Pharmacophore Model-Based Virtual Screening Workflow for Discovery of Inhibitors Targeting Plasmodium falciparum Hsp90
- Authors: Mafethe, Ofentse , Ntseane, Tlhalefo , Dongola, Harmfree Tendamudzimu , Shonhai, Addmore , Gumede, Joyfull Njabulo , Mokoena, Fortunate
- Date: 2023
- Subjects: Virtual screening , Plasmodium falciparum , Malaria , Pharmacophore model
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/11260/14151 , vital:79145 , DOI: https://doi.org/10.1021/acsomega.3c04494
- Description: Plasmodium falciparum causes the most lethal and widespread form of malaria. Eradication of malaria remains a priority due to the increasing number of cases of drug resistance. The heat shock protein 90 of P. falciparum (PfHsp90) is a validated drug target essential for parasite survival. Most PfHsp90 inhibitors bind at the ATP binding pocket found in its N-terminal domain, abolishing the chaperone's activities, which leads to parasite death. The challenge is that the NTD of PfHsp90 is highly conserved, and its disruption requires selective inhibitors that can act without causing off-target human Hsp90 activities. We endeavored to discover selective inhibitors of PfHsp90 using pharmacophore modeling, virtual screening protocols, induced fit docking (IFD), and cell-based and biochemical assays. The pharmacophore model (DHHRR), composed of one hydrogen bond donor, two hydrophobic groups, and two aromatic rings, was used to mine commercial databases for initial hits, which were rescored to 20 potential hits using IFD. Eight of these compounds displayed moderate to high activity toward P. falciparum NF54 (i.e., IC50s ranging from 6.0 to 0.14 μM) and averaged >10 in terms of selectivity indices toward CHO and HepG2 cells. Additionally, four compounds inhibited PfHsp90 with greater selectivity than a known inhibitor, harmine, and bound to PfHsp90 with weak to moderate affinity. Our findings support the use of a pharmacophore model to discover diverse chemical scaffolds such as FM2, FM6, F10, and F11 exhibiting anti-Plasmodium activities and serving as valuable new PfHsp90 inhibitors. Optimization of these hits may enable their development into potent leads for future antimalarial drugs.
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- Date Issued: 2023
Identification of selective novel hits against Mycobacterium tuberculosis KasA potential allosteric sites using bioinformatics approaches
- Authors: Hare, Fadzayi Faith
- Date: 2022-10-14
- Subjects: Tuberculosis , Docking , Molecules Models , Virtual screening , Multidrug-resistant tuberculosis , Fatty acids Synthesis , Drugs Design
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/362842 , vital:65367
- Description: Tuberculosis (TB) is a global health threat that has led to approximately 1.5 million deaths annually. According to the World Health Organization (WHO), TB is among the top ten deadly diseases and is the leading cause of death due to a single infectious agent. The main challenge in the effective treatment and control of TB is the ongoing emergence of resistant strains of Mycobacterium tuberculosis (Mtb) which lead to multi-drug resistant (MDR) and extensive-drug resistant (XDR) TB. Hence, the identification and characterization of novel drug targets and drugs that modulate the activity of the pathogen are an urgent priority. The current situation even necessitates the reengineering or repurposing of drugs in order to achieve effective control. The β-ketoacyl-acyl carrier protein synthase I (KasA) of Mycobacterium tuberculosis is an essential enzyme in the mycobacterial fatty acid synthesis (FAS-II) pathway and is believed to be a promising target for drug discovery in TB. It is one of the five main proteins of the FAS-II pathway and catalyzes a key condensation reaction in the synthesis of meromycolate chains, the precursors of mycolic acids involved in cell wall formation. Although this protein has been extensively studied, little research has been devoted to the allosteric inhibition of potential drug compounds. The main aim of this research was to identify the allosteric sites on the protein that could be involved in the inhibition of substrate binding activities and novel drug compounds that bind to these sites by use of in-silico approaches. The bioinformatics approaches used in this study were divided into four main objectives namely identification of KasA homolog sequences, sequence analysis and protein characterization, allosteric site search and lastly virtual screening of DrugBank compounds via molecular docking. Fifteen homolog sequences were identified from the BLASTP analysis and were derived from bacteria, fungi and mammals. In order to discover important residues and regions within the KasA proteins, sequence alignment, motif analysis and phylogenetic studies were performed using Mtb KasA as a reference. Sequence alignment revealed conserved residues in all KasA proteins that have functional importance such as the catalytic triad residues (Cys171, His311 and His345). Motif analysis identified 18 highly conserved motifs within the KasA proteins with structural and functional roles. In addition, motifs unique to the Mtb KasA protein were also identified and explored for inhibitor drug design purposes. Phylogenetic analysis of the homolog sequences showed a distinct clustering of prokaryotes and eukaryotes. A distinctive clustering was also observed for species belonging to the same genus. Since the mechanism of action of most drugs involves the active site, allosteric site search was conducted on Mtb KasA and the human homolog protein using a combination of pocket detection algorithms with the aim of identifying sites that could be utilized in allosteric modulator drug discovery. This was followed by the virtual screening of 2089 FDA approved DrugBank compounds against the entire protein surfaces of Mtb KasA and Hsmt KasA, performed via molecular docking using AutoDock Vina. Screening of the compounds was based on the binding energies, with more focus on identifying ligands that bound exclusively to the acyl-binding tunnel of Mtb KasA. This reduced the data set to 27 promising drug compounds with a relatively high binding affinity for Mtb KasA, however, further experiments need to be performed to validate this result. Among these compounds were DB08889, DB06755, DB09270, DB11226, DB00392, DB12278, DB08936, DB00781, DB13720 and DB00392, which displayed relatively low binding energies for Mtb KasA when compared to the human homolog protein. , Thesis (MSc) -- Faculty of Science, Biochemistry and Microbiology, 2022
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- Date Issued: 2022-10-14