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 Screening of Therapeutic Targets as a Tool to Optimize the Development of Drugs and Nutraceuticals in the Treatment of Diabetes mellitus: A Systematic Review.

The Target-Based Virtual Screening approach is widely employed in drug development, with docking or molecular dynamics techniques commonly utilized for this purpose. This systematic review (SR) aimed to identify in silico therapeutic targets for treating Diabetes mellitus (DM) and answer the question: What therapeutic targets have been used in in silico analyses for the treatment of DM? The SR was developed following the guidelines of the Preferred Reporting Items Checklist for Systematic Review and Meta-Analysis, in accordance with the protocol registered in PROSPERO (CRD42022353808). Studies that met the PECo strategy (Problem, Exposure, Context) were included using the following databases: Medline (PubMed), Web of Science, Scopus, Embase, ScienceDirect, and Virtual Health Library. A total of 20 articles were included, which not only identified therapeutic targets in silico but also conducted in vivo analyses to validate the obtained results. The therapeutic targets most frequently indicated in in silico studies were GLUT4, DPP-IV, and PPARγ. In conclusion, a diversity of targets for the treatment of DM was verified through both in silico and in vivo reassessment. This contributes to the discovery of potential new allies for the treatment of DM.

Peptides Evaluated In Silico, In Vitro, and In Vivo as Therapeutic Tools for Obesity: A Systematic Review.

Bioinformatics has emerged as a valuable tool for screening drugs and understanding their effects. This systematic review aimed to evaluate whether in silico studies using anti-obesity peptides targeting therapeutic pathways for obesity, when subsequently evaluated in vitro and in vivo, demonstrated effects consistent with those predicted in the computational analysis. The review was framed by the question: "What peptides or proteins have been used to treat obesity in in silico studies?" and structured according to the acronym PECo. The systematic review protocol was developed and registered in PROSPERO (CRD42022355540) in accordance with the PRISMA-P, and all stages of the review adhered to these guidelines. Studies were sourced from the following databases: PubMed, ScienceDirect, Scopus, Web of Science, Virtual Heath Library, and EMBASE. The search strategies resulted in 1015 articles, of which, based on the exclusion and inclusion criteria, 7 were included in this systematic review. The anti-obesity peptides identified originated from various sources including bovine alpha-lactalbumin from cocoa seed (Theobroma cacao L.), chia seed (Salvia hispanica L.), rice bran (Oryza sativa), sesame (Sesamum indicum L.), sea buckthorn seed flour (Hippophae rhamnoides), and adzuki beans (Vigna angularis). All articles underwent in vitro and in vivo reassessment and used molecular docking methodology in their in silico studies. Among the studies included in the review, 46.15% were classified as having an "uncertain risk of bias" in six of the thirteen criteria evaluated. The primary target investigated was pancreatic lipase (n = 5), with all peptides targeting this enzyme demonstrating inhibition, a finding supported both in vitro and in vivo. Additionally, other peptides were identified as PPARγ and PPARα agonists (n = 2). Notably, all peptides exhibited different mechanisms of action in lipid metabolism and adipogenesis. The findings of this systematic review underscore the effectiveness of computational simulation as a screening tool, providing crucial insights and guiding in vitro and in vivo investigations for the discovery of novel anti-obesity peptides.

A Theoretical Study of the Interaction of PARP-1 with Natural and Synthetic Inhibitors: Advances in the Therapy of Triple-Negative Breast Cancer.

In the current study, we have investigated the secondary metabolites present in ethnomedical plants used for medicinal purposes-Astilbe chinensis (EK1), Scutellaria barbata D. Don (EK2), Uncaria rhynchophylla (EK3), Fallugia paradoxa (EK4), and Curcuma zedoaria (Christm.) Thread (EK5)-and we have compared them with five compounds of synthetic origin for the inhibition of PARP-1, which is linked to abnormal DNA replication, generating carcinogenic cells. We have studied these interactions through molecular dynamics simulations of each interacting system under physiological conditions (pH, temperature, and pressure) and determined that the compounds of natural origin have a capacity to inhibit PARP-1 (Poly(ADP-ribose) Polymerase 1) in all the cases inspected in this investigation. However, it is essential to mention that their interaction energy is relatively lower compared to that of compounds of synthetic origin. Given that binding energy is mandatory for the generation of a scale or classification of which is the best interacting agent, we can say that we assume that compounds of natural origin, having a complexation affinity with PARP-1, induce cell apoptosis, a potential route for the prevention of the proliferation of carcinogenic cells.

(-)-Epicatechin metabolites as a GPER ligands: a theoretical perspective.

Diet habits and nutrition quality significantly impact health and disease. Here is delve into the intricate relationship between diet habits, nutrition quality, and their direct impact on health and homeostasis. Focusing on (-)-Epicatechin, a natural flavanol found in various foods like green tea and cocoa, known for its positive effects on cardiovascular health and diabetes prevention. The investigation encompasses the absorption, metabolism, and distribution of (-)-Epicatechin in the human body, revealing a diverse array of metabolites in the circulatory system. Notably, (-)-Epicatechin demonstrates an ability to activate nitric oxide synthase (eNOS) through the G protein-coupled estrogen receptor (GPER). While the precise role of GPER and its interaction with classical estrogen receptors (ERs) remains under scrutiny, the study employs computational methods, including density functional theory, molecular docking, and molecular dynamics simulations, to assess the physicochemical properties and binding affinities of key (-)-Epicatechin metabolites with GPER. DFT analysis revealed distinct physicochemical properties among metabolites, influencing their reactivity and stability. Rigid and flexible molecular docking demonstrated varying binding affinities, with some metabolites surpassing (-)-Epicatechin. Molecular dynamics simulations highlighted potential binding pose variations, while MMGBSA analysis provided insights into the energetics of GPER-metabolite interactions. The outcomes elucidate distinct interactions, providing insights into potential molecular mechanisms underlying the effects of (-)-Epicatechin across varied biological contexts.

Targeting Leishmania infantum Mannosyl-oligosaccharide glucosidase with natural products: potential pH-dependent inhibition explored through computer-aided drug design.

Visceral Leishmaniasis (VL) is a serious public health issue, documented in more than ninety countries, where an estimated 500,000 new cases emerge each year. Regardless of novel methodologies, advancements, and experimental interventions, therapeutic limitations, and drug resistance are still challenging. For this reason, based on previous research, we screened natural products (NP) from Nuclei of Bioassays, Ecophysiology, and Biosynthesis of Natural Products Database (NuBBEDB), Mexican Compound Database of Natural Products (BIOFACQUIM), and Peruvian Natural Products Database (PeruNPDB) databases, in addition to structural analogs of Miglitol and Acarbose, which have been suggested as treatments for VL and have shown encouraging action against parasite's N-glycan biosynthesis. Using computer-aided drug design (CADD) approaches, the potential inhibitory effect of these NP candidates was evaluated by inhibiting the Mannosyl-oligosaccharide Glucosidase Protein (MOGS) from Leishmania infantum, an enzyme essential for the protein glycosylation process, at various pH to mimic the parasite's changing environment. Also, computational analysis was used to evaluate the Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) profile, while molecular dynamic simulations were used to gather information on the interactions between these ligands and the protein target. Our findings indicated that Ocotillone and Subsessiline have potential antileishmanial effects at pH 5 and 7, respectively, due to their high binding affinity to MOGS and interactions in the active center. Furthermore, these compounds were non-toxic and had the potential to be administered orally. This research indicates the promising anti-leishmanial activity of Ocotillone and Subsessiline, suggesting further validation through in vitro and in vivo experiments.

Anti-Obesity Therapeutic Targets Studied In Silico and In Vivo: A Systematic Review.

In the age of information technology and the additional computational search tools and software available, this systematic review aimed to identify potential therapeutic targets for obesity, evaluated in silico and subsequently validated in vivo. The systematic review was initially guided by the research question "What therapeutic targets have been used in in silico analysis for the treatment of obesity?" and structured based on the acronym PECo (P, problem; E, exposure; Co, context). The systematic review protocol was formulated and registered in PROSPERO (CRD42022353808) in accordance with the Preferred Reporting Items Checklist for Systematic Review and Meta-Analysis Protocols (PRISMA-P), and the PRISMA was followed for the systematic review. The studies were selected according to the eligibility criteria, aligned with PECo, in the following databases: PubMed, ScienceDirect, Scopus, Web of Science, BVS, and EMBASE. The search strategy yielded 1142 articles, from which, based on the evaluation criteria, 12 were included in the systematic review. Only seven these articles allowed the identification of both in silico and in vivo reassessed therapeutic targets. Among these targets, five were exclusively experimental, one was exclusively theoretical, and one of the targets presented an experimental portion and a portion obtained by modeling. The predominant methodology used was molecular docking and the most studied target was Human Pancreatic Lipase (HPL) (n = 4). The lack of methodological details resulted in more than 50% of the papers being categorized with an "unclear risk of bias" across eight out of the eleven evaluated criteria. From the current systematic review, it seems evident that integrating in silico methodologies into studies of potential drug targets for the exploration of new therapeutic agents provides an important tool, given the ongoing challenges in controlling obesity.

Computational modelling of extrusion process temperatures on the interactions between black soldier fly larvae protein and corn flour starch.

Insects such as the black soldier fly (BSF) are recently being studied as food sources to address concerns about how to meet the food demand of the growing world population, as conventional production lines for meat proteins are currently unsustainable sources. Studies have been conducted evaluating the use of insect proteins to produce extruded foods such as expanded snacks and meat analogues. However, this field of study is still quite new and not much has been studied beyond digestibility and growth performance. The purpose of this work was to evaluate the compatibility of protein extracted from BSF flour with corn flour starch within an extruded balanced shrimp feed model through molecular dynamics simulations, for which cohesive energy density and solubility parameter (δ) of both components were determined. The calculations' results for the protein molecule systems yielded an average δ of 14.961 MPa0.5, while the δ for starch was calculated to be 23.166 MPa0.5. The range of difference between both δ (10 > Î´ > 7) suggests that the interaction of the BSF protein with corn starch is of a semi-miscible nature. These results suggest that it is possible to obtain a stable starch-protein mixture through the extrusion process.

Evaluation of Urtica dioica Phytochemicals against Therapeutic Targets of Allergic Rhinitis Using Computational Studies.

Allergic rhinitis (AR) is a prevalent inflammatory condition affecting millions globally, with current treatments often associated with significant side effects. To seek safer and more effective alternatives, natural sources like Urtica dioica (UD) are being explored. However, UD's mechanism of action remains unknown. Therefore, to elucidate it, we conducted an in silico evaluation of UD phytochemicals' effects on known therapeutic targets of allergic rhinitis: histamine receptor 1 (HR1), neurokinin 1 receptor (NK1R), cysteinyl leukotriene receptor 1 (CLR1), chemoattractant receptor-homologous molecule expressed on type 2 helper T cells (CRTH2), and bradykinin receptor type 2 (BK2R). The docking analysis identified amentoflavone, alpha-tocotrienol, neoxanthin, and isorhamnetin 3-O-rutinoside as possessing a high affinity for all the receptors. Subsequently, molecular dynamics (MD) simulations were used to analyze the key interactions; the free energy of binding was calculated through Generalized Born and Surface Area Solvation (MMGBSA), and the conformational changes were evaluated. Alpha-tocotrienol exhibited a high affinity while also inducing positive conformational changes across all targets. Amentoflavone primarily affected CRTH2, neoxanthin targeted NK1R, CRTH2, and BK2R, and isorhamnetin-3-O-rutinoside acted on NK1R. These findings suggest UD's potential to treat AR symptoms by inhibiting these targets. Notably, alpha-tocotrienol emerges as a promising multi-target inhibitor. Further in vivo and in vitro studies are needed for validation.

Targeting with Structural Analogs of Natural Products the Purine Salvage Pathway in Leishmania (Leishmania) infantum by Computer-Aided Drug-Design Approaches.

Visceral Leishmaniasis (VL) has a high death rate, with 500,000 new cases and 50,000 deaths occurring annually. Despite the development of novel strategies and technologies, there is no adequate treatment for the disease. Therefore, the purpose of this study is to find structural analogs of natural products as potential novel drugs to treat VL. We selected structural analogs from natural products that have shown antileishmanial activities, and that may impede the purine salvage pathway using computer-aided drug-design (CADD) approaches. For these, we started with the vastly studied target in the pathway, the adenine phosphoribosyl transferase (APRT) protein, which alone is non-essential for the survival of the parasite. Keeping this in mind, we search for a substance that can bind to multiple targets throughout the pathway. Computational techniques were used to study the purine salvage pathway from Leishmania infantum, and molecular dynamic simulations were used to gather information on the interactions between ligands and proteins. Because of its low homology to human proteins and its essential role in the purine salvage pathway proteins network interaction, the findings further highlight the significance of adenylosuccinate lyase protein (ADL) as a therapeutic target. An analog of the alkaloid Skimmianine, N,N-diethyl-4-methoxy-1-benzofuran-6-carboxamide, demonstrated a good binding affinity to APRT and ADL targets, no expected toxicity, and potential for oral route administration. This study indicates that the compound may have antileishmanial activity, which was granted in vitro and in vivo experiments to settle this finding in the future.

Assessment of Kaistella jeonii esterase conformational dynamics in response to poly(ethylene terephthalate) binding.

The pervasive presence of plastic in the environment has reached a concerning scale, being identified in many ecosystems. Bioremediation is the cheapest and most eco-friendly alternative to remove this polymer from affected areas. Recent work described that a novel cold-active esterase enzyme extracted from the bacteria Kaistella jeonii could promiscuously degrade PET. Compared to the well-known PETase from Ideonella sakaiensis, this novel esterase presents a low sequence identity yet has a remarkably similar folding. However, enzymatic assays demonstrated a lower catalytic efficiency. In this work, we employed a strict computational approach to investigate the binding mechanism between the esterase and PET. Understanding the underlying mechanism of binding can shed light on the evolutive mechanism of how enzymes have been evolving to degrade these artificial molecules and help develop rational engineering approaches to improve PETase-like enzymes. Our results indicate that this esterase misses a disulfide bridge, keeping the catalytic residues closer and possibly influencing its catalytic efficiency. Moreover, we describe the structural response to the interaction between enzyme and PET, indicating local and global effects. Our results aid in deepening the knowledge behind the mechanism of biological catalysis of PET degradation and as a base for the engineering of novel PETases.

In silico analysis of alpha-synuclein protein variants and posttranslational modifications related to Parkinson's disease.

Parkinson's disease (PD) is among the most prevalent neurodegenerative disorders, affecting over 10 million people worldwide. The protein encoded by the SNCA gene, alpha-synuclein (ASYN), is the major component of Lewy body (LB) aggregates, a histopathological hallmark of PD. Mutations and posttranslational modifications (PTMs) in ASYN are known to influence protein aggregation and LB formation, possibly playing a crucial role in PD pathogenesis. In this work, we applied computational methods to characterize the effects of missense mutations and PTMs on the structure and function of ASYN. Missense mutations in ASYN were compiled from the literature/databases and underwent a comprehensive predictive analysis. Phosphorylation and SUMOylation sites of ASYN were retrieved from databases and predicted by algorithms. ConSurf was used to estimate the evolutionary conservation of ASYN amino acids. Molecular dynamics (MD) simulations of ASYN wild-type and variants A30G, A30P, A53T, and G51D were performed using the GROMACS package. Seventy-seven missense mutations in ASYN were compiled. Although most mutations were not predicted to affect ASYN stability, aggregation propensity, amyloid formation, and chaperone binding, the analyzed mutations received relatively high rates of deleterious predictions and predominantly occurred at evolutionarily conserved sites within the protein. Moreover, our predictive analyses suggested that the following mutations may be possibly harmful to ASYN and, consequently, potential targets for future investigation: K6N, T22I, K34E, G36R, G36S, V37F, L38P, G41D, and K102E. The MD analyses pointed to remarkable flexibility and essential dynamics alterations at nearly all domains of the studied variants, which could lead to impaired contact between NAC and the C-terminal domain triggering protein aggregation. These alterations may have functional implications for ASYN and provide important insight into the molecular mechanism of PD, supporting the design of future biomedical research and improvements in existing therapies for the disease.

Molecular insight into endosulfan degradation by Ese protein from Arthrobacter: Evidence-based structural bioinformatics and quantum mechanical calculations.

Endosulfan is an organochlorine insecticide widely used for agricultural pest control. Many nations worldwide have restricted or completely banned it due to its extreme toxicity to fish and aquatic invertebrates. Arthrobacter sp. strain KW has the ability to degrade α, ß endosulfan and its intermediate metabolite endosulfate; this degradation is associated with Ese protein, a two-component flavin-dependent monooxygenase (TC-FDM). Employing in silico tools, we obtained the 3D model of Ese protein, and our results suggest that it belongs to the Luciferase Like Monooxygenase family (LLM). Docking studies showed that the residues V59, V315, D316, and T335 interact with α-endosulfan. The residues: V59, T60, V315, D316, and T335 are implicated in the interacting site with ß-endosulfan, and the residues: H17, V315, D316, T335, N364, and Q363 participate in the interaction with endosulfate. Topological analysis of the electron density by means of the Quantum Theory of Atoms in Molecules (QTAIM) and the Non-Covalent Interaction (NCI) index reveals that the Ese-ligands complexes are formed mainly by dispersive forces, where Cl atoms have a predominant role. As Ese is a monooxygenase member, we predict the homodimer formation. However, enzymatic studies must be developed to investigate the Ese protein's enzymatic and catalytic activity.

In silico drug repurposing by combining machine learning classification model and molecular dynamics to identify a potential OGT inhibitor.

O-linked N-acetylglucosamine (O-GlcNAc) is a unique intracellular post-translational glycosylation at the hydroxyl group of serine or threonine residues in nuclear, cytoplasmic and mitochondrial proteins. The enzyme O-GlcNAc transferase (OGT) is responsible for adding GlcNAc, and anomalies in this process can lead to the development of diseases associated with metabolic imbalance, such as diabetes and cancer. Repurposing approved drugs can be an attractive tool to discover new targets reducing time and costs in the drug design. This work focuses on drug repurposing to OGT targets by virtual screening of FDA-approved drugs through consensus machine learning (ML) models from an imbalanced dataset. We developed a classification model using docking scores and ligand descriptors. The SMOTE approach to resampling the dataset showed excellent statistical values in five of the seven ML algorithms to create models from the training set, with sensitivity, specificity and accuracy over 90% and Matthew's correlation coefficient greater than 0.8. The pose analysis obtained by molecular docking showed only H-bond interaction with the OGT C-Cat domain. The molecular dynamics simulation showed the lack of H-bond interactions with the C- and N-catalytic domains allowed the drug to exit the binding site. Our results showed that the non-steroidal anti-inflammatory celecoxib could be a potentially OGT inhibitor.

Antiviral Activity and Molecular Dynamics Simulation of Hops Compounds against Oropouche Virus (Peribunyaviridae).

The Oropouche virus (OROV) is a member of the family Peribunyaviridae (order Bunyavirales) and the cause of a dengue-like febrile illness transmitted mainly by biting midges and mosquitoes. In this study, we aimed to explore acylphloroglucinols and xanthohumol from hops (Humulus lupulus L.) as a promising alternative for antiviral therapies. The evaluation of the inhibitory potential of hops compounds on the viral cycle of OROV was performed through two complementary approaches. The first approach applies cell-based assay post-inoculation experiments to explore the inhibitory potential on the latest steps of the viral cycle, such as genome translation, replication, virion assembly, and virion release from the cells. The second part covers in silico methods evaluating the ability of those compounds to inhibit the activity of the endonuclease domain, which is essential for transcription, binding, and cleaving RNA. In conclusion, the beta acids showed strongest inhibitory potential in post-treatment assay (EC50 = 26.7 µg/mL). Xanthohumol had the highest affinity for OROV endonuclease followed by colupulone and cohumulone. This result contrasts with that observed for docking and MM/PBSA analysis, where cohumulone was found to have a higher affinity. Finally, among the three tested ligands, Lys92 and Arg33 exhibited the highest affinity with the protein.

Calcium-Alginate-Chitosan Nanoparticle as a Potential Solution for Pesticide Removal, a Computational Approach.

Pesticides have a significant negative impact on the environment, non-target organisms, and human health. To address these issues, sustainable pest management practices and government regulations are necessary. However, biotechnology can provide additional solutions, such as the use of polyelectrolyte complexes to encapsulate and remove pesticides from water sources. We introduce a computational methodology to evaluate the capture capabilities of Calcium-Alginate-Chitosan (CAC) nanoparticles for a broad range of pesticides. By employing ensemble-docking and molecular dynamics simulations, we investigate the intermolecular interactions and absorption/adsorption characteristics between the CAC nanoparticles and selected pesticides. Our findings reveal that charged pesticide molecules exhibit more than double capture rates compared to neutral counterparts, owing to their stronger affinity for the CAC nanoparticles. Non-covalent interactions, such as van der Waals forces, π-π stacking, and hydrogen bonds, are identified as key factors which stabilized the capture and physisorption of pesticides. Density profile analysis confirms the localization of pesticides adsorbed onto the surface or absorbed into the polymer matrix, depending on their chemical nature. The mobility and diffusion behavior of captured compounds within the nanoparticle matrix is assessed using mean square displacement and diffusion coefficients. Compounds with high capture levels exhibit limited mobility, indicative of effective absorption and adsorption. Intermolecular interaction analysis highlights the significance of hydrogen bonds and electrostatic interactions in the pesticide-polymer association. Notably, two promising candidates, an antibiotic derived from tetracycline and a rodenticide, demonstrate a strong affinity for CAC nanoparticles. This computational methodology offers a reliable and efficient screening approach for identifying effective pesticide capture agents, contributing to the development of eco-friendly strategies for pesticide removal.

Computer-aided drug design approaches applied to screen natural product's structural analogs targeting arginase in Leishmania spp.

Introduction: Leishmaniasis is a disease with high mortality rates and approximately 1.5 million new cases each year. Despite the new approaches and advances to fight the disease, there are no effective therapies. Methods: Hence, this study aims to screen for natural products' structural analogs as new drug candidates against leishmaniasis. We applied Computer-aided drug design (CADD) approaches, such as virtual screening, molecular docking, molecular dynamics simulation, molecular mechanics-generalized Born surface area (MM-GBSA) binding free estimation, and free energy perturbation (FEP) aiming to select structural analogs from natural products that have shown anti-leishmanial and anti-arginase activities and that could bind selectively against the Leishmania arginase enzyme. Results: The compounds 2H-1-benzopyran, 3,4-dihydro-2-(2-methylphenyl)-(9CI), echioidinin, and malvidin showed good results against arginase targets from three parasite species and negative results for potential toxicities. The echioidinin and malvidin ligands generated interactions in the active center at pH 2.0 conditions by MM-GBSA and FEP methods. Conclusions: This work suggests the potential anti-leishmanial activity of the compounds and thus can be further in vitro and in vivo experimentally validated.

A Multi-epitope Vaccine Candidate Against Bolivian Hemorrhagic fever Caused by Machupo Virus.

Bolivian hemorrhagic fever (BHF) caused by Machupo virus (MACV) is a New World arenavirus having a reported mortality rate of 25-35%. The BHF starts with fever, followed by headache, and nausea which rapidly progresses to severe hemorrhagic phase within 7 days of disease onset. One of the key promoters for MACV viral entry into the cell followed by viral propagation is performed by the viral glycoprotein (GPC). GPC is post-transcriptionally cleaved into GP1, GP2 and a signal peptide. These proteins all take part in the viral infection in host body. Therefore, GPC protein is an ideal target for developing therapeutics against MACV infection. In this study, GPC protein was considered to design a multi-epitope, multivalent vaccine containing antigenic and immunogenic CTL and HTL epitopes. Different structural validations and physicochemical properties were analysed to validate the vaccine. Docking and molecular dynamics simulations were conducted to understand the interactions of the vaccine with various immune receptors. Finally, the vaccine was codon optimised in silico and along with which immune simulation studies was performed in order to evaluate the vaccine's effectiveness in triggering an efficacious immune response against MACV.

Glycosylation and charge distribution orchestrates the conformational ensembles of a biotechnologically promissory phytase in different pHs - a computational study.

Phytases [myo-inositol(1,2,3,4,5,6) hexakisphosphate phosphohydrolases] are phytate-specific phosphatases not present in monogastric animals. Nevertheless, they are an essential supplement to feeding such animals and for human special diets. It is crucial, hence, the biotechnological use of phytases with intrinsic stability and activity at the acid pHs from gastric environments. Here we use Metadynamics (METADY) simulations to probe the conformational space of the Aspergillus nidulans phytase and the differential effects of pH and glycosylation in this same space. The results suggest that strategic combinations of pH and glycosylation affect the stability of native-like conformations and alternate these structures from a metastable to a stable profile. Furthermore, the protein segments previously reported as more thermosensitive in phytases from this family present a pivotal role in the conformational changes at different conditions, especially H2, H5-7, L8, L10, L12, and L17. Also, the glycosylations and the pH-dependent charge balance modulate the mobility and interactions at these same regions, with consequences for the surface solvation and active site exposition. Finally, although the glycosylations have stabilized the native structure and improved the substrate docking at all the studied pHs, the data suggest a higher phytate receptivity at catalytic poses for the unglycosylated structure at pH 6.5 and the glycosylated one at pH 4.5. This behavior agrees with the exact change in optimum pH reported for this enzyme, expressed on low or high glycosylating systems. We hope the results and insights presented here will be helpful in future approaches for rational engineering of technologically promising phytases and intelligent planning of their heterologous expression systems and conditions for use.Communicated by Ramaswamy H. Sarma.

Modeling the zinc effect on OsASR5-STAR1 promoter interaction by molecular dynamics.

Intrinsically disordered proteins (IDPs) have numerous dynamic conformations. Given the difficulties in tracking temporarily folded states of this kind of protein, methods such as molecular modeling and molecular dynamics (MD) simulations make the process less costly, less laborious, and more detailed. Few plant IDPs have been characterized so far, such as proteins from the Abscisic acid, Stress and Ripening (ASR) family. The present work applied, for the first time, the two above-mentioned tools to test the feasibility of determining a three-dimensional transition model of OsASR5 and to investigate the relationship between OsASR5 and zinc. We found that one of OsASR5's conformers contains α-helices, turns, and loops and that the metal binding resulted in a predominance of α-helix. This stability is possibly imperative for the transcription factor activity. The promoter region of a sugar transporter was chosen to test this hypothesis and free energy calculations showed how the ion is mandatory for this complex formation. The results produced here aim to clarify which conformation the protein in the bound state assumes and which residues are involved in the process, besides developing the understanding of how the flexibility of these proteins can contribute to the response to environmental stresses.