Targeting Cathepsin L in Cancer Management: Leveraging Machine Learning, Structure-Based Virtual Screening, and Molecular Dynamics Studies.

Cathepsin L (CTSL) expression is dysregulated in a variety of cancers. Extensive empirical evidence indicates their direct participation in cancer growth, angiogenic processes, metastatic dissemination, and the development of treatment resistance. Currently, no natural CTSL inhibitors are approved for clinical use. Consequently, the development of novel CTSL inhibition strategies is an urgent necessity. In this study, a combined machine learning (ML) and structure-based virtual screening strategy was employed to identify potential natural CTSL inhibitors. The random forest ML model was trained on IC50 values. The accuracy of the trained model was over 90%. Furthermore, we used this ML model to screen the Biopurify and Targetmol natural compound libraries, yielding 149 hits with prediction scores >0.6. These hits were subsequently selected for virtual screening using a structure-based approach, yielding 13 hits with higher binding affinity compared to the positive control (AZ12878478). Two of these hits, ZINC4097985 and ZINC4098355, have been shown to strongly bind CTSL proteins. In addition to drug-like properties, both compounds demonstrated high affinity, ligand efficiency, and specificity for the CTSL binding pocket. Furthermore, in molecular dynamics simulations spanning 200 ns, these compounds formed stable protein-ligand complexes. ZINC4097985 and ZINC4098355 can be considered promising candidates for CTSL inhibition after experimental validation, with the potential to provide therapeutic benefits in cancer management.

Eleven Crucial Pesticides Appear to Regulate Key Genes That Link MPTP Mechanism to Cause Parkinson's Disease through the Selective Degeneration of Dopamine Neurons.

Pesticides kill neurons, but the mechanism leading to selective dopaminergic loss in Parkinson's disease (PD) is unknown. Understanding the pesticide's effect on dopaminergic neurons (DA) can help to screen and treat PD. The critical uptake of pesticides by the membrane receptors at DA is hypothesized to activate a signaling cascade and accelerate degeneration. Using MPTP as a reference, we demonstrate the mechanisms of eleven crucial pesticides through molecular docking, protein networks, regulatory pathways, and prioritization of key pesticide-regulating proteins. Participants were recruited and grouped into control and PD based on clinical characteristics as well as pesticide traces in their blood plasma. Then, qPCR was used to measure pesticide-associated gene expression in peripheral blood mononuclear cells between groups. As a result of molecular docking, all eleven pesticides and the MPTP showed high binding efficiency against 274 membrane receptor proteins of DA. Further, the protein interaction networks showed activation of multiple signaling cascades through these receptors. Subsequent analysis revealed 31 biological pathways shared by all 11pesticides and MPTP that were overrepresented by 46 crucial proteins. Among these, CTNNB1, NDUFS6, and CAV1 were prioritized to show a significant change in gene expression in pesticide-exposed PD which guides toward therapy.

Identifying promising GSK3ß inhibitors for cancer management: a computational pipeline combining virtual screening and molecular dynamics simulations.

Glycogen synthase kinase-3 (GSK3ß), a serine/threonine protein kinase, has been discovered as a novel target for anticancer drugs. Although GSK3ß is involved in multiple pathways linked to the etiology of various cancers, no specific GSK3ß inhibitor has been authorized for cancer therapy. Most of its inhibitors have toxicity effects therefore, there is a need to develop safe and more potent inhibitors. In this study, a library of 4,222 anti-cancer compounds underwent rigorous computational screening to identify potential candidates for targeting the binding pocket of GSK3ß. The screening process involved various stages, including docking-based virtual screening, physicochemical and ADMET analysis, and molecular dynamics simulations. Ultimately, two hit compounds, BMS-754807 and GSK429286A, were identified as having high binding affinities to GSK3ß. BMS-754807 and GSK429286A exhibited binding affinities of -11.9, and -9.8 kcal/mol, respectively, which were greater than that of the positive control (-7.6 kcal/mol). Further, molecular dynamics simulations for 100 ns were employed to optimize the interaction between the compounds and GSK3ß, and the simulations demonstrated that the interaction was stable and consistent throughout the study. These hits were also anticipated to have good drug-like properties. Finally, this study suggests that BMS-754807 and GSK429286A may undergo experimental validation to evaluate their potential as cancer treatments in clinical settings.

SARS-CoV-2 Variants Show a Gradual Declining Pathogenicity and Pro-Inflammatory Cytokine Stimulation, an Increasing Antigenic and Anti-Inflammatory Cytokine Induction, and Rising Structural Protein Instability: A Minimal Number Genome-Based Approach.

Hyper-transmissibility with decreased disease severity is a typical characteristic of the SARS-CoV-2 Omicron variant. To understand this phenomenon, we used various bioinformatics approaches to analyze randomly selected genome sequences (one each) of the Gamma, Delta, and Omicron variants submitted to NCBI from December 15 to 31, 2021. We report that the pathogenicity of SARS-CoV-2 variants decreases in the order of Wuhan > Gamma > Delta > Omicron; however, the antigenic property follows the order of Omicron > Gamma > Wuhan > Delta. The Omicron spike RBD shows lower pathogenicity but higher antigenicity than other variants. The reported decreased disease severity by the Omicron variant may be due to its decreased pro-inflammatory and IL-6 stimulation and increased IFN-γ and IL-4 induction efficacy. The mutations in the N protein are probably associated with this decreased IL-6 induction and human DDX21-mediated increased IL-4 production for Omicron. Due to the mutations, the stability of S, M, N, and E proteins decreases in the order of Omicron > Gamma > Delta > Wuhan. Although a stronger spike RBD-hACE2 binding of Omicron increases its transmissibility, the lowest stability of its spike protein makes spike RBD-hACE2 interaction weak for systemic infection and for causing severe disease. Finally, the highest instability of the Omicron E protein may also be associated with decreased viral maturation and low viral load, leading to less severe disease and faster recovery. Our findings will contribute to the understanding of the dynamics of SARS-CoV-2 variants and the management of emerging variants. This minimal genome-based method may be used for other similar viruses avoiding robust analysis.

Impact of meteorological factors and population density on COVID-19 pandemic in Saudi Arabia.

Transmission and increase in cases and fatalities of coronavirus disease-2019 (COVID-19) are significantly influenced by the parameters of weather, human activities and population factors. However, study gap on the seasonality of COVID-19 and impact of environmental factors on the pandemic in Saudi Arabia is present. The main aim of the study is to evaluate the impact of environment on the COVID-19 pandemic. Data were analyzed from January 2020 to July 2021. The generalized estimating equation (GEE) was used to determine the effect of environmental variables on longitudinal outcomes. Spearman's rank correlation coefficient (rs ) was used to analyze the impact of different parameters on the outcome of the pandemic. Multiple sequence alignment was performed by using ClustalW. Vaccination and fatalities (r s = -0.85) had the highest association followed by vaccination with cases (r s = -0.81) and population density with the fatalities (rs  = 0.71). The growth rate had the highest correlation with sun hours (r s = -0.63). Isolates from variant of concern alpha and beta were detected. Most of the reference sequences in Saudi Arabia were closely related with B.1.427/429 variant. Clade GH (54%) was the most prevalent followed by O (27%), GR (9%), G (6%), and S (4%), respectively. Male to female patient ratio was 1.4:1. About 95% fatality and hospitalization were reported in patients aged >60 years. This study will create a comprehensive insight of the interaction of environmental factors and the pandemic and add knowledge on seasonality of COVID-19 in Saudi Arabia.

Impact of Zinc, Vitamins C and D on Disease Prognosis among Patients with COVID-19 in Bangladesh: A Cross-Sectional Study.

Vitamin C, (ascorbic acid), vitamin D (cholecalciferol) and zinc (zinc sulfate monohydrate) supplements are important in immunity against coronavirus disease-2019 (COVID-19). However, a limited number of studies have been conducted on the association of vitamins and supplements with the reduced risks of COVID-19 infection. This study aims to evaluate the association of vitamins and supplements as treatment options to reduce the severity of COVID-19. Data were collected from 962 participants from 13 December 2020 to 4 February 2021. The presence of COVID-19 was confirmed by qRT-PCR. The Chi-square test and multivariate regression analyses were conducted. The ratio of uptake of vitamin C:vitamin D:zinc was 1:1:0.95. Uptake of vitamin C, vitamin D and zinc were significantly associated with the reduced risk of infection and severity of COVID-19 (OR: 0.006 (95% CI: 0.03-0.11) (p = 0.004)) and (OR: 0.03 (95% CI: 0.01-0.22) (p = 0.005)). The tendency of taking supplements was associated with the presence of infection of COVID-19 (p = 0.001), age (p = 0.02), sex (p = 0.05) and residence (p = 0.04). The duration of supplementation and medication was significantly associated with reduced hospitalization (p = 0.0001). Vitamins C, D and zinc were not significantly (p = 0.9) associated with a reduced risk of severity when taken through the diet. Hospitalization (p = 0.000001) and access to health facilities (p = 0.0097) were significantly associated with the survival period of the participants. Participants with better access to health facilities recovered early (OR: 6.21, 95% CI 1.56-24.7). This study will add knowledge in the field of treatment of COVID-19 by using vitamins and zinc supplements.

Dose-Dependent Effects of Melatonin on the Viability, Proliferation, and Differentiation of Dental Pulp Stem Cells (DPSCs).

(1) Background: Dental pulp stem cells (DPSCs) are derived from pulp tissue lodged within human teeth and are mesenchymal in origin. These DPSCs have been demonstrated to dissociate into clusters of various cell lineages and are very easy to isolate, culture, and expand. Melatonin, a multifaceted molecule with a spectrum of effects in the human body, is known to influence stem cell viability, proliferation, and differentiation, but little is known about the impact melatonin has on the capacity of DPSCs to differentiate into adipocytes, osteocytes, and chondrocytes. The primary objective of this research was to explore the impact that melatonin has on proliferation, and the capacity of DPSCs to differentiate into adipocytes, osteocytes, and chondrocytes. (2) Methodology: DPSCs were extracted from 12 healthy human teeth, cultured, and expanded. Flow cytometry was performed to examine the surface stem cell markers. Further, melatonin was added to the cultured DPSCs in various concentrations, to assess cytotoxicity using an MTT assay. Following this, the DPSCs were tested for their proliferative ability, as well as adipogenic, osteogenic, and chondrogenic differentiation capabilities under the influence of variable concentrations of melatonin. (3) Results: DPSCs obtained from human teeth demonstrated surface characteristics of mesenchymal stem cells, as shown by the positive expression of CD105, CD90, and CD73 markers. An MTT cytotoxicity assay revealed that melatonin was well tolerated by the cells at low (1 µM) and high (25 µM) concentrations. Assessment of DPSC cell differentiation elucidated that melatonin at 1 µM and 25 µM concentrations with the induction media stimulated DPSCs to differentiate into osteocytes, but did not have much influence on adipogenic and chondrogenic differentiation. (4) Conclusions: Melatonin could be used in stem cell and tissue engineering applications for osteogenic differentiation of DPSCs and could protect these cells due to its cytoprotective, immunomodulatory, and antioxidant roles, in addition to being an osteopromoter molecule.

Genomic surveillance, evolution and global transmission of SARS-CoV-2 during 2019-2022.

In spite of the availability of vaccine, the health burden associated with the COVID-19 pandemic continues to increase. An estimated 5 million people have died with SARS-CoV-2 infection. Analysis of evolution and genomic diversity can provide sufficient information to reduce the health burden of the pandemic. This study focused to conduct worldwide genomic surveillance. About 7.6 million genomic data were analyzed during 2019 to 2022. Multiple sequence alignment was conducted by using maximum likelihood method. Clade GK (52%) was the most predominant followed by GRY (12%), GRA (11%), GR (8%), GH (7%), G (6%), GV (3%), and O (1%), respectively. VOC Delta (66%) was the most prevalent variant followed by VOC Alpha (18%), VOC Omicron (13%), VOC Gamma (2%) and VOC Beta (1%), respectively. The frequency of point mutations including E484K, N501Y, N439K, and L452R at spike protein has increased 10%-92%. Evolutionary rate of the variants was 23.7 substitution per site per year. Substitution mutations E484K and N501Y had significant correlation with cases (r = .45, r = .23), fatalities (r = .15, r = .44) and growth rate R0 (r = .28, r = .54). This study will help to understand the genomic diversity, evolution and the impact of the variants on the outcome of the COVID-19 pandemic.

Evaluation of Candidiasis in Upper-Aerodigestive Squamous Cell Carcinoma Patients-A Clinico-Mycological Aspect.

Candida is a commensal yeast. It can be infective when the host's defense mechanism is weakened, as in the case of squamous cell carcinoma patients. We aimed to evaluate the prevalence and clinical mycological manifestation of candidiasis in 150 cancer cases comprised of preoperative and post-operative (with or without radiotherapy) upper aerodigestive squamous cell carcinoma. A total of 150 patients suffering from squamous cell carcinoma of the Upper Aero-Digestive Tract (UADT) were divided into preoperative (n = 48), post-operative without radiotherapy (n = 29) and post-operative with radiotherapy (n = 73). Samples were collected using cotton swabs and cultured. Candida species were identified according to color pigmentation on Candida Differential Agar (CDA) plate. The clinico-mycological association of patients was evaluated by the chi-square test, and 98 out of 150 patients showed the presence of various Candida species. The major species isolated was Candida albicans (53%), followed by Candida tropicalis (16%). There was a significant statistical difference between patients who showed mycological associations and patients who did not have any such association (p = 0.0008). The prevalence of oral candidiasis was found to be 65.33% among total cases of upper aero-digestive squamous cell carcinoma. Chronic erythematous cases of candidiasis were mainly seen in preoperative squamous cell carcinoma cases, whereas the acute erythematous type of candidiasis was mainly seen in post-operative cases who received radiotherapy. The clinicomycological assessment can help to correlate the signs and symptoms with the presence of candidiasis in upper aerodigestive squamous cell carcinoma patients. Meticulous testing and examination can help in the early detection of candidiasis. Future studies are needed to develop advance scientific preventive strategies for high-risk cases.

In Silico Designed Multi-Epitope Immunogen "Tpme-VAC/LGCM-2022" May Induce Both Cellular and Humoral Immunity against Treponema pallidum Infection.

Syphilis, a sexually transmitted infection caused by the spirochete Treponema pallidum, has seen a resurgence over the past years. T. pallidum is capable of early dissemination and immune evasion, and the disease continues to be a global healthcare burden. The purpose of this study was to design a multi-epitope immunogen through an immunoinformatics-based approach. Multi-epitope immunogens constitute carefully selected epitopes belonging to conserved and essential bacterial proteins. Several physico-chemical characteristics, such as antigenicity, allergenicity, and stability, were determined. Further, molecular docking and dynamics simulations were performed, ensuring binding affinity and stability between the immunogen and TLR-2. An in silico cloning was performed using the pET-28a(+) vector and codon adaptation for E. coli. Finally, an in silico immune simulation was performed. The in silico predictions obtained in this work indicate that this construct would be capable of inducing the requisite immune response to elicit protection against T. pallidum. Through this methodology we have designed a promising potential vaccine candidate for syphilis, namely Tpme-VAC/LGCM-2022. However, it is necessary to validate these findings in in vitro and in vivo assays.

Ensemble Deep-Learning-Based Prognostic and Prediction for Recurrence of Sporadic Odontogenic Keratocysts on Hematoxylin and Eosin Stained Pathological Images of Incisional Biopsies.

(1) Background: Odontogenic keratocysts (OKCs) are enigmatic developmental cysts that deserve special attention due to their heterogeneous appearance in histopathological characteristics and high recurrence rate. Despite several nomenclatures for classification, clinicians still confront challenges in its diagnosis and predicting its recurrence. This paper proposes an ensemble deep-learning-based prognostic and prediction algorithm, for the recurrence of sporadic odontogenic keratocysts, on hematoxylin and eosin stained pathological images of incisional biopsies before treatment. (2) Materials and Methods: In this study, we applied a deep-learning algorithm to an ensemble approach integrated with DenseNet-121, Inception-V3, and Inception-Resnet-V3 classifiers. Around 1660 hematoxylin and eosin stained pathologically annotated digital images of OKC-diagnosed (60) patients were supplied to train and predict recurrent OKCs. (3) Results: The presence of SEH (p = 0.004), an incomplete epithelial lining, (p = 0.023), and a corrugated surface (p = 0.049) were the most significant histological parameters distinguishing recurrent and non-recurrent OKCs. Amongst the classifiers, DenseNet-121 showed 93% accuracy in predicting recurrent OKCs. Furthermore, integrating and training the traditional ensemble model showed an accuracy of 95% and an AUC of 0.9872, with an execution time of 192.9 s. In comparison, our proposed model showed 97% accuracy with an execution time of 154.6 s. (4) Conclusions: Considering the outcome of our novel ensemble model, based on accuracy and execution time, the presented design could be embedded into a computer-aided design system for automation of risk stratification of odontogenic keratocysts.

Receptor binding domain of SARS-CoV-2 from Wuhan strain to Omicron B.1.1.529 attributes increased affinity to variable structures of human ACE2.

BACKGROUND: COVID-19 is an infectious disease declared as a global pandemic caused by SARS-CoV-2 virus. Genomic changes in the receptor binding domain (RBD) region of SARS-CoV-2 led to an increased, infectivity in humans through interaction with the angiotensin-converting enzyme2 (ACE2) receptor. Simultaneously, the genetic variants in ACE2 provide an opportunity for SARS-CoV-2 infection and severity. We demonstrate the binding efficiencies of RBDs of SARS-CoV-2 strain with ACE2 variants of the human host. METHODOLOGY: A Total of 615 SARS-CoV-2 genomes were retrieved from repository. Eighteen variations were identified contributing to structural changes in RBD that are distributed in 615 isolates. An analyses of 285 single nucleotide variances at the coding region of the ACE2 receptor showed 34 to be pathogenic. Homology models of 34 ACE2 and 18 RBD structures were constructed with 34 and 18 structural variants, respectively. Protein docking of 612 (34 *18) ACE2-RBD complexes showed variable affinities compared to wildtype Wuhan's and other SARS-CoV-2 RBDs, including Omicron B.1.1.529. Finally, molecular dynamic simulation was performed to determine the stability of the complexes. RESULTS: Among 612, the top 3 complexes showing least binding energy were selected. The ACE2 with rs961360700 variant showed the least binding energy (-895.2 Kcal/mol) on binding with the RBD of Phe160Ser variant compared to Wuhan's RBD complex. Interestingly, the binding energy of RBD of Omicron B.1.1.529 with ACE2 (rs961360700) structure showed least binding energy of -1010 Kcal/mol. Additionally, molecular dynamics showed structure stability for all the analysed complexes with the RMSD (0.22-0.26 nm), RMSF (0.11-0.13 nm), and Rg (2.53-2.56 nm). CONCLUSION: In conclusion, our investigation highlights the clinical variants contributing to structural variants in ACE2 receptors that lead to efficient binding of SARS-CoV-2. Therefore, screening of these ACE2 polymorphisms will help detect COVID-19 risk population so as to provide additional care and for safe management.

Multi-target potential of Indian phytochemicals against SARS-CoV-2: A docking, molecular dynamics and MM-GBSA approach extended to Omicron B.1.1.529.

BACKGROUND: SARS-CoV-2, an emerged strain of corona virus family became almost serious health concern worldwide. Despite vaccines availability, reports suggest the occurrence of SARS-CoV-2 infection even in a vaccinated population. With frequent evolution and expected multiple COVID-19 waves, improved preventive, diagnostic, and treatment measures are required. In recent times, phytochemicals have gained attention due to their therapeutic characteristics and are suggested as alternative and complementary treatments for infectious diseases. This present study aimed to identify potential inhibitors against reported protein targets of SARS-CoV-2. METHODOLOGY: We computationally investigated potential SARS-CoV-2 protein targets from the literature and collected druggable phytochemicals from Indian Medicinal Plants, Phytochemistry and Therapeutics (IMPPAT) database. Further, we implemented a systematic workflow of molecular docking, dynamic simulations and generalized born surface area free-energy calculations (MM-GBSA). RESULTS: Extensive literature search and assessment of 1508 articles identifies 13 potential SARS-CoV-2 protein targets. We screened 501 druggable phytochemicals with proven biological activities. Analysis of 6513(501 *13) docked phytochemicals complex, 26 were efficient against SARS-CoV-2. Amongst, 4,8-dihydroxysesamin and arboreal from Gmelina arborea were ranked potential against most of the targets with binding energy ranging between - 10.7 to - 8.2 kcal/mol. Additionally, comparative docking with known drugs such as arbidol (-6.6 to -5.1 kcal/mol), favipiravir (-5.5 to -4.5 kcal/mol), hydroxychloroquine (-6.5 to -5.1 kcal/mol), and remedesivir (-8.0 to -5.3 kcal/mol) revealed equal/less affinity than 4,8-dihydroxysesamin and arboreal. Interestingly, the nucleocapsid target was found commonly inhibited by 4,8-dihydroxysesamin and arboreal. Molecular dynamic simulation and Molecular mechanics generalized born surface area (MM-GBSA)calculations reflect that both the compounds possess high inhibiting potential against SARS-CoV-2 including the recently emerged Omicron variant (B.1.1.529). CONCLUSION: Overall our study imparts the usage of phytochemicals as antiviral agents for SARS-CoV-2 infection. Additional in vitro and in vivo testing of these phytochemicals is required to confirm their potency.

Role of MicroRNA-31 (miR-31) in Breast Carcinoma Diagnosis and Prognosis.

BACKGROUND/AIM: Breast cancer (BC) is among the most widespread malignant tumors in women. In the current study, we evaluated the role of miR-31 in BC patients and its relation to the different prognostic, clinical, and pathological features. PATIENTS AND METHODS: MiR-31 levels were determined by RT-PCR in BC and adjacent normal breast tissues from 100 BC patients. BC diagnosis was established through histopathological examinations. The expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) receptor in all tumors was determined using immunohistochemistry. RESULTS: MiR-31 expression was reduced in BC tissues relative to adjacent healthy breast tissue (mean levels were 0.93 and 7.2, respectively). Also, the low expression of miR-31 in BC patients was significantly correlated with adverse clinical and pathological features such as: young patient's age, premenopausal status, infiltrative lobular carcinoma, ER and PR negative tumors, HER2 positive tumors, and advanced clinical stage. CONCLUSION: MiR-31 was expressed at low levels in BC tissues and correlated with adverse clinical and pathological features, and poor survival.

Impact of Red Complex Bacteria and TNF-α Levels on the Diabetic and Renal Status of Chronic Kidney Disease Patients in the Presence and Absence of Periodontitis.

Scientific evidence shows a positive association in the etiopathogenesis of periodontitis and chronic kidney disease (CKD). Various confounding factors, such as obesity, diabetes, and inflammation, also play a significant role in the progression of CKD, which remains unexplored. We hypothesise the role of red complex bacteria with various confounding factors associated with chronic kidney disease. The study comprised a total of 120 participants categorised into 4 groups: the control group (C), periodontitis subjects without CKD (P), periodontally healthy chronic kidney disease subjects (CKD), and subjects having both periodontitis and CKD (P + CKD), with 30 subjects in each group. Demographic variables, and periodontal, renal, and diabetic parameters were recorded. Tumour necrosis factor (TNF)-α levels and those of red complex bacteria such as Prophyromonas gingivalis (P.g), Treponema denticola (T.d), and Tonerella forsythia (T.f) were assessed, and the obtained results were statistically analysed. Among the various demographic variables, age showed a level of significance. Mean PI, GI, CAL, and PPD (the proportion of sites with PPD ≥ 5 mm and CAL ≥ 3 mm) were elevated in the P + CKD group. Diabetic parameters such as fasting blood sugar (FBS) and HbA1c levels were also greater in the P + CKD group. Renal parameters such as eGFR and serum creatinine levels were greater in CKD patients. The estimation of red complex periodontal pathogens such as Pg, Td and Tf levels were significantly greater in the P and P + CKD groups. Pearson correlation analysis revealed significant correlation of red complex bacteria with all variables. Greater levels of P.g, T.d and T.f were found in the P groups, thus indicating their important role in the initiation and progression of inflammation of periodontitis and CKD, with diabetes as one of the confounding factors. The study also confirmed a log-linear relationship between TNF-α levels and red complex bacteria, thereby demonstrating the role of inflammatory biomarkers in periodontal disease progression that could contribute to the development of systemic inflammation such as CKD.

Polysaccharide-Drug Conjugates: A Tool for Enhanced Cancer Therapy.

Cancer is one of the most widespread deadly diseases, following cardiovascular disease, worldwide. Chemotherapy is widely used in combination with surgery, hormone and radiation therapy to treat various cancers. However, chemotherapeutic drugs can cause severe side effects due to non-specific targeting, poor bioavailability, low therapeutic indices, and high dose requirements. Several drug carriers successfully overcome these issues and deliver drugs to the desired sites, reducing the side effects. Among various drug delivery systems, polysaccharide-based carriers that target only the cancer cells have been developed to overcome the toxicity of chemotherapeutics. Polysaccharides are non-toxic, biodegradable, hydrophilic biopolymers that can be easily modified chemically to improve the bioavailability and stability for delivering therapeutics into cancer tissues. Different polysaccharides, such as chitosan, alginates, cyclodextrin, pullulan, hyaluronic acid, dextran, guar gum, pectin, and cellulose, have been used in anti-cancer drug delivery systems. This review highlights the recent progress made in polysaccharides-based drug carriers in anti-cancer therapy.

Plant-Derived Antiviral Compounds as Potential Entry Inhibitors against Spike Protein of SARS-CoV-2 Wild-Type and Delta Variant: An Integrative in SilicoApproach.

The wild-type SARS-CoV-2 has continuously evolved into several variants with increased transmissibility and virulence. The Delta variant which was initially identified in India created a devastating impact throughout the country during the second wave. While the efficacy of the existing vaccines against the latest SARS-CoV-2 variants remains unclear, extensive research is being carried out to develop potential antiviral drugs through approaches like in silico screening and drug-repurposing. This study aimed to conduct the docking-based virtual screening of 50 potential phytochemical compounds against a Spike glycoprotein of the wild-type and the Delta SARS-CoV-2 variant. Subsequently, molecular docking was performed for the five best compounds, such as Lupeol, Betulin, Hypericin, Corilagin, and Geraniin, along with synthetic controls. From the results obtained, it was evident that Lupeol exhibited a remarkable binding affinity towards the wild-type Spike protein (-8.54 kcal/mol), while Betulin showed significant binding interactions with the mutated Spike protein (-8.83 kcal/mol), respectively. The binding energy values of the selected plant compounds were slightly higher than that of the controls. Key hydrogen bonding and hydrophobic interactions of the resulting complexes were visualized, which explained their greater binding affinity against the target proteins-the Delta S protein of SARS-CoV-2, in particular. The lower RMSD, the RMSF values of the complexes and the ligands, Rg, H-bonds, and the binding free energies of the complexes together revealed the stability of the complexes and significant binding affinities of the ligands towards the target proteins. Our study suggests that Lupeol and Betulin could be considered as potential ligands for SARS-CoV-2 spike antagonists. Further experimental validations might provide new insights for the possible antiviral therapeutic interventions of the identified lead compounds and their analogs against COVID-19 infection.

Targeting Cytotoxin-Associated Antigen A, a Virulent Factor of Helicobacter pylori-Associated Gastric Cancer: Structure-Based In Silico Screening of Natural Compounds.

Gastric cancer is the fifth most frequent cancer and the third major cause of mortality worldwide. Helicobacter pylori, a bacterial infection linked with GC, injects the cytotoxin-associated antigen A (CagA; an oncoprotein) into host cells. When the phosphorylated CagA protein enters the cell, it attaches to other cellular components, interfering with normal cellular signaling pathways. CagA plays an important role in the progression of GC by interacting with phosphatidylserine of the host cell membrane. Therefore, disrupting the CagA-phosphatidylserine connection using small molecules appears to be a promising therapeutic approach. In this report, we screened the natural compounds from ZINC database against the CagA protein using the bioinformatics tools. Hits were initially chosen based on their physicochemical, absorption, distribution, metabolism, excretion, and toxicity (ADMET) characteristics, as well as other drug-like characteristics. To locate safe and effective hits, the PAINS filter, binding affinities estimation, and interaction analysis were used. Three compounds with high binding affinity and specificity for the CagA binding pocket were discovered. The final hits, ZINC153731, ZINC69482055, and ZINC164387, were found to bind strongly with CagA protein, with binding energies of -11.53, -10.67, and -9.21 kcal/mol, respectively, which were higher than that of the control compound (-7.25 kcal/mol). Further, based on binding affinity and interaction pattern, two leads (ZINC153731, ZINC69482055) were chosen for molecular dynamics (MD) simulation analysis. MD results showed that they displayed stability in their vicinity at 100 ns. This study suggested that these compounds could be used as possible inhibitors of CagA protein in the fight against GC. However, additional benchwork tests are required to validate them as CagA protein inhibitors.

Circulating Long Non-Coding RNA GAS5: A Non-Invasive Molecular Marker for Prognosis, Response to Treatment and Survival in Non-Small Cell Lung Cancer.

Circulating long non-coding RNAs (lncRNA) are dysregulated in several diseases, especially cancers, e.g. non-small-cell lung cancer (NSCLC). Of specific notice in this regard is growth arrest-specific 5 gene (lncRNA GAS5), which is principally recognised as a tumor suppressor gene in numerous cancers. Functionally, GAS5 is involved in arresting cellular growth and induction of apoptosis. We analysed plasma GAS5 expression by qRT-PCR in 100 patients with NSCLC before and after tumour resection surgery. We reported a downregulation of GAS5 expression in NSCLC tissue and plasma, which showed elevation after surgery. Downregulation of GAS5 was associated with poor prognosis of NSCLC patients.