Design of Drugs by Filtering Through ADMET, Physicochemical and Ligand-Target Flexibility Properties
There is a synergistic interaction between medicinal chemistry, chemoinformatics, and bioinformatics. The last one includes analyses of sequences as well as structural analysis which employ computational techniques such as docking studies and molecular dynamics (MD) simulations. Over the last years these techniques have allowed the development of new accurate computational tools for drug design. As a result, there have been an increased number of publications where computational methods such as pharmacophore modeling, de novo drug design, evaluation of physicochemical properties, and analysis of ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties have been quite useful for eliminating the compounds with poor physicochemical or toxicological properties. Furthermore, using MD simulations and docking analysis, it is possible to estimate the binding energy of the protein-ligand complexes by using scoring functions, as well as to structurally depict the binding pose of the compounds on proteins, in order to select the best evaluated compounds for subsequent synthetizing and evaluation through biological assays. In this work, we describe some computational tools that have been used for structure-based drug design of new compounds that target histone deacetylases (HDACs), which are known to be potential targets in cancer and parasitic diseases.
Key wordsHistone deacetylases Rational drug design ADMET properties Pharmacophore modeling Docking analysis Molecular dynamics simulations
This work was supported by CONACYT Mexico (CB-254600 and PDCPN-782), SIP20160204, COFAA-SIP/IPN COFAASIP/IPN and Centro de Nanociencias y Micro y Nanotecnologías del IPN, México, and CYTED: 214RT0482.
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