Investigating molecular descriptors in cell-penetrating peptides prediction with deep learning: Employing N, O, and hydrophobicity according to the Eisenberg scale.

Cell-penetrating peptides comprise a group of molecules that can naturally cross the lipid bilayer membrane that protects cells, sharing physicochemical and structural properties, and having several pharmaceutical applications, particularly in drug delivery. Investigations of molecular descriptors have provided not only an improvement in the performance of classifiers but also less computational complexity and an enhanced understanding of membrane permeability. Furthermore, the employment of new technologies, such as the construction of deep learning models using overfitting treatment, promotes advantages in tackling this problem. In this study, the descriptors nitrogen, oxygen, and hydrophobicity on the Eisenberg scale were investigated, using the proposed ConvBoost-CPP composed of an improved convolutional neural network with overfitting treatment and an XGBoost model with adjusted hyperparameters. The results revealed favorable to the use of ConvBoost-CPP, having as input nitrogen, oxygen, and hydrophobicity together with ten other descriptors previously investigated in this research line, showing an increase in accuracy from 88% to 91.2% in cross-validation and 82.6% to 91.3% in independent test.

BrainPepPass: A Framework Based on Supervised Dimensionality Reduction for Predicting Blood-Brain Barrier-Penetrating Peptides.

Peptides that pass through the blood-brain barrier (BBB) not only are implicated in brain-related pathologies but also are promising therapeutic tools for treating brain diseases, e.g., as shuttles carrying active medicines across the BBB. Computational prediction of BBB-penetrating peptides (B3PPs) has emerged as an interesting approach because of its ability to screen large peptide libraries in a cost-effective manner. In this study, we present BrainPepPass, a machine learning (ML) framework that utilizes supervised manifold dimensionality reduction and extreme gradient boosting (XGB) algorithms to predict natural and chemically modified B3PPs. The results indicate that the proposed tool outperforms other classifiers, with average accuracies exceeding 94% and 98% in 10-fold cross-validation and leave-one-out cross-validation (LOOCV), respectively. In addition, accuracy values ranging from 45% to 97.05% were achieved in the independent tests. The BrainPepPass tool is available in a public repository for academic use (https://github.com/ewerton-cristhian/BrainPepPass).

Comparative analysis of the reactivity of anthocyanidins, leucoanthocyanidins, and flavonols using a quantum chemistry approach.

Anthocyanidins, leucoanthocyanidins, and flavonols are natural compounds mainly known due to their reported biological activities, such as antiviral, antifungal, anti-inflammatory activities, and antioxidant activity. In the present study, we performed a comparative structural, conformational, electronic, and nuclear magnetic resonance analysis of the reactivity of the chemical structure of primary anthocyanidins, leucoanthocyanidins, and flavonoids. We focused our analysis on the following molecular questions: (i) differences in cyanidin catechols ( +)-catechin, leucocyanidin, and quercetin; (ii) the loss of hydroxyl presents in the R1 radical of leucoanthocyanidin in the functional groups linked to C4 (ring C); and (iii) the electron affinity of the 3-hydroxyl group (R7) in the flavonoids delphinidin, pelargonidin, cyanidin, quercetin, and kaempferol. We show unprecedented results for bond critical point (BCP) of leucopelargonidin and leucodelphirinidin. The BCP formed between hydroxyl hydrogen (R2) and ketone oxygen (R1) of kaempferol has the same degrees of covalence of quercetin. Kaempferol and quercetin exhibited localized electron densities between hydroxyl hydrogen (R2) and ketone oxygen (R1). Global molecular descriptors showed quercetin and leucocyanidin are the most reactive flavonoids in electrophilic reactions. Complementary, anthocyanidins are the most reactive in nucleophilic reactions, while the smallest gap occurs in delphinidin. Local descriptors indicate that anthocyanidins and flavonols are more prone to electrophilic attacks, while in leucoanthocyanidins, the most susceptible to attack are localized in the ring A. The ring C of anthocyanidins is more aromatic than the same found in flavonols and leucoanthocyanidins. METHODS: For the analysis of the molecular properties, we used the DFT to evaluate the formation of the covalent bonds and intermolecular forces. CAM-B3LYP functional with the def2TZV basis set was used for the geometry optimization. A broad analysis of quantum properties was performed using the assessment of the molecular electrostatic potential surface, electron localization function, Fukui functions, descriptors constructed from frontier orbitals, and nucleus independent chemical shift.

Host-Guest Inclusion Complexes of Natural Products and Nanosystems: Applications in the Development of Repellents.

Repellents are compounds that prevent direct contact between the hosts and the arthropods that are vectors of diseases. Several studies have described the repellent activities of natural compounds obtained from essential oils. In addition, these chemical constituents have been pointed out as alternatives to conventional synthetic repellents due to their interesting residual protection and low toxicity to the environment. However, these compounds have been reported with short shelf life, in part, due to their volatile nature. Nanoencapsulation provides protection, stability, conservation, and controlled release for several compounds. Here, we review the most commonly used polymeric/lipid nanosystems applied in the encapsulation of small organic molecules obtained from essential oils that possess repellent activity, and we also explore the theoretical aspects related to the intermolecular interactions, thermal stability, and controlled release of the nanoencapsulated bioactive compounds.

Biological Membrane-Penetrating Peptides: Computational Prediction and Applications.

Peptides comprise a versatile class of biomolecules that present a unique chemical space with diverse physicochemical and structural properties. Some classes of peptides are able to naturally cross the biological membranes, such as cell membrane and blood-brain barrier (BBB). Cell-penetrating peptides (CPPs) and blood-brain barrier-penetrating peptides (B3PPs) have been explored by the biotechnological and pharmaceutical industries to develop new therapeutic molecules and carrier systems. The computational prediction of peptides' penetration into biological membranes has been emerged as an interesting strategy due to their high throughput and low-cost screening of large chemical libraries. Structure- and sequence-based information of peptides, as well as atomistic biophysical models, have been explored in computer-assisted discovery strategies to classify and identify new structures with pharmacokinetic properties related to the translocation through biomembranes. Computational strategies to predict the permeability into biomembranes include cheminformatic filters, molecular dynamics simulations, artificial intelligence algorithms, and statistical models, and the choice of the most adequate method depends on the purposes of the computational investigation. Here, we exhibit and discuss some principles and applications of these computational methods widely used to predict the permeability of peptides into biomembranes, exhibiting some of their pharmaceutical and biotechnological applications.

Synthesis, Characterization, Applications, and Toxicity of Green Synthesized Nanoparticles.

Nanotechnology is a cutting-edge area with numerous industrial applications. Nanoparticles are structures that have dimensions ranging from 1 - 100 nm, which significantly exhibit different mechanical, optical, electrical, and chemical properties when compared with their larger counterparts. Synthetic routes that use natural sources, such as plant extracts, honey, and microorganisms, are environmentally friendly and low-cost methods that can be used to obtain nanoparticles. These methods of synthesis generate products that are more stable and less toxic than those obtained using conventional methods. Nanoparticles formed by titanium dioxide, zinc oxide, silver, gold, and copper, as well as cellulose nanocrystals, are among the nanostructures obtained by green synthesis that have shown interesting applications in several technological industries. Several analytical techniques have also been used to analyze the size, morphology, hydrodynamics, diameter, and chemical functional groups involved in the stabilization of the nanoparticles as well as to quantify and evaluate their formation. Despite their pharmaceutical, biotechnological, cosmetic, and food applications, studies have detected their harmful effects on human health and the environment, and thus, caution must be taken in uses involving living organisms. The present review aims to present an overview of the applications, the structural properties, and the green synthesis methods that are used to obtain nanoparticles, and special attention is given to those obtained from metal ions. The review also presents the analytical methods used to analyze, quantify, and characterize these nanostructures.

First report on the Annona exsucca DC. Essential oil and in silico identification of potential biological targets of its major compounds.

In the present study, the essential oil (EO) of Annona exsucca DC. or Rollinia exsucca was extracted by hydrodistillation, and the identification and quantification of volatile compounds were performed by GC-MS and GC-FID. A. exsucca leaves were collected from the Magalhães Barata, northeast of the State of Pará (Brazil) in March and September of 2019. Moreover, we used computational approaches to evaluate possible biological targets for the major compounds of the EO. In the sample obtained in March, 50 compounds were identified, with hydrocarbon sesquiterpenes being the predominant ones with the content of 80.52%. In the sample collected in September, 58 compounds were identified, and the chemical class of hydrocarbon monoterpenes and sesquiterpenes were the dominant ones with contents of 43.36 and 31.29%, respectively. Computational methods demonstrated that some major compounds have potential biological activity against some strains of pathogenic bacteria, as well as against molecular targets involved in cancer development.

Assessment of host-guest molecular encapsulation of eugenol using ß-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 ß-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-ß-cyclodextrin complex stability with temperature increases. Our computational result demonstrates details of the molecular interactions and conformational changes of the eugenol-ß-cyclodextrin complex and explains its stability between temperatures 27°C and 48°C, allowing its use in formulations that are subjected to varied temperatures.

Analysis of Conformational, Structural, Magnetic, and Electronic Properties Related to Antioxidant Activity: Revisiting Flavan, Anthocyanidin, Flavanone, Flavonol, Isoflavone, Flavone, and Flavan-3-ol.

Understanding the antioxidant activity of flavonoids is important to investigate their biological activities as well as to design novel molecules with low toxicity and high activity. Aromaticity is a chemical property found in cyclic structures that plays an important role in their stability and reactivity, and its investigation can help us to understand the antioxidant activity of some heterocyclic compounds. In the present study, we applied the density functional theory (DFT) to investigate the properties of seven flavonoid structures with well-reported antioxidant activity: flavan, anthocyanidin, flavanone, flavonol, isoflavone, flavone, and flavan-3-ol. Conformational, structural, magnetic, and electronic analyses were performed using nuclear magnetic resonance, ionization potentials, electron affinity, bond dissociation energy, proton affinity, frontier molecular orbitals (highest occupied molecular orbital (HOMO)/lowest unoccupied molecular orbital (LUMO)), and aromaticity through nucleus-independent chemical shifts to analyze these seven flavonoid structures. We revised the influence of hydroxyl groups on the properties of flavonoids and also investigated the influence of the aromaticity of these seven flavonoids on the antioxidant activity.

In silico analyses of toxicity of the major constituents of essential oils from two Ipomoea L. species.

Convolvulaceae Juss. is a family of vines and shrubs composed of species of ecological and economic importance. Ipomoea asarifolia (Desr.) Roem. & Schult. and I. setifera Poir. are ruderal and evergreen weeds that invade pastures and cause intoxication in cattle during the dry season. In the present study, the essential oils (EOs) of the leaves from I. setifera (dry season) and I. asarifolia (dry and wet seasons) were obtained by steam distillation for 3h. The chemical composition of the EOs was determined using gas chromatography coupled to gas spectrometry (CG/MS) and gas chromatography with flame ionization detector (CG-FID). To correlate the toxicity of the major chemical constituents of I. setifera and I. asarifolia EOs, we predicted the inhibition activity against the cytochrome P450 (CYP450) and P-glycoprotein 1 (P-gp) using a machine learning-based (ML-based) algorithm. In silico analyses were also applied to evaluate the pharmacokinetics properties related to the penetration in the blood-brain barrier (BBB) and gastrointestinal absorption. The chemical composition of the EO of I. setifera was characterized by high levels of (E)-caryophyllene (36.7%) and ß-elemene (20.49%). The I. asarifolia EO showed a phytol derivative as the main chemical constituent in the dry season (35.49%), and its content was reduced in the sample collected during the wet season (10.67%). The constituent (E)-caryophyllene was also present in the leaves of I. asarifolia, but at lower levels (15.93-19.93%) when compared to the EOs of I. setifera. Our computational analyses indicated that the constituents caryophyllene oxide, cedroxyde, pentadecanal, and phytol can be related to the toxicity of these weeds. This is the first study to report the chemical composition of I. asarifolia and I. setifera EOs and correlate their molecular mechanism of toxicity using in silico approaches.

Unraveling the conformational dynamics of glycerol 3-phosphate dehydrogenase, a nicotinamide adenine dinucleotide-dependent enzyme of Leishmania mexicana.

Allosteric changes modulate the enzymatic activity, leading to activation or inhibition of the molecular target. Understanding the induced fit accommodation mechanism of a ligand in its lowest-free energy state and the subsequent conformational changes induced in the protein are important questions for drug design. In the present study, molecular dynamics (MD) simulations, binding free energy calculations, and principal component analysis (PCA) were applied to analyze the glycerol-3-phosphate dehydrogenase of Leishmania mexicana (LmGPDH) conformational changes induced by its cofactor and substrate binding. GPDH is a nicotinamide adenine dinucleotide (NAD)-dependent enzyme, which has been reported as an interesting target for drug discovery and development against leishmaniasis. Despite its relevance for glycolysis and pentose phosphate pathways, the structural flexibility and conformational motions of LmGPDH in complex with NADH and dihydroxyacetone phosphate (DHAP) remain unexplored. Here, we analyzed the conformational dynamics of the enzyme-NADH complex (cofactor), and the enzyme-NADH-DHAP complex (adduct), mapped the hydrogen-bond interactions for the complexes and pointed some structural determinants of the enzyme that emerge from these contacts to NADH and DHAP. Finally, we proposed a consistent mechanism for the conformational changes on the first step of the reversible redox conversion of dihydroxyacetone phosphate to glycerol 3-phosphate, indicating key residues and interactions that could be further explored in drug discovery.

Measuring the structural impact of mutations on cytochrome P450 21A2, the major steroid 21-hydroxylase related to congenital adrenal hyperplasia.

Congenital adrenal hyperplasia is an inherited autosomal recessive disorder related to deficient cortisol synthesis. The deficiency of steroid 21-hydroxylase (cytochrome P450 21A2), an enzyme involved in cortisol synthesis, is responsible for ∼95% of cases of congenital adrenal hyperplasia. This metabolic disease exhibits three clinical forms: salt-wasting, simple virilizing, and non-classical form, which are divided according to the degree of severity. In the present study, structural and mutational analyses were performed in order to identify the structural impact of mutations on cytochrome P450 21A2 and correlate them with patient clinical severity. The following mutations were selected: arginine-356 to tryptophan (R356W), proline-30 to leucine (P30L), isoleucine-172 to asparagine (I172N), valine-281 to leucine (V281L), and the null mutation glutamine-318 (Q318X). Our computational approach mapped the location of residues on P450 and identified their implications on enzyme electrostatic potential mapping to progesterone and heme binding pockets. Using molecular dynamics simulations, we analyzed the structural stability of ligand binding and protein structure, as well as possible conformational changes at the catalytic pocket that leads to impairment of enzymatic activity. Our study sheds light on the impact structural mutations have over steroid 21-hydroxylase structure-function in the cell.Communicated by Ramaswamy H. Sarma.

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

BACKGROUND: Peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (Pin1) is an enzyme that isomerizes phosphorylated serine or threonine motifs adjacent to proline residues. Pin1 has important roles in several cellular signaling pathways, consequently impacting the development of multiple types of cancers. METHODS: Based on the previously reported inhibitory activity of pentacyclic triterpenoids isolated from the gum resin of Boswellia genus against Pin1, we designed a computational experiment using molecular docking, pharmacophore filtering, and structural clustering allied to molecular dynamics (MD) simulations and binding free energy calculations to explore the inhibitory activity of new triterpenoids against Pin1 structure. RESULTS: Here, we report different computational evidence that triterpenoids from neem (Azadirachta indica A. Juss), such as 6-deacetylnimbinene, 6-Oacetylnimbandiol, and nimbolide, replicate the binding mode of the Pin1 substrate peptide, interacting with high affinity with the binding site and thus destabilizing the Pin1 structure. CONCLUSIONS: Our results are supported by experimental data, and provide interesting structural insights into their molecular mechanism of action, indicating that their structural scaffolds could be used as a start point to develop new inhibitors against Pin1.

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.

Computational study of conformational changes in human 3-hydroxy-3-methylglutaryl coenzyme reductase induced by substrate binding.

The enzyme 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) is mainly involved in the regulation of cholesterol biosynthesis. HMGR catalyses the reduction of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) to mevalonate at the expense of two NADPH molecules in a two-step reversible reaction. In the present study, we constructed a model of human HMGR (hHMGR) to explore the conformational changes of HMGR in complex with HMG-CoA and NADPH. In addition, we analysed the complete sequence of the Flap domain using molecular dynamics (MD) simulations and principal component analysis (PCA). The simulations revealed that the Flap domain plays an important role in catalytic site activation and substrate binding. The apo form of hHMGR remained in an open state, while a substrate-induced closure of the Flap domain was observed for holo hHMGR. Our study also demonstrated that the phosphorylation of Ser872 induces significant conformational changes in the Flap domain that lead to a complete closure of the active site, suggesting three principal conformations for the first stage of hHMGR catalysis. Our results were consistent with previous proposed models for the catalytic mechanism of hHMGR. Communicated by Ramaswamy H. Sarma.

Structural and evolutionary analysis of Leishmania Alba proteins.

The Alba superfamily proteins share a common RNA-binding domain. These proteins participate in a variety of regulatory pathways by controlling developmental gene expression. They also interact with ribosomal subunits, translation factors, and other RNA-binding proteins. The Leishmania infantum genome encodes two Alba-domain proteins, LiAlba1 and LiAlba3. In this work, we used homology modeling, protein-protein docking, and molecular dynamics (MD) simulations to explore the details of the Alba1-Alba3-RNA complex from Leishmania infantum at the molecular level. In addition, we compared the structure of LiAlba3 with the human ribonuclease P component, Rpp20. We also mapped the ligand-binding residues on the Alba3 surface to analyze its druggability and performed mutational analyses in Alba3 using alanine scanning to identify residues involved in its function and structural stability. These results suggest that the RGG-box motif of LiAlba1 is important for protein function and stability. Finally, we discuss the function of Alba proteins in the context of pathogen adaptation to host cells. The data provided herein will facilitate further translational research regarding Alba structure and function.

Structural analysis of viral infectivity factor of HIV type 1 and its interaction with A3G, EloC and EloB.

BACKGROUND: The virion infectivity factor (Vif) is an accessory protein, which is essential for HIV replication in host cells. Vif neutralizes the antiviral host protein APOBEC3 through recruitment of the E3 ubiquitin ligase complex. METHODOLOGY: Fifty thousand Vif models were generated using the ab initio relax protocol of the Rosetta algorithm from sets of three- and nine-residue fragments using the fragment Monte Carlo insertion-simulated annealing strategy, which favors protein-like features, followed by an all-atom refinement. In the protocol, a constraints archive was used to define the spatial relationship between the side chains from Cys/His residues and zinc ions that formed the zinc-finger motif that is essential for Vif function. We also performed centroids analysis and structural analysis with respect to the formation of the zinc-finger, and the residue disposal in the protein binding domains. Additionally, molecular docking was used to explore details of Vif-A3G and Vif-EloBC interactions. Furthermore, molecular dynamics simulation was used to evaluate the stability of the complexes Vif-EloBC-A3G and Vif-EloC. PRINCIPAL FINDINGS: The zinc in the HCCH domain significantly alters the folding of Vif and changes the structural dynamics of the HCCH region. Ab initio modeling indicated that the Vif zinc-finger possibly displays tetrahedral geometry as suggested by Mehle et al. (2006). Our model also showed that the residues L146 and L149 of the BC-box motif bind to EloC by hydrophobic interactions, and the residue P162 of the PPLP motif is important to EloB binding. CONCLUSIONS/SIGNIFICANCE: The model presented here is the first complete three-dimensional structure of the Vif. The interaction of Vif with the A3G protein and the EloBC complex is in agreement with empirical data that is currently available in the literature and could therefore provide valuable structural information for advances in rational drug design.