Screening Of Molecules Research Articles

A ratiometric fluorescent probe for cysteine and glutathione differentiation and its application for cysteine detection in foods

Cysteine (Cys) and glutathione (GSH) are crucial biothiols implicated in cellular redox balance, necessitating accurate detection methods. Herein, we developed a novel fluorescent probe based on the fluorescent dye pyronin (PYR), capable of monitoring both Cys-and GSH using ratiometric fluorescence signals. The probe, named PYR-CG, where "C" stands for Cys-and "G" stands for GSH, demonstrates selective detection capabilities for Cys-and GSH. UV absorption and fluorescence emission spectra changes revealed distinct shifts upon interaction with Cys-and GSH. Theoretical and experimental studies validated PYR-CG's responsiveness to Cys-and GSH, elucidating its mechanism as a ratiometric probe. Notably, PYR-CG exhibited rapid response kinetics for Cys-and GSH, with low detection limits of 88 nM and 164 nM, respectively. Importantly, PYR-CG demonstrated exceptional selectivity for Cys-and GSH over interfering analytes. Screening of molecules with similar structures to Cys-further affirmed PYR-CG's specificity, particularly towards N-terminal Cys-in peptides. Furthermore, recovery experiments underscored PYR-CG's reliability for quantitative Cys-detection in complex food samples. Our findings highlight the innovative design and practical applicability of PYR-CG, offering a valuable tool for sensitive and selective detection of Cys-in diverse biological and food samples.

Photo-Excited Dyes: Emerging Technique Against Tau Protein Aggregation.

Tau aggregates are considered a pathological hallmark of Alzheimer's disease. The screening of molecules against Tau aggregation is a novel strategy for Alzheimer's disease. The photo-excited molecules have proven to be effective as a therapeutic agent in several diseases. In recent studies, the photo-excited dyes showed an inhibitory effect on Alzheimer's disease-related Tau protein aggregation and toxicity. The present chapter deals with the effect of rose bengal on the aggregation of Tau. The in vitro studies carried out with the help of electron microscopy, ThS fluorescence, and circular dichroism suggested that RB attenuated the Tau aggregation under in vitro conditions, whereas PE-RB disaggregated the mature Tau fibrils. Photo-excited rose bengal and the classicalrose bengal induced a low degree of toxicity in cells. Thus, for the treatment of Alzheimer's disease, the rose bengal could be considered a potential molecule.

Comparative evaluation of recommendations for preclinical studies of transporter-mediated drug–drug interactions

Scientific relevance. Sound recommendations for preclinical studies of transporter- mediated pharmacokinetic interactions of medicinal products can help increase the likelihood of identifying potentially nephrotoxic and hepatotoxic medicinal products at the development and authorisation stages. However, overly strict requirements for the number of studies to be performed may lead to a significant increase in the cost of finished medicinal products.Aim. The aim was to compare regulatory documents on studying transporter-mediated drug–drug interactions (DDIs).Discussion. This review examines changes in regulatory requirements for studying DDIs in chronological order from the first guidelines that appeared in 1997. As exemplified in this article, the multiplicity of transporters and the lack of specific inhibitors pose significant challenges in assessing the role of a particular transporter in drug distribution and drug–drug interactions. This comparative review shows that extrapolating from in vitro transporter inhibition studies to in vivo pharmacokinetics can be misleading.Conclusions. A unified approach to studying transporter-mediated DDIs will increase the likelihood of identifying potentially toxic agents at the stage of new molecule screening. At the same time, it is advisable to limit the number of in vitro and in vivo transporter studies and recommend conducting these studies only for medicinal products with a narrow therapeutic index.

Identification and Validation of a Ferroptosis Prognostic Model for Prostate Cancer Patients through Screening the TCGA and scRNA-seq Datasets.

Ferroptosis is currently a common mode of programmed cell death, and the induction of ferroptosis is a new strategy and idea for current tumor therapy. Therefore, the signaling pathways and genes regulated by ferroptosis are significant markers for current malignant tumor therapy. To construct a prognostic model for predicting the survival prognosis of prostate cancer (PCa) based on the molecules and markers related to ferroptosis, we combined with differentially expressed genes (DEGs) in PCa patients, and further analyze the correlation between this risk score and immune cell infiltration. Finally, to validate the expression of risk genes and analyze the expression and localization of risk genes in using the datasets of single cell RNA-sequencing (scRNA-seq). Firstly, we screened the DEGs in PCa patients by the expression profiles of TCGA database. Meanwhile, we collected the information of ferroptosis regulatory genes from FerrDb, and these two parts were intersected. Then the impact of genes on the survival and prognosis of PCa patients was confirmed and selected by LASSO regression, further screening of molecules and fitting the risk format. And the efficacy of the model was evaluated by ROC curves. The immune cell infiltration of PCa tissues was predicted using TIMER. Last, the scRNA-seq of PCa (GSM5155455, GSM3735993) were carried to reveal the expression of risk molecules in different cell types. Besides, the expression of risk molecules was validated using PCa cell lines. We found a total of 259 DEGs associated with ferroptosis in PCa tissues. After LASSO regression, we screened DRD5, LINC00336, ACSF2, RRM2, NOX1, GDF15, ALB, MIOX, and NOX4 as variables to establish a prognostic model, and the specific risk scores was calculated following this format: Risk score = (-1.9465)*DRD5+(-1.6806)*LINC00336+(0.3045)*ACSF2+(0.4747)*RRM2+(-0.2815)*NOX1+(-0.1871)* GDF15+(0.1846)*ALB+(0.2676)*MIOX+(0.1648)*NOX4 (lambda.min = 0.0032), with a 10-yr AUC value of 0.751 (95% CI, 0.549-0.953). Furthermore, we discovered the higher the scores, the fewer CD8+ T cells infiltrated as predicting, showing a negative relationship. By testing the gene sets of scRNA-seq forPCa, we discovered that RRM2, GDF15, ALB, and MIOX were mainly expressed in tumor cells, T cells, B cells and neutrophils of PCa tissues, and not in endothelial cells. Finally, we detected differences in protein expression of RRM2, GDF15, and MIOX in PCa cell lines compared to normal prostate cancer epithelium by WB. We constructed a novel prognostic model for PCa based on ferroptosis-related genes, which showed better predictive validity. And we analyzed the cellular expression of risk genes by scRNA-seq, which will be explored future in relation to prostate cancer radiotherapy.

Antityrosinase Activity of Phycocyanin and Cream Formulation for Hyperpigmentation

Free radicals are involved in the catalytic reactions of tyrosinase to give dopaquinone in melanin biosynthesis. Screening of molecules with antioxidant activity from natural sources which inhibit tyrosinase has become important for cosmetic and medicinal topical products. Tyrosinase inhibitors are used in treating hyperpigmentation. Synthetic tyrosinase inhibitors possess side effects such as skin irritation, dermatitis, dryness, and inflammatory reaction. The objective of the study is to evaluate the tyrosinase inhibition potential of phycocyanin, which is a pigment extracted from the blue green algae Spirulina platensis and formulating a cream that can be used to treat hyperpigmentation. Phycocyanin possesses anticancer, antioxidant, antiviral and anti-inflammatory activities and exhibits the regulative ability of tyrosinase expression and thereby modulates melanogenesis. The spectral characterization of phycocyanin is carried out using UV-vis spectroscopy, FTIR and HPTLC. Phycocyanin showed tyrosinase inhibition potential with an IC50 of 30.88-39.87 μg/ml in SK-Mel-28 melanoma cells. In melanogenesis pathway, tyrosinase regulates the production of melanin by the skin cells and by incorporating phycocyanin in cream will reduce the melanin production and treat hyperpigmentation.

Application of machine learning in combination with mechanistic modeling to predict plasma exposure of small molecules

Prediction of a new molecule’s exposure in plasma is a critical first step toward understanding its efficacy/toxicity profile and concluding whether it is a possible first-in-class, best-in-class candidate. For this prediction, traditional pharmacometrics use a variety of scaling methods that are heavily based on pre-clinical pharmacokinetic (PK) data. We here propose a novel framework based on which preclinical exposure prediction is performed by applying machine learning (ML) in tandem with mechanism-based modeling. In our proposed method, a relationship is initially established between molecular structure and physicochemical (PC)/PK properties using ML, and then the ML-driven PC/PK parameters are used as input to mechanistic models that ultimately predict the plasma exposure of new candidates. To understand the feasibility of our proposed framework, we evaluated a number of mechanistic models (1-compartment, physiologically based pharmacokinetic (PBPK)), PBPK distribution models (Berezhkovskiy, PK-Sim standard, Poulin and Theil, Rodgers and Rowland, and Schmidt), and PBPK parameterizations (using in vivo, or in vitro clearance). For most of the scenarios tested, our results demonstrate that PK profiles can be adequately predicted based on the proposed framework. Our analysis further indicates some limitations when liver microsomal intrinsic clearance (CLint) is used as the only clearance pathway and underscores the necessity of investigating the variability emanating from the different distribution models when providing PK predictions. The suggested approach aims at earlier exposure prediction in the drug development process so that critical decisions on molecule screening, chemistry design, or dose selection can be made as early as possible.

DEL-Dock: Molecular Docking-Enabled Modeling of DNA-Encoded Libraries.

DNA-encoded library (DEL) technology has enabled significant advances in hit identification by enabling efficient testing of combinatorially generated molecular libraries. DEL screens measure protein binding affinity though sequencing reads of molecules tagged with unique DNA barcodes that survive a series of selection experiments. Computational models have been deployed to learn the latent binding affinities that are correlated to the sequenced count data; however, this correlation is often obfuscated by various sources of noise introduced in its complicated data-generation process. In order to denoise DEL count data and screen for molecules with good binding affinity, computational models require the correct assumptions in their modeling structure to capture the correct signals underlying the data. Recent advances in DEL models have focused on probabilistic formulations of count data, but existing approaches have thus far been limited to only utilizing 2-D molecule-level representations. We introduce a new paradigm, DEL-Dock, that combines ligand-based descriptors with 3-D spatial information from docked protein-ligand complexes. 3-D spatial information allows our model to learn over the actual binding modality rather than using only structure-based information of the ligand. We show that our model is capable of effectively denoising DEL count data to predict molecule enrichment scores that are better correlated with experimental binding affinity measurements compared to prior works. Moreover, by learning over a collection of docked poses we demonstrate that our model, trained only on DEL data, implicitly learns to perform good docking pose selection without requiring external supervision from expensive-to-source protein crystal structures.

The β3-subunit modulates the effect of venom peptides ProTx-II and OD1 on NaV 1.7 gating.

The voltage-gated sodium channel NaV 1.7 is involved in various pain phenotypes and is physiologically regulated by the NaV -β3-subunit. Venom toxins ProTx-II and OD1 modulate NaV 1.7 channel function and may be useful as therapeutic agents and/or research tools. Here, we use patch-clamp recordings to investigate how the β3-subunit can influence and modulate the toxin-mediated effects on NaV 1.7 function, and we propose a putative binding mode of OD1 on NaV 1.7 to rationalise its activating effects. The inhibitor ProTx-II slowed the rate of NaV 1.7 activation, whilst the activator OD1 reduced the rate of fast inactivation and accelerated recovery from inactivation. The β3-subunit partially abrogated these effects. OD1 induced a hyperpolarising shift in theV1/2 of steady-state activation, which was not observed in the presence of β3. Consequently, OD1-treated NaV 1.7 exhibited an enhanced window current compared with OD1-treated NaV 1.7-β3 complex. We identify candidate OD1 residues that are likely to prevent the upward movement of the DIV S4 helix and thus impede fast inactivation. The binding sites for each of the toxins and the predicted location of the β3-subunit on the NaV 1.7 channel are distinct. Therefore, we infer that the β3-subunit influences the interaction of toxins with NaV 1.7 via indirect allosteric mechanisms. The enhanced window current shown by OD1-treated NaV 1.7 compared withOD1-treated NaV 1.7-β3 is discussed in the context of differing cellular expressions of NaV 1.7 and the β3-subunit in dorsal root ganglion (DRG) neurons. We propose that β3, as the native binding partner for NaV 1.7 in DRG neurons, should be included during screening of molecules against NaV 1.7 in relevant analgesic discovery campaigns.

Integrative transcriptome analysis of SARS-CoV-2 human-infected cells combined with deep learning algorithms identifies two potential cellular targets for the treatment of coronavirus disease.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) quickly spread worldwide, leading coronavirus disease 2019 (COVID-19) to hit pandemic level less than 4months after the first official cases. Hence, the search for drugs and vaccines that could prevent or treat infections by SARS-CoV-2 began, intending to reduce a possible collapse of health systems. After 2years, efforts to find therapies to treat COVID-19 continue. However, there is still much to be understood about the virus' pathology. Tools such as transcriptomics have been used to understand the impact of SARS-CoV-2 on different cells isolated from various tissues, leaving datasets in the databases that integrate genes and differentially expressed pathways during SARS-CoV-2 infection. After retrieving transcriptome datasets from different human cells infected with SARS-CoV-2 available in the database, we performed an integrative analysis associated with deep learning algorithms to determine differentially expressed targets mainly after infection. The targets found represented a fructose transporter (GLUT5) and a component of proteasome 26s. These targets were then molecularly modeled, followed by molecular docking that identified potential inhibitors for both structures. Once the inhibition of structures that have the expression increased by the virus can represent a strategy for reducing the viral replication by selecting infected cells, associating these bioinformatics tools, therefore, can be helpful in the screening of molecules being tested for new uses, saving financial resources, time, and making a personalized screening for each infectious disease.

Targets preliminary screening for the fresh natural drug molecule based on Cosine-correlation and similarity-comparison of local network

BackgroundChinese herbal medicine is made up of hundreds of natural drug molecules and has played a major role in traditional Chinese medicine (TCM) for several thousand years. Therefore, it is of great significance to study the target of natural drug molecules for exploring the mechanism of treating diseases with TCM. However, it is very difficult to determine the targets of a fresh natural drug molecule due to the complexity of the interaction between drug molecules and targets. Compared with traditional biological experiments, the computational method has the advantages of less time and low cost for targets screening, but it remains many great challenges, especially for the molecules without social ties.MethodsThis study proposed a novel method based on the Cosine-correlation and Similarity-comparison of Local Network (CSLN) to perform the preliminary screening of targets for the fresh natural drug molecules and assign weights to them through a trained parameter.ResultsThe performance of CSLN is superior to the popular drug-target-interaction (DTI) prediction model GRGMF on the gold standard data in the condition that is drug molecules are the objects for training and testing. Moreover, CSLN showed excellent ability in checking the targets screening performance for a fresh-natural-drug-molecule (scenario simulation) on the TCMSP (13 positive samples in top20), meanwhile, Western-Blot also further verified the accuracy of CSLN.ConclusionsIn summary, the results suggest that CSLN can be used as an alternative strategy for screening targets of fresh natural drug molecules.

In-silico characterization of phytochemicals identified from Vitex negundo (L) extract as potential therapy for Wnt-signaling proteins

BackgroundColorectal cancer is the third most diagnosed disease in the world population and current chemotherapy has been used for targeting the cell proliferation and metastasizing ability of tumor cells. Potent chemotherapeutic drugs for colorectal cancer are capecitabine, fluorouracil, irinotecan, etc. which have toxic effects in normal tissues and adverse effects in multiple organs leading to major obstacles in clinical use. The aim of the study is the use of plant-derived compounds that improve the effectiveness of chemotherapeutics with lower and alleviate toxic side effects and reduce the risk of tumor progression.ResultsThe current study is performed using Vitex negundo leaf which has been demonstrated to have positive effects against colorectal cancer. The use of computational approaches will help improve the identification and screening of lead molecules using AutoDock 4.2 and AutoDock Vina. Using computational approaches will help to improve lead identification and screening. Herein, we have retrieved six phytochemicals from published literature and investigated their inhibitory effect with Wnt-associated signaling proteins. Authentication of phytocompounds and Wnt-associated signaling proteins was done using AutoDock.4.2.ConclusionsThe results are screened based on the number of hydrogen bonds, binding energy, and interacting amino acids. The Isoorientin, luteolin, and Chrysophanol get the highest binding energy with target receptors. The binding energy is calculated with all target receptors from the range of − 6.0 to − 8.9 kcal/mol. The In-silico drug likeliness properties are predicted to be the best interacting compounds based on Lipinski Rule of 5 and ADMET analysis. Hence, we propose that Isoorientin, luteolin, and Chrysophanol are the potential inhibitors of Wnt signaling inhibitors, and preclinical studies are needed to confirm the promising therapeutic ability of colorectal cancer.

Hyoscyamus albus nortropane alkaloids reduce hyperglycemia and hyperinsulinemia induced in HepG2 cells through the regulation of SIRT1/NF-kB/JNK pathway

BackgroundChronic superphysiological glucose and insulin concentrations are known to trigger several tissue and organ failures, including insulin resistance, oxidative stress and chronic low-grade inflammation. Hence, the screening for molecules that may counteract such conditions is essential in current existing therapeutic strategies, thereby the use of medicinal plant derivatives represents a promising axis in this regard.MethodsIn this study, the effect of a selected traditional medicinal plant, Hyoscyamus albus from which, calystegines have been isolated, was investigated in an experimental model of hyperinsulinemia and hyperglycemia induced on HepG2 cells. The mRNA and protein expression levels of different insulin signaling, gluconeogenic and inflammatory pathway- related molecules were examined. Additionally, cell viability and apoptosis, oxidative stress extent and mitochondrial dysfunctions were assayed using flow cytometric and qRT-PCR techniques.ResultsTreatment of IR HepG2 cells with calystegines strongly protected the injured cells from apoptosis, oxidative stress and mitochondrial integrity loss. Interestingly, nortropane alkaloids efficiently regulated the impaired glucose metabolism in IR HepG2 cells, through the stimulation of glucose uptake and the modulation of SIRT1/Foxo1/G6PC/mTOR pathway, which is governing the hepatic gluconeogenesis. Furthermore, the alkaloidal extract restored the defective insulin signaling pathway, mainly by promoting the expression of Insr at the mRNA and protein levels. What is more, treated cells exhibited significant mitigated inflammatory response, as evidenced by the modulation and the regulation of the NF- κB/JNK/TLR4 axis and the downstream proinflammatory cytokines recruitment.ConclusionOverall, the present investigation demonstrates that calystegines from Hyoscyamus albus provide cytoprotection to the HepG2 cells against insulin/glucose induced insulin resistance and apoptosis due to the regulation of SIRT1/Foxo1/G6PC/mTOR and NF-κB/JNK/TLR4 signaling pathways.1oVDx9MMsFkfL9sCGFfm2tVideo

Methods in Screening Antiviral Drugs Against Enterovirus 71.

Enteroviruses 71 (EV71) is a single-stranded, neurotrophic RNA virus responsible for the numerous outbreaks of hand, foot, and mouth disease (HFMD) in the Asia-Pacific regions. HFMD primarily affects children to cause range of infection, from mild symptoms to acute flaccid paralysis, and hemorrhage. Despite increased incidence of EV71 epidemics globally and research against EV71 becoming prioritized, no antiviral agent against EV71 has yet been licensed and approved worldwide. In this chapter, detailed EV71 antiviral screening techniques are described, including plaque assay which determines viral titers through the use of a semisolid overlay, carboxymethyl cellulose to allow even viral spread and infection across the host cellular monolayers as well as a crystal violet, a distinct counterstain to visualize circular regions of infectious zones-plaques. qRT-PCR is used to quantify the viral genomic RNA in the infected samples and MTS cell viability assay to quantify the cell viability after infection or toxicity of the compound on the cells. Furthermore, various antiviral inhibition assays including prophylactic, post infection, and virucidal assays are demonstrated for estimation of the antiviral activity of potential antiviral drugs against EV71. These methods can be effectively utilized in virology laboratories for effective high-throughput screening of antiviral molecules against EV71 that can assist in the future development of antiviral drugs.

Isolation and screening for novel bioactive molecules from endophytes associated with Arisaema erubescens (wall.) shott

Isolation and screening for novel bioactive molecules from endophytes associated with Arisaema erubescens (wall.) shott

Congenital muscular dystrophy-associated inflammatory chemokines provide axes for effective recruitment of therapeutic adult stem cell into muscles

BackgroundCongenital muscular dystrophies (CMD) are a clinically and genetically heterogeneous group of neuromuscular disorders characterized by muscle weakness. The two most prevalent forms of CMD, collagen VI-related myopathies (COL6RM) and laminin α2 deficient CMD type 1A (MDC1A), are both caused by deficiency or dysfunction of extracellular matrix proteins. Previously, we showed that an intramuscular transplantation of human adipose-derived stem cells (ADSC) into the muscle of the Col6a1−/− mice results in efficient stem cell engraftment, migration, long-term survival, and continuous production of the collagen VI protein, suggesting the feasibility of the systemic cellular therapy for COL6RM. In order for this therapeutic approach to work however, stem cells must be efficiently targeted to the entire body musculature. Thus, the main goal of this study is to test whether muscle homing of systemically transplanted ADSC can be enhanced by employing muscle-specific chemotactic signals originating from CMD-affected muscle tissue.MethodsProteomic screens of chemotactic molecules were conducted in the skeletal muscles of COL6RM- and MDC1A-affected patients and CMD mouse models to define the inflammatory and immune activities, thus, providing potential markers of disease activity or treatment effect. Also using a pre-clinical animal model, recapitulating mild Ullrich congenital muscular dystrophy (UCMD), the therapeutic relevance of identified chemotactic pathways was investigated in vivo, providing a basis for future clinical investigations.ResultsComprehensive proteomic screens evaluating relevant human and mouse skeletal muscle biopsies offered chemotactic axes to enhance directional migration of systemically transplanted cells into CMD-affected muscles, including CCL5-CCR1/3/5, CCL2-CCR2, CXCL1/2-CXCR1,2, and CXCL7-CXCR2. Also, the specific populations of ADSC selected with an affinity for the chemokines being released by damaged muscle showed efficient migration to injured site and presented their therapeutic effect.ConclusionsCollectively, identified molecules provided insight into the mechanisms governing directional migration and intramuscular trafficking of systemically infused stem cells, thus, permitting broad and effective application of the therapeutic adult stem cells for CMD treatment.

Ligand-based pharmacophore modeling of TNF-α to design novel inhibitors using virtual screening and molecular dynamics

Tumor necrosis factor-α (TNF-α) is one of the promising targets for treating inflammatory (Crohn disease, psoriasis, psoriatic arthritis, rheumatoid arthritis) and various other diseases. Commercially available TNF-α inhibitors are associated with several risks and limitations. In the present study, we have identified small TNF-α inhibitors using in silico approaches, namely pharmacophore modeling, virtual screening, molecular docking, molecular dynamics simulation and free binding energy calculations. The study yielded better and potent hits that bind to TNF-α with significant affinity. The best pharmacophore model generated using LigandScout has an efficient hit rate and Area Under the operating Curve. High throughput virtual screening of SPECS database molecules against crystal structure of TNF-α protein, coupled with physicochemical filtration, PAINS test. Virtual hit compounds used for molecular docking enabled the identification of 20 compounds with better binding energies when compared with previously known TNF-α inhibitors. MD simulation analysis on 20 virtual identified hits showed that ligand binding with TNF-α protein is stable and protein-ligand conformation remains unchanged. Further, 16 compounds passed ADMET analysis suggesting these identified hit compounds are suitable for designing a future class of potent TNF-α inhibitors. Communicated by Ramaswamy H. Sarma

English

Despite the multitude of studies which have shown the use of medicinal plants in the management of parasitic diseases, little data was available on the plants used against onchocerciasis. Ethnobotanical surveys were carried out among traditional healers in the Far North region of Cameroon. Studies were conducted from July 2017 to May 2018 through direct interviews using a semi-structured questionnaire taking into consideration the socio-demographic characteristics of the respondents as well as their knowledge in the art of onchocerciasis and parasitic infections treatment using plant recipes. A total of one hundred people were interviewed in villages found in the Far North region of Cameroon: 43 were females and 57 males, among which, 71 were recognized as traditional healers. Adults were the most represented (71 respondents). The study identified 96 plant species belonging to 49 genera divided into 29 families among which the most represented was the Fabaceae (20 quotes). The most represented biotope was savannah (98%) and trees (51) were the most used followed by shrub (41). The leaves (40) are the organs which are mostly demanded and the main preparation method is a decoction (69) and 36 diseases and / or symptoms related to onchocerciasis and helminthiases were recorded. The medicinal plants identified, constitute an undeniable asset and a good database for the biological screening of plant-based antiparasitic molecules, which can lead to the manufacture of improved traditional medicines. Key words: Onchocerciasis, medicinal plants, ethnobotanical surveys, filariasis, Cameroon.

1H, 13C, 15N backbone and IVL methyl group resonance assignment of the fungal \u03b2-glucosidase from Trichoderma reesei

β-glucosidases have received considerable attention due to their essential role in bioethanol production from lignocellulosic biomass. β-glucosidase can hydrolyse cellobiose in cellulose degradation and its low activity has been considered as one of the main limiting steps in the process. Large-scale conversions of cellulose therefore require high enzyme concentration which increases the cost. β-glucosidases with improved activity and thermostability are therefore of great commercial interest. The fungus Trichoderma reseei expresses thermostable cellulolytic enzymes which have been widely studied as attractive targets for industrial applications. Genetically modified β-glucosidases from Trichoderma reseei have been recently commercialised. We have developed an approach in which screening of low molecular weight molecules (fragments) identifies compounds that increase enzyme activity and are currently characterizing fragment-based activators of TrBgl2. A structural analysis of the 55 kDa apo form of TrBgl2 revealed a classical (α/β)8-TIM barrel fold. In the present study we present a partial assignment of backbone chemical shifts, along with those of the Ile (I)-Val (V)-Leu (L) methyl groups of TrBgl2. These data will be used to characterize the interaction of TrBgl2 with the small molecule activators.

A Three-Dimensional Alzheimer's Disease Cell Culture Model Using iPSC-Derived Neurons Carrying A246E Mutation in PSEN1.

Alzheimer’s disease (AD) is a chronic brain disorder characterized by progressive intellectual decline and memory and neuronal loss, caused mainly by extracellular deposition of amyloid-β (Aβ) and intracellular accumulation of hyperphosphorylated tau protein, primarily in areas implicated in memory and learning as prefrontal cortex and hippocampus. There are two forms of AD, a late-onset form that affects people over 65 years old, and the early-onset form, which is hereditable and affect people at early ages ~45 years. To date, there is no cure for the disease; consequently, it is essential to develop new tools for the study of processes implicated in the disease. Currently, in vitro AD three-dimensional (3D) models using induced pluripotent stem cells (iPSC)-derived neurons have broadened the horizon for in vitro disease modeling and gained interest for mechanistic studies and preclinical drug discovery due to their potential advantages in providing a better physiologically relevant information and more predictive data for in vivo tests. Therefore, this study aimed to establish a 3D cell culture model of AD in vitro using iPSCs carrying the A246E mutation. We generated human iPSCs from fibroblasts from a patient with AD harboring the A246E mutation in the PSEN1 gene. Cell reprogramming was performed using lentiviral vectors with Yamanaka’s factors (OSKM: Oct4, Sox2, Klf4, and c-Myc). The resulting iPSCs expressed pluripotency genes (such as Nanog and Oct4), alkaline phosphatase activity, and pluripotency stem cell marker expression, such as OCT4, SOX2, TRA-1-60, and SSEA4. iPSCs exhibited the ability to differentiate into neuronal lineage in a 3D environment through dual SMAD inhibition as confirmed by Nestin, MAP2, and Tuj1 neural marker expression. These iPSC-derived neurons harbored Aβ oligomers confirmed by Western Blot (WB) and immunostaining. With human iPSC-derived neurons able to produce Aβ oligomers, we established a novel human hydrogel-based 3D cell culture model that recapitulates Aβ aggregation without the need for mutation induction or synthetic Aβ exposure. This model will allow the study of processes implicated in disease spread throughout the brain, the screening of molecules or compounds with therapeutic potential, and the development of personalized therapeutic strategies.

Structural insights on vitamin D receptor and screening of new potent agonist molecules: structure and ligand-based approach

Vitamin D deficiency is one of the common clinical symptoms of severe chronic kidney disease (CKD) patients. Vitamin D receptor (VDR) is a part of the nuclear receptor family exerts vitamin D activation to maintain calcium/phosphorous homeostasis and bone metabolism. The reduction of VDR activity leads to vitamin D deficiency. In this study, we found three potent agonists for VDR protein on the structure and ligand-based screening methods. In the structure-based method, 792 compounds were screened. A 5-point pharmacophore (one hydrogen bond acceptor, two hydrophobic and aromatic rings (AHHRR)) was developed and used to obtain a predictive 3 D-Quantitative structure-activity relationship (QSAR), model. The acquire R2 and Q2 values are 0.8676 and 0.8523 respectively. Further, E-pharmacophore based screening, molecular docking (binding affinity), Molecular Mechanics-Generalized Born Surface Area (binding free energy), chemical reactivity (Density Functional Theory (DFT) study) and molecular dynamics (protein-ligand stability) analysis were done. Hence, the computational investigations demonstrate that the identified ligands such as TCM_1875, TCM_1874, and TCM_2868 showed promising agonist effect on VDR protein. Further validation and experiments need to be done to confirm the potency of the identified compounds shortly. Communicated by Ramaswamy H. Sarma