QSAR Pharmacophore Model Hypo1 Essay

What are the functional groups on this molecule? What is the R group to which they are attached? Is the R group hydrophilic or hydrophobic?

It provides five models based on the amino acid sequence and each model is assigned an individual C-score(confidence scores) calculated based on the significance of threading template alignments and the convergence parameters of the structure assembly simulations[16]. A higher C-score indicates greater confidence and vice-versa. It also provides a TM (template modelling) Score which measures the structural similarity between two structures. A TM-score >0.5 indicates a model of correct topology whereas a TM-score <0.17 indicates a random similarity. It also predicts solvent accessibility and ligand binding sites. Protein sequence was submitted to the webserver and the protein structure was obtained.

The results showed that CMP 1e and 5e inhibited HDAC8 much more significantly at 0.1 μM concentration when compared to the standard drug SAHA. The percentage of inhibition for all the compounds tested was found to be in the range of 56.3 -78.5%. Even though, greater steric tolerance existed at the HDAC8 active site near the entrance of the capping group than the metal binding moiety region, the pyridimine (CMP 1e, 2e & 4e) and pyridine analogues (CMP 5e) displayed the greatest inhibitory activity at IC50 0.1 µM. The polarity of the nitrogen atom

Atomic charges were assigned to the receptor using AMBER7 FF99 force field. The protein complex was minimized using AMBER7 FF99 force field. Finally the 3D structure of the prepared protein was saved as PDB file.

The drug discovery stage goes through a number of actions. The most crucial path in the discovery process instigates as the biological assays are established. In the early stage, it is essential to identify the molecules and its activity on the drug target. After the development, the models will then be used for screening the compound libraries. During this process, the chosen molecules diagnosed.

As indicated previously,17 long alkyl chain and one of the diphenyl ether ring form hydrophobic interaction with Ala140, Met196, Tyr225, Thr231, Ala273, and Met285 that may provide better affinity toward inhibitor than triclosan (Figure 4). In addition, the ring that does not have alkyl chain binds to the pocket at ∼24° tilted position compared to that of the bound triclosan to FabI. Specifically, when the structures of FabIs and FabV were superimposed, conserved M206 through FabIs interfered the binding of the inhibitor of FabV (Figure 4).7,22 Therefore, we postulate that the hydrophobic pocket of FabV has a preference for the alkyl chain of inhibitor than triclosan.

In order to study the binding mode of different inhibitors with McFabZ protein, docking calculation was performed using autodock and autogrid from ADT tools. These nine inhibitors biochanin A, genistein, juglone, epicatechin gallate, quercetin, daidzein, fistein, and myricetin have been docked into the active site of McFabZ. Table 4 shows the binding energy and binding constant calculated by ADT tools.

Pueraria tuberosa is known for its therapeutic potentials in cardiovascular disorders but its effect in angiogenesis not been studied so far. In this study, a computational approach has been applied to elucidate the role of the phytochemicals in inhibition of angiogenesis through modulation of Vascular Endothelial Growth Factor Receptors: VEGFR1 & VEGFR2, major factors responsible for angiogenesis. Metabolite structures retrieved from PubChem and KNApSAcK – 3D databases, were docked using AutoDock4.2 tool. Hydrogen bond and Molecular, ADME and toxicity predictions were carried out using UCSF Chimera, LigPlot+ and PreADMET server respectively. From the docking analysis, it was observed that Puerarone and Tuberostan had significant binding affinity for the intracellular kinase domain of VEGFR1 and VEGFR2 respectively. It is important to mention that both the phytochemicals shared similar interaction profile as that of standard inhibitors of VEGFRs. Besides this, both Puerarone and Tuberostan interacted with Lys861/ Lys868 (ATP binding site of VEGFR1/VEGFR2), thus providing a clue that they may enforce their inhibitory effect by blocking the ATP binding domain of VEGFRs. Moreover, these molecules exhibited good drug-likeness, ADME properties without any carcinogenic and toxic effects. The interaction pattern of the Puerarone and Tuberostan may provide a hint for a novel drug design for VEGF tyrosine kinase receptors with better specificity for the treatment of Angiogenic

Moreover, the Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine, which is a professional computer software program based on chemometrics, is recommended by the Chinese Pharmacopoeia Committee and is primarily applied in similarity studies on chromatographic and spectral patterns [24, 25]. In addition, the relative retention time (RRT) and relative peak area (RPA) of each characteristic peak relative to the internal standard peak have been calculated for the quantitative expression of the chemical properties of chromatographic patterns [26]. The generated data provided valuable insight into the application of the fingerprint analysis and quality

Another alternative, strategy utilized in identification of targets for phytochemical involves “the screening of query compounds against pharmacophore models of PDB ligands”. This strategy is much faster than molecular docking in filtering out compounds that “are not direct mimics of the ligands from which the pharmacophore model is generated”. This method has been used first time for target fishing for plant constituents of Ruta graveolens against a database containing 2208 pharmacophore models. In this study, screening of sixteen bioactive principles of

The monomeric structures of proteins are determined with I-TASSER employing the use of the user-definite distance constraints which equal to

Cheminformatics analysis methods can reduce the time and cost required for parts of the drug development process, possibly making drug development faster and more efficient in general. [4-6].

Identify the binding groups and their optimal alignment with one another, paying particular attention to the hydrogen bonds. Provide at least one example for each type of interaction.

Molecular Docking: To validate the bioprospection model, docking simulations of predominant phytoconstituents against most relevant bioactivity parameter was carried out using Maestro 9.4, Schrodinger, USA

Several thousands of compounds are yet to be discovered, but there are many tools and methods available to uncover the identity of newly synthesized compounds. These techniques include performing NMR spectroscopy, IR spectroscopy, and mass spectrometry, as well as analyzing melting points and refractive indexes. In particular, spectroscopy and spectrometry are especially useful in determining chemical and physical properties, and they are highly applicable to pharmaceutical product development. According to a study published in 2011, pharmaceutical researchers have focused on the implementation and presence of metals, trace metals, and active ingredients in developing drugs (Lewen, 2011). Nuclear magnetic resonance spectroscopy and atomic