44 results match your criteria: "Covenant University Bioinformatics Research (CUBRe).[Affiliation]"

In-silico-based lead optimization of hit compounds targeting mitotic kinesin Eg5 for cancer management.

In Silico Pharmacol

January 2025

Phyto-medicine and Computational Biology Laboratory, Department of Biochemistry, Adekunle Ajasin University, Akungba-Akoko, Ondo State Nigeria.

Unlabelled: Lead optimization is vital for turning hit compounds into therapeutic drugs. This study builds upon a prior in silico research, where the hit compounds had better binding affinity and stability compared to a reference drug. Using a genetic algorithm, 12,500 analogs of the top compounds from the prior study were generated.

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RNA-Puzzles Round V: blind predictions of 23 RNA structures.

Nat Methods

December 2024

GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macao Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China.

Article Synopsis
  • - RNA-Puzzles is a collaborative project focused on improving the prediction of RNA three-dimensional structures, with predictions made by modeling groups before experimental structures are published.
  • - A significant set of predictions was made by 18 groups for 23 different RNA structures, including various elements like ribozymes and aptamers.
  • - The study highlights key challenges in RNA modeling, such as identifying helix pairs and ensuring proper stacking, and notes that some top-performing groups also excelled in a separate competition (CASP15).
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Objective: Nigeria, along with other Sub-Saharan African countries, bears the highest burden of epilepsy worldwide. This high prevalence is attributed to a combination of factors, including a significant incidence of infectious diseases, perinatal complications, and genetic etiologies. Genetic testing is rarely available and is not typically included in the routine diagnostic work-up for individuals with infantile and childhood epilepsy syndromes in these regions.

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Background: Existing antimalarial drugs primarily target blood-stage parasites, but there is a need for transmission-blocking drugs to combat malaria effectively. Calcium-dependent Protein Kinase 4 (CDPK4) is a promising target for such drugs. This study employed advanced in silico analyses of hexahydroquinolines (HHQ) derivatives to identify CDPK4 inhibitors capable of disrupting malaria transmission.

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Increasing reports of insecticide resistance continue to hamper the gains of vector control strategies in curbing malaria transmission. This makes identifying new insecticide targets or alternative vector control strategies necessary. CLassifier of Essentiality AcRoss EukaRyote (CLEARER), a leave-one-organism-out cross-validation machine learning classifier for essential genes, was used to predict essential genes in Anopheles gambiae and selected predicted genes experimentally validated.

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The inhibition of -acetyl sulphydrylase synthase isoforms has been reported to represent a promising approach for the development of antibiotic adjuvants. This occurs via the organism developing an unpaired oxidative stress response, causing a reduction in antibiotic resistance in vegetative and swarm cell populations. This consequently increases the effectiveness of conventional antibiotics at lower doses.

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Computational Studies on 6-Pyruvoyl Tetrahydropterin Synthase (6-PTPS) of .

Bioinform Biol Insights

February 2024

Covenant Applied Informatics and Communication-Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota, Nigeria.

6-Pyruvoyl tetrahydropterin synthase (6-PTPS) is a lyase involved in the synthesis of tetrahydrobiopterin. In species where dihydroneopterin aldolase (DHNA) is absent, it acts in the folate biosynthetic pathway necessary for the growth and survival of the parasite. The 6-pyruvoyl tetrahydropterin synthase of (PTPS) has been identified as a potential antimalarial drug target.

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Malaria remains a significant global health concern causing numerous fatalities and the emergence of antimalarial drug resistance highlights the urgent need for novel therapeutic options with innovative mechanisms of action and targets. This study aimed to design potential inhibitors of 6-pyruvoyltetrahydropterin synthase (PTPS), synthesize them, and experimentally validate their efficacy as antimalarial agents. A structure-based approach was employed to design a series of novel derivatives, including amidinyl, amidoximyl and hydroxamic acid analogs (, , , and ), with a focus on their ability to bind to the Zn present in the active site of PTPS.

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Early identification of genetic risk factors for complex diseases can enable timely interventions and prevent serious outcomes, including mortality. While the genetics underlying many Mendelian diseases have been elucidated, it is harder to predict risk for complex diseases arising from the combined effects of many genetic variants with smaller individual effects on disease aetiology. Polygenic risk scores (PRS), which combine multiple contributing variants to predict disease risk, have the potential to influence the implementation for precision medicine.

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Tandem repeats (TRs) represent one of the largest sources of genetic variation in humans and are implicated in a range of phenotypes. Here we present a deep characterization of TR variation based on high coverage whole genome sequencing from 3550 diverse individuals from the 1000 Genomes Project and H3Africa cohorts. We develop a method, EnsembleTR, to integrate genotypes from four separate methods resulting in high-quality genotypes at more than 1.

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Quinazolin-4(3)-one derivatives have attracted considerable attention in the pharmacological profiling of therapeutic drug targets. The present article reveals the development of arylidene-based quinazolin-4(3)-one motifs as potential antimicrobial drug candidates. The synthetic pathway was initiated through thermal cyclization of acetic anhydride on anthranilic acid to produce 2-methyl-4H-3,1-benzoxazan-4-one 1, which (upon condensation with hydrazine hydrate) gave 3-amino-2-methylquinazolin-4(3)-one 2.

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Personalizing medicine in Africa: current state, progress and challenges.

Front Genet

September 2023

Covenant Applied Informatics and Communication, Africa Centre of Excellence (CApIC-ACE), Covenant University, Ota, Ogun State, Nigeria.

Personalized medicine has been identified as a powerful tool for addressing the myriad of health issues facing different health systems globally. Although recent studies have expanded our understanding of how different factors such as genetics and the environment play significant roles in affecting the health of individuals, there are still several other issues affecting their translation into personalizing health interventions globally. Since African populations have demonstrated huge genetic diversity, there is a significant need to apply the concepts of personalized medicine to overcome various African-specific health challenges.

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Computational prediction of absolute essential genes using machine learning has gained wide attention in recent years. However, essential genes are mostly conditional and not absolute. Experimental techniques provide a reliable approach of identifying conditionally essential genes; however, experimental methods are laborious, time and resource consuming, hence computational techniques have been used to complement the experimental methods.

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Polygenic Risk Score in African populations: progress and challenges.

F1000Res

June 2023

Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, 112212, Nigeria.

Polygenic Risk Score (PRS) analysis is a method that predicts the genetic risk of an individual towards targeted traits. Even when there are no significant markers, it gives evidence of a genetic effect beyond the results of Genome-Wide Association Studies (GWAS). Moreover, it selects  single nucleotide polymorphisms (SNPs) that  contribute to the disease with low effect size  making it more precise at individual level risk prediction.

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Tandem repeats (TRs) represent one of the largest sources of genetic variation in humans and are implicated in a range of phenotypes. Here we present a deep characterization of TR variation based on high coverage whole genome sequencing from 3,550 diverse individuals from the 1000 Genomes Project and H3Africa cohorts. We develop a method, EnsembleTR, to integrate genotypes from four separate methods resulting in high-quality genotypes at more than 1.

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Therapeutic intervention in cyclin-dependent kinase-like 5 (CDKL5) deficiency disorders (CDDs) has remained a concern over the years. Recent advances into the mechanistic interplay of signalling pathways has revealed the role of deficient tropomyosin receptor kinase B (TrkB)/phospholipase C γ1 signalling cascade in CDD. Novel findings showed that in vivo administration of a TrkB agonist, 7,8-dihydroxyflavone (7,8-DHF), resulted in a remarkable reversal in the molecular pathologic mechanisms underlying CDD.

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() 5-aminolevulinic acid synthase (5-ALAS) is an essential enzyme with high selectivity during liver stage development, signifying its potential as a prophylactic antimalarial drug target. The aim of this study was to identify important potential lead compounds which can serve as inhibitors of 5-ALAS using pharmacophore modeling, virtual screening, qualitative structural assessment, ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) evaluation and molecular dynamics simulation. The best model of the tertiary structure of 5-ALAS was obtained using MolProbity, while the following databases were explored for the pharmacophore-based virtual screening: CHEMBL, ChemDiv, ChemSpace, MCULE, MCULE-ULTIMATE, MolPort, NCI Open Chemical Repository, LabNetwork and ZINC databases.

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Quinoline is one of the most common nitrogen-containing heterocycles owing to its fascinating pharmacological properties and synthetic value in organic and pharmaceutical chemistry. Functionalization of this moiety at different positions has allowed for varying pharmacological activities of its derivative. Several publications over the last few decades have specified various methods of synthesis.

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Motivation: Post-genome-wide association studies (pGWAS) analysis is designed to decipher the functional consequences of significant single-nucleotide polymorphisms (SNPs) in the era of GWAS. This can be translated into research insights and clinical benefits such as the effectiveness of strategies for disease screening, treatment and prevention. However, the setup of pGWAS (pGWAS) tools can be quite complicated, and it mostly requires big data.

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Trehalase inhibitors are considered safe alternatives for insecticides and fungicides. However, there are no studies testing these compounds on a major vector of human malaria. This study predicted the three-dimensional structure of trehalase (Tre) and identified potential inhibitors using molecular docking and molecular dynamics methods.

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The second conference of the Nigerian Bioinformatics and Genomics Network (NBGN21) was held from October 11 to October 13, 2021. The event was organized by the Nigerian Bioinformatics and Genomics Network. A 1-day genomic analysis workshop on genome-wide association study and polygenic risk score analysis was organized as part of the conference.

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Genome-wide association studies (GWAS) provide  huge information on statistically significant single-nucleotide polymorphisms (SNPs) associated with various human complex traits and diseases. By performing GWAS studies, scientists have successfully identified the association of hundreds of thousands to  millions of SNPs to a single phenotype. Moreover, the association of some SNPs with rare diseases has been intensively tested.

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Identifying essential genes across eukaryotes by machine learning.

NAR Genom Bioinform

December 2021

Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany.

Identifying essential genes on a genome scale is resource intensive and has been performed for only a few eukaryotes. For less studied organisms essentiality might be predicted by gene homology. However, this approach cannot be applied to non-conserved genes.

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Predicting host dependency factors of pathogens in using machine learning.

Comput Struct Biotechnol J

August 2021

Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany.

Pathogens causing infections, and particularly when invading the host cells, require the host cell machinery for efficient regeneration and proliferation during infection. For their life cycle, host proteins are needed and these Host Dependency Factors (HDF) may serve as therapeutic targets. Several attempts have approached screening for HDF producing large lists of potential HDF with, however, only marginal overlap.

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