Search results for "3D-QSAR"
showing 10 items of 10 documents
A3 adenosine receptor: Homology modeling and 3D-QSAR studies
2012
Adenosine receptors (AR) belong to the superfamily of G-protein-coupled receptors (GPCRs). They are divided into four subtypes (A1, A2A, A2B, and A3) [1], and can be distinguished on the basis of their distinct molecular structures, distinct tissues distribution, and selectivity for adenosine analogs [2,3]. The hA3R, the most recently identified adenosine receptor, is involved in a variety of intracellular signaling pathways and physiological functions [4]. Expression of A3R was reported to be elevated in cancerous tissues [5], and A3 antagonists have been proposed for therapeutic treatments of cancer. The recent literature availability of crystal structure of hA2A adenosine receptor (PDB c…
An Integrated Pharmacophore/Docking/3D-QSAR Approach to Screening a Large Library of Products in Search of Future Botulinum Neurotoxin A Inhibitors
2020
Botulinum toxins are neurotoxins produced by Clostridium botulinum. This toxin can be lethal for humans as a cause of botulism
Ligand binding study revealing a human olfactory receptor involved in waxy-floral odor perception
2006
International audience
Identification of estrogen receptor α ligands with virtual screening techniques.
2016
Utilization of computer-aided molecular discovery methods in virtual screening (VS) is a cost-effective approach to identify novel bioactive small molecules. Unfortunately, no universal VS strategy can guarantee high hit rates for all biological targets, but each target requires distinct, fine-tuned solutions. Here, we have studied in retrospective manner the effectiveness and usefulness of common pharmacophore hypothesis, molecular docking and negative image-based screening as potential VS tools for a widely applied drug discovery target, estrogen receptor α (ERα). The comparison of the methods helps to demonstrate the differences in their ability to identify active molecules. For example,…
Prospective computational design and in vitro bio-analytical tests of new chemical entities as potential selective CYP17A1 lyase inhibitors
2019
[EN] The development and advancement of prostate cancer (PCa) into stage 4, where it metastasize, is a major problem mostly in elder males. The growth of PCa cells is stirred up by androgens and androgen receptor (AR). Therefore, therapeutic strategies such as blocking androgens synthesis and inhibiting AR binding have been explored in recent years. However, recently approved drugs (or in clinical phase) failed in improving the expected survival rates for this metastatic-castration resistant prostate cancer (mCRPC) patients. The selective CYP17A1 inhibition of 17,20-lyase route has emerged as a novel strategy. Such inhibition blocks the production of androgens everywhere they are found in t…
IKK-β inhibitors: An analysis of drug–receptor interaction by using Molecular Docking and Pharmacophore 3D-QSAR approaches
2010
Abstract The IKK kinases family represents a thrilling area of research because of its importance in regulating the activity of NF-kB transcription factors. The discovery of the central role played by IKK-β in the activation of transcription in response to apoptotic or inflammatory stimuli allowed to considerate its modulation as a promising tool for the treatment of chronic inflammation and cancer. To date, several IKK-β inhibitors have been discovered and tested. In this work, an analysis of the interactions between different classes of inhibitors and their biological target was performed, through the application of Molecular Docking and Pharmacophore/3D-QSAR approaches to a set of 141 in…
Receptor-guided 3D-QSAR approach for the discovery of c-kit tyrosine kinase inhibitors
2012
Studies of the the three-dimensional quantitative structure–activity relationships for ninety-five c-kit tyrosine kinase inhibitors were performed. Based on a co-crystallized compound (1 T46), known inhibitors were aligned with c-kit by induced-fit docking, and multiple training/test set splitting was performed to validate the selected pharmacophore model. The best pharmacophore model consisted of five features: one hydrogen-bond donor and four aromatic rings. Reliable statistics were obtained (R 2 = 0.95, R pred 2 = 0.75), and the model was validated by using it to select c-kit inhibitors from a database; 82.1% of the hits it retrieved were active. Accordingly, our model can be reliably u…
Interaction between flavour compounds and beta-lactoglobulin: approach by NMR and 2D/3D-QSAR studies of ligands
2004
author cannot archive publisher's version/PDF; International audience; Interactions between flavour compounds and beta-lactoglobulin (BLG) have been the subject of several studies, but there are no unanimous binding site explanations. In our laboratory, interactions between BLG, and two flavour compounds, beta-ionone and gamma-decalactone, were studied by 2D-NMR spectroscopy. It appears that several amino acids affected by binding of gamma-decalactone are buried in the central cavity, whereas binding of beta-ionone affects amino acids located in a groove near the outer surface of the protein. 2D/3D-QSAR studies were performed using QSAR+ module of Cerius2 and Catalyst. The QSAR equation pr…
3D-QSAR pharmacophore modeling and in silico screening of new Bcl-xl inhibitors.
2010
Bcl-2 proteins family members play several roles in tumoral proliferation: they inhibit proapoptotic activity during oncogenesis, support tumor cells survival, induce chemoresistance. The discovery of new small inhibitors of Bcl-xl represents a new frontier for cancer treatment. In this study, a 3D-QSAR pharmacophore model was developed, based on 42 biarylacylsulfonamides, and used to understand the structural factors affecting the inhibitory potency of these derivatives. Aromatic, negative charge, and hydrogen bond acceptor effects contribute to the inhibitory activity. The model was then employed as 3D search query to screen ZINC drug-like database in order to select new scaffolds. Finall…
Cannabinoid ligands sorting out by a 3D-QSAR approach using catalyst/hypogen
2009
National audience; Understanding how molecular structures are involved in recognition by a biological receptor is a decisive step in drug design, and could constitute an intricate problem because of existence of several binding sites, as is the case of GPCRs (1) that constitute the largest class of membrane receptors. In this context, identification of pharmacophores that should differentiate multiple binding modes is of particular interest. We have recently applied to ligands of a human olfactory receptor an original sorting-out procedure carried out using Catalyst/HypoGen software (Accelrys Ltd) (2). We aimed to validate this sorting out procedure using literature data, and in this way, w…