Evaluation of inhibitory effects of benzothiazole and 3-amino-benzothiazolium derivatives on DNA topoisomerase II by molecular modeling studies

There has been considerable interest in DNA topoisomerases over the last decade, as they have been shown to be one of the major cellular targets in anticancer drug development. Previously we synthesized some benzothiazole derivatives and corresponding benzothiazolium forms, and tested their DNA inhibitory activity to develop novel antitumor agents. Among the 12 prepared compounds, compound BM3 (3-aminobenzothiazole-3-ium 4-methylbenzene sulfonate) exhibited extreme topoisomerase II inhibitory activity compared with the reference drug etoposide. We also tried to determine the DNA and enzyme binding abilities of BM3 and found that BM3 acted on topoisomerase II first at low doses, while it had also showed DNA minor groove binding properties at higher doses. In this study the interactions between DNA topoisomerase II and the compounds were examined in detail by molecular modelling studies such as molecular docking and pharmacophore analysis performed using Discovery Studio 3.5. As a result, it was found that benzothiazolium compounds exhibited a totally different mechanism than benzothiazoles by binding to the different amino acids at the active site of the protein molecule. 3-Aminobenzothiazoliums are worthy of carrying onto anticancer studies; BM3 especially would be a good anticancer candidate for preclinical studies. © 2014 Taylor & Francis

Modeling of Human Prokineticin Receptors: Interactions with Novel Small-Molecule Binders and Potential Off-Target Drugs

The Prokineticin receptor (PKR) 1 and 2 subtypes are novel members of family A GPCRs, which exhibit an unusually high degree of sequence similarity. Prokineticins (PKs), their cognate ligands, are small secreted proteins of ∼80 amino acids; however, non-peptidic low-molecular weight antagonists have also been identified. PKs and their receptors play important roles under various physiological conditions such as maintaining circadian rhythm and pain perception, as well as regulating angiogenesis and modulating immunity. Identifying binding sites for known antagonists and for additional potential binders will facilitate studying and regulating these novel receptors. Blocking PKRs may serve as a therapeutic tool for various diseases, including acute pain, inflammation and cancer.Ligand-based pharmacophore models were derived from known antagonists, and virtual screening performed on the DrugBank dataset identified potential human PKR (hPKR) ligands with novel scaffolds. Interestingly, these included several HIV protease inhibitors for which endothelial cell dysfunction is a documented side effect. Our results suggest that the side effects might be due to inhibition of the PKR signaling pathway. Docking of known binders to a 3D homology model of hPKR1 is in agreement with the well-established canonical TM-bundle binding site of family A GPCRs. Furthermore, the docking results highlight residues that may form specific contacts with the ligands. These contacts provide structural explanation for the importance of several chemical features that were obtained from the structure-activity analysis of known binders. With the exception of a single loop residue that might be perused in the future for obtaining subtype-specific regulation, the results suggest an identical TM-bundle binding site for hPKR1 and hPKR2. In addition, analysis of the intracellular regions highlights variable regions that may provide subtype specificity

COMPUTATIONAL APPROACHES RELATED TO DRUG DISPOSITION

Drug disposition connects with the movement of drug molecules inside the body after administration irrespective with the route of administration. After entering the system, drug molecule and internal body systems comes under various pharmacokinetic interactions followed by observation of suitable biological activity. In this exhaustive process, physicochemical nature of the chemical substance and physiological nature of system makes this movement competitive. In this view, pharmacokinetic and toxic properties of the molecule regulates the destination of the molecule. Various computational processes are available for in silico pharmacokinetic assessment of drug molecule after absorption through biological membrane, distributed throughout the system based on the percent ionization or partition coefficient factors followed by biologically transformed into an another entity in presence of microsomal enzymes and finally excrete out from system using various cellular transport systems as well as related cellular toxicity behavior. In this chapter, we ensemble all the possible information related with the drug movement and related computational tools to understand the possible chemical and pathophysiological changes. Here detailed knowledge on database expedition, establishment of pharmacophore model, homology modelling based on sequence similarity, molecular docking study (rigid and flexible docking) and QSAR/QSPR study (with detailed process and available softwares) are provided. These diversely united informations actually helps a researcher to understand the factual movement of a drug molecule inside the system

The evolution of farnesoid X, vitamin D, and pregnane X receptors: insights from the green-spotted pufferfish (Tetraodon nigriviridis) and other non-mammalian species

<p>Abstract</p> <p>Background</p> <p>The farnesoid X receptor (FXR), pregnane X receptor (PXR), and vitamin D receptor (VDR) are three closely related nuclear hormone receptors in the NR1H and 1I subfamilies that share the property of being activated by bile salts. Bile salts vary significantly in structure across vertebrate species, suggesting that receptors binding these molecules may show adaptive evolutionary changes in response. We have previously shown that FXRs from the sea lamprey (<it>Petromyzon marinus</it>) and zebrafish (<it>Danio rerio</it>) are activated by planar bile alcohols found in these two species. In this report, we characterize FXR, PXR, and VDR from the green-spotted pufferfish (<it>Tetraodon nigriviridis</it>), an actinopterygian fish that unlike the zebrafish has a bile salt profile similar to humans. We utilize homology modelling, docking, and pharmacophore studies to understand the structural features of the <it>Tetraodon </it>receptors.</p> <p>Results</p> <p><it>Tetraodon </it>FXR has a ligand selectivity profile very similar to human FXR, with strong activation by the synthetic ligand GW4064 and by the primary bile acid chenodeoxycholic acid. Homology modelling and docking studies suggest a ligand-binding pocket architecture more similar to human and rat FXRs than to lamprey or zebrafish FXRs. <it>Tetraodon </it>PXR was activated by a variety of bile acids and steroids, although not by the larger synthetic ligands that activate human PXR such as rifampicin. Homology modelling predicts a larger ligand-binding cavity than zebrafish PXR. We also demonstrate that VDRs from the pufferfish and Japanese medaka were activated by small secondary bile acids such as lithocholic acid, whereas the African clawed frog VDR was not.</p> <p>Conclusions</p> <p>Our studies provide further evidence of the relationship between both FXR, PXR, and VDR ligand selectivity and cross-species variation in bile salt profiles. Zebrafish and green-spotted pufferfish provide a clear contrast in having markedly different primary bile salt profiles (planar bile alcohols for zebrafish and sterically bent bile acids for the pufferfish) and receptor selectivity that matches these differences in endogenous ligands. Our observations to date present an integrated picture of the co-evolution of bile salt structure and changes in the binding pockets of three nuclear hormone receptors across the species studied.</p

Common and Distant Structural Characteristics of Feruloyl Esterase Families from Aspergillus oryzae

Background: Feruloyl esterases (FAEs) are important biomass degrading accessory enzymes due to their capability of cleaving the ester links between hemicellulose and pectin to aromatic compounds of lignin, thus enhancing the accessibility of plant tissues to cellulolytic and hemicellulolytic enzymes. FAEs have gained increased attention in the area of biocatalytic transformations for the synthesis of value added compounds with medicinal and nutritional applications. Following the increasing attention on these enzymes, a novel descriptor based classification system has been proposed for FAEs resulting into 12 distinct families and pharmacophore models for three FAE sub-families have been developed. Methodology/Principal Findings: The feruloylome of Aspergillus oryzae contains 13 predicted FAEs belonging to six sub-families based on our recently developed descriptor-based classification system. The three-dimensional structures of the 13 FAEs were modeled for structural analysis of the feruloylome. The three genes coding for three enzymes, viz., A.O.2, A.O.8 and A.O.10 from the feruloylome of A. oryzae, representing sub-families with unknown functional features, were heterologously expressed in Pichia pastoris, characterized for substrate specificity and structural characterization through CD spectroscopy. Common feature-based pharamacophore models were developed according to substrate specificity characteristics of the three enzymes. The active site residues were identified for the three expressed FAEs by determining the titration curves of amino acid residues as a function of the pH by applying molecular simulations. Conclusions/Significance: Our findings on the structure-function relationships and substrate specificity of the FAEs of A. oryzae will be instrumental for further understanding of the FAE families in the novel classification system. The developed pharmacophore models could be applied for virtual screening of compound databases for short listing the putative substrates prior to docking studies or for post-processing docking results to remove false positives. Our study exemplifies how computational predictions can complement to the information obtained through experimental methods. © 2012 Udatha et al.published_or_final_versio

Design, Synthesis, Characterization and Biological Evaluation of Pim-1 Inhibitor for Anticancer Activity.

The present study and research has been to identify new molecule for anticancer capable to inhibit pim 1 hence the following processes were carried out. Identification of Common Pharmacophore for Pim1, Preparation of database of ligands, Scaffold identification by docking, Investigation of ADME parameters of selected molecules, Synthesis of molecules related to scaffhold, Characterization of synthesized molecules by TLC, IR spectroscopy, Nuclear Magnetic Resonance spectroscopy and mass spectroscopy, Acute toxicity study in albino mice, In vitro Anticancer Investigation of synthesized molecules against HCT cell lines. CONCLUSION: The present work is generating the Pharmacophore hypothesis that can be successfully used to predict biological activity. The models were capable of predicting the activities. The knowledge of Pharmacophore model was used to design and selective of new scaffolds. The selection, investigation and preparation of receptor protein from pdb for pim1 and docking of the molecule from the database against prepared Pim 1 receptor protein was carried out. The best scaffold selected from ligand database based, on the Pharmacophore predicted value and docking score against pim1 receptor, were chosen for software based ADME studies. The selected scaffold was investigated for the ADME properties. The selected molecules having good ADME properties, were selected for synthesis. The synthesis of molecules PV1, PV2, PV3 and PV4 was carried out using the identified scaffold. The Synthetic procedure involved condensation followed by cyclisation. The synthesized molecules, where characterized by using IR, NMR and MASS spectrometry. Acute toxicity studied of synthesized molecules was carried using albino mice. The LD50 value of the synthesized compound was above 2000mg/kg. The invitro anticancer activity was done using MTT assay method. The synthesized molecules PV1, PV2 and PV3 showed the activity.PV4 showed the less activity because hydrophobic feature is not available compare to the other compounds

Identification of selective Lyn inhibitors from the chemical databases through integrated molecular modelling approaches

In the current study, the Asinex and ChEBI databases were virtually screened for the identification of potential Lyn protein inhibitors. Therefore, a multi-steps molecular docking study was carried out using the VSW utility tool embedded in Maestro user interface of the Schrödinger suite. On initial screening, molecules having a higher XP-docking score and binding free energy compared to Staurosporin were considered for further assessment. Based on in silico pharmacokinetic analysis and a common-feature pharmacophore mapping model developed from the Staurosporin, four molecules were proposed as promising Lyn inhibitors. The binding interactions of all proposed Lyn inhibitors revealed strong ligand efficiency in terms of energy score obtained in molecular modelling analyses. Furthermore, the dynamic behaviour of each molecule in association with the Lyn protein-bound state was assessed through an all-atoms molecular dynamics (MD) simulation study. MD simulation analyses were confirmed with notable intermolecular interactions and consistent stability for the Lyn protein-ligand complexes throughout the simulation. High negative binding free energy of identified four compounds calculated through MM-PBSA approach demonstrated a strong binding affinity towards the Lyn protein. Hence, the proposed compounds might be taken forward as potential next-generation Lyn kinase inhibitors for managing numerous Lyn associated diseases or health complications after experimental validation.The Deanship of Scientific Research at Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia through the Fast-track Research Funding Program.https://www.tandfonline.com/loi/gsar20hj2022Chemical Patholog

Benchmarking and Developing Novel Methods for G Protein-coupled Receptor Ligand Discovery

G protein-coupled receptors (GPCR) are integral membrane proteins mediating responses from extracellular effectors that regulate a diverse set of physiological functions. Consequently, GPCR are the targets of ~34% of current FDA-approved drugs.3 Although it is clear that GPCR are therapeutically significant, discovery of novel drugs for these receptors is often impeded by a lack of known ligands and/or experimentally determined structures for potential drug targets. However, computational techniques have provided paths to overcome these obstacles. As such, this work discusses the development and application of novel computational methods and workflows for GPCR ligand discovery. Chapter 1 provides an overview of current obstacles faced in GPCR ligand discovery and defines ligand- and structure-based computational methods of overcoming these obstacles. Furthermore, chapter 1 outlines methods of hit list generation and refinement and provides a GPCR ligand discovery workflow incorporating computational techniques. In chapter 2, a workflow for modeling GPCR structure incorporating template selection via local sequence similarity and refinement of the structurally variable extracellular loop 2 (ECL2) region is benchmarked. Overall, findings in chapter 2 support the use of local template homology modeling in combination with de novo ECL2 modeling in the presence of a ligand from the template crystal structure to generate GPCR models intended to study ligand binding interactions. Chapter 3 details a method of generating structure-based pharmacophore models via the random selection of functional group fragments placed with Multiple Copy Simultaneous Search (MCSS) that is benchmarked in the context of 8 GPCR targets. When pharmacophore model performance was assessed with enrichment factor (EF) and goodness-of-hit (GH) scoring metrics, pharmacophore models possessing the theoretical maximum EF value were produced in both resolved structures (8 of 8 cases) and homology models (7 of 8 cases). Lastly, chapter 4 details a method of structure-based pharmacophore model generation using MCSS that is applicable to targets with no known ligands. Additionally, a method of pharmacophore model selection via machine learning is discussed. Overall, the work in chapter 4 led to the development of pharmacophore models exhibiting high EF values that were able to be accurately selected with machine learning classifiers

High-dimension profiling data generate a multifunctional peptide-mimic chemo-structure by connecting conserved fragments based on the neutrophil immune defense CAP37 protein as an in-silico antibacterial and woundhealing candidate agent

CAP37, a protein constitutively EXPRESSED in human neutrophils and induced in responseto infection in corneal epithelial cells, plays a significant role in host defense against infection. Initiallyidentified through its potent bactericidal activity for Gram-negative bacteria, it is now known that CAP37regulates numerous host cell functions, including corneal epithelial cell chemotaxis. Delineation of thedomains of CAP37 that define these functions and synthesize bioactive peptides for therapeutic use have alsobeen explored. Novel findings of a multifunctional domain between a 120 and 146 have also been reported.Here, in Biogenea Pharmaceuticals Ltd we for the first time generated a multifunctional peptide-mimicchemo-structure by connecting conserved fragments based on the neutrophil immune defense CAP37 proteinas an in-silico antibacterial and wound-healing canditate agent. This in silico effort was accomplished byutilizing various generated descriptors of proteins, compounds and their interactions resulting in aperformance/cost evaluation study for a GPU-based drug discovery application on volunteer computingapproaches based on Automated Structure-Activity Relationship Minings in Connecting Chemical Structureto Biological Profiles for the generation of novel Computational biomodeling of 3D drug-protein binding freeenergy evaluation