Absorption, Distribution, Metabolism, Excretion Research Articles

Natural AI-based drug designing by modification of ascorbic acid and curcumin to combat buprofezin toxicity by using molecular dynamics study

Buprofezin, a widely employed insecticide in agricultural practices, has elicited significant apprehension due to its prospective deleterious effects on non-target organisms and ecological systems. Its enduring presence in terrestrial and aquatic environments presents potential hazards to human health and biodiversity, thereby necessitating the investigation of safer alternatives or strategies for mitigation. The research focuses on five principal receptors: CAT (Catalase), IL-1B (Interleukin-1 Beta), IL-6 (Interleukin-6), TNF-alpha (Tumor Necrosis Factor-alpha), and SOD (Superoxide Dismutase). These receptors are integral to the processes of inflammation, oxidative stress, and immune responses, rendering them critical for comprehending the biochemical pathways affected by toxic substances and the potential for protective interventions. The investigation employed WADDAICA (Webserver-Aided Drug Design by Artificial Intelligence) to formulate AI-driven pharmaceuticals, complemented by ADME (Absorption, Distribution, Metabolism, Excretion) evaluations, Molecular Dynamics (MD) simulations, as well as MMGBSA and MMPBSA methodologies to examine the stability and interactions of the compounds with the designated receptors. Docking experiments disclosed that the interaction of CAT with the ascorbic acid AI-derived drug demonstrated a binding energy of -7.1 kcal/mol, signifying a robust interaction, while the complex of IL-1B with the curcumin AI-derived drug exhibited a binding energy of -7.3 kcal/mol. The ADME analysis revealed favorable gastrointestinal absorption and aqueous solubility for both compounds. Furthermore, the drug-likeness metrics were deemed satisfactory, with no breaches of Lipinski’s rule of five, suggesting promising potential for subsequent advancement as therapeutic agents.

In vitro antioxidant, anticancer and in silico studies of polyphenol enriched leaf extract of Asystasia gangetica

Polyphenols are natural biomolecules known for circumventing several diseases including cancer with little adverse effects. This study aimed to investigate the polyphenol enriched fractions from the leaf extract of Asystasia gangetica for their composition, biological activities such as antioxidant activity, haemolytic effects, and in vitro cytotoxicity against cancer cell lines. LC–MS/MS analysis of the enriched fractions identified a total of 35 distinct polyphenols with caffeic acid, luteolin, apigenin, and protocatechuic acid at higher concentrations. Fractions AG-3 and AG-4 exhibited the highest total antioxidant activity with higher concentration of phenolics and flavonoids. The AG-4 fraction had the highest levels of DPPH radical scavenging (IC50 = 32.74 µg mL-1) and ABTS radical scavenging (IC50 = 29.45 µg mL–1) activity, in addition to a modest iron chelating activity and reducing power. The fractions exhibited the least haemolytic activity. The cytotoxic potential of enriched fractions against the HCT-116, HeLa, PC-3, and HDF cell lines was further examined. While the extract showed no inhibitory effect on normal HDF cells, the cytotoxic activity of fractions on cell lines varied, with HCT-116 cells having the strongest anticancer activity with an IC50 of 43.82 µg mL–1. Additionally, fractions induced apoptotic activity in HCT-116 cells, resulting in cell cycle arrest at the G2M phase and an increase in sub-G0/G1 cells, with an IC50 of 13.54 µg mL–1 after 48 h of incubation. The in silico molecular docking of the active compounds against the TNIK receptor protein and ADMET (Absorption–Distribution–Metabolism–Excretion–Toxicity) characteristics are described. Overall, the study highlights the enhanced biological and antiproliferative activities of polyphenols in Asystasia gangetica leaf extract, which could be further utilized as a potential cancer treatment strategy.

Advances in nanomaterials for precision drug delivery: Insights into pharmacokinetics and toxicity

By integrating the cutting-edge principles of nanotechnology with medical science, nanomedicine offers unprecedented opportunities to develop advanced drug delivery systems that surpass the limitations of conventional therapies. These nanoscale systems are designed to enhance treatments' efficacy, specificity, and safety by optimizing pharmacokinetics and biodistribution, ensuring that therapeutic agents reach their intended targets with minimal side effects. The article provides an in-depth analysis of nanomaterials' pivotal role in overcoming challenges related to drug delivery, including the ability to bypass biological barriers, improve bioavailability, and achieve controlled release of drugs. Despite these promising advancements, the transition of nanomedicine from research to clinical practice faces significant hurdles. The review highlights key obstacles such as patient heterogeneity, physiological variability, and the complex ADME (Absorption, Distribution, Metabolism, Excretion) profiles of nanocarriers, which complicate treatment predictability and effectiveness. Moreover, the article addresses the issues of limited tissue penetration, variable patient responses, and the need for standardized protocols in nanomaterial characterization, all of which hinder the widespread clinical adoption of nanomedicine. Nevertheless, the potential of nanomedicine in revolutionizing personalized cancer therapy remains immense. The article advocates for increased translational research and international collaboration to overcome these challenges, paving the way for fully realizing nanomedicine's capabilities in precision oncology and beyond.

Schiff Base Mediated Synthesis of Novel Imidazolidine-4-One Derivatives for Potential Antimicrobial and Anthelmintic Activities.

This study focuses on developing novel antimicrobials to combat drug-resistant pathogens, addressing compounds failing clinical trials due to inadequate physicochemical properties. Sixteen imidazolidine-4-one derivatives were synthesized by extensive evaluation using molecular docking, absorption, distribution, metabolism, excretion (ADME) predictions, and antimicrobial testing. Molecular docking studies conducted with Schrödinger's Glide revealed that compounds S4 and G8 exhibited superior docking scores of -7.839 and -7.776, respectively. The G series outperformed the S series in scores. ADME analysis confirmed all compounds adhered to Lipinski's rule of five. In addition, IR and NMR provided details about the structure of the compounds. Antimicrobial activity was assessed against Escherichia coli, Staphylococcus aureus, and Candida albicans, with compounds G2 and S2 showing exceptional minimum inhibitory concentration (MIC) values of 6.25 μg/mL against E. coli. S2 also demonstrated impressive activity against S. aureus (MIC 3.12 μg/mL), and S4 exhibited potent activity against C. albicans (MIC 0.8 μg/mL) than fluconazole (1.6 μg/mL). Additionally, antihelmintic activity was evaluated, with G1, G3, G8, S2, S4, S7, and S8 showing effective paralysis and death time 20 min and below at 50 mg/mL concentration. These results underscore the potential of new imidazolidine-4-one derivatives as suitable sources to develop a drug candidate to treat resistant infections.

Design, synthesis, in-vitro, in-silico, DFT and POM studies of a novel family of sulfonamides as potent anti-triple-negative breast cancer agents

In this study, a new family of ethacrynic acid-sulfonamides and indazole-sulfonamides was synthesized and tested in vitro against MDA-MB-468 triple-negative breast cancer cells and PBMCs human peripheral blood mononuclear cells, using the MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide) assay. The aim of this research is to discover novel compounds with potential therapeutic effects on breast cancer. The antiproliferative activity of these compounds showed a significant dose-dependent activity, with IC50 values ranging between 2.83 and 7.52 µM. The lead compounds 8 and 9 displayed similar IC50 values to paclitaxel with 2.83, 3.84 and 2.72 µM, respectively. This highlights the novelty and potential of these compounds as alternatives to current treatments. The binding properties of 8, 9, and paclitaxel with the active sites of the PARP1(Poly(ADP-ribose) polymérase 1) and EGFR (Epidermal growth factor receptor) proteins were analyzed by molecular docking methods showing, for PARP1 protein, binding affinities of −9.8 Kcal /mol, −10 Kcal /mol, and −9.4 Kcal /mol, respectively. While their binding affinities for EGFR protein are −7.5 Kcal/mol, −7.2 Kcal/mol and −6.9 Kcal/mol, respectively. Moreover, drug-likeness and ADMET (Absorption–distribution–metabolism–excretion–toxicity) analyses demonstrated that both molecules are orally bioavailable and have good pharmacokinetic and non-toxic profiles. DFT (Density functional theory) was also carried out on both compounds 8 and 9 additionally to POM (Petra/Osiris/Molinspiration) studies on all compounds. The outcomes of this study suggest that compounds 8 and 9 are promising candidates for further development as therapeutic agents against triple-negative breast cancer

A comprehensive review on microbial diversity and anticancer compounds derived from seaweed endophytes: a pharmacokinetic and pharmacodynamic approach.

Seaweed endophytes are a rich source of microbial diversity and bioactive compounds. This review provides a comprehensive analysis of the microbial diversity associated with seaweeds and their interaction between them. These diverse bacteria and fungi have distinct metabolic pathways, which result in the synthesis of bioactive compounds with potential applications in a variety of health fields. We examine many types of seaweed-associated microorganisms, their bioactive metabolites, and their potential role in cancer treatment using a comprehensive literature review. By incorporating recent findings, we hope to highlight the importance of seaweed endophytes as a prospective source of novel anticancer drugs and promote additional studies in this area. We also investigate the pharmacokinetic and pharmacodynamic profiles of these bioactive compounds because understanding their absorption, distribution, metabolism, excretion (ADMET), and toxicity profiles is critical for developing bioactive compounds with anticancer potential into effective cancer drugs. This knowledge ensures the safety and efficacy of proposed medications prior to clinical trials. This study not only provides promise for novel and more effective treatments for cancer with fewer side effects, but it also emphasizes the necessity of sustainable harvesting procedures and ethical considerations for protecting the delicate marine ecology during bioprospecting activities.

Interactions and mechanisms of phenolic compounds with human immunodeficiency virus-1 Tat protein

Human immunodeficiency virus remains a serious health threat, with an increase of 24% newly cases globally. Targeting Tat protein is an emerging therapeutic strategy for inhibiting the feedback loop that drives the exponential increase in viral transcription and particle production of the virus. The study aimed to determine the inhibitory potential of phenolic compounds from Ricinus communis L. and Jatropha curcas L., against the Tat C protein using in silico techniques. Phenolic compounds identified from both plants were screened by absorption-distribution-metabolism-excretion (ADME) analysis using drug-likeness prediction. Molecular docking analysis of the compounds with drug-like properties against the receptor and ligand-protein complexes’ analysis and visualization were performed. The results revealed three phenolic compounds with the highest negative binding affinity to the receptor’s active site: ellagic and neochlorogenic acids with - 7.2 kcal/mol and isohemiphloin with -7.3 kcal/mol. The interacting amino acids of the complexes were majorly His13, Lys19, Lys28, Thr64, His65, Gln66, Pro70, Gln72, and Pro73 via non-covalent interactions: hydrogen bonds, hydrophobic, and electrostatic interactions. The identified phenolic compounds provide a core structure that can be candidate for plant-based antiviral drugs development to potentially aiding in the virus’s therapeutic challenge.

Exploring dimethoxy naphthalenyl methoxyphenyl quinazolinyl amine as a PDE10A inhibitor: In-silico studies, synthesis and binding interactions with serum albumin

Phosphodiesterase 10A (PDE10A) inhibitors stand out as key players in the quest for effective treatments against neurological disorders. Among them, Papaverine has gained attention for its ability to activate striatal output, hinting at potential antipsychotic properties. A thorough computational analysis of 28 alkoxy quinazoline derivatives derived from Papaverine led to the discovery of Dimethoxynaphthalenyl methoxyphenyl quinazolinyl amine (QPhN), addressing its exceptional docking score (-27.71) and binding energy (−44 kJ/mol). The main contributors of this binding were Gln716 and Phe719. Absorption, Distribution, Metabolism, Excretion (ADME) and Toxicity analysis predicted its drug likeness, bioavailability and highest CNS scoring (0.0409). Notably, its synthesis involved two-step process, first cyclic addition of dimethoxy quinazolinyl chloride and dioxaborolanyl phenol took place along with alkylation with bromomethyl naphthalene. To better understand the ADME profile of QPhN, its interaction with serum albumin (SA) was analyzed with the help of Photo physical studies. Fluorescence emission of SA was quenched to reveal the subtle shifts (distinct red shift of around 20 nm) in the protein’s microenvironment. Through static quenching analysis, a binding constant value in the range (K = 104 M−1) underscored the prevalence of non-covalent interactions between QPhN and SA with involvement of one binding site. Additionally, the interaction between QPhN and SA was enthalpically and entropically compelled to sub domain IIA with ΔH (−72.2 kJ/mol), ΔS (−210.37 J mol−1 K−1) and ΔG (−9.62 kJ/mol) values. The binding represents weak perturbation (1–3 %) of α-helix content of SA with increasing concentration of QPhN. The study highlighted the importance of QPhN as a promising marker for PDE10A.

A Robust In Vitro Anti‐tuberculosis, Antimicrobial, and Anti‐inflammatory Activities Based on Azomethine Chelates Incorporating Co(II), Ni (II), Cu(II), and Zn(II) Ions: Synthesis, Characterization, and Investigation of the Aspects of Docking Interaction

ABSTRACTIn recent times, there has been a growing exploration of transition metal complexes as potential solutions for significant health challenges, including tuberculosis, microbes infection, and inflammation. Therefore, in our ongoing effort to identify biologically effective agents, Co(II), Ni(II), Cu(II), and Zn(II) metal complexes of H2L1–H2L2 hydrazone ligands were synthesized. The structural features of synthesized compounds were recognized by employing several techniques such as FT‐IR, 1H NMR, 13C NMR, powder x‐ray diffraction (XRD), UV‐Vis, ESR, TG‐DTA, mass spectrometry, and molar conductance measurements. The bonding of ligands via Ophenolic, Oenolic, and Nazomethine donor atoms and the attachment of the three water molecules with metal ion to form the octahedral structure of complexes were corroborated by different spectroscopic techniques. The anti‐tuberculosis, antimicrobial, and anti‐inflammatory activities of the synthesized compounds were assessed using the microplate alamar blue assay, serial dilution, and bovine serum albumin (BSA) methods, respectively, and highlighted the more potency of the complexes than ligands. The synthesized Cu(II) (9) and Zn(II) (10) metal complexes exhibited excellent ability to inhibit the growth of H37Rv strain of Mycobacterium tuberculosis in comparison to standard drug streptomycin. The Cu(II) (6 and 9) and Zn(II) (10) complexes showed superb ability as antimicrobial agents, whereas Cu(II) (5) and Zn(II) (6) complexes exhibited significant anti‐inflammatory ability. The in vitro findings on the antituberculosis activity were reinforced by a significant molecular docking study, which has become a crucial component of computational research utilizing the enzyme Mtb Pks13 thioesterase domain of M. tuberculosis. Additionally, in this research work, the absorption–distribution–metabolism–excretion–toxicity (ADMET) study sparked the compounds' drug‐like behavior.

Multi-Task ADME/PK prediction at industrial scale: leveraging large and diverse experimental datasets.

ADME (Absorption, Distribution, Metabolism, Excretion) properties are key parameters to judge whether a drug candidate exhibits a desired pharmacokinetic (PK) profile. In this study, we tested multi-task machine learning (ML) models to predict ADME and animal PK endpoints trained on in-house data generated at Boehringer Ingelheim. Models were evaluated both at the design stage of a compound (i. e., no experimental data of test compounds available) and at testing stage when a particular assay would be conducted (i. e., experimental data of earlier conducted assays may be available). Using realistic time-splits, we found a clear benefit in performance of multi-task graph-based neural network models over single-task model, which was even stronger when experimental data of earlier assays is available. In an attempt to explain the success of multi-task models, we found that especially endpoints with the largest numbers of data points (physicochemical endpoints, clearance in microsomes) are responsible for increased predictivity in more complex ADME and PK endpoints. In summary, our study provides insight into how data for multiple ADME/PK endpoints in a pharmaceutical company can be best leveraged to optimize predictivity of ML models.

3D-QSAR, Scaffold Hopping, Virtual Screening, and Molecular Dynamics Simulations of Pyridin-2-one as mIDH1 Inhibitors.

Isocitrate dehydrogenase 1 (IDH1) is a necessary enzyme for cellular respiration in the tricarboxylic acid cycle. Mutant isocitrate dehydrogenase 1 (mIDH1) has been detected overexpressed in a variety of cancers. mIDH1 inhibitor ivosidenib (AG-120) was only approved by the Food and Drug Administration (FDA) for marketing, nevertheless, a range of resistance has been frequently reported. In this study, several mIDH1 inhibitors with the common backbone pyridin-2-one were explored using the three-dimensional structure-activity relationship (3D-QSAR), scaffold hopping, absorption, distribution, metabolism, excretion (ADME) prediction, and molecular dynamics (MD) simulations. Comparative molecular field analysis (CoMFA, R2 = 0.980, Q2 = 0.765) and comparative molecular similarity index analysis (CoMSIA, R2 = 0.997, Q2 = 0.770) were used to build 3D-QSAR models, which yielded notably decent predictive ability. A series of novel structures was designed through scaffold hopping. The predicted pIC50 values of C3, C6, and C9 were higher in the model of 3D-QSAR. Additionally, MD simulations culminated in the identification of potent mIDH1 inhibitors, exhibiting strong binding interactions, while the analyzed parameters were free energy landscape (FEL), radius of gyration (Rg), solvent accessible surface area (SASA), and polar surface area (PSA). Binding free energy demonstrated that C2 exhibited the highest binding free energy with IDH1, which was -93.25 ± 5.20 kcal/mol. This research offers theoretical guidance for the rational design of novel mIDH1 inhibitors.

Green, facile synthesis and evaluation of unsymmetrical carbamide derivatives as antimicrobial and anticancer agents with mechanistic insights

A very practical method for the synthesis of unsymmetrical carbamide derivatives in good to excellent yield was presented, without the need for any catalyst and at room temperature. Using a facile and robust protocol, fifteen unsymmetrical carbamide derivatives (9–23) bearing different aliphatic amine moieties were designed and synthesized by the reaction of secondary aliphatic amines with isocyanate derivatives in the presence of acetonitrile as an appropriate solvent in good to excellent yields. Trusted instruments like IR, mass spectrometry, NMR spectra, and elemental analyses were employed to validate the purity and chemical structures of the synthesized compounds. All the synthesized compounds were tested as antimicrobial agents against some clinically bacterial pathogens such as Salmonella typhimurium, Bacillus subtilis, Pseudomonas aeruginosa, Staphylococcus aureus and Candida albicans. Compounds 15, 16, 17, 19 and 22 showed potent antimicrobial activity with promising MIC values compared to the positive controls. Moreover, compounds 15 and 22 provide a potent lipid peroxidation (LPO) of the bacterial cell wall. On the other hand, we investigated the anti-proliferative activity of compounds 9–23 against selected human cancerous cell lines of breast (MCF-7), colon (HCT-116), and lung (A549) relative to healthy noncancerous control skin fibroblast cells (BJ-1). The mechanism of their cytotoxic activity has been also examined by immunoassaying the levels of key anti- and pro-apoptotic protein markers. The results of MTT assay revealed that compounds 10, 13, 21, 22 and 23 possessed highly cytotoxic effects. Out of these, three synthesized compounds 13, 21 and 22 showed cytotoxicity with IC50 values (13, IC50 = 62.4 ± 0.128 and 22, IC50 = 91.6 ± 0.112 µM, respectively, on MCF-7), (13, IC50 = 43.5 ± 0.15 and 21, IC50 = 38.5 ± 0.17 µM, respectively, on HCT-116). Cell cycle and apoptosis/necrosis assays demonstrated that compounds 13 and 22 induced S and G2/M phase cell cycle arrest in MCF-7 cells, while only compound 13 had this effect on HCT-116 cells. Furthermore, compound 13 exhibited the greatest potency in inducing apoptosis in both cell lines compared to compounds 21 and 22. Docking studies indicated that compounds 10, 13, 21 and 23 could potentially inhibit enzymes and exert promising antimicrobial effects, as evidenced by their lower binding energies and various types of interactions observed at the active sites of key enzymes such as Sterol 14-demethylase of C. albicans, Dihydropteroate synthase of S. aureus, LasR of P. aeruginosa, Glucosamine-6-phosphate synthase of K. pneumenia and Gyrase B of B. subtilis. Moreover, 13, 21, and 22 demonstrated minimal binding energy and favorable affinity towards the active pocket of anticancer receptor proteins, including CDK2, EGFR, Erα, Topoisomerase II and VEGFFR. Physicochemical properties, drug-likeness, and ADME (absorption, distribution, metabolism, excretion, and toxicity) parameters of the selected compounds were also computed.

4D-QSAR, ADMET properties, and molecular dynamics simulations for designing N-substituted urea/thioureas as human glutaminyl cyclase inhibitors

Human glutaminyl cyclase (hQC) inhibitors have great potential to be used as anti- Alzheimer's disease (AD) agents by reducing the toxic pyroform of β-amyloid in the brains of AD patients. The four-dimensional quantitative structure activity relationship (4D-QSAR) model of N-substituted urea/thioureas was established with satisfying predictive ability and statistical reliability (Q2 = 0.521, R2 = 0.933, R2prep = 0.619). By utilizing the developed 4D-QSAR model, a set of new N-substituted urea/thioureas was designed and evaluated for their Absorption Distribution Metabolism Excretion and Toxicity (ADMET) properties. The results of molecular dynamics (MD) simulations, Principal component analysis (PCA), free energy landscape (FEL), dynamic cross-correlation matrix (DCCM) and molecular mechanics generalized Born Poisson-Boltzmann surface area (MM-PBSA) free energy calculations, revealed that the designed compounds were remained stable in protein binding pocket and compounds b ∼ f (−35.1 to −44.55 kcal/mol) showed higher binding free energy than that of compound 14 (−33.51 kcal/mol). The findings of this work will be a theoretical foundation for further research and experimental validation of urea/thiourea derivatives as hQC inhibitors.

Identification and Absorption–Distribution–Metabolism–Excretion–Toxicity Prediction of Potential MTHFD2 Enzyme Inhibitors from Urtica dioica Ethanolic Leaf Extract

This study aimed to explore the potential of Urtica dioica (U. dioica) ethanolic leaf extract for cancer treatment by identifying its components, evaluating its effects on cancer cell lines, and analyzing its molecular docking. The objective of this study was to investigate the anticancer properties of U. dioica ethanolic leaf extract and assess its potential as a therapeutic strategy for cancer treatment. This study utilized high-performance liquid chromatography (HPLC) to analyze the chemical composition of U. dioica ethanolic leaf extract. The anticancer effects of the extract were evaluated by assessing cell viability, determining IC50 values, and conducting ADMET analysis after oral administration. U. dioica ethanolic leaf extract was found to contain methyl hexadecanoate as its primary component, along with flavonoids and polyphenols. It effectively reduced cell viability in various tested cancer cell lines, with IC50 values varying for each cell line. The duration of treatment significantly influenced cell viability, with the most significant reduction observed after 48 h. Molecular docking studies suggested that catechin, kaempferol, and quercetin-3-O-rutinoside may have potential as inhibitors of the MTHFD2 enzyme. This study revealed the potential of U. dioica and its compounds in cancer treatment. Ethanolic leaf extract has been shown to have anticancer effects on various cancer cell lines, with catechin and kaempferol showing promise as inhibitors of the MTHFD2 enzyme. Further research is warranted to explore the therapeutic implications of U. dioica in cancer treatment.

Investigations on Growth, Characterization, NCI-RDG, AIM, Molecular Docking and In-Silico ADME Properties of 1,2-Benzene Dicarboxylic Acid Anhydride

Superior single crystal of 1,2-benzene dicarboxylic acid anhydride additionally called Phthalic anhydride (PAN) was developed via solution growth at low temperatures. Single crystal X-ray diffraction investigation revealed the crystal system and unit cell characteristics. The phase stability and crystalline nature were uncovered by powder X-ray diffraction analysis. FT-IR examination was done for the titular material so as to survey the various functional groups. With the use of the VEDA program's relevant resources, vibrational assignments have been made on the concept of Potential Energy Distribution (PED). Density Functional Theory (DFT) was employed to smooth out the molecular structure of PAN and was additionally utilized to consider FT-IR spectrum at molecular level. Non covalent interactions reduced density gradient (NCI-RDG) analysis has been used for the prediction of the weak interaction in the actual space in terms of the electron density along with its derivatives for PAN. Atoms in Molecules (AIM) analysis was carried for out for PAN. The docking research of the small molecule (PAN) with target protein confirmed that this is a great molecule which docks nicely with numerous targets associated with Hypoxia Inducible Factor 1-α. The absorption, distribution, metabolism, excretion (ADME) characteristics have been calculated with the assist of online server preADMET.

Antibacterial [Zn(nicotinamide)2Cl2] complex for the treatment of skin conditions: An experimental-theoretical study of physicochemical, microbiological and in silico pharmacokinetic properties

A dichlorobis(nicotinamide)zinc(II) complex, [Zn(nicotinamide)2Cl2], was crystallized through the slow evaporation method, and its vibrational, electronic, structural, and thermal properties have been characterized. Density functional theory (DFT) was used for the accurate analysis of intramolecular vibrational modes, obtaining chemical reactivity indices and comparative studies of geometric and electronic parameters, including solvation effects in methanol, ethanol, and water, as well as in vacuum. Additionally, the nature and strength of the bonds associated with the coordination sphere (Cl–Zn and N–Zn) were elucidated from the quantum theory of atoms in molecules and natural bond orbital analyses. Powder X-ray diffraction showed that the coordination compound belongs to a monoclinic symmetry with P21/a (C2h5) space group. Thermal analyses revealed that the material is stable up to 200 °C. From DFT calculations, the complex is chemically more stable in solvents compared to vacuum conditions, with the aqueous medium offering greater stability. The chemical stability was also analyzed by infrared and Raman spectroscopy, with the results showing spectral changes mainly for the vibrational spectra obtained in methanol, ethanol, and water against those obtained in vacuum. Biological experiments showed the complex antibacterial activity against Gram-positive and Gram-negative bacteria, mainly against the Cutibacterium acnes ATCC 6919 strain. A computational study of the absorption, distribution, metabolism, excretion (ADME), and drug-likeness were calculated to support the experimental data.

Absorption Distribution Metabolism Excretion and Toxicity Property Prediction Utilizing a Pre-Trained Natural Language Processing Model and Its Applications in Early-Stage Drug Development.

Machine learning techniques are extensively employed in drug discovery, with a significant focus on developing QSAR models that interpret the structural information of potential drugs. In this study, the pre-trained natural language processing (NLP) model, ChemBERTa, was utilized in the drug discovery process. We proposed and evaluated four core model architectures as follows: deep neural network (DNN), encoder, concatenation (concat), and pipe. The DNN model processes physicochemical properties as input, while the encoder model leverages the simplified molecular input line entry system (SMILES) along with NLP techniques. The latter two models, concat and pipe, incorporate both SMILES and physicochemical properties, operating in parallel and with sequential manners, respectively. We collected 5238 entries from DrugBank, including their physicochemical properties and absorption, distribution, metabolism, excretion, and toxicity (ADMET) features. The models' performance was assessed by the area under the receiver operating characteristic curve (AUROC), with the DNN, encoder, concat, and pipe models achieved 62.4%, 76.0%, 74.9%, and 68.2%, respectively. In a separate test with 84 experimental microsomal stability datasets, the AUROC scores for external data were 78% for DNN, 44% for the encoder, and 50% for concat, indicating that the DNN model had superior predictive capabilities for new data. This suggests that models based on structural information may require further optimization or alternative tokenization strategies. The application of natural language processing techniques to pharmaceutical challenges has demonstrated promising results, highlighting the need for more extensive data to enhance model generalization.

Novel Anthraquinone-Based Benzenesulfonamide Derivatives and Their Analogues as Potent Human Carbonic Anhydrase Inhibitors with Antitumor Activity: Synthesis, Biological Evaluation, and In Silico Analysis.

In this study, we designed two series of novel anthraquinone-based benzenesulfonamide derivatives and their analogues as potential carbonic anhydrase inhibitors (CAIs) and evaluated their inhibitory activities against off-target human carbonic anhydrase II (hCA II) isoform and tumor-associated human carbonic anhydrase IX (hCA IX) isoform. Most of these compounds exhibited good inhibitory activities against hCA II and IX. The compounds that exhibited the best hCA inhibition were further studied against the MDA-MB-231, MCF-7, and HepG2 cell lines under hypoxic and normoxic conditions. Additionally, the compounds exhibiting the best antitumor activity were subjected to apoptosis and mitochondrial membrane potential assays, which revealed a significant increase in the percentage of apoptotic cells and a notable decrease in cell viability. Molecular docking studies were performed to demonstrate the presence of numerous hydrogen bonds and hydrophobic interactions between the compounds and the active site of hCA. Absorption, distribution, metabolism, excretion (ADME) predictions showed that all of the compounds had good pharmacokinetic and physicochemical properties.

Discovery of Novel Noncovalent KRAS G12D Inhibitors through Structure-Based Virtual Screening and Molecular Dynamics Simulations.

The development of effective inhibitors targeting the Kirsten rat sarcoma viral proto-oncogene (KRASG12D) mutation, a prevalent oncogenic driver in cancer, represents a significant unmet need in precision medicine. In this study, an integrated computational approach combining structure-based virtual screening and molecular dynamics simulation was employed to identify novel noncovalent inhibitors targeting the KRASG12D variant. Through virtual screening of over 1.7 million diverse compounds, potential lead compounds with high binding affinity and specificity were identified using molecular docking and scoring techniques. Subsequently, 200 ns molecular dynamics simulations provided critical insights into the dynamic behavior, stability, and conformational changes of the inhibitor-KRASG12D complexes, facilitating the selection of lead compounds with robust binding profiles. Additionally, in silico absorption, distribution, metabolism, excretion (ADME) profiling, and toxicity predictions were applied to prioritize the lead compounds for further experimental validation. The discovered noncovalent KRASG12D inhibitors exhibit promises as potential candidates for targeted therapy against KRASG12D-driven cancers. This comprehensive computational framework not only expedites the discovery of novel KRASG12D inhibitors but also provides valuable insights for the development of precision treatments tailored to this oncogenic mutation.

Vibrational spectra, molecular structure, electronic, pharmaceutical and bonding nature of (4S)-4-(3,4-dihydroxyphenyl)-1,2,3,4-tetrahydroisoquinoline-7,8-diol - anti hypertension agent

Several factors, including environment, behaviours, and heredity, influence the development of hypertension. The title compound dopamine D1 receptor agonist named (4S)-4-(3,4-dihydroxyphenyl)-1,2,3,4-tetrahydroisoquinoline-7,8-diol (4S4D4T) is one of the most important neurotransmitters associated with numerous neural disorders. Using DFT and quantum chemical simulations, the vibrational, electrical, and structural possessions of the heading compound were predicted. To carry out the quantum computational investigations, a highly compatible method entitled B3LYP basis set was adopted. Vibrational Modes of functional groups with PED values were calculated using VEDA software to compute geometric dimensions and assign fundamental vibrations. Using gas and solvent phases, MEP differentiates between nucleophilic and electrophilic sites and creates distribution for the charge of the molecules. The observed wavelength with (TDSCF) UV–Vis spectra for the various solvents phases were compared. The NBO approach provides an understanding of the electron delocalization that results from hyperconjugation. FUKUI analysis is used to determine the area of site reaction. Electron density's topological analysis was carried out using the QTAIM theory. The ADME (Absorption, Distribution, Metabolism, Excretion) profiles are produced with the Swiss ADME online tool. In summary, this dissertation offers a thorough examination that evaluates the impact of particular pharmaceuticals on solvation and enzyme efficiency using a combination of spectral and quantitative computing methodologies. Therefore, plans for further research can profit immensely by the information gathered. The results of protein-ligand docking using the Auto Dock method with various proteins suggest that the molecule has pharmaceutical properties against receptors.