Aconitum and Delphinium alkaloids of curare-like activity. QSAR analysis and molecular docking of alkaloids into AChBP

Stereocontrolled synthesis of the aconitine D ring from D-glucose

The synthesis of a fully oxygenated aconitine D ring precursor from (D)-(+)-glucose is described. The route features a highly diastereoselective alkynyl Grignard ketone addition and a base-mediated enelactone to 1,3-diketone rearrangement.

Design and Evaluation of Nanoscale Materials with Programmed Responsivity towards Epigenetic Enzymes

Self-assembled materials capable of modulating their assembly properties in response to specific enzymes play a pivotal role in advancing 'intelligent' encapsulation platforms for biotechnological applications. Here, we introduce a previously unreported class of synthetic nanomaterials that programmatically interact with histone deacetylase (HDAC) as the triggering stimulus for disassembly. These nanomaterials consist of co-polypeptides comprising poly (acetyl L-lysine) and poly(ethylene glycol) blocks. Under neutral pH conditions, they self-assemble into particles. However, their stability is compromised upon exposure to HDACs, depending on enzyme concentration and exposure time. Our investigation, utilizing HDAC8 as the model enzyme, revealed that the primary mechanism behind disassembly involves a decrease in amphiphilicity within the block copolymer due to the deacetylation of lysine residues within the particles' hydrophobic domains. To elucidate the response mechanism, we encapsulated a fluorescent dye within these nanoparticles. Upon incubation with HDAC, the nanoparticle structure collapsed, leading to controlled release of the dye over time. Notably, this release was not triggered by denatured HDAC8, other proteolytic enzymes like trypsin, or the co-presence of HDAC8 and its inhibitor. We further demonstrated the biocompatibility and cellular effects of these materials and conducted a comprehensive computational study to unveil the possible interaction mechanism between enzymes and particles. By drawing parallels to the mechanism of naturally occurring histone proteins, this research represents a pioneering step toward developing functional materials capable of harnessing the activity of epigenetic enzymes such as HDACs.

Quantitative Structure-Permittivity Relationship Study of a Series of Polymers

Dielectric constant is an important property which is widely utilized in many scientific fields and characterizes the degree of polarization of substances under the external electric field. In this work, a structure-property relationship of the dielectric constants (ε) for a diverse set of polymers was investigated. A transparent mechanistic model was developed with the application of a machine learning approach that combines genetic algorithm and multiple linear regression analysis, to obtain a mechanistically explainable and transparent model. Based on the evaluation conducted using various validation criteria, four- and eight-variable models were proposed. The best model showed a high predictive performance for training and test sets, with R2 values of 0.905 and 0.812, respectively. Obtained statistical performance results and selected descriptors in the best models were analyzed and discussed. With the validation procedures applied, the models were proven to have a good predictive ability and robustness for further applications in polymer permittivity prediction.

Aconitine and its derivatives: bioactivities, structure-activity relationships and preliminary molecular mechanisms

Aconitine (AC), which is the primary bioactive diterpene alkaloid derived from Aconitum L plants, have attracted considerable interest due to its unique structural feature. Additionally, AC demonstrates a range of biological activities, such as its ability to enhance cardiac function, inhibit tumor growth, reduce inflammation, and provide analgesic effects. However, the structure-activity relationships of AC are remain unclear. A clear understanding of these relationships is indeed critical in developing effective biomedical applications with AC. In line with these challenges, this paper summarized the structural characteristics of AC and relevant functional and bioactive properties and the structure-activity relationships presented in biomedical applications. The primary temporal scope of this review was established as the period spanning from 2010 to 2023. Subsequently, the objective of this review was to provide a comprehensive understanding of the specific action mechanism of AC, while also exploring potential novel applications of AC derivatives in the biomedical field, drawing upon their structural characteristics. In conclusion, this review has provided a comprehensive analysis of the challenges and prospects associated with AC in the elucidation of structure-bioactivity relationships. Furthermore, the importance of exploring modern biotechnology approaches to enhance the potential biomedical applications of AC has been emphasized.

Therapeutic Potentials of Aconite-like Alkaloids: Bioinformatics and Experimental Approaches

Compounds from plants that are used in traditional medicine may have medicinal properties. It is well known that plants belonging to the genus Aconitum are highly poisonous. Utilizing substances derived from Aconitum sp. has been linked to negative effects. In addition to their toxicity, the natural substances derived from Aconitum species may have a range of biological effects on humans, such as analgesic, anti-inflammatory, and anti-cancer characteristics. Multiple in silico, in vitro, and in vivo studies have demonstrated the effectiveness of their therapeutic effects. In this review, the clinical effects of natural compounds extracted from Aconitum sp., focusing on aconitelike alkaloids, are investigated particularly by bioinformatics tools, such as the quantitative structure- activity relationship method, molecular docking, and predicted pharmacokinetic and pharmacodynamic profiles. The experimental and bioinformatics aspects of aconitine's pharmacogenomic profile are discussed. Our review could help shed light on the molecular mechanisms of Aconitum sp. compounds. The effects of several aconite-like alkaloids, such as aconitine, methyllycacintine, or hypaconitine, on specific molecular targets, including voltage-gated sodium channels, CAMK2A and CAMK2G during anesthesia, or BCL2, BCL-XP, and PARP-1 receptors during cancer therapy, are evaluated. According to the reviewed literature, aconite and aconite derivatives have a high affinity for the PARP-1 receptor. The toxicity estimations for aconitine indicate hepatotoxicity and hERG II inhibitor activity; however, this compound is not predicted to be AMES toxic or an hERG I inhibitor. The efficacy of aconitine and its derivatives in treating many illnesses has been proven experimentally. Toxicity occurs as a result of the high ingested dose; however, the usage of this drug in future research is based on the small quantity of an active compound that fulfills a therapeutic role.

Stability Constant and Potentiometric Sensitivity of Heavy Metal-Organic Fluorescent Compound Complexes: QSPR Models for Prediction and Design of Novel Coumarin-like Ligands

Industrial wastewater often consists of toxic chemicals and pollutants, which are extremely harmful to the environment. Heavy metals are toxic chemicals and considered one of the major hazards to the aquatic ecosystem. Analytical techniques, such as potentiometric methods, are some of the methods to detect heavy metals in wastewaters. In this work, the quantitative structure-property relationship (QSPR) was applied using a range of machine learning techniques to predict the stability constant (logβ_ML) and potentiometric sensitivity (PS_ML) of 200 ligands in complexes with the heavy metal ions Cu²⁺, Cd²⁺, and Pb²⁺. In result, the logβML models developed for four ions showed good performance with square correlation coefficients (R²) ranging from 0.80 to 1.00 for the training and 0.72 to 0.85 for the test sets. Likewise, the PSML displayed acceptable performance with an R² of 0.87 to 1.00 for the training and 0.73 to 0.95 for the test sets. By screening a virtual database of coumarin-like structures, several new ligands bearing the coumarin moiety were identified. Three of them, namely NEW02, NEW03, and NEW07, showed very good sensitivity and stability in the metal complexes. Subsequent quantum-chemical calculations, as well as physicochemical/toxicological profiling were performed to investigate their metal-binding ability and developability of the designed sensors. Finally, synthesis schemes are proposed to obtain these three ligands with major efficiency from simple resources. The three coumarins designed clearly demonstrated capability to be suitable as good florescent chemosensors towards heavy metals. Overall, the computational methods applied in this study showed a very good performance as useful tools for designing novel fluorescent probes and assessing their sensing abilities.

A review on efforts for improvement in medicinally important chemical constituents inAconitum through biotechnological interventions

The genus Aconitum belongs to the family Ranunculaceae, is endowed with more than 350 species on the earth. Medicinally important aconitine type of diterpenoid alkaloids are the characteristic compounds in most of the Aconitum species. The present review endeavored the major research carried out in the field of genetic resource characterization, pharmacological properties, phytochemistry, major factors influencing quantity, biosynthetic pathways and processing methods for recovery of active ingredients, variety improvement, propagation methods, and important metabolite production through cell/organ culture of various Aconitum species. More than 450 derivatives of aconitine-type C19 and C20-diterpenoid alkaloids along with a few other non-alkaloidal compounds, such as phenylpropanoids, flavonoids, terpenoids, and fatty acids, have been identified in the genus. A few Aconitum species and their common diterpenoid alkaloid compounds are also well characterized for analgesic, inflammatory and cytotoxic properties. However, the different isolated compound needs to be validated for supporting other traditional therapeutical uses of the plant species. Aconitine alkaloids shared common biosynthesis pathway, but their diversification mechanism remains unexplored in the genus. Furthermore, the process needs to be developed on secondary metabolite recovery, mass-scale propagation methods, and agro-technologies for maintaining the quality of products. Many species are losing their existence in nature due to over-exploitation or anthropogenic factors; thus, temporal monitoring of the population status in its habitat, and suitable management programs for ascertaining conservation needs to be developed.

Isolation, Structure Elucidation, Semi-Synthesis, and Structural Modification of C19-Diterpenoid Alkaloids from Aconitum apetalum and Their Neuroprotective Activities

Five new aconitine-type C₁₉-diterpenoid alkaloids, apetalrines A-E (1-5), were isolated from Aconitum apetalum. Their structures were determined by analysis of 1D and 2D NMR, IR, and HRESIMS data. Semisynthesis of apetalrine B (2) from its parent compound aconorine was achieved to confirm the structure proposed. Twenty derivatives of 2 (11a-11l, 12a, 12b, 12d, 12e, 12j, 12k, 12m, 12n) were synthesized via a unified approach relying on simple coupling reactions. The evaluation of neuroprotective effects of compounds (1-5, 11b, 11c, 11f-11i, 12a, 12b, 12d, 12e, 12k, 12m, 12n) with low cytotoxicity revealed compound 2 to exhibit good neuroprotective effects in H₂O₂-treated SH-SY5Y cells at a concentration of 50 μM. A series of studies using flow cytometry, staining, and Western blotting on 2 indicated that its neuroprotective effects may arise from inhibiting cell apoptosis.

A Refractive Index Study of a Diverse Set of Polymeric Materials by QSPR with Quantum-Chemical and Additive Descriptors

Predicting the activities and properties of materials via in silico methods has been shown to be a cost- and time-effective way of aiding chemists in synthesizing materials with desired properties. Refractive index (n) is one of the most important defining characteristics of an optical material. Presented in this work is a quantitative structure–property relationship (QSPR) model that was developed to predict the refractive index for a diverse set of polymers. A number of models were created, where a four-variable model showed the best predictive performance with R² = 0.904 and Q²_LOO = 0.897. The robustness and predictability of the best model was validated using the leave-one-out technique, external set and y-scrambling methods. The predictive ability of the model was confirmed with the external set, showing the R²_ext = 0.880. For the refractive index, the ionization potential, polarizability, 2D and 3D geometrical descriptors were the most influential properties. The developed model was transparent and mechanistically explainable and can be used in the prediction of the refractive index for new and untested polymers.

Amino substituted nitrogen heterocycle ureas as kinase insert domain containing receptor (KDR) inhibitors: Performance of structure–activity relationship approaches

A quantitative structure–activity relationship (QSAR) study was performed on a set of amino-substituted nitrogen heterocyclic urea derivatives. Two novel approaches were applied: (1) the simplified molecular input-line entry systems (SMILES) based optimal descriptors approach; and (2) the fragment-based simplex representation of molecular structure (SiRMS) approach. Comparison with the classic scheme of building up the model and balance of correlation (BC) for optimal descriptors approach shows that the BC scheme provides more robust predictions than the classic scheme for the considered pIC₅₀ of the heterocyclic urea derivatives. Comparison of the SMILES-based optimal descriptors and SiRMS approaches has confirmed good performance of both techniques in prediction of kinase insert domain containing receptor (KDR) inhibitory activity, expressed as a logarithm of inhibitory concentration (pIC50) of studied compounds.

From basic physics to mechanisms of toxicity: the "liquid drop" approach applied to develop predictive classification models for toxicity of metal oxide nanoparticles

Many metal oxide nanoparticles are able to cause persistent stress to live organisms, including humans, when discharged to the environment. To understand the mechanism of metal oxide nanoparticles' toxicity and reduce the number of experiments, the development of predictive toxicity models is important. In this study, performed on a series of nanoparticles, the comparative quantitative-structure activity relationship (nano-QSAR) analyses of their toxicity towards E. coli and HaCaT cells were established. A new approach for representation of nanoparticles' structure is presented. For description of the supramolecular structure of nanoparticles the "liquid drop" model was applied. It is expected that a novel, proposed approach could be of general use for predictions related to nanomaterials. In addition, in our study fragmental simplex descriptors and several ligand-metal binding characteristics were calculated. The developed nano-QSAR models were validated and reliably predict the toxicity of all studied metal oxide nanoparticles. Based on the comparative analysis of contributed properties in both models the LDM-based descriptors were revealed to have an almost similar level of contribution to toxicity in both cases, while other parameters (van der Waals interactions, electronegativity and metal-ligand binding characteristics) have unequal contribution levels. In addition, the models developed here suggest different mechanisms of nanotoxicity for these two types of cells.

Receptor- and ligand-based study of fullerene analogues: comprehensive computational approach including quantum-chemical, QSAR and molecular docking simulations

Fullerene and its derivatives have potential antiviral activity due to their specific binding interactions with biological molecules. In this study fullerene derivatives were investigated by the synergic combination of three approaches: quantum-mechanical calculations, protein-ligand docking and quantitative structure-activity relationship methods. The protein-ligand docking studies and improved structure-activity models have been able both to predict binding affinities for the set of fullerene-C60 derivatives and to help in finding mechanisms of fullerene derivative interactions with human immunodeficiency virus type 1 aspartic protease, HIV-1 PR. Protein-ligand docking revealed several important molecular fragments that are responsible for the interaction with HIV-1 PR. In addition, a density functional theory method has been utilized to identify the optimal geometries and predict physico-chemical parameters of the studied compounds. The 5-variable GA-MLRA based model showed the best predictive ability (r(2)training = 0.882 and r(2)test = 0.738), with high internal and external correlation coefficients.

Aconitum and delphinium diterpenoid alkaloids of local anesthetic activity: comparative QSAR analysis based on GA-MLRA/PLS and optimal descriptors approach

The duration of anesthesia (related to protein binding of a drug) and the onset time (determined by the pKa) are important characteristics in assessment of local anesthetic agents. They are known to be affected by a number of factors. Early studies of antiarrhythmic diterpenoid alkaloids from plants Aconitum and Delphinium suggested that they possess local anesthetic activity due to their ability to suppress sodium currents of excited membranes. In this study we utilized toxicity, duration, and onset of action as endpoints to construct Quantitative Structure-Activity Relationship (QSAR) models for the series of 34 diterpenoid alkaloids characterized by local anesthetic activity using genetic algorithm-based multiple linear regression analysis/partial least squares and simplified molecular input line entry system (SMILES)-based optimal descriptors approach. The developed QSAR models correctly reflected factors that determine three endpoints of interest. Toxicity correlates with descriptors describing partition and reactivity of compounds. The duration of anesthesia was encoded by the parameters defining the ability of a compound to bind at the receptor site. The size and number of H-bond acceptor atoms were found not to favor the speed of onset, while topographic electronic descriptor demonstrated strong positive effect on it. SMILES-based optimal descriptors approach resulted in overall improvement of models. This approach was shown to be more sensitive to structural peculiarities of molecules than regression methods. The results clearly indicate that obtained QSARs are able to provide distinct rationales for compounds optimization with respect to particular endpoint.

A phylogeny of Delphinieae (Ranunculaceae) shows that Aconitum is nested within Delphinium and that Late Miocene transitions to long life cycles in the Himalayas and Southwest China coincide with bursts in diversification

The tribe Delphinieae (Ranunculaceae) comprises two species-rich genera, Aconitum and Delphinium, the latter including Consolida and Aconitella. The 650-700 species are distributed in Eurasia and North America; three species occur on tropical African mountains. Maximum likelihood analyses of 2088 aligned nucleotides of plastid and nuclear sequences obtained from up to 185 species of Delphinieae from throughout the geographic range (plus relevant outgroups) show that three short-lived (facultative annual or biennial) Mediterranean species belonging to Delphinium subgenus Staphisagria are the sister clade to all other Delphinieae, implying that Staphisagria needs to be raised to genus status if Delphinium and Aconitum are to become mutually monophyletic. Molecular clock dating suggests an origin of the sampled Delphinieae in the Early Oligocene (c. 32.3 Ma) and expansion to North America of Aconitum and Delphinium around 3.3 and 2.9 Ma ago, respectively; the East African Mts. were reached by long-distance dispersal some 2.4 Ma ago, coincident with the major uplift of the East African Rift system. The ancestral growth form of the Delphinieae could not be reconstructed, but Late Miocene bursts in diversification rates in the Himalayan and southwestern Chinese clades of Aconitum and Delphinium appear to be associated with transitions from short-lived to long-lived life histories.

Discrimination of agonists versus antagonists of nicotinic ligands based on docking onto AChBP structures

Numerous high-resolution crystallographic structures of the acetylcholine binding protein (AChBP), a molluscan cholinergic protein, homologous to the extracellular domain of nicotinic acetylcholine receptors, are available. This offers opportunities to model the interaction between various ligands and the acetylcholine binding site. Herein we present a study of the interplay between ligand binding and motions of the C-loop capping the binding site. Nicotinic agonists and antagonists were docked on AChBP X-ray structures. It is shown that the studied agonists and antagonists can be discriminated according to their higher affinities for structures respectively obtained in the presence of agonists or antagonists, highlighting the fact that AChBP structures retain a pharmacological footprint of the compound used in crystallography experiments. A detailed analysis of the binding site cavities suggests that this property is mainly related to the shape of the cavities.