Screening inhibitors against the Ef-Tu of Fusobacterium nucleatum: a docking, ADMET and PBPK assessment study.

The oral pathogen Fusobacterium nucleatum has recently been associated with an elevated risk of colorectal cancer (CRC), endometrial metastasis, chemoresistance, inflammation, metastasis, and DNA damage, along with several other diseases. This study aimed to explore the disruption of protein machinery of F. nucleatum via inhibition of elongation factor thermo unstable (Ef-Tu) protein, through natural products. No study on Ef-Tu inhibition by natural products or in Fusobacterium spp. exists till todate. Ef-Tu is an abundant specialized drug target in bacteria that varies from human Ef-Tu. Elfamycins target Ef-Tu and hence, Enacyloxin IIa was used to generate pharmacophore for virtual screening of three natural product libraries, Natural Product Activity and Species Source (NPASS) (n = 30000 molecules), Tibetan medicinal plant database (n = 54 molecules) and African medicinal plant database (n > 6000 molecules). Peptaibol Septocylindrin B (NPC141050), Hirtusneanoside, and ZINC95486259 were prioritized from these libraries as potential therapeutic candidates. ADMET profiling was done for safety assessment, physiological-based pharmacokinetic modeling in human and mouse for getting insight into drug interaction with body tissues and molecular dynamics was used to assess stability of the best hit NPC141050 (Septocylindrin B). Based on the promising results, we propose further in vitro, in vivo and pharmacokinetic testing on the lead Septocylindrin B, for possible translation into therapeutic interventions.

Repositioning of anti-infective compounds against monkeypox virus core cysteine proteinase: a molecular dynamics study.

Monkeypox virus (MPXV) core cysteine proteinase (CCP) is one of the major drug targets used to examine the inhibitory action of chemical moieties. In this study, an in silico technique was applied to screen 1395 anti-infective compounds to find out the potential molecules against the MPXV-CCP. The top five hits were selected after screening and processed for exhaustive docking based on the docked score of ≤ -9.5 kcal/mol. Later, the top three hits based on the exhaustive-docking score and interaction profile were selected to perform MD simulations. The overall RMSD suggested that two compounds, SC75741 and ammonium glycyrrhizinate, showed a highly stable complex with a standard deviation of 0.18 and 0.23 nm, respectively. Later, the MM/GBSA binding free energies of complexes showed significant binding strength with ΔGTOTAL from -21.59 to -15 kcal/mol. This report reported the potential inhibitory activity of SC75741 and ammonium glycyrrhizinate against MPXV-CCP by competitively inhibiting the binding of the native substrate.

Mining therapeutic targets from the antibiotic-resistant Campylobacter coli and virtual screening of natural product inhibitors against its riboflavin synthase.

Campylobacter coli resides in the intestine of several commonly consumed animals, as well as water and soil. It leads to campylobacteriosis when humans eat raw/undercooked meat or come into contact with infected animals. A common manifestation of the infection is fever, nausea, headache, and diarrhea. Increasing antibiotic resistance is being observed in this pathogen. The increased incidence of C. coli infection, and post-infection complications like Guillain-Barré syndrome, make it an important pathogen. It is essential to find novel therapeutic targets and drugs against it, especially with the emergence of antibiotic-resistant strains. In the current study, genomes of 89 antibiotic-resistant strains of C. coli were downloaded from the PATRIC database. Potent drug targets (n = 36) were prioritized from the core genome (n = 1,337 genes) of this species. Riboflavin synthase was selected as a drug target and pharmacophore-based virtual screening was performed to predict its inhibitors from the NPASS (n = ~ 30,000 compounds) natural product library. The top three docked compounds (NPC115144, NPC307895, and NPC470462) were selected for dynamics simulation (for 50 ns) and ADMET profiling. These identified compounds appear safe for targeting this pathogen and can be further validated by experimental analysis before clinical trials.

Cheminformatics and machine learning approaches for repurposing anti-viral compounds against monkeypox virus thymidylate kinase.

One of the emerging epidemic concerns is Monkeypox disease which is spreading globally. This disease is caused by the monkeypox virus (MPXV), with an increasing global incidence with an outbreak in 2022. One of the novel targets for monkeypox disease is thymidylate kinase, which is involved in pyrimidine metabolism. In this study, docking-based virtual screening and molecular dynamics techniques were employed in addition to the machine learning (ML) model to investigate the potential anti-viral natural small compounds to inhibit thymidylate kinase of MPXV. Several potential hits were identified through high-throughput virtual screening, and further top three candidates were selected, which ranked using the ML model. These three compounds were then examined under molecular dynamics simulation and MM/GBSA-binding free energy analysis. Among these, Chlorhexidine HCl showed high potential for binding to the thymidylate kinase with stable and consistent conformation with RMSD < 0.3 nm. The MM/GBSA analysis also showed the minimum binding free energy (ΔGTOTAL) of -62.41 kcal/mol for this compound. Overall, this study used structure-based drug design complemented by machine learning-guided ligand-based drug design to screen potential hit compounds from the anti-viral natural compound database.

Anti-tubercular activity evaluation of natural compounds by targeting Mycobacterium tuberculosis resuscitation promoting factor B inhibition: An in silico study.

Tuberculosis (TB), an infectious disease caused by the Mycobacterium tuberculosis (Mtb), has been responsible for the deaths of millions of individuals around the globe. A vital protein in viral pathogenesis known as resuscitation promoting factor (RpfB) has been identified as a potential therapeutic target of anti-tuberculosis drugs. This study offered an in silico process to examine possible RpfB inhibitors employing a computational drug design pipeline. In this study, a total of 1228 phytomolecules were virtually tested against the RpfB of Mtb. These phytomolecules were sourced from the NP-lib database of the MTi-OpenScreen server, and five top hits (ZINC000044404209, ZINC000059779788, ZINC000001562130, ZINC000014766825, and ZINC000043552589) were prioritized for compute intensive docking with dock score ≤ - 8.5 kcal/mole. Later, molecular dynamics (MD) simulation and principal component analysis (PCA) were used to validate these top five hits. In the list of these top five hits, the ligands ZINC000044404209, ZINC000059779788, and ZINC000043552589 showed hydrogen bond formation with the functional residue Glu292 of the RpfB protein suggesting biological significance of the binding. The RMSD study showed stable protein-ligand complexes and higher conformational consistency for the ligands ZINC000014766825, and ZINC000043552589 with RMSD 3-4 Å during 100 ns MD simulation. The overall analysis performed in the study suggested promising binding of these compounds with the RpfB protein of the Mtb at its functional site, further experimental investigation is needed to validate the computational finding.

In-Silico Screening and Molecular Dynamics Simulation of Drug Bank Experimental Compounds against SARS-CoV-2.

For the last few years, the world has been going through a difficult time, and the reason behind this is severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), one of the significant members of the Coronaviridae family. The major research groups have shifted their focus towards finding a vaccine and drugs against SARS-CoV-2 to reduce the infection rate and save the life of human beings. Even the WHO has permitted using certain vaccines for an emergency attempt to cut the infection curve down. However, the virus has a great sense of mutation, and the vaccine's effectiveness remains questionable. No natural medicine is available at the community level to cure the patients for now. In this study, we have screened the vast library of experimental drugs of Drug Bank with Schrodinger's maestro by using three algorithms: high-throughput virtual screening (HTVS), standard precision, and extra precise docking followed by Molecular Mechanics/Generalized Born Surface Area (MMGBSA). We have identified 3-(7-diaminomethyl-naphthalen-2-YL)-propionic acid ethyl ester and Thymidine-5'-thiophosphate as potent inhibitors against the SARS-CoV-2, and both drugs performed impeccably and showed stability during the 100 ns molecular dynamics simulation. Both of the drugs are among the category of small molecules and have an acceptable range of ADME properties. They can be used after their validation in in-vitro and in-vivo conditions.

Promising Antimycobacterial Activities of Flavonoids against Mycobacterium sp. Drug Targets: A Comprehensive Review.

Tuberculosis (TB) caused by the bacterial pathogen Mycobacterium tuberculosis (Mtb) remains a threat to mankind, with over a billion of deaths in the last two centuries. Recent advancements in science have contributed to an understanding of Mtb pathogenesis and developed effective control tools, including effective drugs to control the global pandemic. However, the emergence of drug resistant Mtb strains has seriously affected the TB eradication program around the world. There is, therefore, an urgent need to develop new drugs for TB treatment, which has grown researchers' interest in small molecule-based drug designing and development. The small molecules-based treatments hold significant potential to overcome drug resistance and even provide opportunities for multimodal therapy. In this context, various natural and synthetic flavonoids were reported for the effective treatment of TB. In this review, we have summarized the recent advancement in the understanding of Mtb pathogenesis and the importance of both natural and synthetic flavonoids against Mtb infection studied using in vitro and in silico methods. We have also included flavonoids that are able to inhibit the growth of non-tubercular mycobacterial organisms. Hence, understanding the therapeutic properties of flavonoids can be useful for the future treatment of TB.

Hemi-Babim and Fenoterol as Potential Inhibitors of MPro and Papain-like Protease against SARS-CoV-2: An In-Silico Study.

The coronaviruses belong to the Coronaviridae family, and one such member, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is causing significant destruction around the world in the form of a global pandemic. Although vaccines have been developed, their effectiveness and level of protection is still a major concern, even after emergency approval from the World Health Organisation (WHO). At the community level, no natural medicine is currently available as a cure. In this study, we screened the vast library from Drug Bank and identified Hemi-Babim and Fenoterol as agents that can work against SARS-CoV-2. Furthermore, we performed molecular dynamics (MD) simulation for both compounds with their respective proteins, providing evidence that the said drugs can work against the MPro and papain-like protease, which are the main drug targets. Inhibiting the action of these targets may lead to retaining the virus. Fenoterol is a beta-2 adrenergic agonist used for the symptomatic treatment of asthma as a bronchodilator and tocolytic. In this study, Hemi-Babim and Fenoterol showed good docking scores of -7.09 and -7.14, respectively, and performed well in molecular dynamics simulation studies. Re-purposing the above medications has huge potential, as their effects are already well-proven and under public utilisation for asthma-related problems. Hence, after the comprehensive pipeline of molecular docking, MMGBSA, and MD simulation studies, these drugs can be tested in-vivo for further human utilisation.

Identification of Potent Natural Resource Small Molecule Inhibitor to Control Vibrio cholera by Targeting Its Outer Membrane Protein U: An In Silico Approach.

Vibrio cholerae causes the diarrheal disease cholera which affects millions of people globally. The outer membrane protein U (OmpU) is the outer membrane protein that is most prevalent in V. cholerae and has already been recognized as a critical component of pathogenicity involved in host cell contact and as being necessary for the survival of pathogenic V. cholerae in the host body. Computational approaches were used in this study to screen a total of 37,709 natural compounds from the traditional Chinese medicine (TCM) database against the active site of OmpU. Following a sequential screening of the TCM database, we report three lead compounds-ZINC06494587, ZINC85510056, and ZINC95910434-that bind strongly to OmpU, with binding affinity values of -8.92, -8.12, and -8.78 kcal/mol, which were higher than the control ligand (-7.0 kcal/mol). To optimize the interaction, several 100 ns molecular dynamics simulations were performed, and the resulting complexes were shown to be stable in their vicinity. Additionally, these compounds were predicted to have good drug-like properties based on physicochemical properties and ADMET assessments. This study suggests that further research be conducted on these compounds to determine their potential use as cholera disease treatment.

Biocomputational Prediction Approach Targeting FimH by Natural SGLT2 Inhibitors: A Possible Way to Overcome the Uropathogenic Effect of SGLT2 Inhibitor Drugs.

The Food and Drug Administration (FDA) approved a new class of anti-diabetic medication (a sodium-glucose co-transporter 2 (SGLT2) inhibitor) in 2013. However, SGLT2 inhibitor drugs are under evaluation due to their associative side effects, such as urinary tract and genital infection, urinary discomfort, diabetic ketosis, and kidney problems. Even clinicians have difficulty in recommending it to diabetic patients due to the increased probability of urinary tract infection. In our study, we selected natural SGLT2 inhibitors, namely acerogenin B, formononetin, (-)-kurarinone, (+)-pteryxin, and quinidine, to explore their potential against an emerging uropathogenic bacterial therapeutic target, i.e., FimH. FimH plays a critical role in the colonization of uropathogenic bacteria on the urinary tract surface. Thus, FimH antagonists show promising effects against uropathogenic bacterial strains via their targeting of FimH's adherence mechanism with less chance of resistance. The molecular docking results showed that, among natural SGLT2 inhibitors, formononetin, (+)-pteryxin, and quinidine have a strong interaction with FimH proteins, with binding energy (∆G) and inhibition constant (ki) values of -5.65 kcal/mol and 71.95 µM, -5.50 kcal/mol and 92.97 µM, and -5.70 kcal/mol and 66.40 µM, respectively. These interactions were better than those of the positive control heptyl α-d-mannopyranoside and far better than those of the SGLT2 inhibitor drug canagliflozin. Furthermore, a 50 ns molecular dynamics simulation was conducted to optimize the interaction, and the resulting complexes were found to be stable. Physicochemical property assessments predicted little toxicity and good drug-likeness properties for these three compounds. Therefore, formononetin, (+)-pteryxin, and quinidine can be proposed as promising SGLT2 inhibitors drugs, with add-on FimH inhibition potential that might reduce the probability of uropathogenic side effects.

Assessment of renal function among covid-19 patients admitted to the intensive care unit.

Severe acute respiratory viral infections are frequently associated with multiple organ failure, including acute kidney damage. The present study aimed to investigate the associated influence of COVID-19 on renal function in patients admitted to the intensive care unit in Asir region, Saudi Arabia. Thirty patients infected with COVID-19 who were referred to the intensive care unit during November and October 2020 at Asir central hospital, Asir region, Saudi Arabia were recruited. The age of patients ranged between 30 and 90 years old. Renal function tests exhibited dramatic changes in the renal biomarkers in patients with COVID-19. Blood urea levels in COVID-19 patients were significantly higher than in the control group. In addition, significantly lower albumin levels with abnormally decreased total protein levels were found in COVID-19 patients. Among the different electrolytes analyzed, a significantly lower calcium level was observed in COVID-19 patients' groups than in the controls. Renal function tests for COVID-19-infected ICU patients revealed significant changes, indicating the major impact of COVID-19 on kidney function. Monitoring renal function tests may assist in the early prognosis of COVID-19 patients. It is, therefore, crucial to increase the understanding of renal function tests in COVID-19 patients who were admitted to the hospital before their condition deteriorated.

Subtractive sequence-mediated therapeutic targets from the conserved gene clusters of Campylobacter hyointestinalis and computational inhibition assessment.

Campylobacter hyointestinalis is a causative agent of enteritis, proctitis, human gastroenteritis, and diarrhea. Reported transmission is from pigs to humans. Link with gastrointestinal carcinoma has also been established in non-Helicobacter pylori patients carrying this strain. The genome size of the strain LMG9260 is 1.8 MB with 1785 chromosomal and seven plasmid proteins. No therapeutic targets have been identified and reported in this bacterium. Therefore, subtractive computational screening of its genome was carried out for the purpose. In total, 31 such targets were mined and riboflavin synthase was utilized for screening natural product inhibitors against it. Among more than 30,000 screened natural compounds from the NPASS library, three (NPC472060, NPC33653, and NPC313886) were prioritized to have the potential to be developed into new antimicrobial drugs. Dynamics simulation assay along with other relevant parameters like absorption, toxicity, and distribution of the inhibiting compounds were also predicted and NPC33653 was identified as having the best drug-like properties among the prioritized compounds. Thus, it has potential to be pursued further for the inhibition of riboflavin synthesis in C. hyointestinalis for subsequent obstruction of its growth and survival.Communicated by Ramaswamy H. Sarma.

Molecular screening reveals Variolin B as a multitargeted inhibitor of lung cancer: a molecular docking-based fingerprinting and molecular dynamics simulation study.

Lung Cancer is the topmost death causing cancer and results from smoking, air pollution, cigar, exposure to asbestos or radon-like substances, and genetic factors. The cases of Lung Cancer in south Asian developing nations are being seen most due to heavy pollution and unbalanced lifestyle and putting a considerable burden on healthcare systems. The Food and Drug Administration of the USA has approved almost 100 drugs against SCLC and NSLC and a few drugs that are given to minimise the side effect of anticancer drugs. However, the drugs are shown to be resistant at significantly higher stages and non-affective on cancerous cells and have long-term side effects due to designing the drug by keeping one protein/gene target while designing or repurposing the drugs. In this study, we have taken five main lung cancer protein targets- Nerve growth factor protein (1SG1), Apoptosis inhibitor survivin (1XOX), Heat shock protein (3IUC), Protein tyrosine phosphate (3ZM3), Aldo-keto reductase (4XZL) and screened the complete prepared Drug Bank library of 155888 compounds and identified Variolin B (DB08694) as a multitargeted inhibitor against lung cancer using HTVS, SP and XP sampling algorithms followed by MM\GBSA calculation to sort the best pose. Variolin B is a natural marine antitumor and antiviral compound, so we analysed the ADMET properties and interaction patterns and then simulated all five P-L complexes for 100 ns in water using the NPT ensemble to check its selves against lung cancer. The docking results, ADMET and fingerprints have shown a good performance, and RMSD and RMSF results were with least deviation and fluctuations (<2Å) and produced a huge contact with other residues making the complex stable. The complexes initially fluctuated and deviated due to changes in the solute medium and sudden heat and stabilise after a few ns. However, extensive experimental validation is required before human use.Communicated by Ramaswamy H. Sarma.

Variolin B from sea sponge against lung cancer: a multitargeted molecular docking with fingerprinting and molecular dynamics simulation study.

Lung Cancer is the one that causes more fatalities in the world compared to other cancers, and its uniqueness is that it can be found in both males and females. However, recent data has shown that males are more affected due to lifestyle habits like smoking, tobacco consumption and inhaling polluted air. The World Health Organization has kept lung cancer on its priority list as it causes 1.8 million deaths worldwide each year, and the predictions show that the cases are going to increase year by year, and by 2050, there can be 3.8 million new cases and 3.2 million deaths, and the global health system is not prepared for it. Also, finding drug candidates that can help shrink cancerous cells and lead to their death is essential to reduce global mortality. The system needs drug compounds that can inhibit multiple paths together not to enter drug resistance quickly and to reduce costs. Our study identified a compound named Variolin B (DB08694) that belongs to the organic compounds class of pyrrolopyridines. The identified compound can inhibit multiple proteins, drastically reducing the global burden. Variolin B was identified as a potential candidate against lung cancer using the multisampling algorithm such as HTVS, SP, and XP, followed by MM\GBSA calculations showing the docking score of -9.245 Kcal/mol to -5.92 Kcal/mol. Also, we have validated it with ADMET predictions and molecular fingerprinting to analyse the interaction patterns. Further, the study was extended to molecular dynamics simulations for 100 ns to understand the complex stability and simulative interactions. The complex's overall molecular dynamics simulation helped us understand that the identified candidate is stable with the lowest deviation and fluctuations.Communicated by Ramaswamy H. Sarma.

Multitargeted Docking, DFT-Based Optimisation, Pharmacokinetics, and MD Simulation Reveal 6-Oxidopamine HBr as a Multitargeted Inhibitor of Cervical Cancer Proteins.

BACKGROUND: Cervical cancer originates in the cervix, the lower part of the uterus, and results from the uncontrolled growth of abnormal cervical cells, forming malignant tumours. It poses a major global health challenge, calling for innovative drug design strategies to enhance treatment outcomes. METHOD: In this study, we have screened the FDA-approved drug library against four proteins, MCM10, MCM6, DNA polymerase epsilon subunit-2, and TBK1, which are essential for DNA replication, DNA repair, and cellular signalling pathways, which are dysregulated in cervical cancer cells, leading to uncontrolled growth. We have used the multisampling algorithms for screening using HTVS, SP, and XP docking; identified 6- oxidopamine HBr (C8H12BrNO3), which is used to create a model of Parkinson's disease in animals, and obtained the docking score ranging from -5.057 to -8.871 Kcal/mol. The poses were filtered with MM\GBSA score ranging from -21.67 to -27.63 Kcal/mol. We performed QM-based DFT and pharmacokinetics studies and compared them with the standard values, suggesting that the compound can be used in cervical cancer proteins. RESULT: The P-L complex's interaction fingerprints have resulted in the most interacting residues, 4THR, 4SER, and 4LYS, showing the compound's interaction pattern. CONCLUSION: Further, the stability of 6-oxidopamine HBr in complex with each protein was evaluated with 100ns MD simulation in the SPC water model in a neutralised state to analyse the deviation, fluctuations, and intermolecular interactions that have proven the compound to have a better inhibitory effect against each protein and that it can be used for cervical cancer; however, experimental validation is suggested before human use.

Structure-Based In Silico Approaches Reveal IRESSA as a Multitargeted Breast Cancer Regulatory, Signalling, and Receptor Protein Inhibitor.

Breast cancer begins in the breast cells, mainly impacting women. It starts in the cells that line the milk ducts or lobules responsible for producing milk and can spread to nearby tissues and other body parts. In 2020, around 2.3 million women across the globe received a diagnosis, with an estimated 685,000 deaths. Additionally, 7.8 million women were living with breast cancer, making it the fifth leading cause of cancer-related deaths among women. The mutational changes, overexpression of drug efflux pumps, activation of alternative signalling pathways, tumour microenvironment, and cancer stem cells are causing higher levels of drug resistance, and one of the major solutions is to identify multitargeted drugs. In our research, we conducted a comprehensive screening using HTVS, SP, and XP, followed by an MM/GBSA computation of human-approved drugs targeting HER2/neu, BRCA1, PIK3CA, and ESR1. Our analysis pinpointed IRESSA (Gefitinib-DB00317) as a multitargeted inhibitor for these proteins, revealing docking scores ranging from -4.527 to -8.809 Kcal/mol and MM/GBSA scores between -49.09 and -61.74 Kcal/mol. We selected interacting residues as fingerprints, pinpointing 8LEU, 6VAL, 6LYS, 6ASN, 5ILE, and 5GLU as the most prevalent in interactions. Subsequently, we analysed the ADMET properties and compared them with the standard values of QikProp. We extended our study for DFT computations with Jaguar and plotted the electrostatic potential, HOMO and LUMO regions, and electron density, followed by a molecular dynamics simulation for 100 ns in water, showing an utterly stable performance, making it a suitable drug candidate. IRESSA is FDA-approved for lung cancer, which shares some pathways with breast cancers, clearing the hurdles of multitargeted drugs against breast and lung cancer. This has the potential to be groundbreaking; however, more studies are needed to concreate IRESSA's role.

Molecular Mimicry Mapping in Streptococcus pneumoniae: Cues for Autoimmune Disorders and Implications for Immune Defense Activation.

Streptococcus pneumoniae contributes to a range of infections, including meningitis, pneumonia, otitis media, and sepsis. Infections by this bacterium have been associated with the phenomenon of molecular mimicry, which, in turn, may contribute to the induction of autoimmunity. In this study, we utilized a bioinformatics approach to investigate the potential for S. pneumoniae to incite autoimmunity via molecular mimicry. We identified 13 S. pneumoniae proteins that have significant sequence similarity to human proteins, with 11 of them linked to autoimmune disorders such as psoriasis, rheumatoid arthritis, and diabetes. Using in silico tools, we predicted the sequence as well as the structural homology among these proteins. Database mining was conducted to establish links between these proteins and autoimmune disorders. The antigenic, non-allergenic, and immunogenic sequence mimics were employed to design and validate an immune response via vaccine construct design. Mimic-based vaccine construct can prove effective for immunization against the S. pneumoniae infections. Immune response simulation and binding affinity was assessed through the docking of construct C8 to human leukocyte antigen (HLA) molecules and TLR4 receptor, with promising results. Additionally, these mimics were mapped as conserved regions on their respective proteins, suggesting their functional importance in S. pneumoniae pathogenesis. This study highlights the potential for S. pneumoniae to trigger autoimmunity via molecular mimicry and the possibility of vaccine design using these mimics for triggering defense response.

Unveiling the multitargeted repurposing potential of taxifolin (dihydroquercetin) in cervical cancer: an extensive MM\GBSA-based screening, and MD simulation study.

Cervical cancer is a significant cause of morbidity and mortality in women worldwide. Despite the availability of effective therapies, the development of drug resistance and adverse side effects remain significant challenges in cervical cancer treatment. Thus, repurposing existing drugs as multitargeted therapies for cervical cancer is an attractive approach. In this study, we extensively screened the complete prepared FDA-approved drugs and identified the repurposing potential of taxifolin, a flavonoid with known antioxidant and anti-inflammatory properties, as a multitargeted therapy for cervical cancer. We performed a computational analysis using molecular docking with various sampling algorithms, namely HTVS, SP, and XP algorithms, for robust sampling pose and filtered with MM/GBSA analysis to determine the binding affinity of taxifolin with potential targets involved in cervical cancer, such as Symmetric Mad2 Dimer, replication initiation factor MCM10-ID, TPX2, DNA polymerase epsilon B-subunit, human TBK1, and alpha-v beta-8. We then conducted MD simulations to investigate the stability and conformational changes of the complex formed between taxifolin and the mentioned proteins. Our results suggest that taxifolin has a high binding affinity ranging from - 6.094 to - 9.558 kcal/mol, indicating its potential as a multitargeted therapy for cervical cancer. Furthermore, interaction fingerprints, pharmacokinetics and MD simulations revealed that the Taxifolin-target complexes remained stable over the simulation period, indicating that taxifolin may bind to the targets for an extended period. Our study suggests that taxifolin has the potential as a multitargeted therapy for cervical cancer, and further experimental studies are necessary to validate our findings.

Unveiling the multitargeted potential of N-(4-Aminobutanoyl)-S-(4-methoxybenzyl)-L-cysteinylglycine (NSL-CG) against SARS CoV-2: a virtual screening and molecular dynamics simulation study.

The coronaviridae family has caused the most destruction among all the viral families in modern sciences. It is one of the recently discovered and added members of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which has caused the global pandemic and significant destruction worldwide. However, scientists worldwide have developed vaccines, which are being given to humans. The mutated strain of the virus has caused various uncertainties about whether the discovered drug and vaccines affect it. Even after the World Health Organization's approval for the vaccines, their effectiveness and protection ratio are still a major concern. At the community level, to this date, there is no medicine available to cure the patients. In this study, we have screened the vast library from Drug Bank and identified N-(4-Aminobutanoyl)-S-(4-methoxybenzyl)-L-cysteinylglycine (NSL-CG) that can work against two major targets of SARS CoV-2, replication-transcription and RNA dependent polymerase. Further, we have performed the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) and molecular dynamics simulation of the compound with both proteins individually, giving us enough evidence that the said drugs can work against the two targets together. Inhibiting the action of any of both proteins may lead to retaining the virus, and having a dual-targeted drug can be an extra precise measure for this process. The NSL-CG is an experimental drug belonging to the peptidomimetics class included in the small group of drugs with a docking score of -9.079 kcal/mol with replication-transcription -7.885 kcal/mol with RNA-dependent polymerase. Hence, through the complete flowed study, the NSL-CG can be further experimentally validated in in-vitro and in-vivo conditions before human utilisation.Communicated by Ramaswamy H. Sarma.

Mining Autoimmune-Disorder-Linked Molecular-Mimicry Candidates in Clostridioides difficile and Prospects of Mimic-Based Vaccine Design: An In Silico Approach.

Molecular mimicry, a phenomenon in which microbial or environmental antigens resemble host antigens, has been proposed as a potential trigger for autoimmune responses. In this study, we employed a bioinformatics approach to investigate the role of molecular mimicry in Clostridioides difficile-caused infections and the induction of autoimmune disorders due to this phenomenon. Comparing proteomes of host and pathogen, we identified 23 proteins that exhibited significant sequence homology and were linked to autoimmune disorders. The disorders included rheumatoid arthritis, psoriasis, Alzheimer's disease, etc., while infections included viral and bacterial infections like HIV, HCV, and tuberculosis. The structure of the homologous proteins was superposed, and RMSD was calculated to find the maximum deviation, while accounting for rigid and flexible regions. Two sequence mimics (antigenic, non-allergenic, and immunogenic) of ≥10 amino acids from these proteins were used to design a vaccine construct to explore the possibility of eliciting an immune response. Docking analysis of the top vaccine construct C2 showed favorable interactions with HLA and TLR-4 receptor, indicating potential efficacy. The B-cell and T-helper cell activity was also simulated, showing promising results for effective immunization against C. difficile infections. This study highlights the potential of C. difficile to trigger autoimmunity through molecular mimicry and vaccine design based on sequence mimics that trigger a defensive response.