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.

Hybrid 2D/3D-quantitative structure-activity relationship studies on the bioactivities and molecular mechanism of antibacterial peptides.

Antimicrobial peptide (AMP) is the polypeptide, which protects the organism avoiding attack from pathogenic bacteria. Studies have shown that there were some antimicrobial peptides with molecular action mechanism involved in crossing the cell membrane without inducing severe membrane collapse, then interacting with cytoplasmic target-nucleic acid, and exerting antibacterial activity by interfacing the transmission of genetic information of pathogenic microorganisms. However, the relationship between the antibacterial activities and peptide structures was still unclear. Therefore, in the present work, a series of AMPs with a sequence of 20 amino acids was extracted from DBAASP database, then, quantitative structure-activity relationship (QSAR) methods were conducted on these peptides. In addition, novel antimicrobial peptides with  stronger antimicrobial activities were designed according to the information originated from the constructed models. Hence, the outcome of this study would lay a solid foundation for the in-silico design and exploration of novel antibacterial peptides with improved activity activities.

Ligand-Based Design of Novel Quinoline Derivatives as Potential Anticancer Agents: An In-Silico Virtual Screening Approach.

In this study, using the Comparative Molecular Field Analysis (CoMFA) approach, the structure-activity relationship of 33 small quinoline-based compounds with biological anti-gastric cancer activity in vitro was analyzed in 3D space. Once the 3D geometric and energy structure of the target chemical library has been optimized and their steric and electrostatic molecular field descriptions computed, the ideal 3D-QSAR model is generated and matched using the Partial Least Squares regression (PLS) algorithm. The accuracy, statistical precision, and predictive power of the developed 3D-QSAR model were confirmed by a range of internal and external validations, which were interpreted by robust correlation coefficients (RTrain2=0.931; Qcv2=0.625; RTest2=0.875). After carefully analyzing the contour maps produced by the trained 3D-QSAR model, it was discovered that certain structural characteristics are beneficial for enhancing the anti-gastric cancer properties of Quinoline derivatives. Based on this information, a total of five new quinoline compounds were developed, with their biological activity improved and their drug-like bioavailability measured using POM calculations. To further explore the potential of these compounds, molecular docking and molecular dynamics simulations were performed in an aqueous environment for 100 nanoseconds, specifically targeting serine/threonine protein kinase. Overall, the new findings of this study can serve as a starting point for further experiments with a view to the identification and design of a potential next-generation drug for target therapy against cancer.

Combining QSAR techniques, molecular docking, and molecular dynamics simulations to explore anti-tumor inhibitors targeting Focal Adhesion Kinase.

Focal Adhesion Kinase (FAK) is an important target for tumor therapy and is closely related to tumor cell genesis and progression. In this paper, we selected 46 FAK inhibitors with anticancer activity in the pyrrolo pyrimidine backbone to establish 3D/2D-QSAR models to explore the relationship between inhibitory activity and molecular structure. We have established two ideal models, namely, the Topomer CoMFA model (q2= 0.715, r2= 0.984) and the Holographic Quantitative Structure-Activity Relationship (HQSAR) model (q2= 0.707, r2= 0.899). Both models demonstrate excellent external prediction capabilities.Based on the QSAR results, we designed 20 structurally modified novel compounds, which were subjected to molecular docking and molecular dynamics studies, and the results showed that the new compounds formed many robust interactions with residues within the active pocket and could maintain stable binding to the receptor proteins. This study not only provides a powerful screening tool for designing novel FAK inhibitors, but also presents a series of novel FAK inhibitors with high micromolar activity that can be used for further characterization. It provides a reference for addressing the shortcomings of drug metabolism and drug resistance of traditional FAK inhibitors, as well as the development of novel clinically applicable FAK inhibitors.Communicated by Ramaswamy H. Sarma.

Design, One-Step Highly Selective Synthesis and Enhancing Insecticidal Activity and Photo-Self-Degradation of Phenylpyrazole Esterified Derivatives as GABA and nACh Receptor Inhibitors.

In the pursuit of novel insecticides with high activity and a unique mode of action on the GABA receptor, a series of phenylpyrazole esterified derivatives (PEs) were synthesized using an improved Pinner reaction with high selectivity. Lewis acid catalysis was employed in a one-step solvent-thermal method to convert the cyano group of fipronil into an ester unit. FeCl3 was found to exhibit the highest selectivity for PEs synthesis, yielding PEs at 96.4%, with the byproduct being phenylpyrazole amide (PE0) at 2.1%. Initial biological assays indicated superior insecticidal activity of the target compounds against Plutella xylostella and Mythimna separata compared to fipronil. Particularly, the smaller and shorter ester units, PE3, PE5, and PE8, demonstrated 2-2.5 times higher insecticidal activity against P. xylostella than fipronil. The higher activity of ester units compared to amide and acylhydrazone units can be attributed to the enhanced lipid solubility of PEs. Additionally, it may be due to the impact of PEs on the neurotransmitter nACh or the coordination of calcium and chloride ions with the ester's -C═O and -O- bonds, blocking the chloride ion channel. Hydrophobic parameters were confirmed by reversed-phase high-performance liquid chromatography (HPLC), indicating the enhanced lipophilicity conferred by the ester units of PEs. Molecular docking and CoMFA analysis preliminarily validated the strong interactions and structure-activity relationships between PEs and the GABA receptor and nACh receptor in P. xylostella. Furthermore, under simulated natural sunlight, PEs exhibited photodegradation capabilities, transforming back into fipronil parent fragments and enhancing their insecticidal activity. Moreover, PEs displayed excellent fluorescent properties, enabling self-detection of residues. These research findings provide new insights and directions for the development of efficient pesticides, with potential wide applications in the fields of medicine and biosensors.

Integration of virtual screening of phytoecdysteroids as androgen receptor inhibitors by 3D-QSAR Model, CoMFA, molecular docking and ADMET analysis: An extensive and interactive machine learning.

Ecdysteroids, a class of naturally isolated polyhydroxylated sterols, stands at a very good place in the pharmaceutical industry from their medicinal point of views like anti-inflammatory, neuroprotective, anti-microbial, anti-diabetic, antioxidant, and anti-tumor effects. Due to their excellent antioxidant and anti-microbial potential, ecdysteroids have extensive use in skin products, especially derma creams. To monitor the best anti-acne phytoecdysteroids, here made use of different computational approaches, by using the rapid, easy, cost-effective and high throughput method to screen and identify ecdysteroids as androgen receptor inhibitors. 3D-QSAR study was carried out on a dataset of ecdysteroids by using comparative molecular field analysis (CoMFA) to determine the factors responsible for the activity of compounds. Statistically a cross-validated (q2) 0.1457 and regression coefficient (r2) 0.9713 indicated the best model. Contour map results showed the influence of steric effect to enhance activity. A molecular docking analysis was done to further find out the binding sites and their anti-acne potential against three crystal structured macromolecules (PDB ID: 2REQ, 2BAC, 4EM0). Docking results were further evaluated by prime MM-GBSA analysis and findings confirmed the accuracy. Toxicity by ADMET assessment was carried out and M2 was found as lead druglike with best anti-acne activity against Propionium acnes GehA lipase bacteria after passing all filters. This research study is novel because it is representing first effort to explore ecdysteroids class for their high therapeutic output as androgen receptor inhibitor by using computational tools and expectedly led to novel scaffold for androgen receptor inhibitor. This is a novel and new approach to investigate the ecdysteroids for first time for their practical applications.

Integrated computational approaches for designing potent pyrimidine-based CDK9 inhibitors: 3D-QSAR, docking, and molecular dynamics simulations.

CDK9 is an emerging target for the development of anticancer drugs. The development of CDK9 inhibitors with significant potency had consistently posed a formidable challenge. In the current research, a number of computational methodologies, such as, 3D-QSAR, molecular docking, fingerprint analysis, molecular dynamic (MD) simulations followed by MMGB/PBSA and ADMET studies were used systemically to uncover the binding mechanism of pyrimidine derivatives against CDK9. The CoMFA and CoMSIA models having high q2 (0.53, 0.54) and r2 values (0.96, 0.93) respectively indicating that model could accurately predict the bioactivities of CDK9 inhibitors. Using the R-group exploration technique implemented by the Spark™ by Cresset group, the structural requirements revealed by the contour maps of model were utilized strategically to create an in-house library of 100 new CDK9 inhibitors. Additionally, the compounds from the in-house library were mapped into 3D-QSAR model which predicted pIC50 values comparable to the experimental values. A comparison between 3D-QSAR generated contours and molecular docking conformation of ligands was performed to elucidate the essentials of CDK9 inhibitor design. MD simulations (100 ns) were performed on the selected docked complexes A21, A14 and D98 which contributed in validating the binding interactions. According to the findings of binding free energy analysis (MMGB/PBSA), It was observed that residues CYS106 and GLU107 had a considerable tendency to facilitate ligand-protein interactions via H-bond interactions. The aforementioned findings have the potential to enhance researchers comprehension of the mechanism underlying CDK9 inhibition and may be utilized in the development of innovative and efficacious CDK9 inhibitors.

QSAR Studies, Synthesis, and Biological Evaluation of New Pyrimido-Isoquinolin-Quinone Derivatives against Methicillin-Resistant Staphylococcus aureus.

According to the WHO, antimicrobial resistance is among the top 10 threats to global health. Due to increased resistance rates, an increase in the mortality and morbidity of patients has been observed, with projections of more than 10 million deaths associated with infections caused by antibacterial resistant microorganisms. Our research group has developed a new family of pyrimido-isoquinolin-quinones showing antibacterial activities against multidrug-resistant Staphylococcus aureus. We have developed 3D-QSAR CoMFA and CoMSIA studies (r2 = 0.938; 0.895), from which 13 new derivatives were designed and synthesized. The compounds were tested in antibacterial assays against methicillin-resistant Staphylococcus aureus and other bacterial pathogens. There were 12 synthesized compounds active against Gram-positive pathogens in concentrations ranging from 2 to 32 µg/mL. The antibacterial activity of the derivatives is explained by the steric, electronic, and hydrogen-bond acceptor properties of the compounds.

Assessing structural insights into in-house arylsulfonyl L-(+) glutamine MMP-2 inhibitors as promising anticancer agents through structure-based computational modelling approaches.

MMP-2 is potentially contributing to several cancer progressions including leukaemias. Therefore, considering MMP-2 as a promising target, novel anticancer compounds may be designed. Here, 32 in-house arylsulfonyl L-(+) glutamines were subjected to various structure-based computational modelling approaches to recognize crucial structural attributes along with the spatial orientation for higher MMP-2 inhibition. Again, the docking-based 2D-QSAR study revealed that the Coulomb energy conferred by Tyr142 and total interaction energy conferred by Ala84 was crucial for MMP-2 inhibition. Importantly, the docking-dependent CoMFA and CoMSIA study revealed the importance of favourable steric, electrostatic, and hydrophobic substituents at the terminal phenyl ring. The MD simulation study revealed a lower fluctuation in the RMSD, RMSF, and Rg values indicating stable binding interactions of MMP-2 and these molecules. Moreover, the residual hydrogen bond and their interaction analysis disclosed crucial amino acid residues responsible for forming potential hydrogen bonding for higher MMP-2 inhibition. The results can effectively aid in the design and discovery of promising small-molecule drug-like MMP-2 inhibitors with greater anticancer potential in the future.

In silico research on new sulfonamide derivatives as BRD4 inhibitors targeting acute myeloid leukemia using various computational techniques including 3D-QSAR, HQSAR, molecular docking, ADME/Tox, and molecular dynamics.

Acute myeloid leukemia, a serious condition affecting stem cells, drives uncontrollable myeloblast proliferation, leading to accumulation. Extensive research seeks rapid, effective chemotherapeutics. A potential option is a BRD4 inhibitor, known for suppressing cell proliferation. Sulfonamide derivatives probed essential structural elements for potent BRD4 inhibitors. To achieve this goal, we employed 3D-QSAR molecular modeling techniques, including CoMFA, CoMSIA, and HQSAR models, along with molecular docking and molecular dynamics simulations. The validation of the 2D/3D QSAR models, both internally and externally, underscores their robustness and reliability. The contour plots derived from CoMFA, CoMSIA, and HQSAR analyses played a pivotal role in shaping the design of effective BRD4 inhibitors. Importantly, our findings highlight the advantageous impact of incorporating bulkier substituents on the pyridinone ring and hydrophobic/electrostatic substituents on the methoxy-substituted phenyl ring, enhancing interactions with the BRD4 target. The interaction mode of the new compounds with the BRD4 receptor (PDB ID: 4BJX) was investigated using molecular docking simulations, revealing favorable binding energies, supported by the formation of hydrogen and hydrophobic bonds with key protein residues. Moreover, these novel inhibitors exhibited good oral bioavailability and demonstrated non-toxic properties based on ADMET analysis. Furthermore, the newly designed compounds along with the most active one from series 58, underwent a molecular dynamics simulation to analyze their behavior. The simulation provided additional evidence to support the molecular docking results, confirming the sustained stability of the analyzed molecules over the trajectory. This outcome could serve as a valuable reference for designing and developing novel and effective BRD4 inhibitors.Communicated by Ramaswamy H. Sarma.

Combining docking, molecular dynamics simulations, AD-MET pharmacokinetics properties, and MMGBSA calculations to create specialized protocols for running effective virtual screening campaigns on the autoimmune disorder and SARS-CoV-2 main protease.

The development of novel medicines to treat autoimmune diseases and SARS-CoV-2 main protease (Mpro), a virus that can cause both acute and chronic illnesses, is an ongoing necessity for the global community. The primary objective of this research is to use CoMFA methods to evaluate the quantitative structure-activity relationship (QSAR) of a select group of chemicals concerning autoimmune illnesses. By performing a molecular docking analysis, we may verify previously observed tendencies and gain insight into how receptors and ligands interact. The results of the 3D QSAR models are quite satisfactory and give significant statistical results: Q_loo∧2 = 0.5548, Q_lto∧2 = 0.5278, R∧2 = 0.9990, F-test = 3,101.141, SDEC = 0.017 for the CoMFA FFDSEL, and Q_loo∧2 = 0.7033, Q_lto∧2 = 0.6827, Q_lmo∧2 = 0.6305, R∧2 = 0.9984, F-test = 1994.0374, SDEC = 0.0216 for CoMFA UVEPLS. The success of these two models in exceeding the external validation criteria used and adhering to the Tropsha and Glorbaikh criteria's upper and lower bounds can be noted. We report the docking simulation of the compounds as an inhibitor of the SARS-CoV-2 Mpro and an autoimmune disorder in this context. For a few chosen autoimmune disorder receptors (protein tyrosine phosphatase, nonreceptor type 22 (lymphoid) isoform 1 (PTPN22), type 1 diabetes, rheumatoid arthritis, and SARS-CoV-2 Mpro, the optimal binding characteristics of the compounds were described. According to their potential for effectiveness, the studied compounds were ranked, and those that demonstrated higher molecular docking scores than the reference drugs were suggested as potential new drug candidates for the treatment of autoimmune disease and SARS-CoV-2 Mpro. Additionally, the results of analyses of drug similarity, ADME (Absorption, Distribution, Metabolism, and Excretion), and toxicity were used to screen the best-docked compounds in which compound 4 scaled through. Finally, molecular dynamics (MD) simulation was used to verify compound 4's stability in the complex with the chosen autoimmune diseases and SARS-CoV-2 Mpro protein. This compound showed a steady trajectory and molecular characteristics with a predictable pattern of interactions. These findings suggest that compound 4 may hold potential as a therapy for autoimmune diseases and SARS-CoV-2 Mpro.

3D-QSAR-based design, synthesis and biological evaluation of 2,4-disubstituted quinoline derivatives as antimalarial agents.

2,4-Disubstituted quinoline derivatives were designed based on a 3D-QSAR study, synthesized and evaluated for antimalarial activity. A large dataset of 178 quinoline derivatives was used to perform a 3D-QSAR study using CoMFA and CoMSIA models. PLS analysis provided statistically validated results for CoMFA (r2ncv = 0.969, q2 = 0.677, r2cv = 0.682) and CoMSIA (r2ncv = 0.962, q2 = 0.741, r2cv = 0.683) models. Two series of a total of 40 2,4-disubstituted quinoline derivatives were designed with amide (quinoline-4-carboxamide) and secondary amine (4-aminoquinoline) linkers at the -C4 position of the quinoline ring. For the purpose of selecting better compounds for synthesis with good pEC50 values, activity prediction was carried out using CoMFA and CoMSIA models. Finally, a total of 10 2,4-disubstituted quinoline derivatives were synthesized, and screened for their antimalarial activity based on the reduction of parasitaemia. Compound #5 with amide linker and compound #19 with secondary amine linkers at the -C4 position of the quinoline ring showed maximum reductions of 64% and 57%, respectively, in the level of parasitaemia. In vivo screening assay confirmed and validated the findings of the 3D-QSAR study for the design of quinoline derivatives.

One-pot multicomponent synthesis of novel pyridine derivatives for antidiabetic and antiproliferative activities.

Background: Due to the close relationship of diabetes with hypertension reported in various research, a set of pyridine derivatives with US FDA-approved drug cores were designed and integrated by artificial intelligence. Methods: Novel pyridines were designed and synthesized. Compounds MNS-1-MNS-4 were evaluated for their structure and were screened for their in vitro antidiabetic (α-amylase) activity and anticancer (HepG2) activity by methyl thiazolyl tetrazolium assay. Comparative 3D quantitative structure-activity relationship analysis and pharmacophore generation were carried out. Results: The study revealed MNS-1 and MNS-4 as good alternatives to acarbose as antidiabetic agents, and MNS-2 as a more viable, better alternative to doxorubicin in the methyl thiazolyl tetrazolium assay. Conclusion: This combination of studies identifies new and more active analogs of existing FDA-approved drugs for the treatment of diabetes.

Employing comparative QSAR techniques for the recognition of dibenzofuran and dibenzothiophene derivatives toward MMP-12 inhibition.

Among various matrix metalloproteinases (MMPs), MMP-12 is one of the potential targets for cancer and other diseases. However, none of the MMP-12 inhibitors has passed the clinical trials to date. Therefore, designing potential MMP-12 inhibitors as new drug molecules can provide effective therapeutic strategies for several diseases. In this study, a series of dibenzofuran and dibenzothiophene derivatives were subjected to different 2D and 3D-QSAR techniques to point out the crucial structural contributions highly influential toward the MMP-12 inhibitory activity. These techniques identified some structural attributes of these compounds that are responsible for influencing their MMP-12 inhibition. The carboxylic group may enhance proper binding with catalytic Zn2+ ion at the MMP-12 active site. Again, the i-propyl sulfonamido carboxylic acid function contributed positively toward MMP-12 inhibition. Moreover, the dibenzofuran moiety conferred stable binding at the S1' pocket for higher MMP-12 inhibition. The steric and hydrophobic groups were found favourable near the furan ring substituted at the dibenzofuran moiety. Besides these ligand-based approaches, molecular docking and molecular dynamic (MD) simulation studies not only elucidated the importance of several aspects of these MMP-12 inhibitors while disclosing the significance of the finding of these QSAR studies and their influences toward MMP-12 inhibition. The MD simulation study also revealed stable and compact binding between such compounds at the MMP-12 active site. Therefore, the findings of these validated ligand-based and structure-based molecular modeling studies can aid the development of selective and potent lead molecules that can be used for the treatment of MMP-12-associated diseases.Communicated by Ramaswamy H. Sarma.

Molecular modeling of pyrrolo-pyrimidine based analogs as potential FGFR1 inhibitors: a scientific approach for therapeutic drugs.

Fibroblast growth factor receptors 1 (FGFR1) is an emerging target for the development of anticancer drugs. Uncontrolled expression of FGFR1 is strongly associated with a number of different types of cancers. Apart from a few FGFR inhibitors, the FGFR family members have not been thoroughly studied to produce clinically effective anticancer drugs. The application of proper computational techniques may aid in understanding the mechanism of protein-ligand complex formation, which may provide a better notion for developing potent FGFR1 inhibitors. In this study, a variety of computational techniques, including 3D-QSAR, flexible docking and MD simulation followed by MMGB/PBSA, H-bonds and distance analysis, have been performed to systematically explore the binding mechanism of pyrrolo-pyrimidine derivatives against FGFR1. The 3D-QSAR model was generated to deduce the structural determinants of FGFR1 inhibition. The high q2 and r2 values for the CoMFA and CoMSIA models indicated that the created 3D-QSAR models could reliably predict the bioactivities of FGFR1 inhibitors. The computed binding free energies (MMGB/PBSA) for the selected compounds were consistent with the ranking of their experimental binding affinities against FGFR1. Furthermore, per-residue energy decomposition analysis revealed that the residues Lys514 in catalytic region, Asn568, Glu571 in solvent accessible portion and Asp641 in DFG motif exhibited a strong tendency to mediate ligand-protein interactions through the hydrogen bonding and Van Der Waals interactions. These findings may benefit researchers in gaining better knowledge of FGFR1 inhibition and may serve as a guideline for the development of novel and highly effective FGFR1 inhibitors.Communicated by Ramaswamy H. Sarma.

Structural Insights on Hyp-Gly-Containing Peptides as Antiplatelet Compounds through Topomer CoMFA and CoMSIA Analysis.

Increasing evidence has shown collagen hydrolysate involves a variety of bioactivities. In our previous study, multiple antiplatelet peptides containing Hyp/Pro-Gly were identified in collagen hydrolysates from Salmo salar and silver carp skin and exhibited anti-thrombosis activity without bleeding risks in vivo. However, the relationship between structure and activity remains unknown. We performed 3D-QSAR studies on 23 Hyp/Pro-Gly-containing peptides in which 13 peptides were reported before. CoMFA, Topomer CoMFA and CoMSIA analyses were used to generate the QSAR models. Topomer CoMFA analysis showed a q2 value of 0.710, an r2 value of 0.826, an r2pred value of 0.930, and the results showed that Hyp instead of Pro was more important for improving the antiplatelet activity. CoMSIA analysis showed a q2 value of 0.461, an r2 value of 0.999, and an r2pred value of 0.999. Compared with the electrostatic field and hydrogen bond donor field, the steric field, hydrophobic field and hydrogen bond receptor field have great influence on the activity of antiplatelet peptides. The predicted peptide EOGE exhibited antiplatelet activity induced by ADP, and inhibited thrombus formation (300 µmol/kg bw) without bleeding risks. Combined results of these studies indicate that OG-containing peptides had a potential to be developed into an effective specific medical food in the prevention of thrombotic diseases.

Design, Synthesis, Antibacterial Evaluation, Three-Dimensional Quantitative Structure-Activity Relationship, and Mechanism of Novel Quinazolinone Derivatives.

Plant bacterial illnesses are common and cause dramatic damage to agricultural goods all over the world, yet there are few efficient bactericides to alleviate them at present. To discover novel antibacterial agents, two series of quinazolinone derivatives with novel structures were synthesized and their bioactivity against plant bacteria was tested. Combining CoMFA model search and the antibacterial bioactivity assay, D32 was identified as a potent antibacterial inhibitor against Xanthomonas oryzae pv. Oryzae (Xoo), with an EC50 value of 1.5 µg/mL, much better in inhibitory capacity compared to bismerthiazol (BT) and thiodiazole copper (TC) (31.9 and 74.2 µg/mL). The activities of compound D32 against rice bacterial leaf blight in vivo were 46.7% (protective activities) and 43.9% (curative activities), better than commercial drug thiodiazole copper (29.3% protective activities and 30.6% curative activities). Flow cytometry, proteomics, reactive oxygen species, and key defense enzymes were used to further investigate the relevant mechanisms of action of D32. The identification of D32 as an antibacterial inhibitor and revelation of its recognition mechanism not only open the possibility of developing new therapeutic strategies for treatment of Xoo but also provide clues for elucidation of the acting mechanism of quinazolinone derivative D32, which is a possible clinical candidate worth in-depth study.

3D-QSAR modeling and molecular docking studies on a series of 2, 4, 5-trisubstituted imidazole derivatives as CK2 inhibitors.

Protein case in kinase II alpha subunit (CK2) plays an imperative function in treating cancer disease. Herein, we have performed a three-dimensional quantitative structure activity relationship (3D-QSAR), and molecular docking analysis on a novel series of 2, 4, 5-trisubstituted imidazole derivatives in order to design potent kinase II alpha subunit (CK2) inhibitors. The 3D-QSAR methods such as comparative molecular similarity indexes analysis (COMSIA), and the comparative molecular field analysis (COMFA) were investigate using twenty-four molecules of 2, 4, 5-trisubstituted imidazole derivatives as anticancer agent. The best COMFA and COMSIA models exhibit excellent Q2 values of 0.66 and 0.75 and R2 values of 0.98 and 0.99 respectively. To check the validity of the selected COMFA and COMSIA models, a variety of validation tests were utilized: Internal validation analyses, and externally validation beside Y-randomization according to the principles of the Organization for Economic Co-operation and Development (OECD), and the Golbraikh and Tropsha's criteria for the validation of 3D-QSAR models. The proposed models for COMFA and COMSIA analysis have been successful. The developed models, indicating that they were reliable for activity prediction. Based on the preceding results, we designed several new potent molecules. Such outcome can proffer helpful theoretical references for future experimental studies.Communicated by Ramaswamy H. Sarma.

Informed Use of 3D-QSAR for the Rational Design of Coumarin Derivatives as Potent and Selective MAO B Inhibitors.

The quantitative structure-activity relationship method based on the three-dimensional structure of the target molecules (3D-QSAR) represents a valuable predictive tool for the design of new bioactive agents. Herewith, a detailed procedure is described which uses a pool comprising 67 derivatives substituted at position 4 and 7 of the common coumarin scaffold as a benchmark for deriving a predictive 3D-QSAR model employed for guiding the rational design of 10 new potent and selective MAO B inhibitors.

Combined computational approaches for developing new anti-Alzheimer drug candidates: 3D-QSAR, molecular docking and molecular dynamics studies of liquiritigenin derivatives.

Butyrylcholinesterase is an acetylcholine-degrading enzyme involved in the memorization process, which is becoming an interesting target for the symptomatic treatment of Alzheimer's disease. In the present investigation, the structure-activity relationship of a set of Liquiritigenin derivatives recently revealed to be Butyrylcholinesterase inhibitors was studied basing on comparative field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMISA). As a result, performant models with high predictive capability have been developed (CoMFA model: R2 = 0.91, Q2 = 0.62, R2 pred = 0.85; CoMISA model: R2 = 0.92, Q2 = 0.59, R2 pred = 0.83) and implemented to design new Liquiritigenin derivatives with improved activity. Besides, the affinity of the designed derivatives towards the active site of Butyrylcholinesterase, was confirmed by molecular docking and molecular dynamics studies. Moreover, they exhibited good pharmacokinetics properties. Accordingly, the outcomes of the present investigations can provide important direction for the development of new anti-Alzheimer's drug candidates.