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In order to better understand the biochemical interactions governing their activities in lowering blood pressure, multiple quantitative structure-activity relationship (QSAR) models were developed from a data set of 58 angiotensin converting enzyme (ACE) inhibitors. The models were built by using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The best CoMFA model had a cross-validation q2 value of 0.940, a non cross-validation r2 value of 0.952 and an external validation statistic Qext 2 value of 0.920. For the best CoMSIA model the values were with q2 = 0.872, r2 = 0.926 and Qext 2 = 0.868. Based on the contour maps, eight new ACE inhibitors were designed. Molecular docking was employed to further explore the binding requirements between the ligands and the receptor protein which included several hydrogen bonds between the ACE inhibitors and active site residues. This study showed extensive interactions between ACE inhibitors and residues of HIS383, GLU384, HIS513, TYR520 and LYS511 in the active site of ACE. The design of potent new inhibitors of ACE can get useful insights from these results.

The ionic-interactions of acetic acid in H2O–PVOH and H2O–alcohol– PVOH solvent systems were studied at different temperatures by the viscosity method. The viscosities of the poly(vinyl alcohol) (PVOH) were increased with increasing concentration of PVOH and decreased with the increasing concentration of acetic acid. The viscosity data were used to evaluate the ion–ion interactions and ion–solvent interactions in terms of the A and B coefficients of the Jones–Dole equation, respectively. The negative values of the B-coefficient increased with increasing temperature, showing that the acid behaves as a structure breaker in PVOH–solvent mixtures and consequently, the values of the A-coefficient were decreased with increasing temperature. Thermodynamic parameters, such as energy of activation (Ea*), Gibbs energy change of activation (ΔG*) and entropy change of activation (ΔS*) were also calculated as a function of the acid (CH3COOH) concentration, PVOH composition, alcohols and temperature.

PLK4(polo-like kinase 4), an enzyme regulating centrioles, has been identified as a highly promising target for cancer treatment, making the development of PLK4 inhibitors crucial for advancing cancer therapy. In this study, 26 PLK4 inhibitors based on the imidazo[3,4- d ]pyrimidine scaffold, exhibiting anti-tumor activity, were selected. Reliable 3D/2D-QSAR models, Topomer CoMFA (q 2 =0.618, r 2 =0.965), and HQSAR (q 2 =0.711, r 2 =0.862), were established, demonstrating excellent internal and external predictive abilities and reliable applicability domains. Using the 3D/2D-QSAR models, nine PLK4 inhibitors with high theoretical activity were designed, and subsequent molecular docking and molecular dynamics studies revealed strong interactions between the new compounds and the receptor protein, particularly hydrophobic interactions. This research provides a robust screening model for the development of PLK4 inhibitors, offering valuable insights into the design of potential solutions to clinical challenges associated with PLK4 inhibitors. • Establishment of Reliable QSAR Models: Established excellent QSAR models to provide an in-depth elucidation of the structure-activity relationship of PLK4 inhibitors. • Molecular Docking and Molecular Dynamic Simulation: The study used molecular docking and molecular dynamics simulations to explore the microscopic binding mechanisms and stability between the newly designed inhibitors and the PLK4 receptor protein. • Design of Novel Inhibitors: Utilizing the QSAR models' predictive power, nine novel PLK4 inhibitors with high theoretical activity were designed, paving the way for new anti-cancer agents. • Contribution to Cancer Treatment: The design of these new PLK4-targeted inhibitors plays a significant role in cancer therapy, providing a targeted approach to treatment that may reduce off-target effects and the likelihood of drug resistance, underscoring the importance of computational technology in rational anti-cancer drug design. [ABSTRACT FROM AUTHOR]

AbstractTuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb) infection, stands as a global infectious disease presenting substantial public health challenges due to its high incidence and mortality rates. The prolonged use of conventional anti-TB therapies has led to the emergence of severe drug resistance in Mtb, resulting in extended treatment durations, increased costs, poor patient compliance, and reduced cure rates. This phenomenon has posed a significant burden on global TB prevention and control efforts, necessitating a shift in research focus toward the exploration of novel anti-TB drugs. In this context, utilizing QSAR modeling methods, our study systematically investigated the relationship between the chemical structures of 36 aryl fluorosulfate derivatives and their inhibitory activity against Mtb. Robust and predictive Topomer CoMFA and HQSAR models were developed, featuring Topomer CoMFA model parameters: q2 = 0.659, r2 = 0.969, F = 102.877, N = 6, SEE = 0.138; HQSAR model parameters: q2 = 0.705, r2 = 0.873, SEE = 0.264, HL = 199, N = 4. Leveraging these models, structural modifications were applied to the compounds using the ZINC15 database, leading to the successful design and screening of three novel compounds with desirable inhibitory activity. Molecular docking and ADMET performance prediction results indicated that these three new compounds exhibit strong binding capabilities and promising pharmaceutical potential. This study provides valuable insights and research directions for the development of aryl fluorosulfate derivatives as potential agents for tuberculosis treatment and as novel drugs. [ABSTRACT FROM AUTHOR]

WD repeat‐containing protein 5 (WDR5) and mixed lineage leukemia (MLL) are critical for maintaining tumorigenesis in human cancers. Disruption of the MLL1–WDR5 interaction has been viewed as a promising therapeutic strategy for the treatment of leukemia. Here, we report a series of protein–protein binding interaction modes targeting MLL1‐WDR5 inhibitors using 3D‐QSAR, and molecular docking. CoMFA with q2 = 0.724, r2 = 0.957, rpred2 = 0.874 and CoMSIA with q2 = 0.826, r2 = 0.995, rpred2 = 0.827. Topomer CoMFA results show q2 = 0.807, r2 = 0.976, rpred2 = 0.789, and HQSAR results show q2 = 0.873, r2 = 0.982, rpred2 = 0.794. The 3D‐QSAR model with high validation and prediction performance is successfully constructed. Contour maps and molecular docking results according to the four models, 26 new compounds are finally designed on the computer after molecular screening. Further molecular dynamics simulations (MD) of compounds G01, G04, G09, G43, and G44 with high predicted activity are carried out to explore their possible binding modes. ILE305, PHE133, CYS261, and ALA176 are found to play crucial roles in stabilizing the inhibitor. ADMET predictions are also performed for these 26 new compounds. These results serve as references for the design of effective WDR5‐MLL1 inhibitors in the future. [ABSTRACT FROM AUTHOR]

AbstractTo elucidate the structure-activity relationship of 17 matrine alkaloids from Oxytropis ochrocephala Bunge, their effect on hepatitis B surface antigen (HBsAg) secretion was studied using the MTT assay. A 3D-QSAR analysis showed a strong correlation between chemical structures and biological activities (q2 = 0.625, r2 = 0.859). Molecular docking and molecular dynamics simulations revealed that hydrogen bonding and hydrophobic interactions with hepatitis B core protein (PDB:5T2P) are key to inhibiting HBsAg secretion, suggesting potential for developing natural anti-hepatitis B drugs. [ABSTRACT FROM AUTHOR]

Hepatitis B virus (HBV) infection is a major global public health problem and a serious threat to human health. The assembly of the HBV outer shell protein is an important step in the HBV life cycle. Influencing the assembly of core proteins to block viral DNA replication has become a popular target for anti‐HBV drug development. In this study, 47 heteroarylpyrimidine (HAP) compounds were investigated by QSAR, and Topomer CoMFA and HQSAR models with strong predictive ability were developed. Eight new compounds with high activity were successfully designed by searching R groups in Topomer Search. The results of molecular docking and ADMET performance prediction showed that all these compounds have good docking scores and potential medicinal values. To further understand the possible conformations and interactions of the compounds at the protein active site, we performed molecular dynamics simulations of the four compounds with high docking scores and confirmed that these complexes have stable binding conformations by free energy mapping. The free energy calculations verified the stable binding results. These results provide an important reference and theoretical basis for the design and development of effective heteroaryldihydropyrimidine analogs as potential HBV capsid inhibitors. [ABSTRACT FROM AUTHOR]

Cancer is a serious threat to human life and social development and the use of scientific methods for cancer prevention and control is necessary. In this study, HQSAR, CoMFA, CoMSIA and TopomerCoMFA methods are used to establish models of 65 imidazo[4,5-b]pyridine derivatives to explore the quantitative structure-activity relationship between their anticancer activities and molecular conformations. The results show that the cross-validation coefficients q2 of HQSAR, CoMFA, CoMSIA and TopomerCoMFA are 0.892, 0.866, 0.877 and 0.905, respectively. The non-cross-validation coefficients r2 are 0.948, 0.983, 0.995 and 0.971, respectively. The externally validated complex correlation coefficients r2pred of external validation are 0.814, 0.829, 0.758 and 0.855, respectively. The PLS analysis verifies that the QSAR models have the highest prediction ability and stability. Based on these statistics, virtual screening based on R group is performed using the ZINC database by the Topomer search technology. Finally, 10 new compounds with higher activity are designed with the screened new fragments. In order to explore the binding modes and targets between ligands and protein receptors, these newly designed compounds are conjugated with macromolecular protein (PDB ID: 1MQ4) by molecular docking technology. Furthermore, to study the nature of the newly designed compound in dynamic states and the stability of the protein-ligand complex, molecular dynamics simulation is carried out for N3, N4, N5 and N7 docked with 1MQ4 protease structure for 50 ns. A free energy landscape is computed to search for the most stable conformation. These results prove the efficient and stability of the newly designed compounds. Finally, ADMET is used to predict the pharmacology and toxicity of the 10 designed drug molecules. [ABSTRACT FROM AUTHOR]

In recent years, blocking the interaction of programmed cell death receptor‐1 (PD‐1) and programmed cell death ligand‐1 (PD‐L1) has been recognized as one of the promising cancer therapies. Due to the many limitations of monoclonal antibodies, the development of small molecule inhibitors targeting PD‐1/PD‐L1 is imminent. This study aims to systematically investigate the interaction mechanisms of novel PD‐1/PD‐L1 inhibitors containing indoline backbone structures using 3D/2D‐QSAR modeling, molecular docking, molecular dynamics (MD) simulation, and ADMET prediction. The performance and predictive ability of the constructed QSAR models were evaluated by internal and external validation techniques. Topomer CoMFA and HQSAR models showed good reliability and predictive capability. By searching for R‐groups in the Topomer search module and combining the existing molecules with high activity contribution values, 24 new compounds with theoretically high activity were obtained, which showed desirable docking scores, appropriate ADMET properties, and good stability. This work not only provides a reliable QSAR model as a valuable screening tool for the development of future drugs targeting PD‐1/PD‐L1, but also makes the newly designed inhibitors expected to be potential PD‐1/PD‐L1 inhibitors that can be used for further synthesis and characterization to obtain novel anti‐cancer drugs targeting PD‐1/PD‐L1. [ABSTRACT FROM AUTHOR]

Microtubulin is an important research target for anti-tumour drugs, which can be used to inhibit microtubulin polymerisation and improve the efficacy of tumour therapy. In this paper, 61 microtubule protein inhibitors with anticancer activity are selected as the data set for building a stable and effective QSAR (Topomer CoMFA) model, resulting in a Topomer CoMFA model with validation coefficients of q 2 = 0.737 and r 2 = 0.922. Fifteen new inhibitors with theoretically high activity are designed by screening the zinc database for new fragments with good activity through the contribution descriptors obtained by Topomer CoMFA. After simulating the binding affinity and interaction of the inhibitors with the proteins by molecular docking, all these compounds formed strong interactions such as hydrogen bonds with multiple amino acids in the receptor proteins. Furthermore, molecular dynamics results show that the predicted highly active compounds exhibited stable and favourable binding patterns to the active pocket. In addition, these new compounds exhibit good ADMET properties. The present work establishes a reliable QSAR model for computational simulation screening of microtubulin drug development and provides a basis for further access to novel microtubulin inhibitors. [ABSTRACT FROM AUTHOR]

Three-dimensional quantitative structure-activity relationships were studied on 35 natural aurone derivatives by the Topomer CoMFA method to establish the 3 D-QSAR models, and exerting potent affections as Qo site inhibitors in cytochrome b activity for anti-malaria. The cross-validated q2 value of the Topmer CoMFA model = 0.539, the non-cross-validated r2 = 0.793, r pred 2 = 0.960, which revealed the model has good stability and predictability. The steric and electrostatic field visualization provided by the Topomer CoMFA model intuitively revealed the effects of different substituent structures. Using this information for molecule design, we theoretically obtained some new aurone derivatives as antimalarial drugs with higher activity. Furthermore, molecular docking was employed to explore the binding requirements between the ligands and the receptor protein. We obtained space relations by hydrogen bonds and hydrophobic interactions between aurone derivatives and the active site residues. The observations from these QSAR and molecular docking studies can be further used to design promising antimalarial drugs. [ABSTRACT FROM AUTHOR]

AbstractThree compounds, including a novel quinolizidine alkaloid, ochrocephalamine G (1), were isolated from Oxytropis ochrocephala. Structural elucidation was achieved through spectroscopic analysis and electronic circular dichroism. Biological assays showed that ochrocephalamine G (100 μM) inhibited HBsAg and HBeAg by 8.28% and 16.17%, respectively. Computational studies, including molecular docking and dynamics simulations, revealed its binding mode with HBV core protein, providing a solid foundation for developing O. ochrocephala as an anti-HBV therapeutic agent. [ABSTRACT FROM AUTHOR]

The normal expression of the main protease (Mpro) plays a vital role in the life cycle of coronavirus. Highly active inhibitors could inhibit the normal circulation of the main protease to achieve therapeutic effects as anti-coronavirus agents. In the present research, 48 peptide compounds with SARS-CoV Mpro inhibition selected from the literature were used to establish robust Topomer CoMFA (q2 = 0.743, r2 = 0.938, and rpred2 = 0.700) and HQSAR (q2 = 0.774, r2 = 0.955, and rpred2 = 0.723) models. Structural modification information was used for designing new Mpro inhibitors. The high contribution-value descriptor generated by Topomer CoMFA was used to screen for the fragments that possess significant inhibitory activities from the ZINC drug database, and 24 new compounds with predicted high inhibitory activity at nanomolar concentration were designed by combining the high contribution value fragments. The molecular docking results further justified that these potential inhibitors could form hydrogen bonds with the residues of CYS145, GLN189, GLU166, HIS163, and GLY143 of target Mpro, which well explains their strong inhibitory effects. The molecular dynamics simulation results indicated that four highly active compounds could stably bond with SARS-CoV-2 Mpro and might be promising anti-SARS-CoV-2 Mpro candidates. Finally, all the newly designed compounds showed premium ADMET properties as per the predictions by the server in the public domain. This research work not only provides robust QSAR models as valuable screening tools for future anti-coronavirus drug development but also renders the newly designed SARS-CoV-2 Mpro inhibitors with activity at nanomolar concentration, which can be used for further characterization to obtain novel anti-coronavirus drugs for both SARS-CoV and SARS-CoV-2. [ABSTRACT FROM AUTHOR]

• Four QSAR models are used to predict enzyme inhibition of SARS-CoV-2 Mpro. • Key amino acids influencing the receptor-ligand interactions have been identified. • The binding affinity is more dependent on hydrophobic interactions. • Six novel SARS-CoV-2 Mpro inhibitors were designed. The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains to be a serious threat due to the lack of a specific therapeutic agent. Computational methods are particularly suitable for rapidly fight against SARS-CoV-2. This present research aims to systematically explore the interaction mechanism of a series of novel bicycloproline-containing SARS-CoV-2 Mpro inhibitors through integrated computational approaches. We designed six structurally modified novel SARS-CoV-2 Mpro inhibitors based on the QSAR study. The four designed compounds with higher docking scores were further explored through molecular docking, molecular dynamics (MD) simulations, free energy calculations, and residual energy contributions estimated by the MM-PBSA approach, with comparison to compound 23(PDB entry 7D3I). This research not only provides robust QSAR models as valuable screening tools for the development of anti-COVID-19 drugs, but also proposes the newly designed SARS-CoV-2 Mpro inhibitors with nanomolar activities that can be potentially used for further characterization to treat SARS-CoV-2 virus. [Display omitted] [ABSTRACT FROM AUTHOR]

[Display omitted] • Two QSAR models are used to predict enzyme inhibition of PLK1. • Key amino acids influencing the receptor-ligand interactions have been identified. • The triazole group is important for enhancing the PLK1 inhibiting effect. • Twelve novel selective PLK1 inhibitors were designed. The forced expression of Polo-like kinase 1 (PLK1) was found to be carcinogenic, making PLK1 an attractive drug target for the treatment of tumor diseases. Drugs that can simultaneously inhibit BRD4 and PLK1 protein overexpression have more ideal therapeutic effects for treating cancer and have been widely favored. This present research aims to systemically explore the interaction mechanism of novel dual DBR4/PLK1 inhibitor BI-2536 scaffold-based derivatives as selective PLK1 inhibitors using 3D/2D-QSAR, molecular docking, molecular dynamics (MD) simulations. The performance and predictive capabilities of the generative QSAR models were evaluated through internal and external verification techniques. The topomer CoMFA and HQSAR models were showed suitable reliabilities ( q 2 = 0.625, 0.697) and predictive abilities (r pred 2 = 0.916, 0.877, respectively) for training and test set of selective PLK1 inhibitors. The SAR of the PLK1 inhibitors was summarized by the information provided by electrostatic field, hydrophobic field, and atomic color code map, which was verified by the molecular docking model. Through the search of the R-group in the topomer search module and the combination of the higher activity contributing groups in the existing molecules, 12 new compounds with theoretically high anti-PLK1 protein activity were obtained, which showed appropriate docking score, suitable ADMET, and drug-likeness properties. The molecular docking modeling verified by MD reveals significant amino acid residues (Cys67, Cys133/134/, Arg136, Phe183) at the active site of PLK1. These theoretical results are possibly beneficial to the rational design of new potent selective PLK1 inhibitors or dual BRD4/PLK1 inhibitors with enhanced effects to treat cancer. [ABSTRACT FROM AUTHOR]