Regulation of protein-ligand binding affinity by hydrogen bond pairing

In Silico Drug Repurposing Against PSMB8 as a Potential Target for Acute Myeloid Leukemia Treatment

PSMB8 emerges as a prominent gene associated with cancer survival, yet its potential therapeutic role in acute myeloid leukemia (AML) remains unexplored within the existing literature. The principal aim of this study is to systematically screen an expansive library of molecular entities, curated from various databases to identify the prospective inhibitory agents with an affinity for PSMB8. A comprehensive assortment of molecular compounds obtained from the ZINC15 database was subjected to molecular docking simulations with PSMB8 by using the AutoDock tool in PyRx (version 0.9.9) to elucidate binding affinities. Following the docking simulations, a select subset of molecules underwent further investigation through comprehensive ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis employing AdmetSar and SwissADME tools. Finally, RMSD, RMSF, Rg, and H bond analyses were conducted via GROMACS to determine the best conformationally dynamic molecule that represents the candidate agent for the study. Following rigorous evaluation, Adozelesin, Fiduxosin, and Rimegepant have been singled out based on considerations encompassing bioavailability scores, compliance with filter criteria, and acute oral toxicity levels. Additionally, ligand interaction analysis indicates that Adozelesin and Fiduxosin exhibit an augmented propensity for hydrogen bond formation, a factor recognized for its facilitative role in protein-ligand interactions. After final analyses, we report that Fiduxosin may offer a treatment possibility by reversing the low survival rates caused by PSMB8 high activation in AML. This study represents a strategic attempt to repurpose readily available pharmaceutical agents, potentially obviating the need for de novo drug development, and thereby offering promising avenues for therapeutic intervention in specific diseases.

Development and biological evaluation of a novel CEACAM6-targeted PET tracer for distinguishing malignant nodules in early-stage lung adenocarcinoma

PURPOSE

Low-dose CT (LDCT) screening effectively reduces lung adenocarcinoma (LUAD) mortality. However, accurately evaluating the malignant potential of indeterminate lung nodules remains a challenge. Carcinoembryonic antigen cell adhesion molecule 6 (CEACAM6), a potential biomarker for distinguishing benign pulmonary nodules from LUAD, may be leveraged for noninvasive positron emission tomography (PET) imaging to aid LUAD diagnosis.

METHODS

This study utilized mRNA, protein, and survival datasets of LUAD patients, along with an animal model of malignant pulmonary nodules, to investigate CEACAM6 expression specificity and its correlation with LUAD. Targeting ligands for CEACAM6 were designed using the Rosetta platform, labeled with [68Ga]Ga, and screened through high-throughput PET imaging to identify the optimal tracer.

RESULTS

CEACAM6 was found to be specifically overexpressed in LUAD and was significantly associated with poor prognosis and disease progression. In vivo, [68Ga]Ga-NODA-P3 demonstrated high specificity for delineating CEACAM6-positive A549 xenografts, a LUAD model, via PET imaging, achieving a highest target-to-background ratio of 7.68 ± 0.44. Region of interest (ROI) analysis showed significantly higher tracer uptake in A549 xenografts compared to CEACAM6-negative Huh7 xenografts (a hepatocellular carcinoma model) at 30 min post-injection (1.81 ± 0.10%ID/g vs. 0.54 ± 0.06%ID/g). Pre-treatment with an excess of unlabeled NODA-P3 significantly reduced tumor uptake to 0.52 ± 0.07%ID/g.

CONCLUSION

These preclinical findings indicate that [68Ga]Ga-NODA-P3 is a candidate radiotracer for the non-invasive visualization of CEACAM6-positive LUAD, demonstrating favorable imaging contrast. Although the current tumor uptake limits its immediate clinical application, ongoing optimization efforts are expected to improve its efficacy, enabling earlier and more accurate diagnosis of malignant pulmonary nodules in LUAD.

Discovery of Potential Anthelmintic Agents Against Gyrodactylus kobayashii Through Computer-Aided Drug Design and In Vivo Evaluation

Monogeneans are ectoparasitic flatworms causing significant economic losses in aquaculture. This study aimed to identify potential anthelmintic agents against these parasites by integrating computer-aided drug design (CADD) and in vivo evaluation. The β-tubulin gene, a well-established anthelmintic target, was cloned from Gyrodactylus kobayashii and its three-dimensional structure was generated using homology modelling. Virtual screening of 2319 FDA-approved drugs and nine common benzimidazoles against the modelled β-tubulin identified several promising compounds with low binding energy. Subsequent in vivo anthelmintic efficacy and acute toxicity assays in goldfish revealed etravirine as a potent candidate with an EC50 value of 0.55 mg/L and a therapeutic index (TI) greater than 18.18. This favourable safety profile highlights etravirine's potential for controlling monogenean infections in aquaculture. Flubendazole and mebendazole also demonstrated potent anthelmintic activity, with EC50 values of 0.022 and 0.023 mg/L and therapeutic indices exceeding 45.45 and 43.48, respectively. Molecular dynamics simulations confirmed stable binding modes for flubendazole and mebendazole with β-tubulin, providing mechanistic insights into their anthelmintic activity. Overall, this study demonstrated the utility of CADD in identifying potential therapeutic agents against monogenean and underscored the importance of β-tubulin as a key target for anthelmintic therapy, contributing to the development of sustainable aquaculture practices.

In-silico analysis of nsSNPs in BCL-2 family proteins: Implications for colorectal cancer pathogenesis and therapeutics

Colorectal cancer (CRC) is a multifaceted disease characterized by abnormal cell proliferation in the colon and rectum. The BCL-2 family proteins are implicated in CRC pathogenesis, yet the impacts of genetic variations within these proteins remains elusive. This in-silico study employs diverse sequence- and structure-based bioinformatics tools to identify potentially pathogenic nonsynonymous single nucleotide polymorphisms (nsSNPs) in BCL-2 family proteins. Leveraging computational tools including SIFT, PolyPhen-2, SNPs&GO, PhD-SNP, PANTHER, and Condel, 94 nsSNPs were predicted as deleterious, damaging, and disease-associated by at least five tools. Stability analysis with I-Mutant2.0, MutPred, and PredictSNP further identified 31 nsSNPs that reduce protein stability. Conservation analysis highlighted highly functional, exposed variants (rs960653284, rs758817904, rs1466732626, rs569276903, rs746711568, rs764437421, rs779690846, and rs2038330314) and structural, buried variants (rs376149674, rs1375767408, rs1582066443, rs367558446, rs367558446, rs1319541919, and rs1370070128). To explore the functional effects of these mutations, molecular docking and molecular dynamics simulations were conducted. G233D (rs376149674) and R12G (rs960653284) mutations in the BCL2 protein exhibited the greatest differences in docking scores with d-α-Tocopherol and Tocotrienol, suggesting enhanced protein-ligand interactions. The simulations revealed that d-α-Tocopherol and Tocotrienol (strong binders) contributed to greater stability of BCL-2 family proteins, while Fluorouracil, though weaker, still demonstrated selective binding stability. This work represents the first comprehensive computational analysis of functional nsSNPs in BCL-2 family proteins, providing insights into their roles in CRC pathogenesis. While these findings demand experimental validation, they hold great promise for guiding future large-scale population studies, facilitating drug repurposing efforts, and advancing the development of targeted diagnostic and therapeutic modalities for CRC.

Computational investigations on the anaesthetic drug, tetracaine (TCA) by DFT, TD-DFT, molecular docking, and molecular dynamic simulation analysis

The current investigation deals with the theoretical exploration of tetracaine (TCA) employing density function theory (DFT), time-dependent density function theory (TD-DFT), molecular docking (MD), and molecular dynamic simulation (MDS). The B3LYP method was utilised for this study in conjunction with a 6-31++G(d,p) basis set. We computed the charge distribution of the molecule tetracaine using molecular electrostatic potential (MEP) analysis, which indicate how molecules interact and what kinds of chemical bonds they have. Additionally, population analysis and Fukui function analysis have explored charges on the atoms. This comprehensive study also includes an assessment of various parameters such as chemical hardness, chemical softness, and electrophilicity index through the Frontier Molecular Orbital (FMO) investigation. The molecule's non-linear optical (NLO) properties were conducted to ascertain the hyperpolarizability and polarity values. Lastly, molecular docking was used to look at how a ligand and two protein receptors, named monoamine oxidase A (code: 2BXR) and monoamine oxidase B (code: 1OJD), interact with a ligand. The resulting binding energies were determined to be -7.7 and -7.6 kcal/mol, respectively. Following the completion of the docking process, an investigation of conformational behaviour was conducted with the assistance of molecular dynamic simulation (MDS). These findings indicate the possible applicability of this interaction in the field of medicine. This study has the potential to be utilized in the future to advance the creation of amphiphilic drugs.

Pharmacophore modeling, 2D-QSAR, molecular docking and ADME studies for the discovery of inhibitors of PBP2a in MRSA

Methicillin-resistant Staphylococcus aureus (MRSA) is considered to be a worldwide threat to human health and the global spread of MRSA has been associated with the emergence of different types of infections and resultant selection pressure due to exposure to many antibiotics. In the current era characterized by incessant antibiotic resistance, assessment of multiple molecular targets represents notable therapeutic opportunities in the medical and pharmaceutical industry and can aid in the discovery of novel molecules that inhibit various receptors effectively to replace the current weak antimicrobial agents. Penicillin binding protein 2a (PBP2a) of MRSA is a major determinant of resistance to β-lactam antibiotics. The activity of PBP2a is not inhibited by β-lactam antibiotics, allowing the strain to survive in the presence of β-lactams leading to resistance to β-lactam antibiotics. The study aimed at identifying potential inhibitors of PBP2a receptor of MRSA through ligand-based pharmacophore modeling, 2D-QSAR, molecular docking, ADMET screening as well as molecular dynamic (MD) simulations. The study led to the development of a satisfactory, predictive and significant 2D-QSAR model for predicting anti-MRSA activity of compounds and also led to the identification of two molecules: C21H25N7O4S2 (ChEMBL30602) and C20H17NO6S (ChEMBL304837) with favorable pharmacophore features and ADME properties with potential to bind strongly to PBP2a receptor of MRSA. MD simulation analysis showed that the interactions of C20H17NO6S (ChEMBL304837) with PBP2a over 100 ns was more stable and similar to the interaction of ceftobiprole with PBP2a and may become potential drug candidate against MRSA which has developed a lot of resistance to current antibiotics.

In silico analysis to explore the therapeutic potential of propolis-derived small molecules as matriptase inhibitors to suppress breast cancer growth and metastasis

Breast cancer is a major cause of death in women, and various drug therapies are used for its treatment. However, current therapies have many side effects and limitations. Propolis, a resinous product of bee hives, possesses a variety of biological activities, including anticancer and chemo-protective properties. The present study aimed to investigate the potential suitability of propolis-derived compounds to inhibit matriptase (MT-SP1), a potential protein target for breast cancer treatment, through comprehensive computational analysis. The MT-SP1 protein structure (PDB ID: 1EAX) was retrieved, energy-minimized, and validated. Five propolis-derived compounds with the highest binding energies to MT-SP1 were selected after virtual screening. Molecular docking of these selected ligands revealed binding energies ranging from -8.4 to -9.1 kcal/mol. Stable complex formation was validated by an additional 250 ns of molecular dynamics simulations. The HOMO-LUMO and DFT characteristics provided further evidence of the chemical reactivity and stability of these five ligands at the MT-SP1 active site. Screening of compounds for drug-likeness, pharmacokinetics (ADMET profiles), and toxicity identified two promising small molecules (PubChem IDs of ligands 72307 and 129827386) as potential drug candidates for inhibiting MT-SP1. However, experimental validation through in vitro or in vivo studies is necessary to confirm these computational findings and explore their therapeutic potential for breast cancer treatment.

Analysis of the bonding affinities between human PSGL-1 and Vpu derived from the different HIV-1 groups - in silico insights

Human P-selectin glycoprotein ligand 1 (PSGL-1) and HIV-1 viral protein U (Vpu) play major roles in limiting and increasing the ability of HIV-1 to infect cells, respectively. There is currently no published data reporting on the specific interactions between PSGL-1 and Vpu, and possible outcomes and consequences of these interactions. To date, it has only been established that Vpu binds human PSGL-1 to degrade PSGL-1 and therefore promote HIV replication. There are, however, four different types of HIV-1, and it would be helpful to know how VpuM, VpuN, VpuO, and VpuP can bind to and possibly inhibit PSGL-1 expression. Bioinformatics methods were used to find out how strongly each type of Vpu found in the different HIV-1 groups bonds with human PSGL-1. Thus, we used molecular docking (MD) and molecular dynamics simulations (MDS) to figure out how PSGL-1 and VpuM, VpuN, VpuO, and VpuP interact with each other. To ensure the reliability of the predicted outcomes, the binding energy of each model was calculated using the MM/GBSA technique. Our findings show that PSGL-1-VpuP (4 H bonds, 2 salt bridges) and PSGL-1-VpuM (3 H bonds, 2 salt bridges) have stronger bonding affinities than PSGL-1-VpuN (4 H bonds, no salt bridges) and PSGL-1-VpuO (2 H bonds, 1 salt bridge). The MDS test also shows that PSGL-1-VpuM and PSGL-1-VpuP protein complexes are more stable and compact, with lower residual fluctuations compared to PSGL-1-VpuN and PSGL-1-VpuO protein complexes. Binding free energies of -82.27 ± 1.35 kcal/mol, -82.17 ± 0.84 kcal/mol, -67.84 ± 0.63 kcal/mol, and -131.86 ± 1.08 kcal/mol were recorded for each of PSGL1-VpuM, PSGL1-VpuN, PSGL1-VpuO, and PSGL1-VpuP, respectively, which further supports our results. Our research shows that Vpu from the M and P HIV-1 groups may be better at blocking human PSGL-1 than VpuO and VpuN groups. These results are novel in this specific realm of HIV research, and as such, further investigations in more robust experimental studies are warranted.

MolSnapper: Conditioning Diffusion for Structure-Based Drug Design

Generative models have emerged as potentially powerful methods for molecular design, yet challenges persist in generating molecules that effectively bind to the intended target. The ability to control the design process and incorporate prior knowledge would be highly beneficial for better tailoring molecules to fit specific binding sites. In this paper, we introduce MolSnapper, a novel tool that is able to condition diffusion models for structure-based drug design by seamlessly integrating expert knowledge in the form of 3D pharmacophores. We demonstrate through comprehensive testing on both the CrossDocked and Binding MOAD data sets that our method generates molecules better tailored to fit a given binding site, achieving high structural and chemical similarity to the original molecules. Additionally, MolSnapper yields approximately twice as many valid molecules as alternative methods.

Memory-Enhancing Effects of Daidzin, Possibly Through Dopaminergic and AChEergic Dependent Pathways

BACKGROUND

The soy isoflavone daidzin (DZN) possesses cognitive-enhancing effects in animals.

OBJECTIVES

However, the mechanism for this effect is yet to be discovered.

METHODS

For this, we investigate its memory-enhancing capacity using the mouse models of marble burying, dust removal, an open-field study, and in silico studies. Adult male Swiss albino mice were randomly assigned to different groups consisting of control (vehicle: 10 mL/kg), DZN 5, 10, and 20 mg/kg, dopamine (agonist: 22 mg/kg), galantamine (inhibitor: 3 mg/kg), and a combination of DZN-10 with standards.

RESULTS

DZN dose-dependently and significantly (P < 0.05) increased marble burying and removed dust while decreasing the total distance in the open-field test (OFT). DZN-10 enhanced dopamine's effect significantly (P < 0.05). In silico findings suggest that DZN has strong binding capacities of -10.3, -7.5, -9.8, and -9.2 kcal/mol to the acetylcholinesterase (AChE), D1, D3, and D5 receptors, respectively.

CONCLUSIONS

Taken together, DZN may exert its memory-enhancing ability by interacting with AChE and dopamine receptors.

Collective in-silico and in-vitro evaluation indicate natural phenolics as a potential therapeutic candidate targeting antimicrobial-resistant genes of Helicobacter pylori

Antibiotic-resistant Helicobacter pylori is a major cause of severe gastric conditions such as ulcers and gastric cancer, with limited treatment options due to the rise of multidrug-resistant strains. This study aims to identify novel drug targets within antimicrobial resistance (AMR) genes and evaluate potential therapeutic candidates using computational and experimental approaches. AMR genes in H. pylori were identified using RAST and their essentiality, metabolic pathways, and druggability. Localization, protein family, and functional annotations were performed using QuickGO and Pfam, while Cytoscape was used for protein interaction analysis and identification of hub proteins. Ddl was selected as the target protein for further study among the AMR genes. Using the PASS tool, two phenolic compounds were identified as potential inhibitors of Ddl, and their interaction potency was confirmed through molecular docking studies. In-vitro experiments demonstrated that α-mangostin significantly attenuated H. pylori-mediated inflammatory responses in the gastric environment. Notably, α-mangostin induced the mitochondrial-mediated intrinsic apoptotic pathway in gastric epithelial cells, offering new insights into its therapeutic potential. This study identified Ddl as a promising drug target among AMR genes in H. pylori and highlighted phenolic compounds, particularly α-mangostin, as potential inhibitors. These findings contribute to the development of novel anti-H. pylori therapies address the growing challenge of antibiotic resistance and pave the way for future research into effective treatments for H. pylori infections.

Computational study of interaction of calixarene with ebola virus structural proteins and its potential therapeutic implications

Ebola virus (EBOV) is a negative-strand RNA virus that causes hemorrhagic fever and fatal illness in humans. According to WHO, the Ebola virus caused 28,646 fatal cases and 11,323 deaths in West Africa due to hemorrhagic fever and deadly disease in humans between 2013 and 2016. Between 1976 and 2022, approximately 15,409 fatalities caused by EBOV took place worldwide. Unfortunately, no effective vaccine or drugs are available to prevent this deadly disease. In the present study, State-of-the-art tools based on in-silico methods were used to elucidate the interaction pattern of calixarene (CAL) with seven EBOV structural proteins, i.e., GP1,2, nucleoprotein (NP), polymerase cofactor (VP35), (VP40), transcription activator (VP30), VP24, and RNA-dependent RNA polymerase (L). CAL is a cage-like compound with supramolecular features. The molecular docking lead analysis using AutoDock tool has been performed to find out the binding pattern of CAL with EBOV proteins. Obtained results revealed efficient inhibitory properties of calixarene (CAL) against seven Ebola virus structural proteins i.e., GP1,2, nucleoprotein (NP), polymerase cofactor (VP35), (VP40), transcription activator (VP30), VP24, and RNA-dependent RNA polymerase (L). Molecular docking analysis shows that the interaction of CAL with VP24 was highest with the total binding energy -12.47 kcal/mol and 26.90 nM inhibitions constant. Molecular Dynamics study has also quantified the efficiency of CAL against VP24. In conclusion, the present study suggests that CAL and its derivatives could be used as inhibitors to counter EBOV infection. Furthermore, in vitro and in vivo laboratory experimentation is required to establish CAL and its derivatives as a potential inhibitor against EBOV.

Assessment of Sedative Activity of Lonicerin: In Vivo Approach With Pharmacokinetics and Molecular Docking

BACKGROUND

Lonicerin (LON) has been identified to have different biological properties, such as anticancer, anti-inflammatory, immunomodulatory, antibacterial, antimicrobial, and neuroprotective. This study aims to assess the sedative effect of LON in Swiss albino mice, which is yet to be discovered.

MATERIALS AND METHODS

Mice were treated with two different doses of LON (5 and 10 mg/kg) and 2 mg/kg of diazepam (DZP), which is the referral GABAergic medication, and the latency time and sleeping duration of animals were observed. A computational study was also conducted to evaluate the docking scores and display the binding sites of LON and receptor (GABAA α1 and β2 subunits). The study also investigated the pharmacokinetics and drug-likeness properties of LON along with toxicological analysis by using SwissADME and Protox-3 software, respectively.

RESULTS

Findings revealed that the higher concentration of LON reduced the latency (9.86 ± 1.44 min) and increased the sleep duration (191.29 ± 7.43 min) compared to the lower concentration. Besides, the combination group of LON and DZP showed the lowest latency (6.17 ± 0.82 min) and highest sleeping time (219.00 ± 6.39 min). In the in silico study, LON exhibited a strong docking score (-8.1 kcal/mol) with the macromolecules, which is closer to the binding affinity of DZP (-8.3 kcal/mol), indicating that LON could show strong sedative activity by binding with the GABAA receptor. Computational toxicity analysis revealed that LON is non-hepatotoxic, non-neurotoxic, noncarcinogenic, noncytotoxic, non-ecotoxic, and non-mutagenic.

CONCLUSION

Therefore, LON may be effective for the treatment of insomnia in the near future.

Molecular Docking and Molecular Dynamics Study of Propolis Compounds of Sulabiroin-A, Sulabiroin-B, and Broussoflavonol F Toward Tuberculosis 3PTY Target Protein

Molecular docking and molecular dynamics simulations were conducted to assess propolis compounds of sulabiroin-A, sulabiroin-B, and broussoflavonol F as tuberculosis (TB) inhibitors with rifampicin as the control ligand. TB remains a significant world health concern, requiring the development of new drug candidates to address more drug-resistant variants. The target protein chosen was 3PTY. The molecular docking simulation showed that sulabiroin-A, sulabiroin-B, and broussoflavonol F docking scores are comparable to rifampicin, with the order of docking score from least favorable to more favorable is sulabiroin-B< sulabiroin-A< rifampicin< broussoflavonol F (-3.397, -3.449, -5.256, -5.961). Molecular dynamics simulations also demonstrated that sulabiroin-B exhibited stable interactions with the target protein, comparable to rifampicin, while sulabiroin-A and broussoflavonol F demonstrated increased fluctuation, suggesting possible instability. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) study verified that all three drugs possess advantageous pharmacokinetic characteristics, with broussoflavonol F exhibiting the most favorable safety and tolerability profile. According to these findings, sulabiroin-B is recognized as the most promising candidate for TB treatment owing to its enhanced stability in molecular dynamics simulations, although broussoflavonol F and sulabiroin-A exhibit intermediate promise. Additional experimental validation is advised to verify their therapeutic efficacy.

Deciphering the Regulatory Potential of Antioxidant and Electron-Shuttling Bioactive Compounds in Oolong Tea

OT has gained attention for its high polyphenol content and therapeutic potential. To elucidate this further, this study investigated the electron-shuttling bioactive compounds of OT and evaluated their effect on dysregulated breast cancer (BC) genes. OT extracts were obtained via solvent extraction (SE) and supercritical fluid extraction (SFE), followed by in vitro assays. Phytochemical analysis revealed that ethanol-extracted OT (OTL-E) had the highest polyphenol, flavonoid, and tannin contents, correlating with strong antioxidant activity, while water-extracted OT (OTL-W) exhibited greater bioelectricity-stimulating properties in microbial fuel cells (MFC), confirmed by cyclic voltammetry (CV). Based on phytochemical analyses, SE displayed a better extraction technique for isolating OT bioactive compounds compared to SFE. In silico approaches through network pharmacology, molecular docking and dynamics simulations revealed that polyphenols with ortho- or para-dihydroxyl groups targeted dysregulated BC proteins involved in kinase signaling, apoptosis, and hormone receptor pathways. Luteolin exhibited the highest binding affinities to MAPK1 and PIK3CA with free energy (ΔG) of -9.1 and -8.4 kcal/mol, respectively. Trajectory-based analyses confirmed enthalpy-favored ligand-induced conformational changes to these oncoproteins, altering their function in BC development. These findings suggest the potential of OT as a bioelectricity-stimulating and chemopreventive agent, warranting further in vitro and in vivo validation.

Computer-Aided Discovery of Natural Compounds Targeting the ADAR2 dsRBD2-RNA Interface and Computational Modeling of Full-Length ADAR2 Protein Structure

Mesothelioma is a rare and aggressive cancer linked to asbestos exposure and characterized by rapid metastasis and poor prognosis. Inhibition of adenosine deaminase acting on dsRNA 2 (ADAR2) RNA binding but not ADAR2 editing has shown antitumor effects in mesothelioma. Natural compounds from the Traditional Chinese Medicine (TCM) database were docked to the RNA-binding interface of ADAR2's second dsRNA binding domain (dsRBD2), and their drug-likeness and predicted safety were assessed. Eight ligands (ZINC000085597263, ZINC000085633079, ZINC000014649947, ZINC000034512861, ZINC000070454124, ZINC000085594944, ZINC000085633008, and ZINC000095909822) showed high binding affinity to dsRBD2 from molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) calculations. Protein-ligand interactions were analyzed to identify key residues contributing to these binding affinities. Molecular dynamics (MD) simulations of dsRBD-ligand-RNA complexes revealed that four compounds (ZINC000085597263, ZINC000085633079, ZINC000014649947, and ZINC000034512861) had negative binding affinities to dsRBD2 in the presence of the RNA substrate GluR-2. Key residues, including Val164, Met165, Lys209, and Lys212, were crucial for ligand binding, even with RNA present, suggesting these compounds could inhibit dsRBD2's RNA-binding function. The predicted biological activities of these compounds indicate potential anticancer properties, particularly for the treatment of mesothelioma. These compounds are structurally similar to known anti-mesothelioma agents or anticancer drugs, highlighting their therapeutic potential. Current mesothelioma treatments are limited. Optimization of these compounds, alone or in combination with current therapeutics, has potential for mesothelioma treatment. Additionally, five high-quality full-length ADAR2 models were developed. These models provide insights into ADAR2 function, mutation impacts, and potential areas for protein engineering to enhance stability, RNA-binding specificity, or protein interactions, particularly concerning dimerization or complex formation with other proteins and RNAs.

Medicinal Phytocompounds as Potential Inhibitors of p300-HIF1α Interaction: A Structure-Based Screening and Molecular Dynamics Simulation Study

Background: Hypoxia plays a key role in cancer progression, mainly by stabilizing and activating hypoxia-inducible factor-1 (HIF-1). For HIF-1 to function under low oxygen conditions, it must interact with the transcriptional coactivator p300, a critical step for promoting cancer cell survival and adaptation in hypoxic environments. Methods: Consequently, we used drug design and molecular simulation techniques to screen phytochemical databases, including traditional Chinese and African medicine sources, for compounds that could disrupt the p300/HIF-1 interaction. Results: In this study, we identified potential compounds with high docking scores such as EA-176920 (-8.719), EA-46881231 (-8.642), SA-31161 (-9.580), SA-5280863 (-8.179), NE-5280362 (-10.287), NE-72276 (-9.017), NA-11210533 (-10.366), NA-11336960 (-7.818), TCM-5281792 (-12.648), and TCM-6441280 (-9.470 kcal/mol) as lead compounds. Furthermore, the compound with the highest docking score from each database (EA-176920, SA-31161, NE-5280362, NA-11210533, and TCM-5281792) was subjected to further analysis. The stable binding affinity of these compounds with p300 was confirmed by Post-simulation binding free energy (-22.0020 kcal/mol, -25.4499 kcal/mol, -32.4530 kcal/mol, -33.9918 kcal/mol, and -57.7755 kcal/mol, respectively) and KD analysis. Moreover, the selected compounds followed the Lipinski rules with favorable ADMET properties like efficient intestinal absorption, high water solubility, and no toxicity. Conclusions: Our findings highlight the potential of natural compounds to target key protein-protein interactions in cancer and lay the groundwork for future in vitro and in vivo studies to explore their therapeutic potential. Specifically, disrupting the p300/HIF-1 interaction could interfere with hypoxia-driven pathways that promote tumor growth, angiogenesis, and metastasis, offering a promising strategy to suppress cancer progression at the molecular level.

Identification and molecular mechanism of novel salt-enhancing peptide in crocodile hemoglobin: a combined E-tongue, molecular docking, and dynamic simulation

BACKGROUND

This study aimed to reduce salt intake without compromising food sensory properties. Novel salt-enhancing peptides were identified from crocodile hemoglobin via virtual screening and evaluated for their salt-reducing effects using molecular docking, electronic tongue analysis, and molecular dynamics simulations.

RESULTS

A total of 24 water-soluble and non-toxic peptides were obtained by virtual enzymolysis. The protein structure of human transmembrane channel-like 4 (TMC4), a novel salt taste receptor, was constructed using AlphaFold2 and applied as a receptor. The salt-reducing effect of these peptides was verified using electronic tongue analysis, in which the peptide SSDDK had a significant salt-reducing effect. Molecular docking results showed that the main force for peptide binding to the TMC4 receptor was conventional hydrogen bonding, and Arg 583, Arg330, and Glu284 were the key amino acid residues for its binding. Molecular dynamics simulations also verified the stability of peptide-receptor binding.

CONCLUSION

This study demonstrates that the peptide SSDDK, derived from crocodile hemoglobin, can be used to enhance salty taste and reduce sodium salt use. © 2025 Society of Chemical Industry.

Structural Mechanisms Driving the Selective Efficacy of Oxamniquine against Schistosoma mansoni and Schistosoma japonicum

Oxamniquine (OXA) exhibits selective efficacy against different Schistosoma species, with the highest activity observed in Schistosoma mansoni sulfotransferase (SmSULT) and the lowest in Schistosoma japonicum sulfotransferase (SjSULT). This study utilises advanced atomistic and molecular simulations to elucidate the structural dynamics induced by OXA binding to SmSULT and SjSULT, aiming to unravel the underpinnings of this selective efficacy. Binding free energy (BFE) analyses revealed a markedly higher affinity of OXA for SmSULT (-48.04 kcal/mol) compared to wtSjSULT (-22.84 kcal/mol), with a significant restoration of binding affinity (-39.23 kcal/mol) observed in SjSULT following the mutation of Val139 to Gly139. Comprehensive conformational assessments highlighted that SmSULT-OXA achieves its superior efficacy by stabilising the protein structure, in stark contrast to the erratic conformational behaviour of wild-type SjSULT. Notably, this erratic behaviour is ameliorated upon mutation, leading to a restoration of OXA's efficacy in SjSULT. These insights elucidate the structural mechanisms underpinning OXA's selective efficacy and provide valuable perspectives on its targeted action against Schistosoma spp.

The Saccharomyces cerevisiae amino acid transporter Lyp1 has a broad substrate spectrum

The main mediators for the amino acid uptake in Saccharomyces cerevisiae are the permeases belonging to the yeast amino acid transporter family. Recently, we discovered that members of this family support growth on more amino acids than previously described. Here we study the substrate spectrum of Lyp1, the main transporter responsible for the uptake of lysine in yeast. We show that overexpressed Lyp1 supports growth on alanine, asparagine, leucine, methionine, phenylalanine, serine, and valine when these are provided as the sole source of nitrogen to a strain severely deficient for the uptake of amino acids. We show that alanine and serine compete with lysine for the common transport system, albeit with much lower affinity. Thus, Lyp1 has a much broader substrate spectrum than previously thought, which may be true for many amino acid transporters.

Screening of medicinal phytocompounds with structure-based approaches to target key hotspot residues in tyrosyl-DNA phosphodiesterase 1: augmenting sensitivity of cancer cells to topoisomerase I inhibitors

One of cancer's well-known hallmarks is DNA damage, yet it's intriguing that DNA damage has been explored as a therapeutic strategy against cancer. Tyrosyl-DNA phosphodiesterase 1, involved in DNA repair from topoisomerase I inhibitors, a chemotherapy class for cancer treatment. Inhibiting TDP1 can increase unresolved Top1 cleavage complexes in cancer cells, inducing DNA damage and cell death. TDP1's catalytic activity depends on His263 and His493 residues. Using molecular simulation, structure-based drug design, and free energy calculation, we identified potential drugs against TDP1. A multi-step screening of medicinal plant compound databases (North Africa, East Africa, Northeast Africa, and South Africa) identified the top four candidates. Docking scores for top hits 1-4 were -7.76, -7.37, -7.35, and -7.24 kcal/mol. Top hit 3 exhibited the highest potency, forming a strong bonding network with both His263 and His493 residues. All-atoms simulations showed consistent dynamics for top hits 1-4, indicating stability and potential for efficient interaction with interface residues. Minimal fluctuations in residue flexibility suggest these compounds can stabilize internal flexibility upon binding. The binding free energies of -35.11, -36.70, -31.38, and -23.85 kcal/mol were calculated for the top hit 1-4 complexes. Furthermore, the chosen compounds demonstrate outstanding ADMET characteristics, such as excellent water solubility, effective gastrointestinal absorption, and the absence of hepatotoxicity. Cytotoxicity analysis revealed top hit 2 higher probability of activity against 24 cancer cell lines. Our findings suggest that these compounds (top hits 1-4) hold promise for innovative drug therapies, suitable for both in vivo and in vitro experiments.

Docking Survey, ADME, Toxicological Insights, and Mechanistic Exploration of the Diels-Alder Reaction Between Hexachlorocyclopentadiene and Dichloroethylene

The Diels-Alder (DA) reaction between hexachlorocyclopentadiene and 1,2-dichloroethylene has been studied using the Molecular Electron Density Theory (MEDT) through Density Functional Theory (DFT) calculations at the B3LYP/6-31G(d) level. The electronic structure of the reagents has been characterized through the electron localization function (ELF) and the conceptual DFT (CDFT). The DA reaction of hexachlorocyclopentadiene with 1,2-dichloroethylene proceeds via a synchronous or low asynchronous one-step mechanism. Based on the conducted research, a two-step mechanism with a biradical intermediate was completely ruled out. Bonding Evolution Theory (BET) study of the DA reaction shows that this reaction is topologically characterized by nine different phases. The reaction begins with the rupture of the double bonds in substrate molecules. Formation of the first CC single bond takes place in phase VII, while the second CC single bond takes place in phase IX. Formation of these two single bonds takes place by sharing the nonbonding electron densities of the two pairs of pseudoradical centers. In addition, this study evaluates some ligands as potential HIV-1 inhibitors. Docking results identified 5 and 5-F as the most promising candidates, surpassing AZT in theoretical affinity. ADME analysis revealed limitations in solubility and absorption for compounds 3, 4, and 5, while 5-F showed better solubility but low absorption. Toxicity concerns around 5-F suggest the need for risk management, while the other compounds require further safety assessment.

Enhanced sampling simulations to explore himalayan phytochemicals as potential phosphodiesterase-1 inhibitor for neurological disorders

The rising incidence of neurological and neuropsychiatric disorders underscores the urgent need for innovative and evidence based treatment strategies. Phosphodiesterase-1 (PDE1) is a dual-substrate (cAMP/cGMP) phosphodiesterase expressed in the central nervous system and peripheral areas, which modulates cyclic nucleotide signaling cascades. Inhibiting PDE1 enhances cAMP/cGMP levels, promoting neuronal plasticity and neuroprotection, making it a promising therapeutic strategy for neurological disorders. The pursuit of targeting this enzyme for treating neurological and neuropsychiatric disorders has faced obstacles due to the absence of potent, selective, and brain-penetrating inhibitors. This study aimed to identify potent PDE1 inhibitors by leveraging a diverse collection of bioactive molecules derived from Himalayan flora through computational screening methods. The four most promising hit molecules were chosen for further investigation and subjected to Molecular Dynamics (MD) simulations, binding free energy calculations, along with standard molecules. It was found that the hit molecules stigmast-7, corilagin and emblicanin-A had formed the most stable complexes, and also, the least binding free energy was observed for stigmast-7 among the hit molecules. Additionally, the pulling simulations indicated that stigmast-7 and corilagin were the most robust binders, and required the highest force to dissociate from the binding cavity completely. The umbrella sampling simulations also revealed the lowest binding free energy for corilagin and stigmast-7. The insights gained from this study provide a foundation for future research into PDE1-targeted therapies, highlighting the potential of Himalayan bioactive compounds in developing novel therapeutic interventions.

InertDB as a generative AI-expanded resource of biologically inactive small molecules from PubChem

The development of robust artificial intelligence (AI)-driven predictive models relies on high-quality, diverse chemical datasets. However, the scarcity of negative data and a publication bias toward positive results often hinder accurate biological activity prediction. To address this challenge, we introduce InertDB, a comprehensive database comprising 3,205 curated inactive compounds (CICs) identified through rigorous review of over 4.6 million compound records in PubChem. CIC selection prioritized bioassay diversity, determined using natural language processing (NLP)-based clustering metrics, while ensuring minimal biological activity across all evaluated bioassays. Notably, 97.2% of CICs adhere to the Rule of Five, a proportion significantly higher than that of overall PubChem dataset. To further expand the chemical space, InertDB also features 64,368 generated inactive compounds (GICs) produced using a deep generative AI model trained on the CIC dataset. Compared to conventional approaches such as random sampling or property-matched decoys, InertDB significantly improves predictive AI performance, particularly for phenotypic activity prediction by providing reliable inactive compound sets.Scientific contributionsInertDB addresses a critical gap in AI-driven drug discovery by providing a comprehensive repository of biologically inactive compounds, effectively resolving the scarcity of negative data that limits prediction accuracy and model reliability. By leveraging language model-based bioassay diversity metrics and generative AI, InertDB integrates rigorously curated inactive compounds with an expanded chemical space. InertDB serves as a valuable alternative to random sampling and decoy generation, offering improved training datasets and enhancing the accuracy of phenotypic pharmacological activity prediction.

Pharmacophore-based virtual screening and in silico investigations of small molecule library for discovery of human hepatic ketohexokinase inhibitors for the treatment of fructose metabolic disorders

Introduction

Excessive fructose consumption is a significant driver of metabolic disorders, including obesity, diabetes, non-alcoholic fatty liver disease and non-alcoholic steatohepatitis primarily by promoting insulin resistance and fat accumulation. Ketohexokinase C (KHK-C), a pivotal enzyme in fructose metabolism, catalyzes the phosphorylation of fructose to fructose-1-phosphate, initiating a cascade of downstream metabolic processes. In contrast to glucose metabolism, KHK-C lacks negative feedback regulation, allowing the continuous phosphorylation of fructose, which leads to heightened levels of glucose, glycogen, and triglycerides in the bloodstream and liver. While targeting KHK-C offers a promising therapeutic avenue, no drugs have yet been approved for clinical use. Pfizer's PF-06835919 has progressed to phase II trials, demonstrating a reduction in liver fat and improved insulin sensitivity, while Eli Lilly's LY-3522348 also shows significant potential. Nonetheless, there remains a critical need for the development of novel KHK-C inhibitors that offer improved pharmacokinetics, enhanced efficacy, and superior safety profiles.

Methods

In the present study, a comprehensive computational strategy was employed to screen 460,000 compounds from the National Cancer Institute library for potential KHK-C inhibitors. Initially, pharmacophore-based virtual screening was used to identify potential hits, followed by multi-level molecular docking, binding free energy estimation, pharmacokinetic analysis, and molecular dynamics (MD) simulations to further evaluate the compounds. This multi-step approach aimed to identify compounds with strong binding affinity, favorable pharmacokinetic profiles, and high potential for efficacy as KHK-C inhibitors.

Results

Ten compounds exhibited docking scores ranging from -7.79 to -9.10 kcal/mol, surpassing those of the compounds currently undergoing clinical trials, PF-06835919 (-7.768 kcal/mol) and LY-3522348 (-6.54 kcal/mol). Their calculated binding free energies ranged from -57.06 to -70.69 kcal/mol, further demonstrating their superiority over PF-06835919 (-56.71 kcal/mol) and LY-3522348 (-45.15 kcal/mol). ADMET profiling refined the selection to five compounds (1, 2, and 4-6), and molecular dynamics simulations identified compound 2 as the most stable and promising candidate compared to the clinical candidate PF-06835919.

Conclusion

These findings highlight compound 2 as a potent KHK-C inhibitor with predicted pharmacokinetics and toxicity profiles supporting its potential for treating fructose-driven metabolic disorders, warranting further validation.

Exploring global natural product databases for NLRP3 inhibition: Unveiling novel combinatorial therapeutic strategy for hidradenitis suppurativa

BACKGROUND

Hidradenitis suppurativa (HS) is a chronic inflammatory skin condition of the terminal hair follicle, which can present in sporadic, familial, or syndromic forms. The exact pathogenesis of HS remains elusive, posing a challenge for the development of effective treatments. Among the various immunological mechanisms, the NLRP3 inflammasome is thought to contribute to the pathogenesis of HS, releasing cytokines such as IL-1β and IL-18 which initiates and exacerbates inflammation. Consequently, targeting NLRP3 offers a potential strategy for mitigating inflammation in HS-affected skin.

METHODS

In this study we used the docking, molecular dynamics simulation and binding free energy approaches to identify the potent inhibitor of NLRP3 by screening the African phytocompounds and traditional Chinese medicine databases.

RESULTS

Our virtual drug screening analysis identified two lead compounds from each database, characterized by high docking scores such as SA-21676268 (-8.135 kcal/mol), SA-167673 (-10.251 kcal/mol), EA-45360194 (-10.376 kcal/mol), EA-46881231 (-10.011 kcal/mol), NEA-44258150 (-9.856 kcal/mol), NEA-135926572 (-7.662 kcal/mol), NA-163089376 (-9.237 kcal/mol), NA-440735 (-8.826 kcal/mol), TCM-392442 (-10.438 kcal/mol), and TCM-10043097 (-9.046 kcal/mol) which highlighted the strong binding affinity as compared to the control NP3-146 drug (-5.09 kcal/mol). Moreover, the values of dissociation constant further validated the strong binding affinity between the identified lead compounds and NLRP3. The dynamic stability and strong bonding energies of the lead compounds-NLRP3 complexes were confirmed by the molecular dynamic simulation and binding free energy calculation. The analysis of ADMET properties for all compounds indicated high intestinal absorption, water solubility, absence of hepatotoxicity, and skin sensitivity.

CONCLUSION

In conclusion, our molecular simulations and binding free energy calculations confirmed the strong affinity of these lead compounds for NLRP3 as compared to the control drug, highlighting their potential as part of a combinatorial therapeutic strategy for HS to effectively reduce disease-related inflammation.

High-throughput virtual screening and empirical validation of probable inhibitors of Plasmodium falciparum and vivax glutathione transferase using bromosulfophthalein as the benchmark ligand

Plasmodium falciparum Glutathione S-Transferase (PfGST) and Plasmodium vivax Glutathione S-Transferase (PvGST) play vital roles in detoxification and parasite survival, making them key targets for antimalarial drug development. These enzymes offer potential for creating therapies with improved efficacy, reduced resistance, and minimal toxicity. Natural compounds like flavonoids, known for their antiplasmodial properties, are promising scaffolds for new drug designs. This study computationally screened baicalin (BA) and 5,7,3'-Trihydroxy-6,4',5'-trimethoxyflavone (TTMF), synthesizable and affordable flavonoids from the MedChemExpress database, as potential inhibitors of PfGST and PvGST, outperforming BSP. Molecular dynamics simulations revealed that BA and TTMF stabilize enzyme interactions through hydrogen bonds and van der Waals forces, altering protein compactness and dynamics, suggesting non-competitive, allosteric inhibition. Empirical validation showed complete enzymatic inhibition by BA and TTMF with IC50 values of 1.69 and 1.71 μM, respectively, while minimizing human GST inhibition. Using 1-chloro-2,4-dinitrobenzene and reduced glutathione (GSH) as substrates, BA and TTMF demonstrated tight binding near the hydrophobic substrate-binding sites of PfGST and PvGST. Spectroscopic analysis using 8-anilino-1-naphthalenesulfonate (ANS) confirmed their ligandin effects and binding at the dimer interface. These findings highlight BA and TTMF as promising candidates for developing effective antimalarial therapies.

Synthesis, crystal structure, and in silico mol-ecular docking studies of 4-hy-droxy-3,5-di-meth-oxy-benzaldehyde (6-chloro-pyridazin-3-yl)hydrazone monohydrate

In the title compound, C13H13ClN4O3·H2O, the organic mol-ecule has an E configuration with regard to the C=N bond of the hydrazone bridge. The phenyl and pyridazine rings subtend a dihedral angle of 2.1 (1)° between their mean planes, while the hydrazone moiety makes dihedral angles of 1.6 (2) and 3.0 (2)°, respectively, with these aromatic rings. This renders the entire mol-ecule comparably flat. A C-H⋯N hydrogen bond generates an inversion dimer with a large R 2 2(14) ring motif. Within this ring, a further C-H⋯N hydrogen bond establishes a smaller R 2 2(8) ring. The mol-ecules of a dimer are thereby firmly linked by four hydrogen bonds. A bifurcated O-H⋯(O,O) hydrogen bond is formed between a water hydrogen atom and the hydroxyl and meth-oxy oxygen atoms of an adjacent mol-ecule, leading to the formation of an R 2 1(5) membered ring. C-H⋯π and face-to-face π-π stacking inter-actions are also present in the two-dimensional framework, which may be of relevance for the packing. In a complementary analysis, the compound was docked in silico to EGFR and HER2 receptors and the results imply that the compound targets EGFR preferentially over HER2.

Targeting AFP-RARβ complex formation: a potential strategy for treating AFP-positive hepatocellular carcinoma

Alpha-fetoprotein (AFP) is a glycoprotein primarily expressed during embryogenesis, with declining levels postnatally. Elevated AFP levels correlate with pathological conditions such as liver fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). Recent investigations underscore AFP's intracellular role in HCC progression, wherein it forms complexes with proteins like Phosphatase and tensin homolog (PTEN), Caspase 3 (CASP3), and Retinoic acid receptors and Retinoid X receptors (RAR/RXR). RAR and RXR regulate gene expression linked to cell death and tumorigenesis in normal physiology. AFP impedes RAR/RXR dimerization, nuclear translocation, and function, promoting gene expression favoring cancer progression in HCC that provoked us to target AFP as a drug candidate. Despite extensive studies, inhibitors targeting AFP to disrupt complex formation and activities remain scarce. In this study, employing protein-protein docking, amino acid residues involved in AFP-RARβ interaction were identified, guiding the definition of AFP's active site for potential inhibitor screening. Currently, kinase inhibitors play a significant role in cancer treatment and, the present study explores the potential of repurposing FDA-approved protein kinase inhibitors to target AFP. Molecular docking with kinase inhibitors revealed Lapatinib as a candidate drug of the AFP-RARβ complex. Molecular dynamics simulations and binding energy calculations, employing Mechanic/Poisson-Boltzmann Surface Area (MM-PBSA), confirmed Lapatinib's stability with AFP. The study suggests Lapatinib's potential in disrupting the AFP-RARβ complex, providing a promising avenue for treating molecularly stratified AFP-positive HCC or its early stages.

Pharmacophore modeling and molecular dynamics simulations to study the conformational stability of natural HER2 inhibitors in breast cancer therapy

HER2-positive breast cancer remains a significant clinical challenge, often exhibiting resistance to standard therapies. This study applies a comprehensive in silico approach to identify the natural compounds with potential inhibitory effects on HER2, focusing on pharmacophore modeling, virtual screening, molecular dynamics (MD) simulations, and binding affinity estimation. Initially, 24 known HER2 inhibitors from the BindingDB database were analyzed using Schrödinger's Phase module to generate a pharmacophore model, highlighting one hydrophobic (H) and three aromatic rings (RRR) features essential for HER2 binding. Screening against the Coconut Database, comprising 406,076 natural compounds, yielded 60,581 hits that matched the HRRR pharmacophore. These hits underwent a rigorous docking workflow with Glide (HTVS, SP, and XP modes), narrowing the candidates to 757 compounds with high binding affinity. Further refinement using Lipinski's rule of five produced a final set of 12 compounds exhibiting drug-like properties. 500-ns MD simulations evaluated these complexes' stability and dynamic behavior, while MM-GBSA calculations confirmed strong binding affinities dominated by van der Waals and electrostatic interactions. Compounds CNP0116178, CNP0356942, and CNP0136985 demonstrated superior binding profiles compared to the reference, marking them as lead candidates for HER2 inhibition. This study underscores the efficacy of computational methods in early-stage drug discovery and highlights promising candidates for further experimental validation and optimization. These findings offer a basis for developing targeted HER2 therapies and demonstrate the potential of natural compounds in advancing breast cancer treatment.

Thiophosphate bioisosteres of inositol hexakisphosphate enhance binding affinity and residence time on bacterial virulence factors

Inositol phosphates are essential for mammalian cell signalling with critical roles in cellular processes. The fully phosphorylated inositol phosphate, myo-inositol hexakisphosphate (IP6), modulates numerous eukaryotic proteins and bacterial virulence factors. It has been suggested that the high charge density of IP6 causes restructuring of virulence factors in mammalian cells, activating their enzymatic activity. IP6 is challenging to study due to its phytase instability and propensity to precipitate. Here we suggest that the thiophosphate bioisostere, myo-inositol hexakisthiophosphate (IT6), will mitigate these issues, as thiophosphate substitution has been found to be phytase resistant and improve solubility. Assessment of the chemical properties of IT6 has indeed validated these characteristics. In addition, we performed biophysical characterization of IT6 binding to the virulence factors Salmonella enterica serovar Typhimurium AvrA, Vibrio parahaemolyticus VopA, and Clostridioides difficile TcdB. Our data show that the higher charge density of IT6 increased its binding affinity and residence time on the proteins, which improved stabilization of the bound-state. IT6 is a valuable tool for structural biology research and the described biophysical characteristics of thiophosphate substitution are of value in medicinal chemistry.

In silico identification of novel ligands targeting stress-related human FKBP5 protein in mental disorders

FK506-binding protein 51 (FKBP51 or FKBP5) serves as a crucial stress modulator implicated in mental disorders, presenting a potential target for intervention. Inhibitors like SAFit2, rapamycin, and tacrolimus exhibit promising interactions with this protein. Despite these advances, challenges persist in diversifying FKBP5 ligands, prompting further exploration of interaction partners. Hence, this study aims to identify other potential ligands. Employing molecular docking, we generated complexes with various ligands (rapamycin, tacrolimus, SAFit2-Selective antagonist of FKBP51 by induced fit, ascomycin, pimecrolimus, rosavin, salidroside, curcumin, apigenin, uvaricin, ruscogenin, neoruscogenin, pumicalagin, castalagin, and grandinin). We identified the top 3 best ligands, of which ruscogenin and neoruscogenin had notable abilities to cross the blood-brain barrier and have high gastrointestinal absorption, like curcumin. Toxicity predictions show ruscogenin and neoruscogenin to be the least toxic based on oral toxicity classification (Class VI). Tyrosine (Tyr113) formed consistent interactions with all ligands in the complex, reinforcing their potential and involvement in stress modulation. Molecular dynamic (MD) simulation validated strong interactions between our three key ligands and FKBP5 protein and provided an understanding of the stability of the complex. The binding free energy (ΔG) of the best ligands (based on pharmacological properties) from MD simulation analysis is -31.78 kcal/mol for neoruscogenin, -30.41 kcal/mol for ruscogenin, and -27.6 kcal/mol for curcumin. These molecules, therefore, can serve as therapeutic molecules or biomarkers for research in stress-impacted mental disorders. While offering therapeutic implications for mental disorders by attenuating stress impact, it is crucial to emphasize that these ligands' transition to clinical applications necessitates extensive experimental research, including clinical trials, to unravel the intricate molecular and neural pathways involved in these interactions.

New Synthesis and Pharmacological Evaluation of Enantiomerically Pure (R)- and (S)-Methadone Metabolites as N-Methyl-d-aspartate Receptor Antagonists

N-Methyl-d-aspartate receptor (NMDAR) is gaining increasing interest as a pharmacological target for the development of fast-acting antidepressants. (S)-Methadone (esmethadone), has recently shown promising efficacy for the treatment of major depressive disorder. However, methods for its enantiopure preparation still rely on complex and expensive resolution procedures. In addition, enantiopure methadone metabolites have never been evaluated for their NMDAR activity. Here, we report the development of a novel chiral pool approach, based on cyclic sulfamidate ring-opening reaction, for the asymmetric synthesis of (R)- and (S)-methadone, and the application of this methodology to the stereodivergent synthesis of 20 enantiopure methadone metabolites. The compounds were evaluated for their NMDAR antagonism and for their affinity toward a series of relevant CNS receptors. Strikingly, N-demethylated (6R)-methadol metabolites retain the higher NMDAR uncompetitive antagonism of (R)-methadone, while presenting lower opioid receptor affinity compared to (S)-methadone. These compounds could represent novel candidates for drug development in CNS disorders.

Computer-aided drug design approach for alkaloids isolated from Stephania glandulifera Miers as potential acetylcholinesterase inhibitors

Considering the medicinal importance of alkaloids from Stephania glandulifera Miers, five major compounds (stepharine, stepharanine, stepholidine, palmatine and tetrahydropalmatine) from the plant were analyzed for their acetylcholinesterase activity using molecular docking, molecular dynamics simulations and in silico pharmacokinetics. As acetylcholinesterase has been significantly studied for their role in Alzheimer's disease, the enzyme from Torpedo californica (PDB ID: 1QTI) was taken as a receptor protein. AutoDock Vina was used to study the docking affinities during the initial screening of compounds where, stepharine showed promising binding energy (-10.3 kcal/mol) forming crucial interactions with active site residues (His 440, Tyr 121, and Trp 84). Molecular dynamics simulations were performed for 200 ns to analyze the stability of the docked complex. The study of trajectories obtained after simulation showed stepharine with a strong binding affinity and stability with AChE. Moreover, drug likeness and ADMET analysis conducted via Swiss ADME and pKCSM affirmed stepharine's favorable pharmacological properties. Overall, this research highlights stepharine as a potent acetylcholinesterase inhibitor which could be further developed as potential drug against Alzheimer's disease.

Analyzing Molecular Traits of H9N2 Avian Influenza Virus Isolated from a Same Poultry Farm in West Java Province, Indonesia, in 2017 and 2023

Background

Indonesia is one of the countries that is endemic to avian influenza virus subtype H9N2. This study aims to compare the molecular characteristics of avian influenza virus (AIV) subtype H9N2 from West Java.

Methods

Specific pathogen-free (SPF) embryonated chicken eggs were used to inoculate samples. RNA extraction and RT-qPCR confirmed the presence of H9 and N2 genes in the samples. RT-PCR was employed to amplify the H9N2-positive sample. Nucleotide sequences were obtained through Sanger sequencing and analyzed using MEGA 7. Homology comparison and phylogenetic tree analysis, utilizing the neighbor-joining tree method, assessed the recent isolate's similarity to reference isolates from GenBank. Molecular docking analysis was performed on the HA1 protein of the recent isolate and the A/Layer/Indonesia/WestJava-04/2017 isolate, comparing their interactions with the sialic acids Neu5Ac2-3Gal and Neu5Ac2-6Gal.

Results

RT-qPCR confirmed the isolate samples as AIV subtype H9N2. The recent virus exhibited 11 amino acid residue differences compared to the A/Layer/Indonesia/WestJava-04/2017 isolate. Phylogenetically, the recent virus remains within the h9.4.2.5 subclade. Notably, at antigenic site II, the recent isolate featured an amino acid N at position 183, unlike A/Layer/Indonesia/WestJava-04/2017. Molecular docking analysis revealed a preference of HA1 from the 2017 virus for Neu5Ac2-3Gal, while the 2023 virus displayed a tendency to predominantly bind with Neu5Ac2-6Gal.

Conclusion

In summary, the recent isolate displayed multiple mutations and a strong affinity for Neu5Ac2-6Gal, commonly found in mammals.

LeScore: a scoring function incorporating hydrogen bonding penalty for protein-ligand docking

CONTEXT

Molecular docking is vital for structure-based virtual screening and heavily depends on accurate and robust scoring functions. Scoring functions often inadequately account for the breakage of solvent hydrogen bonds, hindering the accuracy of predicting binding energy. Here, we introduce LeScore, a novel scoring function that specifically incorporates the hydrogen bonding penalty (HBP) in an aqueous environment, aiming to penalize unfavorable polar interactions when hydrogen bonds with water are broken but the energy loss is not fully compensated by newly formed protein-ligand interactions. LeScore was optimized for descriptor combinations and subsequently validated using a testing data set, achieving a Pearson correlation coefficient (rp) of 0.53 in the training set and 0.52 in the testing set. To evaluate its screening capability, a subset of the Directory of Useful Decoys: Enhanced (DUD-E) was used. And LeScore achieved an AUC of 0.71 for specific targets, outperforming models without HBP and enhancing the ranking and classification of active compounds. Overall, LeScore provides a robust tool for improving virtual screening, especially in cases where hydrogen bonding is crucial for ligand binding.

METHOD

LeScore is formulated as a linear combination of descriptors, including van der Waals interactions, hydrogen bond energy, ligand strain energy, and newly integrated HBP. The function was optimized using multiple linear regression (MLR) on the PDBbind 2019 dataset. Evaluation metrics, such as Pearson and Spearman correlation coefficients were utilized to assess the performance of 12 descriptor combinations. Additionally, the study employed datasets from the DUD-E to evaluate LeScore's ability to distinguish active ligands from decoys across multiple target proteins.

In vitro, in silico, and STD-NMR studies of flavonoids from Hypericum helianthemoides (Spach) Boiss. against Leishmania major pteridine reductase 1 (LmPTR1)

Apigenin (1) and 3I,8II-biapigenin (2), a dimer of apigenin, were isolated from the aerial parts of Hypericum helianthemoides (Spach) Boiss. (Hypericaceae family). This study aimed to evaluate the in vitro inhibitory effects of flavonoids 1 and 2 against Leishmania major pteridine reductase-1 (LmPTR1), an essential enzyme for the growth of Leishmania parasites and other trypanosomatid protozoa. The second objective was to understand the binding interactions and structural properties of LmPTR1 inhibition at the atomic level through extensive in silico analyses and Saturation-Transfer Difference (STD)-NMR studies. Anti-LmPTR1 results showed that the dimeric form (2) was active (IC50 of 34.65 μM), while the monomeric form (1) was inactive. Computational analyses yielded a grid score of -52.14 kcal/mol and a free energy binding score of -38.23 kcal/mol. A stable ligand-receptor complex at the LmPTR1 binding site was observed for 2. Moreover, several important binding residues in the catalytic triad (Y194 and K198) and the substrate loop (L226, S227, S229, V230, and M233) interacted with 2. The STD-NMR results corroborated the computational simulations, indicating that H-6I and H-6II of the conjugated ring system on the biapigenin structure showed the highest interaction with the LmPTR1 active site. MTT assay results for 2 against human normal fibroblast cells (BJ cells) exhibited no cytotoxicity at concentrations of 50 and 100 μM. Overall, 3I,8II-biapigenin (2) displayed promise as a candidate for in vivo studies and anti-leishmanial drug development. Further evaluation of the anti-leishmanial and anti-LmPTR1 activities of bioflavonoid 2, along with its analogues, is warranted.

Data Mining and in Silico Analysis of Ethiopian Traditional Medicine: Unveiling the Therapeutic Potential of Rumex abyssinicus Jacq

Multicomponent traditional medicine prescriptions are widely used in Ethiopia for disease treatment. However, inconsistencies across practitioners, cultures, and locations have hindered the development of reliable therapeutic medicines. Systematic analysis of traditional medicine data is crucial for identifying consistent and reliable medicinal materials. In this study, we compiled and analyzed a dataset of 505 prescriptions, encompassing 567 medicinal materials used for treating 106 diseases. Using association rule mining, we identified significant associations between diseases and medicinal materials. Notably, wound healing-the most frequently treated condition-was strongly associated with Rumex abyssinicus Jacq., showing a high support value. This association led to further in silico and network analysis of R. abyssinicus Jacq. compounds, revealing 756 therapeutic targets enriched in various KEGG pathways and biological processes. The Random-Walk with Restart (RWR) algorithm applied to the CODA PPI network identified these targets as linked to diseases such as cancer, inflammation, and metabolic, immune, respiratory, and neurological disorders. Many hub target genes from the PPI network were also directly associated with wound healing, supporting the traditional use of R. abyssinicus Jacq. for treating wounds. In conclusion, this study uncovers significant associations between diseases and medicinal materials in Ethiopian traditional medicine, emphasizing the therapeutic potential of R. abyssinicus Jacq. These findings provide a foundation for further research, including in vitro and in vivo studies, to explore and validate the efficacy of traditional and natural product-derived medicines.

Computational identification of novel natural inhibitors against triple mutant DNA gyrase A in fluoroquinolone-resistant Salmonella Typhimurium

The rising resistance to fluoroquinolones in Salmonella Typhimurium poses a significant global health challenge. This computational research addresses the pressing need for new therapeutic drugs by utilizing various computational tools to identify potential natural compounds that can inhibit the triple mutant DNA gyrase subunit A enzyme, which is crucial in fluoroquinolone resistance. Initially, the three-dimensional structure of the wild-type DNA gyrase A protein was modeled using homology modeling, and followed by in silico mutagenesis to create the clinically relevant triple mutant (SER83PHE, ASP87GLY, ALA119SER) DNA gyrase A protein structure. The structural stability and integrity of the modeled protein were ensured through rigorous validation. Subsequently, a high-throughput virtual screening of a curated library of natural compounds was conducted to identify potential inhibitors against wild-type and triple-mutant proteins. The selected potent lead molecules comprehensively evaluated their physicochemical properties, ADME/T properties, and binding affinities via ADME/T assessment and molecular docking studies. The safest and most promising ligands were chosen for dynamics studies to analyze their dynamic behavior and protein stability before and after the binding of ligands. Our results showed that the natural compounds from the ChemDiv database, CID: 0407-0108, N039-0003, 1080-0568, and 0099-0261 have binding energies ranging from -4.32 to -5.69 kcal/mol and exhibit excellent physio-chemical properties, affinities, and are stable in their dynamic environments over 100 ns for both wild-type and triple mutant DNA gyrase A complexes. These compounds provide a promising alternative treatment for fluoroquinolone-resistant Salmonella Typhimurium infections.

Immunomodulatory activity and molecular mechanisms of action of peptides derived from casein hydrolysate by alcalase and flavourzyme based on virtual screening

This study aimed to screen novel immunomodulatory peptides from casein hydrolysates (CH) using alcalase and flavorzyme by virtual screening, and their molecular mechanism were further studied. Based on the primary structural characteristics of immunomodulatory peptides, along with their hydrophobicity and isoelectric point, 3 novel immunomodulatory peptides (ALPMHIR, AMKPWIQPK, NPWDQVKR) were quickly found using virtual screening. These peptides exhibited strong interactions with TLR2/TLR4 through hydrogen bonding and hydrophobic interactions. Molecular docking verified that the key binding sites, such as Ile733, Ala732, and Phe774 in TLR2/TLR4 contributed to docking. Interestingly, the peptide AMKPWIQPK exhibited the strongest immunomodulatory activity and anti-inflammatory activity as 2-way immunomodulatory peptides. Based on western blot analysis and validation using specific inhibitors against MAPK/NF-κB signaling pathways, the results demonstrated that AMKPWIQPK could recognize the TLR2 and TLR4 receptor of the macrophages to upregulate the phospho-IκBα, phospho-p38, and phospho-p65, and further activated the MAPKs/NF-κB signaling pathways to enhance the immunomodulatory activity. These results confirmed that screening and optimizing immunomodulatory peptides by virtual screening and molecular docking were a novel and rapidly feasible method. The peptide AMKPWIQPK was expected to be used as natural-derived immunomodulatory active ingredients in nutritional health care and functional foods.

Chemical composition of essential oil from Lindera caesia Reinw. ex Fern.-Vill. and its antifungal, antibiofilm, and molecular docking studies

The chemical composition, antifungal, antibiofilm, and molecular docking studies of the essential oil obtained from Lindera caesia were investigated. A total of thirty-nine components (96.7%) were identified using gas chromatography (GC-FID) and gas chromatography-mass spectrometry (GC-MS). The major components included terpinen-4-ol (26.3%), neo-intermedeol (23.2%), eudesma-4,11-dien-3-one (10.4%), and o-cymene (5.3%). The antifungal activity was tested against Candida albicans and Streptococcus mutans using the broth microdilution assay, whereas the microbial biofilms were determined using a semi-quantitative static biofilm. The essential oil exhibited activity against C. albicans (MIC 125 µg/mL) and S. mutans (MIC 250 µg/mL), and increased the biofilm of C. albicans by 31.25% when treated with 500 µg/mL. The molecular docking study shows neo-intermedeol, eudesma-4,11-dien-3-one, α-selinene, and β-selinene as the good candidate to target Erg11 with a binding energy of -7.3 kcal/mol. These findings demonstrated that the essential oil may have potential in dental application for caries prevention.

Telomeric RNA quadruplexes as targets for cancer prevention: The therapeutic potential of agonodepsides

BACKGROUND

Cancer remains an awful challenge, despite years of targeting proteins to control its relentless growth and spread. Fungal metabolites, a treasure of natural chemicals, offer a glimmer of hope. Telomeres, the cellular "caps," are a focal point in cancer research. This study explores the potential of stabilizing Telomeric Repeats-containing RNA G-quadruplex (TERRA G4) structures within telomeres. This stabilization could block telomerase, the enzyme that repairs telomeres, and potentially trigger cancer cell death. Agonodepsides A and B, two promising fungal metabolites, were chosen to investigate this exciting possibility.

METHODS

Agonodepside A and B were initially screened for drug likeness employing SwissAdme. AutoDock Vina was used for molecular docking, and ligands and TERRA G4 were prepared using PyRx and MGL tool. Discovery Studio software was utilized for the visualization of interactions between ligands and TERRA G4. For validation of docking results MD simulation for control and complexes was carried out for 250 ns and trajectories were analyzed for different parameters. MMPBSA was used to calculate binding free energy for control and complexes. To find the stable and lower energy states of complexes in comparison to control principal component analysis (PCA) and free energy landscape (FEL) were conducted.

RESULTS

Absorption, distribution, metabolism, and excretion (ADME) of both agonodepsides followed Lipinski's rule of five with zero violation. Molecular docking revealed several key interactions including hydrogen bonds, van der Waals interactions, π-alkyl and π-anion. MD simulation revealed that Agonodepside A interact with TERRA G4 and stabilize it while Agonodepside B interactions were transient. The MMPBSA binding free energy calculation, PCA and free energy landscapes supported the docking and MD simulation results.

CONCLUSION

Lichenized fungi produce agonodepsides A and B, may fight cancer by targeting telomeres. Agonodepside A binds more strongly to telomeres than B, potentially blocking enzyme telomerase. Further studies are required to validate these findings and evaluate potential safety concerns.

Investigation and drug design for novel molecules from natural products as inhibitors for controlling multiple myeloma disease using in-silico tools

Multiple myeloma (MM) is a disease that causes plasma cell growth in the bone marrow and immune globulin buildup in blood and urine. Despite recent advances in MM therapy, many still die due to its high mortality rate. A study using computational simulations analyzed 100 natural ingredients from the SANC database to determine if they inhibited the IgH domain, a known cause of multiple myeloma. Natural component Diospyrin inhibited the IgH enzyme with the best binding energy of -10.3 kcal/mol and three carbon-hydrogen bonds, followed by Parviflorone F complex with a binding energy of -10.1 kcal/mol and two conventional-hydrogen bonds. As a result, the Molecular Dynamic simulation was used to test the stability of the two complexes. During the simulation, the Diospyrin molecule dissociated from the protein at roughly 67.5 ns, whereas the Parviflorone F molecule stayed attached to the protein throughout. The latter was the subject of the investigation. The analysis of the production run data revealed that the Parviflorone F molecule exhibits a variety of conformations within the binding pocket while keeping a relatively constant distance from the protein's center of mass. The analysis of the production run data revealed that the Parviflorone F molecule exhibited a variety of conformations within the binding pocket while keeping a relatively constant distance from the protein's center of mass. The root mean square deviation (RMSD) plots for both the protein and complex showed a stable and steady average value of 4.4 Å for the first 82 nanoseconds of manufacture. As a result, the average value increased to 8.3 Å. Furthermore, the components of the binding free energy, as computed by MM-GBSA, revealed that the mean binding energy of the Parviflorone F molecule was -23.88 kcal/mol. Finally, after analyzing all of the examination data, Parviflorone F was identified as a powerful inhibitor of the IgH domain and hence of the MM disease, which requires further in-vivo conformation.

Identification and evaluation of bioactive compounds from Azadirachta indica as potential inhibitors of DENV-2 capsid protein: An integrative study utilizing network pharmacology, molecular docking, molecular dynamics simulations, and machine learning techniques

Background

Dengue fever is a viral disease caused by the dengue flavivirus and transmitted through mosquito bites in humans. According to the World Health Organization, severe dengue causes approximately 40,000 deaths annually, and nearly 4 billion people are at risk of dengue infection. The urgent need for effective treatments against the dengue virus has led to extensive research on potential bioactive compounds.

Objective

In this study, we utilized a network pharmacology approach to identify the DENV-2 capsid protein as an appropriate target for intervention. Subsequently, we selected a library of 537 phytochemicals derived from Azadirachta indica (Family: Meliaceae), known for their anti-dengue properties, to explore potential inhibitors of this protein.

Methods

The compound library was subjected to molecular docking to the capsid protein to identify potent inhibitors with high binding affinity. We selected 81 hits based on a thorough analysis of their binding affinities, particularly those exhibiting higher binding energy than the established inhibitor ST-148. After evaluating their binding characteristics, we identified two top-scored compounds and subjected them to molecular dynamics simulations to assess their stability and binding properties. Additionally, we predicted ADMET properties using in silico methods.

Results

One of the inhibitors, [(5S,7R,8R,9R,10R,13R,17R)-17-[(2R)-2-hydroxy-5-oxo-2H-furan-4-yl]-4,4,8,10,13-pentamethyl-3-oxo-5,6,7,9,11,12,16,17-octahydrocyclopenta[a]phenanthren-7-yl] acetate (AI-59), showed the highest binding affinity at -10.4 kcal/mol. Another compound, epoxy-nimonol (AI-181), demonstrated the highest number of H-bonds with a binding affinity score of -9.5 kcal/mol. During molecular dynamics simulation studies, both compounds have exhibited noteworthy outcomes. Through molecular mechanics employing Generalized Born surface area (MM/GBSA) calculations, AI-59 and AI-181 displayed negative ΔG_bind scores of -74.99 and -83.91 kcal/mol, respectively.

Conclusion

The hit compounds identified in the present investigation hold the potential for developing drugs targeting dengue virus infections. Furthermore, the knowledge gathered from this study serves as a foundation for the structure- or ligand-based exploration of anti-dengue compounds.

Structure-Based Discovery of a Highly Selective, Oral Polo-Like Kinase 1 Inhibitor with Potent Antileukemic Activity

Polo-like kinase 1 (PLK1) plays pivotal roles in cell division and cancer pathogenesis, making it a highly coveted therapeutic target for anticancer strategies. This article reports a series of PLK1 inhibitors developed using a structure-based strategy, culminating in the discovery of compound B31, a novel isoform-specific PLK1 inhibitor with excellent kinome selectivity. In vitro, this compound exhibited superior anticancer potency across a broad spectrum of cell lines, particularly against K562, achieving a remarkable IC50 value of 0.08 nM. In a mouse model harboring subcutaneous K562 tumors, oral administration of B31 at dosages of 10 or 20 mg/kg twice weekly exhibited remarkable antileukemic activity. B31 had minimal impact on HEK293T cells and very weak inhibitory activity against the hERG channel. Furthermore, in the acute toxicity test, this compound demonstrated an extraordinary safety profile even at a dosage of 500 mg/kg, highlighting its potential as a novel antileukemic agent.

Fenugreek seeds as a natural source of L-arginine-encapsulated lipid nanoparticles against diabetes

Diabetes, affecting over 10.5% of the global population, leads to severe health complications and economic burdens, highlighting the urgent need for effective therapeutic approaches. Current treatments are often insufficient, prompting the exploration of novel therapeutic agents and delivery mechanisms. This study addresses this gap by investigating the roles of L-arginine (identified as a target drug candidate through network pharmacology) in diabetes management, while also evaluating lipid nanocarriers synthesized from fenugreek seed oil for improved drug delivery. Our docking analyses revealed L-arginine's strong interactions with diabetes-target genes (CYP1A2, CYP2C19, and NFKB), with multiple hydrogen bonds and binding energies ranging from - 7.2 to - 8.9 kcal/mol. Encapsulated L-arginine lipid nanoparticles were characterized using UV-Visible spectroscopy, showing absorbance peaks at 415 nm for simple nanoparticles and 521 nm for L-arginine-loaded nanoparticles. Scanning electron microscopy confirmed an average nanoparticle size of 100.2 nm, and zeta potential analysis indicated a neutral surface charge (- 9.37 mV). Antioxidative activity showed 84.44% inhibition with an IC50 value of 40.5 µg/mL The nanoparticles inhibited albumin denaturation by 81.10% and alpha-amylase by 89.30%, surpassing metformin (78.43% at 1000 µg/mL). Hemolysis percentage was minimal at 10.54%. These findings demonstrate the potential of L-arginine as an anti-diabetic agent and highlight the efficacy of lipid nanocarriers as innovative drug delivery systems, providing a foundation for advancing therapeutic interventions against diabetes.

Molecular docking, free energy calculations, ADMETox studies, DFT analysis, and dynamic simulations highlighting a chromene glycoside as a potential inhibitor of PknG in Mycobacterium tuberculosis

Introduction

Tuberculosis (TB), caused by the Mycobacterium tuberculosis (M.tb), remains a serious medical concern globally. Resistant M.tb strains are emerging, partly because M.tb can survive within alveolar macrophages, resulting in persistent infection. Protein kinase G (PknG) is a mycobacterial virulence factor that promotes the survival of M.tb in macrophages. Targeting PknG could offer an opportunity to suppress the resistant M.tb strains.

Methods

In the present study, multiple computational tools were adopted to screen a library of 460,000 molecules for potential inhibitors of PknG of M.tb.

Results and discussions

Seven Hits (1-7) were identified with binding affinities exceeding that of the reference compound (AX20017) towards the PknG catalytic domain. Next, the ADMETox studies were performed to identify the best hit with appropriate drug-like properties. The chromene glycoside (Hit 1) was identified as a potential PknG inhibitor with better pharmacokinetic and toxicity profiles rendering it a potential drug candidate. Furthermore, quantum computational analysis was conducted to assess the mechanical and electronic properties of Hit 1, providing guidance for further studies. Molecular dynamics simulations were also performed for Hit 1 against PknG, confirming the stability of its complex. In sum, the findings in the current study highlight Hit 1 as a lead with potential for development of drugs capable of treating resistant TB.

Overcoming beta-lactam resistance in Pseudomonas aeruginosa by targeting metallo-beta-lactamase VIM-1: a one-microsecond molecular dynamics simulation study

Pseudomonas aeruginosa (P. aeruginosa) is a Gram-negative opportunistic pathogen with a high resistance to beta-lactam antibiotics, mainly due to the production of metallo-beta-lactamase VIM-1 (MBL-VIM-1) enzyme. This study aimed to identify new inhibitors targeting MBL-VIM-1 to restore the efficacy of beta-lactam antibiotics. Extensive screening of natural compounds from the COCONUT database was performed to identify the structural analogs of the existing inhibitor of the MBL-VIM-1 protein. The virtual screening process selected four top-performing compounds (CNP0390322, CNP03905695, CNP0079056, and CNP0338283) that exhibited promising docking scores. These compounds were then subjected to re-docking and one-microsecond molecular dynamics (MD) simulations to assess their binding stability and interactions within the MBL-VIM-1 active site. Finally, post-MD simulation calculations were employed to estimate the interaction strengths and compare the efficacy of these compounds against the reference inhibitor. The findings highlighted that these four potent MBL-VIM-1 inhibitors show superior binding affinity and stability, suggesting their potential to combat antibiotic resistance in P. aeruginosa. The identified compounds offer a promising avenue for developing novel therapeutics to restore the efficacy of beta-lactam antibiotics against resistant bacterial strains. Therefore, further in vitro and in vivo studies are warranted to validate their potential.

Comprehensive Computational Screening and Analysis of Natural Compounds Reveals Promising Estrogen Receptor Alpha Inhibitors for Breast Cancer Therapy

Breast cancer remains a leading cause of death among women, with estrogen receptor alpha (ERα) overexpression playing a pivotal role in tumor growth and progression. This study aimed to identify novel ERα inhibitors from a library of 561 natural compounds using computational techniques, including virtual screening, molecular docking, and molecular dynamics simulations. Four promising candidates - Protopine, Sanguinarine, Pseudocoptisine, and Stylopine - were selected based on their high binding affinities and interactions with key ERα residues. Molecular dynamics simulations conducted over 500 nanoseconds revealed that Protopine and Sanguinarine exhibited more excellent stability with minimal fluctuations, suggesting strong and stable binding. In contrast, Pseudocoptisine and Stylopine showed higher flexibility, indicating less stable interactions. Binding free energy calculations further supported the potential of Protopine and Sanguinarine as ERα inhibitors, though their binding strength was slightly lower than that of the reference compound. These findings highlight Protopine and Sanguinarine as leading candidates for further investigation, and in vitro and in vivo studies are recommended to evaluate their therapeutic potential in breast cancer treatment.

Potential matrix metalloproteinase 2 and 9 inhibitors identified from Ehretia species for the treatment of chronic wounds - Computational drug discovery approaches

Matrix metalloproteinases (MMPs) serve as prognostic factors in several pathophysiological conditions, including chronic wounds. Therefore, they are considered important therapeutic targets in the intervention and treatment of these conditions. In this study, computational tools such as molecular docking and molecular dynamics simulations were used to gain insight into protein‒ligand interactions and determine the free binding energy between Ehretia species phytoconstituents and gelatinases (MMP2 and MMP9). A total of 74 phytoconstituents from Ehretia species were compiled from the literature, and 46 of these compounds were identified as potential inhibitors of at least one type of MMP. Molecular docking revealed that lithospermic acid B, rosmarinic acid, and danshensu had stronger binding affinities against the two enzymes than the reference ligands. Furthermore, (9S, 10E, 12Z, 15Z)-9-hydroxy-10,12,15-octadecatrienoic (∗-octadecatrienoic) had a higher binding energy for MMP2, whereas caffeic anhydride and caffeic acid established stronger binding energy with MMP9 than the reference ligand. These complexes also demonstrated relatively stable, favourable, and comparable conformational changes with those of unbound proteins at 500 ns. The free energy decomposition results further provide detailed insights into the contributions of active site residues and different types of interactions to the overall binding free energy. Finally, most of the hit phytoconstituents (rosmarinic acid, caffeic anhydride, caffeic acid, and danshensu) had good physicochemical, drug-likeness, and pharmacokinetic properties. Collectively, our findings showed that phytoconstituents from Ehretia species could be beneficial in the search for novel MMP inhibitors as therapeutic agents for the treatment of chronic wounds.