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.

Novel Autotaxin Inhibitor ATX-1d Significantly Enhances Potency of Paclitaxel-An In Silico and In Vitro Study.

The development of drug resistance in cancer cells poses a significant challenge for treatment, with nearly 90% of cancer-related deaths attributed to it. Over 50% of ovarian cancer patients and 30-40% of breast cancer patients exhibit resistance to therapies such as Taxol. Previous literature has shown that cytotoxic cancer therapies and ionizing radiation damage tumors, prompting cancer cells to exploit the autotaxin (ATX)-lysophosphatidic acid (LPA)-lysophosphatidic acid receptor (LPAR) signaling axis to enhance survival pathways, thus reducing treatment efficacy. Therefore, targeting this signaling axis has become a crucial strategy to overcome some forms of cancer resistance. Addressing this challenge, we identified and assessed ATX-1d, a novel compound targeting ATX, through computational methods and in vitro assays. ATX-1d exhibited an IC50 of 1.8 ± 0.3 µM for ATX inhibition and demonstrated a significant binding affinity for ATX, as confirmed by MM-GBSA, QM/MM-GBSA, and SAPT in silico methods. ATX-1d significantly amplified the potency of paclitaxel, increasing its effectiveness tenfold in 4T1 murine breast carcinoma cells and fourfold in A375 human melanoma cells without inducing cytotoxic effects as a single agent.

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.

Pharmacophore-Based Study: An In Silico Perspective for the Identification of Potential New Delhi Metallo-ß-lactamase-1 (NDM-1) Inhibitors.

In the ongoing battle against antibiotic-resistant bacteria, New Delhi metallo-ß-lactamase-1 (NDM-1) has emerged as a significant therapeutic challenge due to its ability to confer resistance to a broad range of ß-lactam antibiotics. This study presents a pharmacophore-based virtual screening, docking, and molecular dynamics simulation approach for the identification of potential inhibitors targeting NDM-1, a critical enzyme associated with antibiotic resistance. Through the generation of a pharmacophore model and subsequent virtual screening of compound libraries, candidate molecules (ZINC29142850 (Z1), ZINC78607001 (Z2), and ZINC94303138 (Z3)) were prioritized based on their similarity to known NDM-1 binder (hydrolyzed oxacillin (0WO)). Molecular docking studies further elucidated the binding modes and affinities of the selected compounds towards the active site of NDM-1. These compounds demonstrated superior binding affinities to the enzyme compared to a control compound (-7.30 kcal/mol), with binding scores of -7.13, -7.92, and -8.10 kcal/mol, respectively. Binding interactions within NDM-1's active site showed significant interactions with critical residues such as His250, Asn220, and Trp93 for these compounds. Subsequent molecular dynamics simulations were conducted to assess the stability of the ligand-enzyme complexes, showing low root mean square deviation (RMSD) values between 0.5 and 0.7 nm for Z1, Z2, which indicate high stability. Z2's compactness in principal component analysis (PCA) suggests that it can stabilize particular protein conformations more efficiently. Z2 displays a very cohesive landscape with a notable deep basin, suggesting a very persistent conformational state induced by the ligand, indicating robust binding and perhaps efficient inhibition. Z2 demonstrates the highest binding affinity among the examined compounds with a binding free energy of -25.68 kcal/mol, suggesting that it could offer effective inhibition of NDM-1. This study highlights the efficacy of computational tools in identifying novel antimicrobial agents against resistant bacteria, accelerating drug discovery processes.

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.

Exploring Natural Compounds as Potential CDK4 Inhibitors for Therapeutic Intervention in Neurodegenerative Diseases through Computational Analysis.

CDK4 is a member of the serine-threonine kinase family, which has been found to be overexpressed in a plethora of studies related to neurodegenerative diseases. CDK4 is one of the most validated therapeutic targets for neurodegenerative diseases. Hence, the discovery of potent inhibitors of CDK4 is a promising candidate in the drug discovery field. Firstly, the reference drug Palbociclib was identified from the available literature as a potential candidate against target CDK4. In the present study, the Collection of Open Natural Products (COCONUT) database was accessed for determining potential CDK4 inhibitors using computational approaches based on the Tanimoto algorithm for similarity with the target drug, i.e., Palbociclib. The potential candidates were analyzed using SWISSADME, and the best candidates were filtered based on Lipinski's Rule of 5, Brenk, blood-brain barrier permeability, and Pains parameter. Further, the molecular docking protocol was accessed for the filtered compounds to anticipate the CDK4-ligand binding score, which was validated by the fastDRH web-based server. Based on the best docking score so obtained, the best four natural compounds were chosen for further molecular dynamic simulation to assess their stability with CDK4. In this study, two natural products, with COCONUT Database compound ID-CNP0396493 and CNP0070947, have been identified as the most suitable candidates for neuroprotection.

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.

Interaction of Per- and Polyfluoroalkyl Substances with Estrogen Receptors in Rainbow Trout (Oncorhynchus mykiss): An In Silico Investigation.

Fresh water sources, including lakes, such as the Great Lakes, are some of the most important ecosystems in the world. Despite the importance of these lakes, there is increasing concern about the presence of per- and polyfluoroalkyl substances (PFAS)─among the most prevalent contaminants of our time─due to the ability of PFAS to bioaccumulate and persist in the environment, as well as to its linkages to detrimental human and animal health effects. In this study, PFAS exposure on rainbow trout (Oncorhynchus mykiss) is examined at the molecular level, focusing on the impact of PFAS binding on the alpha (α) and beta (ß) estrogen receptors (ERs) using molecular dynamics simulations, binding free energy calculations, and structural analysis. ERs are involved in fundamental physiological processes, including reproductive system development, muscle regeneration, and immunity. This study shows that PFAS binds to both the estrogen α and estrogen ß receptors, albeit via different binding modes, due to a modification of an amino acid in the binding site as a result of a reorientation of residues in the binding pocket. As ER overactivation can occur through environmental toxins and pollutants, this study provides insights into the influence of different types of PFAS on protein function.

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.

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.

In-silico study MM/GBSA binding free energy and molecular dynamics simulation of some designed remdesivir derivatives as the inhibitory potential of SARS-CoV-2 main protease.

Background and purpose: Coronavirus disease (COVID-19) is one of the greatest challenges of the twentieth century. Recently, in silico tools help to predict new inhibitors of SARS-CoV-2. In this study, the new compounds based on the remdesivir structure (12 compounds) were designed. Experimental approach: The main interactions of remdesivir and designed compounds were investigated in the 3CLpro active site. The binding free energy of compounds by the MM-GBSA method was calculated and the best compound (compound 12 with the value of -88.173 kcal/mol) was introduced to the molecular dynamics simulation study. Findings/Results: The simulation results were compared with the results of protein simulation without the presence of an inhibitor and in the presence of remdesivir. Additionally, the RMSD results for the protein backbone showed that compound 12 in the second 50 nanoseconds has less fluctuation than the protein alone and in the presence of remdesivir, which indicates the stability of the compound in the active site of the Mpro protein. Furthermore, protein compactness was investigated in the absence of compounds and the presence of compound 12 and remdesivir. The Rg diagram shows a fluctuation of approximately 0.05 A, which indicates the compressibility of the protein in the presence and absence of compounds. The results of the RMSF plot also show the stability of essential amino acids during protein binding. Conclusion and implications: Supported by the theoretical results, compound 12 could have the potential to inhibit the 3CLpro enzyme, which requires further in vitro studies and enzyme inhibition must also be confirmed at protein levels.

Uncovering the anti-breast cancer activity potential of east Kalimantan propolis by In vitro and bioinformatics analysis.

Numerous side effects of breast cancer drugs have prompted researchers to explore more into new therapeutic approaches derived from natural substances. In this context, our study focused on uncovering the potential of East Kalimantan propolis from Trigona apicalis for breast cancer treatment including the underlying mechanisms through bioinformatics approached. We conducted integrated in vitro and bioinformatics analysis of network pharmacology, molecular docking, molecular dynamics and MM-GBSA analysis. Initially, in vitro cytotoxic assay demonstrated the anti-breast cancer activity potential of ethanol extract of East Kalimantan propolis, particularly its ethyl acetate fraction, which exhibited similar activity to doxorubicin, as indicated by their IC50 value. This study revealed eight propolis compounds, consisting of flavonoids and phenolic acids, in East Kalimantan propolis. By integrating microarray datasets (GSE29431, GSE36295, and GSE42568) analysis with potential targets derived from propolis compounds, 39 shared target genes were identified. Subsequently, GO and KEGG pathway, protein-protein interaction (PPI) network, core hub genes and gene expression analysis revealed three major targets, namely, PTGS2, CXCL2, and MMP9. Among them, only MMP9 was highly expressed in breast cancer than normal. Moreover, molecular docking revealed the six of propolis compounds which exhibited pronounced binding affinity towards MMP-9, better than marimastat as control drug. Dynamic simulation confirmed the stability of chrysin and quercetin as best compounds. Additionally, MM-GBSA analysis revealed a relative binding energy for chrysin (-25.6403 kcal/mol) that was comparable to marimastat (-27.3827 kcal/mol). In conclusion, this study reveals how East Kalimantan Propolis affect breast cancer and emphasizes MMP9 as a key target for future therapeutics.

Antiviral Activity, Pharmacoinformatics, Molecular Docking, and Dynamics Studies of Azadirachta indica Against Nipah Virus by Targeting Envelope Glycoprotein: Emerging Strategies for Developing Antiviral Treatment.

The Nipah virus (NiV) belongs to the Henipavirus genus is a serious public health concern causing numerous outbreaks with higher fatality rate. Unfortunately, there is no effective medication available for NiV. To investigate possible inhibitors of NiV infection, we used in silico techniques to discover treatment candidates in this work. As there are not any approved treatments for NiV infection, the NiV-enveloped attachment glycoprotein was set as target for our study, which is responsible for binding to and entering host cells. Our in silico drug design approach included molecular docking, post-docking molecular mechanism generalised born surface area (MM-GBSA), absorption, distribution, metabolism, excretion/toxicity (ADME/T), and molecular dynamics (MD) simulations. We retrieved 418 phytochemicals associated with the neem plant (Azadirachta indica) from the IMPPAT database, and molecular docking was used to ascertain the compounds' binding strength. The top 3 phytochemicals with binding affinities of -7.118, -7.074, and -6.894 kcal/mol for CIDs 5280343, 9064, and 5280863, respectively, were selected for additional study based on molecular docking. The post-docking MM-GBSA of those 3 compounds was -47.56, -47.3, and -43.15 kcal/mol, respectively. As evidence of their efficacy and safety, all the chosen drugs had favorable toxicological and pharmacokinetic (Pk) qualities. We also performed MD simulations to confirm the stability of the ligand-protein complex structures and determine whether the selected compounds are stable at the protein binding site. All 3 phytochemicals, Quercetin (CID: 5280343), Cianidanol (CID: 9064), and Kaempferol (CID: 5280863), appeared to have outstanding binding stability to the target protein than control ribavirin, according to the molecular docking, MM-GBSA, and MD simulation outcomes. Overall, this work offers a viable approach to developing novel medications for treating NiV infection.

Computational screening combined with well-tempered metadynamics simulations identifies potential TMPRSS2 inhibitors.

Type-II transmembrane serine proteases are effective pharmacological targets for host defence against viral entry and in certain cancer cell progressions. These serine proteases cleave viral spike proteins to expose the fusion peptide for cell entry, which is essential to the life cycle of the virus. TMPRSS2 inhibitors can also fight against respiratory viruses that employ them for cell entry. Our study combining virtual screening, all-atom molecular dynamics, and well-tempered metadynamics simulation identifies vicenin-2, neohesperidin, naringin, and rhoifolin as promising TMPRSS2 antagonists. The binding energies obtained are - 16.3, - 15.4, - 13.6, and - 13.8 kcal/mol for vicenin-2, neohesperidin, naringin, and rhoifolin respectively. The RMSD, RMSF, PCA, DCCM, and binding free energy profiles also correlate with the stable binding of these ligands at the active site of TMPRSS2. The study reveals that these molecules could be promising lead molecules for combating future outbreaks of coronavirus and other respiratory viruses.

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.

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.

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.

In Silico-Based Identification of Natural Inhibitors from Traditionally Used Medicinal Plants that can Inhibit Dengue Infection.

Dengue fever (DF) is an endemic disease that has become a public health concern around the globe. The NS3 protease-helicase enzyme is an important target for the development of antiviral drugs against DENV (dengue virus) due to its impact on viral replication. Inhibition of the activity of the NS3 protease-helicase enzyme complex significantly inhibits the infection associated with DENV. Unfortunately, there are no scientifically approved antiviral drugs for its prevention. However, this study has been developed to find natural bioactive molecules that can block the activity of the NS3 protease-helicase enzyme complex associated with DENV infection through molecular docking, MM-GBSA (molecular mechanics-generalized born surface area), and molecular dynamics (MD) simulations. Three hundred forty-two (342) compounds selected from twenty traditional medicinal plants were retrieved and screened against the NS3 protease-helicase protein by molecular docking and MM-GBSA studies, where the top six phytochemicals have been identified based on binding affinities. The six compounds were then subjected to pharmacokinetics and toxicity analysis, and we conducted molecular dynamics simulations on three protein-ligand complexes to validate their stability. Through computational analysis, this study revealed the potential of the two selected natural bioactive inhibitors (CID-440015 and CID-7424) as novel anti-dengue agents.

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.

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.