Natural compounds for oxidative stress and neuroprotection in schizophrenia: composition, mechanisms, and therapeutic potential.

OBJECTIVE: An imbalance between the generation of reactive oxygen species (ROS) and the body's antioxidant defense mechanisms is believed to be a critical factor in the development of schizophrenia (SCZ) like neurological illnesses. Understanding the roles of ROS in the development of SCZ and the potential activity of natural antioxidants against SCZ could lead to more effective therapeutic options for the prevention and treatment of the illness. METHODS: SCZ is a mental disorder characterised by progressive impairments in working memory, attention, and executive functioning. In present investigation, we summarized the experimental findings for understanding the role of oxidative stress (OS) in the development of SCZ and the potential neuroprotective effects of natural antioxidants in the treatment of SCZ. RESULTS: Current study supports the use of the mentioned antioxidant natural compounds as a potential therapeutic candidates for the treatment of OS mediated neurodegeneration in SCZ. DISCUSSION: Elevated levels of harmful ROS and reduced antioxidant defense mechanisms are indicative of increased oxidative stress (OS), which is associated with SCZ. Previous research has shown that individuals with SCZ, including non-medicated, medicated, first-episode, and chronic patients, exhibit decreased levels of total antioxidants and GSH. Additionally, they have reduced antioxidant enzyme levels such as catalase (CAT), glutathione (GPx), and, superoxide dismutase (SOD) and lower serum levels of brain-derived neurotrophic factor (BDNF) in their brain tissue. The mentioned natural antioxidants may assist in reducing oxidative damage in individuals with SCZ and increasing BDNF expression in the brain, potentially improving cognitive function and learning ability.

Computational Exploration of Naturally Occurring Flavonoids as TGF-ß Inhibitors in Breast Cancer: Insights from Docking and Molecular Dynamics Simulations and In-vitro Cytotoxicity Study.

Breast cancer is a global health concern, demanding innovative treatments. Targeting the Transforming Growth Factor-beta (TGF-ß) signaling pathway, pivotal in breast cancer, is a promising approach. TGF-ß inhibits proliferation via G1 phase cell cycle arrest, acting as a suppressor initially, but in later stages, it promotes progression by enhancing motility, invasiveness, and metastasis formation. This study explores naturally occurring flavonoids' interactions with TGF-ß. Using molecular docking against the protein's crystal structure (PDB Id: 1PY5), Gossypin showed the highest docking score and underwent molecular dynamics simulation, revealing complex flexibility and explaining how flavonoids impede TGF-ß signaling in breast cancer. ADMET predictions adhered to Lipinski's rule of Five. Insights into flavonoid-TGF-ß binding offer a novel angle for breast cancer treatment. Flavonoids having a good docking score like gossypin, morin, luteolin and taxifolin shown potent cytotoxic effect on breast cancer cell line, MCF-7. Understanding these interactions could inspire flavonoid-based therapies targeting TGF-ß to halt breast cancer growth. These findings pave the way for personalized, targeted breast cancer therapies, offering hope against this formidable disease.

Carbonylbis(hydrazine-1-carbothioamide) derivatives as a new class of α-glucosidase inhibitors and their mechanistic insights via molecular docking and dynamic simulations.

In the past, efforts have been made to find a cure for diabetes, mainly evaluating new classes of compounds to explore their potency. In this study, we present the synthesis and evaluation of carbonylbis(hydrazine-1-carbothioamide) derivatives as potential α-glucosidase inhibitors, employing both in vivo and in silico investigations. The in vitro experiments revealed that all tested compounds were significantly potent for α-glucosidase inhibition, with the lead compound 3a displaying approximately 80 times higher activity than acarbose. To delve deeper, in silico induced fit docking, pharmacokinetics, and molecular dynamics studies were conducted. Significantly, compound 3a exhibited a docking score of -7.87 kcal/mol, surpassing acarbose, which had a docking score of -6.59 kcal/mol. The in silico ADMET indicated that most of the synthesized compounds have properties conducive to drug development. Molecular dynamics analysis demonstrated that, when the ligand 3a was coupled with the target 3TOP, Cα-RMSD backbone RMSD values below 2.4 Å and "Lig_fit_Prot" values below 2.7 Å were observed. QSAR analysis demonstrates that the "fOC8A" descriptor positively correlates with α-glucosidase inhibition activity, while "lipoplus_AbSA" positively contributes and "notringC_notringO_8B" negatively contributes to this activity.

Synthesis of the chromone-thiosemicarbazone scaffold as promising α-glucosidase inhibitors: An in vitro and in silico approach toward antidiabetic drug design.

Diabetes is a serious metabolic disorder affecting individuals of all age groups and prevails globally due to the failure of previous treatments. This study aims to address the most prevalent form of type 2 diabetes mellitus (T2DM) by reporting on the design, synthesis, and in vitro as well as in silico evaluation of chromone-based thiosemicarbazones as potential α-glucosidase inhibitors. In vitro experiments showed that the tested compounds were significantly more potent than the standard acarbose, with the lead compound 3n exhibiting an IC50 value of 0.40 ± 0.02 µM, ~2183-fold higher than acarbose having an IC50 of 873.34 ± 1.67 µM. A kinetic mechanism analysis demonstrated that compound 3n exhibited reversible inhibition of α-glucosidase. To gain deeper insights, in silico molecular docking, pharmacokinetics, and molecular dynamics simulations were conducted for the investigation of the interactions, orientation, stability, and conformation of the synthesized compounds within the active pocket of α-glucosidase.

Chemical Composition of Piper nigrum L. Cultivar Guajarina Essential Oils and Their Biological Activity.

The essential oils and aroma derived from the leaves (L), stems (St), and spikes (s) of Piper nigrum L. cv. Guajarina were extracted; the essential oils were extracted using hydrodistillation (HD), and steam distillation (SD), and the aroma was obtained by simultaneous distillation and extraction (SDE). Chemical constituents were identified and quantified using GC/MS and GC-FID. Preliminary biological activity was assessed by determining the toxicity against Artemia salina Leach larvae, calculating mortality rates, and determining lethal concentration values (LC50). The predominant compounds in essential oil samples included α-pinene (0-5.6%), ß-pinene (0-22.7%), limonene (0-19.3%), 35 linalool (0-5.3%), δ-elemene (0-10.1%), ß-caryophyllene (0.5-21.9%), γ-elemene (7.5-33.9%), and curzerene (6.9-31.7%). Multivariate analysis, employing principal component analysis (PCA) and hierarchical cluster analysis (HCA), revealed three groups among the identified classes and two groups among individual compounds. The highest antioxidant activity was found for essential oils derived from the leaves (167.9 41 mg TE mL-1). Larvicidal potential against A. salina was observed in essential oils obtained from the leaves (LC50 6.40 µg mL-1) and spikes (LC50 6.44 µg mL-1). The in silico studies demonstrated that the main compounds can interact with acetylcholinesterase, thus showing the potential molecular interaction responsible for the toxicity of the essential oil in A. salina.

Theoretical and Anti-Klebsiella pneumoniae Evaluations of Substituted 2,7-dimethylimidazo[1,2-a]pyridine-3-carboxamide and Imidazopyridine Hydrazide Derivatives.

A series of multistep synthesis protocols was adopted to synthesize substituted imidazopyridines (IMPs) (SM-IMP-01 to SM-IMP-13, and DA-01-05). All substituted IMPs were then characterized using standard spectroscopic techniques such as 1H-NMR, 13C-NMR, elemental analyses, and mass spectrometry. Our both in vitro qualitative and quantitative results for antibacterial analysis, against Klebsiella pneumoniae ATCC 4352 and Bacillus subtilis ATCC 6051 suggested that all compounds essentially exhibited activity against selected strains of bacteria. Our DFT analyses suggested that the compounds of the SM-IMP-01-SM-IMP-13 series have HOMO/LUMO gaps within 4.43-4.69 eV, whereas the compounds of the DA-01-DA-05 series have smaller values of the HOMO/LUMO gaps, 3.24-4.17 eV. The lowest value of the global hardness and the highest value of the global softness, 2.215 and 0.226 eV, respectively, characterize the compound SM-IMP-02; thus, it is the most reactive compound in the imidazopyridine carboxamide series (except hydrazide series). This compound also depicted lesser MIC values against Klebsiella pneumoniae ATCC 4352 and Bacillus subtilis ATCC 6051 as 4.8 µg/mL, each. In terms of another series, hydrazide DA-05 depicted strong antimicrobial actions (MIC: 4.8 µg/mL against both bacterial strains) and also had the lowest energy gap (3.24 eV), higher softness (0.309 eV), and lesser hardness (1.62 eV). Overall, when we compare qualitative and quantitative antimicrobial results, it is been very clear that compounds with dibromo substitutions on imidazopyridine (IMP) rings would act as better antimicrobial agents than those with -H at the eighth position on the IMP ring. Furthermore, substituents of higher electronegativities would tend to enhance the biological activities of dibromo-IMP compounds. DFT properties were also well comparable to this trend and overall, we can say that the electronic behavior of compounds under investigation has key roles in their bioactivities.

QSAR Evaluations to Unravel the Structural Features in Lysine-Specific Histone Demethylase 1A Inhibitors for Novel Anticancer Lead Development Supported by Molecular Docking, MD Simulation and MMGBSA.

Using 84 structurally diverse and experimentally validated LSD1/KDM1A inhibitors, quantitative structure-activity relationship (QSAR) models were built by OECD requirements. In the QSAR analysis, certainly significant and understated pharmacophoric features were identified as critical for LSD1 inhibition, such as a ring Carbon atom with exactly six bonds from a Nitrogen atom, partial charges of lipophilic atoms within eight bonds from a ring Sulphur atom, a non-ring Oxygen atom exactly nine bonds from the amide Nitrogen, etc. The genetic algorithm-multi-linear regression (GA-MLR) and double cross-validation criteria were used to create robust QSAR models with high predictability. In this study, two QSAR models were developed, with fitting parameters like R2 = 0.83-0.81, F = 61.22-67.96, internal validation parameters such as Q2LOO = 0.79-0.77, Q2LMO = 0.78-0.76, CCCcv = 0.89-0.88, and external validation parameters such as, R2ext = 0.82 and CCCex = 0.90. In terms of mechanistic interpretation and statistical analysis, both QSAR models are well-balanced. Furthermore, utilizing the pharmacophoric features revealed by QSAR modelling, molecular docking experiments corroborated with the most active compound's binding to the LSD1 receptor. The docking results are then refined using Molecular dynamic simulation and MMGBSA analysis. As a consequence, the findings of the study can be used to produce LSD1/KDM1A inhibitors as anticancer leads.

QSAR, Molecular Docking, MD Simulation and MMGBSA Calculations Approaches to Recognize Concealed Pharmacophoric Features Requisite for the Optimization of ALK Tyrosine Kinase Inhibitors as Anticancer Leads.

ALK tyrosine kinase ALK TK is an important target in the development of anticancer drugs. In the present work, we have performed a QSAR analysis on a dataset of 224 molecules in order to quickly predict anticancer activity on query compounds. Double cross validation assigns an upward plunge to the genetic algorithm−multi linear regression (GA-MLR) based on robust univariate and multivariate QSAR models with high statistical performance reflected in various parameters like, fitting parameters; R2 = 0.69−0.87, F = 403.46−292.11, etc., internal validation parameters; Q2LOO = 0.69−0.86, Q2LMO = 0.69−0.86, CCCcv = 0.82−0.93, etc., or external validation parameters Q2F1 = 0.64−0.82, Q2F2 = 0.63−0.82, Q2F3 = 0.65−0.81, R2ext = 0.65−0.83 including RMSEtr < RMSEcv. The present QSAR evaluation successfully identified certain distinct structural features responsible for ALK TK inhibitory potency, such as planar Nitrogen within four bonds from the Nitrogen atom, Fluorine atom within five bonds beside the non-ring Oxygen atom, lipophilic atoms within two bonds from the ring Carbon atoms. Molecular docking, MD simulation, and MMGBSA computation results are in consensus with and complementary to the QSAR evaluations. As a result, the current study assists medicinal chemists in prioritizing compounds for experimental detection of anticancer activity, as well as their optimization towards more potent ALK tyrosine kinase inhibitor.

Identification of potent aldose reductase inhibitors as antidiabetic (Anti-hyperglycemic) agents using QSAR based virtual Screening, molecular Docking, MD simulation and MMGBSA approaches.

The aldose reductase (AR) enzyme is an important target enzyme in the development of therapeutics against hyperglycaemia induced health complications such as retinopathy, etc. In the present study, a quantitative structure activity relationship (QSAR) evaluation of a dataset of 226 reported AR inhibitor (ARi) molecules is performed using a genetic algorithm - multi linear regression (GA-MLR) technique. Multi-criteria decision making (MCDM) analysis furnished two five variables based QSAR models with acceptably high performance reflected in various statistical parameters such as, R2 = 0.79-0.80, Q2 LOO = 0.78-0.79, Q2 LMO = 0.78-0.79. The QSAR model analysis revealed some of the molecular features that play crucial role in deciding inhibitory potency of the molecule against AR such as; hydrophobic Nitrogen within 2 Å of the center of mass of the molecule, non-ring Carbon separated by three and four bonds from hydrogen bond donor atoms, number of sp2 hybridized Oxygen separated by four bonds from sp2 hybridized Carbon atoms, etc. 14 in silico generated hits, using a compound 18 (a most potent ARi from present dataset with pIC50 = 8.04 M) as a template, on QSAR based virtual screening (QSAR-VS) furnished a scaffold 5 with better ARi activity (pIC50 = 8.05 M) than template compound 18. Furthermore, molecular docking of compound 18 (Docking Score = -7.91 kcal/mol) and scaffold 5 (Docking Score = -8.08 kcal/mol) against AR, divulged that they both occupy the specific pocket(s) in AR receptor binding sites through hydrogen bonding and hydrophobic interactions. Molecular dynamic simulation (MDS) and MMGBSA studies right back the docking results by revealing the fact that binding site residues interact with scaffold 5 and compound 18 to produce a stable complex similar to co-crystallized ligand's conformation. The QSAR analysis, molecular docking, and MDS results are all in agreement and complementary. QSAR-VS successfully identified a more potent novel ARi and can be used in the development of therapeutic agents to treat diabetes.

Multi-Target In-Silico modeling strategies to discover novel angiotensin converting enzyme and neprilysin dual inhibitors.

Cardiovascular diseases, including heart failure, stroke, and hypertension, affect 608 million people worldwide and cause 32% of deaths. Combination therapy is required in 60% of patients, involving concurrent Renin-Angiotensin-Aldosterone-System (RAAS) and Neprilysin inhibition. This study introduces a novel multi-target in-silico modeling technique (mt-QSAR) to evaluate the inhibitory potential against Neprilysin and Angiotensin-converting enzymes. Using both linear (GA-LDA) and non-linear (RF) algorithms, mt-QSAR classification models were developed using 983 chemicals to predict inhibitory effects on Neprilysin and Angiotensin-converting enzymes. The Box-Jenkins method, feature selection method, and machine learning algorithms were employed to obtain the most predictive model with ~ 90% overall accuracy. Additionally, the study employed virtual screening of designed scaffolds (Chalcone and its analogues, 1,3-Thiazole, 1,3,4-Thiadiazole) applying developed mt-QSAR models and molecular docking. The identified virtual hits underwent successive filtration steps, incorporating assessments of drug-likeness, ADMET profiles, and synthetic accessibility tools. Finally, Molecular dynamic simulations were then used to identify and rank the most favourable compounds. The data acquired from this study may provide crucial direction for the identification of new multi-targeted cardiovascular inhibitors.

QSAR modeling approaches to identify a novel ACE2 inhibitor that selectively bind with the C and N terminals of the ectodomain.

Due to the high rates of drug development failure and the massive expenses associated with drug discovery, repurposing existing drugs has become more popular. As a result, we have used QSAR modelling on a large and varied dataset of 657 compounds in an effort to discover both explicit and subtle structural features requisite for ACE2 inhibitory activity, with the goal of identifying novel hit molecules. The QSAR modelling yielded a statistically robust QSAR model with high predictivity (R2tr=0.84, R2ex=0.79), previously undisclosed features, and novel mechanistic interpretations. The developed QSAR model predicted the ACE2 inhibitory activity (PIC50) of 1615 ZINC FDA compounds. This led to the detection of a PIC50 of 8.604 M for the hit molecule (ZINC000027990463). The hit molecule's docking score is -9.67 kcal/mol (RMSD 1.4). The hit molecule revealed 25 interactions with the residue ASP40, which defines the N and C termini of the ectodomain of ACE2. The HIT molecule conducted more than thirty contacts with water molecules and exhibited polar interaction with the ARG522 residue coupled with the second chloride ion, which is 10.4 nm away from the zinc ion. Both molecular docking and QSAR produced comparable findings. Moreover, MD simulation and MMGBSA studies verified docking analysis. The MD simulation showed that the hit molecule-ACE2 receptor complex is stable for 400 ns, suggesting that repurposed hit molecule 3 is a viable ACE2 inhibitor.

Synthesis, biological evaluation, and molecular modelling of substituted thiazolyl thiourea derivatives: A new class of prolyl oligopeptidase inhibitors.

Prolyl oligopeptidase (POP) is a compelling therapeutic target associated with aging and neurodegenerative disorders due to its pivotal role in neuropeptide processing. Despite initial promise demonstrated by early-stage POP inhibitors, their progress in clinical trials has been halted at Phase I or II. This impediment has prompted the pursuit of novel inhibitors. The current study seeks to contribute to the identification of efficacious POP inhibitors through the design, synthesis, and comprehensive evaluation (both in vitro and in silico) of thiazolyl thiourea derivatives (5a-r). In vitro experimentation exhibited that the compounds displayed significant higher potency as POP inhibitors. Compound 5e demonstrated an IC50 value of 16.47 ± 0.54 µM, representing a remarkable potency. A meticulous examination of the structure-activity relationship indicated that halogen and methoxy substituents were the most efficacious. In silico investigations delved into induced fit docking, pharmacokinetics, and molecular dynamics simulations to elucidate the intricate interactions, orientation, and conformational changes of these compounds within the active site of the enzyme. Moreover, our pharmacokinetic assessments confirmed that the majority of the synthesized compounds possess attributes conducive to potential drug development.

Structural, dynamic behaviour, in-vitro and computational investigations of Schiff's bases of 1,3-diphenyl urea derivatives against SARS-CoV-2 spike protein.

The COVID-19 has had a significant influence on people's lives across the world. The viral genome has undergone numerous unanticipated changes that have given rise to new varieties, raising alarm on a global scale. Bioactive phytochemicals derived from nature and synthetic sources possess lot of potential as pathogenic virus inhibitors. The goal of the recent study is to report new inhibitors of Schiff bases of 1,3-dipheny urea derivatives against SARS COV-2 spike protein through in-vitro and in-silico approach. Total 14 compounds were evaluated, surprisingly, all the compounds showed strong inhibition with inhibitory values between 79.60% and 96.00% inhibition. Here, compounds 3a (96.00%), 3d (89.60%), 3e (84.30%), 3f (86.20%), 3g (88.30%), 3h (86.80%), 3k (82.10%), 3l (90.10%), 3m (93.49%), 3n (85.64%), and 3o (81.79%) exhibited high inhibitory potential against SARS COV-2 spike protein. While 3c also showed significant inhibitory potential with 79.60% inhibition. The molecular docking of these compounds revealed excellent fitting of molecules in the spike protein receptor binding domain (RBD) with good interactions with the key residues of RBD and docking scores ranging from - 4.73 to - 5.60 kcal/mol. Furthermore, molecular dynamics simulation for 150 ns indicated a strong stability of a complex 3a:6MOJ. These findings obtained from the in-vitro and in-silico study reflect higher potency of the Schiff bases of 1,3-diphenyl urea derivatives. Furthermore, also highlight their medicinal importance for the treatment of SARS COV-2 infection. Therefore, these small molecules could be a possible drug candidate.

Unveiling dynamics of nitrogen content and selected nitrogen heterocycles in thrombin inhibitors: a ceteris paribus approach.

BACKGROUND: Despite the progress in comprehending molecular design principles and biochemical processes associated with thrombin inhibition, there is a crucial need to optimize efforts and curtail the recurrence of synthesis-testing cycles. Nitrogen and N-heterocycles are key features of many anti-thrombin drugs. Hence, a pragmatic analysis of nitrogen and N-heterocycles in thrombin inhibitors is important throughout the drug discovery pipeline. In the present work, the authors present an analysis with a specific focus on understanding the occurrence and distribution of nitrogen and selected N-heterocycles in the realm of thrombin inhibitors. RESEARCH DESIGN AND METHODS: A dataset comprising 4359 thrombin inhibitors is used to scrutinize various categories of nitrogen atoms such as ring, non-ring, aromatic, and non-aromatic. In addition, selected aromatic and aliphatic N-heterocycles have been analyzed. RESULTS: The analysis indicates that ~62% of thrombin inhibitors possess five or fewer nitrogen atoms. Substituted N-heterocycles have a high occurrence, like pyrrolidine (23.24%), pyridine (20.56%), piperidine (16.10%), thiazole (9.61%), imidazole (7.36%), etc. in thrombin inhibitors. CONCLUSIONS: The majority of active thrombin inhibitors contain nitrogen atoms close to 5 and a combination of N-heterocycles like pyrrolidine, pyridine, piperidine, etc. This analysis provides crucial insights to optimize the transformation of lead compounds into potential anti-thrombin inhibitors.

Synthesis and antiproliferative evaluation of novel 3,5,8-trisubstituted coumarins against breast cancer.

Aim: This study focused on designing and synthesizing novel derivatives of 3,5,8-trisubstituted coumarin. Results: The synthesized compounds, particularly compound 5, exhibited significant cytotoxic effects on MCF-7 cells, surpassing staurosporine, and reduced toxicity toward MCF-10A cells, highlighting potential pharmacological advantages. Further, compound 5 altered the cell cycle and significantly increased apoptosis in MCF-7 cells, involving both early (41.7-fold) and late stages (33-fold), while moderately affecting necrotic signaling. The antitumor activity was linked to a notable reduction (4.78-fold) in topoisomerase IIß expression. Molecular modeling indicated compound 5's strong affinity for EGFR, human EGF2 and topoisomerase II proteins. Conclusion: These findings highlight compound 5 as a multifaceted antitumor agent for breast cancer.

[Box: see text].

Application of in-silico drug discovery techniques to discover a novel hit for target-specific inhibition of SARS-CoV-2 Mpro's revealed allosteric binding with MAO-B receptor: A theoretical study to find a cure for post-covid neurological disorder.

Several studies have revealed that SARS-CoV-2 damages brain function and produces significant neurological disability. The SARS-CoV-2 coronavirus, which causes COVID-19, may infect the heart, kidneys, and brain. Recent research suggests that monoamine oxidase B (MAO-B) may be involved in metabolomics variations in delirium-prone individuals and severe SARS-CoV-2 infection. In light of this situation, we have employed a variety of computational to develop suitable QSAR model using PyDescriptor and genetic algorithm-multilinear regression (GA-MLR) models (R2 = 0.800-793, Q2LOO = 0.734-0.727, and so on) on the data set of 106 molecules whose anti-SARS-CoV-2 activity was empirically determined. QSAR models generated follow OECD standards and are predictive. QSAR model descriptors were also observed in x-ray-resolved structures. After developing a QSAR model, we did a QSAR-based virtual screening on an in-house database of 200 compounds and found a potential hit molecule. The new hit's docking score (-8.208 kcal/mol) and PIC50 (7.85 M) demonstrated a significant affinity for SARS-CoV-2's main protease. Based on post-covid neurodegenerative episodes in Alzheimer's and Parkinson's-like disorders and MAO-B's role in neurodegeneration, the initially disclosed hit for the SARS-CoV-2 main protease was repurposed against the MAO-B receptor using receptor-based molecular docking, which yielded a docking score of -12.0 kcal/mol. This shows that the compound that inhibits SARS-CoV-2's primary protease may bind allosterically to the MAO-B receptor. We then did molecular dynamic simulations and MMGBSA tests to confirm molecular docking analyses and quantify binding free energy. The drug-receptor complex was stable during the 150-ns MD simulation. The first computational effort to show in-silico inhibition of SARS-CoV-2 Mpro and allosteric interaction of novel inhibitors with MAO-B in post-covid neurodegenerative symptoms and other disorders. The current study seeks a novel compound that inhibits SAR's COV-2 Mpro and perhaps binds MAO-B allosterically. Thus, this study will enable scientists design a new SARS-CoV-2 Mpro that inhibits the MAO-B receptor to treat post-covid neurological illness.

Mechanistic QSAR modeling derived virtual screening, drug repurposing, ADMET and in-vitro evaluation to identify anticancer lead as lysine-specific demethylase 5a inhibitor.

A lysine-specific demethylase is an enzyme that selectively eliminates methyl groups from lysine residues. KDM5A, also known as JARID1A or RBP2, belongs to the KDM5 Jumonji histone demethylase subfamily. To identify novel molecules that interact with the LSD5A receptor, we created a quantitative structure-activity relationship (QSAR) model. A group of 435 compounds was used in a study of the quantitative relationship between structure and activity to guess the IC50 values for blocking LASD5A. We used a genetic algorithm-multilinear regression-based quantitative structure-activity connection model to forecast the bioactivity (PIC50) of 1615 food and drug administration pharmaceuticals from the zinc database with the goal of repurposing clinically used medications. We used molecular docking, molecular dynamic simulation modelling, and molecular mechanics generalised surface area analysis to investigate the molecule's binding mechanism. A genetic algorithm and multi-linear regression method were used to make six variable-based quantitative structure-activity relationship models that worked well (R2 = 0.8521, Q2LOO = 0.8438, and Q2LMO = 0.8414). ZINC000000538621 was found to be a new hit against LSD5A after a quantitative structure-activity relationship-based virtual screening of 1615 zinc food and drug administration compounds. The docking analysis revealed that the hit molecule 11 in the KDM5A binding pocket adopted a conformation similar to the pdb-6bh1 ligand (docking score: -8.61 kcal/mol). The results from molecular docking and the quantitative structure-activity relationship were complementary and consistent. The most active lead molecule 11, which has shown encouraging results, has good absorption, distribution, metabolism, and excretion (ADME) properties, and its toxicity has been shown to be minimal. In addition, the MTT assay of ZINC000000538621 with MCF-7 cell lines backs up the in silico studies. We used molecular mechanics generalise borne surface area analysis and a 200-ns molecular dynamics simulation to find structural motifs for KDM5A enzyme interactions. Thus, our strategy will likely expand food and drug administration molecule repurposing research to find better anticancer drugs and therapies.Communicated by Ramaswamy H. Sarma.

Impact of tautomery of 3-(4H-1,2,4-triazol-3-ylthio)-N-phenylpropanamide on the COX-1 inhibitory mechanism.

Earlier, we have reported the synthesis and anti-inflammatory evaluation of different 3-(4H-1,2,4-triazol-3-ylthio)-N-substituted propanamide. In this article, we are reporting the various tautomeric forms of the most active anti-inflammatory compound, 3-(4H-1,2,4-triazol-3-ylthio)-N-phenylpropanamide (6a) and their virtual screening by molecular docking using six principle tautomeric forms. Docking analysis suggested that compound 3-(4H-1,2,4-triazol-3-ylthio)-N-phenylpropanamide (6a) bound with COX-1 selectively and drug receptor complex was stabilized by tautomerism. Noticeably, hydroxy group formed by tautomerism appreciably improve the drug receptor interactions. It was also supervised that the compound 3-(4H-1,2,4-triazol-3-ylthio)-N-phenylpropanamide (6a) docked near the gate of COX-1 active site and might block the conversion of arachidonic acid to prostaglandin (PG) H2 in the active site of COXs. Moreover, we have carried out receptor based electrostatic analysis to clarify the electronic, steric and hydrophobic field requirement of 3-(4H-1,2,4-triazol-3-ylthio)-N-phenylpropanamide (6a) to interact with COX -1 receptor.

In-silico studies to recognize repurposing therapeutics toward arginase-I inhibitors as a potential onco-immunomodulators.

Rudolf Virchow was the first person to point out the important link between immune function and cancer. He did this by noticing that leukocytes were often found in tumors. Overexpression of arginase 1 (ARG1) and inducible nitric oxide synthase (iNOS) in myeloid-derived suppressor cells (MDSCs) and tumour-associated macrophages (TAMs) depletes both intracellular and extracellular arginine. TCR signalling is slowed as a result, and the same types of cells produce reactive oxygen and nitrogen species (ROS and RNS), which aggravates the situation. Human arginase I is a double-stranded manganese metalloenzyme that helps L-arginine break down into L-ornithine and urea. Thus, a quantitative structure-activity relationship (QSAR) analysis was performed to unearth the unrecognised structural aspects crucial for arginase-I inhibition. In this work, a balanced QSAR model with good prediction performance and clear mechanistic interpretation was developed using a dataset of 149 molecules encompassing a broad range of structural scaffolds and compositions. The model was made to meet OECD standards, and all of its validation parameters have values that are higher than the minimum requirements (R2 tr = 0.89, Q2 LMO = 0.86, and R2 ex = 0.85). The present QSAR study linked structural factors to arginase-I inhibitory action, including the proximity of lipophilic atoms to the molecule's centre of mass (within 3A), the position of the donor to the ring nitrogen (exactly 3 bonds away), and the surface area ratio. As OAT-1746 and two others are the only arginase-I inhibitors in development at the time, we have performed a QSAR-based virtual screening with 1650 FDA compounds taken from the zinc database. In this screening, 112 potential hit compounds were found to have a PIC50 value of less than 10 nm against the arginase-I receptor. The created QSAR model's application domain was evaluated in relation to the most active hit molecules identified using QSAR-based virtual screening, utilising a training set of 149 compounds and a prediction set of 112 hit molecules. As shown in the Williams plot, the top hit molecule, ZINC000252286875, has a low leverage value of HAT i/i h* = 0.140, placing it towards the boundary of the usable range. Furthermore, one of 112 hit molecules with a docking score of -10.891 kcal/mol (PIC50 = 10.023 M) was isolated from a study of arginase-I using molecular docking. Protonated ZINC000252286875-linked arginase-1 showed 2.9 RMSD, whereas non-protonated had 1.8. RMSD plots illustrate protein stability in protonated and non-protonated ZINC000252286875-bound states. Protonated-ZINC000252286875-bound proteins contain 25 Rg. The non-protonated protein-ligand combination exhibits a 25.2-Rg, indicating compactness. Protonated and non-protonated ZINC000252286875 stabilised protein targets in binding cavities posthumously. Significant root mean square fluctuations (RMSF) were seen in the arginase-1 protein at a small number of residues for a time function of 500 ns in both the protonated and unprotonated states. Protonated and non-protonated ligands interacted with proteins throughout the simulation. ZINC000252286875 bound Lys64, Asp124, Ala171, Arg222, Asp232, and Gly250. Aspartic acid residue 232 exhibited 200% ionic contact. 500-ns simulations-maintained ions. Salt bridges for ZINC000252286875 aided docking. ZINC000252286875 created six ionic bonds with Lys68, Asp117, His126, Ala171, Lys224, and Asp232 residues. Asp117, His126, and Lys224 showed 200% ionic interactions. In protonated and deprotonated states, GbindvdW, GbindLipo, and GbindCoulomb energies played crucial role. Moreover, ZINC000252286875 meets all of the ADMET standards to serve as a drug. As a result, the current analyses were successful in locating a novel and potent hit molecule that inhibits arginase-I effectively at nanomolar concentrations. The results of this investigation can be used to develop brand-new arginase I inhibitors as an alternative immune-modulating cancer therapy.

CoMSIA and POM analyses of anti-malarial activity of synthetic prodiginines.

In present work, 53 synthetic prodiginines were selected to establish thriving CoMSIA (Comparative Molecular Similarity Indices Analysis) model to explore the structural features influencing their anti-malarial activity. POM (Petra/Osiris/Molinspiration) was carried out to get insight into requirements that can lead to the improvement of the activity of these molecules. The CoMSIA model, based on a combination of steric, electrostatic and H-bond acceptor/donor effects, is with R(2)(cv)=0.738 and R(2)=0.911. The analyses reveal that lipophilicity, hydrogen donor/acceptor and steric factors play crucial role. The study with constructive propositions could be useful for the design of new analogues with enhanced activity.