In Silico Screening, Molecular Dynamics Simulation and Binding Free Energy Identify Single-Point Mutations That Destabilize p53 and Reduce Binding to DNA.

Considering p53's pivotal role as a tumor suppressor protein, proactive identification and characterization of potentially harmful p53 mutations are crucial before they appear in the population. To address this, four computational prediction tools-SIFT, Polyphen-2, PhD-SNP, and MutPred2-utilizing sequence-based and machine-learning algorithms, were employed to identify potentially deleterious p53 nsSNPs (nonsynonymous single nucleotide polymorphisms) that may impact p53 structure, dynamics, and binding with DNA. These computational methods identified three variants, namely, C141Y, C238S, and L265P, as detrimental to p53 stability. Furthermore, molecular dynamics (MD) simulations revealed that all three variants exhibited heightened structural flexibility compared to the native protein, especially the C141Y and L265P mutations. Consequently, due to the altered structure of mutant p53, the DNA-binding affinity of all three variants decreased by approximately 1.8 to 9.7 times compared to wild-type p53 binding with DNA (14 µM). Notably, the L265P mutation exhibited an approximately ten-fold greater reduction in binding affinity. Consequently, the presence of the L265P mutation in p53 could pose a substantial risk to humans. Given that p53 regulates abnormal tumor growth, this research carries significant implications for surveillance efforts and the development of anticancer therapies.

Identification of putative antiviral bioactive compounds derived from family Asteraceae: An in silico approach.

This computational study investigates 21 bioactive compounds from the Asteraceae family as potential inhibitors targeting the Spike protein (S protein) of SARS-CoV-2. Employing in silico methods and simulations, particularly CDOCKER and MM-GBSA, the study identifies two standout compounds, pterodontic acid and cichoric acid, demonstrating robust binding affinities (-46.1973 and -39.4265 kcal/mol) against the S protein. Comparative analysis with Favipiravir underscores their potential as promising inhibitors. Remarkably, these bioactives exhibit favorable ADMET properties, suggesting safety and efficacy. Molecular dynamics simulations validate their stability and interactions, signifying their potential as effective SARS-CoV-2 inhibitors.

PCSK9 inhibitors as safer therapeutics for atherosclerotic cardiovascular disease (ASCVD): Pharmacophore design and molecular dynamics analysis.

Cardiovascular disorders are still challenging and are among the deadly diseases. As a major risk factor for atherosclerotic cardiovascular disease, dyslipidemia, and high low-density lipoprotein cholesterol in particular, can be prevented primary and secondary by lipid-lowering medications. Therefore, insights are still needed into designing new drugs with minimal side effects. Proprotein convertase subtilisin/kexin 9 (PCSK9) enzyme catalyses protein-protein interactions with low-density lipoprotein, making it a critical target for designing promising inhibitors compared to statins. Therefore, we screened for potential compounds using a redesigned PCSK9 conformational behaviour to search for a significantly extensive chemical library and investigated the inhibitory mechanisms of the final compounds using integrated computational methods, from ligand essential functional group screening to all-atoms MD simulations and MMGBSA-based binding free energy. The inhibitory mechanisms of the screened compounds compared with the standard inhibitor. K31 and K34 molecules showed stronger interactions for PCSK9, having binding energy (kcal/mol) of -33.39 and -63.51, respectively, against -27.97 of control. The final molecules showed suitable drug-likeness, non-mutagenesis, permeability, and high solubility values. The C-α atoms root mean square deviation and root mean square fluctuation of the bound-PCSK9 complexes showed stable and lower fluctuations compared to apo PCSK9. The findings present a model that unravels the mechanism by which the final molecules proposedly inhibit the PCSK9 function and could further improve the design of novel drugs against cardiovascular diseases.

In Silico Approach: Anti-Tuberculosis Activity of Caespitate in the H37Rv Strain.

Tuberculosis is a highly lethal bacterial disease worldwide caused by Mycobacterium tuberculosis (Mtb). Caespitate is a phytochemical isolated from Helichrysum caespititium, a plant used in African traditional medicine that shows anti-tubercular activity, but its mode of action remains unknown. It is suggested that there are four potential targets in Mtb, specifically in the H37Rv strain: InhA, MabA, and UGM, enzymes involved in the formation of Mtb's cell wall, and PanK, which plays a role in cell growth. Two caespitate conformational structures from DFT conformational analysis in the gas phase (GC) and in solution with DMSO (CS) were selected. Molecular docking calculations, MM/GBSA analysis, and ADME parameter evaluations were performed. The docking results suggest that CS is the preferred caespitate conformation when interacting with PanK and UGM. In both cases, the two intramolecular hydrogen bonds characteristic of caespitate's molecular structure were maintained to achieve the most stable complexes. The MM/GBSA study confirmed that PanK/caespitate and UGM/caespitate were the most stable complexes. Caespitate showed favorable pharmacokinetic characteristics, suggesting rapid absorption, permeability, and high bioavailability. Additionally, it is proposed that caespitate may exhibit antibacterial and antimonial activity. This research lays the foundation for the design of anti-tuberculosis drugs from natural sources, especially by identifying potential drug targets in Mtb.

Exploring the immune evasion of SARS-CoV-2 variant harboring E484K by molecular dynamics simulations.

Although the current coronavirus disease 2019 (COVID-19) vaccines have been used worldwide to halt spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the emergence of new SARS-CoV-2 variants with E484K mutation shows significant resistance to the neutralization of vaccine sera. To better understand the resistant mechanism, we calculated the binding affinities of 26 antibodies to wild-type (WT) spike protein and to the protein harboring E484K mutation, respectively. The results showed that most antibodies (~85%) have weaker binding affinities to the E484K mutated spike protein than to the WT, indicating the high risk of immune evasion of the mutated virus from most of current antibodies. Binding free energy decomposition revealed that the residue E484 forms attraction with most antibodies, while the K484 has repulsion from most antibodies, which should be the main reason of the weaker binding affinities of E484K mutant to most antibodies. Impressively, a monoclonal antibody (mAb) combination was found to have much stronger binding affinity with E484K mutant than WT, which may work well against the mutated virus. Based on binding free energy decomposition, we predicted that the mutation of four more residues on receptor-binding domain (RBD) of spike protein, viz., F490, V483, G485 and S494, may have high risk of immune evasion, which we should pay close attention on during the development of new mAb therapeutics.

Cheminformatics-based analysis identified (Z)-2-(2,5-dimethoxy benzylidene)-6-(2-(4-methoxyphenyl)-2-oxoethoxy) benzofuran-3(2H)-one as an inhibitor of Marburg replication by interacting with NP.

The highly pathogenic Marburg virus (MARV) is a member of the Filoviridae family, a non-segmented negative-strand RNA virus. This article represents the computer-aided drug design (CADD) approach for identifying drug-like compounds that prevent the MARV virus disease by inhibiting nucleoprotein, which is responsible for their replication. This study used a wide range of in silico drug design techniques to identify potential drugs. Out of 368 natural compounds, 202 compounds passed ADMET, and molecular docking identified the top two molecules (CID: 1804018 and 5280520) with a high binding affinity of -6.77 and -6.672 kcal/mol, respectively. Both compounds showed interactions with the common amino acid residues SER_216, ARG_215, TYR_135, CYS_195, and ILE_108, which indicates that lead compounds and control ligands interact in the common active site/catalytic site of the protein. The negative binding free energies of CID: 1804018 and 5280520 were -66.01 and -31.29 kcal/mol, respectively. Two lead compounds were re-evaluated using MD modeling techniques, which confirmed CID: 1804018 as the most stable when complexed with the target protein. PC3 of the (Z)-2-(2,5-dimethoxybenzylidene)-6-(2-(4-methoxyphenyl)-2-oxoethoxy) benzofuran-3(2H)-one (CID: 1804018) was 8.74 %, whereas PC3 of the 2'-Hydroxydaidzein (CID: 5280520) was 11.25 %. In this study, (Z)-2-(2,5-dimethoxybenzylidene)-6-(2-(4-methoxyphenyl)-2-oxoethoxy) benzofuran-3(2H)-one (CID: 1804018) unveiled the significant stability of the proteins' binding site in ADMET, Molecular docking, MM-GBSA and MD simulation analysis studies, which also showed a high negative binding free energy value, confirming as the best drug candidate which is found in Angelica archangelica which may potentially inhibit the replication of MARV nucleoprotein.

Anti-quorum sensing activity of α-amidoamides against Agrobacterium tumefaciensNT1: Insights from molecular docking and dynamic investigations to synergistic approach of metronidazole release from gel formulations.

A unique approach is imperative for the development of drugs aimed at inhibiting various stages of infection, rather than solely focusing on bacterial viability. Among the array of unconventional targets explored for formulating novel antimicrobial medications, blocking the quorum-sensing (QS) system emerges as a highly effective and promising strategy against a variety of pathogenic microbes. In this investigation, we have successfully assessed nine α-aminoamides for their anti-QS activity using Agrobacterium tumefaciensNT1 as a biosensor strain. Among these compounds, three (2, 3and, 4) have been identified as potential anti-QS candidates. Molecular docking studies have further reinforced these findings, indicating that these compounds exhibit favorable pharmacokinetic profiles. Additionally, we have assessed the ligand's stability within the protein's binding pocket using molecular dynamics (MD) simulations and MMGBSA analysis. Further, combination of antiquorum sensing properties with antibiotics viaself-assembly represents a promising approach to enhance antibacterial efficacy, overcome resistance, and mitigate the virulence of bacterial pathogens. The release study also reflects a slow and gradual release of the metronidazole at both pH 6.5 and pH 7.4, avoiding the peaks and troughs associated with more immediate release formulations.

Insight of the molecular mechanism of inhibitors located at different allosteric sites regulating the activity of wild type and mutant KRAS (G12).

As the important hub of many cellular signaling networks, KRAS (Kirsten rat sarcoma viral oncogene homologue) has been identified as a tumor biomarker. It is the frequently mutated oncogene in human cancers, and KRAS protein activation caused by mutations, such as G12D, has been found in many human tumors tissues. Although, there are two specific allosteric sites (AS1 and AS2) on the KRAS protein that can be used as the targets for inhibitor development, the difference of regulatory mechanisms between two individual allosteric sites still not be reported. Here, using molecular dynamics simulations combined with molecular mechanics generalized born surface area (MM/GBSA) analysis, we found that both of the inhibitors, located at AS1 and AS2, were able to reduce the binding free energy between wild type, mutant KRAS (G12/D/V/S/C) and GTP remarkably, however the effect of inhibitors on the binding free energy between wild type, mutant KRAS and GDP was limited. In addition, the degree of decrease of binding free energy between KRAS and GTP caused by inhibitors at AS2 was significantly greater than that caused by inhibitors at AS1. Further analysis revealed that both inhibitors at AS1 and AS2 were able to regulate the fluctuation of Switch Ⅰ and Switch Ⅱ to expand the pocket of the orthosteric site (GTP binding site), thereby reducing the binding of KRAS to GTP. Noteworthy there was significant differences in the regulatory preferences on Switch Ⅰ and Switch Ⅱ between two type inhibitor. The inhibitor at AS2 mainly regulated Switch Ⅱ to affect the pocket of the orthosteric site, while the inhibitor at AS1 mainly expand the pocket of the orthosteric site by regulating the fluctuation of Switch Ⅰ. Our study compared the differences between two type inhibitors in regulating the KRAS protein activity and revealed the advantages of the AS2 as the small molecule drug target, aiming to provide theoretical guidance for the research of novel KRAS protein inhibitors.

Structural insights into the potential binding sites of Cathepsin D using molecular modelling techniques.

Alzheimer's disease (AD) is the most prevalent type of dementia caused by the accumulation of amyloid beta (Aß) peptides. The extracellular deposition of Aß peptides in human AD brain causes neuronal death. Therefore, it has been found that Aß peptide degradation is a possible therapeutic target for AD. CathD has been known to breakdown amyloid beta peptides. However, the structural role of CathD is not yet clear. Hence, for the purpose of gaining a deeper comprehension of the structure of CathD, the present computational investigation was performed using virtual screening technique to predict CathD's active site residues and substrate binding mode. Ligand-based virtual screening was implemented on small molecules from ZINC database against crystal structure of CathD. Further, molecular docking was utilised to investigate the binding mechanism of CathD with substrates and virtually screened inhibitors. Localised compounds obtained through screening performed by PyRx and AutoDock 4.2 with CathD receptor and the compounds having highest binding affinities were picked as; ZINC00601317, ZINC04214975 and ZINCC12500925 as our top choices. The hydrophobic residues Viz. Gly35, Val31, Thr34, Gly128, Ile124 and Ala13 help stabilising the CathD-ligand complexes, which in turn emphasises substrate and inhibitor selectivity. Further, MM-GBSA approach has been used to calculate binding free energy between CathD and selected compounds. Therefore, it would be beneficial to understand the active site pocket of CathD with the assistance of these discoveries. Thus, the present study would be helpful to identify active site pocket of CathD, which could be beneficial to develop novel therapeutic strategies for the AD.

Chemical analogue based drug design for cancer treatment targeting PI3K: integrating machine learning and molecular modeling.

Cancer is a generic term for a group of disorders defined by uncontrolled cell growth and the potential to invade or spread to other parts of the body. Gene and epigenetic alterations disrupt normal cellular control, leading to abnormal cell proliferation, resistance to cell death, blood vessel development, and metastasis (spread to other organs). One of the several routes that play an important role in the development and progression of cancer is the phosphoinositide 3-kinase (PI3K) signaling pathway. Moreover, the gene PIK3CG encodes the catalytic subunit gamma (p110γ) of phosphoinositide 3-kinase (PI3Kγ), a member of the PI3K family. Therefore, in this study, PIK3CG was targeted to inhibit cancer by identifying a novel inhibitor through computational methods. The study screened 1015 chemical fragments against PIK3CG using machine learning-based binding estimation and docking to select the potential compounds. Later, the analogues were generated from the selected hits, and 414 analogues were selected, which were further screened, and as most potential candidates, three compounds were obtained: (a) 84,332, 190,213, and 885,387. The protein-ligand complex's stability and flexibility were then investigated by dynamic modeling. The 100 ns simulation revealed that 885,387 exhibited the steadiest deviation and constant creation of hydrogen bonds. Compared to the other compounds, 885,387 demonstrated a superior binding free energy (ΔG = -18.80 kcal/mol) with the protein when the MM/GBSA technique was used. The study determined that 885,387 showed significant therapeutic potential and justifies further experimental investigation as a possible inhibitor of the PIK3CG target implicated in cancer.

An insight for the inhibition of anxiolytic and anti-convulsant effects in zebrafish using the curcumins via exploring molecular docking and molecular dynamics simulations.

In the contemporary landscape, anxiety and seizures stand as major areas of concern, prompting researchers to explore potential drugs against them. While numerous drugs have shown the potential to treat these two neurological conditions, certain adverse effects emphasize the need for development of safer alternatives. This study seeks to employ an in silico approach to evaluate natural compounds, particularly curcumins, as potential inhibitors of GABA-AT to mitigate anxiety and seizures. The proposed methodology includes generating a compound library, minimizing energy, conducting molecular docking using AutoDock, molecular dynamics simulations using Amber, and MM-GBSA calculations. Remarkably, CMPD50 and CMPD88 exhibited promising binding affinities of - 9.0 kcal/mol and - 9.1 kcal/mol with chains A and C of GABA-AT, respectively. Further, MM-GBSA calculations revealed binding free energies of - 10.88 kcal/mol and - 10.72 kcal/mol in CMPD50 and CMPD88, respectively. ADME analysis showed that these compounds contain drug-likeness properties and might be considered as potential drug candidates. The findings from this study will have practical applications in the field of drug discovery for the development of safer and effective drugs for treatment of anxiety and seizures. Overall, this study will lay the groundwork for providing valuable insights into the potential therapeutic effects of curcumins in alleviating anxiety and seizures, establishing a computational framework for future experimental validation.

Comprehensive computational investigation for ligand recognition and binding dynamics of SdiA: a degenerate LuxR -type receptor in Klebsiella pneumoniae.

SdiA is a LuxR-type receptor that controls the virulence of Klebsiella pneumoniae, a Gram-negative bacterium that causes various infections in humans. SdiA senses exogenous acyl-homoserine lactones (AHLs) and autoinducer-2 (AI-2), two types of quorum sensing signals produced by other bacterial species. However, the molecular details of how SdiA recognizes and binds to different ligands and how this affects its function and regulation in K. pneumoniae still need to be better understood. This study uses computational methods to explore the protein-ligand binding dynamics of SdiA with 11 AHLs and 2 AI-2 ligands. The 3D structure of SdiA was predicted through homology modeling, followed by molecular docking with AHLs and AI-2 ligands. Binding affinities were quantified using MM-GBSA, and complex stability was assessed via Molecular Dynamics (MD) simulations. Results demonstrated that SdiA in Klebsiella pneumoniae exhibits a degenerate binding nature, capable of interacting with multiple AHLs and AI-2. Specific ligands, namely C10-HSL, C8-HSL, 3-oxo-C8-HSL, and 3-oxo-C10-HSL, were found to have high binding affinities and formed critical hydrogen bonds with key amino acid residues of SdiA. This finding aligns with the observed preference of SdiA for AHLs having 8 to 10 carbon-length acyl chains and lacking hydroxyl groups. In contrast, THMF and HMF demonstrated poor binding properties. Furthermore, AI-2 exhibited a low affinity, corroborating the inference that SdiA is not the primary receptor for AI-2 in K. pneumoniae. These findings provide insights into the protein-ligand binding dynamics of SdiA and its role in quorum sensing and virulence of K. pneumoniae.

First report on chemometrics-driven multilayered lead prioritization in addressing oxysterol-mediated overexpression of G protein-coupled receptor 183.

Contemporary research has convincingly demonstrated that upregulation of G protein-coupled receptor 183 (GPR183), orchestrated by its endogenous agonist, 7α,25-dihydroxyxcholesterol (7α,25-OHC), leads to the development of cancer, diabetes, multiple sclerosis, infectious, and inflammatory diseases. A recent study unveiled the cryo-EM structure of 7α,25-OHC bound GPR183 complex, presenting an untapped opportunity for computational exploration of potential GPR183 inhibitors, which served as our inspiration for the current work. A predictive and validated two-dimensional QSAR model using genetic algorithm (GA) and multiple linear regression (MLR) on experimental GPR183 inhibition data was developed. QSAR study highlighted that structural features like dissimilar electronegative atoms, quaternary carbon atoms, and CH2RX fragment (X: heteroatoms) influence positively, while the existence of oxygen atoms with a topological separation of 3, negatively affects GPR183 inhibitory activity. Post assessment of true external set prediction capability, the MLR model was deployed to screen 12,449 DrugBank compounds, followed by a screening pipeline involving molecular docking, druglikeness, ADMET, protein-ligand stability assessment using deep learning algorithm, molecular dynamics, and molecular mechanics. The current findings strongly evidenced DB05790 as a potential lead for prospective interference of oxysterol-mediated GPR183 overexpression, warranting further in vitro and in vivo validation.

Multi-method computational evaluation of the inhibitors against leucine-rich repeat kinase 2 G2019S mutant for Parkinson's disease.

Leucine-rich repeat kinase 2 G2019S mutant (LRRK2 G2019S) is a potential target for Parkinson's disease therapy. In this work, the computational evaluation of the LRRK2 G2019S inhibitors was conducted via a combined approach which contains a preliminary screening of a large database of compounds via similarity and pharmacophore, a secondary selection via structure-based affinity prediction and molecular docking, and a rescoring treatment for the final selection. MD simulations and MM/GBSA calculations were performed to check the agreement between different prediction methods for these inhibitors. 331 experimental ligands were collected, and 170 were used to build the structure-activity relationship. Eight representative ligand structural models were employed in similarity searching and pharmacophore screening over 14 million compounds. The process for selecting proper molecular descriptors provides a successful sample which can be used as a general strategy in QSAR modelling. The rescoring used in this work presents an alternative useful treatment for ranking and selection.

The efficacy of Linum usitatissimum seeds to inhibit estrogen receptor as a natural therapy for PCOS: An in silico and in vitro analysis.

Polycystic ovarian syndrome (PCOS) is an endocrinological disorder aroused due to hormonal disturbances. It is characterized by anovulation due to an excess of androgen and estrogen hormones, thus leading to the formation of multiple cysts, imposing life-threatening conditions. This manuscript aimed to introduce a natural estrogen receptor (ESR) inhibitors that can provide protection against PCOS. The computational analysis of Linum usitatissimum seeds  compounds against ESR alpha receptor was performed, and the binding affinities of the ligand compounds and receptor proteins were scrutinized. Nine lignin compounds were docked, and the results were compared with that of reference estrogen receptor inhibitors, clomiphene, and tamoxifen. The binding affinity scores for pinoresinol, lariciresinol, secoisolariciresinol, and matairesinol were -10.67, -10.66, -10.91, and -10.60 kcal mol-1 , respectively. These were comparable to the binding affinity score of reference compounds -11.406 kcal mol-1 for clomiphene and -10.666 kcal mol-1 for tamoxifen. Prime MM-GBSA studies showcased that Linum usitatissimum seeds compounds exhibit significant efficacy and efficiency towards receptor protein. Moreover, MD-simulation studies were performed and the results depict that the lignin compounds form stable complexes at 300 K throughout the simulation time. For further clarity, in-vitro experiments were carried out. The results exhibit the decline in cell proliferation in a concentration-dependent manner by extract 1 (ethyl acetate) EX1 and extract 2 (petroleum ether) EX2. Hence, providing evidence regarding the anti-estrogenic activity of the sample extracts. Collectively, these results showed that flax seed can reduce the levels of estrogen, which can induce ovulation and prevent cyst formation, and ultimately can provide protection against PCOS.

Evaluation of Anti-Hyperlipidemic Activity of the Seeds Extracts of Ficus carica: In Vitro and In Silico Approaches.

Obesity and hyperlipidemia have become major disorders predominantly causing prevailing cardiovascular diseases and ultimately death. The prolonged use of anti-obesity drugs and statins for reducing obesity and blood lipid levels is leading toward adverse effects of kidneys and muscles, specifically rhabdomyolysis. The objective of this study is to evaluate potential of seeds of Ficus carica against hyperlipidemia. Various extracts and isolated compounds from fig seeds were analyzed and evaluated for their anti-hyperlipidemic potential. Methanol extract and its ethyl acetate fraction showed maximum pancreatic lipase inhibition of 61.93% and 86.45% in comparison to reference drug Orlistat. Four compounds isolated by HPLC-PDA technique were determined as Gallic acid, Catechin, Epicatechin, and Quercetin also showed strong potential to inhibit enzyme pancreatic lipase comparable to Orlistat. These isolated compounds were further analyzed for molecular docking and MM-GBSA studies. Three ligands, namely Quercetin, Epicatechin, and Catechin were found more effective against pancreatic lipase as these possessed docking scores (-9.881, -9.741, -9.410) higher to that of the reference ligand Orlistat (-5.273). The binding free energies of these compounds were -55.03, -56.54, and 60.35 kcal/mol, respectively. The results have shown that Quercetin has the highest binding affinity correlating with the highest inhibition of pancreatic lipase enzyme 1LPB. Hence, it is suggested that seeds of F. carica have promising anti-hyperlipidemic potential and foremost in reducing obesity.

Computational prediction of the effect of amino acid changes on the binding affinity between SARS-CoV-2 spike RBD and human ACE2.

The association of the receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein with human angiotensin-converting enzyme 2 (hACE2) represents the first required step for cellular entry. SARS-CoV-2 has continued to evolve with the emergence of several novel variants, and amino acid changes in the RBD have been implicated with increased fitness and potential for immune evasion. Reliably predicting the effect of amino acid changes on the ability of the RBD to interact more strongly with the hACE2 can help assess the implications for public health and the potential for spillover and adaptation into other animals. Here, we introduce a two-step framework that first relies on 48 independent 4-ns molecular dynamics (MD) trajectories of RBD-hACE2 variants to collect binding energy terms decomposed into Coulombic, covalent, van der Waals, lipophilic, generalized Born solvation, hydrogen bonding, π-π packing, and self-contact correction terms. The second step implements a neural network to classify and quantitatively predict binding affinity changes using the decomposed energy terms as descriptors. The computational base achieves a validation accuracy of 82.8% for classifying single-amino acid substitution variants of the RBD as worsening or improving binding affinity for hACE2 and a correlation coefficient of 0.73 between predicted and experimentally calculated changes in binding affinities. Both metrics are calculated using a fivefold cross-validation test. Our method thus sets up a framework for screening binding affinity changes caused by unknown single- and multiple-amino acid changes offering a valuable tool to predict host adaptation of SARS-CoV-2 variants toward tighter hACE2 binding.

Thiazolobenzamide-Naphthalene Hybrids as Potent Anticancer agents compared to Doxorubicin: Design, Synthesis, SAR, In-silico and Toxicity Analysis.

In order to determine whether thiazolobenzamide molecules connected to naphthalene could inhibit the growth of three different tumor cell lines, MCF7 (breast carcinoma), A549 (pulmonary carcinoma), and DU145 (prostatic adenocarcinoma) a novel series of ten molecules, designated TA 1-10, was designed, synthesized, and tested. Among these compounds, TA7 showed promising results against cell lines, especially showing exceptional efficacy against breast cancer. Antioxidant activity tests consistently showed the best performance from the TA7 molecule. Furthermore, when a dose of 50 to 500 mg/kg of the total mass of rats is given, the most effective chemical, TA7, did not exhibit any harmful effects during acute oral toxicity tests. The biochemical indicators (SGOT and SGPT) for hepatotoxicity associated with compound TA7 were found to be fairly similar to those of the control group. The findings from molecular docking, XP visualization, and MM-GBSA dG binding investigations are in agreement with the outcomes of in-vitro tests of antioxidant and anticancer capabilities. TA7 was the most effective compound among those that were docked; it bound free energy and had adequate properties for metabolism (biochemical processes), distribution (dispersion), absorption (assimilation), and excretion (elimination). This study found that the TA7 molecule, a thiazole ring system derivative connected to naphthalene, is to be a promising and possible anticancer agent and its efficacy may be further explored in clinical studies.

Investigating the Potential of 2-Ethylbutyl-(Phenoxy)phosphoryl-D-Alaninate Against RNA-Dependent RNA Polymerase (RdRp) of SARS-CoV-2.

There was an emergency call globally when COVID-19 was detected in December 2019. The SARS-CoV-2 virus, a modified virus, is what causes this contagious disease. Although research is being conducted throughout the world, the main target is still to find the promising candidate to target RNA-dependent RNA polymerase (RdRp) to provide possible drug against COVID-19. Aim of this work is to find a molecule to inhibit the translational process of viral protein synthesis. Density Functional Theory calculations revealed information about the formation of the desired ligand (RD). Molecular docking of RD with RdRp was performed and compared with some reported molecules and the data revealed that RD had the best docking score with RdRp (-6.7 kcal/mol). Further, molecular dynamics (MD) simulations of RD with RdRp of SARS-CoV-2 revealed the formation of stable complex with a maximum number of seven hydrogen bonds. Root mean square deviations values are in acceptable range and root mean square fluctuations has less fluctuation indicate stable complex formation. Further, based on MM-GBSA calculation, RD formed a stable complex with RdRp of nCoV with ΔG° of -12.28 kcal·mol-1.

LC-HRMS Profiling and Cytotoxic Potential of Actinomycetes Associated with the Red Sea Soft Coral Sarcophyton glaucum: In vitro and In silico Studies.

In the current study, the actinomycetes associated with the red sea-derived soft coral Sarcophyton glaucum were investigated in terms of biological and chemical diversity. Four different media, M1, ISP2, Marine Agar (MA), and Actinomycete isolation agar (AIA) were used for the isolation of three strains of actinomycetes that were identified as Streptomyces sp. UR 25, Micromonospora sp. UR32 and Saccharomonospora sp. UR 19. LC-HRMS analysis was used to investigate the chemical diversity of the isolated actinobacteria. The LC-HRMS data were statistically processed using MetaboAnalyst 5.0 viz to differentiate the extract groups and determine the optimal growth culturing conditions. Multivariate data statistical analysis revealed that the Micromonospora sp. extract cultured on (MA) medium is the most distinctive extract in terms of chemical composition. While, the Streptomyces sp. UR 25 extracts are differ significantly from Micromonospora sp. UR32 and Saccharomonospora sp. UR 19. Biological investigation using in vitro cytotoxic assay for actinobacteria extracts revealed the prominent potentiality of the Streptomyces sp. UR 25 cultured on oligotrophic medium against human hepatoma (HepG2), human breast adenocarcinoma (MCF-7) and human colon adenocarcinoma (CACO2) cell lines (IC50 =3.3, 4.2 and 6.8 µg/mL, respectively). SwissTarget Prediction speculated that among the identified compounds, 16-deethyl, indanomycin (8) could have reasonable affinity on HDM2 active site. In this respect, molecular docking study was performed for compound (8) to reveal a substantial affinity on HDM2 active site. In addition, molecular dynamics simulations were carried out at 200 ns for the most active compound (8) compared to the co-crystallized inhibitor DIZ giving deeper information regarding their thermodynamic and dynamic properties as well.