Tailored-pharmacophore model to enhance virtual screening and drug discovery: a case study on the identification of potential inhibitors against drug-resistant Mycobacterium tuberculosis (3R)-hydroxyacyl-ACP dehydratases

2017 ◽  
Vol 9 (10) ◽  
pp. 1055-1071 ◽  
Author(s):  
Kgothatso E Machaba ◽  
Ndumiso N Mhlongo ◽  
Yussif M Dokurugu ◽  
Mahmoud ES Soliman
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Drug Discovery ◽  
Virtual Screening ◽  
Pharmacophore Model ◽  
Drug Resistant ◽  
Potential Inhibitors

scholarly journals Structure-based virtual screening for new lead compounds targeted Plasmodium α-tubulin

2021 ◽  
Vol 28 ◽  
pp. 135-139
Author(s):  
O. V. Rayevsky ◽  
O. M. Demchyk ◽  
P. A. Karpov ◽  
S. P. Ozheredov ◽  
S. I. Spivak ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Protein Interaction ◽  
Specific Binding ◽  
Pharmacophore Model ◽  
Computational Prediction ◽  
Mitotic Apparatus ◽  
Ligand Interaction ◽  
Lead Compounds ◽  
Key Functional Groups ◽  
Potential Inhibitors

Aim. Search for new dinitroaniline and phosphorothioamide compounds, capable of selective binding with Plasmodium α-tubulin, affecting its mitotic apparatus. Methods. Structural biology methods of computational prediction of protein-ligand interaction: molecular docking, molecular dynamics and pharmacophore analysis. Selection of compounds based on pharmacophore characteristics and virtual screening results. Results. The protocol and required structural conditions for target (α-tubulin of P. falciparum) preparation and correct modeling of the ligand-protein interaction (docking and virtual screening) were developed. The generalized pharmacophore model of ligand-protein interaction and key functional groups of ligands responsible for specific binding were identified. Conclusions. Based on results of virtual screening, 22 commercial compounds were selected. Identified compounds proposed as potential inhibitors of Plasmodium mitotic machinery and the base of new antimalarial drugs. Keywords: malaria, Plasmodium, intermolecular interaction, dinitroaniline derived, phosphorothioamidate derived.

scholarly journals Computational and micro-analytical techniques to study the in vitro and in silico models of novel therapeutic drugs

2016 ◽  
Author(s):  
◽  
Njabulo Joyfull Gumede
Keyword(s):  
Drug Discovery ◽  
In Silico ◽  
Pharmacophore Model ◽  
Binding Affinities ◽  
Ic50 Values ◽  
Database Screening ◽  
Pharmacophore Models ◽  
Novel Therapeutic

In drug discovery and development projects, metabolism of new chemical entities (NCEs) is a major contributing factor for the withdrawal of drug candidates, a major concern for other chemical industries where chemical-biological interactions are involved. NCEs interact with a target macro-molecule to stimulate a pharmacological or toxic response, known as pharmacodynamics (PD) effect or through the Adsorption, Distribution, Metabolism, and Excretion (ADME) process, triggered when a bio-macromolecule interacts with a therapeutic drug. Therefore, the drug discovery process is important because 75% of diseases known to human kind are not all cured by therapeutics currently available in the market. This is attributed to the lack of knowledge of the function of targets and their therapeutic use in order to design therapeutics that would trigger their pharmacological responses. Accordingly, the focus of this work is to develop cost saving strategies for medicinal chemists involved with drug discovery projects. Therefore, studying the synergy between in silico and in vitro approaches maybe useful in the discovery of novel therapeutic compounds and their biological activities. In this work, in silico methods such as structure-based and ligand-based approaches were used in the design of the pharmacophore model, database screening and flexible docking methods. Specifically, this work is presented by the following case studies: The first involved molecular docking studies to predict the binding modes of catechin enantiomer to human serum albumin (HSA) interaction; the second involved the use of docking methods to predict the binding affinities and enantioselectivity of the interaction of warfarin enantiomers to HSA. the third case study involved a combined computational strategy in order to generate information on a diverse set of steroidal and non-steroidal CYP17A1 inhibitors obtained from literature with known experimental IC50 values. Finally, the fourth case study involved the prediction of the site of metabolisms (SOMs) of probe substrates to Cytochrome P450 metabolic enzymes CYP 3A4, 2D6, and 2C9 making use of P450 module from Schrödinger suite for ADME/Tox prediction. The results of case study I were promising as they were able to provide clues to the factors that drive the synergy between experimental kinetic parameters and computational thermodynamics parameters to explain the interaction between drug enantiomers and thetarget protein. These parameters were correlated/converted and used to estimate the pseudo enantioselectivity of catechin enantiomer to HSA. This approach of combining docking methodology with docking post-processing methods such as MM-GBSA proved to be vital in estimating the correct pseudo binding affinities of a protein-ligand complexes. The enantioselectivity for enantiomers of catechin to HSA were 1,60 and 1,25 for site I and site II respectively. The results of case study II validates and verifies the preparation of ligands and accounting for tautomers at physiological pH, as well as conformational changes prior to and during docking with a flexible protein. The log KS = 5.43 and log KR = 5.34 for warfarin enantiomer-HSA interaction and the enantioselectivity (ES = KS/KR) of 1.23 were close to the experimental results and hence referred to as experimental-like affinity constants which validated and verified their applicability to predict protein-ligand binding affinities. In case study III, a 3D-QSAR pharmacophore model was developed by using 98 known CYP17A1 inhibitors from the literature with known experimental IC50 values. The starting compounds were diverse which included steroidal and non-steroidal inhibitors. The resulting pharmacophore models were trained with 69 molecules and 19 test set ligands. The best pharmacophore models were selected based on the regression coefficient for a best fit model with R2 (ranging from 0.85-0.99) & Q2 (ranging from 0.80-0.99) for both the training and test sets respectively, using Partial Least Squares (PLS) regression. On the other hand, the best pharmacophore model selected was further used for a database screening of novel inhibitors and the prediction of their CYP17A1 inhibition. The hits obtained from the database searches were further subjected to a virtual screening workflow docked to CYP17A1 enzyme in order to predict the binding mode and their binding affinities. The resulting poses from the virtual screening workflow were subjected to Induced Fit Docking workflow to account for protein flexibility during docking. The resulting docking poses were examined and ranked ordered according to the docking scores (a measure of affinity). Finally, the resulting hits designed from an updated model from case study III were further synthesized in an external organic chemistry laboratory and the synthetic protocols as well as spectroscopic data for structure elucidation forms part of the provisional patent specification. A provisional patent specification has been filed (RSA Pat. Appln. 2015/ 07849). The case studies performed in this thesis have enabled the discovery of non-steroidal CYP17A1 inhibitors.

scholarly journals Identification of Potential Inhibitors of the Antigen 85C of Mycobacterium tuberculosis from Natural Resources by Virtual Screening

2019 ◽  
Vol 11 (2) ◽  
pp. 449-467
Author(s):  
Elivelton de J. Cerqueira ◽  
Isis B. Santana ◽  
Kryzia S. da Silva ◽  
Manoelito C. dos S. Junior
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Virtual Screening ◽  
Natural Resources ◽  
Potential Inhibitors

scholarly journals New Isoniazid Complexes, Promising Agents Against Mycobacterium tuberculosis

2017 ◽  
Vol 57 (3) ◽  
Author(s):  
Mariana Poggi ◽  
Rafael Barroso ◽  
Antonio José Costa-Filho ◽  
Heloisa Barbosa de Barros ◽  
Fernando Pavan ◽  
...  
Keyword(s):  
Public Health ◽  
Mycobacterium Tuberculosis ◽  
Drug Discovery ◽  
Cobalt Complexes ◽  
Selectivity Index ◽  
Synthesis And Characterization ◽  
Drug Resistant ◽  
Critical Situation ◽  
Research Priority ◽  
Microbial Strains

Tuberculosis (TB) is a public health disease that produces several million deaths annually worldwide. Due to this critical situation and the appearance of drug-resistant microbial strains, innovation in TB drug discovery is a research priority. In this work, the synthesis and characterization by elemental analysis, hermogravimetry, conductimetric measurements and spectroscopies UV-Vis, IR and EPR of [Cu(INH)(H<sub>2</sub>O)]SO<sub>4</sub>⋅2H<sub>2</sub>O (Cu-INH) and [CoCl(INH)<sub>2</sub>(H<sub>2</sub>O)] Cl⋅2.5H<sub>2</sub>O (Co-INH) complexes with isoniazid (INH) are reported. Besides, the lipophilicity, the activity against <em>Mycobacterium tuberculosis</em> (MIC<sub>Cu-INH</sub> = 0.78 μg/mL and MIC<sub>Co-INH</sub> = 0.19 μg/mL) and the cytotoxicity (IC<sub>50</sub> = 48.8 and 625 μg/mL for the copper and cobalt complexes, respectively) were measured and the selectivity index (62.5 for Cu-INH and 3205 for Co-INH) was calculated. These results indicate that these complexes are good candidates for further studies.

scholarly journals Ensemble-based virtual screening of Mycobacterium tuberculosis ClpC1 inhibitors

2021 ◽  
Author(s):  
Hafsa Tayyab ◽  
Nor F W Ridzwan ◽  
Saharuddin B Mohamad
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Virtual Screening ◽  
Dynamics Simulation ◽  
Stable Complex ◽  
Promising Target ◽  
Toxicological Profile ◽  
New Treatment ◽  
The Stability ◽  
Potential Inhibitors ◽  
Natural Product Compounds

Tuberculosis (TB) is an airborne transmissible disease caused by Mycobacterium tuberculosis (Mtb), responsible for 1.3 million deaths per year. Due to increased cases of drug resistance to Mtb, a new treatment regime for TB needs to be discovered. ClpC1 plays a crucial role in the protein homeostasis of Mtb thus, presents as a promising target in controlling TB infection. The present study aimed to identify potential inhibitors for the ClpC1 N-terminal domain (ClpC1-NTD) by applying the relaxed complex scheme in virtual screening that accounts for the target and ligand flexibility. A filtered library of natural product compounds was virtually screened against each of the selected ClpC1-NTD dominant conformations from the ensemble generated using molecular dynamics simulation. The promising compounds with the strong binding affinity to ClpC1 protein were then further analysed for their molecular interactions. The stability of the most potent compound was examined through a complex MD simulation while the pharmacokinetics properties were gathered using SwissADME and pkCSM. The results showed that ligand NP132 formed a strong and stable complex with good pharmacokinetics and toxicological profile.

Hybridization approach to drug discovery inhibiting Mycobacterium tuberculosis. An overview.

2020 ◽  
Vol 20 ◽  
Author(s):  
Daniele Zampieri ◽  
Maria G. Mamolo
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Drug Discovery ◽  
Cause Of Death ◽  
Medicinal Chemistry ◽  
Causes Of Death ◽  
Infectious Agent ◽  
Drug Resistant ◽  
New Chemical Entities ◽  
Hybrid Ligands

: Tuberculosis is one of the top 10 causes of death worldwide and the leading cause of death from a single infectious agent mainly due to Mycobacterium tuberculosis (MTB). Recently, clinical prognoses have worsened due to the emergence of multi-drug resistant (MDR) and extensive-drug resistant (XDR) tuberculosis which lead to the need of new, efficient and safely drugs. Among the several strategies, polypharmacology could be considered one of the best solutions, in particular the multi-target directed ligands strategy (MTDLs), based on the synthesis of hybrid ligands acting against two targets of the pathogen. The framework strategy comprises linking, fusing and merging approaches to develop new chemical entities. With these premises, this review aims to provide an overview of recent hybridization approach, in medicinal chemistry, of the most recent and promising multitargeting antimycobacterial candidates.

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