An In Silico Approach to Exploring the Antinociceptive Biological Activities of Linalool and its Metabolites.

Pain is characterized by the unpleasant sensory and emotional sensation associated with actual or potential tissue damage, whereas nociception refers to the mechanism by which noxious stimuli are transmitted from the periphery to the CNS. The main drugs used to treat pain are nonsteroidal anti-inflammatory drugs (NSAIDs) and opioid analgesics, which have side effects that limit their use. Therefore, in the search for new drugs with potential antinociceptive effects, essential oils have been studied, whose constituents (monoterpenes) are emerging as a new therapeutic possibility. Among them, linalool and its metabolites stand out. The present study aims to investigate the antinociceptive potential of linalool and its metabolites through a screening using an in silico approach. Molecular docking was used to evaluate possible interactions with important targets involved in antinociceptive activity, such as α2-adrenergic, GABAergic, muscarinic, opioid, adenosinergic, transient potential, and glutamatergic receptors. The compounds in the investigated series obtained negative energies for all enzymes, representing satisfactory interactions with the targets and highlighting the multi-target potential of the L4 metabolite. Linalool and its metabolites have a high likelihood of modulatory activity against the targets involved in nociception and are potential candidates for future drugs.

Inhibitory effects against SARSCoV-2 main protease (Mpro) of biflavonoids and benzophenones from the fruit of Platonia insignis.

The SARS-CoV-2 mutation and the limitation of the approved drug against COVID-19 are still a challenge in many country healthcare systems and need to be affronted despite the set of vaccines to prevent this viral infection. To contribute to the identification of new antiviral agents, the present study focused on natural products from an edible fruit with potential inhibitory effects against the SARS-CoV-2 main protease (Mpro). First, LC-ESIMS analysis of Platonia insignis fruits was performed and showed the presence of biflavonoids and benzophenones in the seed and pulp, respectively. Then, maceration and chromatographic purification led to the identification of two triglycerides (1 and 2) alongside chamaejasmine (3) and volkensiflavone (4) from the seed and isogarcinol (5) and cycloxanthochymol (6), from the pulp. Compounds 1-6 after evaluating their inhibitory against Mpro, displayed from no to significant activity. Compound 5 was the most potent with an IC50 value of 0.72 µM and was more active than the positive control, Ebselen (IC50 of 3.4 µM). It displayed weak and no cytotoxicity against THP-1 (CC50 of 116.2 µM) and Vero cell lines, respectively. Other active compounds showed no cytotoxicity against THP-1. and Vero cell lines. Molecular docking studies revealed interactions in the catalytic pocket between compound 5 and amino acid residues that composed the catalytic dyads (His 41 and Cyst 145).

Semisynthetic Sesquiterpene Lactones Generated by the Sensibility of Glaucolide B to Lewis and Brønsted-Lowry Acids and Bases: Cytotoxicity and Anti-Inflammatory Activities.

Sesquiterpene lactone (SL) subtypes including hirsutinolide and cadinanolide have a controversial genesis. Metabolites of these classes are either described as natural products or as artifacts produced via the influence of solvents, chromatographic mobile phases, and adsorbents used in phytochemical studies. Based on this divergence, and to better understand the sensibility of these metabolites, different pH conditions were used to prepare semisynthetic SLs and evaluate the anti-inflammatory and antiproliferative activities. Therefore, glaucolide B (1) was treated with various Brønsted-Lowry and Lewis acids and bases-the same approach was applied to some of its derivatives-allowing us to obtain 14 semisynthetic SL derivatives, 10 of which are hereby reported for the first time. Hirsutinolide derivatives 7a (CC50 = 5.0 µM; SI = 2.5) and 7b (CC50 = 11.2 µM; SI = 2.5) and the germacranolide derivative 8a (CC50 = 3.1 µM; SI = 3.0) revealed significant cytotoxic activity and selectivity against human melanoma SK-MEL-28 cells when compared with that against non-tumoral HUVEC cells. Additionally, compounds 7a and 7c.1 showed strongly reduced interleukin-6 (IL-6) and nitrite (NOx) release in pre-treated M1 macrophages J774A.1 when stimulated with lipopolysaccharide. Despite the fact that hirsutinolide and cadinanolide SLs may be produced via plant metabolism, this study shows that acidic and alkaline extraction and solid-phase purification processes can promote their formation.

Computational Studies Applied to Linalool and Citronellal Derivatives Against Alzheimer's and Parkinson's Disorders: A Review with Experimental Approach.

Alzheimer's and Parkinson's are neurodegenerative disorders that affect a great number of people around the world, seriously compromising the quality of life of individuals, due to motor and cognitive damage. In these diseases, pharmacological treatment is used only to alleviate symptoms. This emphasizes the need to discover alternative molecules for use in prevention. Using Molecular Docking, this review aimed to evaluate the anti-Alzheimer's and anti-Parkinson's activity of linalool and citronellal, as well as their derivatives. Before performing Molecular Docking simulations, the compounds' pharmacokinetic characteristics were evaluated. For Molecular Docking, 7 chemical compounds derived from citronellal, and 10 compounds derived from linalool, and molecular targets involved in Alzheimer's and Parkinson's pathophysiology were selected. According to the Lipinski rules, the compounds under study presented good oral absorption and bioavailability. For toxicity, some tissue irritability was observed. For Parkinson-related targets, the citronellal and linalool derived compounds revealed excellent energetic affinity for α-Synuclein, Adenosine Receptors, Monoamine Oxidase (MAO), and Dopamine D1 receptor proteins. For Alzheimer disease targets, only linalool and its derivatives presented promise against BACE enzyme activity. The compounds studied presented high probability of modulatory activity against the disease targets under study, and are potential candidates for future drugs.

Milonine attenuates the lipopolysaccharide-induced acute lung injury in mice by modulating the Akt/NF-κB signaling pathways.

Acute lung injury is an inflammation that triggers acute respiratory distress syndrome with perialveolar neutrophil infiltration, alveolar-capillary barrier damage, and lung edema. Activation of the toll-like receptor 4 complex (TLR4/MD2) and its downstream signaling pathways are responsible for the cytokine storm and cause alveolar damage. Due to the complexity of this pulmonary inflammation, a defined pharmacotherapy has not been established. Thus, this study evaluated the anti-inflammatory potential of milonine, an alkaloid of Cissampelos sympodialis Eichl, in an experimental model of lung inflammation. BALB/c mice were lipopolysaccharide-challenged and treated with milonine at 2.0 mg/kg. Twenty-four hours later, the bronchoalveolar fluid, peripheral blood, and lungs were collected for cellular and molecular analysis. The milonine treatment decreased the cell migration (mainly neutrophils) to the alveoli, the pulmonary edema, and the cytokine levels (IL-1ß, IL-6, TNF-α). The systemic IL-6 level was also reduced. The milonine docking analysis demonstrated hydrophobic interaction at TLR4/MD2 groove with Ile124 and Phe126 amino acids. Indeed, the alkaloid downregulated the kinase-Akt and NF-κB through TLR4/MD2. Therefore, milonine is an effective inflammatory modulator being a potential molecule for the treatment of lung inflammation.

γ-Terpinene complexed with ß-cyclodextrin attenuates spinal neuroactivity in animals with cancer pain by Ca2+ channel block.

OBJECTIVES: Considering that γ-terpinene (γ-TPN) is a monoterpene found in Cannabis oil, with high lipophilicity and limited pharmacokinetics, our objective was to evaluate whether its complexation in ß-cyclodextrin (γ-TPN/ß-CD) could improve its physicochemical properties and action on cancer pain, as well as verify the mechanisms of action involved. METHODS: The γ-TPN/ß-CD was prepared and submitted to physicochemical characterization. Animals with sarcoma 180 were treated (vehicle, γ-TPN 50 mg/kg, γ-TPN/ß-CD 5 mg/kg or morphine) and assessed for hyperalgesia, TNF-α and IL-1ß levels, iNOS and c-Fos activity. The effects of γ-TPN on calcium channels were studied by patch-clamp and molecular docking. RESULTS: ß-CD improved the physicochemical properties and prolonged the anti-hyperalgesic effect of γ-TPN. This compound also reduced the levels of IL-1ß, TNF-α and iNOS in the tumour, and c-Fos protein in the spinal cord. In addition, it reduced Ca2+ current, presenting favourable chemical interactions with different voltage-dependent calcium channels. CONCLUSION: These results indicate that the complexation of γ-TPN into ß-CD increases its stability and time effect, reducing spinal neuroactivity and inflammation by blocking calcium channels.

A higher flexibility at the SARS-CoV-2 main protease active site compared to SARS-CoV and its potentialities for new inhibitor virtual screening targeting multi-conformers.

The main-protease (Mpro) catalyzes a crucial step for the SARS-CoV-2 life cycle. The recent SARS-CoV-2 presents the main protease (MCoV2pro) with 12 mutations compared to SARS-CoV (MCoV1pro). Recent studies point out that these subtle differences lead to mobility variances at the active site loops with functional implications. We use metadynamics simulations and a sort of computational analysis to probe the dynamic, pharmacophoric and catalytic environment differences between the monomers of both enzymes. So, we verify how much intrinsic distinctions are preserved in the functional dimer of MCoV2pro, as well as its implications for ligand accessibility and optimized drug screening. We find a significantly higher accessibility to open binding conformers in the MCoV2pro monomer compared to MCoV1pro. A higher hydration propensity for the MCoV2pro S2 loop with the A46S substitution seems to exercise a key role. Quantum calculations suggest that the wider conformations for MCoV2pro are less catalytically active in the monomer. However, the statistics for contacts involving the N-finger suggest higher maintenance of this activity at the dimer. Docking analyses suggest that the ability to vary the active site width can be important to improve the access of the ligand to the active site in different ways. So, we carry out a multiconformational virtual screening with different ligand bases. The results point to the importance of taking into account the protein conformational multiplicity for new promissors anti MCoV2pro ligands. We hope these results will be useful in prospecting, repurposing and/or designing new anti SARS-CoV-2 drugs.Communicated by Ramaswamy H. Sarma.

PTML modeling for peptide discovery: in silico design of non-hemolytic peptides with antihypertensive activity.

Hypertension is a medical condition that affects millions of people worldwide. Despite the high efficacy of the current antihypertensive drugs, they are associated with serious side effects. Peptides constitute attractive options for chemical therapy against hypertension, and computational models can accelerate the design of antihypertensive peptides. Yet, to the best of our knowledge, all the in silico models predict only the antihypertensive activity of peptides while neglecting their inherent toxic potential to red blood cells. In this work, we report the first sequence-based model that combines perturbation theory and machine learning through multilayer perceptron networks (SB-PTML-MLP) to enable the simultaneous screening of antihypertensive activity and hemotoxicity of peptides. We have interpreted the molecular descriptors present in the model from a physicochemical and structural point of view. By strictly following such interpretations as guidelines, we performed two tasks. First, we selected amino acids with favorable contributions to both the increase of the antihypertensive activity and the diminution of hemotoxicity. Then, we assembled those suitable amino acids, virtually designing peptides that were predicted by the SB-PTML-MLP model as antihypertensive agents exhibiting low hemotoxicity. The potentiality of the SB-PTML-MLP model as a tool for designing potent and safe antihypertensive peptides was confirmed by predictions performed by online computational tools reported in the scientific literature. The methodology presented here can be extended to other pharmacological applications of peptides.

Virtual Screening and Molecular Docking: Discovering Novel c-KIT Inhibitors.

Gastrointestinal stromal tumors (GISTs) are unusual cancers, which are developed in specialized cells in the gastrointestinal tract wall. Various strategies involving single-agents, combinations, and rapid complementary inhibitor cycling are now being used to control such tumors. Based on promising early clinical trial experience, certain novel KIT and PDGFRA tyrosine kinase inhibitors have shown advanced clinical development. Resistance to tyrosine kinase inhibitors has brought immense difficulties, with patients now requiring additional therapeutic options. This review describes and discusses the last five years (2016-2020) in developing novel c-KIT kinase inhibitors using virtual screening and docking approaches. Computational techniques can be used to complement experimental studies to identify new candidate molecules for therapeutic use. Molecular modeling strategies allow the analysis of the required characteristics that compounds must have to effectively bind c-KIT. Through such analyses, it is possible to both discover and design novel inhibitors against cancer-related proteins that play a critical role in tumor development (including mutant strains). Docking showed potential in the detection of the key residues responsible for ligand recognition and is very helpful to understand the interactions in the active site that can be used to develop new compounds/classes of anticancer drugs and help millions of cancer patients.

In Silico Drug Repurposing for Anti-Inflammatory Therapy: Virtual Search for Dual Inhibitors of Caspase-1 and TNF-Alpha.

Inflammation involves a complex biological response of the body tissues to damaging stimuli. When dysregulated, inflammation led by biomolecular mediators such as caspase-1 and tumor necrosis factor-alpha (TNF-alpha) can play a detrimental role in the progression of different medical conditions such as cancer, neurological disorders, autoimmune diseases, and cytokine storms caused by viral infections such as COVID-19. Computational approaches can accelerate the search for dual-target drugs able to simultaneously inhibit the aforementioned proteins, enabling the discovery of wide-spectrum anti-inflammatory agents. This work reports the first multicondition model based on quantitative structure-activity relationships and a multilayer perceptron neural network (mtc-QSAR-MLP) for the virtual screening of agency-regulated chemicals as versatile anti-inflammatory therapeutics. The mtc-QSAR-MLP model displayed accuracy higher than 88%, and was interpreted from a physicochemical and structural point of view. When using the mtc-QSAR-MLP model as a virtual screening tool, we could identify several agency-regulated chemicals as dual inhibitors of caspase-1 and TNF-alpha, and the experimental information later retrieved from the scientific literature converged with our computational results. This study supports the capabilities of our mtc-QSAR-MLP model in anti-inflammatory therapy with direct applications to current health issues such as the COVID-19 pandemic.

Indirect-Acting Pan-Antivirals vs. Respiratory Viruses: A Fresh Perspective on Computational Multi-Target Drug Discovery.

Respiratory viruses continue to afflict mankind. Among them, pathogens such as coronaviruses [including the current pandemic agent known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)] and the one causing influenza A (IAV) are highly contagious and deadly. These can evade the immune system defenses while causing a hyperinflammatory response that can damage different tissues/organs. Simultaneously targeting several immunomodulatory proteins is a plausible antiviral strategy since it could lead to the discovery of indirect-acting pan-antiviral (IAPA) agents for the treatment of diseases caused by respiratory viruses. In this context, computational approaches, which are an essential part of the modern drug discovery campaigns, could accelerate the identification of multi-target immunomodulators. This perspective discusses the usefulness of computational multi-target drug discovery for the virtual screening (drug repurposing) of IAPA agents capable of boosting the immune system through the activation of the toll-like receptor 7 (TLR7) and/or the stimulator of interferon genes (STING) while inhibiting key inflammation-related proteins such as caspase-1 and tumor necrosis factor-alpha (TNF-α).

Multi-target Drug Discovery via PTML Modeling: Applications to the Design of Virtual Dual Inhibitors of CDK4 and HER2.

BACKGROUND: Cyclin-dependent kinase 4 (CDK4) and the human epidermal growth factor receptor 2 (HER2) are two of the most promising targets in oncology research. Thus, a series of computational approaches have been applied to the search for more potent inhibitors of these cancerrelated proteins. However, current approaches have focused on chemical analogs while predicting the inhibitory activity against only one of these targets, but never against both. AIMS: We report the first perturbation model combined with machine learning (PTML) to enable the design and prediction of dual inhibitors of CDK4 and HER2. METHODS: Inhibition data for CDK4 and HER2 were extracted from ChEMBL. The PTML model relied on artificial neural networks to allow the classification/prediction of molecules as active or inactive against CDK4 and/or HER2. RESULTS: The PTML model displayed sensitivity and specificity higher than 80% in the training set. The same statistical metrics had values above 75% in the test set. We extracted several molecular fragments and estimated their quantitative contributions to the inhibitory activity against CDK4 and HER2. Guided by the physicochemical and structural interpretations of the molecular descriptors in the PTML model, we designed six molecules by assembling several fragments with positive contributions. Three of these molecules were predicted as potent dual inhibitors of CDK4 and HER2, while the other three were predicted as inhibitors of at least one of these proteins. All the molecules complied with Lipinski's rule of five and its variants. CONCLUSION: The present work represents an encouraging alternative for future anticancer chemotherapies.

Characterization of ß-cyclodextrin/myrtenol complex and its protective effect against nociceptive behavior and cognitive impairment in a chronic musculoskeletal pain model.

Myrtenol has gained wide interest because of its pharmacological profiles, mainly for treatment of chronic diseases. To improve the solubility of myrtenol, the formation of inclusion complexes with ß-cyclodextrin was performed by physical mixture, kneading process or slurry complexation (SC) methods and characterized using thermal analysis, XRD, SEM and NMR. From these results, myrtenol complexed by SC was successfully complexed into ß-cyclodextrin cavity. The interaction between myrtenol and ß-cyclodextrin was confirmed by molecular docking. Hence, the SC ß-cyclodextrin-myrtenol complex was evaluate for its anti-hyperalgesic, anxiolytic and antioxidant activity in a fibromyalgia model. Results show that myrtenol and ß-cyclodextrin form a stable complex and have anti-hyperalgesic effect, improve the cognitive impairment caused and have an anxiolytic-like effect. Furthermore, the ß-cyclodextrin/myrtenol complex decrease lipoperoxidation, increased catalase activity and a reduce SOD/CAT ratio. Therefore, ß-cyclodextrin/myrtenol complex reduce painful behavior, improves motor skills and emotional behavior and decreases oxidative stress in a fibromyalgia model.

Bioactive Compounds from the Aerial Parts of Evolvulus linarioides.

Three new caryophyllane-type sesquiterpenoids, linariophyllenes A-C (1-3), two new hamamelitol derivatives, linaritols A (4) and B (5), two new chromones, linariosides A (6) and B (7), and three known chromones, cnidimol C (8), monnieriside A (9), and undulatoside A (10), were identified from the aerial parts of Evolvulus linarioides. The structures of these compounds were elucidated by NMR, MS, and IR data. The absolute configurations of compounds 1-5 and 7 were established via electronic circular dichroism data. The anti-inflammatory potential of compounds 1-5 and 7-10 was evaluated by determining their ability to inhibit the production of nitric oxide (NO) and proinflammatory cytokine IL-1ß by stimulated J774 macrophages. Compounds tested at noncytotoxic concentrations inhibited NO production by macrophages, exhibiting IC50 values between 17.8 and 66.2 µM, and inhibited IL-1ß production by stimulated macrophages by 72.7-96.2%.

Advances in Nanoparticles as Anticancer Drug Delivery Vector: Need of this Century.

BACKGROUND: Nanotechnology has contributed a great deal to the field of medical science. Smart drugdelivery vectors, combined with stimuli-based characteristics, are becoming increasingly important. The use of external and internal stimulating factors can have enormous benefits and increase the targeting efficiency of nanotechnology platforms. The pH values of tumor vascular tissues are acidic in nature, allowing the improved targeting of anticancer drug payloads using drug-delivery vectors. Nanopolymers are smart drug-delivery vectors that have recently been developed and recommended for use by scientists because of their potential targeting capabilities, non-toxicity and biocompatibility, and make them ideal nanocarriers for personalized drug delivery. METHOD: The present review article provides an overview of current advances in the use of nanoparticles (NPs) as anticancer drug-delivery vectors. RESULTS: This article reviews the molecular basis for the use of NPs in medicine, including personalized medicine, personalized therapy, emerging vistas in anticancer therapy, nanopolymer targeting, passive and active targeting transports, pH-responsive drug carriers, biological barriers, computer-aided drug design, future challenges and perspectives, biodegradability and safety. CONCLUSION: This article will benefit academia, researchers, clinicians, and government authorities by providing a basis for further research advancements.