In silico methods and tools for drug discovery

Identifying therapeutic target for prostate cancer: exploring Diosmetin as a CYP inhibitor

Prostate cancer is a prevalent and highly heterogeneous malignancy that affects men globally. Despite the availability of various treatment targets, Cytochrome P450 (CYP) enzymes have gained significant attention due to their crucial role in metabolizing both endogenous and exogenous compounds. This study explores Diosmetin as a potential CYP antagonist for treating prostate cancer. To evaluate Diosmetin's potential as a CYP antagonist, we employed a comprehensive in silico approach. Molecular docking was conducted using the Glide software to assess the binding affinity of Diosmetin with CYP enzymes, specifically CYP17A1 and CYP19A1, which are associated with prostate cancer. The druglike properties of Diosmetin were evaluated, focusing on its pharmacokinetic attributes. Additionally, Diosmetin's ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) characteristics were analyzed to determine its suitability as a therapeutic agent. Molecular dynamics (MD) simulations were performed using Desmond to assess the stability and persistence of Diosmetin binding with the CYP enzymes over a 200 ns simulation period. Molecular docking studies revealed robust binding affinities between Diosmetin and CYP17A1 (- 11.261 kcal/mol) and CYP19A1 (- 11.145 kcal/mol). Diosmetin demonstrated favorable pharmacokinetic properties and advantageous ADMET characteristics, including high bioavailability, good dispersion, and favorable metabolism. MD simulations indicated persistent binding interactions between Diosmetin and the CYP enzymes throughout the 200 ns simulation, reinforcing the reliability of these interactions. Pharmacoinformatics investigations provide valuable insights into the potential of Diosmetin as a promising lead compound for the development of novel drug candidates against prostate cancer. The strong binding affinity and favorable pharmacokinetic and ADMET profiles suggest that Diosmetin could be an effective CYP antagonist and warrants further investigation as a potential therapeutic agent for prostate cancer.

Identification of novel inhibitors of cancer target telomerase using a dual structure-based pharmacophore approach to virtually screen libraries, molecular docking and validation by molecular dynamics simulations

In about 85% of cancer malignancies, replicative immortality caused by increased telomerase activity makes it an attractive target for developing anticancer therapeutics. However, the lack of approved small-molecule inhibitors rooted in the structural ambiguity of telomerase has impeded drug development for decades. In this study, we have exploited the FVYL pocket in the thumb domain, which plays a key role in the enzyme's processivity. Due to the unavailability of a co-crystalized structure of BIBR1532 with the catalytic hTERT thumb domain, we utilized the molecular dynamics method to identify the precise binding site of the inhibitor. Two pharmacophore models were generated and validated for the putative (Site-I) and newly identified (Site-II) binding pockets which were screened virtually through the ChemDiv anticancer library, Otava drug-like green collection to identify novel lead compounds, and Binding database to screen out thumb domain-specific telomerase inhibitors. The top hits obtained were filtered using drug-likeliness parameters followed by redocking using a three-level screening strategy into their binding site. The structural investigation, molecular docking studies, and confirmatory molecular dynamics revealed that the exact binding site of BIBR1532 is away from the reported FVYL pocket with characteristic interactions conserved. Subsequently, the lead compounds with the highest docking scores and significant interactions in the newly discovered extended FVYL pocket were validated using 100 ns MD simulations. Additionally, cross-validated binding free energy calculations were performed using MM-PB(GB)SA methods followed by PCA and FEL characterization. The identified top lead compounds can be validated in vitro and taken forward for anticancer drug development.

Rationalize the Functional Roles of Protein-Protein Interactions in Targeted Protein Degradation by Kinetic Monte Carlo Simulations

Targeted protein degradation is a promising therapeutic strategy to tackle disease-causing proteins that lack binding pockets for traditional small-molecule inhibitors. Its first step is to trigger the proximity between a ubiquitin ligase complex and a target protein through a heterobifunctional molecule, such as proteolysis targeting chimeras (PROTACs), leading to the formation of a ternary complex. The properties of protein-protein interactions play an important regulatory role during this process, which can be reflected by binding cooperativity. Unfortunately, although computer-aided drug design has become a cornerstone of modern drug development, the endeavor to model-targeted protein degradation is still in its infancy. The development of computational tools to understand the impacts of protein-protein interactions on targeted protein degradation, therefore, is highly demanded. To reach this goal, we constructed a nonredundant structural benchmark of the most updated ternary complexes and applied a kinetic Monte Carlo method to simulate the association between ligases and PROTAC-targeted proteins in the benchmark. Our results show that proteins in most complexes with positive cooperativity tend to associate into native-like configurations more often. In contrast, proteins very likely failed to associate into native-like configurations in complexes with negative cooperativity. Moreover, we compared protein-protein association through different interfaces generated from molecular docking. The native-like binding interface shows a higher association probability than all the other alternative interfaces only in the complex with positive cooperativity. These observations support the idea that the formation of ternary complexes is closely regulated by the binary interactions between proteins. Finally, we applied our method to cyclin-dependent kinases 4 and 6 (CDK4/6). We found that their interactions with the ligase are not as similar as their structures. Altogether, our study paves the way for understanding the role of protein-protein interactions in the PROTAC-induced ternary complex formation. It can potentially help in searching for degraders that selectively target specific proteins.

Natural anti-adhesive components against pathogenic bacterial adhesion and infection in gastrointestinal tract: case studies of Helicobacter pylori, Salmonella enterica, Clostridium difficile, and diarrheagenic Escherichia coli

Antimicrobial resistance (AMR) poses a global public health concern. Recognizing the critical role of bacterial adhesion in pathogenesis of infection, anti-adhesive therapy emerges as a promising approach to impede initial bacterial attachment, thus preventing pathogenic colonization and infection. Natural anti-adhesive agents derived from food sources are generally safe and have the potential to inhibit the emergence of resistant bacteria. This comprehensive review explored diverse natural dietary components exhibiting anti-adhesive activities against several model enteric pathogens, including Helicobacter pylori, Salmonella enterica, Clostridium difficile, and three key diarrheagenic Escherichia coli (i.e., enterotoxigenic E. coli, enteropathogenic E. coli, and enterohemorrhagic E. coli). Investigating various anti-adhesive products will advance our understanding of current research of the field and inspire further development of these agents as potential nutraceuticals or adjuvants to improve the efficacy of conventional antibiotics.

Identification of Novel Drug Molecules Against NS3-Like Helicase Enzyme of Alongshan Virus

Alongshan virus (ALSV) is a novel tick-borne virus associated with human diseases. The ALSV is a segmented flavivirus from the family Flaviviridae. It is currently considered as tick-borne arbovirus. There is a high incidence of fever and headache among patients with ALSV infection, and some patients also present with fatigue, coma, depression, nausea, myalgia/arthralgia, and skin rashes. Neither a licensed vaccine nor a drug is currently available to treat ALSV. The development of new, practical, and innovative therapeutic approaches is needed to overcome the emergence of the pathogen. Research on drugs remains a complex, time-consuming, and expensive. The field of drug development has undergone a revolution due to the use of computational approaches, which provide several benefits that speed up and improve the process of developing novel drugs. The goal of this study is to identify novel drug-like molecules against NS3-like helicase enzyme of Alongshan virus. Using molecular docking, the binding potential of the top three ligands to the specified target was determined. Molecular dynamic simulations were used to identify the stabilities of the best-docked conformations followed by energy calculations and ADMET analysis. Three potential and promising compounds were identified by performing structure-based virtual screening of non-structural protein 3 (NS3) like helicase of Alongshan virus. The best-docked complexes identified through virtual screening were BDC-23169381, BDB-26412846, BDB-2641954. All these compounds had good pharmacokinetics characteristics and were identified as drug like.

Physiologically-based pharmacokinetic model of in vitro porcine ear skin permeation for drug delivery research

In silico techniques, such as physiologically based pharmacokinetic modeling (PBKP), are recently gaining importance. Computational methods in drug discovery and development and the generic drugs industry enhance research effectiveness by saving time and money and avoiding ethical issues. One key advantage is the ability to conduct toxicology studies without risking harm to living beings. This study aimed to repurpose the multi-phase multi-layer mechanistic dermal absorption (MPML MechDermA) PBPK model for simulation permeation through porcine ear skin under in vitro conditions. The work was divided into four steps: (1) the development of a pig ear skin model based on a previously collected dataset; (2) testing the model's ability to discriminate permeation between pig ear, human abdomen, and human back skin; (3) development of a caffeine permeation model; and (4) testing the caffeine model's performance against in vitro generated data sourced from the scientific literature. Data from 31 manuscripts were used for the development of the pig skin model. Based on these data, values specific to pig skin were found for 22 parameters of the MPML MechDermA model. The model was able to discriminate permeation between pig and human skin. A caffeine model was developed and used to simulate seven experiments identified in the literature. The model's performance was assessed by comparing simulated to observed results. Based on a visual check, all simulations were considered acceptable, whereas three out of seven experiments met the twofold difference criterion. The variability of the experimental data was considered the biggest challenge for reliable model assessment.

Targeting bacterial growth in biofilm conditions: rational design of novel inhibitors to mitigate clinical and food contamination using QSAR

Antimicrobial resistance (AMR) is a pressing global issue exacerbated by the abuse of antibiotics and the formation of bacterial biofilms, which cause up to 80% of human bacterial infections. This study presents a computational strategy to address AMR by developing three novel quantitative structure-activity relationship (QSAR) models based on molecular topology to identify potential anti-biofilm and antibacterial agents. The models aim to determine the chemo-topological pattern of Gram (+) antibacterial, Gram (-) antibacterial, and biofilm formation inhibition activity. The models were applied to the virtual screening of a commercial chemical database, resulting in the selection of 58 compounds. Subsequent in vitro assays showed that three of these compounds exhibited the most promising antibacterial activity, with potential applications in enhancing food and medical device safety.

Neuroprotective Properties of Coriander-Derived Compounds on Neuronal Cell Damage under Oxidative Stress-Induced SH-SY5Y Neuroblastoma and in Silico ADMET Analysis

An imbalance between reactive oxygen species (ROS) production and antioxidant defense driven by oxidative stress and inflammation is a critical factor in the progression of neurodegenerative diseases such as Alzheimer's and Parkinson's. Coriander (Coriandrum sativum L.), a culinary plant in the Apiaceae family, displays various biological activities, including anticancer, antimicrobial, and antioxidant effects. Herein, neuroprotective properties of three major bioactive compounds derived from coriander (i.e., linalool, linalyl acetate, and geranyl acetate) were investigated on hydrogen peroxide-induced SH-SY5Y neuroblastoma cell death by examining cell viability, ROS production, mitochondrial membrane potential, and apoptotic profiles. Moreover, underlying mechanisms of the compounds were determined by measuring intracellular sirtuin 1 (SIRT1) enzyme activity incorporated with molecular docking. The results showed that linalool, linalyl acetate, and geranyl acetate elicited their neuroprotection against oxidative stress via protecting cell death, reducing ROS production, preventing cell apoptosis, and modulating SIRT1 longevity. Additionally, in silico pharmacokinetic predictions indicated that these three compounds are drug-like agents with a high probability of absorption and distribution, as well as minimal potential toxicities. These findings highlighted the potential neuroprotective linalool, linalyl acetate, and geranyl acetate for developing alternative natural compound-based neurodegenerative therapeutics and prevention.

In silico exploration of phytochemicals as inhibitors for acute myeloid leukemia by targeting LIN28A gene: A cheminformatics study

BACKGROUND

Recent discoveries have illustrated that Lin28A is an oncogene in various cancers, particularly acute myeloid leukemia (AML). The upregulation of Lin28A can actively contribute to tumorigenesis and migration processes in multiple organs. Hence, the inhibition of Lin28A can be achieved by applying phytochemical herbals and targeting Lin28A protein using a computer-aided drug design (CAAD) approach.

METHODS

In this study, we comprehensively applied several bioinformatics tools, including gene ontologies, gene enrichment analysis, and protein-protein interactions (PPI), to determine the biological pathways, functional gene ontology, and biological pathway. Furthermore, we investigated a list of phytochemical herbs as a candidate drug by applying a computation technique involving molecular docking, density functional theory (DFT), molecular dynamics simulation (MDs), and pharmacokinetic and physiochemical properties by applying the SwissADME, pkCSM, and Molsoft LLC web-servers.

RESULTS

The Lin28A gene is related to two significant enrichment pathways, including proteoglycans in cancer and the pluripotency of stem cells through interactions with different genes such as MAPK12, MYC, MTOR, and PIK3CA. Interestingly, limonin, 18β Glycyrrhetic Acid, and baicalein have the highest binding energy scores of -8.4, -8.2, and -7.3 kcal/mol, respectively. The DFT study revealed that baicalein has a higher reactivity than limonin and 18β-Glycyrrhetic due to a small energy gap between LUMO and HUMO. Molecular dynamics simulation exhibited that baicalein complex with Lin28A protein is more stable than other complexes during simulation time due to low fluctuation with simulation periods as compared with other complexes, which indicated that baicalein was more fitting to docking and combining in the protein cave because of the largest number of H-bonds available for the docking simulation process. Furthermore, the drug-likeness and ADMET profiles revealed the activity of limonin, baicalein, and 18β-glycyrrhizic Acid, which possess significant inhibiting Lin28A proteins.

CONCLUSION

This study elucidated that baicalein, 18β-glycyrrhizic, and limonin may be applied as potential candidates for targeting Lin28A as an active oncogene for acute myeloid leukemia.

Protein-Ligand Interaction Energies from Quantum-Chemical Fragmentation Methods: Upgrading the MFCC-Scheme with Many-Body Contributions

Quantum-chemical fragmentation methods offer an attractive approach for the accurate calculation of protein-ligand interaction energies. While the molecular fractionation with conjugate caps (MFCC) scheme offers a rather straightforward approach for this purpose, its accuracy is often not sufficient. Here, we upgrade the MFCC scheme for the calculation of protein-ligand interactions by including many-body contributions. The resulting fragmentation scheme is an extension of our previously developed MFCC-MBE(2) scheme [J. Comput. Chem. 2023, 44, 1634-1644]. For a diverse test set of protein-ligand complexes, we demonstrate that by upgrading the MFCC scheme with many-body contributions, the error in protein-ligand interaction energies can be reduced significantly, and one generally achieves errors below 20 kJ/mol. Our scheme allows for systematically reducing these errors by including higher-order many-body contributions. As it combines the use of single amino acid fragments with high accuracy, our scheme provides an ideal starting point for the parametrization of accurate machine learning potentials for proteins and protein-ligand interactions.

QSAR Modeling and Biological Testing of Some 15-LOX Inhibitors in a Series of Homo- and Heterocyclic Compounds

This paper examines the quantitative structure-inhibitory activity relationship of 15-lipoxygenase (15-LOX) in sets of 100 homo- and heterocyclic compounds using GUSAR 2019 software. Statistically significant valid models were built to predict the IC50 parameter. A combination of MNA and QNA descriptors with three whole molecular descriptors (topological length, topological volume and lipophilicity) was used to develop 18 statistically significant, valid consensus QSAR models. These compounds showed varying degrees of inhibition of the catalytic activity of 15-LOX: the range of variation in the pIC50 value was 3.873. The satisfactory coincidence between the theoretically calculated and experimentally determined pIC50 values for compounds TS1, TS2 and 1-8 suggests the potential use of models M1-M18 for the virtual screening of virtual libraries and databases to find new potentially efficient inhibitors of 15-LOX.

SLNP-based CDK4- targeted nanotherapy against glioblastoma

Introduction

Glioblastoma is a grade IV solid brain tumor and has a 15-month survival rate even after treatment. Glioblastoma development is heavily influenced by retinoblastoma protein (pRB) pathway changes. The blood-brain barrier, drug resistance, and severe toxicity of Temozolamide are key obstacles in treating glioblastoma. Innovative treatments targeting the pRB pathway with efficient delivery vehicles are required to treat glioblastoma.

Methods

For this purpose, a library of 691 plant extracts previously tested in vitro for anti-cancerous, anti inflammatory, and anti-proliferative characteristics was created after thorough literature investigations. Compounds were docked against pRB pathway protein ligands using molecular operating environment and chimera. Their nuclear structure and drug-like properties were predicted through Lipinski rule and density functional theory analysis. Physio-chemical characterizations of naked and drug-encapsulated SLNPs assessed size, stability, entrapment efficiency, and drug release rate. Anti-cancer potential of drug and drug- loaded SLNPs was evaluated using U87, U251, and HEK cell lines. Formulations were tested for cancer cell metastatic potential using cell migration assays.

Results

Silymarin (Sil) was identified as the most potent compound against CDK4, which was then encapsulated in stearic acid solid lipid nanoparticles (SLNP-Sil). Sil showed decreased cell viability 72 h after treatment against both U87 and U251 cell lines but had negligible cytotoxic effect on HEK-293. IC50 value of Sil was 155.14 µM for U87 and 195.93 µM for U251. Sil and SLNP-Sil effectively inhibited U87 and U251 cell migration 24 h after treatment.

Discussion

Our results indicated that Sil and SLNP-Sil are promising therapeutic approaches against glioblastoma and merit in vivo experimental verification using orthotropic xenograft mouse models against glioblastoma.

Identification, screening, and comprehensive evaluation of novel thrombin inhibitory peptides from the hirudo produced using pepsin

Purpose

The inhibition of thrombin has proven to be an efficacious therapeutic approach for managing cardiovascular disease (CVD), with widespread implementation in clinical settings. Oral ingestion of peptides and protein drugs is influenced by gastrointestinal digestive enzymes. We aimed to evaluate the thrombin inhibitory properties of hirudo hydrolysates (HHS) produced by pepsin and propose a comprehensive approach to screen and evaluate thrombin inhibitors.

Methods

We evaluated the in vitro inhibitory properties of the hirudo extract, both before and after hydrolysis with pepsin, toward thrombin. We screened for the most potent thrombin inhibitory peptide (TIP) using nano liquid chromatography-tandem mass spectrometry (Nano LC-MS/MS) coupled with in silico analysis. Next, we employed the thrombin inhibition activity IC50 to investigate the interaction between TIP and thrombin, and conducted in vitro evaluations of its anticoagulant effects (APTT, TT, PT), as well as its ability to inhibit platelet aggregation. Furthermore, we utilized UV-Vis spectroscopy to explore structural changes in thrombin upon binding with TIP and employed molecular dynamics simulations to delve deeper into the potential atomic-level interaction modes between thrombin and TIP.

Results

The retention rate of thrombin inhibition for HHS was found to be between 60% and 75%. A total of 90 peptides from the HHS were identified using LC-MS/MS combined with de novo sequencing. Asn-Asp-Leu-Trp-Asp-Gln-Gly-Leu-Val-Ser-Gln-Asp-Leu (NDLWDQGLVSQDL, P1) was identified as the most potent thrombin inhibitory peptide after in silico screening (molecular docking and ADMET). Then, the in vitro study revealed that P1 had a high inhibitory effect on thrombin (IC50: 2,425.5 ± 109.7 μM). P1 exhibited a dose-dependent prolongation of the thrombin time (TT) and a reduction in platelet aggregation rate. Both UV-Vis spectroscopy and molecular dynamics simulations demonstrated that P1 binds effectively to thrombin.

Conclusion

Overall, the results suggested that HHS provides new insights for searching and evaluating potential antithrombotic compounds. The obtained P1 can be structurally optimized for in-depth evaluation in animal and cellular experiments.

Insilico discovery of novel Phosphodiesterase 4 (PDE4) inhibitors for the treatment of psoriasis: Insights from computer aided drug design approaches

Psoriasis is chronic immune-mediated inflammatory disorder characterized by various comorbidities, erythematous plaques with silvery scale which can lead to psoriatic arthritis. The phosphodiesterase 4 (PDE4) protein is a potential drug target to control Psoriasis. In the current study, pharmacophore-based virtual screening of Diversity library of ChemDiv database was first performed, and then the screened hits were docked to the active site of PDE4 to choose the best binding modes. Forty-six hits generated during the virtual screening were prepared and docked to the PDE4 receptor by SP docking module of glide. The binding affinities of the selected hits were calculated by molecular docking and based on the affinities, ten hits were selected for the bioactivity scores prediction and ADMET analysis. Based on the ADMET profiling, four hits D356-2630, C700-2058, G842-0420 and F403-0203 were processed to MD simulations for stability analysis. The outcomes showed that these compounds showed strong binding with proteins with better binding free energies. Based on the results of our study, we proposed that these hits can function as lead in the biological assays and in vitro studies are required to develop the novel drug candidates.

Alkaloids Isolated from Vepris glandulosa with Antidiabetic Properties: An In Vitro and In Silico Analysis

Diabetes is a major global health issue and as current treatments fail, the search for new antidiabetic drugs is crucial. This investigation, focusing on identifying potential antidiabetic compounds from the endangered plant species Vepris glandulosa, led to the isolation of two known alkaloids, choisyine acetate (1) and choisyine (2). The study established the in vitro inhibitory activities and in silico molecular interaction of the two alkaloids with α-amylase based on IC50 values, Linewaever-Burk/Dixon plot kinetic analyses and Molecular docking, respectively. The α-amylase inhibition assay revealed noncompetitive inhibition for both compounds with IC50 and Ki values of 4.74±0.17 and 4.75 mM for compound 1, and 11.29±0.44 and 12.37 mM for compound 2, respectively. In comparison, the standard drug acarbose displayed a competitive mode of inhibition, with IC50 and Ki values of 11.99±0.02 and 12.68 mM, respectively. The binding affinities with α-amylase were -6.42 and -6.07 kcal/mol for compounds 1 and 2, respectively relative to acarbose -8.03 Kcal/mol. Moreover, these two compounds' predicted physicochemical and ADMET properties justified their potential as lead compounds for drug discovery. These compounds demonstrated remarkable inhibition potential comparable to the standard drug, highlighting their potential as viable alternatives in managing diabetes.

A comprehensive survey of drug-target interaction analysis in allopathy and siddha medicine

Effective drug delivery is the cornerstone of modern healthcare, ensuring therapeutic compounds reach their intended targets efficiently. This paper explores the potential of personalized and holistic healthcare, driven by the synergy between traditional and allopathic medicine systems, with a specific focus on the vast reservoir of medicinal compounds found in plants rooted in the historical legacy of traditional medicine. Motivated by the desire to unlock the therapeutic potential of medicinal plants and bridge the gap between traditional and allopathic medicine, this survey delves into in-silico computational approaches for studying Drug-Target Interactions (DTI) within the contexts of allopathy and siddha medicine. The contributions of this survey are multifaceted: it offers a comprehensive overview of in-silico methods for DTI analysis in both systems, identifies common challenges in DTI studies, provides insights into future directions to advance DTI analysis, and includes a comparative analysis of DTI in allopathy and siddha medicine. The findings of this survey highlight the pivotal role of in-silico computational approaches in advancing drug research and development in both allopathy and siddha medicine, emphasizing the importance of integrating these methods to drive the future of personalized healthcare.

Platycodin D ameliorates polycystic ovary syndrome-induced ovarian damage by upregulating CD44 to attenuate ferroptosis

Recently, the potential association between polycystic ovary syndrome (PCOS) development and progression and ferroptosis has garnered attention. Increasing evidence suggests that targeting ferroptosis may be an effective strategy for treating PCOS. First, we observed that the expression of the ferroptosis regulatory molecules SLC7A11, GPX4, and FTH1 was decreased in the granulosa cells (GCs) of patients with PCOS and ovarian tissues of rats with PCOS; in contrast, TFR1 expression was increased. This suggests that GC ferroptosis is involved in PCOS pathogenesis. Furthermore, bioinformatics analysis of GC datasets from patients with PCOS and PCOS clinical samples and animal model analysis revealed CD44 as a key molecule regulating ferroptosis in PCOS, which was down-regulated in GCs of PCOS patients and rats. Subsequently, molecular docking was performed to screen existing natural compounds for inhibiting ferroptosis. Dynamic simulation and cellular thermal shift assay identified platycodin D as a natural plant extract for inhibiting ferroptosis by targeting CD44 in GCs. Subsequently, a series of functional experiments revealed that platycodin D ameliorated ovarian damage in rats with PCOS. This was primarily owing to the protective effects achieved by promoting glutathione production, attenuating lipid accumulation and lipid peroxidation in GCs, inhibiting iron overload, and scavenging reactive oxygen species. In addition, western blotting and immunofluorescence staining revealed that platycodin D upregulated the expression of CD44 and SLC7A11 in GCs. Furthermore, by knocking down CD44 and SLC7A11 in vivo and in vitro, respectively, the ameliorative effect of platycodin D on ferroptosis in the GCs of rats with PCOS was reversed. Collectively, these findings suggest that platycodin D attenuates ferroptosis in GCs by activating CD44/SLC7A11 axis, thereby upregulating system Xc-. In conclusion, platycodin D can attenuate ferroptosis in GCs by activating CD44, potentially ameliorating ovarian damage in PCOS.

Optimizing Antitumor Effect of Triple-Negative Breast Cancer via Rosmarinic Acid-β-Cyclodextrin Inclusion Complex

Background: Rosmarinic acid (ROS) has gained notable attention for its anticancer potential; however, its limited aqueous solubility hinders its effective delivery and application in pharmaceutical formulations. Methods: To overcome this limitation, an inclusion complex of ROS with β-cyclodextrin (β-CD) was prepared using the recrystallization method. The resultant ROS-β-CD complex was comprehensively characterized by powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM). Results: The ROS-β-CD complex showed a significant improvement in the solubility and dissolution profile of ROS, underscoring its potential for enhanced bioavailability and therapeutic efficacy in pharmaceutical applications. In vitro assays were performed to assess the effects on cell viability, proliferation, apoptotic pathways, and 3D spheroid tumor models. Conclusions: The results demonstrated that ROS-β-CD exhibited superior anticancer properties compared to free ROS, effectively reducing the viability and proliferation of the MD-MBA-231 cell line and inducing apoptosis. This research signifies a substantial advancement in developing therapeutic strategies for TNBC, leveraging the distinct properties of the ROS-β-CD inclusion complex.

The new paradigm in animal testing - "3Rs alternatives"

Regulatory studies have revolutionised over time. Today, the focus has shifted from animal toxicity testing to non-animal for regulatory safety testing. This move is in line with the international 3Rs (Replacement, Reduction, and Refinement) principle and has also changed the regulator's perspective. The 3R principle has stimulated changes in policy, regulations, and new approaches to safety assessment in drug development in many countries. The 3Rs approach has led to the discovery and application of new technologies and more human-relevant in vitro approaches that minimise the use of animals including non-human primates, in research and improve animal welfare. In 2016, the European Medicines Agency published the Guidelines on the principles of regulatory acceptance of 3Rs testing approaches, followed by a conceptual paper in 2023 to align with current 3R standards. Additionally, the United States Food and Drug Administration passed new legislation in 2023 that no longer requires all new human drugs to be tested on animals, which will change the current testing paradigm. This review paper provides the adoption of the 3Rs and the current regulatory perspective regarding their implementation.

Extension of impurity profiling on eltrombopag olamine to in-silico predictions: An effort to exploit correlated forced degradation products and known drug-related substances in drug discovery

The recent pandemic has highlighted the impact of diseases on global health and the economy. The rapid discovery of new hit molecules remains a tough challenge. Pharmaceutical impurity profiling can be linked to drug discovery through the identification of new hits from compounds identified during the analytical profiling. The present study demonstrates this linkage through the extension of the impurity (forced degradation) profiling of eltrombopag (ELT) olamine, a thrombopoietin (TPO) receptor agonist. The drug was exposed to standard degradation and the degradation products were primarily resolved and identified by UPLC-ESI-MS. This led to the identification of five forced degradation products (FDP). Thirty-three other known related substances (RS) of ELT, identified in the literature, were also considered. Molecular similarity checks were performed using Tanimoto/Jaccard's similarity searches. A set of structurally and topologically similar molecules, including ELT and 15 RS, was established and subjected to in-silico toxicity-, absorption-, distribution-, metabolism-, and elimination (ADME) predictions. The RS, predicted with similar or lower toxicity than ELT and a comparable ADME profile, were subjected to molecular docking to trace changes in TPO receptor affinity. The results indicated that five RS had a high Jaccard's similarity with ELT and higher or comparable docking scores. These compounds, along with few other impurities were predicted to have lower toxicity, better or comparable absorption, distribution, metabolism, and also a better excretion profile than ELT. This justifies their entry as potential novel TPO receptor agonists in drug discovery.

Medicinal plants as a potential resource for the discovery of novel structures towards cancer drug resistance treatment

Despite extensive research in chemotherapy, global cancer concerns persist, exacerbated by the challenge of drug resistance, which imposes economic and medical burdens. Natural compounds, particularly secondary metabolites from medicinal plants, present promising avenues for overcoming cancer drug resistance due to their diverse structures and essential pharmacological effects. This review provides a comprehensive exploration of cancer cell resistance mechanisms and target actions for reversing resistance and highlights the in vitro and in vivo efficacy of noteworthy alkaloids, flavonoids, and other compounds, emphasizing their potential as therapeutic agents. The molecular properties supporting ligand interactions are thoroughly examined, providing a robust theoretical foundation. The review concludes by discussing methods including quantitative structure-activity relationships and molecular docking, offering insights into screening potential candidates. Current trends in clinical treatment, contributing to a holistic understanding of the multifaceted approaches to address cancer drug resistance are also outlined.

Biological network comparison identifies a novel synergistic mechanism of Ginseng Radix-Astragali Radix herb pair in cancer-related fatigue

ETHNOPHARMACOLOGICAL RELEVANCE

Ginseng Radix and Astragali Radix are commonly combined to tonify Qi and alleviate fatigue. Previous studies have employed biological networks to investigate the mechanisms of herb pairs in treating different diseases. However, these studies have only elucidated a single network for each herb pair, without emphasizing the superiority of the herb combination over individual herbs.

AIM OF THE STUDY

This study proposes an approach of comparing biological networks to highlight the synergistic effect of the pair in treating cancer-related fatigue (CRF).

METHODS

The compounds and targets of Ginseng Radix, Astragali Radix, and CRF diseases were collected and predicted using different databases. Subsequently, the overlapping targets between herbs and disease were imported into the STRING and DAVID tools to build protein-protein interaction (PPI) networks and analyze enriched KEGG pathways. The biological networks of Ginseng Radix and Astragali Radix were compared separately or together using the DyNet application. Molecular docking was used to verify the predicted results. Further, in vitro experiments were conducted to validate the synergistic pathways identified in in silico studies.

RESULTS

In the PPI network comparison, the combination created 89 new interactions and an increased average degree (11.260) when compared to single herbs (10.296 and 9.394). The new interactions concentrated on HRAS, STAT3, JUN, and IL6. The topological analysis identified 20 core targets of the combination, including three Ginseng Radix-specific targets, three Astragali Radix-specific targets, and 14 shared targets. In KEGG enrichment analysis, the combination regulated additional signaling pathways (152) more than Ginseng Radix (146) and Astragali Radix (134) alone. The targets of the herb pair synergistically regulated cancer pathways, specifically hypoxia-inducible factor 1 (HIF-1) signaling pathway. In vitro experiments including enzyme-linked immunosorbent assay and Western blot demonstrated that two herbs combination could up-regulate HIF-1α signaling pathway at different combined concentrations compared to either single herb alone.

CONCLUSION

The herb pair increased protein interactions and adjusted metabolic pathways more than single herbs. This study provides insights into the combination of Ginseng Radix and Astragali Radix in clinical practice.

Discovery of novel CDK4/6 inhibitors from fungal secondary metabolites

The development of targeted therapies for breast cancer, particularly those focusing on cyclin-dependent kinases 4/6 (CDK4/6), has significantly improved patient outcomes. However, the currently approved CDK4/6 inhibitors are associated with various side effects, underscoring the need for novel compounds with enhanced efficacy and safety profiles. This study aimed to identify potential CDK4/6 inhibitors from MeFSAT, a database of fungal secondary metabolites using an in-silico screening approach. The virtual screening process incorporated drug-likeness filters, ADME and toxicity predictions, consensus molecular docking, and 200 ns molecular dynamics simulations. Out of 411 initial compounds, two molecules demonstrated favorable binding interactions and stability with the CDK4/6 protein complex. The MTT assay showed that MSID000025 had dose-dependent cytotoxicity against MCF7 breast cancer cells. This suggests that MSID000025 could be a good candidate CDK4/6 inhibitor for treating breast cancer. Our study highlights the potential of fungal secondary metabolites as a source of novel compounds for drug discovery. It provides a framework for identifying CDK4/6 inhibitors with improved therapeutic properties.

In silico prediction of some pharmacokinetic, safety, biological activity and molecular docking studies of 1-piperazine indole hybrid with nicotinic amide and nicotinic acid and their analogues

Background

In silico predictions are now being utilized in drug discovery and design to assess the physicochemical, pharmacokinetics, and safety properties of compounds at the beginning of the drug discovery process. This early evaluation of the physicochemical, pharmacokinetics, and safety properties of compounds helps the researchers to invest their time and resources only in the best prospective lead compounds by eliminating compounds with a low chance of success.

Objective

The purpose of this study was to explore a promising lead compound designed from 1-piperazine indole hybrid with nicotinic amide and nicotinic acid analogs targeted on Trypanosoma brucei phosphofructokinase for Trypanosomiasis activity by using in silico predictions strategy.

Results

The physicochemical, safety, pharmacokinetic, and biological activity properties of those molecules were predicted by using ADMETlab 2.0, ACD labs Chem Sketch software version 14.0, Molinspiration software, and MolPredictX online tool. Our results indicate that several promising candidates exhibit favorable characteristics. Based on Molinspiration software both nicotinic acid and nicotinic amide derivatives showed higher kinase inhibitor activity and all nicotinic acid derivatives revealed enzyme inhibitors and GPCR ligand activity. According to the MolPredictX online tool, the most biologically active derivatives were NA-4, NA-11, and NAD-11.

Conclusion

Overall, our findings offer valuable insights into the potential efficacy and safety of these compounds. It appears that almost all of the compounds have successfully passed the pharmacokinetic evaluations and integration of nicotinic acid into indole appears to be more beneficial than nicotinic amide regarding certain biological activities.

Data mining of PubChem bioassay records reveals diverse OXPHOS inhibitory chemotypes as potential therapeutic agents against ovarian cancer

Focused screening on target-prioritized compound sets can be an efficient alternative to high throughput screening (HTS). For most biomolecular targets, compound prioritization models depend on prior screening data or a target structure. For phenotypic or multi-protein pathway targets, it may not be clear which public assay records provide relevant data. The question also arises as to whether data collected from disparate assays might be usefully consolidated. Here, we report on the development and application of a data mining pipeline to examine these issues. To illustrate, we focus on identifying inhibitors of oxidative phosphorylation, a druggable metabolic process in epithelial ovarian tumors. The pipeline compiled 8415 available OXPHOS-related bioassays in the PubChem data repository involving 312,093 unique compound records. Application of PubChem assay activity annotations, PAINS (Pan Assay Interference Compounds), and Lipinski-like bioavailability filters yields 1852 putative OXPHOS-active compounds that fall into 464 clusters. These chemotypes are diverse but have relatively high hydrophobicity and molecular weight but lower complexity and drug-likeness. These chemotypes show a high abundance of bicyclic ring systems and oxygen containing functional groups including ketones, allylic oxides (alpha/beta unsaturated carbonyls), hydroxyl groups, and ethers. In contrast, amide and primary amine functional groups have a notably lower than random prevalence. UMAP representation of the chemical space shows strong divergence in the regions occupied by OXPHOS-inactive and -active compounds. Of the six compounds selected for biological testing, 4 showed statistically significant inhibition of electron transport in bioenergetics assays. Two of these four compounds, lacidipine and esbiothrin, increased in intracellular oxygen radicals (a major hallmark of most OXPHOS inhibitors) and decreased the viability of two ovarian cancer cell lines, ID8 and OVCAR5. Finally, data from the pipeline were used to train random forest and support vector classifiers that effectively prioritized OXPHOS inhibitory compounds within a held-out test set (ROCAUC 0.962 and 0.927, respectively) and on another set containing 44 documented OXPHOS inhibitors outside of the training set (ROCAUC 0.900 and 0.823). This prototype pipeline is extensible and could be adapted for focus screening on other phenotypic targets for which sufficient public data are available.Scientific contributionHere, we describe and apply an assay data mining pipeline to compile, process, filter, and mine public bioassay data. We believe the procedure may be more broadly applied to guide compound selection in early-stage hit finding on novel multi-protein mechanistic or phenotypic targets. To demonstrate the utility of our approach, we apply a data mining strategy on a large set of public assay data to find drug-like molecules that inhibit oxidative phosphorylation (OXPHOS) as candidates for ovarian cancer therapies.

Alzheimer's Disease Immunotherapy and Mimetic Peptide Design for Drug Development: Mutation Screening, Molecular Dynamics, and a Quantum Biochemistry Approach Focusing on Aducanumab::Aβ2-7 Binding Affinity

Seven treatments are approved for Alzheimer's disease, but five of them only relieve symptoms and do not alter the course of the disease. Aducanumab (Adu) and lecanemab are novel disease-modifying antiamyloid-β (Aβ) human monoclonal antibodies that specifically target the pathophysiology of Alzheimer's disease (AD) and were recently approved for its treatment. However, their administration is associated with serious side effects, and their use is limited to early stages of the disease. Therefore, drug discovery remains of great importance in AD research. To gain new insights into the development of novel drugs for Alzheimer's disease, a combination of techniques was employed, including mutation screening, molecular dynamics, and quantum biochemistry. These were used to outline the interfacial interactions of the Aducanumab::Aβ2-7 complex. Our analysis identified critical stabilizing contacts, revealing up to 40% variation in the affinity of the Adu chains for Aβ2-7 depending on the conformation outlined. Remarkably, two complementarity determining regions (CDRs) of the Adu heavy chain (HCDR3 and HCDR2) and one CDR of the Adu light chain (LCDR3) accounted for approximately 77% of the affinity of Adu for Aβ2-7, confirming their critical role in epitope recognition. A single mutation, originally reported to have the potential to increase the affinity of Adu for Aβ2-7, was shown to decrease its structural stability without increasing the overall binding affinity. Mimetic peptides that have the potential to inhibit Aβ aggregation were designed by using computational outcomes. Our results support the use of these peptides as promising drugs with great potential as inhibitors of Aβ aggregation.

Investigational new drugs for the treatment of leishmaniasis

INTRODUCTION

Over the past 20 years, significant progress has been made in anti-leishmanial therapy. Three new drugs/formulations are available for the treatment of various forms of leishmaniasis, namely oral miltefosine, paromomycin and liposomal amphotericin B. However, these advances in drug development have added considerable complexity for clinicians including toxicity, emergence of resistance and decreased sensitivity of available drugs. The development of newer drugs with less toxicity and more efficacy is urgently needed.

AREAS COVERED

This review comprehensively examines the latest developments and current status of antileishmanial drugs for the treatment of leishmaniasis across the world. Several new investigational drugs that showed anti-leishmanial activity under in vitro or in vivo conditions and either underwent the phase-I/II clinical trials or are on the verge of entering the trials were reviewed. We also delve into the challenges of drug resistance and discuss the emergence of new and effective antileishmanial compounds.

EXPERT OPINION

The available treatments for leishmaniasis are limited in number, toxic, expensive, and demand extensive healthcare resources. Every available antileishmanial drug is associated with several disadvantages, such as drug resistance and toxicity or high cost. Miltefosine is potentially teratogenic. New antileishmanial drugs/treatment modalities are sorely needed for expanding future treatment options.

Uncovering the unique characteristics of different groups of 5-HT5AR ligands with reference to their interaction with the target protein

BACKGROUND

The serotonin 5-HT5A receptor has attracted much more research attention, due to the therapeutic potential of its ligands being increasingly recognized, and the possibilities that lie ahead of these findings. There is a growing body of evidence indicating that these ligands have procognitive, pro-social, and anti-depressant properties, which offers new avenues for the development of treatments that could address socially important conditions related to the malfunctioning of the central nervous system. The aim of our study was to unravel the molecular determinants for 5-HT5AR ligands that govern their activity towards the receptor.

METHODS

In response to the need for identification of molecular determinants for 5-HT5AR activity, we prepared a comprehensive collection of 5-HT5AR ligands, carefully gathering literature and patent data. Leveraging molecular modeling techniques, such as pharmacophore hypothesis development, docking, and molecular dynamics simulations enables to gain valuable insights into the specific interactions of 5-HT5AR ligand groups with the receptor.

RESULTS

The obtained comprehensive set of 2160 compounds was divided into dozens of subsets, and a pharmacophore model was developed for each group. The results from the docking and molecular dynamics simulations have enabled the identification of crucial ligand-protein interactions that are essential for the compound's activity towards 5-HT5AR.

CONCLUSIONS

The findings from the molecular modeling study provide valuable insights that can guide medicinal chemists in the development of new 5-HT5AR ligands. Considering the pharmacological significance of these compounds, they have the potential to become impactful treatments for individuals and communities in the future. Understanding how different crystal/cryo-EM structures of 5-HT5AR affect molecular modeling experiments could have major implications for future computational studies on this receptor.

High-throughput virtual screening of Streptomyces spp. metabolites as antiviral inhibitors against the Nipah virus matrix protein

Nipah virus (NiV) remains a significant global concern due to its impact on both the agricultural industry and human health, resulting in substantial economic and health consequences. Currently, there is no cure or commercially available vaccine for the virus. Therefore, it is crucial to prioritize the discovery of new and effective treatment options to prevent its continued spread. Streptomyces spp. are rich sources of metabolites known for their bioactivity against certain diseases; however, their potential as antiviral drugs against the Nipah virus remain unexplored. In this study, 6524 Streptomyces spp. metabolites were screened through in silico methods for their inhibitory effects against the Nipah virus matrix (NiV-M) protein, which assists in virion assembly of Nipah virus. Different computer-aided tools were utilized to carry out the virtual screening process: ADMET profiling revealed 913 compounds with excellent safety and efficacy profiles, molecular docking predicted the binding poses and associated docking scores of the ligands in their respective targets, MD simulations confirmed the binding stability of the top ten highest-scoring ligands in a 100 ns all-atom simulation, PCA elucidated simulation convergence, and MMPB(GB)SA calculations estimated the binding energies of the final candidate compounds and determined the key residues crucial for complex formation. Using in silico methods, we identified six metabolites targeting the main substrate-binding site and five targeting the dimerization site that exhibited excellent stability and strong binding affinity. We recommend testing these compounds in the next stages of drug development to confirm their effectiveness as therapeutic agents against Nipah virus.

Rationalize the Functional Roles of Protein-Protein Interactions in Targeted Protein Degradation by Kinetic Monte-Carlo Simulations

Targeted protein degradation is a promising therapeutic strategy to tackle disease-causing proteins that lack binding pockets for traditional small-molecule inhibitors. Its first step is to trigger the proximity between a ubiquitin ligase complex and a target protein through a heterobifunctional molecule, such as proteolysis targeting chimeras (PROTACs), leading to the formation of a ternary complex. The properties of protein-protein interactions play an important regulatory role during this process, which can be reflected by binding cooperativity. Unfortunately, although computer-aided drug design has become a cornerstone of modern drug development, the endeavor to model targeted protein degradation is still in its infancy. The development of computational tools to understand the impacts of protein-protein interactions on targeted protein degradation, therefore, is highly demanded. To reach this goal, we constructed a non-redundant structural benchmark of the most updated ternary complexes and applied a kinetic Monte-Carlo method to simulate the association between ligases and PROTAC-targeted proteins in the benchmark. Our results show that proteins in most complexes with positive cooperativity tend to associate into native-like configurations more often. In contrast, proteins very likely failed to associate into native-like configurations in complexes with negative cooperativity. Moreover, we compared the protein-protein association through different interfaces generated from molecular docking. The native-like binding interface shows a higher association probability than all the other alternative interfaces only in the complex with positive cooperativity. These observations support the idea that the formation of ternary complexes is closely regulated by the binary interactions between proteins. Finally, we applied our method to cyclin-dependent kinases 4 and 6 (CDK4/6). We found that their interactions with the ligase are not as similar as their structures. Altogether, our study paves the way for understanding the role of protein-protein interactions in PROTACE-induced ternary complex formation. It can potentially help in searching for degraders that selectively target specific proteins.

In silico approach revealed the membrane receptor PHO36 as a new target for synthetic anticandidal peptides

Aim: Synthetic antimicrobial peptides (SAMPs) present the potential to fight systemic fungal infections. Here, the PHO36 receptor from Candida albicans was analyzed by in silico tools as a possible target for three anticandidal SAMPs: RcAlb-PepIII, PepGAT and PepKAA.Materials & methods: Molecular docking, dynamics and quantum biochemistry were employed to understand the individual contribution of amino acid residues in the interaction region.Results: The results revealed that SAMPs strongly interact with the PHO36 by multiple high-energy interactions. This is the first study to employ quantum biochemistry to describe the interactions between SAMPs and the PHO36 receptor.Conclusion: This work contributes to understanding and identifying new molecular targets with medical importance that could be used to discover new drugs against systemic fungal infections.

Marine natural compounds as potential CBP bromodomain inhibitors for treating cancer: an in-silico approach using molecular docking, ADMET, molecular dynamics simulations and MM-PBSA binding free energy calculations

The cAMP-responsive element binding protein (CREB) binding protein (CBP), a bromodomain-containing protein, engages with multiple transcription factors and enhances the activation of many genes. CBP bromodomain acts as an epigenetic reader and plays an important role in the CBP-chromatin interaction which makes it an important drug target for treating many diseases. Though inhibiting CBP bromodomain was reported to have great potential in cancer therapeutics, approved CBP bromodomain inhibitor is yet to come. We utilized various in silico approaches like molecular docking, ADMET, molecular dynamics (MD) simulations, MM-PBSA calculations, and in silico PASS predictions to identify potential CBP bromodomain inhibitors from marine natural compounds as they have been identified as having distinctive chemical structures and greater anticancer activities. To develop a marine natural compound library for this investigation, Lipinski's rule of five was used. Sequential investigations utilizing molecular docking, ADMET studies, 100 ns MD simulations, and MM-PBSA calculations revealed that three marine compounds-ascididemin, neoamphimedine, and stelletin A-demonstrated superior binding affinity compared to the standard inhibitor, 69 A. These compounds also exhibited suitable drug-like properties, a favorable safety profile, and formed stable protein-ligand complexes. The in-silico PASS tool predicted that these compounds have significant potential for anticancer activity. Among them, ascididemin demonstrated the highest binding affinity in both molecular docking and MM-PBSA calculations, as well as a better stability profile in MD simulations. Hence, ascididemin can be a potential inhibitor of CBP bromodomain. However, in vitro and in vivo validation is required for further confirmation of these findings.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00258-5.

From pixels to druggable leads: A CADD strategy for the design and synthesis of potent DDR1 inhibitors

BACKGROUND AND OBJECTIVE

While numerous in silico tools exist for target-based drug discovery, the inconsistent integration of in vitro data with predictive models hinders research and development productivity. This is particularly apparent during the Hit-to-Lead stage, where unreliable in-silico tools often lead to suboptimal lead selection. Herein, we address this challenge by presenting a CADD-guided pipeline that successfully integrates rational drug design with in-silico hits to identify a promising DDR1 lead.

METHODS

2 × 1000 ns MD simulations along with their respective FEL and MMPBSA analyses were employed to guide the rational design and synthesis of 12 novel compounds which were evaluated for their DDR inhibition.

RESULTS

The molecular dynamics investigation of the initial hit led to the identification of key structural features within the DDR1 binding pocket. The identified key features were used to guide the rational design and synthesis of twelve novel derivatives. SAR analysis, biological evaluation, molecular dynamics, and free energy calculations were carried out for the synthesized derivatives to understand their mechanism of action. Compound 4c exhibited the strongest inhibition and selectivity for DDR1, with an IC50 of 0.11 µM.

CONCLUSIONS

The MD simulations led to the identification of a key hydrophobic groove in the DDR1 binding pocket. The integrated approach of SAR analysis with molecular dynamics led to the identification of compound 4c as a promising lead for further development of potent and selective DDR1 inhibitors. Moreover, this work establishes a protocol for translating in silico hits to real world bioactive druggable leads.

Antifungal activity of synthetic xanthenone against fluconazole-resistant Candida auris and its mechanism of action

Candida auris, an emerging multidrug-resistant fungal pathogen discovered in Japan in 2009, poses a significant global health threat, with infections reported in about 25 countries. The escalation of drug-resistant strains underscores the urgent need for new treatment options. This study aimed to investigate the antifungal potential of 2,3,4,4a-tetrahydro-1H-xanthen-1-one (XA1) against C. auris, as well as its mechanism of action and toxic profile. The antifungal activity of XA1 was first evaluated by determining the minimum inhibitory concentration (MIC), time-kill kinetics and biofilm inhibition. In addition, structural changes, membrane permeability, reactive oxygen species (ROS) production, and in vitro and in vivo toxicity of C. auris after exposure to XA1 were investigated. The results indicated that XA1 exhibited an MIC of 50 μg/mL against C. auris, with time-kill kinetics highlighting its efficacy. Field emission scanning electron microscopy (FE-SEM) showed structural damage in XA1-treated cells, supported by increased membrane permeability leading to cell death. Furthermore, XA1 induced ROS production and significantly inhibited biofilm formation. Importantly, XA1 exhibited low cytotoxicity in human epidermal keratinocytes (HaCaT), with a cell viability of over 90 % at 6.25 μg/mL. In addition, an LD50 of 17.68 μg/mL was determined in zebrafish embryos 24 h post fertilization (hpf), with developmental delay observed at prolonged exposure at 6.25 μg/mL (48-96 hpf). These findings position XA1 as a promising candidate for further research and development of an effective antifungal agent.

Log D7.4 and plasma protein binding of synthetic cannabinoid receptor agonists and a comparison of experimental and predicted lipophilicity

The emergence of new synthetic cannabinoid receptor agonists (SCRAs) onto the illicit drugs market continues to cause harm, and the overall availability of physicochemical and pharmacokinetic data for new psychoactive substances is lacking. The lipophilicity of 23 SCRAs and the plasma protein binding (PPB) of 11 SCRAs was determined. Lipophilicity was determined using a validated chromatographic hydrophobicity index (CHI) log D method; tested SCRAs showed moderate to high lipophilicity, with experimental log D7.4 ranging from 2.48 (AB-FUBINACA) to 4.95 (4F-ABUTINACA). These results were also compared to in silico predictions generated using seven commercially available software packages and online tools (Canvas; ChemDraw; Gastroplus; MoKa; PreADMET; SwissADME; and XlogP). Licenced, dedicated software packages provided more accurate lipophilicity predictions than those which were free or had prediction as a secondary function; however, the latter still provided competitive estimates in most cases. PPB of tested SCRAs, as determined by equilibrium dialysis, was in the upper range of the lipophilicity scale, ranging from 90.8% (ADB-BUTINACA) to 99.9% (BZO-HEXOXIZID). The high PPB of these drugs may contribute to reduced rate of clearance and extended durations of pharmacological effects compared to lesser-bound SCRAs. The presented data improve understanding of the behaviour of these drugs in the body. Ultimately, similar data and predictions may be used in the prediction of the structure and properties of drugs yet to emerge on the illicit market.

Molecular docking and antimicrobial activities of photoexcited inhibitors in antimicrobial photodynamic therapy against Enterococcus faecalis biofilms in endodontic infections

Antimicrobial photodynamic therapy (aPDT) is a promising approach to combat antibiotic resistance in endodontic infections. It eliminates residual bacteria from the root canal space and reduces the need for antibiotics. To enhance its effectiveness, an in silico and in vitro study was performed to investigate the potential of targeted aPDT using natural photosensitizers, Kojic acid and Parietin. This approach aims to inhibit the biofilm formation of Enterococcus faecalis, a frequent cause of endodontic infections, by targeting the Ace and Esp proteins. After determining the physicochemical characteristics of Ace and Esp proteins and model quality assessment, the molecular dynamic simulation was performed to recognize the structural variations. The stability and physical movement of the protein-ligand complexes were evaluated. In silico molecular docking was conducted, followed by ADME/Tox profiling, pharmacokinetics characteristics, and assessment of drug-likeness properties of the natural photosensitizers. The study also investigated the changes in the expression of genes (esp and ace) involved in E. faecalis biofilm formation. The results showed that both Kojic acid and Parietin complied with Lipinski's rule of five and exhibited drug-like properties. In silico analysis indicated stable complexes between Ace and Esp proteins and the natural photosensitizers. The molecular docking studies demonstrated good binding affinity. Additionally, the expression of the ace and esp genes was significantly downregulated in aPDT using Kojic acid and Parietin with blue light compared to the control group. This investigation concluded that Kojic acid and Parietin with drug-likeness could efficiently interact with Ace and Esp proteins with a strong binding affinity. Hence, natural photosensitizers-mediated aPDT can be considered a promising adjunctive treatment against endodontic infections.

Targeting PI3K family with small-molecule inhibitors in cancer therapy: current clinical status and future directions

The Phosphatidylinositol-3-kinase (PI3K) family is well-known to comprise three classes of intracellular enzymes. Class I PI3Ks primarily function in signaling by responding to cell surface receptor stimulation, while class II and III are more involved in membrane transport. Under normal physiological conditions, the PI3K signaling network orchestrates cell growth, division, migration and survival. Aberrant activation of the PI3K signaling pathway disrupts cellular activity and metabolism, often marking the onset of cancer. Currently, the Food and Drug Administration (FDA) has approved the clinical use of five class I PI3K inhibitors. These small-molecule inhibitors, which exhibit varying selectivity for different class I PI3K family members, are primarily used in the treatment of breast cancer and hematologic malignancies. Therefore, the development of novel class I PI3K inhibitors has been a prominent research focus in the field of oncology, aiming to enhance potential therapeutic selectivity and effectiveness. In this review, we summarize the specific structures of PI3Ks and their functional roles in cancer progression. Additionally, we critically evaluate small molecule inhibitors that target class I PI3K, with a particular focus on their clinical applications in cancer treatment. Moreover, we aim to analyze therapeutic approaches for different types of cancers marked by aberrant PI3K activation and to identify potential molecular targets amenable to intervention with small-molecule inhibitors. Ultimately, we propose future directions for the development of therapeutic strategies that optimize cancer treatment outcomes by modulating the PI3K family.

Gastroprotective role of a flavonoid-rich subfraction from Fridericia chica (Bonpl.) L. G. Lohmann: a medicinal plant used in the Amazon region

Fridericia chica is an Amazonian plant used to treat stomach disorders. However, the pharmacological activity of flavonoids in the extract has yet to be investigated. Therefore, we considered that a flavonoid-rich F. chica subfraction (FRS) has gastroprotective functions. For this, before the induction of gastric ulcers with ethanol or piroxicam, the rats received vehicle (water), omeprazole (30 mg/kg), or FRS (30 mg/kg), and the ulcer area was measured macro and microscopically, and the antisecretory action was investigated in pylorus-ligated rats. In addition, the roles of nitric oxide (NO) and nonprotein sulfhydryl compounds (NP-SH) in the gastroprotective effects of FRS were studied. FRS reduced ethanol- and piroxicam-induced ulcerations by 81% and 77%, respectively, as confirmed histologically. Antioxidant effects were observed for FRS through the maintenance of GSH and LPO levels, and the SOD and CAT activity similar to those found in the nonulcerated group. Moreover, FRS avoided the increase in MPO activity and TNF, IL-6, IL-4 and IL-10 levels. Moreover, mucin staining increased in ulcerated rats receiving FRS, and the pharmacological mechanism gastroprotective seems to involve the NO and NP-SH in addition to antisecretory actions. The chemical study by mass spectrometry confirmed the presence of flavonoids in FRS, and molecular docking studies have shown that these compounds interact with cyclooxygenase-1 and NO synthase. Furthermore, there was no indication that FRS had cytotoxic effects. Our results support the popular use of F. chica, and we conclude that the gastroprotection effect promoted by FRS can be attributed to the combined effect of the flavonoids.

In silico exploration of PD-L1 binding compounds: Structure-based virtual screening, molecular docking, and MD simulation

Programmed death-ligand 1 (PD-L1), a transmembrane protein, is associated with the regulation of immune system. It frequently has overexpression in various cancers, allowing tumor cells to avoid immune detection. PD-L1 inhibition has risen as a potential strategy in the field of therapeutic immunology for cancer. In the current study, structure-based virtual screening of drug libraries was conducted and then the screened hits were docked to the active residues of PD-L1 to select the optimal binding poses. The top ten compounds with binding affinities ranging from -10.734 to -10.398 kcal/mol were selected for further analysis. The ADMET analysis of selected compounds showed the compounds meet the criteria of ADMET properties. Further, the conformational changes and binding stability of the top two compounds was analyzed by conducting 200 ns simulation and it was observed that the hits did not exert conformational changes to the protein structure. All the results suggest that the chosen hits can be considered as lead compounds for the inhibition of biological activity of PD-L1 in in vitro studies.

Synthesis of new two 1,2-disubstituted benzimidazole compounds: their in vitro anticancer and in silico molecular docking studies

In this study, two new molecules were synthesized from the reaction of 2-methyl-1H-benzo[d]imidazole with aryl halides in the presence of a strong base. The structures newly of synthesized 1,2-disubstituted benzimidazole compounds were characterized using spectroscopic techniques (FT-IR, 1HNMR, 13CNMR) and chromatographic technique (LC/MS). For discovering an effective anticancer drug, the developed heterocyclic compounds were screened against three different human cancer cell lines (A549, DLD-1, and L929). The results demonstrated that of IC50 values of compound 2a were higher as compared to cisplatin for the A549 and DLD-1 cell lines. The frontier molecular orbital (FMO), and molecular electrostatic potential map (MEP) analyses were studied by using DFT (density functional theory) calculations at B3LYP/6-31G** level of theory. The molecular docking studies of the synthesized compound with lung cancer protein, PDB ID: 1M17, and colon cancer antigen proteins, PDB ID: 2HQ6 were performed to compare with experimental and theoretical data. Compound 2a had shown the best binding affinity with -6.6 kcal/mol. It was observed that the theoretical and experimental studies carried out supported each other.

Catechol compounds as dual-targeting agents for fish protection against Ichthyophthirius multifiliis infections

Aquaculture is one of the fastest growing sectors in global food production, recognized as a significant contributor to poverty alleviation, food security, and income generation. However, the frequent occurrence of diseases caused by pathogen infections result in reduced yields and economic losses, posing a substantial constraint to the sustainable development of aquaculture. Here, our study identified that four catechol compounds, quercetin, luteolin, caffeic acid, and chlorogenic acid, exhibited potent antiparasitic effects against Ichthyophthirius multifiliis in both, in vitro and in vivo. The parasite is recognized as one of the most pathogenic to fish worldwide. Using a combination of in silico methods, the dipeptidyl peptidase (DPP) was identified as a critical target for catechol compounds. The two hydroxyl radicals of the catechol group were essential for its binding to and interacting with the DPP protein. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that catechol compounds disrupt pathways associated with the metabolism and growth of I. multifiliis, thereby exerting antiparasitic effects. Furthermore, these compounds attenuated the expression of proinflammatory cytokines in vivo in fish and promoted macrophage polarization toward M2 phenotype by inhibiting the STAT1 signaling pathway. The dual activity of catechol compounds, acting as both direct antiparasitic and anti-inflammatory agents in fish, offers a promising therapeutic approach for combating I. multifiliis infections in aquaculture.

Using induced pluripotent stem cells for drug discovery in arrhythmias

INTRODUCTION

Arrhythmias are disturbances in the normal rhythm of the heart and account for significant cardiovascular morbidity and mortality worldwide. Historically, preclinical research has been anchored in animal models, though physiological differences between these models and humans have limited their clinical translation. The discovery of human induced pluripotent stem cells (iPSC) and subsequent differentiation into cardiomyocyte has led to the development of new in vitro models of arrhythmias with the hope of a new pathway for both exploration of pathogenic variants and novel therapeutic discovery.

AREAS COVERED

The authors describe the latest two-dimensional in vitro models of arrhythmias, several examples of the use of these models in drug development, and the role of gene editing when modeling diseases. They conclude by discussing the use of three-dimensional models in the study of arrythmias and the integration of computational technologies and machine learning with experimental technologies.

EXPERT OPINION

Human iPSC-derived cardiomyocytes models have significant potential to augment disease modeling, drug discovery, and toxicity studies in preclinical development. While there is initial success with modeling arrhythmias, the field is still in its nascency and requires advances in maturation, cellular diversity, and readouts to emulate arrhythmias more accurately.

Structural screening and molecular simulation identify potential ligands against the K700E hot spot variant and functional pockets of SF3B1 to modulate splicing in myelodysplastic syndrome

Myelodysplastic syndrome (MDS), a blood disorder with ineffective hematopoiesis and risk of transformation to acute myeloid leukemia, is characterized by recurring cytogenetic and molecular alterations. By chromosome analysis, approximately 60% of patients, carry chromosome 5 and 7 alterations, trisomy of chromosome 8 and may also present with increasingly complex karyotypes, especially in higher grade MDS (MDS with refractory anemia and increased blasts type 1 and 2). Moreover, somatic pathogenic variants in genes associated with aberrant mRNA splicing are frequently mutated with SF3B1 the most frequently mutated. In the setting of SF3B1, the K700E hot-spot mutation is present in approximately 50% of cases. Since recent studies have highlighted modulation of functional dynamics in SF3B1 by mutant splicing factors, the objective of the study was to identify potential small molecule modulators against the frequently mutated RNA splicing factor SF3B1(K700E) and functional allosteric sites by using a molecular structure-based approach and a molecular dynamic simulation. To identify potential SF3B1 modulators, we collected a series of chemical compounds from the Zinc and Enamine database. An initial screen followed by further molecular analysis and simulation using the Schrödinger suite was performed. Parameters used to monitor the stability and binding of the protein-ligand complex included: RMSF, protein-ligand contacts, electrostatic, Van Der Waals forces and binding energies (MMGBSA). A 100-nanosecond simulation showed strong binding between selected compounds and key amino acid residues, including the mutation hot-spot K700E and functional allosteric amino acid residue R630. Ligand binding energies between compounds and key amino acid residues ranged from -50.67 to -58.04 kcal/mol. In brief, small molecule modulators show strong binding to SF3B1 suggesting these compounds may be used against cells harboring the K700E variant or to modulate splicing by targeting functional allosteric sites.

Molecular docking of antidiabetic molecules of libas (Spondias pinnata) fruit and prediction of their pharmacokinetic properties

Diabetes mellitus is one of the chronic metabolic disorders that affects more than 16 million Filipinos. Proper education, medical intervention, and a good lifestyle can help individuals control and manage this disease. Spondias pinnata is one of the underutilized crops in the Philippines that is well-known for its satisfactory flavor and medicinal properties, including its antidiabetic activity. The quest for a natural and effective drug to manage diseases is a continuous work in progress. Drug discovery and design is a tedious and expensive process. Computer-aided drug design guides the design and makes the process more efficient and less costly. Molecular docking was used to determine the potential antidiabetic compounds from the 48 reported compounds found in S. pinnata fruit. Seven compounds namely squalene (-9.1 kcal/mol), rutin (-9 kcal/mol), catechin (-8.7 kcal/mol), quercetin (-8.5 kcal/mol), tocopherol (-8.4 kcal/mol), myricetin (-8.4 kcal/mol), and ellagic acid (-8.3 kcal/mol) showed binding affinities comparable to those of pioglitazone, a standard drug, with peroxisome proliferator-activated receptor gamma (PPARγ). Tocopherol and catechin showed good ADMET properties. Among the two compounds, catechin passed the four filters for drug-likeness. Thus, catechin could be a potential compound for the development of antidiabetic drugs.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00230-3.

Accurate and Efficient Conformer Sampling of Cyclic Drug-Like Molecules with Inverse Kinematics

Identification of all of the influential conformers of biomolecules is a crucial step in many tasks of computational biochemistry. Specifically, molecular docking, a key component of in silico drug development, requires a comprehensive set of conformations for potential candidates in order to generate the optimal ligand-receptor poses and, ultimately, find the best drug candidates. However, the presence of flexible cycles in a molecule complicates the initial search for conformers since exhaustive sampling algorithms via torsional random and systematic searches become very inefficient. The devised inverse-kinematics-based Monte Carlo with refinement (MCR) algorithm identifies independently rotatable dihedral angles in (poly)cyclic molecules and uses them to perform global conformational sampling, outperforming popular alternatives (MacroModel, CREST, and RDKit) in terms of speed and diversity of the resulting conformer ensembles. Moreover, MCR quickly and accurately recovers naturally occurring macrocycle conformations for most of the considered molecules.

Site Identification and Next Choice Protocol for Hit-to-Lead Optimization

Time efficiency and cost savings are major challenges in drug discovery and development. In this process, the hit-to-lead stage is expected to improve efficiency because it primarily exploits the trial-and-error approach of medicinal chemists. This study proposes a site identification and next choice (SINCHO) protocol to improve the hit-to-lead efficiency. This protocol selects an anchor atom and growth site pair, which is desirable for a hit-to-lead strategy starting from a 3D complex structure. We developed and fine-tuned the protocol using a training data set and assessed it using a test data set of the preceding hit-to-lead strategy. The protocol was tested for experimentally determined structures and molecular dynamics (MD) ensembles. The protocol had a high prediction accuracy for applying MD ensembles, owing to the consideration of protein flexibility. The SINCHO protocol enables medicinal chemists to visualize and modify functional groups in a hit-to-lead manner.

Corydalis ternata Nakai Alleviates Cognitive Decline in Alzheimer's Disease by Reducing β-Amyloid and Neuroinflammation

Recently, natural herbs have gained increasing attention owing to their comparatively low toxicity levels and the abundance of historical medical documentation regarding their use. Nevertheless, owing to a lack of knowledge regarding these herbs and their compounds, attempts to find those that could be beneficial for treating diseases have often been ad hoc; thus, there is now a growing demand for an in silico method to identify beneficial herbs. In this study, we present a computational approach for identifying natural herbs specifically effective in treating cognitive decline in Alzheimer's disease (AD) sufferers, which analyzes the similarities between herbal compounds and known drugs targeting AD-related proteins. Our in silico method suggests that Corydalis ternata can improve cognitive decline in AD sufferers. Behavioral tests with an AD mouse model for the confirmation of the in silico prediction reveals that C. ternata significantly alleviated the cognitive decline (memory and motor functions) caused by neurodegeneration. Further pathology analyses reveal that C. ternata decreases the level of Aβ plaques, reduces neuroinflammation, and promotes autophagy flux, and thus C. ternata can be clinically effective for preventing mild cognitive impairment during the early stages of AD. These findings highlight the potential utility of our in silico method and the potential clinical application of the identified natural herb in treating and preventing AD.

Unveiling G-protein coupled receptor kinase-5 inhibitors for chronic degenerative diseases: Multilayered prioritization employing explainable machine learning-driven multi-class QSAR, ligand-based pharmacophore and free energy-inspired molecular simulation

GRK5 holds a pivotal role in cellular signaling pathways, with its overexpression in cardiomyocytes, neuronal cells, and tumor cells strongly associated with various chronic degenerative diseases, which highlights the urgent need for potential inhibitors. In this study, multiclass classification-based QSAR models were developed using diverse machine learning algorithms. These models were built from curated compounds with experimentally derived GRK5 inhibitory activity. Additionally, a pharmacophore model was constructed using active compounds from the dataset. Among the models, the SVM-based approach proved most effective and was initially used to screen DrugBank compounds within the applicability domain. Compounds showing significant GRK5 inhibitory potential underwent evaluation for key pharmacophoric features. Prospective compounds were subjected to molecular docking to assess binding affinity towards GRK5's key active site amino acid residues. Stability at the binding site was analyzed through 200 ns molecular dynamics simulations. MM-GBSA analysis quantified individual free energy components contributing to the total binding energy with respect to binding site residues. Metadynamics analysis, including PCA, FEL, and PDF, provided crucial insights into conformational changes of both apo and holo forms of GRK5 at defined energy states. The study identifies DB02844 (S-Adenosyl-1,8-Diamino-3-Thiooctane) and DB13155 (Esculin) as promising GRK5 inhibitors, warranting further in vitro and in vivo validation studies.

Microalgae Octapeptide IIAVEAGC Alleviates Oxidative Stress and Neurotoxicity in 6-OHDA-Induced SH-SY5Y Cells by Regulating the Nrf2/HO-1and Jak2/Stat3 Pathways

Neurodegenerative diseases are characterized by the progressive loss of selectively vulnerable populations of neurons, and many factors are involved in its causes. Neurotoxicity and oxidative stress, are the main related factors. The octapeptide Ile-Ile-Ala-Val-Glu-Ala-Gly-Cys (IEC) was identified from the microalgae Isochrysis zhanjiangensis and exhibited potential anti-oxidative stress activity. In this study, the stability of α-synaptic protein binding to IEC was modeled using molecular dynamics, and the results indicated binding stabilization within 60 ns. Oxidative stress in neurons is the major cause of α-synaptic protein congestion. Therefore, we next evaluated the protective effects of IEC against oxidative stress and neurotoxicity in 6-ohdainduced Parkinson's disease (PD) model SH-SY5Y cells in vitro. In oxidative stress, IEC appeared to increase the expression of the antioxidant enzymes HO-1 and GPX through the antioxidant pathway of Nrf2, and molecular docking of IEC with Nrf2 and GPX could generate hydrogen bonds. Regarding apoptosis, IEC protected cells by increasing the Bcl-2/Bax ratio, inhibiting the caspase cascade, acting on p53, and modulating the Jak2/Stat3 pathway. The results indicated that IEC exerted neuroprotective effects through the inhibition of α-synaptic protein aggregation and antioxidant activity. Therefore, microalgal peptides have promising applications in the prevention and treatment of neurodegenerative diseases.

DeLA-DrugSelf: Empowering multi-objective de novo design through SELFIES molecular representation

In this paper, we introduce DeLA-DrugSelf, an upgraded version of DeLA-Drug [J. Chem. Inf. Model. 62 (2022) 1411-1424], which incorporates essential advancements for automated multi-objective de novo design. Unlike its predecessor, which relies on SMILES notation for molecular representation, DeLA-DrugSelf employs a novel and robust molecular representation string named SELFIES (SELF-referencing Embedded String). The generation process in DeLA-DrugSelf not only involves substitutions to the initial string representing the starting query molecule but also incorporates insertions and deletions. This enhancement makes DeLA-DrugSelf significantly more adept at executing data-driven scaffold decoration and lead optimization strategies. Remarkably, DeLA-DrugSelf explicitly addresses the SELFIES-related collapse issue, considering only collapse-free compounds during generation. These compounds undergo a rigorous quality metrics evaluation, highlighting substantial advancements in terms of drug-likeness, uniqueness, and novelty compared to the molecules generated by the previous version of the algorithm. To evaluate the potential of DeLA-DrugSelf as a mutational operator within a genetic algorithm framework for multi-objective optimization, we employed a fitness function based on Pareto dominance. Our objectives focused on target-oriented properties aimed at optimizing known cannabinoid receptor 2 (CB2R) ligands. The results obtained indicate that DeLA-DrugSelf, available as a user-friendly web platform (https://www.ba.ic.cnr.it/softwareic/delaself/), can effectively contribute to the data-driven optimization of starting bioactive molecules based on user-defined parameters.