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

Repositioning of Small Molecules through the Inverse Virtual Screening in silico Tool: Case of Benzothiazole-Based Inhibitors of Soluble Epoxide Hydrolase (sEH)

Computational techniques accelerate drug discovery by identifying bioactive compounds for specific targets, optimizing molecules with moderate activity, or facilitating the repositioning of inactive items onto new targets. Among them, the Inverse Virtual Screening (IVS) approach is aimed at the evaluation of one or a small set of molecules against a panel of targets for addressing target identification. In this work, a focused library of benzothiazole-based compounds was re-investigated by IVS. Four items, originally synthesized and tested on bromodomain-containing protein 9 (BRD9) but yielding poor binding, were critically re-analyzed, disclosing only a partial fit with 3D structure-based pharmacophore models, which, in the meanwhile, were developed for this target. Afterwards, these compounds were re-evaluated through IVS on a panel of proteins involved in inflammation and cancer, identifying soluble epoxide hydrolase (sEH) as a putative interacting target. Three items were subsequently confirmed as able to interfere with sEH activity, leading to inhibition percentages spanning from 70 % up to 30 % when tested at 10 μM. Finally, one benzothiazole-based compound emerged as the most promising inhibitor featuring an IC50 in the low micromolar range (IC50=6.62±0.13 μM). Our data confirm IVS as a predictive tool for accelerating the target identification and repositioning processes.

Trends and Applications in Computationally Driven Drug Repurposing

Drug repurposing is a widely used approach originally developed to aid in the identification of new uses of already existing drugs outside the scope of the original medical indication [...].

Exploring the chemical space of functionalized [1,2,4]triazolo[4,3-a]quinoxaline-based compounds targeting the bromodomain of BRD9

Here we report a detailed structure-activity relationship (SAR) study related to [1,2,4]triazolo[4,3-a]quinoxaline-based compounds targeting the reader module of bromodomain containing-protein 9 (BRD9). 3D structure-based pharmacophore models, previously introduced by us, were here employed to evaluate a second generation of compounds, exploring different substitution patterns on the heterocyclic core. Starting from the promising data obtained from our previously identified [1,2,4]triazolo[4,3-a]quinoxaline-based compounds 1-4, the combination of in silico studies, chemical synthesis, biophysical and in vitro assays led to the identification of a new set of derivatives, selected for thoroughly exploring the chemical space of the bromodomain binding site. In more details, the investigation of different linkers at C-4 position highlighted the amine spacer as mandatory for the binding with the protein counterpart and the crucial role of the alkyl substituents at C-1 for increasing the selectivity toward BRD9. Additionally, the importance of a hydrogen bond donor group, critical to anchor the ZA region and required for the interaction with Ile53 residue, was inferred from the analysis of our collected results. Herein we also propose an optimization and an update of our previously reported "pharm-druglike2" 3D structure-based pharmacophore model, introducing it as "pharm-druglike2.1". Compounds 24-26, 32, 34 and 36 were identified as new valuable BRD9 binders featuring IC50 values in the low micromolar range. Among them, 24 and 36 displayed an excellent selectivity towards BRD9 and a good antiproliferative effect on a panel of leukemia models, especially toward CCRF-CEM cell line, with no cytotoxicity on healthy cells. Notably, the interaction of 24 and 36 with the bromodomain and PHD finger-containing protein 1 (BRPF1) also emerged, disclosing them as new and unexplored dual inhibitors for these two proteins highly involved in leukemia. These findings highlight the potential for the identification of new attractive dual epidrugs as well as a promising starting point for the development of chemical degraders endowed with anticancer activities.

Target identification by structure-based computational approaches: Recent advances and perspectives

The use of computational techniques in the early stages of drug discovery has recently experienced a boost, especially in the target identification step. Finding the biological partner(s) for new or existing synthetic and/or natural compounds by "wet" approaches may be challenging; therefore, preliminary in silico screening is even more recommended. After a brief overview of some of the most known target identification techniques, recent advances in structure-based computational approaches for target identification are reported in this digest, focusing on Inverse Virtual Screening and its recent applications. Moreover, future perspectives concerning the use of such methodologies, coupled or not with other approaches, are analyzed.

Identification of 2-Aminoacyl-1,3,4-thiadiazoles as Prostaglandin E2 and Leukotriene Biosynthesis Inhibitors

The application of a multi-step scientific workflow revealed an unprecedented class of PGE₂/leukotriene biosynthesis inhibitors with in vivo activity. Specifically, starting from a combinatorial virtual library of ∼4.2 × 10⁵ molecules, a small set of compounds was identified for the synthesis. Among these, four novel 2-aminoacyl-1,3,4-thiadiazole derivatives (3, 6, 7, and 9) displayed marked anti-inflammatory properties in vitro by strongly inhibiting PGE₂ biosynthesis, with IC₅₀ values in the nanomolar range. The hit compounds also efficiently interfered with leukotriene biosynthesis in cell-based systems and modulated IL-6 and PGE₂ biosynthesis in a lipopolysaccharide-stimulated J774A.1 macrophage cell line. The most promising compound 3 showed prominent in vivo anti-inflammatory activity in a mouse model, with efficacy comparable to that of dexamethasone, attenuating zymosan-induced leukocyte migration in mouse peritoneum with considerable modulation of the levels of typical pro-/anti-inflammatory cytokines.

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

Cannabis sativa L. is a plant belonging to the Cannabaceae family, cultivated for its psychoactive cannabinoid (Δ⁹-THC) concentration or for its fiber and nutrient content in industrial use. Industrial hemp shows a low Δ⁹-THC level and is a valuable source of phytochemicals, mainly represented by cannabinoids, flavones, terpenes, and alkaloids, with health-promoting effects. In the present study, we investigated the phytochemical composition of leaves of the industrial hemp cultivar Futura 75, a monoecious cultivar commercially used for food preparations or cosmetic purposes. Leaves are generally discarded, and represent waste products. We analyzed the methanol extract of Futura 75 leaves by HPLC and NMR spectroscopy and the essential oil by GC-MS. In addition, in order to compare the chemical constituents, we prepared the water infusion. One new cannabinoid derivative (1) and seven known components, namely, cannabidiol (2), cannabidiolic acid (3), β-cannabispirol (4), β-cannabispirol (5), canniprene (6), cannabiripsol (7), and cannflavin B (8) were identified. The content of CBD was highest in all preparations. In addition, we present the outcomes of a computational study focused on elucidating the role of 2α-hydroxy-Δ^3,7-cannabitriol (1), CBD (2), and CBDA (3) in inflammation and thrombogenesis.

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

Natural products have been the main source of bioactive molecules for centuries. We tested the biological profile of two metabolites extracted from Gentiana lutea L. by means of computational techniques and in vitro assays. The two molecules (loganic acid and gentiopicroside) were tested in silico using an innovative technique, named Inverse Virtual Screening (IVS), to highlight putative partners among a panel of proteins involved in inflammation and cancer events. A positive binding with cyclooxygenase-2 (COX-2), alpha-1-antichymotrypsin, and alpha-1-acid glycoprotein emerged from the computational experiments and the outcomes from the promising interaction with COX-2 were confirmed by Western blot, highlighting the reliability of IVS in the field of the natural products.