The crystal structure of a mutant nitrile hydratase

Includes bibliographical references.Nitrile hydratases can be used as industrial biocatalysts. They catalyze the conversion of nitriles to their corresponding amides. These industrial biocatalysts have recently gained attention due to the economic production of industrial commodities such as acrylamide and nicotinamide (Thomas et at., 2002). Nitrile hydratases (NHases) are metalloenzymes made up of α and β subunits, and exist mostly as heterotetramers (αβ)₂. They are categorized into Co-containing and Fe-containing types depending on their co-factor requirements

Development of a hepatitis C virus knowledgebase with computational prediction of functional hypothesis of therapeutic relevance

Philosophiae Doctor - PhDTo ameliorate Hepatitis C Virus (HCV) therapeutic and diagnostic challenges requires robust intervention strategies, including approaches that leverage the plethora of rich data published in biomedical literature to gain greater understanding of HCV pathobiological mechanisms. The multitudes of metadata originating from HCV clinical trials as well as low and high-throughput experiments embedded in text corpora can be mined as data sources for the implementation of HCV-specific resources. HCV-customized resources may support the generation of worthy and testable hypothesis and reveal potential research clues to augment the pursuit of efficient diagnostic biomarkers and therapeutic targets. This research thesis report the development of two freely available HCV-specific web-based resources: (i) Dragon Exploratory System on Hepatitis C Virus (DESHCV) accessible via http://apps.sanbi.ac.za/DESHCV/ or http://cbrc.kaust.edu.sa/deshcv/ and(ii) Hepatitis C Virus Protein Interaction Database (HCVpro) accessible via http://apps.sanbi.ac.za/hcvpro/ or http://cbrc.kaust.edu.sa/hcvpro/.DESHCV is a text mining system implemented using named concept recognition and cooccurrence based approaches to computationally analyze about 32, 000 HCV related abstracts obtained from PubMed. As part of DESHCV development, the pre-constructed dictionaries of the Dragon Exploratory System (DES) were enriched with HCV biomedical concepts, including HCV proteins, name variants and symbols to enable HCV knowledge specific exploration. The DESHCV query inputs consist of user-defined keywords, phrases and concepts. DESHCV is therefore an information extraction tool that enables users to computationally generate association between concepts and support the prediction of potential hypothesis with diagnostic and therapeutic relevance.Additionally, users can retrieve a list of abstracts containing tagged concepts that can be used to overcome the herculean task of manual biocuration. DESHCV has been used to simulate previously reported thalidomide-chronic hepatitis C hypothesis and also to model a potentially novel thalidomide-amantadine hypothesis.HCVpro is a relational knowledgebase dedicated to housing experimentally detected HCV-HCV and HCV-human protein interaction information obtained from other databases and curated from biomedical journal articles. Additionally, the database contains consolidated biological information consisting of hepatocellular carcinoma(HCC) related genes, comprehensive reviews on HCV biology and drug development,functional genomics and molecular biology data, and cross-referenced links to canonical pathways and other essential biomedical databases. Users can retrieve enriched information including interaction metadata from HCVpro by using protein identifiers,gene chromosomal locations, experiment types used in detecting the interactions, PubMed IDs of journal articles reporting the interactions, annotated protein interaction IDs from external databases, and via “string searches”. The utility of HCVpro has been demonstrated by harnessing integrated data to suggest putative baseline clues that seem to support current diagnostic exploratory efforts directed towards vimentin. Furthermore,eight genes comprising of ACLY, AZGP1, DDX3X, FGG, H19, SIAH1, SERPING1 and THBS1 have been recommended for possible investigation to evaluate their diagnostic potential. The data archived in HCVpro can be utilized to support protein-protein interaction network-based candidate HCC gene prioritization for possible validation by experimental biologists

Development of a Hepatitis C Virus knowledgebase with computational prediction of functional hypothesis of therapeutic relevance

Philosophiae Doctor - PhDTo ameliorate Hepatitis C Virus (HCV) therapeutic and diagnostic challenges requires robust intervention strategies, including approaches that leverage the plethora of rich data published in biomedical literature to gain greater understanding of HCV pathobiological mechanisms. The multitudes of metadata originating from HCV clinical trials as well as low and high-throughput experiments embedded in text corpora can be mined as data sources for the implementation of HCV-specific resources. HCV-customized resources may support the generation of worthy and testable hypothesis and reveal potential research clues to augment the pursuit of efficient diagnostic biomarkers and therapeutic targets. This research thesis report the development of two freely available HCV-specific web-based resources: (i) Dragon Exploratory System on Hepatitis C Virus (DESHCV) accessible via http://apps.sanbi.ac.za/DESHCV/ or http://cbrc.kaust.edu.sa/deshcv/ and (ii) Hepatitis C Virus Protein Interaction Database (HCVpro) accessible via http://apps.sanbi.ac.za/hcvpro/ or http://cbrc.kaust.edu.sa/hcvpro/. DESHCV is a text mining system implemented using named concept recognition and cooccurrence based approaches to computationally analyze about 32, 000 HCV related abstracts obtained from PubMed. As part of DESHCV development, the pre-constructed dictionaries of the Dragon Exploratory System (DES) were enriched with HCV biomedical concepts, including HCV proteins, name variants and symbols to enable HCV knowledge specific exploration. The DESHCV query inputs consist of user-defined keywords, phrases and concepts. DESHCV is therefore an information extraction tool that enables users to computationally generate association between concepts and support the prediction of potential hypothesis with diagnostic and therapeutic relevance. Additionally, users can retrieve a list of abstracts containing tagged concepts that can be used to overcome the herculean task of manual biocuration. DESHCV has been used to simulate previously reported thalidomide-chronic hepatitis C hypothesis and also to model a potentially novel thalidomide-amantadine hypothesis. HCVpro is a relational knowledgebase dedicated to housing experimentally detected HCV-HCV and HCV-human protein interaction information obtained from other databases and curated from biomedical journal articles. Additionally, the database contains consolidated biological information consisting of hepatocellular carcinoma (HCC) related genes, comprehensive reviews on HCV biology and drug development, functional genomics and molecular biology data, and cross-referenced links to canonical pathways and other essential biomedical databases. Users can retrieve enriched information including interaction metadata from HCVpro by using protein identifiers, gene chromosomal locations, experiment types used in detecting the interactions, PubMed IDs of journal articles reporting the interactions, annotated protein interaction IDs from external databases, and via “string searches”. The utility of HCVpro has been demonstrated by harnessing integrated data to suggest putative baseline clues that seem to support current diagnostic exploratory efforts directed towards vimentin. Furthermore, eight genes comprising of ACLY, AZGP1, DDX3X, FGG, H19, SIAH1, SERPING1 and THBS1 have been recommended for possible investigation to evaluate their diagnostic potential. The data archived in HCVpro can be utilized to support protein-protein interaction network-based candidate HCC gene prioritization for possible validation by experimental biologists.South Afric

Electrochemical Response of Cells Using Bioactive Plant Isolates

Traditional herbal medical practices continue to be part of the healthcare needs of the world especially residents of sub-Sahara Africa (sSA). However, the mechanism of action of the plant metabolites to elicit their potency continue to be a mystery due to the lack of standardized methods. The mechanism of plant bioactive compounds to cause cell death is gradually being linked to membrane polarization and depolarization behaviour. The current work seeks to probe the electrochemical response of model cells using bioactive compounds captured in bio-zeolites or membrane mimetics. The voltage and current fluctuations emanating from such studies will establish a correlation between cell death and membrane depolarization. It will be a useful biological interface sensing material with the potential to identify plant metabolites that can selectively detect and destroy diseased cells. Several model membranes have already been developed for biomedical applications and this new paradigm will elevate the usefulness of these model systems. The concept was investigated using extracts from Dioclea reflexa (DR) hook which belongs to the leguminous family. There are certain class of compounds in Dioclea reflexa (DR) that have clinical usefulness in both temperate and tropical regions, however the identity of the bioactive compounds responsible for inducing cell death continue to be a major challenge

Honey as a Natural Product Worthy of Re-Consideration in Treating MRSA Wound Infections

The use of antibiotics to treat bacterial infections have largely been successful. However, the misuse and overuse of these precious drugs have led to the development of bacterial resistance and this seems to have jeopardized their effectiveness. Many antibiotics that hitherto were seen as “miraculous drugs”, have witnessed a low efficacy and this has threatened the life of humanity as never before. The rapid emergence of antibiotic resistance in bacteria is the major cause of this sad development. One such superbug is methicillin-resistant Staphylococcus aureus (MRSA). MRSA is a general problem in most healthcare centers with a reported astronomical incidence of invasive MRSA infections causing death. Honey, a natural product, popular for its antibacterial activity is increasingly being used owing to its reported antibiotic potential against ‘stubborn’ bacteria. This review discusses the fact that though honey is an ancient remedy, it is still relevant and its application in modern medicine for the treatment of chronically infected wounds caused by MRSA should be re-visited. Furthermore, the in vitro antibacterial and antibiofilm activities of medical-grade honey on S. aureus infections and challenges encountered by Researchers in developing honey, into an acceptable medical, therapeutic antibacterial agent for wound care have also been highlighted

Homology Modeling, <i>de Novo</i> Design of Ligands, and Molecular Docking Identify Potential Inhibitors of <i>Leishmania donovani</i> 24-Sterol Methyltransferase.

The therapeutic challenges pertaining to leishmaniasis due to reported chemoresistance and toxicity necessitate the need to explore novel pathways to identify plausible inhibitory molecules. Leishmania donovani 24-sterol methyltransferase (LdSMT) is vital for the synthesis of ergosterols, the main constituents of Leishmania cellular membranes. So far, mammals have not been shown to possess SMT or ergosterols, making the pathway a prime candidate for drug discovery. The structural model of LdSMT was elucidated using homology modeling to identify potential novel 24-SMT inhibitors via virtual screening, scaffold hopping, and de-novo fragment-based design. Altogether, six potential novel inhibitors were identified with binding energies ranging from -7.0 to -8.4 kcal/mol with e-LEA3D using 22,26-azasterol and S1-S4 obtained from scaffold hopping via the ChEMBL, DrugBank, PubChem, ChemSpider, and ZINC15 databases. These ligands showed comparable binding energy to 22,26-azasterol (-7.6 kcal/mol), the main inhibitor of LdSMT. Moreover, all the compounds had plausible ligand efficiency-dependent lipophilicity (LELP) scores above 3. The binding mechanism identified Tyr92 to be critical for binding, and this was corroborated via molecular dynamics simulations and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. The ligand A1 was predicted to possess antileishmanial properties with a probability of activity (Pa) of 0.362 and a probability of inactivity (Pi) of 0.066, while A5 and A6 possessed dermatological properties with Pa values of 0.205 and 0.249 and Pi values of 0.162 and 0.120, respectively. Structural similarity search via DrugBank identified vabicaserin, daledalin, zanapezil, imipramine, and cefradine with antileishmanial properties suggesting that the de-novo compounds could be explored as potential antileishmanial agents

In silico screening of phytochemicals from Dissotis rotundifolia against Plasmodium falciparum Dihydrofolate Reductase

Background: Malaria remains a major health concern in developing countries with high morbidity and mortality, especially in pregnant women and infants. A major obstacle to the treatment of malaria is a low effectiveness and an increase resistance of the parasite to antimalarial drugs. As a result, there is an ongoing demand for new and potent antimalarial drugs. Medicinal plants remain a potential source for the development of new antimalarial drugs. Amongst them is Dissotis rotundifolia is an ethnomedical important plant used in West Africa to treat malaria. Purpose: This study aimed at identifying new potential antifolates by virtually screening phytochemicals characterized from the whole plant methanolic extract of D. rotundifolia against Plasmodium falciparum Dihydrofolate Reductase (PfDHFR). Methods: LC-ESI-Q-TOF-MS analysis was employed to identify the phytochemicals present in the whole plant methanolic extract of D. rotundifolia. These phytochemicals were docked against the catalytic site of PfDHFR. The docking protocol was evaluated using the Area Under the Curve (AUC) of a Receiver Operating Characteristic (ROC) curve. The binding mechanisms and the drug-likeness of the phytochemicals were characterized. A 100 ns Molecular Dynamics (MD) simulation and Molecular Mechanics-Poisson Boltzmann Surface Area (MM-PBSA) calculations were utilized to analyze the stability, the energy decomposition per residue and the binding free energy of the potential leads. Results: Twenty nine phytochemicals were characterized and docked against PfDHFR. Dimethylmatairesinol, flavodic acid, sakuranetin, and sesartemin were identified as potential leads with binding affinities of -8.4, -8.9, -8.6, and -8.9 kcal/mol respectively, greater than a stringent threshold of -8.0 kcal/mol. The potential leads also interacted hydrophobically with critical residue Phe58. A novel critical residue, Leu46 was identified to be crucial in the catalytic activity of PfDHFR. The potential leads were also predicted to be anti-protozoal with a probability of active (Pa) value ranging from 0.319 to 0.537. Conclusion: This study elucidates the potential inhibition of PfDHFR by dimethylmatairesinol, flavodic acid, sakuranetin and sesartemin present in D. rotundifolia. These compounds are druglike, do not violate Lipinski's rule of five, have a high binding affinity to PfDHFR, and interact with crucial residues involved in the catalytic activity PfDHFR. Dimethylmatairesinol, flavodic acid, sakuranetin and sesartemin could therefore be further investigated and developed as new antifolate drugs for malaria