Targeting Peptidyl-prolyl Cis-trans Isomerase NIMA-interacting 1: A Structure-based Virtual Screening Approach to Find Novel Inhibitors

Limonoids from neem (Azadirachta indica A. Juss.) are potential anticancer drug candidates

Neem (Azadirachta indica A. Juss.), a versatile evergreen tree recognized for its ethnopharmacological value, is a rich source of limonoids of the triterpenoid class, endowed with potent medicinal properties. Extracts of neem have been documented to display anticancer effects in diverse malignant cell lines as well as in preclinical animal models that has largely been attributed to the constituent limonoids. Of late, neem limonoids have become the cynosure of research attention as potential candidate agents for cancer prevention and therapy. Among the various limonoids found in neem, azadirachtin, epoxyazadiradione, gedunin, and nimbolide, have been extensively investigated for anticancer activity. Azadirachtin, a potent biodegradable pesticide, exhibits profound antiproliferative effects by preventing mitotic spindle formation and cell division. The antiproliferative activity of gedunin has been demonstrated to be mediated primarily via inhibition of heat shock protein90 and its client proteins. Epoxyazadiradione inhibits pro-inflammatory and kinase-driven signaling pathways to block tumorigenesis. Nimbolide, the most potent cytotoxic neem limonoid, inhibits the growth of cancer cells by regulating the phosphorylation of keystone kinases that drive oncogenic signaling besides modulating the epigenome. There is overwhelming evidence to indicate that neem limonoids exert anticancer effects by preventing the acquisition of hallmark traits of cancer, such as cell proliferation, apoptosis evasion, inflammation, invasion, angiogenesis, and drug resistance. Neem limonoids are value additions to the armamentarium of natural compounds that target aberrant oncogenic signaling to inhibit cancer development and progression.

Cell-Penetrating Milk-Derived Peptides with a Non-Inflammatory Profile

Milk-derived peptides are known to confer anti-inflammatory effects. We hypothesised that milk-derived cell-penetrating peptides might modulate inflammation in useful ways. Using computational techniques, we identified and synthesised peptides from the milk protein Alpha-S1-casein that were predicted to be cell-penetrating using a machine learning predictor. We modified the interpretation of the prediction results to consider the effects of histidine. Peptides were then selected for testing to determine their cell penetrability and anti-inflammatory effects using HeLa cells and J774.2 mouse macrophage cell lines. The selected peptides all showed cell penetrating behaviour, as judged using confocal microscopy of fluorescently labelled peptides. None of the peptides had an effect on either the NF-κB transcription factor or TNFα and IL-1β secretion. Thus, the identified milk-derived sequences have the ability to be internalised into the cell without affecting cell homeostatic mechanisms such as NF-κB activation. These peptides are worthy of further investigation for other potential bioactivities or as a naturally derived carrier to promote the cellular internalisation of other active peptides.

Assessment of host-guest molecular encapsulation of eugenol using β-cyclodextrin

Eugenol is a natural compound with well-known repellent activity. However, its pharmaceutical and cosmetic applications are limited, since this compound is highly volatile and thermolabile. Nanoencapsulation provides protection, stability, conservation, and controlled release for several compounds. Here, eugenol was included in β-cyclodextrin, and the complex was characterized through X-ray diffraction analysis (XRD) and Fourier-transform infrared spectroscopy (FTIR). Additionally, we used molecular dynamics simulations to explore the eugenol-β-cyclodextrin complex stability with temperature increases. Our computational result demonstrates details of the molecular interactions and conformational changes of the eugenol-β-cyclodextrin complex and explains its stability between temperatures 27°C and 48°C, allowing its use in formulations that are subjected to varied temperatures.

In Vitro Antibacterial Activity and in Silico Analysis of the Bioactivity of Major Compounds Obtained from the Essential Oil of Virola surinamensis Warb (Myristicaceae)

Essential oils are well known for their antimicrobial activity and they are used as an effective food preservative. Virola is one of the five genera of Myristicaceae and this genus is native to the American continent, especially in neotropical regions. The largest number of species of this genus is found in the Amazon region and the most important species include Virola surinamensis Warb. and Virola sebifera Aubl. In the present study, we describe the chemical composition of the essential oil of the V. surinamensis obtained at two different periods of the day in two seasons (rainy and dry), as well as their antimicrobial activity against pathogenic bacterial strains of Pseudomonas aeruginosa, Escherichia coli, and Staphylococcus aureus. In addition, we investigated, using in silico tools, the antimicrobial activity of the major chemical compounds present in the essential oil of V. surinamensis. The samples collected at different seasons and times showed a similar chemical profile, characterized by the major constituents α-pinene (>33%) and β-pinene (>13%). The essential oil of V. surinamensis showed an interesting antibacterial activity, exhibiting low inhibitory concentrations against the tested bacterial species. The computational investigation indicated that limonene, myrcene, and β-pinene could be related to the antibacterial activity against the tested pathogenic bacterial strains. Our results shed light on the possible constituents of essential oil that could be related to its activity against bacterial species and might be useful for further experimental tests that aim to discover new potential antibacterial agents for food preservation.

Virtual screening of natural products against 5-enolpyruvylshikimate-3-phosphate synthase using the Anagreen herbicide-like natural compound library

The shikimate pathway enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) catalyzes a reaction involved in the production of amino acids essential for plant growth and survival. EPSPS is the main target of glyphosate, a broad-spectrum herbicide that acts as a competitive inhibitor concerning phosphoenolpyruvate (PEP), which is the natural substrate of EPSPS. In the present study, we introduce a natural compound library, named Anagreen, which is a compendium of herbicide-like compounds obtained from different natural product databases. Herein, we combined the structure- and ligand-based virtual screening strategies to explore Anagreen against EPSPS using the structure of glyphosate complexed with a T102I/P106S mutant of EPSPS from Eleusine indica (EiEPSPS) as a starting point. First, ligand-based pharmacophore screening was performed to select compounds with a similar pharmacophore to glyphosate. Then, structure-based pharmacophore modeling was applied to build a model which represents the molecular features of glyphosate. Then, consensus docking was performed to rank the best poses of the natural compounds against the PEP binding site, and then molecular dynamics simulations were performed to analyze the stability of EPSPS complexed with the selected ligands. Finally, we have investigated the binding affinity of the complexes using free energy calculations. The selected hit compound, namely AG332841, showed a stable conformation and binding affinity to the EPSPS structure and showed no structural similarity to the already known weed EPSPS inhibitors. Our computational study aims to clarify the inhibition of the mutant EiEPSPS, which is resistant to glyphosate, and identify new potential herbicides from natural products.

Gonçalves Vianez JL, Santana da Costa K, de Molfetta FA, Nahum Alves C. Analysis of Kojic Acid Derivatives as Competitive Inhibitors of Tyrosinase: A Molecular Modeling Approach

Tyrosinases belong to the functional copper-containing proteins family, and their structure contains two copper atoms, in the active site, which are coordinated by three histidine residues. The biosynthesis of melanin in melanocytes has two stages depending on the actions of the natural substrates L-DOPA and L-tyrosine. The dysregulation of tyrosinase is involved in skin cancer initiation. In the present study, using molecular modeling tools, we analyzed the inhibition activity of tyrosinase activity using kojic acid (KA) derivatives designed from aromatic aldehydes and malononitrile. All derivatives showed conformational affinity to the enzyme active site, and a favorable distance to chelate the copper ion, which is essential for enzyme function. Molecular dynamics simulations revealed that the derivatives formed promising complexes, presenting stable conformations with deviations between 0.2 and 0.35 Å. In addition, the investigated KA derivatives showed favorable binding free energies. The most stable KA derivatives showed the following binding free energies: -17.65 kcal mol-1 (D6), -18.07 kcal mol-1 (D2), -18.13 (D5) kcal mol-1, and -10.31 kcal mol-1 (D4). Our results suggest that these derivatives could be potent competitive inhibitors of the natural substrates of L-DOPA (-12.84 kcal mol-1) and L-tyrosine (-9.04 kcal mol-1) in melanogenesis.

Predicting cell-penetrating peptides using machine learning algorithms and navigating in their chemical space

Cell-penetrating peptides (CPPs) are naturally able to cross the lipid bilayer membrane that protects cells. These peptides share common structural and physicochemical properties and show different pharmaceutical applications, among which drug delivery is the most important. Due to their ability to cross the membranes by pulling high-molecular-weight polar molecules, they are termed Trojan horses. In this study, we proposed a machine learning (ML)-based framework named BChemRF-CPPred (beyond chemical rules-based framework for CPP prediction) that uses an artificial neural network, a support vector machine, and a Gaussian process classifier to differentiate CPPs from non-CPPs, using structure- and sequence-based descriptors extracted from PDB and FASTA formats. The performance of our algorithm was evaluated by tenfold cross-validation and compared with those of previously reported prediction tools using an independent dataset. The BChemRF-CPPred satisfactorily identified CPP-like structures using natural and synthetic modified peptide libraries and also obtained better performance than those of previously reported ML-based algorithms, reaching the independent test accuracy of 90.66% (AUC = 0.9365) for PDB, and an accuracy of 86.5% (AUC = 0.9216) for FASTA input. Moreover, our analyses of the CPP chemical space demonstrated that these peptides break some molecular rules related to the prediction of permeability of therapeutic molecules in cell membranes. This is the first comprehensive analysis to predict synthetic and natural CPP structures and to evaluate their chemical space using an ML-based framework. Our algorithm is freely available for academic use at http://comptools.linc.ufpa.br/BChemRF-CPPred .

Nimbolide, a Neem Limonoid, Is a Promising Candidate for the Anticancer Drug Arsenal

Nimbolide, a major limonoid constituent of Azadirachta indica, commonly known as neem, has attracted increasing research attention owing to its wide spectrum of pharmacological properties, predominantly anticancer activity. Nimbolide is reported to exert potent antiproliferative effects on a myriad cancer cell lines and chemotherapeutic efficacy in preclinical animal tumor models. The potentiality of nimbolide to circumvent multidrug resistance and aid in targeted protein degradation broaden its utility in enhancing therapeutic modalities and outcome. Accumulating evidence indicates that nimbolide prevents the acquisition of cancer hallmarks such as sustained proliferation, apoptosis evasion, invasion, angiogenesis, metastasis, and inflammation by modulating kinase-driven oncogenic signaling networks. Nimbolide has been demonstrated to abrogate aberrant activation of cellular signaling by influencing the subcellular localization of transcription factors and phosphorylation of kinases in addition to influencing the epigenome. Nimbolide, with its ever-expanding repertoire of molecular targets, is a valuable addition to the anticancer drug arsenal.

Targeting shikimate pathway: In silico analysis of phosphoenolpyruvate derivatives as inhibitors of EPSP synthase and DAHP synthase

The shikimate pathway consists of seven enzymatic steps involved in the conversion of erythrose-4-phosphate and phosphoenolpyruvate to chorismate and also responsible to the production of aromatic amino acids, such as phenylalanine, tyrosine, and tryptophan which are essential to the bacterial metabolism. The 3-deoxy-D-arabino-heptulosonate-7-phosphate synthase (DAHPS) and 5-enolpyruvylshikimate 3-phosphate synthase (EPSPS) catalyze important steps in the shikimate pathway using as substrate the phosphoenolpyruvate (PEP). Due to the importance of PEP in shikimate pathway, its structure has been investigated to develop new bioinspired competitive inhibitors against DAHPS and EPSPS. In the present study, we perform a literature survey of 28 PEP derivatives, then we analyzed the selectivity and affinity of these compounds against the EPSPS and DAHPS structures using consensual molecular docking, pharmacophore prediction, molecular dynamics (MD) simulations, and binding free energy calculations. Here, we propose consistent binding modes of the selected ligands and indicate that their structures show interesting pharmacophoric properties related to multi-targets inhibitors for both enzymes. Our computational results are supported by previous experimental findings related to the interactions of PEP derivatives with DAHPS and EPSPS structures.

Exploring the Potentiality of Natural Products from Essential Oils as Inhibitors of Odorant-Binding Proteins: A Structure- and Ligand-Based Virtual Screening Approach To Find Novel Mosquito Repellents

Odorant-binding proteins (OBPs) are the main olfactory proteins of mosquitoes, and their structures have been widely explored to develop new repellents. In the present study, we combined ligand- and structure-based virtual screening approaches using as a starting point 1633 compounds from 71 botanical families obtained from the Essential Oil Database (EssOilDB). Using as reference the crystallographic structure of N,N-diethyl-meta-toluamide interacting with the OBP1 homodimer of Anopheles gambiae (AgamOBP1), we performed a structural and pharmacophoric similarity search to select potential natural products from the library. Thymol acetate, 4-(4-methyl phenyl)-pentanal, thymyl isovalerate, and p-cymen-8-yl demonstrated a favorable chemical correlation with DEET and also had high-affinity interactions with the OBP binding pocket that molecular dynamics simulations showed to be stable. To the best of our knowledge, this is the first study to evaluate on a large scale the potentiality of NPs from essential oils as inhibitors of the mosquito OBP1 using in silico approaches. Our results could facilitate the design of novel repellents with improved selectivity and affinity to the protein binding pocket and can shed light on the mechanism of action of these compounds against insect olfactory recognition.