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Computer-Aided Drug Design for the Identification of Multi-Target Directed Ligands (MTDLs) in Complex Diseases: An Overview
Published in Peter Grunwald, Pharmaceutical Biocatalysis, 2019
A pharmacophore can be defined as the basic structural features (such as H-bond acceptors and donors, hydrophobic aliphatic, hydrophobic aromatic, and ring aromatic) along with the proper geometrical constraints (distance, and dihedral angle), which are essential in a ligand for showing biological activity or interactions against a biological target. In silico pharmacophore development technique can be classified into ligand-based (by overlapping a set of known active and inactive compounds for identifying the common structural features that are required for their biological activity) and structure-based (by finding the potential interaction points between the ligands and target protein) pharmacophore modeling. Pharmacophore modeling is a highly useful as well as time-saving technique for identifying MTDLs, where the simplest approach is to develop a set of pharmacophore models against the protein targets of interest and then screen the available chemical (synthetic and/or natural compounds) databases from each of the developed and validated pharmacophore. The compounds that successfully pass (possessing minimum required features) through more than one pharmacophore models can be explored further for confirming activity against the respective targets. Here, the screened compounds can be ranked based on their geometric fit values. Another way is to derive a common pharmacophore from a set of pharmacophore models against different targets and then the single pharmacophore model is used to screen and identify MTDLs (Ambure and Roy, 2017). Ligand-based pharmacophore modeling can be done using several available software—such as HipHop and HypoGen (Li et al., 2000) (by Accelrys Inc., http://www.accelrys.com), PHASE (Dixon et al., 2006) (by Schrödinger Inc., http://www.schrodinger.com), DISCO (Martin, 2000), GASP (Jones et al., 2000), and GALAHAD (Poptodorov et al., 2006) (by Tripos Inc., http://www.tripos.com).
Computational prediction models for assessing endocrine disrupting potential of chemicals
Published in Journal of Environmental Science and Health, Part C, 2018
Sugunadevi Sakkiah, Wenjing Guo, Bohu Pan, Rebecca Kusko, Weida Tong, Huixiao Hong
Pharmacophore modeling is common in drug design. There are two types of pharmacophore modeling: ligand-based and structure-based pharmacophores. The ligand-based pharmacophore modeling functions by extracting the common structural features shared by active chemicals but lacking in inactive chemicals. Hip-Hop and HypoGen algorithms are two popular pharmacophore modeling algorithms.49 The pharmacophore models generated using the HypoGen algorithm can predict activity of new chemicals. The structure-based pharmacophore model is generated based on interactions between a protein and its ligands. Pharmacophore models can pinpoint potential active chemicals for downstream experimental testing from large computational databases and additionally can design molecules with improved specific properties.