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Abstract

Malaria is a parasitic disease that has caused suffering to humans since ancient times and remains a major public health concern in tropical and subtropical regions.The development of novel antimalarials therefore becomes of utmost importance by targeting aspartic protease. The computational study utilized a molecular docking approach to identify hit compounds. In this study a molecular docking approach was employed to identify potential hit compounds. The molecular docking analysis yielded three hit compounds CMNPD229, ZINC000000018635, and ZINC000005425464 along with the reference drug chloroquine, with binding energy scores of -8.1 kcal/mol, -8.0 kcal/mol, -7.8 kcal/mol, and − 6.8 kcal/mol, respectively. Subsequently density function theory (DFT) was performed. Afterward, the protein-ligand (PL) complexes were subjected to molecular dynamic simulation (MDS) to identify the stability and rigidity of the complexes in a fleeting and dynamic setting. The complex CMNPD229 exhibited good stability followed by ZINC000000018635, ZINC000005425464, and the Control. The compounds showed good MM-PBSA/GBSA, WaterSwap, and entropy energy values. The calculated MM-PBSA/GBSA binding free energy scores were − 120.78 kcal/mol, -107.16 kcal/mol, -91.00 kcal/mol, and − 97.49 kcal/mol for CMNPD229, ZINC000000018635, ZINC000005425464, and the reference drug, respectively.Additionally, salt bridge analysis and secondary structure evaluation revealed that CMNPD229 formed the highest number of interactions (Glu290-Arg23 and Glu305-Lys306), indicating its stability as a potential drug candidate. This study suggests that CMNPD229 holds promise as a potent antimalarial drug by effectively inhibiting Plasmodium falciparum and Plasmodium vivax aspartic proteases.

Details

1009240
Title
Computational identification of aspartic protease inhibitors for antimalarial drug development against Plasmodium Vivax
Author
Alruwaili, Muharib 1 ; Alhassan, Hassan H. 1 ; Almutary, Hayfa 2 ; Tahir ul Qamar, Muhammad 3 

 Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, 72388, Sakaka, Al-Jouf, Saudi Arabia (ROR: https://ror.org/02zsyt821) (GRID: grid.440748.b) (ISNI: 0000 0004 1756 6705) 
 Medical Surgical Nursing Department, Faculty of Nursing, King Abdulaziz University, Jeddah, Saudi Arabia (ROR: https://ror.org/02ma4wv74) (GRID: grid.412125.1) (ISNI: 0000 0001 0619 1117) 
 Department of Bioinformatics and Biotechnology, Government College University Faisalabad (GCUF), 38000, Faisalabad, Pakistan (ROR: https://ror.org/051zgra59) (GRID: grid.411786.d) (ISNI: 0000 0004 0637 891X) 
Volume
15
Issue
1
Pages
14824
Number of pages
21
Publication year
2025
Publication date
2025
Section
Article
Publisher
Nature Publishing Group
Place of publication
London
Country of publication
United States
Publication subject
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-04-28
Milestone dates
2025-04-11 (Registration); 2024-11-28 (Received); 2025-04-11 (Accepted)
Publication history
 
 
   First posting date
28 Apr 2025
ProQuest document ID
3246376249
Document URL
https://www.proquest.com/scholarly-journals/computational-identification-aspartic-protease/docview/3246376249/se-2?accountid=208611
Copyright
corrected publication 2025. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the "License"). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-09-04
Database
2 databases
  • Coronavirus Research Database
  • ProQuest One Academic