RESUMEN
Plants produced natural generating products play a significant role in drug discovery of new bioactive compounds and these are used for advancement of innovative curative drugs for specific target health diseases. In this study Docking and ADME/T virtual screening method are apply for in drug discovery and can be divided into ligand- and target structure-based. The aim of this study was to analyze the Decalepis hamiltonii isolated compounds by using the evaluation of molecular docking and virtual screening of anticancer drugs. MOE docking ADME/Toxicity and virtual screening approaches. A docking energy -12.97 kcal/mol; -9.93- kcal/mol on cancer responsible protein was targeted. Further, the compounds were filtered through the rule of five, ADME/Toxicity risk and synthetic accessibility. The active compound were then docked to recognize the possible target binding pocket to obtain a set of a ligand poses and to prioritize the predicted active compounds. The scrutinize compounds, as well as their metabolites were evaluated for different pharmacokinetics parameter such as ADME/Toxicity. Therefore, the result shows that a large number of compounds were found to be ADME/toxicity positive to be a positive drug molecule against cancer, selected compounds under study satisfies parameters for ADME and Toxicity properties. The present study demonstrate to identifying the novel structures which are having similar structural feature with like activity with respect to the compounds 3,5-Dimethyl-1,3,4-Hexanetriol and Dodecanoic acid that are shown best binding energy with the receptors 4igk and 4b3z respectively. This study may provide significant clues for discovery novel drug inhibitors for cancer properties.
Asunto(s)
Ácidos Láuricos , Alcoholes Grasos , Ligandos , Simulación del Acoplamiento MolecularRESUMEN
BACKGROUND: Several medicinal plants are being used in Indian medicine systems from ancient times. However, in most cases, the specific molecules or the active ingredients responsible for the medicinal or therapeutic properties are not yet known. OBJECTIVE: This study aimed to report a computational protocol as well as a tool for generating novel potential drug candidates from the bioactive molecules of Indian medicinal and aromatic plants through the chemoinformatics approach. METHODS: We built a database of the Indian medicinal and aromatic plants coupled with associated information (plant families, plant parts used for the medicinal purpose, structural information, therapeutic properties, etc.) We also developed a Java-based chemoinformatics open-source tool called DoMINE (Database of Medicinally Important Natural products from plantaE) for the generation of virtual library and screening of novel molecules from known medicinal plant molecules. We employed chemoinformatics approaches to in-silico screened metabolites from 104 Indian medicinal and aromatic plants and designed novel drug-like bioactive molecules. For this purpose, 1665 ring containing molecules were identified by text mining of literature related to the medicinal plant species, which were later used to extract 209 molecular scaffolds. Different scaffolds were further used to build a focused virtual library. Virtual screening was performed with cluster analysis to predict drug-like and lead-like molecules from these plant molecules in the context of drug discovery. The predicted drug-like and lead-like molecules were evaluated using chemoinformatics approaches and statistical parameters, and only the most significant molecules were proposed as the candidate molecules to develop new drugs. RESULTS AND CONCLUSION: The supra network of molecules and scaffolds identifies the relationship between the plant molecules and drugs. Cluster analysis of virtual library molecules showed that novel molecules had more pharmacophoric properties than toxicophoric and chemophoric properties. We also developed the DoMINE toolkit for the advancement of natural product-based drug discovery through chemoinformatics approaches. This study will be useful in developing new drug molecules from the known medicinal plant molecules. Hence, this work will encourage experimental organic chemists to synthesize these molecules based on the predicted values. These synthesized molecules need to be subjected to biological screening to identify potential molecules for drug discovery research.
Asunto(s)
Productos Biológicos/síntesis química , Quimioinformática , Diseño de Fármacos , Preparaciones Farmacéuticas/síntesis química , Plantas Medicinales/química , Productos Biológicos/química , Productos Biológicos/metabolismo , Bases de Datos Farmacéuticas , India , Preparaciones Farmacéuticas/química , Preparaciones Farmacéuticas/metabolismo , Plantas Medicinales/metabolismoRESUMEN
A conceptual basis to define and detect organic functional groups is developed. The basic model of a functional group is termed as a primary functional group and is characterized by a group center composed of one or more group center atoms bonded to terminal atoms and skeletal carbon atoms. The generic group center patterns are identified from the structures of known functional groups. Accordingly, a chemical ontology 'Font' is developed to organize the existing functional groups as well as the new ones to be defined by the chemists. The basic model is extended to accommodate various combinations of primary functional groups as functional group assemblies. A concept of skeletal group is proposed to define the characteristic groups composed of only carbon atoms to be regarded as equivalent to functional groups. The combination of primary functional groups with skeletal groups is categorized as skeletal group assembly. In order to make the model suitable for reaction modeling purpose, a Graphical User Interface (GUI) is developed to define the functional groups and to encode in XML format appropriate to detect them in chemical structures. The system is capable of detecting multiple instances of primary functional groups as well as the overlapping poly-functional groups as the respective assemblies.