International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 08 | Aug 2023
p-ISSN: 2395-0072
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Development Of Antimalarial Drugs by Computational Analysis of Malarial Parasite Ligands Anshul1, Sanjeev Sharma2 Research Scholar, Department of Chemistry1, Om Sterling Global University, Hisar, Haryana (India)1 Associate professor, Department of Chemistry2, Om Sterling Global University, Hisar, Haryana (India)2 ---------------------------------------------------------------------------***------------------------------------------------------------------------molecular targets. The primary objective of this study is to Abstract: This research paper explores the application of examine the efficacy of computational approaches in expediting the process of discovering new antimalarial drugs [2].
computational analysis in the investigation of different ligands that target malarial parasites, with the objective of advancing the development of antimalarial drugs. This study aims to identify possible lead compounds with efficacy against malarial parasites by employing several computational tools, such as molecular docking, virtual screening, and quantitative structure-activity relationship (QSAR) modelling. The findings provided in this study provide valuable insights into the interactions between ligands and receptors, as well as the binding affinities and predictive models associated with these interactions. These results contribute significantly to the current efforts aimed at treating malaria.
Keywords:
Malaria, plasmodium molecular docking, virtual screening.
2. METHODS OF COMPUTING 2.1 Docking of Molecules: Theory and Practice: Molecular docking, an essential component of structurebased drug design, facilitates the simulation of the interaction between ligands and receptor binding sites. Docking algorithms employ a methodical search strategy in order to ascertain the most advantageous binding conformations and orientations. By utilizing the analysis of binding energies, scholars can examine the propensity and specificity of ligands[3].
falciparum,QASR,
2.2 Strategies for Ranking and Choosing Ligands in Computer-Based Screening: In order to identify potentially valuable compounds for further investigation, researchers employ a technique known as "virtual screening," which involves the computational analysis of extensive libraries of chemical compounds. Compounds undergo filtration and prioritization processes, wherein their capacity to interact with target proteins is assessed using diverse screening methodologies, including structure-based and ligand-based approaches[4].
1. INTRODUCTION 1.1 Background and Importance: Malaria, a disease caused by Plasmodium parasites, continues to pose a substantial worldwide health concern, with a special emphasis on places characterized by tropical and subtropical climates. The prioritization of the development of efficacious antimalarial medications holds significant significance in mitigating the adverse effects of the disease on both human well-being and societal welfare. Nevertheless, the rise of drug-resistant strains of parasites has emphasized the necessity for novel strategies, such as computational techniques, to accelerate the process of drug discovery[1].
2.3 Interactions Between Ligands and Targets QSAR modeling's projections of the outcome: It is now possible to create predictions regarding the behaviours of biological things by integrating molecular features with quantitative structure-activity relationship (QSAR) models. This makes it possible to forecast how biological entities will behave. Quantitative structure-activity relationship, or QSAR, models provide useful insights into the interactions that occur between ligands and targets. These models also make it possible to optimize lead compounds by analyzing connections between chemical structure and activity[5].
1.2 Reasons for Using Computational Methods in the Discovery of Drugs: Conventional methods employed in the process of drug development are frequently characterized by their protracted duration and substantial allocation of resources. Computational methodologies provide a supplementary approach for efficiently evaluating and forecasting the binding affinity of prospective pharmaceutical candidates towards bio
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