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Item Targeting invasion-associated proteins PfSUB2 and PfTRAMP in Plasmodium falciparum: identification of potential inhibitors via molecular docking(BMC Infectious Diseases, 2025) Okafor, Esther. O.; Bella-Omunagbe, Mercy; Elugbadebo, Temitope; Dokunmu, Titilope M.; Adebiyi, EzekielPlasmodium falciparum subtilisin-like protease 2 (PfSUB2) is responsible for processing Plasmodium falciparum thrombospondin-related apical merozoite protein (PfTRAMP). These proteins are essential for asexual blood stage growth and RBC invasion and have, therefore, been identified as potential drug targets. This study predicted the three-dimensional structure of PfSUB2 and PfTRAMP and identified potential inhibitors using molecular docking methods. Five hundred nineteen compounds were docked against both proteins with AutoDock Vina in PyRx. Compounds 139,974,934 and 154,414,021 exhibited better binding affinities when compared to the standard inhibitors, PMSF, which highlights them as suitable inhibitors and potential antimalarials targeting PfTRAMP and PfSUB2. It also highlights 155,204,487 as a compound with dual antimalarial target potential, exhibiting a better binding affinity to PfTRAMP and PfSUB2. The study recommends 139,974,934, 154,414,021, and 155,204,487 as possible compounds for antimalarial drug development.Item Ex Vivo Molecular Studies and In Silico Small Molecule Inhibition of Plasmodium falciparum Bromodomain Protein 1(Drugs Drug Candidates, 2025-06-22) Oladejo, David O.; Dokunmu, Titilope M.; Oduselu, Gbolahan O.; Oladejo, Daniel O.; Ogunlana, Olubanke O.; Iweala, Emeka E. J.Background: Malaria remains a significant global health burden, particularly in sub- Saharan Africa, accounting for high rates of illness and death. The growing resistance to frontline antimalarial therapies underscores the urgent need for novel drug targets and therapeutics. Bromodomain-containing proteins, which regulate gene expression through chromatin remodeling, have gained attention as potential targets. Plasmodium falciparum bromodomain protein 1 (Pf BDP1), a 55 kDa nuclear protein, plays a key role in recognizing acetylated lysine residues and facilitating transcription during parasite development. Methods: This study investigated ex vivo PfBDP1 gene mutations and identified potential small molecule inhibitors using computational approaches. Malariapositive blood samples were collected. Genomic DNA was extracted, assessed for quality, and amplified using Pf BDP1-specific primers. DNA sequencing and alignment were performed to determine single-nucleotide polymorphism (SNP). Structural modeling used the PfBDP1 crystal structure (PDB ID: 7M97), and active site identification was conducted using CASTp 3.0. Virtual screening and pharmacophore modeling were performed using Pharmit and AutoDock Vina, followed by ADME/toxicity evaluations with SwissADME, OSIRIS, and Discovery Studio. GROMACS was used for 100 ns molecular dynamics simulations. Results: The malaria prevalence rate stood at 12.24%, and the sample size was 165. Sequencing results revealed conserved PfBDP1 gene sequences compared to the 3D7 reference strain. Virtual screening identified nine lead compounds with binding affinities ranging from −9.8 to −10.7 kcal/mol. Of these, CHEMBL2216838 had a binding affinity of −9.9 kcal/mol, with post-screening predictions of favorable drug-likeness (8.60), a high drug score (0.78), superior pharmacokinetics, and a low toxicity profile compared to chloroquine. Molecular dynamics simulations confirmed its stable interaction within the PfBDP1 active site. Conclusions: Overall, this study makes a significant contribution to the ongoing search for novel antimalarial drug targets by providing both molecular and computational evidence for PfBDP1 as a promising therapeutic target. The prediction of CHEMBL2216838 as a lead compound with favorable binding affinity, drug-likeness, and safety profile, surpassing those of existing drugs like chloroquine, sets the stage for preclinical validation and further structure-based drug design efforts. These findings are supported by prior experimental evidence showing significant parasite inhibition and gene suppression capability of predicted hits.Item Plasmodium falciparum Transketolase as a Drug Target in Malaria: A Review of Current Research and Future Perspectives(Journal of Science and Technology, Research Vol. 7, Special Issue: Landmark University International Conference, 2025) Orogun, Yetunde; Fadare, Olatomide; Bajepade, Tobilola; Raimi, Olawale; Ogunlana, OlubankeMalaria is a severe infectious disease caused by Plasmodium species, primarily Plasmodium falciparum, which accounts for the most deaths globally. Africa bears the heaviest malaria burden, with countries like Nigeria, Congo, and Mozambique contributing to a significant percentage of global cases. It is transmitted through the bite of an infected female Anopheles mosquito. The fight against malaria has been challenged by the emergence of resistance to most antimalarial drugs, including Artemisinin-based Combination Therapies (ACTs). This highlights the urgent need for novel drug targets. Transketolase (Tk), a key enzyme in the pentose phosphate pathway (PPP) non-oxidative branch, plays a vital role in cellular metabolism and has been identified to support parasite survival. Plasmodium falciparum transketolase (PfTk) has been identified as an emerging drug target due to its essential role in the parasite's metabolism and low structural homology with human transketolase (HTk). This review aims to provide an overview of PfTk as a potential anti-malarial drug target and to highlight the key research direction for future drug development. It examines the current research on PfTk as a therapeutic target, focusing on its biochemical properties, structural and functional characteristics, and potential inhibitors' development as a therapeutic strategy while exploring future perspectives.Item SINGLE NUCLEOTIDE POLYMORPHISMS OF Pfdhfr RESISTANCE GENE AMONG SYMPTOMATIC PATIENTS’ ISOLATES FROM SELECTED HOSPITALS IN IFO LGA, OGUN STATE(Covenant University Ota, 2025-10) SULE, Queen Elizabeth; Covenant University DissertationMalaria remains a primary universal health concern, particularly in endemic areas where drug resistance poses a serious threat to the effectiveness of key treatment and prevention strategies. Sulfadoxine-pyrimethamine (SP), commonly used for malaria prophylaxis, is increasingly compromised by resistance associated with mutations in the Plasmodium falciparum dihydrofolate reductase (Pfdhfr) gene. This study aimed to assess the prevalence of P. falciparum infection and identify the single-nucleotide polymorphisms (SNPs) in the Pfdhfr resistance gene among symptomatic patients in Ifo Local Government Area, Ogun State, Nigeria. Five hundred patients with severe P. falciparum infection were recruited, and demographic data were recorded. Blood samples were analysed for P. falciparum stages and parasitemia levels using microscopy. DNA was extracted from samples with high parasitemia and genotyped for Pfdhfr mutations using PCR, followed by visualisation on 1% agarose gel electrophoresis. Microscopy confirmed P. falciparum malaria in 300 patients (60%). A significantly higher prevalence (71.05%) was recorded in the 0–4 years’ age group, while males accounted for 64.31% of cases (p < 0.05). Parasitemia levels (greater than 200 parasites/100 μL) were more pronounced in males than in females, and were highest among individuals aged 0–4 years. Among the 10.67% Pfdhfr genotypes identified, males exhibited a higher frequency (6.0%) than females. The overall prevalence of pfdhfr SNPs in N51I, C59R, S108, and I64L was (96%), (96%), (100%), and (0%), respectively. tripple mutant halotype (N51I+ C59R+S108), prevance was 92%. Males have a higher mutation rate (60%) than females (40%). The overall prevalence of pfdhfr SNPs in N51I, C59R, S108, and I164L was (96%), (96%), (100%), and (0%), respectively. tripple mutant halotype (N51I+ C59R+S108), prevance was 92%. Males have a higher mutation rate (60%) than females (40%). Also, individuals aged 0-4 years (20%) and 15-20 years (20%) show higher SNPs than the other age groups. The study highlights a high prevalence of P. falciparum and emerging Pfdhfr resistance mutations, emphasising the need for continuous surveillance and targeted interventions in malaria-endemic regions, such as Ifo LGA, Nigeria.Item EVALUATION OF SYNTHETIC FLAVONOID BASED COMPOUNDS AS INHIBITORS OF Plasmodium falciparum TRANSKETOLASE(Covenant University Ota, 2025-09) OROGUN, Yetunde Grace; Covenant University DissertationMalaria, primarily attributed to Plasmodium falciparum, remains a significant contributor to global mortality, with Africa experiencing the greatest burden, particularly in countries such as Nigeria, the Democratic Republic of Congo, and Mozambique. The rise in resistance to present therapies, including Artemisinin-based Combination Therapies (ACTs), underscores the urgent need for novel drug targets. Transketolase, a thiamine-dependent enzyme in the non-oxidative arm of the pentose phosphate pathway, is vital for parasite metabolism and structurally distinct from the human enzyme, making it a promising selective target. Twenty synthetic flavonoid-based compounds were evaluated as potential inhibitors of P. falciparum transketolase (PfTk). Molecular docking revealed strong binding affinities, while ADMET profiling showed that most compounds complied with Lipinski’s rule. Notably, Compounds 6, 7, 11, and 13 were predicted to be orally bioavailable with favorable pharmacokinetic and drug-likeness properties. The compounds were further tested in vitro against PfTk and human transketolase (hTk), with oxythiamine as the positive control, and cytotoxicity was assessed using hemolysis assays on human red blood cells. The results demonstrated that several compounds exhibited high potency and selective inhibition of PfTk with minimal activity on hTk. Among them, Compounds 6, 7, and 10 emerged as the most promising leads, combining high selectivity, oral bioavailability, and favorable safety margins. Additionally, Compounds 11 and 13, analogues of Compound 10, showed good drug-likeness and oral bioavailability, indicating potential for structural optimization. Hemolysis assays confirmed minimal red blood cell lysis across all compounds, supporting their safety. In conclusion, this study validates PfTk as a viable drug target and identifies Compounds 6, 7, and 10 as strong lead candidates, with Compounds 11 and 13 as promising analogues for further optimization and development of safe, effective antimalarial agents.Item DEVELOPMENT OF A MULTI-LABEL CLASSIFIER FOR PREDICTING GENETIC MARKERS ASSOCIATED WITH MULTI-DRUG RESISTANCE IN Plasmodium falciparum STRAINS(Covenant University Ota, 2025-08) OGUNDIMU, Temitayo Ayomikun; Covenant University DissertationMalaria is an infectious disease of global health importance caused by Plasmodium falciparum. It is highly complicated by parasite’s ability to gain resistance to multiple antimalarial drugs simultaneously, a phenomenon known as multidrug resistance (MDR). Single-label models only predict resistance to one drug at a time and as such would not capture these complex resistance patterns, limiting their utility for real-world surveillance. To bridge this gap, this study developed and evaluated four advanced multi-label classification models: Random Forest with Binary Relevance (RFDTBR), Ensemble of Classifier Chains (ECCJ48), Ensemble of Binary Relevance (EBRJ48), and a Backpropagation Neural Network (BPNN), using genomic and phenotypic data for five key antimalarials. Notably, RFDTBR and EBRJ48 outperformed others in predicting exact MDR profiles, while BPNN performed faster compared to the other models. Sulfadoxine-Pyrimethamine had the lowest performance across the models. Specific genomic features consistently emerged as key predictive factors across all models. These findings demonstrate the value of multi-label learning for comprehensive MDR prediction. Also, effective models and genomic regions were identified, warranting further investigation, thereby paving the way for improved resistance surveillanceItem GENOME-WIDE IDENTIFICATION OF SHORT TANDEM REPEATS ASSOCIATED WITH MULTI-DRUG RESISTANCE IN Plasmodium falciparum STRAINS(Covenant University Ota, 2025-08) EMMANUELLA EKURI MAMTUMAMBOH; Covenant University DissertationAntimalarial drug resistance in Plasmodium falciparum threatens global malaria control, and while single nucleotide polymorphisms (SNPs) are well-studied, the role of short tandem repeats (STRs) remains underexplored. This study investigates the contribution of pathogenic STRs to drug resistance using STR genotypes from HipSTR, phenotypic resistance data, and machine learning models. Allele frequency analysis revealed consistently lower alternative allele frequencies in resistant strains across all 14 chromosomes, with strong selective signals on chromosomes 2, 3, 4, 8, and 13. Population differentiation analyses (PCA, FST) identified key resistance loci near PfKelch13 and plasmepsin 2/3, along with potential novel resistance regions. A logistic regression model trained on STR alleles achieved perfect classification (AUC = 1.00), demonstrating the strong predictive power of STRs in distinguishing resistant from sensitive parasites. Top STRs showed both known and novel associations with resistance, reinforcing the polygenic nature of antimalarial resistance. These findings establish STRs as important genetic markers for resistance surveillance and highlight their potential utility in guiding malaria treatment strategies.Item AN OPTIMIZED DEEP-FOREST MODEL USING A MODIFIED DIFFERENTIAL EVOLUTION OPTIMIZATION ALGORITHM: A CASE OF HOST-PATHOGEN PROTEIN-PROTEIN INTERACTION PREDICTION(Covenant University Ota, 2025-04) EMMANUEL JERRY DAUDA; Covenant University ThesisDeep forest is an advanced ensemble learning technique that employs forest structures within a cascade framework, leveraging deep architectures to enhance predictive performance by adaptively capturing high-level feature representations. Despite its promise, deep forest models often face critical challenges, including manual hyperparameter optimization and inefficiencies in computational time and memory usage. To address these limitations, Bayesian optimization, a prominent model-based hyperparameter optimization method, is frequently utilized, with Differential Evolution (DE) serving as the acquisition function in recent implementations. However, DE's reliance on random index selection for constructing donor vectors introduces inefficiencies, as suboptimal or redundant indices may hinder the search for optimal solutions. This study introduces an optimized deep forest algorithm that integrates a modified DE acquisition function into Bayesian optimization to improve host-pathogen protein-protein interaction (HPPPI) prediction. The modified DE approach incorporates a weighted and adaptive donor vector selection mechanism, enhancing the exploration and exploitation of hyperparameter configurations. Performance evaluations using 10-fold cross-validation on human–Plasmodium falciparum (PF) protein sequence datasets sourced from reputable databases demonstrated the model's superiority over traditional Bayesian optimization, genetic algorithms, evolutionary strategies, and conventional machine learning models. The optimized framework achieved an accuracy of 89.3%, sensitivity of 85.4%, precision of 91.6%, and Area Under the Receiver Operating Characteristic Curve (AUROC) of 89.1%, surpassing existing methods. Additionally, the model exhibited reduced computational time and memory usage. The optimized DF was deployed as a web-based pipeline, DFH3PI (Deep Forest Host-Pathogen Protein-Protein Interaction Prediction), which successfully identified three potential human–PF PPIs previously classified as non-interacting: P50250–P08319, Q8ILI6–O94813, and Q7KQL3–Q96GQ7. These findings not only present the potential of DFH3PI for advancing HPPPI prediction but also establish the optimized deep forest framework as a transformative tool in computational biology. Its ability to combine accuracy and efficiency marks a significant step forward in predictive modeling.