Macrophage-Targeted Punicalagin Nanoengineering to Alleviate Methotrexate-Induced Neutropenia: A Molecular Docking, DFT, and MD Simulation Analysis

Unveiling the multitargeted potential of deprodone and control comparison with linezolid against hydrolase and transferase enzymes of methicillin-resistant Staphylococcus aureus

Staphylococcus aureus (S. aureus), commonly found on the skin and nose, causes minor skin conditions to life-threatening diseases, including boils or impetigo, pneumonia, and bloodstream infections. MRSA (Methicillin-Resistant S. aureus) is a strain resistant to many antibiotics and poses a significant challenge in clinical settings. Nowadays, the alternative drug Linezolid is used, and it is not clear when MRSA starts resistance to it, necessitating the need for more alternative drugs with the least chance of developing resistance. This study aims to identify a multitargeted drug candidate with better efficacy than Linezolid. We have taken three hydrolase and transferase proteins from S. aureus, performed the multitargeted docking studies with human-approved drugs, and compared them with the control drug Linezolid. The docking and MM\GBSA scores ranging from -6.79 to -5.78 Kcal/mol and - 37.47 to 30.16 Kcal/mol, respectively, that revealed Deprodone (used for inflammatory skin disorders, bowel disease, and fatty acid metabolism disorders) can be a far better and multitargeted drug candidate than Linezolid. We extended our studies to include extensive pharmacokinetics and molecular interaction fingerprints for interaction pattern studies. Also, the DFT computations optimised the drug, and we extended our studies for MD Simulation in water for 100 ns, which showed the complexes among the identified drug with proteins are entirely stable with acceptable deviation, fluctuations and many intermolecular interactions that make them stable. We also performed the MM\GBSA studies on MD simulation's all 1000 frames to understand the complex energy level. All the results reveal promising interactions between Deprodone and the targeted enzymes, suggesting its potential as a multitargeted therapeutic agent-however, experimental studies need to validate Deprodone against MRSA.

Multitargeted docking approach reveals droxidopa against DNA replication and repair-related protein of cervical cancer

Cervical cancer begins in the cells lining the cervix and is caused by persistent infection with certain types of human papillomavirus (HPV). Initially, it has no symptoms, and later it causes pelvic pain, abnormal vaginal bleeding, and pain during intercourse. It is the fourth-ranked cancer among women, and many women die from cervical cancer every year, particularly in low-income countries and the majority could be prevented with early detection and treatment. In this study, we have taken Cervical Cancer DNA Replication and Repair-Related Protein with the PDBID- 3H15, 5VBN, and 6NT9 and performed the multitargeted molecular docking with the FDA-approved drug library using HTVS, SP and XP docking. Then, the poses were filtered with MM\GBSA for proper computations of free energy, identified a multitargeted inhibitor Droxidopa with docking and MM\GBSA scores ranging from - 5.559 to - 6.835 Kcal/mol and - 26.04 to - 37.33 Kcal/mol, respectively. We also performed interaction fingerprints revealing 2VAL, 2LYS, 1ALA, 1ARG, 1ASN, 1CYS, 1GLN, 1GLU, 1ILE, 1MET, 1PHE, 1PRO, 1SER, and 1THR were most interacted residues and computed the ADMET properties with QikProp and DFT with Jaguar, which supported the study and compounds' suitability. Moreover, we performed the 100ns MD simulation in water, showing the controlled deviation and fluctuations of the residues with many interactions, and MM\GBSA was performed with the same trajectories, showing a better understanding of each frame's total complex and binding-free energy. The whole study favours droxidopa as an inhibitor of cervical cancer DNA Replication and Repair-Related Proteins-however, experimental studies are needed before use.

Unveiling the multitargeted potency of Sodium Danshensu against cervical cancer: a multitargeted docking-based, structural fingerprinting and molecular dynamics simulation study

Cervical Cancer (CC) is one of the most common types of cancer in women worldwide, with a significant number of deaths reported yearly. Despite the various treatment options available, the high mortality rate associated with CC highlights the need to develop new and effective therapeutic agents. In this study, we have screened the complete prepared FDA library against the Mitotic kinesin-like protein 1, Cyclin B1, DNA polymerase, and MCM10-ID using three glide-based molecular docking algorithms: HTVS, SP and XP to produce a robust calculation. All four proteins are crucial proteins that actively participate in CC development, and inhibiting them together can be a game-changer step for multitargeted drug designing. Our multitargeted screening identified Sodium (Na) Danshensu, a natural FDA-approved phenolic compound of caffeic acid derivatives isolated from Salvia miltiorrhiza. The docking score ranges from -5.892 to -13.103 Kcal/mol, and the screening study was evaluated with the pharmacokinetics and interaction fingerprinting to identify the pattern of interactions that revealed that the compound has bound to the best site it can be fitted to where maximum bonds were created to make the complex stable. The molecular dynamics simulations for 100 ns were then extended to validate the stability of the protein-ligand complexes. The results provide insight into the repurposing, and Na-danshensu exhibited strong binding affinity and stable complex formation with the target proteins, indicating its potential as a multitargeted drug against CC.Communicated by Ramaswamy H. Sarma.

Supervised screening of Tecovirimat-like compounds as potential inhibitors for the monkeypox virus E8L protein

Monkeypox virus (MPXV) is a budding public health threat worldwide, and there lacks a personalized drug availability to treat MPXV infections. Tecovirimat, an antiviral drug against pox viruses, is recently confirmed to be effective against the MPXV in vitro using nanomolar concentrations. Therefore, the current study considers Tecovirimat as a reference compound for a machine learning-based guided screening to scan bioactive compounds from the DrugBank with similar chemical features or moieties as the Tecovirimat to inhibit the MPXV E8L surface binding protein. We used AlphaFold2 to model the E8L's 3D structure, followed by the conformational activity investigation of shortlisted drugs through computational structural biology approaches, including molecular docking and molecular dynamics simulations. As a result, we have shortlisted five drugs named ABX-1431, Alflutinib, Avacopan, Caspitant, and Darapalib that effectively engage the MPXV surface binding protein. Furthermore, the affinity of the proposed drugs is relatively higher than the Tecovirimat by having higher docking scores, establishing more hydrogen and hydrophobic bonds, engaging key residues in the target's structure, and exhibiting stable molecular dynamics.Communicated by Ramaswamy H. Sarma.

Harnessing machine learning potential for personalised drug design and overcoming drug resistance

Drug resistance in cancer treatment presents a significant challenge, necessitating innovative approaches to improve therapeutic efficacy. Integrating machine learning (ML) in cancer research is promising as ML algorithms outrival in analysing complex datasets, identifying patterns, and predicting treatment outcomes. Leveraging diverse data sources such as genomic profiles, clinical records, and drug response assays, ML uncovers molecular mechanisms of drug resistance, enabling personalised treatment, maximising efficacy and minimising adverse effects. Various ML algorithms contribute to the drug discovery process - Random Forest and Decision Trees predict drug-target interactions and aid in virtual screening, and SVM classify leads on bioactivity data. Neural Networks model QSAR to optimise lead compounds and K-means clustering group compounds with similar chemical properties aiding compound selection. Gaussian Processes predict drug responses, Bayesian Networks infer causal relationships, Autoencoders generate novel compounds, and Genetic Algorithms optimise molecular structures. These algorithms collectively enhance efficiency and success rates in drug design endeavours, from lead identification to optimisation and are cost-effective, empowering clinicians with real-time treatment monitoring and improving patient outcomes. This review highlights the immense potential of ML in revolutionising cancer care through effective drug design to reduce drug resistance, and we have also discussed various limitations and research gaps to understand better.

Unveiling the potency of FDA-approved oxidopamine HBr for cervical cancer regulation and replication proteins

Cervical Cancer remains a women's health concern worldwide and ranks among the most prevalent cancers, particularly in developing countries. Many women are diagnosed with cervical cancer, with a substantial number succumbing to the disease even after the availability of vaccines and drugs. The tumour microenvironment often exhibits immune evasion, including suppression of T-cell activity and altered cytokine, impacting the efficacy of therapeutic interventions and highlighting the need for treatments to modulate the immune response. Despite efforts to promote HPV vaccination and regular screenings, it causes many deaths, underscoring the urgent need for continued research, healthcare access, and rapid drug development or repurposing. In this study, we identified various proteins involved in cervical cancer cell cycle regulation and DNA replication proteins, performed the multitargeted docking with an FDA-approved library, and identified Oxidopamine HBr as a multitargeted drug. Studies extended with pharmacokinetics and compared with the standard values followed by DFT, which supported the compound as a multitargeted inhibitor. Further, the docked complexes were taken for the interaction fingerprints, and it was identified that there are many 9 polar, 5 hydrophobic, 2 aromatic, and 2 basic residues. We extended our studies for 100ns MD Simulation in water, and the computations explored the deviation and fluctuations under 2Å and many intermolecular interactions; the same trajectory files were used for the MM\GBSA studies. All the studies have supported the Oxidopamine HBr as a cervical cancer multitargeted inhibitor-however, experimental studies are needed before human use.

Unrevealing the multitargeted potency of 3-1-BCMIYPPA against lung cancer structural maintenance and suppression proteins through pharmacokinetics, QM-DFT, and multiscale MD simulation studies

Lung cancer, a relentless and challenging disease, demands unwavering attention in drug design research. Single-target drugs have yielded limited success, unable to effectively address this malignancy's profound heterogeneity and often developed resistance. Consequently, the clarion call for lung cancer drug design echoes louder than ever, and multitargeted drug design emerges as an imperative approach in this landscape, which is done by concurrently targeting multiple proteins and pathways and offering a beacon of hope. This study is focused on the multitargeted drug designing approach by identifying drug candidates against human cyclin-dependent kinase-2, SRC-2 domains of C-ABL, epidermal growth factor and receptor extracellular domains, and insulin-like growth factor-1 receptor kinase. We performed the multitargeted molecular docking studies of Drug Bank compounds using HTVS, SP and XP algorithms and poses filter with MM\GBSA against all proteins and identified DB02504, namely [3-(1-Benzyl-3-Carbamoylmethyl-2-Methyl-1h-Indol-5-Yloxy)-Propyl-]-Phosphonic Acid (3-1-BCMIYPPA) as multitargeted lead with docking and MM\GBSA score range from -8.242 to -6.274 and -28.2 and -44.29 Kcal/mol, respectively. Further, the QikProp-based pharmacokinetic computations and QM-based DFT showed acceptance results against standard values, and interaction fingerprinting reveals that THR, MET, GLY, VAL, LEU, GLU and ASP were among the most interacting residues. The NPT ensemble-based 100ns MD simulation in a neutralised state with an SPC water model has also shown a stable performance and produced deviation and fluctuations <2Å with huge interactions, making it a promising multitargeted drug candidate-however, experimental studies are suggested.

Polyphenol-Rich Extracts from Agroindustrial Waste and Byproducts: Results and Perspectives According to the Green Chemistry and Circular Economy

Polyphenols are natural secondary metabolites found in plants endowed with multiple biological activities (antioxidant, anti-inflammatory, antimicrobial, cardioprotective, and anticancer). In view of these properties, they find many applications and are used as active ingredients in nutraceutical, food, pharmaceutical, and cosmetic formulations. In accordance with green chemistry and circular economy strategies, they can also be recovered from agroindustrial waste and reused in various sectors, promoting sustainable processes. This review described structural characteristics, methods for extraction, biological properties, and applications of polyphenolic extracts obtained from two selected plant materials of the Mediterranean area as olive (Olea europaea L.) and pomegranate (Punica granatum L.) based on recent literature, highlighting future research perspectives.

Identification of 5-nitroindazole as a multitargeted inhibitor for CDK and transferase kinase in lung cancer: a multisampling algorithm-based structural study

Lung cancer is the second most common cancer, which is the leading cause of cancer death worldwide. The FDA has approved almost 100 drugs against lung cancer, but it is still not curable as most drugs target a single protein and block a single pathway. In this study, we screened the Drug Bank library against three major proteins- ribosomal protein S6 kinase alpha-6 (6G77), cyclic-dependent protein kinase 2 (1AQ1), and insulin-like growth factor 1 (1K3A) of lung cancer and identified the compound 5-nitroindazole (DB04534) as a multitargeted inhibitor that potentially can treat lung cancer. For the screening, we deployed multisampling algorithms such as HTVS, SP and XP, followed by the MM\GBSA calculation, and the study was extended to molecular fingerprinting analysis, pharmacokinetics prediction, and Molecular Dynamics simulation to understand the complex's stability. The docking scores against the proteins 6G77, 1AQ1, and 1K3A were - 6.884 kcal/mol, - 7.515 kcal/mol, and - 6.754 kcal/mol, respectively. Also, the compound has shown all the values satisfying the ADMET criteria, and the fingerprint analysis has shown wide similarities and the water WaterMap analysis that helped justify the compound's suitability. The molecular dynamics of each complex have shown a cumulative deviation of less than 2 Å, which is considered best for the biomolecules, especially for the protein-ligand complexes. The best feature of the identified drug candidate is that it targets multiple proteins that control cell division and growth hormone mediates simultaneously, reducing the burden of the pharmaceutical industry by reducing the resistance chance.

Chlordiazepoxide against signalling, receptor and regulatory proteins of breast cancer: a structure-based in-silico approach

Among the most prevalent forms of cancer are breast, lung, colon-rectum, and prostate cancers, and breast cancer is a major global health challenge, contributing to 2.26 million cases with approximately 685,000 deaths worldwide in 2020 alone, typically beginning in the milk ducts or lobules that produce and transport milk during lactation and it is becoming challenging to treat as the tissues are developing resistance, which makes urgent calls for new multitargeted drugs. The multitargeted drug design provides a better solution, simultaneously targeting multiple pathways, even when the drug resists one, it remains effective for others. In this study, we included four crucial proteins that perform signalling, receptor, and regulatory action, namely- NUDIX Hydrolases, Dihydrofolate Reductase, HER2/neu Kinase and EGFR and performed multitargeted molecular docking studies against human-approved drugs using HTVS, SP and extra precise algorithms and filtered the poses with MM\GBSA, suggested a benzodiazepine derivative chlordiazepoxide, used as an anxiolytic agent, can be a multitargeted inhibitor with docking and MM\GBSA score ranging from - 4.628 to - 7.877 and - 18.59 to - 135.86 kcal/mol, respectively, and the most interacted residues were 6ARG, 6GLU, 3TRP, and 3VAL. The QikProp-based ADMET and DFT computations showed the suitability and stability of the drug candidate followed by 100 ns MD simulation in water and MMGBSA on trajectories, resulting in stable performance and many intermolecular interactions to make the complexes stable, which favours that chlordiazepoxide can be a multitargeted breast cancer inhibitor. However, experimental validation is needed before its use.

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.

Structure-based multitargeted docking screening, pharmacokinetics, DFT, and dynamics simulation studies reveal mitoglitazone as a potent inhibitor of cellular survival and stress response proteins of lung cancer

Lung cancer is a disease in which lung cells grow abnormally and uncontrollably, and the cause of it is direct smoking, secondhand smoke, radon, asbestos, and certain chemicals. The worldwide leading cause of death is lung cancer, which is responsible for more than 1.8 million deaths yearly and is expected to rise to 2.2 million by 2030. The most common type of lung cancer is non-small cell lung cancer (NSCLC), which accounts for about 80% and small cell lung cancer (SCLC), which is more aggressive than NSCLC and is often diagnosed later and accounts for 20% of cases. The global concern for lung cancer demands efficient drugs with the slightest chance of developing resistance, and the idea of multitargeted drug designing came up with the solution. In this study, we have performed multitargeted molecular docking studies of Drug Bank compounds with HTVS, SP and XP algorithms followed by MM\GBSA against the four proteins of lung cancer cellular survival and stress responses, which revealed Mitoglitazone as a multitargeted inhibitor with a docking and MM\GBSA score ranging from - 5.784 to - 7.739 kcal/mol and - 25.81 to - 47.65kcal/mol, respectively. Moreover, we performed pharmacokinetics studies and QM-based DFT analysis, showing suitable candidate and interaction pattern analysis revealed the most count of interacting residues was 4GLY, 5PHE, 6ASP, 6GLU, 6LYS, and 6THR. Further, the results were validated with SPC water model-based MD simulation for 100ns in neutralised condition, showing the cumulative deviation and fluctuation < 2Å with many intermolecular interactions. The whole analysis has suggested that Mitoglitazone can be used as a multitargeted inhibitor against lung cancer-however, experimental studies are needed before human use.

Mitoxantrone 2HCl's adroit activity against cervical cancer replication and maintenance proteins: a multitargeted approach

Cervical cancer poses a significant global health challenge, ranking as the fourth most common cancer among women worldwide and resulting in approximately 300,000 deaths yearly, predominantly caused by high-risk human papillomavirus strains (HPV), mainly types 16 and 18. The scenario poses the urgent need of the hour to develop effective treatment strategies that can address the complexity of cervical cancer and multitargeted inhibitor designing that holds promise as it can simultaneously target multiple proteins and pathways involved in its progression and have the potential to enhance treatment efficacy, reduce the likelihood of drug resistance. In this study, we have performed multitargeted molecular docking of FDA-approved drugs against cervical cancer replication and maintenance proteins- Xenopus kinesin-like protein-2 (3KND), cell division cycle protein-20 (4N14), MCM2-histone complex (4UUZ) and MCM6 Minichromosome maintenance (2KLQ) with HTVS, SP and XP algorithms and have obtained the docking and MM\GBSA score ranging from -8.492 to -5.189 Kcal/mol and -58.16 to -39.07 Kcal/mol. Further, the molecular interaction fingerprints identified ALA, THR, SER, ASN, LEU, and ILE were among the most interacted residues, leaning towards hydrophobic and polar amino acids. The pharmacokinetics and DFT of the compound have shown promising results. The complexes were simulated for 100 ns to study the stability by computing the deviation, fluctuations, and intermolecular interactions formed during the simulation. This study produced promising results, satisfying the criteria that Mitoxantrone 2HCl can be a multitargeted inhibitor against cervical cancer proteins-however, experimental validation is a must before human use.Communicated by Ramaswamy H. Sarma.

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.

Delineated 3-1-BenCarMethInYlPro-Phosphonic Acid's Adroit Activity against Lung Cancer through Multitargeted Docking, MM\GBSA, QM-DFT and Multiscale Simulations

Lung cancer is a pervasive and challenging disease with limited treatment options, with global health challenges often present with complex molecular profiles necessitating the exploration of innovative therapeutic strategies. Single-target drugs have shown limited success due to the heterogeneity of this disease. Multitargeted drug designing is imperative to combat this complexity by simultaneously targeting multiple target proteins and pathways, which can enhance treatment efficacy and overcome resistance by addressing the dynamic nature of the disease and stopping tumour growth and spread. In this study, we performed the molecular docking studies of Drug Bank compounds with a multitargeted approach against crucial proteins of lung cancer such as heat shock protein 5 (BIP/GRP78) ATPase, myosin 9B RhoGAP, EYA2 phosphatase inhibitor, RSK4 N-terminal kinase, and collapsin response mediator protein-1 (CRMP-1) using HTVS, SP with XP algorithms, and poses were filtered using MM\GBSA which identified [3-(1-Benzyl-3-Carbamoylmethyl-2-Methyl-1h-Indol-5-Yloxy)-Propyl-]-Phosphonic Acid (3-1-BenCarMethIn YlPro-Phosphonic Acid) (DB02504) as multitargeted drug candidate with docking and MM\GBSA score ranges from -5.83 to -10.66 and -7.56 to -50.14 Kcal/mol, respectively. Further, the pharmacokinetic and QM-based DFT studies have shown complete acceptance results, and interaction fingerprinting reveals that ILE, GLY, VAL, TYR, LEU, and GLN were among the most interacting residues. The 100 ns MD simulation in the SPC water model with NPT ensemble showed stable performance with deviation and fluctuations <2 Å with huge interactions, making it a promising multitargeted drug candidate; however, experimental studies are needed before use.

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.

Delineating Pixantrone Maleate's adroit activity against cervical cancer proteins through multitargeted docking-based MM\GBSA, QM-DFT and MD simulation

Cervical cancer poses a substantial worldwide health challenge, especially in low- and middle-income nations, caused by high-risk types of human papillomavirus. It accounted for a significant percentage of cancer-related deaths among women, particularly in areas with limited healthcare resources, necessitating innovative therapeutic approaches, and single-targeted studies have produced significant results, with a considerable chance of developing resistance. Therefore, the multitargeted studies can work as a beacon of hope. This study is focused on performing the multitargeted molecular docking of FDA-approved drugs with the three crucial proteins TBK1, DNA polymerase epsilon, and integrin α-V β-8 of cervical cancer. The docking studies using multisampling algorithms HTVS, SP, and XP reveal Pixantrone Maleate (DB06193) as a multitargeted inhibitor with docking scores of -8.147, -8.206 and -7.31 Kcal/mol and pose filtration with MM\GBSA computations with scores -40.55, -33.67, and -37.64 Kcal/mol. We also have performed QM-based DFT and pharmacokinetics studies of the compound and compared it with the standard values, which results in the compound being entirely suitable against cervical cancer proteins. The interaction fingerprints have revealed that PHE, VAL, SER and ALA are the residues among most interactions. We also explore the stability of the multitargeted potential of Pixantrone Maleate through 100ns MD simulations and investigate the RMSD, RMSF and intermolecular interactions between all three proteins-ligand complexes. All computational studies favour Pixantrone Maleate as a multitargeted inhibitor of the TBK1, DNA polymerase epsilon, and integrin α-V β-8 and can be validated experimentally before use.

Design of new Mcl-1 inhibitors for cancer using fragments hybridization, molecular docking, and molecular dynamics studies

Apoptosis is a critical process that regulates cell survival and death and plays an essential role in cancer development. The Bcl-2 protein family, including myeloid leukemia 1 (Mcl-1), is a key regulator of the intrinsic apoptosis pathway, and its overexpression in many human cancers has prompted efforts to develop Mcl-1 inhibitors as potential anticancer agents. In this study, we aimed to design new Mcl-1 inhibitors using various computational techniques. First, we used the Mcl-1 receptor-ligand complex to build an e-pharmacophore hypothesis and screened a library of 567,000 fragments from the Enamine database. We obtained 410 fragments and used them to design 92,384 novel compounds, which we then docked into the Mcl-1 binding cavity using HTVS, SP, and XP docking modes of Glide. To assess their suitability as drug candidates, we conducted MM-GBSA calculations and ADME prediction, leading to the identification of 10 compounds with excellent binding affinity and favorable pharmacokinetic properties. To further investigate the interaction strength, we performed molecular dynamics simulations on the top three Mcl-1 receptor-ligand complexes to study their interaction stability. Overall, our findings suggest that these compounds have promising potential as anticancer agents, pending further experimental validation such as Mcl-1 apoptosis Assay. By combining experimental methods with various in silico approaches, these techniques prove to be invaluable for identifying novel drug candidates with distinct therapeutic applications using fragment-based drug design. This methodology has the potential to expedite the drug discovery process while also reducing its costs.Communicated by Ramaswamy H. Sarma.

Multitargeted inhibitory effect of Mitoxantrone 2HCl on cervical cancer cell cycle regulatory proteins: a multitargeted docking-based MM\GBSA and MD simulation study

Cervical cancer remains a significant global health concern that starts in the cervix, the lower part of the uterus that connects to the vagina and is caused by the human papillomavirus (HPV), necessitating the development of effective multitargeted effective and resistance-proof therapies. In early-stage cervical cancer may not show any symptoms, however, as the cancer progresses, some people may experience- abnormal vaginal bleeding, watery or bloody vaginal discharge, pain in the pelvis or lower back, pain during sex, and frequent and painful urination. In this study, we screened the complete FDA-approved drug library using a multitargeted inhibitory approach against four cervical cancer proteins, namely mitotic arrest deficient -2, DNA polymerase epsilon B-subunit, benzimidazole-related -1, and threonine-protein kinase-1 which crucially plays its role for the in its development process. We employed the HTVS, SP and XP algorithms for efficient filtering and screening that helped to identify Mitoxantrone 2HCl against all of them with docking and MM\GBSA scores ranging from - 11.63 to - 7.802 kcal/mol and - 74.38 to - 47.73 kcal/mol, respectively. We also evaluated the interaction patterns of each complex and the pharmacokinetics properties that helped gain insight into interactions. Subsequently, we performed multiscale MD simulations for 100 ns to understand the dynamic behaviour and stability of the Mitoxantrone 2HCl -protein complexes that revealed the formation of stable drug-protein complexes and provided insights into the molecular interactions that contribute to Mitoxantrone's inhibitory effects on these proteins and can be a better drug for cervical cancer. However, experimental studies of these findings could pave the way for therapies to combat cervical cancer effectively.

PheroxyPyrabenz and Carbopyrropyridin against major proteins of SARS CoV-2: a comprehensive in-silico molecular docking and dynamics simulation studies

The pandemic that started in 2020 left us with so much information about viruses and respiratory diseases, and the cause behind it was severe acute respiratory syndrome coronavirus-2 (SARS CoV-2). The world is still recovering, which costs so many economic and other indirect disasters; despite that, no medications are available on the market. Although the WHO approved a few vaccines on an emergency basis, the remarks and the reinfection chances are still under investigation, and a few pharmaceutical companies are also claiming that a few medications can be effective. However, there is no situation in control. SARS CoV-2 mutates and comes in different forms, making the situation unpredictable. In this study, we have screened the complete Asinex's BioDesign library, which contains 170,269 compounds, and shorted the data against the docking score that helps in the identification of 4-[5-(3-Ethoxy-4-hydroxyphenyl)-1-(2-hydroxyethyl)-1H-pyrazol-3-yl]-1, 2-benzenediol (PheroxyPyrabenz) and 1-[(3R,4R)-1-(5-Aminopentanoyl)-4-hydroxy-3-pyrrolidinyl]-1H-pyrrolo[2,3-b]pyridine-4-carboxamide (Carbopyrropyridin) as a significant drug candidate that can work against the multiple proteins of the SARS CoV-2 resulting in seizing the complete biological process of the virus. Further, the study extended to Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) and molecular dynamics (MD) simulation of both the compounds with their complexity. The complete workflow of the study has shown satisfactory results, and both drug candidates can potentially stop the hunt for drugs against this virus after its experimental validation. Further, we checked both compounds' absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, showing case-proof validatory results.Communicated by Ramaswamy H. Sarma.

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.

Theoretical aspects of interaction of the anticancer drug cytarabine with human serum albumin

Despite diagnostic and therapeutic methods, cancer is a major cause of death worldwide. Since anticancer drugs affect both normal and cancer cells, targeted drug delivery systems can play a key role in reducing the destructive effects of anticancer drugs on normal cells. In this regard, the use of stimulus-sensitive polymers has increased in recent years. This study has attempted to investigate interaction of the anticancer drug cytarabine with a stimuli-sensitive polymer, human serum albumin (HSA), one of the most abundant protein in blood plasma, via computational methods at both body temperature and tumor temperature. For this purpose, molecular docking was performed using Molegro virtual Docker software to select the best ligand in terms of binding energy to simulate molecular dynamics. Then, molecular dynamics simulation was performed on human serum albumin with code (1Ao6) and cytarabine with code (AR3), using Gromacs software and the results were presented in the graphs. The simulations were performed at 310 K (normal cell temperature) and 313 K (cancer cell temperature) in 100 ns. Results showed drug release occurred at a temperature of 313 K. These findings demonstrated the sensitivity of human serum albumin to temperature.

Molecular docking, ADMET and molecular dynamics simulation revealed metralindole as a multitargeted inhibitor for division kinases

Lung cancer is the most common type of cancer in the world, and alone, in 2020, almost 2.21 million new cases were diagnosed, with 1.80 million deaths, and are increasing daily. Non-small cell lung (NSCLC) is the primary type of lung cancer, predominantly forms around 80% of cases compared to small cell carcinoma, and about 75% of patients are already in an advanced state when diagnosed. Despite notable advances in early diagnosis and treatment, the five-year survival rate for NSCLC is not encouraging. Therefore, it is crucial to investigate the molecular causes of non-small cell lung cancer to create more efficient therapeutic approaches. Lung cancer showed a more significant and persistent binding affinity and energy landscape with the target CDK2 staurosporine and FGF receptor-1. In this study, we have picked two essential target proteins, human cyclin-dependent kinase-2 and Human Protein Kinase CK2 Holoenzyme and screened the entire prepared DrugBank prepared library of 1,55,888 compounds and identified 2-(2-methyl-5-nitroimidazole-1-yl) ethanol (Metralindole) as a major inhibitor. Metralindole has displayed high docking scores of -5.159 Kcal/mol and -5.99 Kcal/mol with good hydrogen bonding and other bonding topologies such as van der Waals force, and ADMET results shown excellent bioavailability, outstanding solubility, no side effects, and toxicity. The molecular dynamics simulation for 100ns in a water medium confirmed the compound's stability and interaction pattern with the lowest deviation and fluctuations. Our in-silico study suggests Metralindole, an experimental compound, can effectively cure lung cancer. Further, the experimental validation of the compound is a must before any prescription.

Molecular docking analysis of mefluhybenamine with lung cancer targets

Lung cancer is the most prevalent type of cancer worldwide, with 2.21 million cases and 1.80 million fatalities in 2020. The main factor influencing lung cancer is smoking, and the most common form of lung cancer, non-small cell lung cancer (NSCLC), accounts for around 80% of instances compared to small cell carcinoma, and about 75% of patients are already in an advanced stage when they are detected. Despite significant early detection and therapy improvements, the five-year survival rate for NSCLC is not encouraging. Therefore, it is essential to look into the molecular origins of non-small cell lung cancer to develop more effective therapeutic strategies-the binding affinities and energy landscape with the proteins. Cyclin Dependent kinase 2 (CDK2) and Insulin-like Growth Factor 1 Receptor (IGF1) were more substantial and sustained in lung cancer that was chosen as the two primary target proteins in this. We screened the entire Drug Bank-prepared library of 1,55,888 compounds and found (2R,3R)-7-(Methylsulfonyl)-3-(2,4,5-trifluorophenyl) -1,2,3,4-tetrahydropyrido[1,2-a] benzimidazol-2-aminium (Mefluhybenamine) to be a significant inhibitor. Mefluhybenamine showed strong hydrogen bonding and other bonding topologies, such as van der Waals force, in its high docking scores of -6.168 Kcal/mol and -5.26 Kcal/mol, and ADMET results showed excellent bioavailability, remarkable solubility, no side effects, and toxicity. The molecular dynamicsimulation confirmed the compound's stability and interaction pattern for 100 ns in an SPC water medium with the slightest deviation and fluctuation. Data shows that Mefluhybenamine is a potential candidate. However, validation of the compound is essential.

Antioxidant and Cytotoxic Activity of New Polyphenolic Derivatives of Quinazolin-4(3H)-one: Synthesis and In Vitro Activities Evaluation

The development of hybrid molecules with significant human therapeutic properties is one of the main approaches of pharmaceutical research. One of the most important pharmacophores is the quinazolin-4(3H)-one heterocycle moiety, due to its wide range of biological activities. By its derivatization with polyphenolic compounds, in our previous research, it proved to possess a good antiradical activity of ortho-diphenolic derivatives of quinazolin-4(3H)-one. In this study, we developed two new series of compounds, with an additional phenolic group or with a methyl group on the thioacetohydrazone fragment. The methods used to evaluate the activity of the compounds were radical scavenging, reduction of oxidizing reagents and transition metals' ions chelation assays. Quantum descriptors were also calculated in order to evaluate the influence of substituents and their position on the activity of the compounds. The cytotoxic activity was evaluated using normal human foreskin fibroblast cells (BJ) and two cancerous cell lines, lung adenocarcinoma cells (A549) and prostate carcinoma cells (LNCaP). The results obtained for the pyrogallol derivatives showed a high antioxidant activity compared to ascorbic acid and Trolox. All the synthesized compounds displayed a higher cytotoxicity against the cancerous cell types and a high cytocompatibility with the normal cells. The antioxidant activity was deeply influenced by the addition of the third phenolic group in the synthesized molecules.

Oxalactam A, a Novel Macrolactam with Potent Anti-Rhizoctonia solani Activity from the Endophytic Fungus Penicillium oxalicum

A novel macrolactam named oxalactam A (1), three known dipeptides (2-4) as well as other known alkaloids (5-7) were obtained from the endophytic fungus Penicillium oxalicum, which was derived from the tuber of Icacina trichantha (Icacinaceae). All chemical structures were established based on spectroscopic data, chemical methods, ECD calculations, and ¹³C-DP4+ analysis. Among them, oxalactam A (1) is a 16-membered polyenic macrolactam bearing a new skeleton of 2,9-dimethyl-azacyclohexadecane core and exhibited potent anti-Rhizoctonia solani activity with a MIC value of 10 μg/mL in vitro. The plausible biosynthetic pathway of 1 was also proposed via the alanyl protecting mechanism. Notably, three dipeptides (2-4) were first identified from the endophytic fungus P. oxalicum and the NMR data of cyclo(L-Trp-L-Glu) (2) was reported for the first time. In addition, the binding interactions between compound 1 and the sterol 14α-demethylase enzyme (CYP51) were studied by molecular docking and dynamics technologies, and the results revealed that the 16-membered polyenic macrolactam could be a promising CYP51 inhibitor to develop as a new anti-Rhizoctonia solani fungicide.