Interactions between (4Z)-hex-4-en-1-ol and 2-methylbutyl 2-methylbutanoate with olfactory receptors using computational methods

The first step in the perception of an odor is the activation of one or more olfactory receptors (ORs) following binding of the odorant molecule to the OR. The compounds (4Z)-hex-4-en-1-ol and 2-methylbutyl 2-methylbutanoate are two important odorants molecules known as food flavor. In this research, we investigate the potential targets for this two molecules and try to interpret the type of binding with different ORs models and their relationship with the retention/release property. We used the SWISS-MODEL modelling server to predict the three-dimensional (3D) structure of the ORs. We then used the Autodock vina and Autodock tools to predict the binding site and binding energy for the ligands to these receptors. The results indicate that the molecule (4Z)-hex-4-en-1-ol has given more hydrogen bonds with the majority of these receptors and the 2-methylbutyl 2-methylbutanoate molecule mainly has given Pi bonds interaction type

Structure-toxicity relationships for phenols and anilines towards Chlorella vulgaris using quantum chemical descriptors and statistical methods.

Quantitative structure–toxicity relationship (QSTR) models are useful to understand how chemical structure relates to the toxicity of natural and synthetic chemicals. The chemical structures of 67 phenols and anilines have been characterized by electronic and physic-chemical descriptors. Density functional theory (DFT) with Beck’s three parameter hybrid functional using the LYP correlation functional (B3LYP/6-31G(d)) calculations have been carried out in order to get insights into the structure chemical and property information for the study compounds. The statistical quality of the MLR and MNLR models was found to be efficient for the predicting of the toxicity, but when compared to the obtained results by ANN model, we realized that the predictions achieved by this latter one were more effective. The results indicated that the developed models could produce satisfactory predictive results for the four different toxicity endpoints with high squared correlation coefficients (R2 ). Leave-one-out cross validation, external validation, Y-randomized validation and application domain analysis demonstrated the accuracy, robustness and reliability of these models. Accordingly.the obtained results suggested that the proposed descriptors could be useful to predict the toxicity of phenols and anilines towards Chlorella vulgaris.

Cortistatin and plakinamine steroidal alkaloids from the marine sponges of the genus Corticium: Insights into their chemistry, pharmacology, pharmacokinetics and structure activity relationships (SARs)

Cortistatins and plakinamines represent a unique class of marine-derived steroidal alkaloids, renowned for their structural diversity and potent pharmacological activities. This review provides a comprehensive overview of their chemical characteristics, pharmacological profiles, pharmacokinetics, and drug-likeness properties, with a particular focus on structure–activity relationships (SARs). Indeed, we explored their distinct molecular architectures and classification within the broader family of marine alkaloids, highlighting key subclasses and derivatives identified through advanced analytical techniques. Their broad-spectrum bioactivities, including anticancer, anti-inflammatory, antimicrobial, and antiviral effects, are discussed in detail, supported by insights into SARs and pharmacophore identification that illuminate the molecular basis of their bioactivity. Additionally, we evaluate their pharmacokinetic attributes, including absorption, distribution, metabolism, and elimination (ADME), alongside their compliance with drug-likeness criteria, offering a holistic perspective on their potential for drug development

Investigating the structure-activity relationship of laulimalides marine macrolides as promising inhibitors for SARS-CoV-2 main Protease (Mpro)

SARS-CoV-2, the new coronavirus variant has been a worldwide health crisis that may outbreak any time in the future. Over spans of human history, preparations derived from natural products have always been recognized as a preliminary source of medications. Taking into account the SARS-CoV-2 main protease (Mpro) as the essential element of the viral cycle and as a main target, herein we highlight a computer-aided comprehensive virtual screening for a focused chemical list of 14 laulimalides marine macrolides against SARS-CoV-2 main protease (Mpro) using a set of integrated modern computational techniques including molecular docking (MDock), molecule dynamic simulations (MDS) and structure-activity relationships (SARs). Based on their remarkable ligand-protein energy scores and relevant binding affinities with SARS-CoV-2 (Mpro) pocket residues, two promising macrolides [laulimalides LA4 (6) and LA18 (13)] are selected as proposed inhibitor compounds. Consequently, they are thermodynamically investigated by deciphering their MD simulations at 100 ns, where they show noticeable stability within the accommodated (Mpro) pockets. Moreover, in-deep SARs studies suggest crucial roles for C-23 substituted side chain and C-20 methoxy as essential pharmacophoric structural features for activity. Further in vitro/vivo examinations of the selected marine macrolides would pave the way towards developing effective antiviral drugs from natural resources

Combining DFT and QSAR computation to predict the interaction of flavonoids with the GABA (A) receptor using electronic and topological descriptors

AbstractTo establish a quantitative structure-activity relationship model of the binding affinity constants (−log Ki) of 41 flavonoid derivatives towards the GABA (A) receptor, the DFT-B3LYP method with basis set 6-31G (d) was performed to gain insights into the chemical structure and property information for the studied compounds. The best topological and electronic descriptors were selected. This work was conducted with principal component analysis (PCA), multiple linear regression (MLR), multiple non-linear regression (MNLR) and artificial neural network (ANN). According to these analyses, we propose quantitative models and interpret the activity of the compounds based on multivariate statistical analysis. The statistical results of the MLR, MNLR and ANN indicate that the determination coefficients R2 were 0.896, 0.925 and 0.916, respectively. The results show that the three modelling methods can predict the studied activity well and may be useful for predicting the biological activity of new compounds. The statistical results indicate that the models are statistically significant and stable with data variation in the external validation

Cephalostatins and ritterazines: Distinctive dimeric marine-derived steroidal pyrazine alkaloids with intriguing anticancer activities

Cephalostatins and ritterazines represent fascinating classes of dimeric marine derived steroidal alkaloids with unique chemical structures and promising biological activities. Originally isolated from marine tube worms and the tunicate Ritterella tokioka collected off the coast of Japan, cephalostatins and ritterazines display potent anticancer effects by inducing apoptosis, disrupting cell cycle progression, and targeting multiple molecular pathways. This review covers the chemistry and bioactivities of 45 cephalostatins and ritterazines from 1988 to 2024, highlighting their complex structures and medicinal contributions. With insights into their structure activity relationships (SAR). Key structural elements, such as the pyrazine ring and 5/6 spiroketal moieties, are found crucial for their biological effects, suggesting interactions with lipid membranes or hydrophobic protein domains. Additionally, the formation of oxocarbenium ions from spiroketal cleavage may enhance their potency by covalently modifying DNA. The pharmacokinetics, ADMET and Drug likeness properties of these steroidal alkaloids are thoroughly addressed. Drug likeness analysis shows that these compounds fit well with the Rule of 4 (Ro4) for Protein-Protein Interaction Drugs (PPIDs), underscoring their potential in this area. Ten compounds (20, 27, 33, 34, 39, 40, 41, 42, 43, and 45) have demonstrated favourable pharmacokinetic and ADMET profiles, making them promising candidates for further research. Future efforts should focus on alternative administration routes, structural modifications, and innovative delivery systems, such as prodrugs and nanoparticles, to improve bioavailability and therapeutic effects. Advances in synthetic chemistry, mechanistic insights, and interdisciplinary collaborations will be essential for translating cephalostatins and ritterazines into effective anticancer therapies