Auxins, auxin transport inhibitors, and competitors for auxin receptors do not show statistically significant differences in 212 molecular descriptors

[EN] This study compares 212 molecular descriptors of four auxins (indolebutyric acid; indoleacetic acid; 2,4-dichlorophenoxyacetic acid; 1-naphthaleneacetic acid), three auxin transport inhibitors [2-(naphthalen-1-ylcarbamoyl)benzoic acid; 2,3,5-triiodobenzoic acid; 9-hydroxy-9H-fluorene-9-carboxylic acid], and five competitors for auxin receptors [2-(2,4,6-trichlorophenoxy)acetic acid; 2-(4-chlorophenoxy)-2-methylpropanoic acid; 3-phenylpropanoic acid; 3-(2-chlorophenoxy)butanoic acid; 2-amino-3-(5-methyl-1H-indol-3yl) propanoic acid]. The analysed compounds did not show statistically significant differences in any of those descriptors, suggesting that chemical and structural differences, per se, do not determine their functional diversities. We propose that combination with other, yet unknown chemical groups confers the specificity necessary for these molecules to act as auxins, as auxin transport inhibitors or auxin receptor competitors.This research was supported by the Bioplant Centre (University of Ciego de Avila, Cuba) and the Universitat Politecnica de Valencia (Spain).Andújar, I.; Gómez, D.; Pérez, L.; Vicente, O.; Lorenzo, JC. (2019). Auxins, auxin transport inhibitors, and competitors for auxin receptors do not show statistically significant differences in 212 molecular descriptors. Romanian Biotechnological Letters. 24(3):407-411. https://doi.org/10.25083/rbl/24.3/407.411S40741124

Physicochemical properties, pharmacokinetic studies, DFT approach, and antioxidant activity of nitro and chloro indolinone derivatives

The process of developing of new drugs is greatly hampered by their inadequate physicochemical, pharmacokinetic, and intrinsic characteristics. In this regard, the selected chloro indolinone, (Z)-6-chloro-3-(2-chlorobenzylidene)indolin-2-one (C1), and nitro indolinone, (Z)-6-chloro-3-(2-nitrobenzylidene)indolin-2-one (C2), were subjected to SwissADME and density function theory (DFT) analysis. For compounds C1 and C2, the BOILED-Egg pharmacokinetic model predicted intestinal absorption, blood–brain barrier (BBB) penetration, and p-glycoprotein interaction. According to the physicochemical analysis, C1 has exceptional drug-like characteristics suitable for oral absorption. Despite only being substrates for some of the major CYP 450 isoforms, compounds C1 and C2 were anticipated to have strong plasma protein binding and efficient distribution and block these isoforms. The DFT study using the B3LYP/6-311G(d,p) approach with implicit water effects was performed to assess the structural features, electronic properties, and global reactivity parameters (GRP) of C1 and C2. The DFT results provided further support for other studies, implying that C2 is more water-soluble than C1 and that both compounds can form hydrogen bonds and (weak) dispersion interactions with other molecules, such as solvents and biomolecules. Furthermore, the GRP study suggested that C1 should be more stable and less reactive than C2. A concentration-dependent 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS) radical scavenging activity was shown by both C1 and C2. In brief, this finding has provided a strong foundation to explore further the therapeutic potential of these molecules against a variety of human disorders

On the origins of three-dimensionality in drug-like molecules.

Aim Many medicinal chemistry-relevant structures and core scaffolds tend toward geometric planarity, which hampers the optimization of physicochemical properties desirable in drug-like molecules. As challenging drug target classes emerge, the exploitation of molecular three-dimensionality in lead optimization is becoming increasingly important. While recent interest has emphasized the importance of enhanced three-dimensionality in molecular fragment designs, the extent to which this is required in core scaffolds remains unclear.Materials & methods Three computational methods, Scaffold Tree deconstruction, Synthetic Disconnection Rules retrosynthetic deconstruction and virtual library enumeration, are applied, together with the descriptors plane of best fit and principal moments of inertia, to investigate the origins of three-dimensionality in drug-like molecules.Conclusion This study informs on the stage at which molecular three-dimensionality should be considered in drug design

Investigation of anti-nociceptive, anti-inflammatory potential and ADMET studies of pure compounds isolated from Isodon rugosus Wall. ex Benth

The strong ethnopharmacological utilization of Isodon rugosus Wall. Ex. Benth is evident in the treatment of several types of pain and inflammation, including toothache, earache, abdominal pain, gastric pain, and generalized body pain and inflammation. Based on this background, the antinociceptive effects of the crude extract, various fractions, and essential oil have been reported previously. In this research work, we isolate and characterize pure bioactive compounds from I. rugosus and evaluate possible mechanisms using various in vivo and in vitro models. The pure compounds were analyzed for analgesic and anti-inflammatory activities through various assays. The column chromatography of the chloroform fraction of I. rugosus led to the identification of two pure compounds, i.e., 1 and 2. Compound 1 demonstrated notable inhibition (62% writhing inhibition, 72.77% COX-2 inhibition, and 76.97% 5-LOX inhibition) and anti-inflammatory potential (>50% paw edema inhibition at various intervals). The possible mechanism involved in antinociception was considered primarily, a concept that has already been elucidated through the application of naloxone (an antagonist of opioid receptors). The involvement of adrenergic receptors was investigated using a hot plate model (an adrenergic receptor antagonist). The strong ethnomedicinal analgesic background of I. rugosus, supported by previous reports and current observations, leads to the conclusion that I. rugosus is a potential source of antinociceptive and anti-inflammatory bioactive compounds. It may be concluded from the results that the isolated analgesic compounds of I. rugosus may be a possible alternative remedy for pain and inflammation management with admirable efficacy and safety profiles

Synthesis, in-vitro inhibition of cyclooxygenases and in silico studies of new isoxazole derivatives

Isoxazole belongs to the class of five-membered heterocyclic compounds. The process of developing new drugs has significantly gained attention due to inadequate pharmacokinetic and safety attributes of the available drugs. This study aimed to design a new diverse array of ten novel isoxazole derivatives via Claisen Schmidt condensation reaction. In vitro COX-1/2 anti-inflammatory assay, in silico molecular docking of potent compounds, Molecular docking simulation, and SwissADME pharmacokinetic profile were investigated in this research. The in vitro COX-1 and COX-2 enzyme inhibitory assay showed that almost all the tested compounds exhibited anti-inflammatory effects whereas C6, C5, and C3 were found to be the most potent COX-2 enzyme inhibitors among the tested compounds and are good candidates for selective COX-2 inhibitors. In silico molecular docking studies coupled with molecular dynamic simulation has been done to rationalize the time-evolved mode of interaction of selected inhibitor inside the active pockets of target COX-2. The binding orientations and binding energy results also showed the selectivity of compounds towards COX-2. Physicochemical properties, pharmacokinetic profile, lipophilicity, water solubility, drug metabolism, drug-likeness properties, and medicinal chemistry of the synthesized isoxazole derivatives were assessed. The SwissADME (absorption, distribution, metabolism, and excretion) database was used to assess the physicochemical properties and drug-likeness properties of the synthesized isoxazole derivatives. All the compounds were shown high GI absorption except Compound 7 (C7). Compound 1 (C1) and Compound 2 (C2) were found to cross the blood-brain barrier (BBB). Lipinski’s rule of five is not violated by any of the ten synthesized isoxazole derivatives. It was predicted with the SwissADME database that C2, C5, C6, C7, and C8 are potent inhibitors of cytochrome (CYP) subtype CYP-2C19. A subtype of CYP-2C9 was inhibited by C4 and C7. The medicinal chemistry of all the compounds C1-C10 showed no PAIN (Pan assay interference compounds) alerts. The improved gastrointestinal (GI) absorption and BBB permeability of C1 and C2 can provide a future prospective for new researchers in the medicinal field to investigate the compounds for the management of chronic diseases. The synthesized isoxazole compounds showed excellent in vitro COX-1/2 enzymes anti-inflammatory investigations, in silico studies, good physicochemical properties, and improved pharmacokinetic profile which will be further investigated via in vivo anti-inflammatory activities. Moreover, to further support our findings of the computational research and in vitro studies, an in-vivo pharmacokinetic profile is suggested in the future

Computational pharmacology and computational chemistry of 4-hydroxyisoleucine: Physicochemical, pharmacokinetic, and DFT-based approaches

Computational pharmacology and chemistry of drug-like properties along with pharmacokinetic studies have made it more amenable to decide or predict a potential drug candidate. 4-Hydroxyisoleucine is a pharmacologically active natural product with prominent antidiabetic properties. In this study, ADMETLab 2.0 was used to determine its important drug-related properties. 4-Hydroxyisoleucine is compliant with important drug-like physicochemical properties and pharma giants’ drug-ability rules like Lipinski’s, Pfizer, and GlaxoSmithKline (GSK) rules. Pharmacokinetically, it has been predicted to have satisfactory cell permeability. Blood–brain barrier permeation may add central nervous system (CNS) effects, while a very slight probability of being CYP2C9 substrate exists. None of the well-known toxicities were predicted in silico, being congruent with wet lab results, except for a “very slight risk” for respiratory toxicity predicted. The molecule is non ecotoxic as analyzed with common indicators such as bioconcentration and LC50 for fathead minnow and daphnia magna. The toxicity parameters identified 4-hydroxyisoleucine as non-toxic to androgen receptors, PPAR-γ, mitochondrial membrane receptor, heat shock element, and p53. However, out of seven parameters, not even a single toxicophore was found. The density functional theory (DFT) study provided support to the findings obtained from drug-like property predictions. Hence, it is a very logical approach to proceed further with a detailed pharmacokinetics and drug development process for 4-hydroxyisoleucine

Molecular similarity searching based on deep learning for feature reduction

The concept of molecular similarity has been widely used in rational drug design, where structurally similar molecules are explored in molecular databases for retrieving functionally similar molecules. The most used conventional similarity methods are two-dimensional (2D) fingerprints to evaluate the similarity of molecules towards a target query. However, these descriptors include redundant and irrelevant features that might impact the effectiveness of similarity searching methods. Moreover, the majority of existing similarity searching methods often disregard the importance of some features over others and assume all features are equally important. Thus, this study proposed three approaches for identifying the important features of molecules in chemical datasets. The first approach was based on the representation of the molecular features using Autoencoder (AE), which removes irrelevant and redundant features. The second approach was the feature selection model based on Deep Belief Networks (DBN), which are used to select only the important features. In this approach, the DBN is used to find subset of features that represent the important ones. The third approach was conducted to include descriptors that complement to each other. Different important features from many descriptors were filtered through DBN and combined to form a new descriptor used for molecular similarity searching. The proposed approaches were experimented on the MDL Data Drug Report standard dataset (MDDR). Based on the test results, the three proposed approaches overcame some of the existing benchmark similarity methods, such as Bayesian Inference Networks (BIN), Tanimoto Similarity Method (TAN), Adapted Similarity Measure of Text Processing (ASMTP) and Quantum-Based Similarity Method (SQB). The results showed that the performance of the three proposed approaches proved to be better in term of average recall values, especially with the use of structurally heterogeneous datasets that could produce results than other methods used previously to improve molecular similarity searching

Computational Estimation of Biliary Excretion of Compounds and the Role of Transporters

Biliary excretion is one of the main elimination pathways for drugs and/or their metabolites. Therefore, an insight into the structural profile of cholephilic compounds through accurate modelling of the biliary excretion is important for the estimation of clinical pharmacokinetics in early stages of drug discovery. The aim of this project was to develop Quantitative Structure-Activity Relationships(QSAR) as computational tools for the estimation of biliary excretion. In addition, the structural requirements for biliary excretion were investigated in relation to the structural requirements for binding to uptake and efflux transporter proteins that are involved in hepatobiliary elimination. The study used three datasets; 1. percentage of dose excreted intact into bile in rat for 217 compounds, 2. P-gp inhibition constants for 219 compound, 3. percentage inhibition of OATP transporters, OATP1B1, OATP1B3 and OATP2B1. Statistical techniques were stepwise regression analysis, Classification and Regression Trees (C&RT), Chi-square Automatic Interaction Detector (CHAID), Boosted trees (BT), Random Forest (RF) and Multivariate Adaptive Regression Splines (MARS) models. The study resulted in QSARs for the prediction of biliary excretion, P-gp binding constants and percentage inhibition of OATPs, along with QSARs incorporating predicted P-gp and OATP inhibition values for the prediction of biliary excretion. Simple regression tree models were of similar accuracy to the boosted trees model in the estimation of the percentage of bile excretion of compounds. Molecular descriptors selected by these models indicated a higher biliary excretion for relatively hydrophilic compounds especially if they have acid/base dissociation, and a large molecular size above 348 Da. The major role of OATPs in biliary excretion was indicated using interactive decision tree models with OATP1B1 binding being the most successful predictor of biliary excretion amongst the three OATP subfamilies. In contrast, predicted P-gp binding parameters were not successful in the prediction of biliary excretion. This may be due to problems in extrapolating the in vitro P-gp binding data to the in vivo situation, or due to the difference in the chemical spaces of the P-gp and biliary excretion datasets which may lead to the compounds in biliary excretion dataset to fall outside the applicability domain of the P-gp models