parasites, and thus there is need to identify new class of drugs and drug targets. Protein translation is important for survival of malarial parasite, Plasmodium, and the pathway is present in all of its life cycle stages. Aminoacyl tRNA synthetases are primary enzymes in protein translation as they catalyse amino acid addition to the cognate tRNA. This study sought to understand differences between Plasmodium and human aminoacyl tRNA synthetases through bioinformatics analysis
Modulation of human Hsp90α conformational dynamics by allosteric ligand interaction at the c-terminal domain:
Recent years have seen heat shock protein 90 kDa (Hsp90) attract significant interest as a viable drug target, particularly for cancer. To date, designed inhibitors that target the ATPase domain demonstrate potent anti-proliferative effects, but have failed clinical trials due to high levels of associated toxicity. To circumvent this, the focus has shifted away from the ATPase domain. One option involves modulation of the protein through allosteric activation/inhibition. Here, we propose a novel approach: we use previously obtained information via residue perturbation scanning coupled with dynamic residue network analysis to identify allosteric drug targeting sites for inhibitor docking
Improving fold resistance prediction of HIV-1 against protease and reverse transcriptase inhibitors using artificial neural networks:
Drug resistance in HIV treatment is still a worldwide problem. Predicting resistance to antiretrovirals (ARVs) before starting any treatment is important. Prediction accuracy is essential, as low-accuracy predictions increase the risk of prescribing sub-optimal drug regimens leading to patients developing resistance sooner. Artificial Neural Networks (ANNs) are a powerful tool that would be able to assist in drug resistance prediction. In this study, we constrained the dataset to subtype B, sacrificing generalizability for a higher predictive performance, and demonstrated that the predictive quality of the ANN regression models have definite improvement for most ARVs
How to establish a bioinformatics postgraduate degree programme—a case study from South Africa
The Research Unit in Bioinformatics at Rhodes University (RUBi), South Africa, offers a Masters of Science in Bioinformatics.Growing demand for bioinformatics qualifications results in applications from across Africa.Courses aim to bridge gaps in the diverse backgrounds of students who range from biologists with no prior computing exposure to computer scientists with no biology background. The programme is evenly split between coursework and research, with diverse modules from a range of departments coveringmathematics, statistics, computer science and biology, with emphasis on application to bioinformatics research. The early focus on research helps bring students up to speed with working as a researcher. We measure success of the programme by the high rate of subsequent entry to PhD study: 10 of 14 students who completed in the years 2011-2013
Comparing sequence and structure of falcipains and human homologs at prodomain and catalytic active site for malarial peptide-based inhibitor design:
Falcipains are major cysteine proteases of Plasmodium falciparum involved in haemoglobin degradation and remain attractive anti-malarial drug targets. Several inhibitors against these proteases have been identified, yet none of them has been approved for malaria treatment. Other Plasmodium species also possess highly homologous proteins to falcipains. For selective therapeutic targeting, identification of sequence and structure differences with homologous human cathepsins is necessary. The substrate processing activity of these proteins is tightly controlled via a prodomain segment occluding the active site which is chopped under low pH conditions exposing the catalytic site. Current work characterizes these proteases to identify residues mediating the prodomain regulatory function for the design of peptide based anti-malarial inhibitors
Role of structural bioinformatics in drug discovery by computational SNP analysis: analyzing variation at the protein level
With the completion of the human genome project at the beginning of the 21st century, the biological sciences entered an unprecedented age of data generation, and made its first steps toward an era of personalized medicine. This abundance of sequence data has led to the proliferation of numerous sequence-based techniques for associating variation with disease, such as genome-wide association studies and candidate gene association studies. However, these statistical methods do not provide an understanding of the functional effects of variation. Structure-based drug discovery and design is increasingly incorporating structural bioinformatics techniques to model and analyze protein targets, perform large scale virtual screening to identify hit to lead compounds, and simulate molecular interactions. These techniques are fast, cost-effective, and complement existing experimental techniques such as high throughput sequencing. In this paper, we discuss the contributions of structural bioinformatics to drug discovery, focusing particularly on the analysis of nonsynonymous single nucleotide polymorphisms. We conclude by suggesting a protocol for future analyses of the structural effects of nonsynonymous single nucleotide polymorphisms on proteins and protein complexes
HUMA: A platform for the analysis of genetic variation in humans
The completion of the human genome project at the beginning of the 21st century, along with the rapid advancement of sequencing technologies thereafter, has resulted in exponential growth of biological data. In genetics, this has given rise to numerous variation databases, created to store and annotate the ever-expanding dataset of known mutations. Usually, these databases focus on variation at the sequence level. Few databases focus on the analysis of variation at the 3D level, that is, mapping, visualizing, and determining the effects of variation in protein structures. Additionally, these Web servers seldom incorporate tools to help analyze these data. Here, we present the Human Mutation Analysis (HUMA) Web server and database. HUMA integrates sequence, structure, variation, and disease data into a single, connected database. A user-friendly interface provides click-based data access and visualization, whereas a RESTfulWebAPI provides programmatic access to the data. Tools have been integrated into HUMA to allow initial analyses to be carried out on the server. Furthermore, users can upload their private variation datasets, which are automatically mapped to public data and can be analyzed using the integrated tools. HUMA is freely accessible at https://huma.rubi.ru.ac.za
Structural Characterization of Carbonic Anhydrase VIII and Effects of Missense Single Nucleotide Variations to Protein Structure and Function:
Human carbonic anhydrase 8 (CA-VIII) is an acatalytic isoform of the α -CA family. Though the protein cannot hydrate CO2, CA-VIII is essential for calcium (Ca2+) homeostasis within the body, and achieves this by allosterically inhibiting the binding of inositol 1,4,5-triphosphate (IP3) to the IP3 receptor type 1 (ITPR1) protein. However, the mechanism of interaction of CA-VIII to ITPR1 is not well understood. In addition, functional defects to CA-VIII due to non-synonymous single nucleotide polymorphisms (nsSNVs) result in Ca2+ dysregulation and the development of the phenotypes such as cerebellar ataxia, mental retardation and disequilibrium syndrome 3 (CAMRQ3). The pathogenesis of CAMRQ3 is also not well understood. The structure and function of CA-VIII was characterised, and pathogenesis of CAMRQ3 investigated. Structural and functional characterisation of CA-VIII was conducted through SiteMap and CPORT to identify potential binding site residues
Identification of Selective Novel Hits against Plasmodium falciparum Prolyl tRNA Synthetase Active Site and a Predicted Allosteric Site Using in silico Approaches:
Recently, there has been increased interest in aminoacyl tRNA synthetases (aaRSs) as potential malarial drug targets. These enzymes play a key role in protein translation by the addition of amino acids to their cognate tRNA. The aaRSs are present in all Plasmodium life cycle stages, and thus present an attractive malarial drug target. Prolyl tRNA synthetase is a class II aaRS that functions in charging tRNA with proline. Various inhibitors against Plasmodium falciparum ProRS (PfProRS) active site have been designed. However, none have gone through clinical trials as they have been found to be highly toxic to human cells. Recently, a possible allosteric site was reported in PfProRS with two possible allosteric modulators: glyburide and TCMDC-124506. In this study, we sought to identify novel selective inhibitors targeting PfProRS active site and possible novel allosteric modulators of this enzyme. To achieve this, virtual screening of South African natural compounds against PfProRS and the human homologue was carried out using AutoDock Vina. The modulation of protein motions by ligand binding was studied by molecular dynamics (MD) using the GROningen MAchine for Chemical Simulations (GROMACS) tool. To further analyse the protein global motions and energetic changes upon ligand binding, principal component analysis (PCA), and free energy landscape (FEL) calculations were performed
Modulation of human Hsp90α conformational dynamics by allosteric ligand interaction at the c-terminal domain:
Recent years have seen heat shock protein 90 kDa (Hsp90) attract significant interest as a viable drug target, particularly for cancer. To date, designed inhibitors that target the ATPase domain demonstrate potent anti-proliferative effects, but have failed clinical trials due to high levels of associated toxicity. To circumvent this, the focus has shifted away from the ATPase domain. One option involves modulation of the protein through allosteric activation/inhibition. Here, we propose a novel approach: we use previously obtained information via residue perturbation scanning coupled with dynamic residue network analysis to identify allosteric drug targeting sites for inhibitor docking
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