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  1. AU="Mahmoud E. S. Soliman"
  2. AU="Müller, Silvana"
  3. AU=Kaneto Hideaki AU=Kaneto Hideaki

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  1. Artikel ; Online: Highlighting the mechanistic role of Olutasidenib (FT-2102) in the selective inhibition of mutated isocitrate dehydrogenase 1 (mIDH1) in cancer therapy

    Elliasu Y. Salifu / Clement Agoni / Mahmoud E.S. Soliman

    Informatics in Medicine Unlocked, Vol 28, Iss , Pp 100829- (2022)

    2022  

    Abstract: Mutations in isocitrate dehydrogenase enzymes 1 and 2 (mIDH1/2) results in an aberrant accumulation of (R)-2-hydroxyglutarate (2-HG), excess of which has been shown to inhibit alpha ketoglutarate (αKG)-dependent enzymes leading to the development of ... ...

    Abstract Mutations in isocitrate dehydrogenase enzymes 1 and 2 (mIDH1/2) results in an aberrant accumulation of (R)-2-hydroxyglutarate (2-HG), excess of which has been shown to inhibit alpha ketoglutarate (αKG)-dependent enzymes leading to the development of gliomas. Inhibition of mutant IDH1 has therefore been evaluated clinically as a treatment option for gliomas. Recently, Olutasidenib (FT-2102), was discovered as a highly potent and selective inhibitor of mIDH1. However, the mechanistic activities surrounding its selective inhibitory potency remain unclear. Herein, this study provides the structural and mechanistic insights that underpin the reported selectivity of FT-2102 on mDH1 using molecular dynamic (MD) simulations and advanced post-MD analysing techniques. Findings revealed that the selectivity of FT-2102 towards mIDH1 is mediated by high-affinity interactions with residues Arg109, Ile128 and Val281 within the binding pocket. Also, a unidirectional orientation of FT-2102 within mIDH1 anchored by the high-affinity interactions accounted for its higher stability and stronger binding of −56.82 kcal/mol relative to lower binding affinity of −14.48 kcal/mol towards mIDH2. Furthermore, the binding of FT-2102 in mIDH1 conferred more stability at the binding pocket which resulted in maintenance of crucial atomic interactions as compared to mIDH2 where binding was characterized by inconsistency and loss of crucial interactions. These findings thus present a detailed insight into the selective inhibitory mechanism of FT-2102 towards mIDH1 and could aid in the design and development of novel mutant IDH inhibitors.
    Schlagwörter Isocitrate dehydrogenase 1 and 2 ; Olutasidenib ; Molecular dynamic simulation ; Binding affinity ; Dual-inhibition ; Mutation ; Computer applications to medicine. Medical informatics ; R858-859.7
    Thema/Rubrik (Code) 540
    Sprache Englisch
    Erscheinungsdatum 2022-01-01T00:00:00Z
    Verlag Elsevier
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  2. Artikel ; Online: Establishing the mutational effect on the binding susceptibility of AMG510 to KRAS switch II binding pocket

    Abdul Rashid Issahaku / Aimen Aljoundi / Mahmoud E.S. Soliman

    Informatics in Medicine Unlocked, Vol 30, Iss , Pp 100952- (2022)

    Computational insights

    2022  

    Abstract: After decades of leaving patients with limited treatment options due to the ‘undruggability’ of Kirsten rat sarcoma, the kernel was finally cracked with the discovery of Sotorasib. This novel drug binds to a small pocket on the switch II of Kirsten rat ... ...

    Abstract After decades of leaving patients with limited treatment options due to the ‘undruggability’ of Kirsten rat sarcoma, the kernel was finally cracked with the discovery of Sotorasib. This novel drug binds to a small pocket on the switch II of Kirsten rat sarcoma by exploiting the mutation that occurs at codon 12 wherein glycine is replaced by cysteine. However, this pocket is not only prone to cysteine mutation but other mutations occur as well including at codon 13. These mutations have been reported to drive cancer in the lungs, colorectal and in solid tumors with varying degree of expressions. Sotorasib is therefore only effective in a small group of patients especially those expressing cysteine at codon 12, reminding drug hunters of the unfinished work. This study employs computational techniques to understand the susceptibility of the mutated binding pocket to the binding of Sotorasib. It was revealed that the binding affinity of Sotorasib to other mutations aside Cysteine was significantly affected via the total free binding energies presented by the mutated complexes. Furthermore, the quantum of energy contributed by the mutated residues except cysteine was significantly reduced suggesting the binding of Sotorasib is enhanced in only cysteine mutated Kirsten rat sarcoma. Residual interaction network showed Sotorasib in complex with the cysteine mutated protein presented the highest degree centrality, shortest path betweenness, shortest path centrality and shortest path degree indicating Sotorasib controls more information flow within the cysteine mutated protein than in other mutations. Insight unraveled here will provide aid in the development of pan Kirsten rat sarcoma inhibitory small molecules.
    Schlagwörter AMG510 ; Mutations ; KRASG12C ; KRAS Protein ; MMPBSA ; Residue interaction network ; Computer applications to medicine. Medical informatics ; R858-859.7
    Thema/Rubrik (Code) 540
    Sprache Englisch
    Erscheinungsdatum 2022-01-01T00:00:00Z
    Verlag Elsevier
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  3. Artikel ; Online: Immunoinformatics prediction of potential B-cell and T-cell epitopes as effective vaccine candidates for eliciting immunogenic responses against Epstein–Barr virus

    Fisayo A. Olotu / Mahmoud E.S. Soliman

    Biomedical Journal, Vol 44, Iss 3, Pp 317-

    2021  Band 337

    Abstract: Background: The ongoing search for viable treatment options to curtail Epstein Barr Virus (EBV) pathogenicity has necessitated a paradigmatic shift towards the design of peptide-based vaccines. Potential B-cell and T-cell epitopes were predicted for nine ...

    Abstract Background: The ongoing search for viable treatment options to curtail Epstein Barr Virus (EBV) pathogenicity has necessitated a paradigmatic shift towards the design of peptide-based vaccines. Potential B-cell and T-cell epitopes were predicted for nine antigenic EBV proteins that mediate epithelial cell-attachment and spread, capsid self-assembly, DNA replication and processivity. Methods: Predictive algorithms incorporated in the Immune Epitope Database (IEDB) resources were used to determine potential B-cell epitopes based on their physicochemical attributes. These were combined with a string-kernel method and an antigenicity predictive AlgPred tool to enhance accuracy in the end-point selection of highly potential antigenic EBV B-cell epitopes. NetCTL 1.2 algorithms enabled the prediction of probable T-cell epitopes which were structurally modeled and subjected to blind peptide-protein docking with HLA-A*02:01. All-atom molecular dynamics (MD) simulation and Molecular Mechanics Generalized-Born Surface Area methods were used to investigate interaction dynamics and affinities of predicted T-cell peptide-protein complexes. Results: Computational predictions and sequence overlapping analysis yielded 18 linear (continuous) and discontinuous (conformational) subunit epitopes from the antigenic proteins with characteristic surface accessibility, flexibility and antigenicity, and predictive scores above the threshold value (1) set. A novel site was identified on HLA-A*02:01 with preferential affinity binding for modeled BMRF2, BXLF1 and BGLF4 T-cell epitopes. Interaction dynamics and energies were also computed in addition to crucial residues that mediated complex formation and stability. Conclusion: This study implemented an integrative meta-analytical approach to model highly probable B-cell and T-cell epitopes as potential peptide-vaccine candidates for the treatment of EBV-related diseases.
    Schlagwörter Immunoinformatics ; Epstein-bar virus ; Epitopes ; Major histocompatibility complex 1 ; Antigenic proteins ; Peptide-based vaccine ; Medicine (General) ; R5-920 ; Biology (General) ; QH301-705.5
    Thema/Rubrik (Code) 570
    Sprache Englisch
    Erscheinungsdatum 2021-06-01T00:00:00Z
    Verlag Elsevier
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  4. Artikel ; Online: Integrative immunoinformatics paradigm for predicting potential B-cell and T-cell epitopes as viable candidates for subunit vaccine design against COVID-19 virulence

    Vyshnavie R. Sarma / Fisayo A. Olotu / Mahmoud E.S. Soliman

    Biomedical Journal, Vol 44, Iss 4, Pp 447-

    2021  Band 460

    Abstract: Background: The increase in global mortality rates from SARS-COV2 (COVID-19) infection has been alarming thereby necessitating the continual search for viable therapeutic interventions. Due to minimal microbial components, subunit (peptide-based) ... ...

    Abstract Background: The increase in global mortality rates from SARS-COV2 (COVID-19) infection has been alarming thereby necessitating the continual search for viable therapeutic interventions. Due to minimal microbial components, subunit (peptide-based) vaccines have demonstrated improved efficacies in stimulating immunogenic responses by host B- and T-cells. Methods: Integrative immunoinformatics algorithms were used to determine linear and discontinuous B-cell epitopes from the S-glycoprotein sequence. End-point selection of the most potential B-cell epitope was based on highly essential physicochemical attributes. NetCTL-I and NetMHC-II algorithms were used to predict probable MHC-I and II T-cell epitopes for globally frequent HLA-A∗O2:01, HLA-B∗35:01, HLA-B∗51:01 and HLA-DRB1∗15:02 molecules. Highly probable T-cell epitopes were selected based on their high propensities for C-terminal cleavage, transport protein (TAP) processing and MHC-I/II binding. Results: Preferential epitope binding sites were further identified on the HLA molecules using a blind peptide-docking method. Phylogenetic analysis revealed close relativity between SARS-CoV-2 and SARS-CoV S-protein. LALHRSYLTPGDSSSGWTAGAA242→263 was the most probable B-cell epitope with optimal physicochemical attributes. MHC-I antigenic presentation pathway was highly favourable for YLQPRTFLL269-277 (HLA-A∗02:01), LPPAYTNSF24-32 (HLA-B∗35:01) and IPTNFTISV714-721 (HLA-B∗51:01). Also, LTDEMIAQYTSALLA865-881 exhibited the highest binding affinity to HLA-DR B1∗15:01 with core interactions mediated by IAQYTSALL870-878. COVID-19 YLQPRTFLL269-277 was preferentially bound to a previously undefined site on HLA-A∗02:01 suggestive of a novel site for MHC-I-mediated T-cell stimulation. Conclusion: This study implemented combinatorial immunoinformatics methods to model B- and T-cell epitopes with high potentials to trigger immunogenic responses to the S protein of SARS-CoV-2.
    Schlagwörter Immunoinformatics ; SARS-CoV-2 ; B-cell epitopes ; T-cell epitopes ; Vaccine design ; High-affinity binding ; Medicine (General) ; R5-920 ; Biology (General) ; QH301-705.5
    Thema/Rubrik (Code) 570
    Sprache Englisch
    Erscheinungsdatum 2021-08-01T00:00:00Z
    Verlag Elsevier
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    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  5. Artikel ; Online: QSAR AND MOLECULAR DOCKING STUDY OF GONADOTROPIN-RELEASING HORMONE RECEPTOR INHIBITORS

    David Ebuka Arthur / Mahmoud E.S. Soliman / Shola Elijah Adeniji / Oluwaseye Adedirin / Florence Peter

    Scientific African, Vol 17, Iss , Pp e01291- (2022)

    2022  

    Abstract: Background: A case study of activities of pyrimidine-based molecules to the gonadotropin-releasing hormone receptor is used to develop a QSAR model. The chemical dataset collected as CHEMBL1855 were curated in line with published works of Prof. Gramatica. ...

    Abstract Background: A case study of activities of pyrimidine-based molecules to the gonadotropin-releasing hormone receptor is used to develop a QSAR model. The chemical dataset collected as CHEMBL1855 were curated in line with published works of Prof. Gramatica. The parameters for QSAR model validation and ability to predict activities of future chemicals (internal robustness, exclusion of chance correlation, external predictivity, applicability domain) are presented in the work, while the molecular descriptors used for the model were calculated using the free PaDEL-Descriptor software. Other important information regarding the model was done with the aid of the QSARINS. This work uses the Setubal principle as a guideline in hypothesizing a well outlined step in designing novel more active compounds using a ligand based-design approach. We highlighted a list of things to be considered when selecting a lead compound, after which the hypothesis was tested and a series of novel compounds were manually designed. Result: The QSAR models initially developed was used to predict the activities of the new compounds before subjecting the novel compounds a molecular docking study. The external validation parameter R2ext = 0.5328, while the internal cross validation parameter for the model was found to be Q2loo= 0.5316, this shows that the model could be used to predict the activitie of other inhibitor within its chemical space. The model was used to design several compound with better inhibitory potential than their lead or parent structures. One of such compounds B8, was ported to have a calculated binding energy of -30.442 kcal/mol, which was significantly lower than the binding energy of the parent compound (LeadB) which is -21.373 kcal/mol. The calculated pKI value of B8 and other designed novel compounds were predicted with the developed model was found to be better than their parent compounds used in their design. Conclusion: The predicted pKI values from the QSAR predictions and the Molecular docking studies of the novel ...
    Schlagwörter QSAR ; Gonadotrophs ; Molecular docking ; Insurbia plot ; Williams plot ; Science ; Q
    Thema/Rubrik (Code) 540
    Sprache Englisch
    Erscheinungsdatum 2022-09-01T00:00:00Z
    Verlag Elsevier
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  6. Artikel ; Online: Artificial Intelligence, Machine Learning, and Big Data for Ebola Virus Drug Discovery

    Samuel K. Kwofie / Joseph Adams / Emmanuel Broni / Kweku S. Enninful / Clement Agoni / Mahmoud E. S. Soliman / Michael D. Wilson

    Pharmaceuticals, Vol 16, Iss 332, p

    2023  Band 332

    Abstract: The effect of Ebola virus disease (EVD) is fatal and devastating, necessitating several efforts to identify potent biotherapeutic molecules. This review seeks to provide perspectives on complementing existing work on Ebola virus (EBOV) by discussing the ... ...

    Abstract The effect of Ebola virus disease (EVD) is fatal and devastating, necessitating several efforts to identify potent biotherapeutic molecules. This review seeks to provide perspectives on complementing existing work on Ebola virus (EBOV) by discussing the role of machine learning (ML) techniques in the prediction of small molecule inhibitors of EBOV. Different ML algorithms have been used to predict anti-EBOV compounds, including Bayesian, support vector machine, and random forest algorithms, which present strong models with credible outcomes. The use of deep learning models for predicting anti-EBOV molecules is underutilized; therefore, we discuss how such models could be leveraged to develop fast, efficient, robust, and novel algorithms to aid in the discovery of anti-EBOV drugs. We further discuss the deep neural network as a plausible ML algorithm for predicting anti-EBOV compounds. We also summarize the plethora of data sources necessary for ML predictions in the form of systematic and comprehensive high-dimensional data. With ongoing efforts to eradicate EVD, the application of artificial intelligence-based ML to EBOV drug discovery research can promote data-driven decision making and may help to reduce the high attrition rates of compounds in the drug development pipeline.
    Schlagwörter drug discovery ; deep learning ; artificial intelligence ; big data ; Ebola virus ; classifiers ; Medicine ; R ; Pharmacy and materia medica ; RS1-441
    Thema/Rubrik (Code) 006
    Sprache Englisch
    Erscheinungsdatum 2023-02-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  7. Artikel ; Online: Identification and classification of differentially expressed genes reveal potential molecular signature associated with SARS-CoV-2 infection in lung adenocarcinomal cells

    Opeyemi S. Soremekun / Kehinde F. Omolabi / Mahmoud E.S. Soliman

    Informatics in Medicine Unlocked, Vol 20, Iss , Pp 100384- (2020)

    2020  

    Abstract: Genomic techniques such as next-generation sequencing and microarrays have facilitated the identification and classification of molecular signatures inherent in cells upon viral infection, for possible therapeutic targets. Therefore, in this study, we ... ...

    Abstract Genomic techniques such as next-generation sequencing and microarrays have facilitated the identification and classification of molecular signatures inherent in cells upon viral infection, for possible therapeutic targets. Therefore, in this study, we performed a differential gene expression analysis, pathway enrichment analysis, and gene ontology on RNAseq data obtained from SARS-CoV-2 infected A549 cells. Differential expression analysis revealed that 753 genes were up-regulated while 746 down-regulated. SNORA81, OAS2, SYCP2, LOC100506985, and SNORD35B are the top 5 upregulated genes upon SARS-Cov-2 infection. Expectedly, these genes have been implicated in the immune response to viral assaults. In the Ontology of protein classification, a high percentage of the genes are classified as Gene-specific transcriptional regulator, metabolite interconversion enzyme, and Protein modifying enzymes. Twenty pathways with P-value lower than 0.05 were enriched in the up-regulated genes while 18 pathways are enriched in the down-regulated DEGs. The toll-like receptor signalling pathway is one of the major pathways enriched. This pathway plays an important role in the innate immune system by identifying the pathogen-associated molecular signature emanating from various microorganisms. Taken together, our results present a novel understanding of genes and corresponding pathways upon SARS-Cov-2 infection, and could facilitate the identification of novel therapeutic targets and biomarkers in the treatment of COVID-19.
    Schlagwörter Differentially expressed genes ; SARS-CoV-2 ; COVID-19 ; Enrichment analysis ; RNAseq ; Computer applications to medicine. Medical informatics ; R858-859.7 ; covid19
    Thema/Rubrik (Code) 570 ; 572
    Sprache Englisch
    Erscheinungsdatum 2020-01-01T00:00:00Z
    Verlag Elsevier
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    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  8. Artikel ; Online: Leaving no stone unturned

    Fisayo A. Olotu / Kehinde F. Omolabi / Mahmoud E.S. Soliman

    Informatics in Medicine Unlocked, Vol 21, Iss , Pp 100451- (2020)

    Allosteric targeting of SARS-CoV-2 spike protein at putative druggable sites disrupts human angiotensin-converting enzyme interactions at the receptor binding domain

    2020  

    Abstract: The systematic entry of SARS-CoV-2 into host cells, as mediated by its Spike (S) protein, is highly essential for pathogenicity in humans. Hence, targeting the viral entry mechanisms remains a major strategy for COVID-19 treatment. Although recent ... ...

    Abstract The systematic entry of SARS-CoV-2 into host cells, as mediated by its Spike (S) protein, is highly essential for pathogenicity in humans. Hence, targeting the viral entry mechanisms remains a major strategy for COVID-19 treatment. Although recent efforts have focused on the direct inhibition of S-protein receptor-binding domain (RBD) interactions with human angiotensin-converting enzyme 2 (hACE2), allosteric targeting remains an unexplored possibility. Therefore, in this study, for the first time, we employed an integrative meta-analytical approach to investigate the allosteric inhibitory mechanisms of SARS-CoV-2 S-protein and its association with hACE2. Findings revealed two druggable sites (Sites 1 and 2) located at the N-terminal domain (NTD) and S2 regions of the protein. Two high-affinity binders; ZINC3939013 (Fosaprepitant – Site 1) and ZINC27990463 (Lomitapide – Site 2) were discovered via site-directed high-throughput screening against a library of ~1500 FDA approved drugs. Interestingly, we observed that allosteric binding of both compounds perturbed the prefusion S-protein conformations, which in turn, resulted in unprecedented hACE2 displacement from the RBD. Estimated ΔGbinds for both compounds were highly favorable due to high-affinity interactions at the target sites. In addition, Site 1 residues; R190, H207, K206 and K187, I101, R102, I119, F192, L226, V126 and W104 were identified for their crucial involvement in the binding and stability of ZINC3939013. Likewise, energy contributions of Q957, N953, Q954, L303, Y313, Q314, L858, V952, N953, and A956 corroborated their importance to ZINC27990463 binding at the predicted Site 2. We believe these findings would pave way for the structure-based discovery of allosteric SARS-CoV-2 S-protein inhibitors for COVID-19 treatment.
    Schlagwörter SARS-CoV-2 ; Spike protein ; Allosteric targeting ; Virtual high-throughput screening ; Receptor binding domain ; High-affinity binding ; Computer applications to medicine. Medical informatics ; R858-859.7
    Thema/Rubrik (Code) 500
    Sprache Englisch
    Erscheinungsdatum 2020-01-01T00:00:00Z
    Verlag Elsevier
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    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  9. Artikel ; Online: Coupling of HSP72 α-Helix Subdomains by the Unexpected Irreversible Targeting of Lysine-56 over Cysteine-17; Coevolution of Covalent Bonding

    Aimen Aljoundi / Ahmed El Rashedy / Patrick Appiah-Kubi / Mahmoud E. S. Soliman

    Molecules, Vol 25, Iss 4239, p

    2020  Band 4239

    Abstract: Covalent inhibition has recently gained a resurgence of interest in several drug discovery areas. The expansion of this approach is based on evidence elucidating the selectivity and potency of covalent inhibitors when bound to particular amino acids of a ...

    Abstract Covalent inhibition has recently gained a resurgence of interest in several drug discovery areas. The expansion of this approach is based on evidence elucidating the selectivity and potency of covalent inhibitors when bound to particular amino acids of a biological target. The unexpected covalent inhibition of heat shock protein 72 (HSP72) by covalently targeting Lys-56 instead of Cys-17 was an interesting observation. However, the structural basis and conformational changes associated with this preferential coupling to Lys-56 over Cys-17 remain unclear. To resolve this mystery, we employed structural and dynamic analyses to investigate the structural basis and conformational dynamics associated with the unexpected covalent inhibition. Our analyses reveal that the coupling of the irreversible inhibitor to Lys-56 is intrinsically less dynamic than Cys-17. Conformational dynamics analyses further reveal that the coupling of the inhibitor to Lys-56 induced a closed conformation of the nucleotide-binding subdomain (NBD) α-helices, in contrast, an open conformation was observed in the case of Cys-17. The closed conformation maintained the crucial salt-bridge between Glu-268 and Lys-56 residues, which strengthens the interaction affinity of the inhibitor nearly identical to adenosine triphosphate (ADP/Pi) bound to the HSP72-NBD. The outcome of this report provides a substantial shift in the conventional direction for the design of more potent covalent inhibitors.
    Schlagwörter covalent MD simulation ; HSP72 ; 8- N -benzyladenosine ; coupling ; principal component analysis ; Organic chemistry ; QD241-441
    Thema/Rubrik (Code) 540
    Sprache Englisch
    Erscheinungsdatum 2020-09-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  10. Artikel ; Online: Using bioinformatics tools for the discovery of Dengue RNA-dependent RNA polymerase inhibitors

    Nomagugu B. Nncube / Pritika Ramharack / Mahmoud E.S. Soliman

    PeerJ, Vol 6, p e

    2018  Band 5068

    Abstract: Background Dengue fever has rapidly manifested into a serious global health concern. The emergence of various viral serotypes has prompted the urgent need for innovative drug design techniques. Of the viral non-structural enzymes, the NS5 RNA-dependent ... ...

    Abstract Background Dengue fever has rapidly manifested into a serious global health concern. The emergence of various viral serotypes has prompted the urgent need for innovative drug design techniques. Of the viral non-structural enzymes, the NS5 RNA-dependent RNA polymerase has been established as a promising target due to its lack of an enzymatic counterpart in mammalian cells and its conserved structure amongst all serotypes. The onus is now on scientists to probe further into understanding this enzyme and its mechanism of action. The field of bioinformatics has evolved greatly over recent decades, with updated drug design tools now being publically available. Methods In this study, bioinformatics tools were used to provide a comprehensive sequence and structural analysis of the two most prominent serotypes of Dengue RNA-dependent RNA polymerase. A list of popular flavivirus inhibitors were also chosen to dock to the active site of the enzyme. The best docked compound was then used as a template to generate a pharmacophore model that may assist in the design of target-specific Dengue virus inhibitors. Results Comparative sequence alignment exhibited similarity between all three domains of serotype 2 and 3.Sequence analysis revealed highly conserved regions at residues Meth530, Thr543 Asp597, Glu616, Arg659 and Pro671. Mapping of the active site demonstrated two highly conserved residues: Ser710 and Arg729. Of the active site interacting residues, Ser796 was common amongst all ten docked compounds, indicating its importance in the drug design process. Of the ten docked flavivirus inhibitors, NITD-203 showed the best binding affinity to the active site. Further pharmacophore modeling of NITD-203 depicted significant pharmacophoric elements that are necessary for stable binding to the active site. Discussion This study utilized publically available bioinformatics tools to provide a comprehensive framework on Dengue RNA-dependent RNA polymerase. Based on docking studies, a pharmacophore model was also designed to unveil ...
    Schlagwörter Dengue drug discovery ; RNA-dependent RNA Polymerase ; Bioinformatics ; Flavivirus therapeutics ; Medicine ; R
    Thema/Rubrik (Code) 540
    Sprache Englisch
    Erscheinungsdatum 2018-09-01T00:00:00Z
    Verlag PeerJ Inc.
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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