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Thandivel S, Rajan P, Gunasekar T, Arjunan A, Khute S, Kareti SR, Paranthaman S. In silico molecular docking and dynamic simulation of anti-cholinesterase compounds from the extract of Catunaregam spinosa for possible treatment of Alzheimer's disease. Heliyon 2024; 10:e27880. [PMID: 38560123 PMCID: PMC10981039 DOI: 10.1016/j.heliyon.2024.e27880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 03/01/2024] [Accepted: 03/07/2024] [Indexed: 04/04/2024] Open
Abstract
Alzheimer's disease (AD), is characterized by a progressive loss of cognitive abilities as well as behavioral symptoms including disorientation, trouble solving problems, personality and mood changes. Acetylcholinesterase (AChE) is a promising target for symptomatic improvement in AD due to its consistent and early cholinergic deficit. This research has investigated the potential compounds from Catunaregam spinosa as AChE inhibitors as a treatment option for AD, aiming to enhance cholinergic neurotransmission and alleviate cognitive decline. Tacrine, the FDA's first approved treatment for AD, is no longer in use due to its hepatotoxicity. Box-Behnken design (BBD) modelling was used to optimise the ultrasonic extraction of alkaloids from the dried fruits of C. spinosa. GC-MS analysis revealed the presence of ninety phytoconstituents in the extract. Among them, eighty-nine new phytoconstituents are reported in this plant fruit for the first time. Out of ninety phytoconstituents, eight phytoconstituents showed the best binding affinity against the AChE enzyme, i.e., PDB IDs 1GQR, 1QTI and 4PQE of AD targets using iGEMDOCK. The lead hits were tested for their drug-like properties and atomistic binding mechanisms using in silico ADMET prediction, LigPlot analysis, and molecular dynamics simulation. The results suggest four compounds such as 1,4,7,10,13,16-hexaoxacyclooctadecane; butanoic acid, 3-methyl-2-[(phenylmethoxy)imino]-, trime; butane-1,2,3,4-tetraol; and D-(+)-ribonic acid.gamma-lactone as potent inhibitors of AChE for the possible treatment of AD.
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Affiliation(s)
- Sathish Thandivel
- Department of Pharmacognosy, Sri Shanmugha College of Pharmacy, Salem district, Sankari, 637 304, Tamil Nadu, India
| | - Poovarasan Rajan
- Department of Pharmacognosy, Sri Shanmugha College of Pharmacy, Salem district, Sankari, 637 304, Tamil Nadu, India
| | - Tamizharasan Gunasekar
- Department of Pharmacognosy, Sri Shanmugha College of Pharmacy, Salem district, Sankari, 637 304, Tamil Nadu, India
| | - Abisek Arjunan
- Department of Pharmacognosy, Sri Shanmugha College of Pharmacy, Salem district, Sankari, 637 304, Tamil Nadu, India
| | - Sulekha Khute
- Institute of Pharmacy, Pandit Ravishankar Shukla University, Raipur, 492 010, Chhattisgarh, India
| | - Srinivasa Rao Kareti
- Department of Pharmacy, Indira Gandhi National Tribal University, Amarkantak, 484 887, Madhya Pradesh, India
| | - Subash Paranthaman
- Department of Pharmacognosy, Sri Shanmugha College of Pharmacy, Salem district, Sankari, 637 304, Tamil Nadu, India
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Girdhar N, Yadav V, Kumari N, Subbarao N, Krishnamachari A. Insilico screening to identify novel inhibitors targeting 30S ribosomal protein S12 in meningitis-causing organism ' Elizabethkingia meningoseptica'. J Biomol Struct Dyn 2024:1-12. [PMID: 38407814 DOI: 10.1080/07391102.2024.2321511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 02/15/2024] [Indexed: 02/27/2024]
Abstract
The current trend in biomedical research is on prioritizing infections based on multidrug resistance. Elizabethkingia meningoseptica, a nosocomial infection-causing organism emerging from Neonatal Intensive Care Units (NICUs), leads to neonatal meningitis and sepsis resulting in severe illness, and, in some cases, fatal. Finding a solution remains challenging due to limited prior work. Translational S12 ribosomal proteins play a crucial role in decoding the codon-anticodon helix, which is essential for the survival of E. meningoseptica. These proteins do not exhibit significant similarity with humans, making them potential drug targets. An in silico study aims to identify specific inhibitors for E. meningoseptica ribosomal proteins among known bioactive compounds targeting prokaryotic 30S ribosomal protein. A 3D model of the 7JIL_h protein from Flavobacterium johnsoniae, showing 90% sequence similarity with the target protein was generated using SWISS-MODEL software. The model was validated through Molprobity v4.4, VERIFY 3D, Errata, and ProSA analysis, confirming conserved residues of the target protein. Insilico screening of known bioactive compounds and their analogs identified potential ligands for the target protein. Molecular Docking and post-docking analysis assessed the stability of the protein-ligand complexes among the shortlisted compounds. The top two compounds with high Gold fitness scores and low predicted binding energy underwent MD simulation and further estimation of free binding energy using the MM_PBSA module. These computationally shortlisted compounds, namely chEMBL 1323619 and chEMBL 312490 may be considered for future in-vivo studies as potential inhibitors against the modeled 30S ribosomal protein S12 of E. meningoseptica.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Neha Girdhar
- Department of Bioscience and Biotechnology, Banasthali Vidyapith, Rajasthan, India
| | - Vikas Yadav
- School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India
| | - Nilima Kumari
- Department of Bioscience and Biotechnology, Banasthali Vidyapith, Rajasthan, India
| | - Naidu Subbarao
- School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India
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Xie S, Yang G, Wu J, Jiang L, Yuan C, Xu P, Huang M, Liu Y, Li J. In silico screening of natural products as uPAR inhibitors via multiple structure-based docking and molecular dynamics simulations. J Biomol Struct Dyn 2023:1-12. [PMID: 38111151 DOI: 10.1080/07391102.2023.2295386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 12/07/2023] [Indexed: 12/20/2023]
Abstract
Cancer remains one of the most pressing challenges to global healthcare, exerting a significant impact on patient life expectancy. Cancer metastasis is a critical determinant of the lethality and treatment resistance of cancer. The urokinase-type plasminogen activator receptor (uPAR) shows great potential as a target for anticancer and antimetastatic therapies. In this work, we aimed to identify potential uPAR inhibitors by structural dynamics-based virtual screenings against a natural product library on four representative apo-uPAR structural models recently derived from long-timescale molecular dynamics (MD) simulations. Fifteen potential inhibitors (NP1-NP15) were initially identified through molecular docking, consensus scoring, and visual inspection. Subsequently, we employed MD-based molecular mechanics-generalized Born surface area (MM-GBSA) calculations to evaluate their binding affinities to uPAR. Structural dynamics analyses further indicated that all of the top 6 compounds exhibited stable binding to uPAR and interacted with the critical residues in the binding interface between uPAR and its endogenous ligand uPA, suggesting their potential as uPAR inhibitors by interrupting the uPAR-uPA interaction. We finally predicted the ADMET properties of these compounds. The natural products NP5, NP12, and NP14 with better binding affinities to uPAR than the uPAR inhibitors previously discovered by us were proven to be potentially orally active in humans. This work offers potential uPAR inhibitors that may contribute to the development of novel effective anticancer and antimetastatic therapeutics.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Song Xie
- College of Chemistry, Fuzhou University, Fuzhou, China
| | - Guiqian Yang
- College of Chemistry, Fuzhou University, Fuzhou, China
| | - Juhong Wu
- College of Chemistry, Fuzhou University, Fuzhou, China
| | | | - Cai Yuan
- College of Chemistry, Fuzhou University, Fuzhou, China
| | - Peng Xu
- College of Chemistry, Fuzhou University, Fuzhou, China
| | | | - Yichang Liu
- School of Pharmacy, Nantong University, Nantong, China
| | - Jinyu Li
- College of Chemistry, Fuzhou University, Fuzhou, China
- Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, Xiamen, China
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