Molecular modeling, simulation and virtual screening of ribosomal phosphoprotein P1 from Plasmodium falciparum

2014 ◽  
Vol 343 ◽  
pp. 113-119 ◽  
Author(s):  
Sweta Kumari ◽  
Arumugam Mohana Priya ◽  
Sajitha Lulu ◽  
Mohammad Tauqueer
Author(s):  
Suraj N. Mali ◽  
Anima Pandey

Malarial parasites have been reported for moderate-high resistance towards classical antimalarial agents and henceforth development of newer novel chemical entities targeting multiple targets rather than targeting single target will be a highly promising strategy in antimalarial drug discovery. Herein, we carried out molecular modeling studies on 2,4-disubstituted imidazopyridines as anti-hemozoin formation inhibitors by using Schrödinger’s molecular modeling package (2020_4). We have developed statistically robust atom-based 3D-QSAR model (training set, [Formula: see text]; test set, [Formula: see text]; [Formula: see text] [Formula: see text]; root-mean-square error, [Formula: see text]; standard deviation, [Formula: see text]). Our molecular docking, in-silico ADMET analysis showed that dataset molecule 37, has highly promising results. Our ligand-based virtual screening resulted in top five ZINC hits, among them ZINC73737443 hit was observed with lesser energy gap, i.e. 7.85[Formula: see text]eV, higher softness value (0.127[Formula: see text]eV), and comparatively good docking score of [Formula: see text]10.2[Formula: see text]kcal/mol. Our in-silico analysis for a proposed hit, ZINC73737443 showed that this molecule has good ADMET, in-silico nonames toxic as well as noncarcinogenic profile. We believe that further experimental as well as the in-vitro investigation will throw more lights on the identification of ZINC73737443 as a potential antimalarial agent.


2019 ◽  
Vol 4 (6) ◽  
Author(s):  
Eleni Koulouridi ◽  
Marilia Valli ◽  
Fidele Ntie-Kang ◽  
Vanderlan da Silva Bolzani

Abstract Databases play an important role in various computational techniques, including virtual screening (VS) and molecular modeling in general. These collections of molecules can contain a large amount of information, making them suitable for several drug discovery applications. For example, vendor, bioactivity data or target type can be found when searching a database. The introduction of these data resources and their characteristics is used for the design of an experiment. The description of the construction of a database can also be a good advisor for the creation of a new one. There are free available databases and commercial virtual libraries of molecules. Furthermore, a computational chemist can find databases for a general purpose or a specific subset such as natural products (NPs). In this chapter, NP database resources are presented, along with some guidelines when preparing an NP database for drug discovery purposes.


2017 ◽  
Vol 10 (17) ◽  
pp. 127
Author(s):  
Berwi Fazri Pamudi ◽  
Azizahwati Azizahwati ◽  
Arry Yanuar

  Objective: Malaria is a parasitic infection that causes worldwide health problems. The absence of an effective vaccine and Plasmodium strains that are resistant to antimalarial drugs emphasize the importance of developing new chemotherapeutic agents. The use of computers for in-silico screening, or virtual screening, is currently being developed as a method for discovering antimalarial drugs. One of the enzymes that can support the development of the malaria parasite is the Plasmodium falciparum enoyl-acyl carrier protein reductase (PfENR). Inhibition of these enzymes leads to Type II lipid biosynthesis inhibition on the parasite.Methods: This research investigates the use of virtual screening to find PfENR inhibitor candidates. A molecular docking method using GOLD software and the medicinal plants in Indonesia database will be used. This target has been optimized by the removal of residues and the addition of charge. Ligand is expected to be an inhibitor of PfENR.Results: In-silico screening, or virtual screening, found that the top five compounds with the highest GOLD score at trial are kaempferol 3-rhamnosyl- (1-3)-rhamnosyl-(1-6)-glucoside; cyanidin 3,5-di-(6-malonylglucoside); 8-hydroxyapigenin 8-(2’’, 4’’-disulfato glucuronide); epigallocatechin 3,5,-di- O-gallat; quercetin 3,4’-dimethyl ether 7-alpha-L-arabinofuranosyl-(1-6)-glucoside. They had GOLD scores of 94.73, 95.90, 86.46, 85.39, and 84.40, respectively.Conclusions: There are two candidate inhibitor compounds from tea (Camellia sinensis), which have potential for development as an antimalarial drug, which are kaempferol 3-rhamnosyl-(1-3)-rhamnosyl-(1-6)-glucoside and epigallocatechin 3,5,-di-O-gallate, with a GOLD score of 94.73 and 85.39, respectively.


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