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The widespread emergence of antimalarial drug resistance has created a major threat to public health. Malaria is a life‐threatening infectious disease caused by Plasmodium spp., which includes Apicoplast DNA polymerase and Plasmodium falciparum cysteine protease falcipain‐2. These components play a critical role in their life cycle and metabolic pathway, and are involved in the breakdown of erythrocyte hemoglobin in the host, making them promising targets for anti‐malarial drug design. Our current study has been designed to explore the potential inhibitors from haplopine derivatives against these two targets using an in silico approach. A total of nine haplopine derivatives were used to perform molecular docking, and the results revealed that Ligands 03 and 05 showed strong binding affinity compared to the control compound atovaquone. Furthermore, these ligand‐protein complexes underwent molecular dynamics simulations, and the results demonstrated that the complexes maintained strong stability in terms of RMSD (root mean square deviation), RMSF (root mean square fluctuation), and Rg (radius of gyration) over a 100 ns simulation period. Additionally, PCA (principal component analysis) analysis and the dynamic cross‐correlation matrix showed positive outcomes for the protein‐ligand complexes. Moreover, the compounds exhibited no violations of the Lipinski rule, and ADMET (absorption, distribution, metabolism, excretion, and toxicity) predictions yielded positive results without indicating any toxicity. Finally, density functional theory (DFT) and molecular electrostatic potential calculations were conducted, revealing that the mentioned derivatives exhibited better stability and outstanding performance. Overall, this computational approach suggests that these haplopine derivatives could serve as a potential source for developing new, effective antimalarial drugs to combat malaria. However, further in vitro or in vivo studies might be conducted to determine their actual effectiveness. [ABSTRACT FROM AUTHOR]

Tick-borne Babesiosis is a parasitic infection caused by Babesia microti that can infect both animals and humans and may spread by tick, blood transfusions, and organ transplantation. The current therapeutic options for B. microti are limited, and drug resistance is a concern. This study proposes using computational drug design approaches to find and design an effective drug against B. microti. The study investigated the potentiality of nine natural compounds against the pathogenic human B. microti parasite and identified Vasicinone and Evodiamine as the most promising drugs. The ligand structures were optimized using density functional theory, molecular docking, molecular dynamics simulations, quantum mechanics such as HOMO-LUMO, druglikeness and theoretical absorption, distribution, metabolism, excretion, and toxicity (ADMET), and pharmacokinetics characteristics performed. The results showed that Vasicinone (-8.6 kcal/mol and -7.8 kcal/mol) and Evodiamine (-8.7 kcal/mol and -8.5 kcal/mol) had the highest binding energy and anti-parasitic activity against B. microti lactate dehydrogenase and B. microti lactate dehydrogenase apo form. The strongest binding energy was reported by Vasicinone and Evodiamine; the compounds were evaluated through molecular dynamics simulation at 100 ns, and their stability when they form complexes with the targeted receptors was determined. Finally, the pkCSM web server is employed to predict the ADMET qualities of specific molecules, which can help prevent negative effects that arise from taking the treatment. The SwissADME web server is used to assess the Lipinski rule of five and druglikeness properties including topological polar surface area and bioavailability. The Lipinski rule is used to estimate significant drug-likeness. The theoretical pharmacokinetics analysis and drug-likeness of the selected compounds are confirmed to be accepted by the Lipinski rule and have better ADMET features. Thus, to confirm their experimental value, these mentioned molecules should be suggested to carry out in wet lab, pre-clinical, and clinical levels. [ABSTRACT FROM AUTHOR]