Targeted drug delivery to the thrombus by fusing streptokinase with a fibrin-binding peptide (CREKA): an in silico study

Aim: Streptokinase has poor selectivity and provokes the immune response. In this study, we used in silico studies to design a fusion protein to achieve targeted delivery to the thrombus. Materials & methods: Streptokinase was analyzed computationally for mapping. The fusion protein modeling and quality assessment were carried out on several servers. The enzymatic activity and the stability of the fusion protein and its complex with plasminogen were assessed through molecular docking analysis and molecular dynamics simulation respectively. Results: Physicochemical properties analysis, protein quality assessments, protein-protein docking and molecular dynamics simulations predicted that the designed fusion protein is functionally active. Conclusion: Our results showed that this fusion protein might be a prospective candidate as a novel thrombolytic agent with better selectivity.

The Potential Role of Phytochemicals of Juniperus procera in the Treatment of Ovarian Cancer and the Inhibition of Human Topoisomerase II Alpha Activity

A variety of active chemicals found in medicinal plants can be used to develop new medications with few adverse effects. In vitro and in silico analyses were used to evaluate the anticancer properties of Juniperus procera fruit and leaf extracts. Here, we show that the methanolic extract from J procera fruit and leaf extracts inhibits 2 human ovarian cancer cell lines, A2780CP and SKOV-3. The leaf extract demonstrated strong cytotoxicity against A2780CP with an IC50 of 1.2 μg/mL, almost matching the IC50 of the anticancer medication doxorubicin (0.9 μg/mL). Higher antioxidant activity was observed in the fruit than leaf extract. The molecular docking results showed that the active component, podocarpusflavone A, was the best-docked chemical with the human topoisomerase II alpha enzyme. According to our knowledge, this is the first in vitro study to show the cytotoxicity of J procera extracts against the 2 previously described human ovarian cancer cell lines. The fact that the podocarpusflavone A molecule may have an inhibitory effect on the human topoisomerase II alpha enzyme was also revealed by this first in silico analysis. Our findings imply that the J procera fruit and leaf methanolic extract has anticancer characteristics that may guide future in vivo studies.

Prediction of physicochemical and pharmacokinetic properties of botanical constituents by computational models

Botanicals contain complex mixtures of chemicals most of which lack pharmacokinetic data in humans. Since physicochemical and pharmacokinetic properties dictate the in vivo exposure of botanical constituents, these parameters greatly impact the pharmacological and toxicological effects of botanicals in consumer products. This study sought to use computational (i.e., in silico) models, including quantitative structure-activity relationships (QSAR) and physiologically based pharmacokinetic (PBPK) modeling, to predict properties of botanical constituents. One hundred and three major constituents (e.g., withanolides, mitragynine, and yohimbine) in 13 botanicals (e.g., ashwagandha, kratom, and yohimbe) were investigated. The predicted properties included biopharmaceutical classification system (BCS) classes based on aqueous solubility and permeability, oral absorption, liver microsomal clearance, oral bioavailability, and others. Over half of these constituents fell into BCS classes I and II at dose levels no greater than 100 mg per day, indicating high permeability and absorption (%Fa > 75%) in the gastrointestinal tract. However, some constituents such as glycosides in ashwagandha and Asian ginseng showed low bioavailability after oral administration due to poor absorption (BCS classes III and IV, %Fa < 40%). These in silico results fill data gaps for botanical constituents and could guide future safety studies. For example, the predicted human plasma concentrations may help select concentrations for in vitro toxicity testing. Additionally, the in silico data could be used in tiered or batteries of assays to assess the safety of botanical products. For example, highly absorbed botanical constituents indicate potential high exposure in the body, which could lead to toxic effects.

Phytochemical analysis and antioxidant potential of Mondia whitei and Guibourtia tessmannii against H2O2-induced cytotoxicity in PC3 cells

The management of oxidative stress-related disorders has garnered significant interest, particularly in the exploration of medicinal plants possessing potent antioxidant activities. This study was undertaken to evaluate the antioxidant activity of Mondia whitei (MW) and Guibourtia tessmannii (GT) against H2O2-induced cytotoxicity in PC3 cells. The phytochemical composition of MW and GT was determined by GC-MS analysis. Total phenolic (TP) and total flavonoid (TF) contents were quantified by Folin Ciocalteu and AlCl3 methods, respectively. The antioxidant potential of the extracts was determined using the DPPH and ABTS+ radicals scavenging method, as well as cupric and ferric reducing capacity assay. Moreover, all phytocompounds were docked against acetylcholinesterase (AChE) and glutathione S-transferase (GST) using ArgusLab, and results were analyzed using the BIOVIA Discovery Studio Visualizer 2021 client. MW and GT comprised 20 and 22 compounds, respectively. GT exhibited higher TP and TF contents (210.70 ± 12.7; 12.61 ± 1.3 GAE/g DW) compared to MW (132.59 ± 12.59; 5.53 ± 1.3 mg of GAE/g DW). Both MW and GT demonstrated substantial antioxidant activity, with GT proving to be more effective in preventing H2O2-induced cytotoxicity. For instance, MW and GT significantly (p < .001) increased the DPPH, ABTS+, and cupric activity, compared with the H2O2 group. All compounds identified in MW and GT exhibited a strong binding affinity against AChE and GST. Drug likeness and toxicity of all phytocompounds were under the acceptable norms of Lipinski's rule. In conclusion, these plants could be effective candidates for the management/treatment of oxidative stress-related disorders.Communicated by Ramaswamy H. Sarma.

Enzymatic Performance of Aspergillus oryzae α-Amylase in the Presence of Organic Solvents: Activity, Stability, and Bioinformatic Studies

Enzymatic reactions can be modulated by the incorporation of organic solvents, leading to alterations in enzyme stability, activity, and reaction rates. These solvents create a favorable microenvironment that enables hydrophobic reactions, facilities enzyme-substrate complex formation, and reduces undesirable water-dependent side reactions. However, it is crucial to understand the impact of organic solvents on enzymatic activity, as they can also induce enzyme inactivation. In this study, the enzymatic performance of Aspergillus oryzae α-amylase (Taka-amylase) in various organic solvents both experimentally and computationally was investigated. The results demonstrated that ethanol and ether sustain Taka-amylase activity up to 20% to 25% of the organic solvents, with ether providing twice the stability of ethanol. Molecular dynamics simulations further revealed that Taka-amylase has a more stable structure in ether and ethanol relative to other organic solvents. In addition, the analysis showed that the loop located near the active site in the AB-domain is a vulnerable site for enzyme destabilization when exposed to organic solvents. The ability of Taka-amylase to preserve the secondary loop structure in ether and ethanol contributed to the enzyme's activity. In addition, the solvent accessibility surface area of Taka-amylase is distributed throughout all enzyme structures, thereby contributing to the instability of Taka-amylase in the presence of most organic solvents.

Anti-Parkinson potential of hesperetin nanoparticles: in vivo and in silico investigations

Parkinson's disease (PD) is characterised by the gradual demise of dopaminergic neurons. In recent years, there has been significant interest in herbal treatments. In this study, hesperetin nanoparticles (HTN) were developed and compared their anti-PD potential with hesperetin (HT) on rotenone induced PD rats. Molecular docking was also performed to evaluate the binding affinity of hesperetin on pathological protein, i.e. D2 dopamine receptors (DR2), using Auto Dock Vina tools. The results showed a higher binding relationship of HTN on dopamine receptors (-7.2 kcal/mol) compared to L-dopa (-6.4 kcal/mol), supporting their potential as drug candidates for PD therapy. HTN was effectively synthesised using the fabrication technique and characterised by zeta potential and SEM analysis. HTN had favourable characteristics, including a size of 249.8 ± 14.9 nm and a Z-potential of -32.9 mV. After being administered orally, HTN demonstrated a notable anti-Parkinsonian effects, indicated by the significant improvement in motor function as assessed by the rota rod test (p < .001***), pole test (p < .001***), stair test (p < .01**), wood walk test (p < .01**) and an increase in substantia nigra (SN) antioxidant levels, CAT (p < .001***), SOD (p < .001***), GSH (p < .01**). Additionally, HTN led to increased dopamine levels (p < .01**) and a decrease in the oxidant system, MDA levels (p < .01**). Furthermore, histopathological examination revealed decreased SN neuronal necrosis in diseased animals treated with HTN compared to those treated with HT in a rat model of Parkinson's disease. Therefore, HTN can be regarded as a viable platform for efficient therapy of PD.

Prediction of Overall Disease Burden in (y)pN1 Breast Cancer Using Knowledge-Based Machine Learning Model

BACKGROUND

We aimed to construct an expert knowledge-based Bayesian network (BN) model for assessing the overall disease burden (ODB) in (y)pN1 breast cancer patients and compare ODB across arms of ongoing trials.

METHODS

Utilizing institutional data and expert surveys, we developed a BN model for (y)pN1 breast cancer. Expert-derived probabilities and disability weights for radiotherapy-related benefit (e.g., 7-year disease-free survival [DFS]) and toxicities were integrated into the model. ODB was defined as the sum of disability weights multiplied by probabilities. In silico predictions were conducted for Alliance A011202, PORT-N1, RAPCHEM, and RT-CHARM trials, comparing ODB, 7-year DFS, and side effects.

RESULTS

In the Alliance A011202 trial, 7-year DFS was 80.1% in both arms. Axillary lymph node dissection led to higher clinical lymphedema and ODB compared to sentinel lymph node biopsy with full regional nodal irradiation (RNI). In the PORT-N1 trial, the control arm (whole-breast irradiation [WBI] with RNI or post-mastectomy radiotherapy [PMRT]) had an ODB of 0.254, while the experimental arm (WBI alone or no PMRT) had an ODB of 0.255. In the RAPCHEM trial, the radiotherapy field did not impact the 7-year DFS in ypN1 patients. However, there was a mild ODB increase with a larger irradiation field. In the RT-CHARM trial, we identified factors associated with the major complication rate, which ranged from 18.3% to 22.1%.

CONCLUSIONS

The expert knowledge-based BN model predicted ongoing trial outcomes, validating reported results and assumptions. In addition, the model demonstrated the ODB in different arms, with an emphasis on quality of life.

Antioxidant potential of alkaloids and polyphenols of Viola canescens wall using in vitro and in silico approaches

Background: V. canescens Wall, a plant renowned for its ethno-medical properties, was investigated in this study for its antioxidant potential based on its wide therapeutic applications in traditional healthcare systems. The study aimed to assess the antioxidant potential of the plant extract/fractions and to predict the active phytochemicals using computational techniques. Methods: Five fractions were obtained from the crude methanolic extract of Viola canescens, and six concentrations (25, 50, 75, 100, 125, and 150 μg/mL) were prepared for each fraction. The antioxidant activity of these fractions was evaluated using the Tetraoxomolybdate (VI) and 1,1-diphenyl-2-picrylhydrazyl (DPPH) assay. In-silico docking studies and molecular dynamic simulations were conducted to further elucidate the molecular interactions underlying the antioxidant activity. Results: The aqueous extract of V. canescens exhibited significant antioxidant and free radical scavenging activity against DPPH. Additionally, the crude flavonoid extract demonstrated moderate activity with IC50 value of 57.863 μg/mL, indicating potent inhibition of cell growth. In-silico docking studies revealed a strong interaction between emetine and the aromatase protein, suggesting its potential as an antioxidant. Conclusion: The study findings highlight the antioxidant potential of V. canescens extract, indicating its suitability as a source of natural antioxidants. These results suggest its potential application in pharmaceutical preparations aimed at harnessing antioxidant properties for therapeutic purposes.

Genomic characteristics of Salmonella Montevideo and Pomona: impact of isolation source on antibiotic resistance, virulence and metabolic capacity

Salmonella enterica is known for its disease-causing serotypes, including Montevideo and Pomona. These serotypes have been found in various environments, including river water, sediments, food, and animals. However, the global spread of these serotypes has increased, leading to many reported infections and outbreaks. The goal of this study was the genomic analysis of 48 strains of S. Montevideo and S. Pomona isolated from different sources, including clinical. Results showed that environmental strains carried more antibiotic resistance genes than the clinical strains, such as genes for resistance to aminoglycosides, chloramphenicol, and sulfonamides. Additionally, the type 4 secretion system, was only found in environmental strains. .Also many phosphotransferase transport systems were identified and the presence of genes for the alternative pathway Entner-Doudoroff. The origin of isolation may have a significant impact on the ability of Salmonella isolates to adapt and survive in different environments, leading to genomic flexibility and a selection advantage.

Comprehensive evaluation of nucleic acid amplification methods widely used for generic detection of sandfly-borne phleboviruses

Sandfly-borne phleboviruses (SBPs), which cause sandfly fever, aseptic meningitis, encephalitis, and meningoencephalitis, are emerging pathogens of major public health concern. Virus nucleic acid testing is essential for SBP diagnosis, especially in the early stages of infection, and for the discovery of novel SBPs. The efficacy of utilizing generic primers that target conserved nucleotide sequences for the detection of both known and novel SBPs has not been extensively evaluated. We aimed to compare and evaluate the performance of five generic primer sets, widely used to detect S- and L-segments of arthropod-borne phleboviruses and designed as singleplex (n = 3) and nested (n = 2) formats, including both well-known and recently characterized 15 Old World virus strains. Furthermore, we performed in silico analysis to assess the detection capabilities of these generic primer sets. The initial evaluation of previously published generic primer sets for SBP detection yielded two singleplex primer sets with the potential to be adapted for use in real-time or high-throughput detection settings. Studies are ongoing to develop and further optimize a preliminary assay and test various hosts and vectors to assess their capacity to detect known and novel viruses.

IMPORTANCE

Virus nucleic acid testing is the primary diagnostic method, particularly in the early stages of illness. Virus-specific or syndromic tests are widely used for this purpose. The use of generic primers has had a considerable impact on the discovery, identification, and detection of Old World sandfly-borne phleboviruses (OWSBP). The study is significant because it is the first to carry out a comparative evaluation of all published OWSBP generic primer sets.

OptiMo-LDLr: An Integrated In Silico Model with Enhanced Predictive Power for LDL Receptor Variants, Unraveling Hot Spot Pathogenic Residues

Familial hypercholesterolemia (FH) is an inherited metabolic disease affecting cholesterol metabolism, with 90% of cases caused by mutations in the LDL receptor gene (LDLR), primarily missense mutations. This study aims to integrate six commonly used predictive software to create a new model for predicting LDLR mutation pathogenicity and mapping hot spot residues. Six predictive-software are selected: Polyphen-2, SIFT, MutationTaster, REVEL, VARITY, and MLb-LDLr. Software accuracy is tested with the characterized variants annotated in ClinVar and, by bioinformatic and machine learning techniques all models are integrated into a more accurate one. The resulting optimized model presents a specificity of 96.71% and a sensitivity of 98.36%. Hot spot residues with high potential of pathogenicity appear across all domains except for the signal peptide and the O-linked domain. In addition, translating this information into 3D structure of the LDLr highlights potentially pathogenic clusters within the different domains, which may be related to specific biological function. The results of this work provide a powerful tool to classify LDLR pathogenic variants. Moreover, an open-access guide user interface (OptiMo-LDLr) is provided to the scientific community. This study shows that combination of several predictive software results in a more accurate prediction to help clinicians in FH diagnosis.

In Vitro Human Dermal Absorption Studies on Pesticides in Complex Mixtures: Investigation of Guidance Criteria and Possible Impact Parameters

Pesticides must not pose unacceptable risks to human health, so risk assessments are conducted before products are authorised. Dermal exposure is often the main route of intake, so estimating realistic and trustworthy dermal absorption values is crucial for risk assessment. Although there are agreed test guidelines for in vitro dermal absorption studies, not every product is tested due to cost reasons. The present dataset consists of 945 individual in vitro experiments on the dermal absorption of human skin with 179 active substances of pesticides in 353 different mixtures, including concentrates and dilutions. The dataset was evaluated to identify the possible impacts of experimental conditions and physico-chemical properties on dermal absorption. The dataset was also analysed to assess the appropriateness of the pro rata correction for untested dilutions, and the set concentration cut-off to decide on the dilution status for choosing a default value on dermal absorption. The study found that the implementation of specific guidelines improved the harmonisation of study conduct, with support for approaches such as pro rata correction and default values. Further analysis of the specific co-formulants may identify influencing factors that may be more important than the experimental variables.

BEERS2: RNA-Seq simulation through high fidelity in silico modeling

Simulation of RNA-seq reads is critical in the assessment, comparison, benchmarking and development of bioinformatics tools. Yet the field of RNA-seq simulators has progressed little in the last decade. To address this need we have developed BEERS2, which combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline. BEERS2 takes input transcripts (typically fully length messenger RNA transcripts with polyA tails) from either customizable input or from CAMPAREE simulated RNA samples. It produces realistic reads of these transcripts as FASTQ, SAM or BAM formats with the SAM or BAM formats containing the true alignment to the reference genome. It also produces true transcript-level quantification values. BEERS2 combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline and is designed to include the effects of polyA selection and RiboZero for ribosomal depletion, hexamer priming sequence biases, GC-content biases in polymerase chain reaction (PCR) amplification, barcode read errors and errors during PCR amplification. These characteristics combine to make BEERS2 the most complete simulation of RNA-seq to date. Finally, we demonstrate the use of BEERS2 by measuring the effect of several settings on the popular Salmon pseudoalignment algorithm.

In situtumor model for longitudinal in silico imaging trials

Objective.In this article, we introduce a computational model for simulating the growth of breast cancer lesions accounting for the stiffness of surrounding anatomical structures.Approach.In our model, ligaments are classified as the most rigid structures while the softer parts of the breast are occupied by fat and glandular tissues As a result of these variations in tissue elasticity, the rapidly proliferating tumor cells are met with differential resistance. It is found that these cells are likely to circumvent stiffer terrains such as ligaments, instead electing to proliferate preferentially within the more yielding confines of the breast's soft topography. By manipulating the interstitial tumor pressure in direct proportion to the elastic constants of the tissues surrounding the tumor, this model thus creates the potential for realizing a database of unique lesion morphology sculpted by the distinctive topography of each local anatomical infrastructure. We modeled the growth of simulated lesions within volumes extracted from fatty breast models, developed by Graffet alwith a resolution of 50μm generated with the open-source and readily available Virtual Imaging Clinical Trials for Regulatory Evaluation (VICTRE) imaging pipeline. To visualize and validate the realism of the lesion models, we leveraged the imaging component of the VICTRE pipeline, which replicates the siemens mammomat inspiration mammography system in a digital format. This system was instrumental in generating digital mammogram (DM) images for each breast model containing the simulated lesions.Results.By utilizing the DM images, we were able to effectively illustrate the imaging characteristics of the lesions as they integrated with the anatomical backgrounds. Our research also involved a reader study that compared 25 simulated DM regions of interest (ROIs) with inserted lesions from our models with DM ROIs from the DDSM dataset containing real manifestations of breast cancer. In general the simulation time for the lesions was approximately 2.5 hours, but it varied depending on the lesion's local environment.Significance.The lesion growth model will facilitate and enhance longitudinal in silico trials investigating the progression of breast cancer.

Novel strategies for drug repurposing

Synthetic biology, precision medicine, and nanobiotechnology are the three main emerging areas that drive translational innovation toward commercialization. There are several strategies used in precision medicine and drug repurposing is one of the key approaches as it addresses the challenges in drug discovery (high cost and time). Here, we provide a perspective on various new approaches to drug repurposing for cancer precision medicine. We report here our optimized wound healing methodology that can be used to validate drug sensitivity and drug repurposing. Using HeLa as our benchmark, we demonstrated that the assay can be applied to identify drugs that limit cell proliferation. From a future perspective, this assay can be expanded to ex vivo culturing of solid tumors in 2D culture and leukemia in 3D culture.

Influence of posterior cruciate ligament tension on tibiofemoral and patellofemoral joint contact mechanics in cruciate-retaining total knee replacement: a combined musculoskeletal multibody and finite-element simulation

The influence of posterior cruciate ligament (PCL) tension on the clinical outcome of cruciate-retaining total knee replacement (CR-TKR) remains controversial. Various numerical approaches have been used to study this influence systematically, but the models used are limited by certain assumptions and simplifications. Therefore, the objective of this computational study was to develop a combined musculoskeletal multibody and finite-element simulation during a squat motion to 90° knee flexion with a CR-TKR design to overcome previous limitations regarding model inputs. In addition, different PCL tensions (tight, lax, resected) were modeled and the influence on tibiofemoral and resurfaced patellofemoral joint dynamics and contact stresses was evaluated. The effect of the PCL on knee joint dynamics and contact stresses was more pronounced at higher flexion angles. Tibiofemoral joint dynamics were influenced and a tight PCL induced increased posterior femoral translation during flexion. The maximum contact stress in the tibial insert increased from 20.6 MPa to 22.5 MPa for the resected and tightest PCL at 90° knee flexion. Patellofemoral joint dynamics were only slightly affected by PCL tension. However, the maximum contact stress in the patellar component decreased from 58.0 MPa to 53.7 MPa for the resected and tightest PCL at 90° knee flexion. The combination of musculoskeletal multibody and finite-element simulation is a sufficient method to comprehensively investigate knee joint dynamics and contact stresses in CR-TKR. The PCL tension after CR-TKR affects joint dynamics and contact stresses at the articulating implant surfaces.

A novel method to derive a human safety limit for PFOA by gene expression profiling and modelling

Perfluorooctanoic acid (PFOA) is a persistent environmental contaminant that can accumulate in the human body due to its long half-life. This substance has been associated with liver, pancreatic, testicular and breast cancers, liver steatosis and endocrine disruption. PFOA is a member of a large group of substances also known as "forever chemicals" and the vast majority of substances of this group lack toxicological data that would enable their effective risk assessment in terms of human health hazards. This study aimed to derive a health-based guidance value for PFOA intake (ng/kg BW/day) from in vitro transcriptomics data. To this end, we developed an in silico workflow comprising five components: (i) sourcing in vitro hepatic transcriptomics concentration-response data; (ii) deriving molecular points of departure using BMDExpress3 and performing pathway analysis using gene set enrichment analysis (GSEA) to identify the most sensitive molecular pathways to PFOA exposure; (iii) estimating freely-dissolved PFOA concentrations in vitro using a mass balance model; (iv) estimating in vivo doses by reverse dosimetry using a PBK model for PFOA as part of a quantitative in vitro to in vivo extrapolation (QIVIVE) algorithm; and (v) calculating a tolerable daily intake (TDI) for PFOA. Fourteen percent of interrogated genes exhibited in vitro concentration-response relationships. GSEA pathway enrichment analysis revealed that "fatty acid metabolism" was the most sensitive pathway to PFOA exposure. In vitro free PFOA concentrations were calculated to be 2.9% of the nominal applied concentrations, and these free concentrations were input into the QIVIVE workflow. Exposure doses for a virtual population of 3,000 individuals were estimated, from which a TDI of 0.15 ng/kg BW/day for PFOA was calculated using the benchmark dose modelling software, PROAST. This TDI is comparable to previously published values of 1.16, 0.69, and 0.86 ng/kg BW/day by the European Food Safety Authority. In conclusion, this study demonstrates the combined utility of an "omics"-derived molecular point of departure and in silico QIVIVE workflow for setting health-based guidance values in anticipation of the acceptance of in vitro concentration-response molecular measurements in chemical risk assessment.

Preparation, identification, and molecular docking of novel angiotensin-converting enzyme inhibitory peptides derived from rice-based distillers' spent cakes

BACKGROUND

Rice-based distillers' spent cake (RDSC), a by-product of the Chinese liquor (Baijiu) industry, is a potential source of ACE inhibitory peptide. Since angiotensin-converting enzyme (ACE) plays a crucial role in controlling hypertension, inhibition of ACE has been widely emphasized. The ACE inhibitory active peptide derived from by-products of food has been recognized as safer and cheaper inhibitors.

RESULTS

Aimed to discover ACE-inhibiting active peptides in RDSC. Hydrolysis of RDSC by alcalase for 4 h followed by ultrafiltration yielded low-molecular-weight (< 3 kDa) fractions. Subsequently, a comprehensive method that using a combination of LC-Q-TOF-MS and LC-Q Exactive-MS to identify the novel short- (3-5 amino acids residues; n = 7) and medium-sized peptides (more than 6 amino acids residues; n = 6). In vitro activity assay showed that the peptides KPFFPGL, GFPRPLL, GPPGVF, and VGK exhibited the highest activity with IC50 of 11.63, 12.34, 19.55, and 33.54 μM. Molecular docking reveal that the active and inactive sites (Glu123, Asp121, Arg522, and Lys118) play important roles in enhancing the ACE inhibitory activity of peptides.

CONCLUSION

Here we report a comprehensive method that effectively extracted and identified the bioactive peptides from RDSC. Four highly active novel peptides may be the most promising candidates for functional foods to against hypertension, provide significant information for enhancing value of rice-based distilled by-products. This article is protected by copyright. All rights reserved.

Enhancing the Catalytic Efficiency of D-lactonohydrolase through the Synergy of Tunnel Engineering, Evolutionary Analysis, and Force-Field Calculations

Computational design advances enzyme evolution and their use in biocatalysis in a faster and more efficient manner. In this study, a synergistic approach integrating tunnel engineering, evolutionary analysis, and force-field calculations has been employed to enhance the catalytic activity of D-lactonohydrolase (D-Lac), which is a pivotal enzyme involved in the resolution of racemic pantolactone during the production of vitamin B5. The best mutant, N96S/A271E/F274Y/F308G (M3), was obtained and its catalytic efficiency (kcat/KM) was nearly 23-fold higher than that of the wild-type. The M3 whole-cell converted 20 % of DL-pantolactone into D-pantoic acid (D-PA, >99 % e.e.) with a conversion rate of 47 % and space-time yield of 107.1 g L-1 h-1, demonstrating its great potential for industrial-scale D-pantothenic acid production. Molecular dynamics (MD) simulations revealed that the reduction in the steric hindrance within the substrate tunnel and conformational reconstruction of the distal loop resulted in a more favourable"catalytic" conformation, making it easier for the substrate and enzyme to enter their pre-reaction state. This study illustrates the potential of the distal residue on the pivotal loop at the entrance of the D-Lac substrate tunnel as a novel modification hotspot capable of reshaping energy patterns and consequently influencing the enzymatic activity.

SKping cell cycle regulation: role of ubiquitin ligase SKP2 in hematological malignancies

SKP2 (S-phase kinase-associated protein 2) is a member of the F-box family of substrate-recognition subunits in the SCF ubiquitin-protein ligase complexes. It is associated with ubiquitin-mediated degradation in the mammalian cell cycle components and other target proteins involved in cell cycle progression, signal transduction, and transcription. Being an oncogene in solid tumors and hematological malignancies, it is frequently associated with drug resistance and poor disease outcomes. In the current review, we discussed the novel role of SKP2 in different hematological malignancies. Further, we performed a limited in-silico analysis to establish the involvement of SKP2 in a few publicly available cancer datasets. Interestingly, our study identified Skp2 expression to be altered in a cancer-specific manner. While it was found to be overexpressed in several cancer types, few cancer showed a down-regulation in SKP2. Our review provides evidence for developing novel SKP2 inhibitors in hematological malignancies. We also investigated the effect of SKP2 status on survival and disease progression. In addition, the role of miRNA and its associated families in regulating Skp2 expression was explored. Subsequently, we predicted common miRNAs against Skp2 genes by using miRNA-predication tools. Finally, we discussed current approaches and future prospective approaches to target the Skp2 gene by using different drugs and miRNA-based therapeutics applications in translational research.

IL-18 and CD14 variants in chronic HBV predisposition: a case-control study with in silico analyses focused on transcription and splicing

Hepatitis B virus (HBV), a vaccine-avoidable infection, is a health concern worldwide, leading to liver disorders such as acute self-constraint and chronic hepatitis, liver failure, hepatic cirrhosis, and even hepatocellular carcinoma if untreated. 'Immunogeneticprofiling', genetic variations of the pro- and anti-inflammatory cytokines responsible for regulating the immune responses, cause person-to-person differences and impact the clinical manifestation of the disease. The current experimental-bioinformatics research was conducted to examine whether promoteric IL-18-rs187238 C > G and -rs1946518 T > G and intronic CD14-rs2569190 A > G variations are associated with chronic HBV. A total of 400 individuals (200 in each case and control group) participated in the study and were genotyped using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique. The data was also assessed bioinformatics-wise for conservation, genomic transcription and splicing, and protein interactions. Findings proposed that unlike the IL-18-rs1946518 T > G and CD14-rs2569190 A > G, the IL-18-rs187238 C > G is a protector against chronic HBV (odds ratio [OR] = 0.62, 95% confidence intervals [CI]: 0.46-0.83, and p = 0.002). The TG/CC/AA, TG/CC/AG, TT/CC/AG, and GG/CC/AA combined genotypes significantly increased chronic HBV risk (p < 0.05), while the IL-18 G/T and G/G haplotypes lessened it (p < 0.05). Moreover, IL-18-rs1946518 T > G is in the protected genomic regions across mammalian species. In contrast to the IL-18-rs1946518 T > G, IL-18-rs187238 C > G is likely to create novel binding sites for transcription factors, and the CD14-rs2569190 A > G presumably changed the ribonucleic acid splicing pattern. More research on larger populations and other ethnicities is required to authenticate these results.

Integrating network pharmacology with molecular docking to rationalize the ethnomedicinal use of Alchornea laxiflora (Benth.) Pax & K. Hoffm. for efficient treatment of depression

Background: Alchornea laxiflora (Benth.) Pax & K. Hoffm. (A. laxiflora) has been indicated in traditional medicine to treat depression. However, scientific rationalization is still lacking. Hence, this study aimed to investigate the antidepressant potential of A. laxiflora using network pharmacology and molecular docking analysis. Materials and methods: The active compounds and potential targets of A. laxiflora and depression-related targets were retrieved from public databases, such as PubMed, PubChem, DisGeNET, GeneCards, OMIM, SwissTargetprediction, BindingDB, STRING, and DAVID. Essential bioactive compounds, potential targets, and signaling pathways were predicted using in silico analysis, including BA-TAR, PPI, BA-TAR-PATH network construction, and GO and KEGG pathway enrichment analysis. Later on, with molecular docking analysis, the interaction of essential bioactive compounds of A. laxiflora and predicted core targets of depression were verified. Results: The network pharmacology approach identified 15 active compounds, a total of 219 compound-related targets, and 14,574 depression-related targets with 200 intersecting targets between them. SRC, EGFR, PIK3R1, AKT1, and MAPK1 were the core targets, whereas 3-acetyloleanolic acid and 3-acetylursolic acid were the most active compounds of A. laxiflora with anti-depressant potential. GO functional enrichment analysis revealed 129 GO terms, including 82 biological processes, 14 cellular components, and 34 molecular function terms. KEGG pathway enrichment analysis yielded significantly enriched 108 signaling pathways. Out of them, PI3K-Akt and MAPK signaling pathways might have a key role in treating depression. Molecular docking analysis results exhibited that core targets of depression, such as SRC, EGFR, PIK3R1, AKT1, and MAPK1, bind stably with the analyzed bioactive compounds of A. laxiflora. Conclusion: The present study elucidates the bioactive compounds, potential targets, and pertinent mechanism of action of A. laxiflora in treating depression. A. laxiflora might exert an antidepressant effect by regulating PI3K-Akt and MAPK signaling pathways. However, further investigations are required to validate.

Biodirected Screening and Preparation of Larimichthys crocea Angiotensin-I-Converting Enzyme-Inhibitory Peptides by a Combined In Vitro and In Silico Approach

Food-derived angiotensin-I-converting enzyme (ACE)-inhibitory peptides have gained attention for their potent and safe treatment of hypertensive disorders. However, there are some limitations of conventional methods for preparing ACE-inhibitory peptides. In this study, in silico hydrolysis, the quantitative structure-activity relationship (QSAR) model, LC-MS/MS, inhibition kinetics, and molecular docking were used to investigate the stability, hydrolyzability, in vitro activity, and inhibition mechanism of bioactive peptides during the actual hydrolysis process. Six novel ACE-inhibitory peptides were screened from the Larimichthys crocea protein (LCP) and had low IC50 values (from 0.63 ± 0.09 µM to 10.26 ± 0.21 µM), which were close to the results of the QSAR model. After in vitro gastrointestinal simulated digestion activity of IPYADFK, FYEPFM and NWPWMK were found to remain almost unchanged, whereas LYDHLGK, INEMLDTK, and IHFGTTGK were affected by gastrointestinal digestion. Meanwhile, the inhibition kinetics and molecular docking results were consistent in that ACE-inhibitory peptides of different inhibition forms could effectively bind to the active or non-central active centers of ACE through hydrogen bonding. Our proposed method has better reproducibility, accuracy, and higher directivity than previous methods. This study can provide new approaches for the deep processing, identification, and preparation of Larimichthys crocea.

Phytochemical profiling of the essential oils from three Curcuma species and their in vitro and in silico dengue protease inhibition activity

The chemical compositions, in vitro and in silico anti-dengue activity of the essential oils of the rhizomes of Curcuma longa Linn., C. aeruginosa Roxb., and C. xanthorrhiza Roxb. had been investigated. The C. longa oil was mainly composed of ar-turmerone (54.0%) and curlone (17.7%), while the C. aeruginosa oil was rich in curzerenone (23.4%), 1,8-cineole (21.2%), and camphor (7.1%). Xanthorrhizol (21.6%), β-curcumene (19.5%), ar-curcumene (14.2%), and camphor (9.2%) were the major compounds in the C. xanthorrhiza oil. Among the oils, the C. longa oil was found to be the most active NSB-NS3 protease inhibitor (IC50 1.98 μg/mL). PLS biplot disclosed that the essential oils were classified into three separated clusters based on their characteristic chemical compositions, with C. longa positioned closest to the in vitro anti-dengue activity. Four compounds from the C. longa oil have both hydrogen and hydrophobic bonds that could be responsible for the DENV-2 NS2B-NS3 inhibitory effect.

Synthesis, in silico screening, and biological evaluation of novel pyridine congeners as anti-epileptic agents targeting AMPA (α-amino-3-hydroxy-5-methylisoxazole) receptors

The research involves the synthesis of a series of new pyridine analogs 5(i-x) and their evaluation for anti-epileptic potential using in silico and in vivo models. Synthesis of the compounds was accomplished by using the Vilsmeier-Haack reaction principle. AutoDock 4.2 was used for their in silico screening against AMPA (-amino-3-hydroxy-5-methylisoxazole) receptor (PDB ID:3m3f). For in vivo testing, the maximal electroshock seizure (MES) model was used. The physicochemical, pharmacokinetic, drug-like, and drug-score features of all synthesized compounds were assessed using the online Swiss ADME and Protein Plus software. The in silico results showed that all the synthesized compounds 5(i-x) had 1-3 interactions and affinities ranging from -6.5 to -8.0 kJ/mol with the targeted receptor compared to the binding affinities of the standard drug phenytoin and the original ligand of the target (P99), which were -7.6 and -6.8 kJ/mol, respectively. In vivo study results showed that the compound 5-Carbamoyl-2-formyl-1-[2-(4-nitrophenyl)-2-oxo-ethyl]-pyridinium gave 60% protection against epileptic seizures compared to 59% protection afforded by regular phenytoin. All of them met Lipinski's rule of five and had drug-likeness and drug score values of 0.55 and 0.8, respectively, making them chemically and functionally like phenytoin. According to the findings of the studies, the synthesized derivatives have the potential to be employed as a stepping stone in the development of novel anti-epileptic drugs.