Addressing the Target Identification and Accelerating the Repositioning of Anti‐Inflammatory/Anti‐Cancer Organic Compounds by Computational Approaches

Abstract

The use of computational chemistry techniques has led to notable advances in the structural and pharmacological investigation of organic compounds. The combination of quantum mechanical (QM) approaches with experimental methods (e. g., NMR spectroscopy) has contributed to the configurational and conformational structural assignment of the investigated items. Once this information has been obtained, in silico tools have been employed for assessing the pharmacological features of natural and synthetic molecules, especially those lacking precise information about their interacting macromolecules. With this aim, we have developed and implemented the Inverse Virtual Screening (IVS) computational methodology for addressing the target identification task. This minireview focuses on the key technical information and on successful examples about the convenient and fast use of such computational methods in the frame of the drug repositioning and the discovery of antiinflammatory/anti-cancer agents.

6‐Methylquinazolin‐4(3H)‐one Based Compounds as BRD9 Epigenetic Reader Binders: A Rational Combination of in silico Studies and Chemical Synthesis

“…Indeed, we firstly performed computational studies by means of docking calculations and pharmacophore screening, in order to validate this chemical core as promising molecular platform for the development of new BRD9 binders. [11] Prior to accurately developing a synthetic procedure leading to the building of a combinatorial library of 6-methylquinazolin-4(3H)one derivatives, the selected core was docked onto the BRD9 binding site (PDB code: 5F1H). [10a] Subsequently, the output docking poses were screened through 3D structure-based pharmacophore model, i. e., AHRR 4-points model ("pharmfragment"), AAHHRRR 7-points model ("pharm-druglike1") and AAHRRRX 7 points model ("pharm-druglike2") developed by us and previously reported (Figure 1 and Figure S1).…”

Phytochemical Analysis of the Methanolic Extract and Essential Oil from Leaves of Industrial Hemp Futura 75 Cultivar: Isolation of a New Cannabinoid Derivative and Biological Profile Using Computational Approaches

“…Inverse Virtual Screening (IVS) is a computational technique that aims to highlight the most promising protein partner(s) for a molecule among a large set of possible targets [63][64][65]. In detail, IVS is structured into three steps: (1) molecular docking of the studied compound(s) against the target panel; (2) normalization of each ligand/target complex binding affinity; and (3) analysis of the obtained results.…”

“…The normalization step, which helps to prevent false-positive results, was based on the ratio between the calcu-lated binding affinity for the test compound (V 0 ) and the average binding affinity value obtained when testing decoy molecules (V R ); see Equation (1). This ratio generates a dimensionless parameter, called the "V value", which is used to obtain a ranking of promising ligand/protein complex divisions for each investigated target that share similar chemical features with the compound of interest [63][64][65].…”

Biological Profile of Two Gentiana lutea L. Metabolites Using Computational Approaches and In Vitro Tests

“…In the Inverse Virtual Screening [18][19][20], conversely to classic Virtual Screening, one or few molecules (see Section 2.5) are docked against a large panel of protein targets (cancerand/or inflammation-related proteins in this case) to highlight putative targets. The target panel accounted in this study contained 3060 proteins that were previously prepared using a tool developed by our group [24] (see Section 2.6).…”

“…Among the most innovative techniques, Inverse Virtual Screening (IVS) plays a significant role. This methodology, developed and optimized by us in recent years [18][19][20], is designed to retrieve the most probable targets for specific molecule and/or a library of compounds by carrying out molecular docking calculations on a pre-defined panel of protein structures (e.g., belonging to the same pathological pathway, enzyme class, etc.). Several examples have been reported in which IVS was used as the driving force for a repurposing study or in the target identification process, leading to interesting results [20].…”