Antimalarial drug discovery against malaria parasites through haplopine modification: An advanced computational approach

Journal of Cellular and Molecular Medicine, Journal Year: 2023, Volume and Issue: 27(20), P. 3168 - 3188

Published: Sept. 19, 2023

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

Language: Английский

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Design, Synthesis, and Molecular Docking Studies of 2‐Azetidinone‐Based Combretastatin A‐4 Analogues with Anticancer Activity

ChemistrySelect, Journal Year: 2025, Volume and Issue: 10(6)

Published: Feb. 1, 2025

Abstract This study develops new combretastatin A‐4 (CA‐4) analogues to enhance anticancer efficacy, selectivity, and address drug resistance. A series of 2‐azetidinones, designed as CA‐4 analogues, feature two substituted phenyl rings bridged by an amidic carbonyl a β‐lactam ring. Target compounds (7–11, 20–23, 28–31) were synthesized through two‐step routes characterized using FT‐IR, 1 H NMR, 13 C mass spectrometry. Anti‐proliferative activity against the breast cancer cell line MCF‐7 normal WRL 68 revealed 9 21 most potent, with IC 50 values 34.27 28.86 µM, respectively. Molecular docking studies these showed high binding affinity colchicine site on tubulin (PDB ID: 4O2B). Results suggest that symmetrical aromatic in this scaffold may activity, highlighting promising candidates.

Language: Английский

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Molecular interactions between fibrinogen and 6-methoxydihydrosanguinarine and their modulation of anticancer activity in melanoma A375 cells

International Journal of Biological Macromolecules, Journal Year: 2025, Volume and Issue: unknown, P. 142170 - 142170

Published: March 1, 2025

Language: Английский

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Pharmacophore-based virtual screening, molecular docking and molecular dynamics studies for the discovery of novel neuraminidase inhibitors

Journal of Biomolecular Structure and Dynamics, Journal Year: 2023, Volume and Issue: 42(10), P. 5308 - 5320

Published: June 19, 2023

The in silico evaluation of 27 p-aminosalicylic acid derivatives, also referred to as neuraminidase inhibitors was the focus current study. To search and predict new potential inhibitors, this study based on ligand-based pharmacophore modeling, 3D QSAR, molecular docking, ADMET MD simulation studies. data generated from recently reported divided into two groups, one these group has 17 compounds for training second 10 testing purpose. known ADDPR_4 found statistically significant 3D-QSAR model owing high trust scores (R2 = 0.974, Q2 0.905, RMSE 0.23). Morever external validation employed evaluate prediction capacity built (R2pred 0.905). In addition, ADMET, analyses were obtained hits drug likeness properties. stability formed complexes further evaluated using dynamics. Top showed stable with Neuraminidase calculated total binding energy by MM-PBSA.Communicated Ramaswamy H. Sarma

Language: Английский

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Discovery of novel potent drugs for influenza by inhibiting the vital function of neuraminidase via fragment-based drug design (FBDD) and molecular dynamics simulation strategies

Journal of Biomolecular Structure and Dynamics, Journal Year: 2023, Volume and Issue: 42(18), P. 9294 - 9308

Published: Aug. 28, 2023

AbstractThe current work describes a fragment linking methodology to generate new neuraminidase inhibitors. A total number of 28,977 fragments from Zinc 20 have been obtained and screened for receptor affinity. Using Schrödinger software, the highest-scoring 270 hits (with scores greater than −7.6) were subjected combining create 100 molecules. These novel compounds studied using XP docking evaluate molecular interaction modes their binding affinity receptor. The top ten molecules selected, ADMET, drug-likeness features. Based on these characteristics, best four developed Zanamivir submitted dynamics simulation investigation estimate within Gromacs software. All MD findings show that generated complexes are very stable when compared clinical inhibitor (Zanamivir). In addition, designed inhibitors formed with energies ranging −83.50 −107.85 Kj/mol) according energy calculated by MM-PBSA. For objective developing influenza medications, potential be further evaluated in vitro vivo drug discovery.Communicated Ramaswamy H. SarmaKeywords: Influenzaneuraminidase inhibitorsfragment-based designmolecular dockingADMETmolecular dynamicsMM-PBSAgromacs Disclosure statementNo conflict interest was reported author(s).Additional informationFundingThe author(s) there is no funding associated featured this article.

Language: Английский

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Comprehensive In Silico Analysis of Uncaria Tomentosa Extract: Chemical Profiling, Antioxidant Assessment, and CLASP Protein Interaction for Drug Design in Neurodegenerative Diseases

Current Computer - Aided Drug Design, Journal Year: 2024, Volume and Issue: 21(1), P. 94 - 109

Published: Feb. 4, 2024

Background: Uncaria tomentosa is a traditional medicinal herb renowned for its anti-inflammatory, antioxidant, and immune-enhancing properties. In the realm of neurodegenerative diseases (NDDS), CLASP proteins, responsible regulating microtubule dynamics in neurons, have emerged as critical players. Dysregulation proteins associated with NDDS, such Alzheimer's, Parkinson's, Huntington's diseases. Consequently, comprehending role NDDS holds promise development innovative therapeutic interventions. Objectives: The objectives research were to identify phytoconstituents hydroalcoholic extract (HEUT), evaluate antioxidant potential through vitro free radical scavenging assays explore interaction using silico molecular docking studies. Methods: HPLC LC-MS techniques used quantify phytochemicals HEUT. was assessed DPPH, ferric reducing power (FRAP), nitric oxide (NO) superoxide (SO) methods. Interactions between conventional quinovic acid, chlorogenic epicatechin, corynoxeine, rhynchophylline syringic acid studied Auto Dock 4.2. Results: HEUT demonstrated highest concentration derivatives. exhibited strong radical-scavenging activity IC50 values 0.113 μg/ml (DPPH) 9.51 μM (FRAP). It also suppressed NO production by 47.1 ± 0.37% at 40 inhibited 77.3 0.69% SO generation. Additionally, revealed NDDS. Conclusion: protein suggest promising treating linked dysregulation.

Language: Английский

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Computer-aided Drug Discovery Approaches in the Identification of Natural Products against SARS-CoV-2: A Review

Current Computer - Aided Drug Design, Journal Year: 2023, Volume and Issue: 20(4), P. 313 - 324

Published: March 30, 2023

The COVID-19 pandemic is raising a worldwide search for compounds that could act against the disease, mainly due to its mortality. With this objective, many researchers invested in discovery and development of drugs natural origin. To assist search, potential computational tools reduce time cost entire process known. Thus, review aimed identify how these have helped identification products SARS-CoV-2. For purpose, literature was carried out with scientific articles proposal where it possible observe different classes primary and, mainly, secondary metabolites were evaluated molecular targets, mostly being enzymes spike, using techniques, emphasis on use docking. However, noted silico evaluations still much contribute an anti- SARS-CoV-2 substance, vast chemical diversity products, targets advancement.

Language: Английский

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Computational identification and exploration of novel FGFR tyrosine kinase inhibitors for the treatment of cholangiocarcinoma

Journal of Biomolecular Structure and Dynamics, Journal Year: 2023, Volume and Issue: 42(23), P. 13153 - 13164

Published: Oct. 28, 2023

Tyrosine kinase inhibitors are a specific drug class revolutionizing cancer treatment. FGFR (Fibroblast Growth Factor Receptor) is member of the receptor tyrosine family that has been involved in various alterations which have increasingly recognized as critical molecular drivers cholangiocarcinoma, malignant tumor originating from bile duct epithelial cells. The paper focuses on stepwise computational investigations for discovery novel using pharmacophore modeling, virtual screening, docking, ADMET analysis, dynamics, and knowledge-based structure-activity relationship. To begin with, we considered library 120314868 compounds ZINC 15 database through was narrowed down to 110 having binding affinity >−8.0 kcal mol−1. were analyzed screening compared with FDA-approved pemigatinib, provided 34 hits affinities >−6.5 Finally, top 4 property analysis drug-likeness. MD MM-GBSA performed predict free energy these chemicals determine their stability. gain insight into structure interactions compounds, SAR analyses electrostatic potential maps computed DFT. Several techniques employed build improved based SAR, they then utilizing ADMET, studies, analyses. results suggested identified four developed this current work can be effectively prospective treating Cholangiocarcinoma.

Language: Английский

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Pharmacophore-Based Virtual Screening of Potential SARS-CoV-2 Main Protease Inhibitors from Library of Natural Products

Natural Product Communications, Journal Year: 2022, Volume and Issue: 17(12)

Published: Dec. 1, 2022

Background: The SARS-CoV-2 main protease (M pro ) is an attractive target for drug discovery. Methods: A pharmacophore model was built using the three-dimensional (3D) generation algorithm HypoGen in Discovery Studio 2019. best selected validation a test set of 24 compounds and used as 3D query further screening in-house database natural compounds. Lipinski's rule five to assess drug-like properties hit filtered were then subjected bioactivity evaluations. active docked into site M crystal structure (PDB ID: 7D1M). Results: suitable model, Hypo1, found be consisting four features (one hydrophobic feature, one hydrogen bond donor, two acceptors). Pharmacophore-based virtual with Hypo1 search 34 439 resulted 1502 hits. Among these, 255 satisfied five. highest ranking 10 experimental testing, (W-7) illustrated inhibitory activity against IC 50 value 75 μM. Docking studies revealed that this compound retained necessary interactions within . Conclusion identified lead could provide scaffold development inhibitors.

Language: Английский

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In Silico Drug Discovery: The Next Frontier in the Fight Against SARS-CoV-2

Published: Aug. 11, 2023

Covid-19 is one of humanity’s biggest threat in the 21st century with WHO figures reporting 636 million cases and up to 6.6 deaths globally. SARS-CoV-2, virus that causes disease, characterized by high mutation which contributes its rapid spread. While several vaccines have been produced minimize severity coronavirus diverse treatment regimens approved US FDA under Emergency Use Authorization (EUA), SARS-CoV-2 viral mutations continue derail efforts scientists as emerging variants evade recommended therapies. Nonetheless, computational models exist offer an opportunity overcome barriers involved developing new drugs. In this review, focus on use various virtual screening techniques like molecular docking, dynamics simulations, QSAR, pharmacophore modeling, homology modeling repurposing therapeutics. The results promising from computer-aided drug design (CADD) studies suggesting potential compounds for helping bringing pandemic control.

Language: Английский

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