Salsoline derivatives, genistein, semisynthetic derivative of kojic acid, and naringenin as inhibitors of A42R profilin-like protein of monkeypox virus: in silico studies.

Monkeypox virus (MPV) infection has developed into a re-emerging disease, and despite the potential of tecovirimat and cidofovir drugs, there is currently no conclusive treatment. The treatment's effectiveness and cost challenges motivate us to use In Silico approaches to seek natural compounds as candidate antiviral inhibitors. Using Maestro 11.5 in Schrodinger suite 2018, available natural molecules with validated chemical structures collected from Eximed Laboratory were subjected to molecular docking and ADMET analysis against the highly conserved A42R Profilin-like Protein of Monkeypox Virus Zaire-96-I-16 (PDB: 4QWO) with resolution of 1.52 Å solved 3D structure. Compared to the FDA-approved Tecovirimat, molecular docking revealed that Salsoline derivatives, Genistein, Semisynthetic derivative of kojic acid, and Naringenin had strengthened affinity (-8.9 to -10 kcal/mol) to 4QWO, and the molecular dynamic's simulation confirmed their high binding stability. In support of these results, the hydrogen bond analysis indicated that the Salsoline derivative had the most robust interaction with the binding pockets of 4QWO among the four molecules. Moreover, the comparative free energy analyses using MM-PBSA revealed an average binding free energy of the complexes of Salsoline derivative, Genistein, Semisynthetic derivative of kojic acid, Naringenin, of -106.418, -46.808, -50.770, and -63.319 kJ/mol, respectively which are lower than -33.855 kJ/mol of the Tecovirimat complex. Interestingly, these results and the ADMET predictions suggest that the four compounds are promising inhibitors of 4QWO, which agrees with previous results showing their antiviral activities against other viruses.

QSAR, ADMET, molecular docking, and dynamics studies of 1,2,4-triazine-3(2H)-one derivatives as tubulin inhibitors for breast cancer therapy.

Breast cancer remains a leading cause of cancer-related deaths among women globally, necessitating the development of more effective therapeutic agents with minimal side effects. This study explores novel 1,2,4-triazine-3(2H)-one derivatives as potential inhibitors of Tubulin, a pivotal protein in cancer cell division, highlighting a targeted approach in cancer therapy. Using an integrated computational approach, we combined quantitative structure-activity relationship (QSAR) modeling, ADMET profiling, molecular docking, and molecular dynamics simulations to evaluate and predict the efficacy and stability of these compounds. Our QSAR models, developed through rigorous statistical analysis, revealed that descriptors such as absolute electronegativity and water solubility significantly influence inhibitory activity, achieving a predictive accuracy (R2) of 0.849. Molecular docking studies identified compounds with high binding affinities, particularly Pred28, which exhibited the best docking score of - 9.6 kcal/mol. Molecular dynamics simulations conducted over 100 ns provided further insights into the stability of these interactions. Pred28 demonstrated notable stability, with the lowest root mean square deviation (RMSD) of 0.29 nm and root mean square fluctuation (RMSF) values indicative of a tightly bound conformation to Tubulin. The novelty of this work lies in its methodological rigor and the integration of multiple advanced computational techniques to pinpoint compounds with promising therapeutic potential. Our findings advance the current understanding of Tubulin inhibitors and open avenues for the synthesis and experimental validation of these compounds, aiming to offer new solutions for breast cancer treatment.

Meta-analysis of MTHFR C677T polymorphism and type 2 diabetes mellitus in MENA region.

BACKGROUND AND AIMS: The association of the C677T polymorphism of the Methylenetetrahydrofolate Reductase (MTHFR) gene with susceptibility to type 2 diabetes mellitus (T2DM) has been widely debated. Therefore, our aim is to conclusively resolve this controversy in the Middle East and North Africa region population through a meta-analysis. MATERIEL AND METHODS: We identified relevant articles by searching literature databases, such as PubMed, Web of Science, and Science Direct, to retrieve studies that examined the association between the MTHFR C677T polymorphism and the risk of developing T2DM. Using meta-analysis, we calculated the odds ratio (OR) and confidence interval (CI) values of these studies to assess the susceptibility to T2DM related to the C677T polymorphism of MTHFR gene. RESULTS: In this meta-analysis, we included a total of 13 publications comprising 2072 T2DM patients and 2164 control subjects. The results of the meta-analysis suggested that there is a significant association between the C677T polymorphism and T2DM risk in overall comparisons for allele contrasts (T vs C): OR = 1.25, 95% CI = 1.04-1.50, p = 0.015 and homozygous (TT vs CC): OR = 1.44, 95% CI = 1.01-2.05, p = 0.038). Subgroup analysis revealed that the C677T polymorphism is associated with a risk of T2DM in Asian populations, while there is no significant association between this polymorphism and T2DM in Caucasian and African populations. Furthermore, there was no evidence of publication bias. CONCLUSION: Our study's results suggest that the allele contrast of the C677T polymorphism of the MTHFR gene is associated with an increased risk of T2DM in the overall population, particularly among Asians.

Potent VEGFR-2 inhibitors for resistant breast cancer: a comprehensive 3D-QSAR, ADMET, molecular docking and MMPBSA calculation on triazolopyrazine derivatives.

More people are being diagnosed with resistant breast cancer, increasing the urgency of developing new effective treatments. Several lines of evidence suggest that blocking the kinase activity of VEGFR-2 reduces angiogenesis and slows tumor growth. In this study, we developed novel VEGFR-2 inhibitors based on the triazolopyrazine template by using comparative molecular field analysis (CoMFA) and molecular similarity indices (CoMSIA) models for 3D-QSAR analysis of 23 triazolopyrazine-based compounds against breast cancer cell lines (MCF -7). Both CoMFA (Q2 = 0.575; R 2 = 0.936, Rpred 2 = 0.956) and CoMSIA/SE (Q2 = 0.575; R 2 = 0.936, Rpred 2 = 0.847) results demonstrate the robustness and stability of the constructed model. Six novel compounds with potent inhibitory activity were carefully designed, and screening of ADMET properties revealed their good oral bioavailability and ability to diffuse through various biological barriers. When compared with the most active molecule in the data set and with Foretinib (breast cancer drug), molecular docking revealed that the six designed compounds had strengthened affinity (-8.9 to -10 kcal/mol) to VEGFR-2. Molecular Dynamics Simulations and MMPBSA calculations were applied to the selected compound T01 with the highest predicted inhibitory activity, confirming its stability in the active pocket of VEGFR-2 over 100 ns. The present results provided the basis for the chemical synthesis of new compounds with improved inhibitory properties against the breast cancer cell line (MCF -7).

Exploring microbial worlds: a review of whole genome sequencing and its application in characterizing the microbial communities.

The classical microbiology techniques have inherent limitations in unraveling the complexity of microbial communities, necessitating the pivotal role of sequencing in studying the diversity of microbial communities. Whole genome sequencing (WGS) enables researchers to uncover the metabolic capabilities of the microbial community, providing valuable insights into the microbiome. Herein, we present an overview of the rapid advancements achieved thus far in the use of WGS in microbiome research. There was an upsurge in publications, particularly in 2021 and 2022 with the United States, China, and India leading the metagenomics research landscape. The Illumina platform has emerged as the widely adopted sequencing technology, whereas a significant focus of metagenomics has been on understanding the relationship between the gut microbiome and human health where distinct bacterial species have been linked to various diseases. Additionally, studies have explored the impact of human activities on microbial communities, including the potential spread of pathogenic bacteria and antimicrobial resistance genes in different ecosystems. Furthermore, WGS is used in investigating the microbiome of various animal species and plant tissues such as the rhizosphere microbiome. Overall, this review reflects the importance of WGS in metagenomics studies and underscores its remarkable power in illuminating the variety and intricacy of the microbiome in different environments.

Therapeutic efficacy of ß-sitosterol treatment on Trypanosoma congolense infection, anemia development, and trans-sialidase (TconTS1) gene expression.

Background: African animal trypanosomiasis hinders sustainable livestock productivity in sub-Saharan Africa. About 17 million infected cattle are treated with trypanocides annually but most of the drugs are associated with drawbacks, necessitating the search for a promising chemotherapeutic agent. Objectives: In this study, the effects of ß-sitosterol on Trypanosoma congolense infection were investigated along with its effect on the trans-sialidase gene expressions. Results: Oral treatment with ß-sitosterol at 15 and 30 mg/kg body weight (BW) for 14 days significantly (p < 0.05) reduced parasitemia and ameliorated the parasite-induced anemia. Also, the parasite-induced increase in serum urea level and renal histopathological damage scores in addition to renal hypertrophy was significantly (p < 0.05) reverted following treatment with 30 mg/kg BW ß-sitosterol. The compound also significantly (p < 0.05) down-regulated the expression of TconTS1 but not TconTS2, TconTS3, and TconTS4. Correlation analysis between free serum sialic acid with the TconTS1 and TconTS2 gene variants revealed negative correlations in the ß-sitosterol-treated groups although they were non-significant (p > 0.05) in the group treated with 15 mg/kg BW ß-sitosterol. Similarly, a non-significant negative (p > 0.05) correlation between the biomolecule and the TconTS3 and TconTS4 gene variants was observed in the ß-sitosterol-treated groups while positive correlations were observed in the infected untreated control group. Conclusion: The observed effect of ß-sitosterol on T. congolense infection could make the compound a possible template for the design of novel trypanocides.

Unleashing Nature's potential: a computational approach to discovering novel VEGFR-2 inhibitors from African natural compound using virtual screening, ADMET analysis, molecular dynamics, and MMPBSA calculations.

One of the characteristic features of cancer is angiogenesis, the process by which new, aberrant blood vessels are formed from pre-existing blood vessels. The process of angiogenesis begins when VEGF binds to its receptor, the VEGF receptor (VEGFR). The formation of new blood vessels provides nutrients that can promote the growth of cancer cells. When it comes to new blood vessel formation, VEGFR2 is a critical player. Therefore, inhibiting VEGFR2 is an effective way to target angiogenesis in cancer treatment. The aim of our research was to find new VEGFR-2 inhibitors by performing a virtual screening of 13313 from African natural compounds using different in silico techniques. Using molecular docking calculations and ADMET properties, we identified four compounds that exhibited a binding affinity ranging from -11.0 kcal/mol to -11.5 Kcal/mol when bound to VEGFR-2. These four compounds were further analyzed with 100 ns simulations to determine their stability and binding energy using the MM-PBSA method. After comparing the compounds with Regorafenib, a drug approved for anti-angiogenesis treatment, it was found that all the candidates (EANPDB 252, NANPDB 4577, and NANPDB 4580), with the exception of EANPDB 76, could target VEGFR-2 similarly effectively to Regorafenib. Therefore, we recommend three of these agents for anti-angiogenesis treatment because they are likely to deactivate VEGFR-2 and thus inhibit angiogenesis. However, it should be noted that the safety and suitability of these agents for clinical use needs further investigation, as the computer-assisted study did not include in vitro or in vivo experiments.

A bibliometric analysis of the global impact of metaproteomics research.

Background: Metaproteomics is a subfield in meta-omics that is used to characterize the proteome of a microbial community. Despite its importance and the plethora of publications in different research area, scientists struggle to fully comprehend its functional impact on the study of microbiomes. In this study, bibliometric analyses are used to evaluate the current state of metaproteomic research globally as well as evaluate the specific contribution of Africa to this burgeoning research area. In this study, we use bibliometric analyses to evaluate the current state of metaproteomic research globally, identify research frontiers and hotspots, and further predict future trends in metaproteomics. The specific contribution of Africa to this research area was evaluated. Methods: Relevant documents from 2004 to 2022 were extracted from the Scopus database. The documents were subjected to bibliometric analyses and visualization using VOS viewer and Biblioshiny package in R. Factors such as the trends in publication, country and institutional cooperation networks, leading scientific journals, author's productivity, and keywords analyses were conducted. The African publications were ranked using Field-Weighted Citation Impact (FWCI) scores. Results: A total of 1,138 documents were included and the number of publications increased drastically from 2004 to 2022 with more publications (170) reported in 2021. In terms of publishers, Frontiers in Microbiology had the highest number of total publications (62). The United States of America (USA), Germany, China, and Canada, together with other European countries were the most productive. Institution-wise, the Helmholtz Zentrum für Umweltforschung, Germany had more publications while Max Plank Institute had the highest total collaborative link strength. Jehmlich N. was the most productive author whereas Hettich RL had the highest h-index of 63. Regarding Africa, only 2.2% of the overall publications were from the continent with more publication outputs from South Africa. More than half of the publications from the continent had an FWCI score ≥ 1. Conclusion: The scientific outputs of metaproteomics are rapidly evolving with developed countries leading the way. Although Africa showed prospects for future progress, this could only be accelerated by providing funding, increased collaborations, and mentorship programs.

Multi-combined QSAR, molecular docking, molecular dynamics simulation, and ADMET of Flavonoid derivatives as potent cholinesterase inhibitors.

In searching for a new and efficient therapeutic agent against Alzheimer's disease, a Quantitative structure-activity relationship (QSAR) was derived for 45 Flavonoid derivatives recently synthesized and evaluated as cholinesterase inhibitors. The multiple linear regression method (MLR) was adopted to develop an adequate mathematical model that describes the relationship between a variety of molecular descriptors of the studied compounds and their biological activities (cholinesterase inhibitors). Golbraikh and Tropsha criteria were applied to verify the validity of the built model. The built MLR model was statistically reliable, robust, and predictive (R2 = 0.801, Q2cv = 0.876, R2test = 0.824). Dreiding energy and Molar Refractivity were the major factors that govern the Anti-cholinesterase activity. These results were further exploited to design a new series of Flavonoid derivatives with higher Anti-cholinesterase activities than the existing ones. Thereafter, molecular docking and molecular dynamic studies were performed to predict the binding types of the designed compounds and to investigate their stability at the active site of the Butyrylcholinestérase BuChE protein. The negative and low binding affinity calculated for all designed compounds shows that designed compound 1 has a favorable affinity for the 4TPK. Moreover, molecular dynamics simulation studies confirmed the stability of designed compound 1 in the active pocket of 4TPK over 100 ns. Finally, the ADMET analysis was incorporated to analyze the pharmacokinetics and toxicity parameters. The designed compounds were found to meet the ADMET descriptor criteria at an acceptable level having respectable intestinal permeability and water solubility and can reach the intended destinations.Communicated by Ramaswamy H. Sarma.

In silico design of novel CDK2 inhibitors through QSAR, ADMET, molecular docking and molecular dynamics simulation studies.

The present study aims to investigate about the quantitative structure-activity relationship (QSAR) of a series of Thiazole derivatives reported as anticancer agents (hepatocellular carcinoma), using principally the electronic descriptors calculated by the DFT method and by applying the multiple linear regression method. The developed model showed good statistical parameters (R2 = 0.725, R2adj = 0.653, MSE = 0.060, R2test = 0.827, Q2cv = 0.536). The energy EHOMO orbital, electronic energy (TE), shape coefficient (I), number of rotatable bonds (NROT), and index of refraction (n) were revealed to be the main descriptors influencing the anti-cancer activity. Further, new Thiazole derivatives have been designed and their activities and pharmacokinetic properties have been predicted using the validated QSAR model. The designed molecules were then assessed to molecular docking (MD), and molecular dynamic (MDs) simulation accompanied by the calculation of the binding affinity using MMPBSA script according to 100 ns a simulation trajectory, to study both their affinity and their stability towards CDK2 as a target protein for the cancer disease treatment. This research concluded with the identification of four new CDK2 inhibitors which are A1, A3, A5, and A6 showing good pharmacokinetic properties. The MDs results revealed that the newly designed compound A5 remained stable in the active center of the discovered CDK2 protein, indicating its potential as a novel inhibitor for the treatment of hepatocellular carcinoma. The current findings may eventually contribute to the development of robust CDK2 inhibitors in the future.Communicated by Ramaswamy H. Sarma.

Afro-TB dataset as a large scale genomic data of Mycobacterium tuberuclosis in Africa.

Mycobacterium tuberculosis (MTB) is a pathogenic bacterium accountable for 10.6 million new infections with tuberculosis (TB) in 2021. The fact that the genetic sequences of M. tuberculosis vary widely provides a basis for understanding how this bacterium causes disease, how the immune system responds to it, how it has evolved over time, and how it is distributed geographically. However, despite extensive research efforts, the evolution and transmission of MTB in Africa remain poorly understood. In this study, we used 17,641 strains from 26 countries to create the first curated African Mycobacterium tuberculosis (MTB) classification and resistance dataset, containing 13,753 strains. We identified 157 mutations in 12 genes associated with resistance and additional new mutations potentially associated with resistance. The resistance profile was used to classify strains. We also performed a phylogenetic classification of each isolate and prepared the data in a format that can be used for phylogenetic and comparative analysis of tuberculosis worldwide. These genomic data will extend current information for comparative genomic studies to understand the mechanisms and evolution of MTB drug resistance.

In silico protein engineering shows that novel mutations affecting NAD+ binding sites may improve phosphite dehydrogenase stability and activity.

Pseudomonas stutzeri phosphite dehydrogenase (PTDH) catalyzes the oxidation of phosphite to phosphate in the presence of NAD, resulting in the formation of NADH. The regeneration of NADH by PTDH is greater than any other enzyme due to the substantial change in the free energy of reaction (G°' = - 63.3 kJ/mol). Presently, improving the stability of PTDH is for a great importance to ensure an economically viable reaction process to produce phosphite as a byproduct for agronomic applications. The binding site of NAD+ with PTDH includes thirty-four residues; eight of which have been previously mutated and characterized for their roles in catalysis. In the present study, the unexplored twenty-six key residues involved in the binding of NAD+ were subjected to in silico mutagenesis based on the physicochemical properties of the amino acids. The effects of these mutations on the structure, stability, activity, and interaction of PTDH with NAD+ were investigated using molecular docking, molecular dynamics simulations, free energy calculations, and secondary structure analysis. We identified seven novel mutations, A155I, G157I, L217I, P235A, V262I, I293A, and I293L, that reduce the compactness of the protein while improving PTDH stability and binding to NAD+.

Whole Genome Sequence of Bacillus anthracis MDMC_159, Isolated from the Moroccan Desert Erg Lihoudi.

We report the complete genome sequence of Bacillus anthracis strain MDMC_159, which was isolated from a deserted sandy area of Erg Lihoudi in southeastern Morocco. This strain is pathogenic and well adapted to the harsh conditions of the Moroccan desert.

Assessing the effect of a series of mutations on the dynamic behavior of phosphite dehydrogenase using molecular docking, molecular dynamics and quantum mechanics/molecular mechanics simulations.

Discovered in Pseudomonas stutzeri, phosphite dehydrogenase (PTDH) is an enzyme that catalyzes the oxidation of phosphite to phosphate while simultaneously reducing NAD+ to NADH. Despite several investigations into the mechanism of reaction and cofactor regeneration, only a few studies have focused on improving the activity and stability of PTDH. In this study, we combine molecular docking, molecular dynamics (MD) simulation, and Quantum Mechanics/Molecular Mechanics (QM/MM) to identify the impact of 30 mutations on the activity and stability of PTDH. Molecular docking results suggest that E266Q, K76A, K76M, K76R, K76C, and R237K can act on the NAD+ binding site through relatively weak bond development due to their high free binding energy. Moreover, Mulliken population analysis and potential energy barrier indicate that T101A, E175A, E175A/A176R, A176R, and E266Q act on phosphite oxidation. The mutants M53N, M53A, K76R, D79N, D79A, T101A, W134A, W134F Y139F, A146S, E175A, F198I, F198M, E266Q, H292K, S295A, R301K, and R301A were found to act on the structural dynamic of PTDH. The remaining mutants cause the loss of the nitrogen atom of R237 and H292, respectively, inactivating the enzyme. This study provides specific explanations of how mutations affect weak interactions of PTDH. The results should allow researchers to conduct experimental studies to improve PTDH activity and stability.Communicated by Ramaswamy H. Sarma.

Hybrid Molecules as Potential Drugs for the Treatment of HIV: Design and Applications.

Human immunodeficiency virus (HIV) infection is a major problem for humanity because HIV is constantly changing and developing resistance to current drugs. This necessitates the development of new anti-HIV drugs that take new approaches to combat an ever-evolving virus. One of the promising alternatives to combination antiretroviral therapy (cART) is the molecular hybrid strategy, in which two or more pharmacophore units of bioactive scaffolds are combined into a single molecular structure. These hybrid structures have the potential to have higher efficacy and lower toxicity than their parent molecules. Given the potential advantages of the hybrid molecular approach, the development and synthesis of these compounds are of great importance in anti-HIV drug discovery. This review focuses on the recent development of hybrid compounds targeting integrase (IN), reverse transcriptase (RT), and protease (PR) proteins and provides a brief description of their chemical structures, structure-activity relationship, and binding mode.

Host Cell Proteases Mediating SARS-CoV-2 Entry: An Overview.

The outbreak of the SARS-CoV-2 virus in late 2019 and the spread of the COVID-19 pandemic have caused severe health and socioeconomic damage worldwide. Despite the significant research effort to develop vaccines, antiviral treatments, and repurposed therapeutics to effectively contain the catastrophe, there are no available effective vaccines or antiviral drugs that can limit the threat of the disease, so the infections continue to expand. To date, the search for effective treatment remains a global challenge. Therefore, it is imperative to develop therapeutic strategies to contain the spread of SARS-CoV-2. Like other coronaviruses, SARS-CoV-2 invades and infects human host cells via the attachment of its spike envelope glycoprotein to the human host cell receptor hACE2. Subsequently, several host cell proteases facilitate viral entry via proteolytic cleavage and activation of the S protein. These host cell proteases include type II transmembrane serine proteases (TTSPs), cysteine cathepsins B and L, furin, trypsin, and Factor Xa, among others. Given the critical role of the host cell proteases in coronavirus pathogenesis, their inhibition by small molecules has successfully targeted SARS-CoV-2 in vitro, suggesting that host cell proteases are attractive therapeutic targets for SARS-CoV-2 infection. In this review, we focus on the biochemical properties of host cell proteases that facilitate the entry of SARS-CoV-2, and we highlight therapeutic small molecule candidates that have been proposed through in silico research.

Monte Carlo Method and GA-MLR-Based QSAR Modeling of NS5A Inhibitors against the Hepatitis C Virus.

Hepatitis C virus (HCV) is a serious disease that threatens human health. Despite consistent efforts to inhibit the virus, it has infected more than 58 million people, with 300,000 deaths per year. The HCV nonstructural protein NS5A plays a critical role in the viral life cycle, as it is a major contributor to the viral replication and assembly processes. Therefore, its importance is evident in all currently approved HCV combination treatments. The present study identifies new potential compounds for possible medical use against HCV using the quantitative structure-activity relationship (QSAR). In this context, a set of 36 NS5A inhibitors was used to build QSAR models using genetic algorithm multiple linear regression (GA-MLR) and Monte Carlo optimization and were implemented in the software CORAL. The Monte Carlo method was used to build QSAR models using SMILES-based optimal descriptors. Four splits were performed and 24 QSAR models were developed and verified through internal and external validation. The model created for split 3 produced a higher value of the determination coefficients using the validation set (R2 = 0.991 and Q2 = 0.943). In addition, this model provides interesting information about the structural features responsible for the increase and decrease of inhibitory activity, which were used to develop eight novel NS5A inhibitors. The constructed GA-MLR model with satisfactory statistical parameters (R2 = 0.915 and Q2 = 0.941) confirmed the predicted inhibitory activity for these compounds. The Absorption, Distribution, Metabolism, Elimination, and Toxicity (ADMET) predictions showed that the newly designed compounds were nontoxic and exhibited acceptable pharmacological properties. These results could accelerate the process of discovering new drugs against HCV.

Syzygium aqueum (Burm.f.) Alston Prevents Streptozotocin-Induced Pancreatic Beta Cells Damage via the TLR-4 Signaling Pathway.

Although several treatments are available for the treatment of type 2 diabetes mellitus, adverse effects and cost burden impose the search for safe, efficient, and cost-effective alternative herbal remedies. Syzygium aqueum (Burm.f.) Alston, a natural anti-inflammatory, antioxidant herb, may suppress diabetes-associated inflammation and pancreatic beta-cell death. Here, we tested the ability of the bioactive leaf extract (SA) to prevent streptozotocin (STZ)-induced oxidative stress and inflammation in pancreatic beta cells in rats and the involvement of the TLR-4 signaling pathway. Non-fasted rats pretreated with 100 or 200 mg kg-1 SA 2 days prior to the STZ challenge and for 14 days later had up to 52 and 39% reduction in the glucose levels, respectively, while glibenclamide, the reference standard drug (0.5 mg kg-1), results in 70% reduction. Treatment with SA extract was accompanied by increased insulin secretion, restoration of Langerhans islets morphology, and decreased collagen deposition as demonstrated from ELISA measurement, H and E, and Mallory staining. Both glibenclamide and SA extract significantly decreased levels of TLR-4, MYD88, pro-inflammatory cytokines TNF-α, and TRAF-6 in pancreatic tissue homogenates, which correlated well with minimal pancreatic inflammatory cell infiltration. Pre-treatment with SA or glibenclamide decreased malondialdehyde, a sensitive biomarker of ROS-induced lipid peroxidation, and restored depleted reduced glutathione in the pancreas. Altogether, these data indicate that S. aqueum is effective in improving STZ-induced pancreatic damage, which could be beneficial in treating type 2 diabetes mellitus.

Function of selected natural antidiabetic compounds with potential against cancer via modulation of the PI3K/AKT/mTOR cascade.

Diabetes mellitus (DM) is a metabolic disorder with growing global incidence, as 387 million people were diagnosed in 2014 with an expected projection of 642 million in 2040. Several complications are associated with DM including heart attack, stroke, kidney failure, blindness, and cancer. The latter is the second leading cause of death worldwide accounting for one in every six deaths, with liver, pancreas, and endometrium cancers are the most abundant among patients with diabetes. Phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR) pathway plays a vital role in developing a wide array of pathological disorders, among them diabetes and cancer. Natural secondary metabolites that counteract the deleterious effects of reactive oxygen species (ROS) and modulate PI3K/Akt/mTOR pathway could be a promising approach in cancer therapy. Here, 717 medicinal plants with antidiabetic activities were highlighted along with 357 bioactive compounds responsible for the antidiabetic activity. Also, 43 individual plant compounds with potential antidiabetic activities against cancer via the modulation of PI3K/Akt/mTOR cascade were identified. Taken together, the available data give an insight of the potential of repurposing medicinal plants and/or the individual secondary metabolites with antidiabetic activities for cancer therapy.

Machine learning applications in RNA modification sites prediction.

Ribonucleic acid (RNA) modifications are post-transcriptional chemical composition changes that have a fundamental role in regulating the main aspect of RNA function. Recently, large datasets have become available thanks to the recent development in deep sequencing and large-scale profiling. This availability of transcriptomic datasets has led to increased use of machine learning based approaches in epitranscriptomics, particularly in identifying RNA modifications. In this review, we comprehensively explore machine learning based approaches used for the prediction of 11 RNA modification types, namely, m 1 A , m 6 A , m 5 C , 5 hmC , ψ , 2 ' - O - Me , ac 4 C , m 7 G , A - to - I , m 2 G , and D . This review covers the life cycle of machine learning methods to predict RNA modification sites including available benchmark datasets, feature extraction, and classification algorithms. We compare available methods in terms of datasets, target species, approach, and accuracy for each RNA modification type. Finally, we discuss the advantages and limitations of the reviewed approaches and suggest future perspectives.