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The de novo design of small molecule-binding proteins has seen exciting recent progress; however, high-affinity binding and tunable specificity typically require laborious screening and optimization after computational design. We developed a computational procedure to design a protein that recognizes a common pharmacophore in a series of poly(ADP-ribose) polymerase-1 inhibitors. One of three designed proteins bound different inhibitors with affinities ranging from

A series of new diterpene quinopimaric acid derivatives modified at the hydroxyl group with different pharmacophore fragments has been synthesised and their (along with previously obtained compounds) inhibitory properties towards cholinesterases were studied. Thereby an indole-3-acetyl derivative 7 and a propargyl substituted compound 28 were shown to be excellent and acetylcholinesterase-selective inhibitors. Both compounds inhibited the enzyme as a mixed type inhibitor, and Ki values of 0.41 and 0.44 µM and Ki' values of 0.98 and 2.26 µM were determined. The binding interactions between all active compounds and ligands protein were confirmed through molecular docking study. [ABSTRACT FROM AUTHOR]

Numerous research studies have demonstrated the significant correlation of phosphatidylinositol‐3 kinase gamma (PI3Kγ) with the onset and progression of various human diseases, highlighting PI3Kγ as a promising therapeutic target. However, PI3Kγ demonstrates considerable similarity with other isoforms in the PI3K family, presenting significant challenges in the creation of PI3Kγ inhibitors. This study presents an ensemble‐based virtual screening approach to discover novel inhibitors targeting PI3Kγ. Eganelisib (IPI‐549) is the sole selective PI3Kγ inhibitor that has progressed to clinical trials, making it a significant model for the advancement of novel PI3Kγ inhibitors. Initially, common feature pharmacophore and receptor–ligand pharmacophore models were independently developed using IPI‐549 and its potent derivatives, in conjunction with the crystal complex of PI3Kγ/IPI‐549. Both qualitative pharmacophore models proved highly effective at distinguishing between active and inactive compounds. Then, four widely utilized docking programs were chosen for assessment, where the Glide_SP mode demonstrated superior predictive accuracy in sampling ligand conformations during binding, effectively distinguishing between PI3Kγ inhibitors and noninhibitors. Finally, a virtual screening protocol was conducted to screen the ChEMBL database, utilizing similarity search, consensus‐based pharmacophore mapping, and sequential molecular docking. This process resulted in the identification of multiple molecules exhibiting notable promise as potent PI3Kγ inhibitors. [ABSTRACT FROM AUTHOR]

A wide range of bioactive compounds have been created using the versatile pharmacophore pyrimidine. In order to improve biological applications, we, therefore, envisioned adding these privileged moieties. In this work, we developed an efficient 2-aminopyrimidine derivatives. We further investigated the anticancer activity of all the compounds against colon cancer cell lines COLO-205 and HT-29. Out of several compounds synthesized, two compounds SD2 and SD4 have shown comparable potent anticancer activity when compared to standard Cabozantinib. The most potent cytotoxic compound against colon cancer cells in our study was found to be SD2 with an IC50 value of 9.57 μ M. The investigation from molecular docking showed the best binding affinity. The complex stability within an enzyme's pocket was demonstrated by the molecular dynamic simulation running for 100 ns. The work intends to critically search 2-aminopyrimidine derivatives for anticancer activity in two colon cancer cell lines (HT-29 and COLO-205). Advanced computational studies are carried out to provide more insight. Two compounds showed comparative anticancer activity in cytotoxicity and molecular modeling studies with standard. [ABSTRACT FROM AUTHOR]

Cerebroside sulfotransferase (CST) is considered as therapeutic target for substrate reduction therapy (SRT) for metachromatic leukodystrophy (MLD). The present study evaluates the therapeutic potential of 57 phytoconstituents of Withania somnifera against CST. Using binding score cutoff ≤-7.0 kcal/mol, top 10 compounds were screened and after ADME and toxicity-based screening, Withasomidienone, 2,4-methylene-cholesterol, and 2,3-Didehydrosomnifericin were identified as safe and potent drug candidates for CST inhibition. Key substrate binding site residues involved in interaction were LYS82, LYS85, SER89, TYR176, PHE170, PHE177. Four steroidal Lactone-based withanolide backbone of these compounds played a critical role in stabilizing their position in the active site pocket. 100 ns molecular dynamics simulation and subsequent trajectory analysis through structural deviation and compactness, principal components, free energy landscape and correlation matrix confirmed the stability of CST-2,3-Didehydrosomnifericin complex throughout the simulation and therefore is considered as the most potent drug candidate for CST inhibition and Withasomidienone as the second most potent drug candidate. The reverse pharmacophore analysis further confirmed the specificity of these two compounds towards CST as no major cross targets were identified. Thus, identified compounds in this study strongly present their candidature for oral drug and provide route for further development of more specific CST inhibitors. [ABSTRACT FROM AUTHOR]

Introduction: Prostate cancer (PCa) is the second most frequent cancer diagnosis in men and the fifth leading cause of death worldwide. Prostate Specific Membrane Antigen (PSMA) and Gastrin Releasing Peptide (GRP) receptors are overexpressed in PCa. In this study, we have developed iron oxide nanoparticles (IONs) functionalized with the Prostate Specific Membrane Antigen (PSMA) and Gastrin Releasing Peptide (GRP) ligands for dual targeting of Prostate cancer. Methods: IONs were developed with a thin silica layer on their surface with MPTES (carrying -SH groups, IONs-SH), and they were coupled either with a pharmacophore targeting PSMA (IONs-PSMA) or with bombesin peptide (IONs-BN), targeting GRP receptors, or with both (IONs-PSMA/BN). The functionalized IONs were characterized for their size, zeta potential, and efficiency of functionalization using dynamic light scattering (DLS) and Fourier-Transform Infrared Spectroscopy (FT-IR). All the aforementioned types of IONs were radiolabeled directly with Technetium-99m (99mTc) and evaluated for their radiolabeling efficiency, stability, and binding ability on two different PCa cell lines (PC3 and LNCaP). Results and Discussion: The MTT assay demonstrated low toxicity of the IONs against PC3 and LNCaP cells, while the performed wound-healing assay further proved that these nanostructures did not affect cellular growth mechanisms. The observed hemolysis ratio after co-incubation with red blood cells was extremely low. Furthermore, the 99mTc-radiolabeled IONs showed good stability in human serum, DTPA, and histidine, and high specific binding rates in cancer cells, supporting their future utilization as potential diagnostic tools for PCa with Single Photon Emission Computed Tomography (SPECT) imaging. [ABSTRACT FROM AUTHOR]

Background and Purpose Experimental Approach Key Results Conclusion and Implications Drug repurposing (DR) offers a compelling alternative to traditional drug discovery's lengthy, resource‐intensive process. DR is the process of identifying alternative clinical applications for pre‐approved drugs as a low‐risk and low‐cost strategy. Computational approaches are crucial during the early hypothesis‐generating stage of DR. However, ‘large‐scale’ data retrieval remains a significant challenge. A computational workflow addressing such limitations might improve hypothesis generation, ultimately benefit patients and advance DR research.We introduce a novel computational workflow (combining free‐accessible computational platforms) to provide ‘proof‐of‐concept’ of the pre‐approved drug's suitability for repurposing. Three key phases are included: target fishing (via reverse pharmacophore mapping), target identification (via disease‐ and drug‐target pathway identification) and retrospective literature and drug‐like analysis (via in silico ADMET properties determination). Istradefylline is a Parkinson's disease‐approved drug with literature‐attributed antidepressant properties remaining unclear. Practically applied, istradefylline's antidepressant activity was assessed in the context of major depressive disorder (MDD).Data mining aided by target identification resulted in istradefylline potentially representing a novel antidepressant drug class. Retrieved drug targets (KYNU, MAO‐B, ALOX12 and PLCB2) associated with selected MDD pathways (tryptophan metabolism and serotonergic synapse) generated a hypothesis that istradefylline increased extracellular 5‐HT levels (MAO‐B inhibition) and reduced inflammation (KYNU, ALOX12 and PLCB2 inhibition).The practically applied workflow's generated hypothesis aligns with known experimental data, validating the effectiveness of this novel computational workflow. It is a low‐risk and low‐cost DR computational tool providing a bird's‐eye view for exploring alternative clinical applications of pre‐approved drugs. [ABSTRACT FROM AUTHOR]

A general phase‐transfer catalyst (PTC) mediated enantioselective alkylation of N‐acylsulfenamides is reported. Essential to achieving high selectivity was the use of the triethylacetyl sulfenamide protecting group along with aqueous KOH as the base under biphasic aqueous conditions to enable the reaction to be performed at −40 °C. With these key parameters, enantiomeric ratios up to 97.5 : 2.5 at the newly generated chiral sulfur center were achieved with an inexpensive cinchona alkaloid derived PTC. Broad scope and excellent functional group compatibility was observed for a variety of S‐(hetero)aryl and branched and unbranched S‐alkyl sulfenamides. Moreover, to achieve high selectivity for the opposite enantiomer, a pseudoenantiomeric catalyst was designed and synthesized from inexpensive cinchonidine. Given that sulfoximines are a bioactive pharmacophore of ever‐increasing interest, selected product sulfilimines were oxidized to the corresponding sulfoximines with subsequent reductive cleavage affording the free‐NH sulfoximines in high yields. The utility of the disclosed method was further demonstrated by the efficient asymmetric synthesis of atuveciclib, a phase I clinical candidate for which only chiral HPLC separation had previously been reported for isolation of the desired (R)‐sulfoximine stereoisomer. [ABSTRACT FROM AUTHOR]

The medicinal importance, natural rarity, and challenges associated with the synthesis of C3-functionalized 1 H -indazoles have propelled the development of novel and practical 1 H -indazole N-oxides for the production of diverse arrays of C3-functionalized 1 H -indazoles. The use of 1 H -indazole N-oxides has been remarkably effective for the selective introduction of diverse functional groups, including amino (NHAr), chloro (Cl), hydroxy (OH), sulfonyl (SO2 Ar), aromatic (Ar), olefin, alkyl, and N-formyl (NRCHO) groups, to indazole pharmacophore molecules. This review offers a concise overview of the synthetic approaches and practical applications of 1 H -indazole N-oxides, including recent studies conducted by the authors. Transformative reactions involving 1 H -indazole N-oxides not only offer strategies for synthesizing C3-functionalized 1 H -indazoles but also hold significant potential in medicinal chemistry. 1 Introduction 2 Synthetic Approaches and Applications of 1 H -Indazole N -Oxides 3 Summary and Outlook [ABSTRACT FROM AUTHOR]

In the present work, we performed a computational study on hydroxamic acid containing compounds as acid sphingomyelinase (ASM) inhibitors. The study starts from the development of 3D‐QSAR and pharmacophore models, which were further taken as a source for the enumeration and virtual screening study. The 3D‐QSAR results showed the best statistical model with Q2, R2, and R2 scrambling values of 0.7175, 0.9019, and 0.7128, respectively. The pharmacophore hypothesis generated one of the best hypotheses including five features such as 2 aromatic rings, 2 hydrogen bond donors, and 1 hydrogen bond acceptor. The enumeration study paved the path in the discovery of novel compounds where pharmacophore hypothesis and 3D QSAR study data was used for the identification of novel compounds. Compound 9f_20 showed good docking score −11.399 and binding interactions with amino acids HIP317, ASN316, GLH386, Zn701, Zn702, HIP317, and HIP280 required for ASM inhibitory activity. The virtual screening study was performed on the basis of developed pharmacophore ADDRR_1 where ZINC000013941849 showed good binding interactions with receptor including amino acids Zn701, Zn702, HIP280, LYS103, HIP317, ASN316, and ILE487. ZINC000013941849 with docking score −13.101. The screened compounds may be taken for the further development of novel antidepressant agents. [ABSTRACT FROM AUTHOR]

Perry disease (PeD) is a rare, neurodegenerative, genetic disorder inherited in an autosomal dominant manner. The disease manifests as parkinsonism, with psychiatric symptoms on top, such as depression or sleep disorders, accompanied by unexpected weight loss, central hypoventilation, and aggregation of DNA-binding protein (TDP-43) in the brain. Due to the genetic cause, no causal treatment for PeD is currently available. The only way to improve the quality of life of patients is through symptomatic therapy. This work aims to review the latest data on potential PeD treatment, specifically from the medicinal chemistry and computer-aided drug design (CADD) points of view. We select proteins that might represent therapeutic targets for symptomatic treatment of the disease: monoamine oxidase B (MAO-B), serotonin transporter (SERT), dopamine D2 (D2R), and serotonin 5-HT1A (5-HT1AR) receptors. We report on compounds that may be potential hits to develop symptomatic therapies for PeD and related neurodegenerative diseases and relieve its symptoms. We use Phase pharmacophore modeling software (version 2023.08) implemented in Schrödinger Maestro as a ligand selection tool. For each of the chosen targets, based on the resolved protein–ligand structures deposited in the Protein Data Bank (PDB) database, pharmacophore models are proposed. We review novel, active compounds that might serve as either hits for further optimization or candidates for further phases of studies, leading to potential use in the treatment of PeD. [ABSTRACT FROM AUTHOR]

Gprotein-coupled receptors (GPCRs) regulate several physiological and pathological processes and represent the target of approximately 30% of Food and Drug Administration-approved drugs. GPCR-mediated signaling was thought to occur exclusively at the plasma membrane. However, recent studies have unveiled their presence and function at subcellular membrane compartments. There is a growing interest in studying compartmentalized signaling of GPCRs. This requires development of tools to separate GPCR signaling at the plasma membrane from the ones initiated at intracellular compartments. We leveraged the structural and pharmacological information available for β-adrenergic receptors (βARs) and focused on β1AR as exemplary GPCR that functions at subcellular compartments, and rationally designed spatially restricted antagonists. We generated a cell-impermeable βAR antagonist by conjugating a suitable pharmacophore to a sulfonate-containing fluorophore. This cell-impermeable antagonist only inhibited β1AR on the plasma membrane. In contrast, a cell-permeable βAR antagonist containing a nonsulfonated fluorophore efficiently inhibited both the plasma membrane and Golgi pools of β1ARs. Furthermore, the cell-impermeable antagonist selectively inhibited the phosphorylation of PKA downstream effectors near the plasma membrane, which regulate sarcoplasmic reticulum (SR) Ca2+ release in adult cardiomyocytes, while the β1AR Golgi pool remained active. Our tools offer promising avenues for investigating compartmentalized βAR signaling in various contexts, potentially advancing our understanding of βAR-mediated cellular responses in health and disease. They also offer a general strategy to study compartmentalized signaling for other GPCRs in various biological systems. [ABSTRACT FROM AUTHOR]

ABSTRACT The study examines the binding affinities and pharmacological potential of synthesized metal compounds with PfNDH2 in Plasmodium falciparum. So as to identify the combatting agent for malaria, six new organotellurium (IV) complexes (8a–8f) were prepared through a condensation reaction of 3‐methyl‐2‐thiophene carboxaldehyde and p‐nitroaniline. The synthesized compounds were inclusively characterized through physical and spectral techniques signifying a distorted octahedral geometry. The reported complexes were screened for antimalarial and antioxidant activities and analyzed using micro assays and DPPH assays, respectively. Using docking interactions, the research evaluates the binding energies, hydrogen bonds, and steric interactions of various compounds with PfNDH2, aiming to identify promising candidates for antimalarial drug development. Among the compounds, 8f showed the strongest binding affinity, with the lowest binding energy of −135.626 kcal/mol, and diverse hydrogen bonds with the target enzyme. Structure‐based pharmacophore modeling revealed critical interaction profiles and selectivity scores for the compounds, with 8f emerging as a promising candidate. Molecular electrostatic potential (MESP) analysis offered insights into the distribution of electron density within the compounds, influencing their reactivity and potential as antimalarial agents. ADMET analysis highlighted the pharmacokinetic and toxicological profiles of the compounds, revealing critical aspects for optimizing safety and efficacy. Overall, the findings provide valuable information for further development and optimization of potential antimalarial drugs. [ABSTRACT FROM AUTHOR]

Ubiquitin-specific protease-7 (USP7) is a potential target for cancer therapy. In this work, the evaluation and design of USP7 inhibitors are conducted employing a comprehensive computational approach. Initially, a large database of compounds undergoes preliminary screening via similarity and pharmacophore analyses. Subsequently, a secondary selection process is executed based on both quantitative structure–activity relationship modeling and molecular docking. The final selection is refined through rescoring treatments via consensus scores and MM/GBSA binding free energy. A total of 138 experimental USP7 inhibitors were collected for the construction of random forest regression models using four different feature selection methods. 17 top experimentally active inhibitors were used as models in similarity searching, and eight representative USP7-ligand binding models were used in pharmacophore screening, performed over a database of 14 million compounds. The rescoring approach applied in this study offers an alternative and beneficial method for the ranking and selection of desired molecules. Based on the molecular scaffolds of the highly active inhibitors, some new derivatives have been designed and received high predicted scores for inhibition. The inhibitors against USP7 were evaluated using an integrated approach including QSAR, pharmacophore, molecular docking, and binding free energy calculations. Random Forests regression models were well built via several methods of feature selection. The rescoring treatment can be used as a helpful strategy for virtual database screening in drug design. [ABSTRACT FROM AUTHOR]

Medicinal plants are enriched sources of drugs due to their chemically and functionally diverse secondary metabolites. Conventional methods of screening these bioactive metabolites require a long time, incur high costs, utilize substantial amounts of solvents, involve repeated exposure to heat (harmful for the thermo-labile compounds), and often lead to undesirable products. However, computer-aided drug discovery (CADD) has emerged as a versatile and cost-effective tool for expediting the screening of plant-based bioactive compounds. In this review, we focus on structure-based and ligand-based drug discovery approaches and their roles in rationalizing drug development. We discuss the technicalities, limitations, and successful applications of key components of structure-based (molecular docking and molecular dynamics) and ligand-based (quantitative structure–activity relationship and pharmacophore modeling) approaches in medicinal plant-derived drug discovery. Furthermore, our study highlights the significance of the pharmacokinetic and ADMET profiling of plant-based therapeutics in drug development. Besides the applications of computational drug discovery, we also briefly overview the corroborative in-silico and experimental approaches to identify potential therapeutics from medicinal plants. This study suggests that integrating advanced Machine Learning and Artificial Intelligence approaches could alleviate the challenges faced by traditional computational techniques, thus enriching the screening process. [Display omitted] • The screening of therapeutic phytochemicals remains challenging. • Computational approaches can expedite drug discovery from medicinal plants. • Structure- and ligand-based modeling are vital pillars of in-silico drug discovery. • Early-stage ADME-Tox analysis of phytocompounds aids the discovery of potent drug. • Combined in-silico and in-vitro studies can validate the drug discovery results. [ABSTRACT FROM AUTHOR]

Background: Type-2 Diabetes (T2DM) is a long-term medical disorder characterized by Insulin deficiency and high blood glucose levels. Among other medications to cure T2DM, the review of the literature found that various Pyrimidine derivatives act as an agonist for G-protein-coupled receptor 119 (GPR119) was proposed to control blood glucose levels by enhancing the function of pancreatic Beta-cells and its mechanism of action with fewer adverse effects. In the present research work, In-silico investigations were carried out to investigate the potential of the Pyrimidine analog as an agonist to the protein target GPR119 receptor. We performed exhaustive molecular modeling and protein modeling methodologies such as homology modeling, and molecular docking along with various drug designing tools such as 3D-QSAR and Pharmacophore Mapping to ascertain the design of better GPR119 agonists. Results: Based on in-depth computational studies, we designed new pyrimidine moiety and analyzed them for GPR119 receptor agonist and further explored the ADMET properties. Designed compounds were found to exhibit better-predicted activities as compared to reference compound. Conclusions: The current research on pyrimidine derivatives, using molecular docking, 3D-QSAR and Pharmacophore mapping demonstrated that the obtained computational model has significant properties and the designed molecules and Dataset from this model, produced antidiabetic compound against the target GPR119 i.e., compound 1S, 1Z and 1D with the docking score of − 11.696, − 9.314 and − 8.721, respectively. The pharmacokinetics and drug-likeness studies revealed that these compounds may be the future candidates for the treatment of diabetes acting via the GPR119 agonist mechanism. [ABSTRACT FROM AUTHOR]

Background: Overexpression of monopolar spindle 1 (MPS1) and histone deacetylase 8 (HDAC8) is associated with the proliferation of liver cancer cells, so simultaneous inhibition of both MPS1 and HDAC8 could offer a promising therapeutic approach for the treatment of liver cancer. Dual-targeted MPS1/ HDAC8 inhibitors have not been reported. Methods: A combined approach of pharmacophore modeling and molecular docking was used to identify potent dual-target inhibitors of MPS1 and HDAC8. Enzyme inhibition assays were performed to evaluate the optimal compound with the strongest inhibitory activity against MPS1 and HDAC8. The selectivity of MPH-5 for MPS1 and HDAC8 was assessed on a panel of 68 kinases and other histone deacetylases. Subsequently,molecular dynamics (MD) simulation verified the binding stability of the optimal compound to MPS1 and HDAC8. Ultimately, in vitro cellular assays and in vivo antitumor assays evaluated the antitumor efficacy of the most promising compound for the treatment of hepatocellular carcinoma. Results: Six dual-target compounds (MPHs 1--6) of both MPS1 and HDAC8 were identified from the database using a combined virtual screening protocol. Notably, MPH-5 showed nanomolar inhibitory effect on both MPS1 (IC50 = 4.52 ± 0.21 nM) and HDAC8 (IC50 = 6.07 ± 0.37 nM). MD simulation indicated that MPH-5 stably binds to both MPS1 and HDAC8. Importantly, cellular assays revealed that MPH-5 exhibited significant antiproliferative activity against human liver cancer cells, especially HepG2 cells. Moreover, MPH-5 exhibited low toxicity and high efficacy against tumor cells, and it overcomes drug resistance to some extent. In addition, MPH-5 may exert its antitumor effects by downregulating MPS1-driven phosphorylation of histone H3 and upregulating HDAC8-mediated K62 acetylation of PKM2. Furthermore, MPH-5 showed potent inhibition of HepG2 xenograft tumor growth in mice with no apparent toxicity and presented favorable pharmacokinetics. Conclusion: The study suggests that MPH-5 is a potent, selective, high-efficacy, and low-toxicity antitumor candidate for the treatment of hepatocellular carcinoma. [ABSTRACT FROM AUTHOR]

ABSTRACT Benzothiazole alkaloids are a class of rare heterocyclic alkaloids with unique structures and exhibit a wide range of biological activities. So, the aim of this work is to investigate structural diversity‐guided N‐S heterocyclic derivatives based on natural benzothiazole alkaloids as potential cytotoxic agents. Three series of novel benzothiazole derivatives, including 22 compounds, were designed and synthesized using pharmacophore hybridization, and their in vitro cytotoxic activities against Huh‐7 and A875 were fully evaluated. The results indicated that some of these benzothiazole derivatives had significantly good cytotoxic activities against two tested cell lines compared with the positive control 5‐fluorouracil, and other compounds 3f–3i displayed good selectivity between A875 and Huh‐7 cell lines, which might be used as promising lead molecule for discovery of novel benzothiazole‐type cytotoxic agents. [ABSTRACT FROM AUTHOR]

ABSTRACT A rapid and efficient protocol for synthesizing two series of benzofuran‐based hybrid polyheterocycles is presented: benzofuran‐isatin and benzofuran N‐acylhydrazones, and evaluation of their antibacterial activity both in vitro and in silico against two strains of Pseudomonas aeruginosa, PAO1 and PA14 were determined. Six of the tested compounds were shown to be active against the hypervirulent strain PA14. Docking studies were conducted using RNA polymerase sigmaS protein for P. aeruginosa PAO1 and PqsE protein for P. aeruginosa PA14 to provide additional insights into these results. A pharmacophore model was computed to suggest potential structural derivatives on the target molecules, offering further insights for future research. Finally, 40 novel compounds, including intermediates, were synthesized in a three‐step reaction. [ABSTRACT FROM AUTHOR]

Objective: Biological studies have elucidated that phosphoglycerate dehydrogenase (PHGDH) is the rate-limiting enzyme in the serine synthesis pathway in humans that is abnormally expressed in numerous cancers. Inhibition of the PHGDH activity is thought to be an attractive approach for novel anti-cancer therapy. The development of structurally diverse novel PHGDH inhibitors with high efficiency and low toxicity is a promising drug discovery strategy. Methods: A ligand-based 3D-QSAR pharmacophore model was developed using the HypoGen algorithm methodology of Discovery Studio. The selected pharmacophore model was further validated by test set validation, cost analysis, and Fischer randomization validation and was then used as a 3D query to screen compound libraries with various chemical scaffolds. The estimated activity, druglikeness, molecular docking, growing scaffold, and molecular dynamics simulation processes were applied in combination to reduce the number of virtual hits. Results: The potential candidates against PHGDH were screened based on estimated activity, docking scores, predictive absorption, distribution, metabolism, excretion, and toxicity (ADME/T) properties, and molecular dynamics simulation. Conclusion: Finally, an all-in-one combination was employed successfully to design and develop three potential anti-cancer candidates. [ABSTRACT FROM AUTHOR]

Introduction: The ability of transgenic plants to respond to sudden environmental pollution accidents has become viable. Nonetheless, there is a dearth of research regarding the mechanism by which transgenic plants degrade organic pollutants. Hence, this study aimed to elucidate the process of organic pollutant degradation by plants, offering theoretical support for the application of transgenic plant emergency phytoremediation technology. Methods: In this investigation, we developed a 3D-QSAR pharmacophore model to represent the collective impact of plant resistance and phytodegradation. This was achieved by employing integrated effect values following treatment with a sine function approach. Moreover, we have undertaken an inaugural exploration of the coregulatory mechanism involved in plant resistance and pollutant degradation within plants. Additionally, we applied virtual molecular modification techniques for analysis and validation, striving for a more indepth understanding of the molecular-level enhancement mechanism related to the degradation of pollutants within plant organisms. Results and discussion: The mechanism analysis results of the Hypo 1 pharmacophore model were verified, indicating that hydrophobic characteristics affect the resistance and degradation of PCBs in plants, significantly affecting the degradation effect of pollutants in plants. [ABSTRACT FROM AUTHOR]

Cyclin-dependent kinase 2 (CDK2) has been recognized as one of the crucial factors in cell cycle regulation and has been proposed as a potential target for cancer therapies, particularly for colorectal cancer (CRC). Due to the increased incidence rate of CRC and challenges associated with existing treatment options, there is a need for efficient and selective anti-cancer compounds. The current work aims to explore the ability of novel kaempferol derivatives as CDK2 inhibitors by performing conceptual pharmacophore modeling, molecular docking, and molecular dynamic analysis. Kaempferol and its derivatives were obtained from PubChem, and the optimized 3D structures of the compounds were generated using Maestro Ligprep. Subsequently, a pharmacophore model was developed to identify compounds with high fitness values, resulting in the selection of several kaempferol derivatives for further study. We evaluated the ADMET properties of these compounds to assess their therapeutic potential. Molecular docking was conducted using Maestro and BIOVIA Discovery Studio version 4.0 to predict the binding affinities of the compounds to CDK2. The top candidates were subjected to MM-GBSA analysis to predict their binding free energies. Molecular dynamics simulations using GROMACS were performed to assess the thermodynamic stability of the ligand-protein complexes. The results revealed several kaempferol derivatives with high predicted binding affinities to CDK2 and favorable ADMET properties. Specifically, compounds 5281642, 5318980, and 14427423 demonstrated binding free energies of-30.26, -38.66, and -34.2 kcal/mol, respectively. Molecular dynamics simulations indicated that these ligand-protein complexes remained stable throughout the simulation period, with RMSD values remaining below 2 Ä. In conclusion, the identified kaempferol derivatives show potential as CDK2 inhibitors based on computational predictions and demonstrate stability in molecular dynamics simulations, suggesting their future application in CRC treatment by targeting CDK2. These computational findings encourage further experimental validation and development of kaempferol derivatives as anti-cancer agents. [ABSTRACT FROM AUTHOR]

Anaplastic Lymphoma Kinase (ALK) is a receptor tyrosine kinase within the insulin receptor superfamily. Alterations in ALK, such as rearrangements, mutations, or amplifications, have been detected in various tumours, including lymphoma, neuroblastoma, and non-small cell lung cancer. In this study, we outline a computational workflow designed to uncover new inhibitors of ALK. This process starts with a ligand-based exploration of the pharmacophoric space using 13 diverse sets of ALK inhibitors. Subsequently, quantitative structure-activity relationship (QSAR) modelling is employed in combination with a genetic function algorithm to identify the optimal combination of pharmacophores and molecular descriptors capable of elucidating variations in anti-ALK bioactivities within a compiled list of inhibitors. The successful QSAR model revealed three pharmacophores, two of which share three similar features, prompting their merger into a single pharmacophore model. The merged pharmacophore was used as a 3D search query to mine the National Cancer Institute (NCI) database for novel anti-ALK leads. Subsequent in vitro bioassay of the top 40 hits identified two compounds with low micromolar IC50 values. Remarkably, one of the identified leads possesses a novel chemotype compared to known ALK inhibitors. [ABSTRACT FROM AUTHOR]

Targeting epidermal growth factor receptor (EGFR) mutants is a promising strategy for treating non-small cell lung cancer (NSCLC). This study focused on the computational identification and characterization of potential EGFR mutant-selective inhibitors using pharmacophore design and validation by deep learning, virtual screening, ADMET (Absorption, distribution, metabolism, excretion and toxicity), and molecular docking-dynamics simulations. A pharmacophore model was generated using Pharmit based on the potent inhibitor JBJ-125, which targets the mutant EGFR (PDB 5D41) and is used for the virtual screening of the Zinc database. In total, 16 hits were retrieved from 13,127,550 molecules and 122,276,899 conformers. The pharmacophore model was validated via DeepCoy, generating 100 inactive decoy structures for each active molecule and ADMET tests were conducted using SWISS ADME and PROTOX 3.0. Filtered compounds underwent molecular docking studies using Glide, revealing promising interactions with the EGFR allosteric site along with better docking scores. Molecular dynamics (MD) simulations confirmed the stability of the docked conformations. These results bring out five novel compounds that can be evaluated as single agents or in combination with existing therapies, holding promise for treating the EGFR-mutant NSCLC. [ABSTRACT FROM AUTHOR]

The aim of this work was to obtain and evaluate, as antiprotozoals, new derivatives of benzoate imidazo-1,3,4-thiadiazole 18–23 based on the concepts of molecular repositioning and hybridization. In the design of these compounds, two important pharmacophoric subunits of the fexnidazole prototype were used: metronidazole was used as a repositioning molecule, p-aminobenzoic acid was incorporated as a bridge group, and 1,3,4-thiadiazole group was incorporated as a second pharmacophore, which at position 5 has an aromatic group with different substituents incorporated. The final six compounds were obtained through a five-step linear route with moderate to good yields. The biological results demonstrated the potential of this new class of compounds, since three of them 19–21 showed inhibitory activity on proliferation, in the order of 50%, in the in vitro assay against epimastigotes of T. cruzi (Strain Y sensitive to nifurtimox and benznidazole) and promastigotes of L. donovani, at a single concentration of 50 μM. [ABSTRACT FROM AUTHOR]

A 3D structure-based pharmacophore model built for bromodomain-containing protein 4 (BRD4) is reported here, specifically developed for investigating and identifying the key structural features of the (+)-JQ1 known inhibitor within the BRD4 binding site. Using this pharmacophore model, 273 synthesized and purchased compounds previously considered for other targets but yielding poor results were screened in a drug repositioning campaign. Subsequently, only six compounds showed potential as BRD4 binders and were subjected to further biophysical and biochemical assays. Compounds 2, 5, and 6 showed high affinity for BRD4, with IC50 values of 0.60 ± 0.25 µM, 3.46 ± 1.22 µM, and 4.66 ± 0.52 µM, respectively. Additionally, these compounds were tested against two other bromodomains, BRD3 and BRD9, and two of them showed high selectivity for BRD4. The reported 3D structure-based pharmacophore model proves to be a straightforward and useful tool for selecting novel BRD4 ligands. [ABSTRACT FROM AUTHOR]

Isatin, a versatile heterocyclic compound, has emerged as a key player in synthetic and pharmaceutical chemistry due to its diverse pharmacological properties. Originally synthesized in 1841, isatin has been found in various natural sources and serves as a crucial pharmacophore for the development of synthetic compounds. This review provides a comprehensive overview of the anti-infective properties of isatin, covering its synthesis methods, structural characteristics, reactivity, and diverse biological activities. Synthesis methods such as the Sandmeyer, Stolle, Martinet, and Gassman approaches are discussed, highlighting their importance in accessing isatin derivatives. Structural characteristics, including tautomerization and spectral studies, are elucidated to provide insights into the compound's behavior. The reactivity of isatin at key sites influences its biological activity and synthetic versatility, underscoring its significance in medicinal chemistry research. Moreover, isatin exhibits promising antibacterial, antiviral, and antiparasitic activities, making it a potential candidate for the development of novel anti-infective agents. Through a thorough exploration of isatin's multifaceted properties, this review aims to contribute to the development of innovative strategies for infectious disease management. [ABSTRACT FROM AUTHOR]

Hemisynthesis makes it possible to improve the activity or reduce the toxicity of a biocompound by modifying or adding peripheral groups. Catechin present in different plant species was known for its moderate anti-malarial and anti-SARS-CoV-2 activities. The aim of this work was focused on the identification of new compounds with potential anti-SARS-CoV-2 and/or anti-malarial activities, evaluated through In silico simulation. A polyphenol pharmacophore model, based on (+)-catechin (1) was virtually constructed using previously reported inhibitors. N- and/or S-heterocyclic fragments were inserted on the backbone of (+)-catechin and 12 pharmacophore hypotheses were studied. This study targeted 3 proteins biologically responsible for SARS-CoV-2 (PDB ID: 7JYC, 6M0J, and 6HZD) and one protein responsible for malaria (PDB ID: 3SRJ). Molecular docking had shown that the new catechin-aldehyde candidates have good Ligand-Protein affinity in terms of free energy compared to the study reference Narlaprevir and Artesunate for SARS-CoV-2 and malaria respectively. Theoretically, most compounds didn't show toxicity except compounds 2a, 2i, and 2k, exhibiting hepatotoxic activity. Molecular dynamics was used to prove and assess their binding stability to the target protein for each activity. The 3SRJ-2f and 6HZD-2l structures were selected for anti-malarial and anti-SARS-CoV-2 activity respectively. The 3SRJ-2f and 6HZD-2l complexes showed stable interactions to 100 ns between the inhibitor fragments and the residual amino acids of the protein. To conclude, these novel compounds are probably to become promising lead molecules for the development of effective anti-SARS-CoV-2 and/or anti-malarial of all drugs. [ABSTRACT FROM AUTHOR]

The article is devoted to the polypharmacological profiling of 4-((5-(decylthio)-4-methyl4H-1,2,4-triazole-3-yl)methyl)morpholine, which has potential as an antimicrobial agent. The study was conducted using 15,148 electronic pharmacophore models of organisms, ranked according to the Tversky index. A detailed analysis of the compound’s interactions with selected enzymes showed that 4-((5-(decylthio)-4-methyl-4H-1,2,4-triazole-3- yl)methyl)morpholine forms classical types of bonds with chosen biotargets. The key amino acid residues involved in the formation of complexes were also identified. Based on the binding profiles observed for selected complexes with the active centers of thymidine kinase (4IVR), phosphate synthase (1G6C), and biotin carboxylase (2W6O), it can be concluded that this bioactive ligand is likely to exhibit antibacterial and antiviral effects by inhibiting molecular and biological processes in pathogenic organisms. The chosen targets had acceptable binding modes with 4-((5-(decylthio)-4-methyl-4H-1,2,4-triazole3-yl)methyl)morpholine, did not form unwanted contacts, and interacted with some critically important amino acid residues. This suggests the potential for further use in virtual screening, computer modeling, and more in-depth in vitro and in vivo studies. The results of the multitarget analysis could contribute to the development of new antimicrobial drugs effective against various types of infectious agents. [ABSTRACT FROM AUTHOR]

Breast cancer is one of the most problematic diseases in the world. Currently, there are no potential vaccines for the treatment of this disease. Therefore, finding effective compounds, such as curcumin analogs, is crucial to inhibit breast cancer. Forty-five synthesized curcumin analogs were tested on the MCF7 cell line using the MTT assay. It was shown that nine curcumin compounds, Cpd 5, Cpd 9, Cpd 17, Cpd 18, Cpd 21, Cpd 25, Cpd 28, Cpd 32, and Cpd 45, had better inhibitory activities against breast cancer. Furthermore, in silico analysis was developed using 2D and 3D QSAR models with high predictive ability, with an r2 value of 0.834. In addition, based on molecular docking, molecular dynamics, and pharmacophore results, it was shown that these nine compounds had the lowest binding free energy and were also stable during the simulation. The presence of methoxy groups, hydrogen bond donors, and aromatic ring features are the main factors that enhance the biological activity of curcumin analogs. Therefore, these compounds could serve as references for the next stage of drug design.

In the quest to combat tuberculosis, DprE1, a challenging target for novel anti-tubercular agents due to its small size and membrane location, has been a focus of research. DprE1 catalyzes the transformation of DPR into Ketoribose DPX, with Benzothiazinone emerging as a potent pharmacophore for inhibiting DprE1. Clinical trial drugs such as BTZ043, BTZ038, PBTZ169, and TMC-207 have shown promising results as DprE1 inhibitors. This study employed pharmacophore mapping of Pyrazolopyridine, Dinitrobenzamide, and Benzothiazinone derivatives to identify crucial features for eliciting a biological response. Benzothiazinone (Ligand code: 73) emerged as a reference ligand with a fitness score of 3.000. ROC analysis validated the pharmacophore with an excellent score of 0.71. To build a 3D QSAR model, a series of Benzothiazinone congeneric derivatives were explored. The model exhibited strong performance, with a standard deviation of 0.1531, a correlation coefficient for the training set (R2) value of 0.9754, and a correlation coefficient for test set Q2 value of 0.7632, indicating robust predictive capabilities. Contour maps guided the design of novel benzothiazinone derivatives, emphasizing steric, electrostatic, hydrophobic, H-bond acceptor, and H-bond donor groups for structure-activity relationships. Docking studies against PDB ID: 4NCR demonstrated favorable scores, with interactions aligning well with the in-built ligand 26 J. Docking validation via RMSD values supported the reliability of the docking results. This comprehensive approach aids in the design of novel benzothiazinone derivatives with potential anti-tubercular properties, contributing to the development of novel anti-tubercular agents which can be pivotal in the eradication of tuberculosis. [ABSTRACT FROM AUTHOR]

ABSTRACT Breast cancer, a formidable threat to women's health, mainly manifests in the HER2 subtype, affecting approximately one in five women. Thus, this study endeavors to pioneer novel approaches by exploring the efficacy of benzothiazole‐coupled azetidinone derivatives against EGFR. We aimed to elucidate their potential by employing a comprehensive array of in silico methodologies, including molecular docking, pharmacokinetics profiling, pharmacophore mapping, molecular dynamic simulations, and MMPBSA analysis. Remarkably, our results demonstrate that our designed molecules adhere to Lipinski's rule and comply with essential physiochemical and druggable properties, affirming the promise of these compounds. Ligand MS60 emerges as a lead, showcasing the most substantial interaction with the EGFR receptor, underscored by its impressive docking score of −8.199 kcal/mol. Furthermore, molecular dynamics simulations conducted via GROMACS corroborate the stability of the MS60‐EGFR complex, portraying minimal fluctuations. This assertion is further validated through MMPBSA, PCA analysis, DCCM, and FEL studies, underscoring the robustness of our findings. We have designed the pharmacophore model to unravel critical steric and electronic attributes essential for effective supramolecular interactions with the EGFR receptor. Notably, the presence of the R10, R11, and A4 groups within the ligands underscores their pivotal role in eliciting pharmacological activity, offering valuable insights for further exploration and development. [ABSTRACT FROM AUTHOR]

A new series of imidazole linked 1,3,4‐oxadizoles were designed and synthesized from 2‐butyl‐4‐chloro‐1H‐imidazole‐5‐carbaldehyde (1) as a starting material. The synthesized compounds were characterized by well–known spectroscopic techniques, i. e., IR, 1H NMR, 13C NMR, and mass spectrometry. Against Gram–positive bacteria S. aureus, compounds 8 e, 8 i, and 8 k showed the highest antibacterial activity with diameter zone values 25±0.44, 25±0.65, 22±0.91 mm respectively. Compounds 8 e, 8 g, and 8 i are active against Gram–negative bacteria E. coli with ZI of 26±0.58, 21±0.51, 26±0.71 mm. Interestingly, the molecules 8 a, and 8 h were more selective towards antifungal activity against F. oxysporum (ZI=21±0.11, 21±0.51 mm), compared to clotrimazole (19±0.13 mm). The docking study results of compound 8 d formed highly stable H‐bonding with Asp‐89, Asn‐145, Val‐88, Arg‐144 amino acids, which are plays a crucial role in ensuring efficient binding of the ligand in a crystal structure of S. aureus mutated in GyrB ATPase domain (PDB: 3U2K). The study of computer aided ADMET was also carried out, using SwissADME, ADMETlab2.0 to investigate the pharmacokinetic properties of the tested triazole compounds. [ABSTRACT FROM AUTHOR]

the current investigation, 109 known ERα inhibitors have been developed in the current research; pharmacophore modeling, Molecular docking, MM‐GBSA, and MD study have been performed to investigate the binding affinity of 9‐anilinoacridines with heterocyclic substitutes as selective ERα inhibitors for breast carcinoma. Pharmacophore model have been developed by Schrodinger suite 2019–2 phasemodule. To predict binding free energy of the ligands in complex with PDB and post docked energy minimization was performed by Prime, MM‐GB/SA module. The Induced fit docking studies were performed on the ligand modulated dynamic behaviour of the protein molecular dynamics study. A statistical substantial 3D ‐ QSAR design was created using the pharmacophore hypothesis. 109 known ERα inhibitors have been developed with pIC50 values between 4.0 and 6.0 and were used in ligand‐based pharmacophore modelling and 3D‐QSAR analysis. R2 (0.8294), Q2 (0.7~0.8), and F value (83.5) were used to statistically validate the developed five‐point hypothesis DHRRR1 employing a minimum square of four. Molecular dynamics simulations were run to comprehend the conformational changes and ligand stability at the protein active pocket. The predicted 3D‐QSAR model significantly correlated with experimentally reported in‐vitro antitumor activity. These in‐silico discoveries will help in the future search for potent ERα inhibitors with desirable pharmacophoric properties. [ABSTRACT FROM AUTHOR]

Bovine mastitis is a worldwide disease affecting dairy cattle and causes major economic losses in the dairy industry. Recently, the emergence of microbial resistance to the current antibiotics complicates the treatment protocol which necessitates antibiotic stewardship and further research to find new active compounds. Recently, phytobiotics have gained interest in being used as an alternative to antibiotics in the poultry industry as an antibiotic stewardship intervention. This study evaluated the in vitro antibacterial activity of 16 flavonoids against bovine mastitis pathogens. Two flavones: 2-(4-methoxyphenyl)chromen-4-one (1) and 2-(3-hydroxyphenyl)chromen-4-one (4) showed inhibition of the growth of Klebsiella oxytoca with MIC values range (25–50 µg mL− 1) followed by a structure-activity relationship (SAR) study indicating that the presence of a hydroxyl group at C-3' or methoxy at C-4' increases the activity against Klebsiella oxytoca while the presence of hydroxyl group at C-7 decreases the activity. Furthermore, a structure-based drug development approach was applied using several in silico tools to understand the interactions of active flavones at the active site of the DNA gyrase protein. Compound (4) showed a higher docking score than quercetin (standard) which is known to have antibacterial activity by inhibiting the DNA gyrase. In addition, the structure-based pharmacophores of compound (4) and quercetin showed similar pharmacophoric features and interactions with DNA gyrase. Based on our findings, compounds (1) and (4) are promising for further study as potential anti-microbial phytochemicals that can have a role in controlling bovine mastitis as well as to investigate their mechanism of action further. [ABSTRACT FROM AUTHOR]

Drug repositioning is an important therapeutic strategy for treating breast cancer. Hsp90β chaperone is an attractive target for inhibiting cell progression. Its structure has a disordered and flexible linker region between the N-terminal and central domains. Geldanamycin was the first Hsp90β inhibitor to interact specifically at the N-terminal site. Owing to the toxicity of geldanamycin, we investigated the repositioning of ritonavir as an Hsp90β inhibitor, taking advantage of its proven efficacy against cancer. In this study, we used molecular modeling techniques to analyze the contribution of the Hsp90β linker region to the flexibility and interaction between the ligands geldanamycin, ritonavir, and Hsp90β. Our findings indicate that the linker region is responsible for the fluctuation and overall protein motion without disturbing the interaction between the inhibitors and the N-terminus. We also found that ritonavir established similar interactions with the substrate ATP triphosphate, filling the same pharmacophore zone. [ABSTRACT FROM AUTHOR]

In this work, we report the identification of novel bromodomain‐containing protein 9 (BRD9) binders through a virtual screening based on our developed 3D structure‐based pharmacophore model. The in silico workflow here described led to the identification of a promising initial hit (1) featuring the 1‐ethyl‐1H‐pyrazolo[3,4‐b]pyridine motif which represented an unexplored chemotype for the development of a new class of BRD9 ligands. The encouraging biophysical results achieved for compound 1 prompted us to explore further tailored structural modification around the C‐4 and C‐6 positions of the central core. Hence, the design and synthesis of a set of 19 derivatives (2–20) were performed to extensively investigate the chemical space of BRD9 binding site. Among them, four compounds (5, 11, 12, and 19) stood out in biophysical assays as new valuable BRD9 ligands featuring IC50 values in the low‐micromolar range. Noteworthy, a promising antiproliferative activity was detected in vitro for compound 5 on HeLa and A375 cancer cell line. The successful combination and application of in silico tools, chemical synthesis, and biological assays allowed to identify novel BRD9 binders and to expand the arsenal of promising chemical entities amenable to the recognition of this important epigenetic target. [ABSTRACT FROM AUTHOR]

The performance of molecular docking can be improved by comparing the shape similarity of the flexibly sampled poses against the target proteins' inverted binding cavities. The effectiveness of these pseudo-ligands or negative image-based models in docking rescoring is boosted further by performing enrichment-driven optimization. Here, we introduce a novel shape-focused pharmacophore modeling algorithm O-LAP that generates a new class of cavity-filling models by clumping together overlapping atomic content via pairwise distance graph clustering. Top-ranked poses of flexibly docked active ligands were used as the modeling input and multiple alternative clustering settings were benchmark-tested thoroughly with five demanding drug targets using random training/test divisions. In docking rescoring, the O-LAP modeling typically improved massively on the default docking enrichment; furthermore, the results indicate that the clustered models work well in rigid docking. The C+ +/Qt5-based algorithm O-LAP is released under the GNU General Public License v3.0 via GitHub (https://github.com/jvlehtonen/overlap-toolkit). Scientific contribution: This study introduces O-LAP, a C++/Qt5-based graph clustering software for generating new type of shape-focused pharmacophore models. In the O-LAP modeling, the target protein cavity is filled with flexibly docked active ligands, the overlapping ligand atoms are clustered, and the shape/electrostatic potential of the resulting model is compared against the flexibly sampled molecular docking poses. The O-LAP modeling is shown to ensure high enrichment in both docking rescoring and rigid docking based on comprehensive benchmark-testing. [ABSTRACT FROM AUTHOR]

A number of dengue viruses can seriously impact public health, and their spread has long been a concern. The development and administration of antiviral drugs have played a crucial role in combating viral infections in recent years. These drugs have shown that they can effectively inhibit viral replication and alleviate associated viral complications. The aim of this article is to provide an overview of current evidence on the effectiveness of administered antiviral drugs in controlling viral replication and treating viral problems. In the present study, the PyRx tool was used to docked proteins and ligands. In summary, the present study shows that rosmarinic acid has remarkable docking values against various dengue viral targets. Specifically, it shows a docking value of -8.0 for DENV1-E111, -8.1 for the RNA-dependent RNA polymerase (NS5), -8.2 for the non-structural A chain protein 1 (NS1), and -8.6 for the RNA helicase. These results suggest that rosmarinic acid may have an antiviral effect against the virus's target proteins. Further research is needed to investigate the therapeutic effects of rosmarinic acid in fighting viral infections. In addition, many enzymatic activities of rosmarinic acid have been reported by the PASS (Prediction of Activity Spectra for Substances) tool. The present investigation led to the definitive conclusion that rosmarinic acid possesses remarkable antiviral properties. The present study is promising for future applications, particularly in the search for a drug molecule that can effectively combat a variety of viral infections. [ABSTRACT FROM AUTHOR]

BACKGROUND: The field of toxicology has witnessed substantial advancements in recent years, particularly with the adoption of new approach methodologies (NAMs) to understand and predict chemical toxicity. Class-based methods such as clustering and classification are key to NAMs development and application, aiding the understanding of hazard and risk concerns associated with groups of chemicals without additional laboratory work. Advances in computational chemistry, data generation and availability, and machine learning algorithms represent important opportunities for continued improvement of these techniques to optimize their utility for specific regulatory and research purposes. However, due to their intricacy, deep understanding and careful selection are imperative to align the adequate methods with their intended applications. OBJECTIVES: This commentary aims to deepen the understanding of class-based approaches by elucidating the pivotal role of chemical similarity (structural and biological) in clustering and classification approaches (CCAs). It addresses the dichotomy between general end point–agnostic similarity, often entailing unsupervised analysis, and end point–specific similarity necessitating supervised learning. The goal is to highlight the nuances of these approaches, their applications, and common misuses. DISCUSSION: Understanding similarity is pivotal in toxicological research involving CCAs. The effectiveness of these approaches depends on the right definition and measure of similarity, which varies based on context and objectives of the study. This choice is influenced by how chemical structures are represented and the respective labels indicating biological activity, if applicable. The distinction between unsupervised clustering and supervised classification methods is vital, requiring the use of end point–agnostic vs. end point–specific similarity definition. Separate use or combination of these methods requires careful consideration to prevent bias and ensure relevance for the goal of the study. Unsupervised methods use end point– agnostic similarity measures to uncover general structural patterns and relationships, aiding hypothesis generation and facilitating exploration of datasets without the need for predefined labels or explicit guidance. Conversely, supervised techniques demand end point–specific similarity to group chemicals into predefined classes or to train classification models, allowing accurate predictions for new chemicals. Misuse can arise when unsupervised methods are applied to end point–specific contexts, like analog selection in read-across, leading to erroneous conclusions. This commentary provides insights into the significance of similarity and its role in supervised classification and unsupervised clustering approaches. [ABSTRACT FROM AUTHOR]

To find drugs against COVID-19, caused by the SARS-CoV-2, promising targets include the fusion of the viral spike with the human angiotensin-converting enzyme 2 (ACE2) as well as the main protease (Mpro). These proteins are responsible for viral entry and replication, respectively. We combined several state-of-the-art computational methods, including, protein–ligand interaction fingerprint, 3D-pharmacophores, molecular-docking, MM-GBSA, DFT, and MD simulations to explore two databases: ChEMBL and NANPDB to identify molecules that could both block spike/ACE2 fusion and inhibit Mpro. A total of 1,690,649 compounds from the two databases were screened using the pharmacophore model obtained from PLIF analysis. Five recent complexes of Mpro co-crystallized with different ligands were used to generate the pharmacophore model, allowing 4,829 compounds that passed this prefilter. These were then submitted to molecular docking against Mpro. The 5% top-ranked docking hits from docking result having scores < −8.32 kcal mol−1 were selected and then docked against spike/ACE2. Only four compounds: ChEMBL244958, ChEMBL266531, ChEMBL3680003, and 1-methoxy-3-indolymethyl glucosinolate (4) displayed binding energies < - 8.21 kcal mol−1 (for the native ligand) were considered as putative dual-target inhibitors. Furthermore, predictive ADMET, MM-GBSA and DFT/6-311G(d,p) were performed on these compounds and compared with those of well-known antivirals. DFT calculations showed that ChEMBL244958 and compound 4 had significant predicted reactivity values. Molecular dynamics simulations of the docked complexes were run for 100 ns and used to validate the stability docked poses and to confirm that these hits are putative dual binders of the spike/ACE2 and the Mpro. [ABSTRACT FROM AUTHOR]

To meet the growing demand for intraoperative molecular imaging, the development of compatible imaging agents plays a crucial role. Given the unique requirements of surgical applications compared to diagnostics and therapy, maximizing translational potential necessitates distinctive imaging agent designs. For effective surgical guidance, exogenous signatures are essential and are achievable through a diverse range of imaging labels such as (radio)isotopes, fluorescent dyes, or combinations thereof. To achieve optimal in vivo utility a balanced molecular design of the tracer as a whole is required, which ensures a harmonious effect of the imaging label with the affinity and specificity (e.g., pharmacokinetics) of a pharmacophore/targeting moiety. This review outlines common design strategies and the effects of refinements in the molecular imaging agent design on the agent's pharmacological profile. This includes the optimization of affinity, pharmacokinetics (including serum binding and target mediated background), biological clearance route, the achievable signal intensity, and the effect of dosing hereon. [ABSTRACT FROM AUTHOR]

The human aryl hydrocarbon receptor (AhR), a ligand‐dependent transcription factor, plays a pivotal role in a diverse array of pathways in biological and pathophysiological events. This position AhR as a promising target for both carcinogenesis and antitumor strategies. In this study we utilized computational modeling to screen and identify FDA‐approved drugs binding to the allosteric site between α2 of bHLH and PAS‐A domains of AhR, with the aim of inhibiting its canonical pathway activity. Our findings indicated that nilotinib effectively fits into the allosteric pocket and forms interactions with crucial residues F82, Y76, and Y137. Binding free energy value of nilotinib is the lowest among top hits and maintains stable within its pocket throughout entire (MD) simulations time. Nilotinib has also substantial interactions with F295 and Q383 when it binds to orthosteric site and activate AhR. Surprisingly, it does not influence AhR nuclear translocation in the presence of AhR agonists; instead, it hinders the formation of the functional AhR‐ARNT‐DNA heterodimer assembly, preventing the upregulation of regulated enzymes like CYP1A1. Importantly, nilotinib exhibits a dual impact on AhR, modulating AhR activity via the PAS‐B domain and working as a noncompetitive allosteric antagonist capable of blocking the canonical AhR signaling pathway in the presence of potent AhR agonists. These findings open a new avenue for the repositioning of nilotinib beyond its current application in diverse diseases mediated via AhR. [ABSTRACT FROM AUTHOR]

NADPH oxidases (NOXs) are the sole enzyme in the human body that can directly produce reactive oxygen species. Recent studies have shown that NOXs is a very promising target for the treatment of diabetic nephropathy (DN). Here, a series of quinoline(quinolinone) derivatives have been designed based on pharmacophore strategy, synthesized and evaluated. Among them, 19d exhibits potent antiproliferative and NOXs inhibitory activities, and is worthy for further investigation. [ABSTRACT FROM AUTHOR]

Background: Breast cancer, a leading cause of female mortality, is closely linked to mutations in estrogen receptor beta (ESR2), particularly in the ligand‐binding domain, which contributed to altered signaling pathways and uncontrolled cell growth. Objectives/Aims: This study investigates the molecular and structural aspects of ESR2 mutant proteins to identify shared pharmacophoric regions of ESR2 mutant proteins and potential therapeutic targets aligned within the pharmacophore model. Methods: This study was initiated by establishing a common pharmacophore model among three mutant ESR2 proteins (PDB ID: 2FSZ, 7XVZ, and 7XWR). The generated shared feature pharmacophore (SFP) includes four primary binding interactions: Hydrogen bond donors (HBD), hydrogen bond acceptors (HBA), hydrophobic interactions (HPho), and Aromatic interactions (Ar), along with halogen bond donors (XBD) and totalling 11 features (HBD: 2, HBA: 3, HPho: 3, Ar: 2, XBD: 1). By employing an in‐house Python script, these 11 features distributed into 336 combinations, which were used as query to isolate a drug library of 41,248 compounds and subjected to virtual screening through the generated SFP. Results: The virtual screening demonstrated 33 hits showing potential pharmacophoric fit scores and low RMSD value. The top four compounds: ZINC94272748, ZINC79046938, ZINC05925939, and ZINC59928516 showed a fit score of more than 86% and satisfied the Lipinski rule of five. These four compounds and a control underwent molecular (XP Glide mode) docking analysis against wild‐type ESR2 protein (PDB ID: 1QKM), resulting in binding affinity of −8.26, −5.73, −10.80, and −8.42 kcal/mol, respectively, along with the control −7.2 kcal/mol. Furthermore, the stability of the selected candidates was determined through molecular dynamics (MD) simulations of 200 ns and MM‐GBSA analysis. Conclusion: Based on MD simulations and MM‐GBSA analysis, our study identified ZINC05925939 as a promising ESR2 inhibitor among the top four hits. However, it is essential to conduct further wet lab evaluation to assess its efficacy. [ABSTRACT FROM AUTHOR]

Thymidylate kinase (TMK) is a pivotal enzyme in Mycobacterium tuberculosis (Mtb), crucial for phosphorylating thymidine monophosphate (dTMP) to thymidine diphosphate (dTDP), thereby playing a critical role in DNA biosynthesis. Dysregulation or inhibition of TMK activity disrupts DNA replication and cell division, making it an attractive target for anti-tuberculosis drug development. In this study, the statistically validated pharmacophore mode was developed from a set of known TMK inhibitors. Further, the robust pharmacophore was considered for screening the Enamine database. The chemical space was reduced through multiple molecular docking approaches, pharmacokinetics, and absolute binding energy estimation. Two different molecular docking algorithms favor the strong binding affinity of the proposed molecules towards TMK. Machine learning-based absolute binding energy also showed the potentiality of the proposed molecules. The binding interactions analysis exposed the strong binding affinity between the proposed molecules and active site amino residues of TMK. Several statistical parameters from all atoms MD simulation explained the stability between proposed molecules and TMK in the dynamic states. The MM-GBSA approach also found a strong binding affinity for each proposed molecule. Therefore, the proposed molecules might be crucial TMK inhibitors for managing Mtb inhibition subjected to in vitro/in vivo validations. [ABSTRACT FROM AUTHOR]

Histone deacetylases constitute a group of enzymes that participate in several biological processes. Notably, inhibiting HDAC8 has become a therapeutic strategy for various diseases. The current inhibitors for HDAC8 lack selectivity and target multiple HDACs. Consequently, there is a growing recognition of the need for selective HDAC8 inhibitors to enhance the effectiveness of therapeutic interventions. In our current study, we have utilized a multi-faceted approach, including Quantitative Structure–Activity Relationship (QSAR) combined with Quantitative Read-Across Structure–Activity Relationship (q-RASAR) modeling, pharmacophore mapping, molecular docking, and molecular dynamics (MD) simulations. The developed q-RASAR model has a high statistical significance and predictive ability (Q2F1:0.778, Q2F2:0.775). The contributions of important descriptors are discussed in detail to gain insight into the crucial structural features in HDAC8 inhibition. The best pharmacophore hypothesis exhibits a high regression coefficient (0.969) and a low root mean square deviation (0.944), highlighting the importance of correctly orienting hydrogen bond acceptor (HBA), ring aromatic (RA), and zinc-binding group (ZBG) features in designing potent HDAC8 inhibitors. To confirm the results of q-RASAR and pharmacophore mapping, molecular docking analysis of the five potent compounds (44, 54, 82, 102, and 118) was performed to gain further insights into these structural features crucial for interaction with the HDAC8 enzyme. Lastly, MD simulation studies of the most active compound (54, mapped correctly with the pharmacophore hypothesis) and the least active compound (34, mapped poorly with the pharmacophore hypothesis) were carried out to validate the observations of the studies above. This study not only refines our understanding of essential structural features for HDAC8 inhibition but also provides a robust framework for the rational design of novel selective HDAC8 inhibitors which may offer insights to medicinal chemists and researchers engaged in the development of HDAC8-targeted therapeutics. [ABSTRACT FROM AUTHOR]

FOXM1, a proto-oncogenic transcription factor, plays a critical role in cancer development and treatment resistance in cancers, particularly in breast cancer. Thus, this study aimed to identify potential FOXM1 inhibitors through computational screening of drug databases, followed by in vitro validation of their inhibitory activity against breast cancer cells. In silico studies involved pharmacophore modeling using the FOXM1 inhibitor, FDI-6, followed by virtual screening of DrugBank and Selleckchem databases. The selected drugs were prepared for molecular docking, and the crystal structure of FOXM1 was pre-processed for docking simulations. In vitro studies included MTT assays to assess cytotoxicity, and Western blot analysis to evaluate protein expression levels. Our study identified Pantoprazole and Rabeprazole as potential FOXM1 inhibitors through in silico screening and molecular docking. Molecular dynamics simulations confirmed stable interactions of these drugs with FOXM1. In vitro experiments showed both Pantoprazole and Rabeprazole exhibited strong FOXM1 inhibition at effective concentrations and that showed inhibition of cell proliferation. Rabeprazole showed the inhibitor activity at 10 µM in BT-20 and MCF-7 cell lines. Pantoprazole exhibited FOXM1 inhibition at 30 µM and in BT-20 cells and at 70 µM in MCF-7 cells, respectively. Our current study provides the first evidence that Rabeprazole and Pantoprazole can bind to FOXM1 and inhibit its activity and downstream signaling, including eEF2K and pEF2, in breast cancer cells. These findings indicate that rabeprazole and pantoprazole inhibit FOXM1 and breast cancer cell proliferation, and they can be used for FOXM1-targeted therapy in breast or other cancers driven by FOXM1. [ABSTRACT FROM AUTHOR]

The exploration of chemical space is a fundamental aspect of chemoinformatics, particularly when one explores a large compound data set to relate chemical structures with molecular properties. In this study, we extend our previous work on chemical space visualization at the pharmacophoric level. Instead of using conventional binary classification of affinity (active vs inactive), we introduce a refined approach that categorizes compounds into four distinct classes based on their activity levels: super active, very active, active, and inactive. This classification enriches the color scheme applied to pharmacophore space, where the color representation of a pharmacophore hypothesis is driven by the associated compounds. Using the BCR‐ABL tyrosine kinase as a case study, we identified intriguing regions corresponding to pharmacophore activity discontinuities, providing valuable insights for structure‐activity relationships analysis. [ABSTRACT FROM AUTHOR]