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.

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.

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.

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.

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.

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.

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.

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.

Discovery of potent CSK inhibitors through integrated virtual screening and molecular dynamic simulation.

Oncogenic overexpression or activation of C-terminal Src kinase (CSK) has been shown to play an important role in triple-negative breast cancer (TNBC) progression, including tumor initiation, growth, metastasis, drug resistance. This revelation has pivoted the focus toward CSK as a potential target for novel treatments. However, until now, there are few inhibitors designed to target the CSK protein. Responding to this, our research has implemented a comprehensive virtual screening protocol. By integrating energy-based screening methods with AI-driven scoring functions, such as Attentive FP, and employing rigorous rescoring methods like Glide docking and molecular mechanics generalized Born surface area (MM/GBSA), we have systematically sought out inhibitors of CSK. This approach led to the discovery of a compound with a potent CSK inhibitory activity, reflected by an IC50 value of 1.6 nM under a homogeneous time-resolved fluorescence (HTRF) bioassay. Subsequently, molecule 2 exhibits strong growth inhibition of MD anderson - metastatic breast (MDA-MB) -231, Hs578T, and SUM159 cells, showing a level of growth inhibition comparable to that observed with dasatinib. Treatment with molecule 2 also induced significant G1 phase accumulation and cell apoptosis. Furthermore, we have explored the explicit binding interactions of the compound with CSK using molecular dynamics simulations, providing valuable insights into its mechanism of action.

Molecular Insights into the Specific Targeting of c-MYC G-Quadruplex by Thiazole Peptides.

Stabilization of a G-quadruplex (G4) in the promotor of the c-MYC proto-oncogene leads to inhibition of gene expression, and it thus represents a potentially attractive new strategy for cancer treatment. However, most G4 stabilizers show little selectivity among the many G4s present in the cellular complement of DNA and RNA. Intriguingly, a crescent-shaped cell-penetrating thiazole peptide, TH3, preferentially stabilizes the c-MYC G4 over other promotor G4s, but the mechanisms leading to this selective binding remain obscure. To investigate these mechanisms at the atomic level, we performed an in silico comparative investigation of the binding of TH3 and its analogue TH1 to the G4s from the promotors of c-MYC, c-KIT1, c-KIT2, and BCL2. Molecular docking and molecular dynamics simulations, combined with in-depth analyses of non-covalent interactions and bulk and per-nucleotide binding free energies, revealed that both TH3 and TH1 can induce the formation of a sandwich-like framework through stacking with both the top and bottom G-tetrads of the c-MYC G4 and the adjacent terminal capping nucleotides. This framework produces enhanced binding affinities for c-MYC G4 relative to other promotor G4s, with TH3 exhibiting an outstanding binding priority. Van der Waals interactions were identified to be the key factor in complex formation in all cases. Collectively, our findings fully agree with available experimental data. Therefore, the identified mechanisms leading to specific binding of TH3 towards c-MYC G4 provide valuable information to guide the development of new selective G4 stabilizers.

High-Throughput Molecular Modeling and Evaluation of the Anti-Inflammatory Potential of Açaí Constituents against NLRP3 Inflammasome.

The search for bioactive compounds in natural products holds promise for discovering new pharmacologically active molecules. This study explores the anti-inflammatory potential of açaí (Euterpe oleracea Mart.) constituents against the NLRP3 inflammasome using high-throughput molecular modeling techniques. Utilizing methods such as molecular docking, molecular dynamics simulation, binding free energy calculations (MM/GBSA), and in silico toxicology, we compared açaí compounds with known NLRP3 inhibitors, MCC950 and NP3-146 (RM5). The docking studies revealed significant interactions between açaí constituents and the NLRP3 protein, while molecular dynamics simulations indicated structural stabilization. MM/GBSA calculations demonstrated favorable binding energies for catechin, apigenin, and epicatechin, although slightly lower than those of MCC950 and RM5. Importantly, in silico toxicology predicted lower toxicity for açaí compounds compared to synthetic inhibitors. These findings suggest that açaí-derived compounds are promising candidates for developing new anti-inflammatory therapies targeting the NLRP3 inflammasome, combining efficacy with a superior safety profile. Future research should include in vitro and in vivo validation to confirm the therapeutic potential and safety of these natural products. This study underscores the value of computational approaches in accelerating natural product-based drug discovery and highlights the pharmacological promise of Amazonian biodiversity.

Are Terminal Alkynes Necessary for MAO-A/MAO-B Inhibition? A New Scaffold Is Revealed.

A versatile family of quaternary propargylamines was synthesized employing the KA2 multicomponent reaction, through the single-step coupling of a number of amines, ketones, and terminal alkynes. Sustainable synthetic procedures using transition metal catalysts were employed in all cases. The inhibitory activity of these molecules was evaluated against human monoaminoxidase (hMAO)-A and hMAO-B enzymes and was found to be significant. The IC50 values for hMAO-B range from 152.1 to 164.7 nM while the IC50 values for hMAO-A range from 765.6 to 861.6 nM. Furthermore, these compounds comply with Lipinski's rule of five and exhibit no predicted toxicity. To understand their binding properties with the two target enzymes, key interactions were studied using molecular docking, all-atom molecular dynamics (MD) simulations, and MM/GBSA binding free energy calculations. Overall, herein, the reported family of propargylamines exhibits promise as potential treatments for neurodegenerative disorders, such as Parkinson's disease. Interestingly, this is the first time a propargylamine scaffold bearing an internal alkyne has been reported to show activity against monoaminoxidases.

In Silico Investigations on the Synergistic Binding Mechanism of Functional Compounds with Beta-Lactoglobulin.

Piceatannol (PIC) and epigallocatechin gallate (EGCG) are polyphenolic compounds with applications in the treatment of various diseases such as cancer, but their stability is poor. ß-lactoglobulin (ß-LG) is a natural carrier that provides a protective effect to small molecule compounds and thus improves their stability. To elucidate the mechanism of action of EGCG, PIC, and palmitate (PLM) in binding to ß-LG individually and jointly, this study applied molecular docking and molecular dynamics simulations combined with in-depth analyses including noncovalent interaction (NCI) and binding free energy to investigate the binding characteristics between ß-LG and compounds of PIC, EGCG, and PLM. Simulations on the binary complexes of ß-LG + PIC, ß-LG + EGCG, and ß-LG + PLM and ternary complexes of (ß-LG + PLM) + PIC, (ß-LG + PLM) + EGCG, ß-LG + PIC) + EGCG, and (ß-LG + EGCG) + PIC were performed for comparison and characterizing the interactions between binding compounds. The results demonstrated that the co-bound PIC and EGCG showed non-beneficial effects on each other. However, the centrally located PLM was revealed to be able to adjust the binding conformation of PIC, which led to the increase in binding affinity with ß-LG, thus showing a synergistic effect on the co-bound PIC. The current study of ß-LG co-encapsulated PLM and PIC provides a theoretical basis and research suggestions for improving the stability of polyphenols.

Ligand-Based Design of Novel Quinoline Derivatives as Potential Anticancer Agents: An In-Silico Virtual Screening Approach.

In this study, using the Comparative Molecular Field Analysis (CoMFA) approach, the structure-activity relationship of 33 small quinoline-based compounds with biological anti-gastric cancer activity in vitro was analyzed in 3D space. Once the 3D geometric and energy structure of the target chemical library has been optimized and their steric and electrostatic molecular field descriptions computed, the ideal 3D-QSAR model is generated and matched using the Partial Least Squares regression (PLS) algorithm. The accuracy, statistical precision, and predictive power of the developed 3D-QSAR model were confirmed by a range of internal and external validations, which were interpreted by robust correlation coefficients (RTrain2=0.931; Qcv2=0.625; RTest2=0.875). After carefully analyzing the contour maps produced by the trained 3D-QSAR model, it was discovered that certain structural characteristics are beneficial for enhancing the anti-gastric cancer properties of Quinoline derivatives. Based on this information, a total of five new quinoline compounds were developed, with their biological activity improved and their drug-like bioavailability measured using POM calculations. To further explore the potential of these compounds, molecular docking and molecular dynamics simulations were performed in an aqueous environment for 100 nanoseconds, specifically targeting serine/threonine protein kinase. Overall, the new findings of this study can serve as a starting point for further experiments with a view to the identification and design of a potential next-generation drug for target therapy against cancer.

Molecular recognition between volatile molecules and odorant binding proteins 7 by homology modeling, molecular docking and molecular dynamics simulation.

BACKGROUND: Odorant-binding proteins (OBPs) in insects are key to detection and recognition of external chemical signals associated with survival. OBP7 in Spodoptera frugiperda's larval stage (SfruOBP7) may search for host plants by sensing plant volatiles, which are important sources of pest attractants and repellents. However, the atomic-level basis of binding modes remains elusive. RESULTS: SfruOBP7 structure was constructed through homology modeling, and complex models of six plant volatiles ((E)-2-hexenol, α-pinene, (Z)-3-hexenyl acetate, lauric acid, O-cymene and 1-octanol) and SfruOBP7 were obtained through molecular docking. To study the detailed interactions between the six plant volatile molecules and SfruOBP7, we conducted three 300 ns molecular dynamics simulations for each study object. The correlation coefficients between binding free energy obtained by molecular mechanics/generalized Born surface area together with solvated interaction energy methods and experimental values are 0.90 and 0.88, respectively, showing a good correlation. By comparing binding free energy along with interaction patterns between SfruOBP7 and the six volatile molecules, hotspot residues of SfruOBP7 when binding with different volatile molecules were determined. Hydrophobic interactions stemming from van der Waals interactions play a significant role in SfruOBP7 and these plant volatile systems. CONCLUSION: The optimized three-dimensional structure of SfruOBP7 and its binding modes with six plant volatiles revealed their interactions, thus providing a means for estimating the binding energies of other plant volatiles. Our study will help to guide the rational design of effective and selective insect attractants. © 2024 Society of Chemical Industry.

Tepotinib and tivantinib as potential inhibitors for the serine/threonine kinase of the mpox virus: insights from structural bioinformatics analysis.

The serine/threonine kinase (STK) plays a central role as the primary kinase in poxviruses, directing phosphoryl transfer reactions. Such reactions are pivotal for the activation of certain proteins during viral replication, assembly, and maturation. Therefore, targeting this key protein is anticipated to impede virus replication. In this work, a structural bioinformatics approach was employed to evaluate the potential of drug-like kinase inhibitors in binding to the ATP-binding pocket on the STK of the Mpox virus. Virtual screening of known kinase inhibitors revealed that the top 10 inhibitors exhibited binding affinities ranging from -8.59 to -12.05 kcal/mol. The rescoring of compounds using the deep-learning default model in GNINA was performed to predict accurate binding poses. Subsequently, the top three inhibitors underwent unbiased molecular dynamics (MD) simulations for 100 ns. Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) analysis and Principal Component Analysis (PCA) suggested tepotinib as a competitive inhibitor for Mpox virus STK as evidenced by its binding free energy and the induction of similar conformational behavior of the enzyme. Nevertheless, it is sensible to experimentally test all top 10 compounds, as scoring functions and energy calculations may not consistently align with experimental findings. These insights are poised to provide an attempt to identify an effective inhibitor for the Mpox virus.Communicated by Ramaswamy H. Sarma.

Computational exploration of FOXM1 inhibitors for glioblastoma: an integrated virtual screening and molecular dynamics simulation study.

In this study, a comprehensive investigation of a set of phytochemicals to identify potential inhibitors for the Forkhead box protein M1 (FOXM1) was conducted. FOXM1 is overexpressed in glioblastoma (GBM) cells and plays a crucial role in cell cycle progression, proliferation, and invasion. FOXM1 inhibitors have shown promising results in preclinical studies, and ongoing clinical trials are assessing their efficacy in GBM patients. However, there are limited studies on the identification of novel compounds against this attractive therapeutic target. To address this, the NPACT database containing 1,574 phytochemicals was used, employing a hierarchical multistep docking approach, followed by an estimation of relative binding free energy. By fixing user-defined XP-dock and MM-GBSA cut-off scores of -6.096 and -37.881 kcal/mol, the chemical space was further narrowed. Through exhaustive analysis of molecular binding interactions and various pharmacokinetics profiles, we identified four compounds, namely NPACT00002, NPACT01454, NPACT00856, and NPACT01417, as potential FOXM1 inhibitors. To assess the stability of protein-ligand binding in dynamic conditions, 100 ns Molecular dynamics (MD) simulations studies were performed. Furthermore, Molecular mechanics with generalized Born and surface area solvation (MM-GBSA) based binding free energy estimations of the entire simulation trajectories revealed a strong binding affinity of all identified compounds towards FOXM1, surpassing that of the control drug Troglitazone. Based on extensively studied multistep docking approaches, we propose that these molecules hold promise as FOXM1 inhibitors for potential therapeutic applications in GBM. However, experimental validation will be necessary to confirm their efficacy as targeted therapies.Communicated by Ramaswamy H. Sarma.

Structural insights into the interactions of repositioning and known drugs for Alzheimer's disease with hen egg white lysozyme by MM-GBSA.

Six drugs (dapsone, diltiazem, timolol, rosiglitazone, mesalazine, and milnacipran) that were predicted by network-based polypharmacology approaches as potential anti-Alzheimer's drugs, have been subjected in this study for in silico and in vitro evaluation to check their potential against protein fibrillation, which is a causative factor for multiple diseases such as Alzheimer's disease, Parkinson's disease, Huntington disease, cardiac myopathy, type-II diabetes mellitus and many others. Molecular docking and thereafter molecular dynamics (MD) simulations revealed that diltiazem, rosiglitazone, and milnacipran interact with the binding residues such as Asp52, Glu35, Trp62, and Asp101, which lie within the fibrillating region of HEWL. The MM-GBSA analysis revealed -7.86, -5.05, and -10.29 kcal/mol as the binding energy of diltiazem, rosiglitazone, and milnacipran. The RMSD and RMSF calculations revealed significant stabilities of these ligands within the binding pocket of HEWL. While compared with two reported ligands inhibiting HEWL fibrillation, milnacipran depicted almost similar binding potential with one of the known ligands (Ligand binding affinity -10.66 kcal/mol) of HEWL. Furthermore, secondary structure analyses revealed notable inhibition of the secondary structural changes with our candidate ligand; especially regarding retention of the 3/10 α-helix both by DSSP simulation, Circular dichroism, and FESEM-based microscopic image analyses. Taking further into experimental validation, all three ligands inhibited fibrillation in HEWL in simulated conditions as revealed by blue shift in Congo red assay and later expressing percentage inhibition in ThioflavinT assay as well. However, dose-dependent kinetics revealed that the antifibrillatory effects of drugs are more pronounced at low protein concentrations.Communicated by Ramaswamy H. Sarma.

3D computer modeling of inhibitors targeting the MCF-7 breast cancer cell line.

This study focused on developing new inhibitors for the MCF-7 cell line to contribute to our understanding of breast cancer biology and various experimental techniques. 3D QSAR modeling was used to design new tetrahydrobenzo[4, 5]thieno[2, 3-d]pyrimidine derivatives with good characteristics. Two robust 3D-QSAR models were developed, and their predictive capacities were confirmed through high correlations [CoMFA (Q2 = 0.62, R 2 = 0.90) and CoMSIA (Q2 = 0.71, R 2 = 0.88)] via external validations (R2 ext = 0.90 and R2 ext = 0.91, respectively). These successful evaluations confirm the potential of the models to provide reliable predictions. Six candidate inhibitors were discovered, and two new inhibitors were developed in silico using computational methods. The ADME-Tox properties and pharmacokinetic characteristics of the new derivatives were evaluated carefully. The interactions between the new tetrahydrobenzo[4, 5]thieno[2, 3-d]pyrimidine derivatives and the protein ERα (PDB code: 4XO6) were highlighted by molecular docking. Additionally, MM/GBSA calculations and molecular dynamics simulations provided interesting information on the binding stabilities between the complexes. The pharmaceutical characteristics, interactions with protein, and stabilities of the inhibitors were examined using various methods, including molecular docking and molecular dynamics simulations over 100 ns, binding free energy calculations, and ADME-Tox predictions, and compared with the FDA-approved drug capivasertib. The findings indicate that the inhibitors exhibit significant binding affinities, robust stabilities, and desirable pharmaceutical characteristics. These newly developed compounds, which act as inhibitors to mitigate breast cancer, therefore possess considerable potential as prospective drug candidates.

Discovery of thiazolidinedione-based pancreatic lipase inhibitors as anti-obesity agents: synthesis, in silico studies and pharmacological investigations.

A series of new 2,5-disubstituted arylidene derivatives of thiazolidinedione (16a-e, 17a-d, 18a-c) designed using molecular hybridization approach were synthesized, structurally characterized, and explored for their anti-obesity potential via inhibition of Pancreatic Lipase (PL). Compound 18a presented the most potent PL inhibitory activity with IC50 = 2.71 ± 0.31 µM, as compared to the standard drug, Orlistat (IC50 = 0.99 µM). Kinetic study revealed reversible competitive mode of enzyme inhibition by compound 18a with an inhibitory constant value of 1.19 µM. The most promising compound 18a revealed satisfactory binding mode within the active site of the target protein (human PL, PDB ID: 1LPB). Also, MM/PBSA binding free energy and molecular dynamics (MD) simulation analysis were performed for the most promising compound 18a, which showed potent inhibition according to the results of in vitro studies. Furthermore, a stable conformation of the 1LPB-ligand suggested the stability of this compound in the dynamic environment. The ADME and toxicity analysis of the compounds were examined using web-based online platforms. Results of in vivo studies confirmed the anti-obesity efficacy of compound 18a, wherein oral treatment with compound 18a (30 mg/kg) resulted in a significant reduction in the body weight, BMI, Lee index, feed intake (in Kcal), body fat depots and serum triglycerides. Compound 18a significantly decreased the levels of serum total cholesterol (TC) to 128.6 ± 0.59 mg/dl and serum total triglycerides (TG) to 95.73 ± 0.67 mg/dl as compared to the HFD control group. The present study identified disubstituted TZD derivatives as a new promising class of anti-obesity agents.Communicated by Ramaswamy H. Sarma.