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Related Concept Videos

Malaria01:29

Malaria

Malaria pathogenesis in humans reflects a delicate interplay between parasite biology and host response. Clinical illness reflects a host’s immune response to the parasite’s asexual replication cycle, which is often asymptomatic in individuals with partial immunity. From the parasite's perspective, transmission between mosquito and human with minimal host pathology is evolutionarily advantageous. Among the six Plasmodium species infecting humans, P. falciparum and P. vivax dominate in global...

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Methods to Investigate the Regulatory Role of Small RNAs and Ribosomal Occupancy of Plasmodium falciparum
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MicroRNA Guided In Silico Drug Repositioning for Malaria.

Sowmya R Prabhu1, Akshay Pramod Ware2, Kapaettu Satyamoorthy3,4

  • 1Department of Biotechnology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.

Acta Parasitologica
|September 23, 2024
PubMed
Summary
This summary is machine-generated.

Drug repurposing offers a novel strategy against malaria. This study computationally identified beta-adrenergic drugs, like propranolol, as potential antimalarials by analyzing microRNA interactions, paving the way for new malaria treatments.

Keywords:
PlasmodiumDrug repurposingMalariaMicroRNAMultidrug resistance

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Area of Science:

  • Computational biology
  • Pharmacology
  • Genomics

Background:

  • Rising Plasmodium resistance and vaccine limitations necessitate novel malaria interventions.
  • Drug repurposing accelerates treatment development by identifying new uses for existing drugs.
  • MicroRNAs (miRNAs) are increasingly recognized as therapeutic targets and regulators of drug action.

Purpose of the Study:

  • To computationally predict drug-disease relationships via miRNAs for antimalarial drug repurposing.
  • To develop a model integrating miRNA-drug and miRNA-disease interactions to identify potential antimalarials.
  • To explore the role of miRNAs in establishing novel drug-disease connections for malaria.

Main Methods:

  • Constructed a drug-drug interaction network using curated drug-miRNA data (Pharmaco-miR, SM2miR).
  • Acquired drug-disease relations from the Comparative Toxicogenomics Database (CTD).
  • Applied the Random Walk with Restart (RWR) algorithm and analyzed miRNA-disease associations (HMDD) to predict drug repurposing candidates.

Main Results:

  • Topological network analysis identified beta-adrenergic drugs as potential antimalarials.
  • Literature case studies validated the model's predictive performance.
  • Propranolol, metoprolol, epinephrine, and atenolol were highlighted as promising candidates for malaria treatment.

Conclusions:

  • A computational model was developed to predict beta-adrenergic drugs for malaria repurposing.
  • The model leverages shared miRNA partners to establish mechanistic links between drugs and diseases.
  • This approach elucidates miRNA involvement in novel drug-disease relationships and offers leads for alternative antimalarials.