Virtual screening of natural anti-filarial compounds against glutathione-S-transferase of Brugia malayi and Wuchereria bancrofti

Imran, Mohd; Baig, Mohammad Hassan; Kausar, Mohd Adnan; Shahid, Syed Monowar Alam; Ahmad, Irfan

doi:10.14715/cmb/2018.64.13.13

Cited by 5 publications

(3 citation statements)

References 27 publications

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“…It defines all the possible pockets in the protein structure. It measures the area and volume of each pocket and cavity analytically, both in solvent accessible surface and molecular surface 17-19. Here, we input the target protein for predicting the ligand binding sites, and the CASTp server predicts the amino acids crucial for binding interactions and docking studies.…”

Section: Methodsmentioning

confidence: 99%

Molecular docking based design of Dengue NS5 methyltransferase inhibitors

et al. 2019

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Dengue is a viral infection caused by RNA infection of the family Flaviviridae and spread by the Aedes mosquitoes. Dengue NS5 methyltransferase is a known drug target for the disease. Therefore, it is of interest to design potential inhibitors for the target using molecular docking analysis. Our analysis shows the binding of compounds STOCK1N-98943, STOCK1N-98872, STOCK1N-98956, STOCK1N-98865, and STOCK1N-98950 with the protein drug target with optimal binding features for further in vitro and in vivo evaluations.

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Section: Methodsmentioning

confidence: 99%

Molecular docking based design of Dengue NS5 methyltransferase inhibitors

et al. 2019

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“…For example, in filarial nematodes, enzymes have provided promising targets for anthelminthic and vaccine development. These include GST, which protects the nematode parasite by neutralizing host cytotoxic products (e.g., reactive oxygen species) and mediating drug resistance, and UDP-glucuronosyltransferase (Bm-UGT), a detoxifying enzyme expressed in the B. malayi intestinal lumen that was essential for its survival ( Saeed et al, 2018 ; Flynn et al, 2019 ).…”

Section: Virulence Factorsmentioning

confidence: 99%

The Two Faces of Nematode Infection: Virulence and Immunomodulatory Molecules From Nematode Parasites of Mammals, Insects and Plants

2020

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Helminths stage a powerful infection that allows the parasite to damage host tissue through migration and feeding while simultaneously evading the host immune system. This feat is accomplished in part through the release of a diverse set of molecules that contribute to pathogenicity and immune suppression. Many of these molecules have been characterized in terms of their ability to influence the infectious capabilities of helminths across the tree of life. These include nematodes that infect insects, known as entomopathogenic nematodes (EPN) and plants with applications in agriculture and medicine. In this review we will first discuss the nematode virulence factors, which aid parasite colonization or tissue invasion, and cause many of the negative symptoms associated with infection. These include enzymes involved in detoxification, factors essential for parasite development and growth, and highly immunogenic ES proteins. We also explore how these parasites use several classes of molecules (proteins, carbohydrates, and nucleic acids) to evade the host’s immune defenses. For example, helminths release immunomodulatory molecules in extracellular vesicles that may be protective in allergy and inflammatory disease. Collectively, these nematode-derived molecules allow parasites to persist for months or even years in a host, avoiding being killed or expelled by the immune system. Here, we evaluate these molecules, for their individual and combined potential as vaccine candidates, targets for anthelminthic drugs, and therapeutics for allergy and inflammatory disease. Last, we evaluate shared virulence and immunomodulatory mechanisms between mammalian and non-mammalian plant parasitic nematodes and EPNs, and discuss the utility of EPNs as a cost-effective model for studying nematode-derived molecules. Better knowledge of the virulence and immunomodulatory molecules from both entomopathogenic nematodes and soil-based helminths will allow for their use as beneficial agents in fighting disease and pests, divorced from their pathogenic consequences.

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“…This method has come to be known as Virtual Screening (VS). Virtual Screening (VS) protocols can computationally map compound libraries against biological targets to detect compounds with potential biological activities while eliminating unsuitable compounds [ 5 – 7 ]. Such in silico virtual screening can assess large numbers of compounds rapidly, including molecules yet to be synthesized.…”

Section: Introductionmentioning

confidence: 99%

Towards Effective Consensus Scoring in Structure-Based Virtual Screening

Phuong

Flower

Chattopadhyay³

et al. 2022

Interdiscip Sci Comput Life Sci

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Virtual screening (VS) is a computational strategy that uses in silico automated protein docking inter alia to rank potential ligands, or by extension rank protein–ligand pairs, identifying potential drug candidates. Most docking methods use preferred sets of physicochemical descriptors (PCDs) to model the interactions between host and guest molecules. Thus, conventional VS is often data-specific, method-dependent and with demonstrably differing utility in identifying candidate drugs. This study proposes four universality classes of novel consensus scoring (CS) algorithms that combine docking scores, derived from ten docking programs (ADFR, DOCK, Gemdock, Ledock, PLANTS, PSOVina, QuickVina2, Smina, Autodock Vina and VinaXB), using decoys from the DUD-E repository (http://dude.docking.org/) against 29 MRSA-oriented targets to create a general VS formulation that can identify active ligands for any suitable protein target. Our results demonstrate that CS provides improved ligand–protein docking fidelity when compared to individual docking platforms. This approach requires only a small number of docking combinations and can serve as a viable and parsimonious alternative to more computationally expensive docking approaches. Predictions from our CS algorithm are compared against independent machine learning evaluations using the same docking data, complementing the CS outcomes. Our method is a reliable approach for identifying protein targets and high-affinity ligands that can be tested as high-probability candidates for drug repositioning. Graphical Abstract

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Virtual screening of natural anti-filarial compounds against glutathione-S-transferase of Brugia malayi and Wuchereria bancrofti

Cited by 5 publications

References 27 publications

Molecular docking based design of Dengue NS5 methyltransferase inhibitors

Molecular docking based design of Dengue NS5 methyltransferase inhibitors

The Two Faces of Nematode Infection: Virulence and Immunomodulatory Molecules From Nematode Parasites of Mammals, Insects and Plants

Towards Effective Consensus Scoring in Structure-Based Virtual Screening

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