Screening for Antibiotic Resistance Genes in Bacteria and the Presence of Heavy Metals in the Upstream and Downstream Areas of the Wadi Hanifah Valley in Riyadh, Saudi Arabia.

Valley surface water is considered a focal public health concern owing to the presence of multi-drug-resistant bacteria. The distribution of antimicrobial resistance (AMR) bacteria in the surface water is affected by the presence of multiple factors, including antibiotics coming from wastewater discharge or other contaminant sources such as pharmaceuticals, biocides, and heavy metals. Furthermore, there is evidence suggesting that high levels of antibiotic resistance genes (ARGs) can be transferred within bacterial communities under the influence of heavy metal stress. Hence, the primary aim of this study is to investigate the presence of heavy metals and bacterial ARGs in upstream as well as downstream locations of Wadi Hanifah Valley in Riyadh, Saudi Arabia. Sample collection was conducted at eighteen surface water sites within the valley in total. The selection of ARGs was associated with the most common antibiotics, including ß-lactam, tetracycline, erythromycin, gentamicin, sulphonamide, chloramphenicol, vancomycin, trimethoprim, and colistin antibiotics, which were detected qualitatively using polymerase chain reaction (PCR) technology. The tested antibiotic resistance genes (ARGs) included (blaNDM-1 (for the antibiotic class Beta-lactamases), mecA (methicillin-resistant Staphylococcus aureus), tet(M) and tet(B) (for the antibiotic class Tetracycline), ampC (for the antibiotic class Beta-lactamases), vanA (for the antibiotic class vancomycin), mcr-1 (for the antibiotic class colistin), erm(B) (for the antibiotic class erythromycin), aac6'-Ie-aph2-Ia (for the antibiotic class Gentamicin), sulII (for the antibiotic class sulphonamide), catII (for the antibiotic class Chlorophincol), and dfrA1 (for the antibiotic class trimethoprim). Moreover, an assessment of the levels of heavy metals such as lithium (Li), beryllium (Be), chromium (Cr), cobalt (Co), arsenic (As), cadmium (Cd), tin (Sn), mercury (Hg), and lead (Pb) was conducted by using inductively coupled plasma mass spectrometry (ICPMS). According to our findings, the concentrations of sulphonamide, erythromycin, and chloramphenicol ARGs (erm(B), sulII, and catII) were observed to be the most elevated. Conversely, two ARGs, namely mecA and mcr-1, were not detected in the samples. Moreover, our data illustrated a significant rise in ARGs in the bacteria of water samples from the upstream sites as compared with the water samples from the downstream sites of Wadi Hanifah Valley. The mean concentration of Li, Be, Cr, Co, As, Cd, Sn, Hg, and Pb in the water samples was estimated to be 37.25 µg/L, 0.02 µg/L, 0.56 µg/L,0.32 µg/L, 0.93 µg/L, 0.01 µg/L, 200.4 µg/L, 0.027 µg/L, and 0.26 µg/L, respectively, for the selected 18 sites. Furthermore, it was revealed that the concentrations of the screened heavy metals in the water samples collected from various sites did not surpass the maximum limits set by the World Health Organization (WHO). In conclusion, this study offers a concise overview of the presence of heavy metals and ARGs in water samples obtained from the Wadi Hanifah Valley in Riyadh, KSA. Such findings will contribute to the ongoing monitoring and future risk assessment of ARGs spread in surface water.

Role of small molecules as drug candidates for reprogramming somatic cells into induced pluripotent stem cells: A comprehensive review.

With the use of specific genetic factors and recent developments in cellular reprogramming, it is now possible to generate lineage-committed cells or induced pluripotent stem cells (iPSCs) from readily available and common somatic cell types. However, there are still significant doubts regarding the safety and effectiveness of the current genetic methods for reprogramming cells, as well as the conventional culture methods for maintaining stem cells. Small molecules that target specific epigenetic processes, signaling pathways, and other cellular processes can be used as a complementary approach to manipulate cell fate to achieve a desired objective. It has been discovered that a growing number of small molecules can support lineage differentiation, maintain stem cell self-renewal potential, and facilitate reprogramming by either increasing the efficiency of reprogramming or acting as a genetic reprogramming factor substitute. However, ongoing challenges include improving reprogramming efficiency, ensuring the safety of small molecules, and addressing issues with incomplete epigenetic resetting. Small molecule iPSCs have significant clinical applications in regenerative medicine and personalized therapies. This review emphasizes the versatility and potential safety benefits of small molecules in overcoming challenges associated with the iPSCs reprogramming process.

Novel drug discovery: Advancing Alzheimer's therapy through machine learning and network pharmacology.

Alzheimer's disease (AD), marked by tau tangles and amyloid-beta plaques, leads to cognitive decline. Despite extensive research, its complex etiology remains elusive, necessitating new treatments. This study utilized machine learning (ML) to analyze compounds with neuroprotective potential. This approach exposed the disease's complexity and identified important proteins, namely MTOR and BCL2, as central to the pathogenic network of AD. MTOR regulates neuronal autophagy and survival, whereas BCL2 regulates apoptosis, both of which are disrupted in AD. The identified compounds, including Armepavine, Oprea1_264702,1-cyclopropyl-7-fluoro-8-methoxy-4-oxoquinoline-3-carboxylic acid,(2S)-4'-Hydroxy-5,7,3'-trimethoxyflavan,Oprea1_130514,Sativanone,5-hydroxy-7,8-dimethoxyflavanone,7,4'-Dihydroxy-8,3'-dimethoxyflavanone,N,1-dicyclopropyl-6,Difluoro-Methoxy-Gatifloxacin,6,8-difluoro-1-(2-fluoroethyl),1-ethyl-6-fluoro-7-(4-methylpiperidin-1-yl),Avicenol C, demonstrated potential modulatory effects on these proteins. The potential for synergistic effects of these drugs in treating AD has been revealed via network pharmacology. By targeting numerous proteins at once, these chemicals may provide a more comprehensive therapeutic approach, addressing many aspects of AD's complex pathophysiology. A Molecular docking, dynamic simulation, and Principle Component Analysis have confirmed these drugs' efficacy by establishing substantial binding affinities and interactions with important proteins such as MTOR and BCL2. This evidence implies that various compounds may interact within the AD pathological framework, providing a sophisticated and multifaceted therapy strategy. In conclusion, our study establishes a solid foundation for the use of these drugs in AD therapy. Thus current study highlights the possibility of multi-targeted, synergistic therapeutic approaches in addressing the complex pathophysiology of AD by integrating machine learning, network pharmacology, and molecular docking simulations. This holistic technique not only advances drug development but also opens up new avenues for developing more effective treatments for this difficult and widespread disease.

Subtractive proteomics-guided vaccine targets identification and designing of multi-epitopes vaccine for immune response instigation against Burkholderia pseudomallei.

In this study, a methodical workflow using subtractive proteomics, vaccine designing, molecular simulation, and agent-based modeling approaches were used to annotate the whole proteome of Burkholderia pseudomallei (strain K96243) for vaccine designing. Among the total 5717 proteins in the whole proteome, 505 were observed to be essential for the pathogen's survival and pathogenesis predicted by the Database of Essential Genes. Among these, 23 vaccine targets were identified, of which fimbrial assembly chaperone (Q63UH5), Outer membrane protein (Q63UH1), and Hemolysin-like protein (Q63UE4) were selected for the subsequent analysis based on the systematic approaches. Using immunoinformatic approaches CTL (cytotoxic T lymphocytes), HTL (helper T lymphocytes), IFN-positive, and B cell epitopes were predicted for these targets. A total of 9 CTL epitopes were added using the GSS linker, 6 HTL epitopes using the GPGPG linker, and 6 B cell epitopes using the KK linker. An adjuvant was added for enhanced antigenicity, an HIV-TAT peptide for improved delivery, and a PADRE sequence was added to form a 466 amino acids long vaccine construct. The construct was classified as non-allergenic, highly antigenic, and experimentally feasible. Molecular docking results validated the robust interaction of MEVC with immune receptors such as TLR2/4. Furthermore, molecular simulation revealed stable dynamics and compact nature of the complexes. The binding free energy results further validated the robust binding. In silico cloning, results revealed GC contents of 50.73 % and a CIA value of 0.978 which shows proper downstream processing. Immune simulation results reported that after the three injections of the vaccine a robust secondary immune response, improved antigen clearance, and effective immune memory generation were observed highlighting its potential for effective and sustained immunity. Future directions should encompass experimental validations, animal model studies, and clinical trials to substantiate the vaccine's efficacy, safety, and immunogenicity.

Efficiency of magnesium oxide nanoparticle in contaminants removal from environmental water samples: Optimization through central composite design.

This experimental study was conducted to synthesize magnesium oxide (MgO) nanoparticles and investigate their efficiency in removing arsenic, brilliant cresyl blue, and neutral red from aqueous solutions. The MgO nanoparticles were characterized using X-ray diffraction (XRD), energy dispersive X-ray (EDS), Fourier-transform infrared spectroscopy (FTIR), and field emission scanning electron microscopy (FESEM) analyses. The results revealed that the synthesized MgO nanoparticles had a spherical structure with an estimated average size of approximately 30 nm. The influence of solution pH, concentration, adsorbent amount, type of eluent, and interference of interfering ions was examined and optimized for removing arsenic, brilliant cresyl blue, and neutral red. The optimal conditions for the removal process were determined as pH of 7, MgO amount of 0.037 g, ultrasonication time of 16 min, and concentration of 25 mg L-1. The experimental removal efficiencies of arsenic, brilliant cresyl blue, and neutral red in aqueous samples ranged from 88.49% to 96.03%. The results of eluent selection showed that ethanol had the highest removal efficiency of analytes from the absorbent surface. The reusability of the MgO adsorbent demonstrated its effective use for the continuous removal of arsenic, brilliant cresyl blue, and neutral red for at least four consecutive cycles. Overall, the results suggest that MgO nanoparticles could be an effective and cost-efficient adsorbent for removing arsenic, brilliant cresyl blue, and neutral red from real samples.

Exploring bi-carbazole-linked triazoles as inhibitors of prolyl endo peptidase via integrated in vitro and in silico study.

A serine protease called prolyl endopeptidase (PEP) hydrolyses the peptide bonds on the carboxy side of the proline ring. The excessive PEP expression in brain results in neurodegenerative illnesses like dementia, Alzheimer's disease, and Parkinson's disease. Results of the prior studies on antioxidant activity, and the non-cytotoxic effect of bi-carbazole-linked triazoles, encouraged us to extend our studies towards its anti-diabetic potential. Hence, for this purpose all compounds 1-9 were evaluated to reveal their anti-prolyl endo peptidase activity. Fortunately, seven compounds resulted into significant inhibitory capability ranging from 26 to 63 µM. Among them six compounds 4-9 exhibited more potent inhibitory activity with IC50 values 46.10 ± 1.16, 42.30 ± 1.18, 37.14 ± 1.21, 26.29 ± 0.76, 28.31 ± 0.64 and 31.11 ± 0.84 µM respectively, while compound 3 was the least active compound in the series with IC50 value 63.10 ± 1.58 µM comparing with standard PEP inhibitor bacitracin (IC50 = 125 ± 1.50 µM). Moreover, mechanistic study was performed for the most active compounds 7 and 8 with Ki values 24.10 ± 0.0076 and 23.67 ± 0.0084 µM respectively. Further, the in silico studies suggested that the compounds exhibited potential interactions and significant molecular conformations, thereby elucidating the structural basis for their inhibitory effects.

Revolutionizing and identifying novel drug targets in Citrobacter koseri via subtractive proteomics and development of a multi-epitope vaccine using reverse vaccinology and immuno-informatics.

Citrobacter koseri is a gram-negative rod that has been linked to infections in people with significant comorbidities and immunocompromised immune systems. It is most commonly known to cause urinary tract infections. Thus, the development of an efficacious C. koseri vaccine is imperative, as the pathogen has acquired resistance to current antibiotics. Subtractive proteomics was employed during this research to identify potential antigenic proteins to design an effective vaccine against C. koseri. The pipeline identified two antigenic proteins as potential vaccine targets: DP-3-O-acyl-N-acetylglucosamine deacetylase and Arabinose 5-phosphate isomerase. B and T cell epitopes from the specific proteins were forecasted employing several immunoinformatic and bioinformatics resources. A vaccine was created using a combination of seven cytotoxic T cell lymphocytes (CTL), five helper T cell lymphocyte (HTL), and seven linear B cell lymphocyte (LBL) epitopes. An adjuvant (ß-defensin) was added to the vaccine to enhance immunological responses. The created vaccine was stable for use in humans, highly antigenic, and non-allergenic. The vaccine's molecular and interactions binding affinity with the human immunological receptor TLR3 were studied using MMGBSA, molecular dynamics (MD) simulations, and molecular docking analyses. E. coli (strain-K12) plasmid vector pET-28a (+) was used to examine the ability of the vaccine to be expressed. The vaccine shows great promise in terms of developing protective immunity against diseases, based on the results of these computer experiments. However, in vitro and animal research are required to validate our findings.Communicated by Ramaswamy H. Sarma.

Immunoinformatics-driven In silico vaccine design for Nipah virus (NPV): Integrating machine learning and computational epitope prediction.

The Nipah virus (NPV) is a highly lethal virus, known for its significant fatality rate. The virus initially originated in Malaysia in 1998 and later led to outbreaks in nearby countries such as Bangladesh, Singapore, and India. Currently, there are no specific vaccines available for this virus. The current work employed the reverse vaccinology method to conduct a comprehensive analysis of the entire proteome of the NPV virus. The aim was to identify and choose the most promising antigenic proteins that could serve as potential candidates for vaccine development. We have also designed B and T cell epitopes-based vaccine candidate using immunoinformatics approach. We have identified a total of 5 novel Cytotoxic T Lymphocytes (CTL), 5 Helper T Lymphocytes (HTL), and 6 linear B-cell potential antigenic epitopes which are novel and can be used for further vaccine development against Nipah virus. Then we performed the physicochemical properties, antigenic, immunogenic and allergenicity prediction of the designed vaccine candidate against NPV. Further, Computational analysis indicated that these epitopes possessed highly antigenic properties and were capable of interacting with immune receptors. The designed vaccine were then docked with the human immune receptors, namely TLR-2 and TLR-4 showed robust interaction with the immune receptor. Molecular dynamics simulations demonstrated robust binding and good dynamics. After numerous dosages at varied intervals, computational immune response modeling showed that the immunogenic construct might elicit a significant immune response. In conclusion, the immunogenic construct shows promise in providing protection against NPV, However, further experimental validation is required before moving to clinical trials.

Structural and molecular investigation of the impact of S30L and D88N substitutions in G9R protein on coupling with E4R from Monkeypox virus (MPXV).

Understanding the pathogenesis mechanism of the Monkeypox virus (MPXV) is essential to guide therapeutic development against the Monkeypox virus. In the current study, we investigated the impact of the only two reported substitutions, S30L, D88N, and S30L-D88N on the G9R of the replication complex in 2022 with E4R using structural modeling, simulation, and free energy calculation methods. From the molecular docking and dissociation constant (KD) results, it was observed that the binding affinity did not increase in the mutants, but the interaction paradigm was altered by these substitutions. Molecular simulation data revealed that these mutations are responsible for destabilization, changes in protein packing, and internal residue fluctuations, which can cause functional variance. Additionally, hydrogen bonding analysis revealed that the estimated number of hydrogen bonds are almost equal among the wild-type G9R and each mutant. The total binding free energy for the wild-type G9R with E4R was -85.00 kcal/mol while for the mutants the TBE was -42.75 kcal/mol, -43.68 kcal/mol, and -48.65 kcal/mol respectively. This shows that there is no direct impact of these two reported mutations on the binding with E4R, or it may affect the whole replication complex or any other mechanism involved in pathogenesis. To explore these variations further, we conducted PCA and FEL analyses. Based on our findings, we speculate that within the context of interaction with E4R, the mutations in the G9R protein might be benign, potentially leading to functional diversity associated with other proteins.Communicated by Ramaswamy H. Sarma.

Exploring potent aldose reductase inhibitors for anti-diabetic (anti-hyperglycemic) therapy: integrating structure-based drug design, and MMGBSA approaches.

Aldose reductase (AR) is an important target in the development of therapeutics against hyper-glycemia-induced health complications such as retinopathy, etc. In this study, we employed a combination of structure-based drug design, molecular simulation, and free energy calculation approaches to identify potential hit molecules against anti-diabetic (anti-hyperglycemic)-induced health complications. The 3D structure of aldoreductase was screened for multiple compound libraries (1,00,000 compounds) and identified as ZINC35671852, ZINC78774792 from the ZINC database, Diamino-di nitro-methyl dioctyl phthalate, and Penta-o-galloyl-glucose from the South African natural compounds database, and Bisindolylmethane thiosemi-carbazides and Bisindolylme-thane-hydrazone from the Inhouse database for this study. The mode of binding interactions of the selected compounds later predicted their aldose reductase inhibitory potential. These com-pounds interact with the key active site residues through hydrogen bonds, salt bridges, and π-π interactions. The structural dynamics and binding free energy results further revealed that these compounds possess stable dynamics with excellent binding free energy scores. The structures of the lead inhibitors can serve as templates for developing novel inhibitors, and in vitro testing to confirm their anti-diabetic potential is warranted. The current study is the first to design small molecule inhibitors for the aldoreductase protein that can be used in the development of therapeutic agents to treat diabetes.

Identification of potential inhibitors targeting Ebola virus VP35 protein: a computational strategy.

Ebola virus (EBOV) poses a severe threat as a highly infectious pathogen, causing devastating hemorrhagic fever in both humans and animals. The EBOV virus VP35 protein plays a crucial role in viral replication and exhibits the ability to suppress the host interferon cascade, leading to immune system depletion. As a potential drug target, VP35 protein inhibition holds promise for combating EBOV. To discover new drug candidates, we employed a computer-aided drug design approach, focusing on compounds capable of inhibiting VP35 protein replication. In this connection, a pharmacophore model was generated using molecular interactions between the VP35 protein and its inhibitor. ZINC and Cambridge database were screened using validated pharmacophore model. Further the compounds were filtered based on Lipinski's rule of five and subjected to MD simulation and relative binding free energy calculation. Six compounds manifest a significant docking score and strong binding interaction towards VP35 protein. MD simulations further confirmed the remarkable stability of these six complexes. Relative binding free energy calculations also showed significant ΔG value in the range of -132.3 and -49.3 kcal/mol. This study paves the way for further optimization of these compounds as potential inhibitors of VP35, facilitating subsequent experimental in vitro studies.Communicated by Ramaswamy H. Sarma.

From seeds to survival rates: investigating Linum usitatissimum's potential against ovarian cancer through network pharmacology.

Ovarian cancer is a malignant tumor that primarily forms in the ovaries. It often goes undetected until it has spread to the pelvis and abdomen, making it more challenging to treat and often fatal. Historically, natural products and their structural analogues have played a pivotal role in pharmacotherapy, especially for cancer. Numerous studies have demonstrated the therapeutic potential of Linum usitatissimum against ovarian cancer, but the specific molecular mechanisms remain elusive. This study combines data mining, network pharmacology, and molecular docking analysis to pioneer an innovative approach for ovarian cancer treatment by identifying potent phytochemicals. Findings of current study revealed that Apigenin, Vitamin E, Palmitic acid, Riboflavin, Isolariciresinol, 5-Dehydro-avenasterol, Cholesterol, Pantothenic acid, Nicotinic acid, Campesterol, Beta-Sitosterol, Stigmasterol, Daucosterol, and Vitexin suppress tumor growth by influencing AKT1, JUN, EGFR, and VEGFA. Kaplan-Meier survival analysis spotlighted AKT1, JUN, EGFR, and VEGFA as potential diagnostic and prognostic biomarkers for ovarian cancer. However, it is imperative to conduct in vivo and in vitro examinations to ascertain the pharmacokinetics and biosafety profiles, bolstering the candidacy of L. usitatissimum in ovarian cancer therapeutics.

Exploring therapeutic targets and drug candidates for obesity: a combined network pharmacology, bioinformatics approach.

The remarkably high prevalence of obesity in Saudi Arabia reflects a global epidemic demanding urgent attention due to its associated health risks. The integration of traditional medicine, a vital cultural aspect, involves the use of medicinal plants to address various diseases, including obesity. This research merges network pharmacology (NP) and bioinformatics to innovate obesity treatment by identifying effective phytochemicals from native plants in the Taif valley. Focusing on six indigenous plants-Senna alexandrina, Capsicum annuum, Zingiber officinale, Curcuma longa, Trigonella foenum-graecum, and Foeniculum vulgare-we conducted preliminary screenings for potential bioactive compounds. We systematically compiled compound data from public databases and reviewed literature, revealing active compounds like apigenin, kaempferol, moupinamide, cyclocurcumin, chrysoeriol, isorhamnetin, rheinanthrone, cyclocurcumin, and riboflavin.Constructing a compound-target genes-obesity network unveiled their significant impact on metabolic regulation and fat accumulation, interacting notably with key proteins AKT1 and PTGS2. Molecular docking and 100 ns Molecular Dynamic (MD) simulations demonstrated robust binding affinity and stability at the docking site. Employing adipocytes as a cellular model, we gauged their viability and response to obesity-related stressors post-treatment with these native plant compounds.In conclusion, Saudi Arabia's indigenous plants hold promise as natural solutions for obesity treatment. This research opens new avenues in the battle against this pervasive health crisis by incorporating the potential of native botanicals.Communicated by Ramaswamy H. Sarma.

Toxicological Profile of Polyethylene Terephthalate (PET) Microplastic in Ingested Drosophila melanogaster (Oregon R+) and Its Adverse Effect on Behavior and Development.

Microplastics are readily available in the natural environment. Due to the pervasiveness of microplastic pollution, its effects on living organisms necessitate further investigation. The size, time of exposure, and amount of microplastic particles appear to be the most essential factor in determining their toxicological effects, either organismal or sub-organismal. For our research work, we preferred to work on a terrestrial model organism Drosophila melanogaster (Oregon R+). Therefore, in the present study, we characterized 2-100 µm size PET microplastic and confirmed its accumulation in Drosophila, which allowed us to proceed further in our research work. At larger dosages, research on locomotory activities such as climbing, jumping, and crawling indicated a decline in physiological and neuromuscular functions. Our studies also determined retarded development in flies and decreased survival rate in female flies after exposure to the highest concentration of microplastics. These experimental findings provide insight into the possible potential neurotoxic effects of microplastics and their detrimental effects on the development and growth of flies.

In Silico Identification of Natural Product-Based Inhibitors Targeting IL-1ß/IL-1R Protein-Protein Interface.

IL-1ß mediates inflammation and regulates immune responses, cell proliferation, and differentiation. Dysregulation of IL-1ß is linked to inflammatory and autoimmune diseases. Elevated IL-1ß levels are found in patients with severe COVID-19, indicating its excessive production may worsen the disease. Also, dry eye disease patients show high IL-1ß levels in tears and conjunctival epithelium. Therefore, IL-1ß signaling is a potential therapeutic targeting for COVID-19 and aforementioned diseases. No small-molecule IL-1ß inhibitor is clinically approved despite efforts. Developing such inhibitors is highly desirable. Herein, a docking-based strategy was used to screen the TCM (Traditional Chinese Medicine) database to identify possible IL-1ß inhibitors with desirable pharmacological characteristics by targeting the IL-1ß/IL-1R interface. Primarily, the docking-based screening was performed by selecting the crucial residues of IL-1ß interface to retrieve the potential compounds. Afterwards, the compounds were shortlisted on the basis of binding scores and significant interactions with the crucial residues of IL-1ß. Further, to gain insights into the dynamic behavior of the protein-ligand interactions, MD simulations were performed. The analysis suggests that four selected compounds were stabilized in an IL-1ß pocket, possibly blocking the formation of an IL-1ß/IL-1R complex. This indicates their potential to interfere with the immune response, making them potential therapeutic agents to investigate further.

Identification of Small Molecule Inhibitors of Human Cytomegalovirus pUL89 Endonuclease Using Integrated Computational Approaches.

Replication of Human Cytomegalovirus (HCMV) requires the presence of a metal-dependent endonuclease at the C-terminus of pUL89, in order to properly pack and cleave the viral genome. Therefore, pUL89 is an attractive target to design anti-CMV intervention. Herein, we used integrated structure-based and ligand-based virtual screening approaches in combination with MD simulation for the identification of potential metal binding small molecule antagonist of pUL89. In this regard, the essential chemical features needed for the inhibition of pUL89 endonuclease domain were defined and used as a 3D query to search chemical compounds from ZINC and ChEMBL database. Thereafter, the molecular docking and ligand-based shape screening were used to narrow down the compounds based on previously identified pUL89 antagonists. The selected virtual hits were further subjected to MD simulation to determine the intrinsic and ligand-induced flexibility of pUL89. The predicted binding modes showed that the compounds reside well in the binding site of endonuclease domain by chelating with the metal ions and crucial residues. Taken in concert, the in silico investigation led to the identification of potential pUL89 antagonists. This study provided promising starting point for further in vitro and in vivo studies.

Dihydropyrimidone Derivatives as Thymidine Phosphorylase Inhibitors: Inhibition Kinetics, Cytotoxicity, and Molecular Docking.

Overexpression of the thymidine phosphorylase (TP) enzyme induces angiogenesis, which eventually leads to metastasis and tumor growth. The crucial role of TP in cancer development makes it an important target for anticancer drug discovery. Currently, there is only one US-FDA-approved drug, i.e., Lonsurf, a combination of trifluridine and tipiracil, for the treatment of metastatic colorectal cancer. Unfortunately, numerous adverse effects are associated with its use, such as myelosuppression, anemia, and neutropenia. Since the last few decades, the discovery of new, safe, and effective TP inhibitory agents has been rigorously pursued. In the present study, we evaluated a series of previously synthesized dihydropyrimidone derivatives 1-40 for their TP inhibitory potential. Compounds 1, 12, and 33 showed a good activity with IC50 = 314.0 ± 0.90, 303.5 ± 0.40, and 322.6 ± 1.60 µM, respectively. The results of mechanistic studies revealed that compounds 1, 12, and 33 were the non-competitive inhibitors. These compounds were also evaluated for cytotoxicity against 3T3 (mouse fibroblast) cells and were found to be non-cytotoxic. Finally, the molecular docking suggested the plausible mechanism of non-competitive inhibition of TP. The current study thus identifies some dihydropyrimidone derivatives as potential inhibitors of TP, which can be further optimized as leads for cancer treatment.

Structure-based design of promising natural products to inhibit thymidylate kinase from Monkeypox virus and validation using free energy calculations.

Monkeypox (MPXV) is a globally growing public health concern with 80,328 active cases and 53 deaths have been reported. No specific vaccine or drug is available for the treatment of MPXV. Hence, the current study also employed structure-based drug designing, molecular simulation, and free energy calculation methods to identify potential hit molecules against the TMPK of MPXV, which is a replicatory protein that helps the virus to replicate its DNA and increase the number of DNAs in the host cell. The 3D structure of TMPK was modeled with AlphaFold and screening of multiple natural products libraries (4,71,470 compounds) identified TCM26463, TCM2079, and TCM29893 from traditional Chinese medicines database (TCM), SANC00240, SANC00984, and SANC00986 South African natural compounds database (SANCDB), NPC474409, NPC278434 and NPC158847 from NPASS (natural product activity and species source database) while CNP0404204, CNP0262936, and CNP0289137 were shortlisted from coconut database (collection of open natural products) as the best hits. These compounds interact with the key active site residues through hydrogen bonds, salt bridges, and pie-pie interactions. The structural dynamics and binding free energy results further revealed that these compounds possess stable dynamics with excellent binding free energy scores. Moreover, the dissociation constant (KD) and bioactivity analysis revealed stronger activity of these compounds exhibit stronger biological activity against MPXV and may inhibit it in in vitro conditions. All the results demonstrated that the designed novel compounds possess stronger inhibitory activity than the control complex (TPD-TMPK) from the vaccinia virus. The current study is the first to design small molecule inhibitors for the replication protein of MPXV which may help in controlling the current epidemic and also overcome the challenge of vaccine evasion.

Deciphering the mechanism of resistance by novel double mutations in pncA in Mycobacterium tuberculosis using protein structural graphs (PSG) and structural bioinformatic approaches.

The evolution of MDR and XDR-TB is a growing concern and public health safety threat around the world. Gene mutations are the prime cause of drug resistance in tuberculosis, however the reports of double mutations further aggravated the situation. Despite the large-scale genomic sequencing and identification of novel mutations, structure investigation of the protein is still required to structurally and functionally characterize these novel mutations to design novel drugs for improved clinical outcome. Hence, we used structural bioinformatics approaches i.e. molecular modeling, residues communication and molecular simulation to understand the impact of novel double S59Y-L85P, D86G-V180F and S104G-V130 M mutation on the structure, function of pncA encoded Pyrazinamidase (PZase) and resistance of Pyrazinamide (PZA). Our results revealed that these mutations alter the binding paradigm and destabilize the protein to release the drug. Protein commination network (PCN) revealed variations in the hub residues and sub-networks which consequently alter the internal communication and signaling. The region 1-75 demonstrated higher flexibility in the mutant structures and minimal by the wild type which destabilize of the internally arranged beta-sheets which consequently reduce the binding of PZA and potentially Fe ion in the mutants. Hydrogen bonding analysis further validated the findings. The total binding free energy (ΔG) for each complex i.e. wild type -7.46 kcal/mol, S59Y-L85P -5.21 kcal/mol, S104G-V130 M -5.33 kcal/mol while for the D86G-V180F mutant the TBE was calculated to be -6.26 kcal/mol. This further confirms that these mutations reduce the binding energy of PZA for PZase and causes resistance in the effective therapy for TB. The trajectories motion was also observed to be affected by these mutations. In conclusion, these mutations use destabilizing approach to reduce the binding of PZA and causes resistance. These features can be used to design novel structure-based drugs against Tuberculosis.

Structural Homology-Based Drug Repurposing Approach for Targeting NSP12 SARS-CoV-2.

The severe acute respiratory syndrome coronavirus 2, also known as SARS-CoV-2, is the causative agent of the COVID-19 global pandemic. SARS-CoV-2 has a highly conserved non-structural protein 12 (NSP-12) involved in RNA-dependent RNA polymerase (RdRp) activity. For the identification of potential inhibitors for NSP-12, computational approaches such as the identification of homologous proteins that have been previously targeted by FDA-approved antivirals can be employed. Herein, homologous proteins of NSP-12 were retrieved from Protein DataBank (PDB) and the evolutionary conserved sequence and structure similarity of the active site of the RdRp domain of NSP-12 was characterized. The identified homologous structures of NSP-12 belonged to four viral families: Coronaviridae, Flaviviridae, Picornaviridae, and Caliciviridae, and shared evolutionary conserved relationships. The multiple sequences and structural alignment of homologous structures showed highly conserved amino acid residues that were located at the active site of the RdRp domain of NSP-12. The conserved active site of the RdRp domain of NSP-12 was evaluated for binding affinity with the FDA-approved antivirals, i.e., Sofosbuvir and Dasabuvir in a molecular docking study. The molecular docking of Sofosbuvir and Dasabuvir with the active site that contains conserved motifs (motif A-G) of the RdRp domain of NSP-12 revealed significant binding affinity. Furthermore, MD simulation also inferred the potency of Sofosbuvir and Dasabuvir. In conclusion, targeting the active site of the RdRp domain of NSP-12 with Dasabuvir and Sofosbuvir might reduce viral replication and pathogenicity and could be further studied for the treatment of SARS-CoV-2.