Ursolic acid interaction with transcription factors BRAF, V600E, and V600K: a computational approach towards new potential melanoma treatments.

CONTEXT: Melanoma is one of the cancers with the highest mortality rate for its ability to metastasize. Several targets have undergone investigation for the development of drugs against this pathology. One of the main targets is the kinase BRAF (RAF, rapidly accelerated fibrosarcoma). The most common mutation in melanoma is BRAFV600E and has been reported in 50-90% of patients with melanoma. Due to the relevance of the BRAFV600E mutation, inhibitors to this kinase have been developed, vemurafenib-OMe and dabrafenib. Ursolic acid (UA) is a pentacyclic triterpene with a privileged structure, the pentacycle scaffold, which allows to have a broad variety of biological activity; the most studied is its anticancer capacity. In this work, we reported the interaction profile of vemurafenib-OMe, dabrafenib, and UA, to define whether UA has binding capacity to BRAFWT, BRAFV600E, and BRAFV600K. Homology modeling of BRAFWT, V600E, and V600K; molecular docking; and molecular dynamics simulations were carried out and interactions and residues relevant to the binding of the inhibitors were obtained. We found that UA, like the inhibitors, presents hydrogen bond interactions, and hydrophobic interactions of van der Waals, and π-stacking with I463, Q530, C532, and F583. The ΔG of ursolic acid in complex with BRAFV600K (- 63.31 kcal/mol) is comparable to the ΔG of the selective inhibitor dabrafenib (- 63.32 kcal/mol) in complex to BRAFV600K and presents a ΔG like vemurafenib-OMe with BRAFWT and V600E. With this information, ursolic acid could be considered as a lead compound for design cycles and to optimize the binding profile and the selectivity towards mutations for the development of new selective inhibitors for BRAFV600E and V600K to new potential melanoma treatments. METHODS: The homology modeling calculations were executed on the public servers I-TASSER and ROBETTA, followed by molecular docking calculations using AutoGrid 4.2.6, AutoDockGPU 1.5.3, and AutoDockTools 1.5.6. Molecular dynamics and metadynamics simulations were performed in the Desmond module of the academic version of the Schrödinger-Maestro 2020-4 program, utilizing the OPLS-2005 force field. Ligand-protein interactions were evaluated using Schrödinger-Maestro program, LigPlot + , and PLIP (protein-ligand interaction profiler). Finally, all of the protein figures presented in this article were made in the PyMOL program.

In Silico Analysis of the Molecular Interaction between Anthocyanase, Peroxidase and Polyphenol Oxidase with Anthocyanins Found in Cranberries.

Anthocyanins are bioactive compounds responsible for various physiological processes in plants and provide characteristic colors to fruits and flowers. Their biosynthetic pathway is well understood; however, the enzymatic degradation mechanism is less explored. Anthocyanase (ß-glucosidase (BGL)), peroxidase (POD), and polyphenol oxidase (PPO) are enzymes involved in degrading anthocyanins in plants such as petunias, eggplants, and Sicilian oranges. The aim of this work was to investigate the physicochemical interactions between these enzymes and the identified anthocyanins (via UPLC-MS/MS) in cranberry (Vaccinium macrocarpon) through molecular docking to identify the residues likely involved in anthocyanin degradation. Three-dimensional models were constructed using the AlphaFold2 server based on consensus sequences specific to each enzyme. The models with the highest confidence scores (pLDDT) were selected, with BGL, POD, and PPO achieving scores of 87.6, 94.8, and 84.1, respectively. These models were then refined using molecular dynamics for 100 ns. Additionally, UPLC-MS/MS analysis identified various flavonoids in cranberries, including cyanidin, delphinidin, procyanidin B2 and B4, petunidin, pelargonidin, peonidin, and malvidin, providing important experimental data to support the study. Molecular docking simulations revealed the most stable interactions between anthocyanase and the anthocyanins cyanidin 3-arabinoside and cyanidin 3-glucoside, with a favorable ΔG of interaction between -9.3 and -9.2 kcal/mol. This study contributes to proposing a degradation mechanism and seeking inhibitors to prevent fruit discoloration.

In Silico Design of miniACE2 Decoys with In Vitro Enhanced Neutralization Activity against SARS-CoV-2, Encompassing Omicron Subvariants.

The COVID-19 pandemic has overwhelmed healthcare systems and triggered global economic downturns. While vaccines have reduced the lethality rate of SARS-CoV-2 to 0.9% as of October 2024, the continuous evolution of variants remains a significant public health challenge. Next-generation medical therapies offer hope in addressing this threat, especially for immunocompromised individuals who experience prolonged infections and severe illnesses, contributing to viral evolution. These cases increase the risk of new variants emerging. This study explores miniACE2 decoys as a novel strategy to counteract SARS-CoV-2 variants. Using in silico design and molecular dynamics, blocking proteins (BPs) were developed with stronger binding affinity for the receptor-binding domain of multiple variants than naturally soluble human ACE2. The BPs were expressed in E. coli and tested in vitro, showing promising neutralizing effects. Notably, miniACE2 BP9 exhibited an average IC50 of 4.9 µg/mL across several variants, including the Wuhan strain, Mu, Omicron BA.1, and BA.2 This low IC50 demonstrates the potent neutralizing ability of BP9, indicating its efficacy at low concentrations.Based on these findings, BP9 has emerged as a promising therapeutic candidate for combating SARS-CoV-2 and its evolving variants, thereby positioning it as a potential emergency biopharmaceutical.

Carbohydrate-Binding Mechanism of the Coagulant Lectin from Moringa oleifera Seeds (cMoL) Is Related to the Dimeric Protein Structure.

This study characterized the binding mechanisms of the lectin cMoL (from Moringa oleifera seeds) to carbohydrates using spectroscopy and molecular dynamics (MD). The interaction with carbohydrates was studied by evaluating lectin fluorescence emission after titration with glucose or galactose (2.0-11 mM). The Stern-Volmer constant (Ksv), binding constant (Ka), Gibbs free energy (∆G), and Hill coefficient were calculated. After the urea-induced denaturation of cMoL, evaluations were performed using fluorescence spectroscopy, circular dichroism (CD), and hemagglutinating activity (HA) evaluations. The MD simulations were performed using the Amber 20 package. The decrease in Ksv revealed that cMoL interacts with carbohydrates via a static mechanism. The cMoL bound carbohydrates spontaneously (ΔG < 0) and presented a Ka on the order of 102, with high selectivity for glucose. Protein-ligand complexes were stabilized by hydrogen bonds and hydrophobic interactions. The Hill parameter (h~2) indicated that the binding occurs through the cMoL dimer. The loss of HA at urea concentrations at which the fluorescence and CD spectra indicated protein monomerization confirmed these results. The MD simulations revealed that glucose bound to the large cavity formed between the monomers. In conclusion, the biotechnological application of cMoL lectin requires specific methods or media to improve its dimeric protein structure.

1,2,4-Oxadiazole Derivatives: Physicochemical Properties, Antileishmanial Potential, Docking and Molecular Dynamic Simulations of Leishmania infantum Target Proteins.

Visceral leishmaniasis (VL), caused by protozoa of the genus Leishmania, remains a significant public health concern due to its potentially lethal nature if untreated. Current chemotherapy options are limited by severe toxicity and drug resistance. Derivatives of 1,2,4-oxadiazole have emerged as promising drug candidates due to their broad biological activity. This study investigated the effects of novel 1,2,4-oxadiazole derivatives (Ox1-Ox7) on Leishmania infantum, the etiological agent of VL. In silico predictions using SwissADME suggest that these compounds have high oral absorption and good bioavailability. Among them, Ox1 showed the most promise, with higher selectivity against promastigotes and lower cytotoxicity towards L929 fibroblasts and J774.G8 macrophages. Ox1 exhibited selectivity indices of 18.7 and 61.7 against L. infantum promastigotes and amastigotes, respectively, compared to peritoneal macrophages. Ultrastructural analyses revealed severe morphological damage in both parasite forms, leading to cell death. Additionally, Ox1 decreased the mitochondrial membrane potential in promastigotes, as shown by flow cytometry. Molecular docking and dynamic simulations indicated a strong affinity of Ox1 for the L. infantum CYP51 enzyme. Overall, Ox1 is a promising and effective compound against L. infantum.

Quantum mechanical analysis of newly synthesized HIV-1 protease inhibitors: evaluation of wild-type and resistant strain binding interactions.

Inhibition of HIV-1 protease is a cornerstone of antiretroviral therapy. However, the notorious ability of HIV-1 to develop resistance to protease inhibitors (PIs), particularly darunavir (DRV), poses a major challenge. Using quantum chemistry and computer simulations, this study aims to investigate the interactions between two novel PIs, GRL-004 and GRL-063, as well as a wild-type (WT) HIV strain and a DRV-resistant mutant strain. To do this, we used molecular docking, molecular dynamics simulations, and quantum mechanical calculations to check how well GRL-004 and GRL-063 bound to both WT and DRV-resistant proteases. The results show that GRL-004 and GRL-063 bind very well to ASP29 in the WT strain. ASP29 is an important amino acid in the HIV protease dimer. Remarkably, amino acids such as ILE50 in the WT strains showed substantial binding energies to both drugs. Quantum energy calculations showed a slight reduction in the energy affinity of the interaction between the MUT strain and the ligand GRL-063, compared to the WT strain. GRL-004 showed similar interaction energy for both strains, suggesting that it has greater plasticity than GRL-063 despite its lower interaction affinity. Furthermore, GLY49B demonstrated strong binding energies regardless of mutations. Other relevant residues with strong binding energies include GLY49B, PHE82A, PRO81A, ASP29A, ASP25A and ALA28B. This study improves our understanding of receptor-ligand dynamics and the adaptability of new protease inhibitors (PIs), which has profound implications for the innovation of future antiretroviral drugs.

Analysis of Tribology Properties of Trimethylolpropane-based Lubricant by Molecular Dynamics.

Currently, it is crucial for the lubricant formulation industry to explore cost-effective and environmentally friendly methodologies for analyzing the tribological properties of engine aviation lubricants under high-temperature and high-pressure operating conditions. This study demonstrates the feasibility of employing molecular dynamic simulations to gain essential insights into the evolution of the tribological properties of lubricants during operation. A three-layer molecular model was devised, comprising nickel aluminide molecules in the top and bottom layers, and polyol ester in the core. The impact of sliding velocities ranging from 20 km/h to 100 km/h was investigated under varying temperature and pressure conditions. Concentration, temperature and velocity profiles, radial distribution function, mean square displacement, and friction coefficient were calculated and analyzed in detail. Notably, the highest friction coefficients - ranging from 2.5 to 0.75 - were observed at the lowest temperature and pressure conditions tested. Conversely, other sections of the gas turbine exhibited substantially lower friction coefficients - ranging from 0 to 0.01.Simulations demonstrate that increasing pressure and temperature reduce polymer chain mobility, leading to stronger internal interactions within the lubricant. Consequently, lubricant adsorption onto metal surfaces decreases. Furthermore, the lubricant performs exceptionally well when its molecules encounter higher velocities and temperatures. Based on the results obtained, the research demonstrates that the presented technique provides both quantitative and qualitative tribological information essential for understanding a system molecular behavior, serving as a guiding framework for researchers in the field.

Photoisomerization pathways of trans-resveratrol.

Resveratrol is well-known for promoting health benefits due to its antioxidant, anti-aging, anti-carcinogenic, and other beneficial activities. Understanding the photophysics of resveratrol is essential for determining its applicability to pharmaceutical innovations. In the present work, we used an explore-then-assess strategy to map the internal conversion pathways of trans-resveratrol. This strategy consists of exploring the multidimensional configurational space with nonadiabatic dynamics simulations based on a semiempirical multireference method, followed by a feasibility assessment of reduced-dimensionality pathways at a high ab initio theoretical level. The exploration step revealed that internal conversion to the ground state may occur near five distinct conical intersections. The assessment step showed that the main photoisomerization pathway involves a twisted-pyramidalized S1/S0 conical intersection, yielding either trans or cis isomers. However, a secondary path was identified, where cis-trans isomerization happens in the excited state and internal conversion occurs at a cyclic conical intersection, yielding a closed-ring resveratrol derivative. This derivative, which can be formed through this direct path or an indirect photoexcitation, may be connected to the production of oxygen-reactive species previously reported and have implications in photodynamic therapy.

Structure-Aided Computational Design of Triazole-Based Targeted Covalent Inhibitors of Cruzipain.

Cruzipain (CZP), the major cysteine protease present in T. cruzi, the ethiological agent of Chagas disease, has attracted particular attention as a therapeutic target for the development of targeted covalent inhibitors (TCI). The vast chemical space associated with the enormous molecular diversity feasible to explore by means of modern synthetic approaches allows the design of CZP inhibitors capable of exhibiting not only an efficient enzyme inhibition but also an adequate translation to anti-T. cruzi activity. In this work, a computer-aided design strategy was developed to combinatorially construct and screen large libraries of 1,4-disubstituted 1,2,3-triazole analogues, further identifying a selected set of candidates for advancement towards synthetic and biological activity evaluation stages. In this way, a virtual molecular library comprising more than 75 thousand diverse and synthetically feasible analogues was studied by means of molecular docking and molecular dynamic simulations in the search of potential TCI of CZP, guiding the synthetic efforts towards a subset of 48 candidates. These were synthesized by applying a Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC) centered synthetic scheme, resulting in moderate to good yields and leading to the identification of 12 hits selectively inhibiting CZP activity with IC50 in the low micromolar range. Furthermore, four triazole derivatives showed good anti-T. cruzi inhibition when studied at 50 µM; and Ald-6 excelled for its high antitrypanocidal activity and low cytotoxicity, exhibiting complete in vitro biological activity translation from CZP to T. cruzi. Overall, not only Ald-6 merits further advancement to preclinical in vivo studies, but these findings also shed light on a valuable chemical space where molecular diversity might be explored in the search for efficient triazole-based antichagasic agents.

Alzheimer's Disease Immunotherapy and Mimetic Peptide Design for Drug Development: Mutation Screening, Molecular Dynamics, and a Quantum Biochemistry Approach Focusing on Aducanumab::Aß2-7 Binding Affinity.

Seven treatments are approved for Alzheimer's disease, but five of them only relieve symptoms and do not alter the course of the disease. Aducanumab (Adu) and lecanemab are novel disease-modifying antiamyloid-ß (Aß) human monoclonal antibodies that specifically target the pathophysiology of Alzheimer's disease (AD) and were recently approved for its treatment. However, their administration is associated with serious side effects, and their use is limited to early stages of the disease. Therefore, drug discovery remains of great importance in AD research. To gain new insights into the development of novel drugs for Alzheimer's disease, a combination of techniques was employed, including mutation screening, molecular dynamics, and quantum biochemistry. These were used to outline the interfacial interactions of the Aducanumab::Aß2-7 complex. Our analysis identified critical stabilizing contacts, revealing up to 40% variation in the affinity of the Adu chains for Aß2-7 depending on the conformation outlined. Remarkably, two complementarity determining regions (CDRs) of the Adu heavy chain (HCDR3 and HCDR2) and one CDR of the Adu light chain (LCDR3) accounted for approximately 77% of the affinity of Adu for Aß2-7, confirming their critical role in epitope recognition. A single mutation, originally reported to have the potential to increase the affinity of Adu for Aß2-7, was shown to decrease its structural stability without increasing the overall binding affinity. Mimetic peptides that have the potential to inhibit Aß aggregation were designed by using computational outcomes. Our results support the use of these peptides as promising drugs with great potential as inhibitors of Aß aggregation.

Predicting of novel homoserine dehydrogenase inhibitors against Paracoccidioides brasiliensis: integrating in silico and in vitro approaches.

Aim: To search for potential inhibitors to homoserine dehydrogenase (HSD) in Paracoccidioides brasiliensis the causative agent of paracoccidioidomycosis, an infection with a high mortality rate in Brazil.Materials & methods: The enzyme was modeled and used in the virtual screening of the compounds. The library was first screened by the Autodock, in which 66 molecules were better ranked than substrate, and then, also evaluated by the Molegro and Gold programs.Results: The HS23 and HS87 molecules were selected in common by the three programs, and ADME/Tox evaluation indicates they are not toxic. The molecular dynamics of PbHSD bonded to ligands showed stable complexes until 50 ns. To validate the results, compounds were purchased for assays of minimum inhibitory concentration (MIC), minimum fungicidal concentration (MFC), synergic profile with Amphotericin B (AmB) and cytotoxicity. The two molecules presented MIC of 32 µg/ml and MFC of 64 µg/ml against the P. brasiliensis (strain Pb18). They also showed synergistic activity with AmB and a lack of toxicity against Hela and Vero cell lines.Conclusion: These results suggest that the HS23 and HS87 are promising candidates as PbHSD inhibitors and may be used as hits for the development of new drugs against paracoccidioidomycosis.

[Box: see text].

In silico approach revealed the membrane receptor PHO36 as a new target for synthetic anticandidal peptides.

Aim: Synthetic antimicrobial peptides (SAMPs) present the potential to fight systemic fungal infections. Here, the PHO36 receptor from Candida albicans was analyzed by in silico tools as a possible target for three anticandidal SAMPs: RcAlb-PepIII, PepGAT and PepKAA.Materials & methods: Molecular docking, dynamics and quantum biochemistry were employed to understand the individual contribution of amino acid residues in the interaction region.Results: The results revealed that SAMPs strongly interact with the PHO36 by multiple high-energy interactions. This is the first study to employ quantum biochemistry to describe the interactions between SAMPs and the PHO36 receptor.Conclusion: This work contributes to understanding and identifying new molecular targets with medical importance that could be used to discover new drugs against systemic fungal infections.

Here, computers helped us find new proteins in Candida albicans that may guide the development of new medicines.

Deep learning for discriminating non-trivial conformational changes in molecular dynamics simulations of SARS-CoV-2 spike-ACE2.

Molecular dynamics (MD) simulations produce a substantial volume of high-dimensional data, and traditional methods for analyzing these data pose significant computational demands. Advances in MD simulation analysis combined with deep learning-based approaches have led to the understanding of specific structural changes observed in MD trajectories, including those induced by mutations. In this study, we model the trajectories resulting from MD simulations of the SARS-CoV-2 spike protein-ACE2, specifically the receptor-binding domain (RBD), as interresidue distance maps, and use deep convolutional neural networks to predict the functional impact of point mutations, related to the virus's infectivity and immunogenicity. Our model was successful in predicting mutant types that increase the affinity of the S protein for human receptors and reduce its immunogenicity, both based on MD trajectories (precision = 0.718; recall = 0.800; [Formula: see text] = 0.757; MCC = 0.488; AUC = 0.800) and their centroids. In an additional analysis, we also obtained a strong positive Pearson's correlation coefficient equal to 0.776, indicating a significant relationship between the average sigmoid probability for the MD trajectories and binding free energy (BFE) changes. Furthermore, we obtained a coefficient of determination of 0.602. Our 2D-RMSD analysis also corroborated predictions for more infectious and immune-evading mutants and revealed fluctuating regions within the receptor-binding motif (RBM), especially in the [Formula: see text] loop. This region presented a significant standard deviation for mutations that enable SARS-CoV-2 to evade the immune response, with RMSD values of 5Å in the simulation. This methodology offers an efficient alternative to identify potential strains of SARS-CoV-2, which may be potentially linked to more infectious and immune-evading mutations. Using clustering and deep learning techniques, our approach leverages information from the ensemble of MD trajectories to recognize a broad spectrum of multiple conformational patterns characteristic of mutant types. This represents a strategic advantage in identifying emerging variants, bypassing the need for long MD simulations. Furthermore, the present work tends to contribute substantially to the field of computational biology and virology, particularly to accelerate the design and optimization of new therapeutic agents and vaccines, offering a proactive stance against the constantly evolving threat of COVID-19 and potential future pandemics.

Insight from atomistic molecular dynamics simulations into the supramolecular assembly of the aldo-keto reductase from Trypanosoma cruzi.

CONTEXT: Currently, Chagas disease represents an important public health problem affecting more than 8 million people worldwide. The vector of this disease is the Trypanosoma cruzi (Tc) parasite. Our research specifically focuses on the structure and aggregation states of the enzyme aldo-keto reductase of Tc (TcAKR) reported in this parasite. TcAKR belongs to the aldo-keto reductase (AKR) superfamily, enzymes that catalyze redox reactions involved in crucial biological processes. While most AKRs are found in monomeric forms, some have been reported to form dimeric and tetrameric structures. This is the case for some TcAKR. To better understand how TcAKR multimers form and remain stable, we conducted a comprehensive computational analysis using molecular dynamics (MD) simulations. Our approach to elucidating the aggregation states of TcAKR involved two strategies. Initially, we explored the dynamic behaviour of pre-assembled TcAKR dimers. Subsequently, we examined the self-aggregation of eight monomers. This investigation led to the identification of crucial residues that contribute to the stabilization of protein-protein interactions. It was also found that TcAKRs can form stable supramolecular assemblies, with each monomer typically surrounded by three first neighbours. These findings align with experimental reports of tetrameric or more complex supramolecular structures. Our computational studies could guide further experimental investigations aiming at drug development and assist in designing strategies to modulate aggregation. METHOD: Atomistic molecular dynamics simulations were carried out. The TcAKR 3D model structure was obtained by homology modelling using the Swiss Model for the TcAKR sequence (GenBank accession no. EU558869). Further, we checked the model with Alphafold2 and found a high degree of similarity between models. Several tools were used to build the dimers including CLUSPRO, GRAMM-Docking, Hdock, and Py-dock. Protein superstructures were built using the PACKMOL package. CHARMM-GUI was used to set up the simulation systems. GROMACS version 2020.5 was used to perform the simulations with the CHARMM36 force field for the protein and ions and the TIP3P model for water. Further analyses were performed using VMD, GROMACS, AMBER tools, MDLovoFit, bio3d, and in-house programs.

Tetraasteranes as homologues of cubanes: effective scaffolds for drug discovery.

Classical hydrocarbon scaffolds have long assisted in bringing new molecules to the market for a variety of applications, but one notable omission is that of tetraasteranes, which are homologues of cubanes belonging to a class of polycyclic hydrocarbon cage compounds. Tetraasteranes exhibit potential as scaffolds in drug discovery due to their identical cyclobutane structures and rigid conformation resembling cubanes. Based on the studies of the physical and chemical properties of tetraasteranes by density functional theory, three series of compounds were designed as homologues of cubanes by the substitution of cubane scaffolds in pharmaceuticals with tetraasteranes. Their potential for pharmaceutical applications was evaluated in silico by molecular docking and dynamics simulations. Their pharmacokinetic and physicochemical properties were studied by the ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis. The results indicate that tetraasteranes may be scaffolds as novel bioisosteres of cubanes, as well as hydrogen bond donors or acceptors, which enhance the affinity between ligands and receptors with more stable binding behavior and feasible tolerability in ADMET. All these findings provide new opportunities for tetraasteranes to serve as effective pharmaceutical scaffolds for drug discovery and to accelerate the drug discovery process by repurposing both new and old commercial compounds.

Structural and dynamics characterization of the Zika virus NS2B using nuclear magnetic resonance and RosettaMP: A challenge for transmembrane protein studies.

Zika virus (ZIKV) is an emergent flavivirus that represents a global public health concern due to its association with severe neurological disorders. NS2B is a multifunctional viral membrane protein primarily used to regulate viral protease activity and is crucial for virus replication, making it an appealing target for antiviral drugs. This study presents the structural elucidation of full-length ZIKV NS2B in sodium dodecyl sulfate (SDS) micelles using solution nuclear magnetic resonance experimental data and RosettaMP. The protein structure has four transmembrane α-helices, two amphipathic α-helices, and a ß-hairpin in the hydrophilic region. NS2B presented secondary and tertiary stability in different concentrations of SDS. Furthermore, we studied the dynamics of NS2B in SDS micelles through relaxation parameters and paramagnetic relaxation enhancement experiments. The findings were consistent with the structural calculations. Our work will be essential in understanding the role of NS2B in viral replication and screening for inhibitors against ZIKV.

A contact-based analysis of local energetic frustration dynamics identifies key residues enabling RfaH fold-switch.

Fold-switching enables metamorphic proteins to reversibly interconvert between two highly dissimilar native states to regulate their protein functions. While about 100 proteins have been identified to undergo fold-switching, unveiling the key residues behind this mechanism for each protein remains challenging. Reasoning that fold-switching in proteins is driven by dynamic changes in local energetic frustration, we combined fold-switching simulations generated using simplified structure-based models with frustration analysis to identify key residues involved in this process based on the change in the density of minimally frustrated contacts during refolding. Using this approach to analyze the fold-switch of the bacterial transcription factor RfaH, we identified 20 residues that significantly change their frustration during its fold-switch, some of which have been experimentally and computationally reported in previous works. Our approach, which we developed as an additional module for the FrustratometeR package, highlights the role of local frustration dynamics in protein fold-switching and offers a robust tool to enhance our understanding of other proteins with significant conformational shifts.

Synthesis, Biological Activity, and Molecular-Docking Studies of New Brassinosteroid Analogs.

Much work has been dedicated to the quest to determine the structure-activity relationship in synthetic brassinosteroid (BR) analogs. Recently, it has been reported that analogs with phenyl or benzoate groups in the alkyl chain present activities comparable to those shown by natural BRs, depending on the nature of the substituent in the aromatic ring. However, as it is well known that the activity depends on the structure of the whole molecule, in this work, we have synthesized a series of compounds with the same substituted benzoate in the alkyl chain and a hydroxyl group at C3. The main goal was to compare the activities with analogs with -OH at C2 and C3. Additionally, a molecular-docking study and molecular dynamics simulations were performed to establish a correlation between the experimental and theoretical results. The synthesis of eight new BR analogs was described. All the analogs were fully characterized by spectroscopical methods. The bioactivity of these analogs was assessed using the rice lamina inclination test (RLIT) and the inhibition of the root and hypocotyl elongation of Arabidopsis thaliana. The results of the RLIT indicate that at the lowest tested concentration (1 × 10-8 M), in the BR analogs in which the aromatic ring was substituted at the para position with methoxy, the I and CN substituents were more active than brassinolide (50-72%) and 2-3 times more active than those analogs in which the substituent group was F, Cl or Br atoms. However, at the highest concentrations, brassinolide was the most active compound, and the structure-activity relationship changed. On the other hand, the results of the A. thaliana root sensitivity assay show that brassinolide and the analogs with I and CN as substituents on the benzoyl group were the most active compounds. These results are in line with those obtained via the RLIT. A comparison of these results with those obtained for similar analogs that had a hydroxyl group at C2 indicates the importance of considering the whole structure. The molecular-docking results indicate that all the analogs adopted a brassinolide-like orientation, while the stabilizing effect of the benzoate group on the interactions with the receptor complex provided energy binding values ranging between -10.17 and -13.17 kcal mol-1, where the analog with a nitrile group was the compound that achieved better contact with the amino acids present in the active site.

The Endocannabinoid Peptide RVD-Hemopressin Is a TRPV1 Channel Blocker.

Neurotransmission is critical for brain function, allowing neurons to communicate through neurotransmitters and neuropeptides. RVD-hemopressin (RVD-Hp), a novel peptide identified in noradrenergic neurons, modulates cannabinoid receptors CB1 and CB2. Unlike hemopressin (Hp), which induces anxiogenic behaviors via transient receptor potential vanilloid 1 (TRPV1) activation, RVD-Hp counteracts these effects, suggesting that it may block TRPV1. This study investigates RVD-Hp's role as a TRPV1 channel blocker using HEK293 cells expressing TRPV1-GFP. Calcium imaging and patch-clamp recordings demonstrated that RVD-Hp reduces TRPV1-mediated calcium influx and TRPV1 ion currents. Molecular docking and dynamics simulations indicated that RVD-Hp interacts with TRPV1's selectivity filter, forming stable hydrogen bonds and van der Waals contacts, thus preventing ion permeation. These findings highlight RVD-Hp's potential as a therapeutic agent for conditions involving TRPV1 activation, such as pain and anxiety.

Permeation mechanisms of hydrogen peroxide and water through Plasma Membrane Intrinsic Protein aquaporins.

Hydrogen peroxide (H2O2) transport by aquaporins (AQP) is a critical feature for cellular redox signaling. However, the H2O2 permeation mechanism through these channels remains poorly understood. Through functional assays, two Plasma membrane Intrinsic Protein (PIP) AQP from Medicago truncatula, MtPIP2;2 and MtPIP2;3 have been identified as pH-gated channels capable of facilitating the permeation of both water (H2O) and H2O2. Employing a combination of unbiased and enhanced sampling molecular dynamics simulations, we investigated the key barriers and translocation mechanisms governing H2O2 permeation through these AQP in both open and closed conformational states. Our findings reveal that both H2O and H2O2 encounter their primary permeation barrier within the selectivity filter (SF) region of MtPIP2;3. In addition to the SF barrier, a second energetic barrier at the NPA (asparagine-proline-alanine) region that is more restrictive for the passage of H2O2 than for H2O, was found. This behavior can be attributed to a dissimilar geometric arrangement and hydrogen bonding profile between both molecules in this area. Collectively, these findings suggest mechanistic heterogeneity in H2O and H2O2 permeation through PIPs.