Search

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.

InP microcrystal was successfully synthesized via a facile hydrothermal route, and then Ag nanoparticles were loaded on the surface of InP microcrystal using UV lamp to reduce silver versions. The as-prepared composites were characterized by X-ray diffraction (XRD) and field-emission scanning electron microscopy (FE-SEM). The results show that Ag/InP composite is composed of lots of spherical microcrystals with a size of 500nm and Ag nanoparticles with a diameter of 20 nm loaded uniformly on the surface of cubic phase InP microspheres,the surface is rough. Using Congo red as model organic pollutant, the photo-catalytic performance of Ag/InP microspheres is further detected by fluorescence and UV-vis spectra. It is found that the as-prepared composite exhibits a superior photo-catalytic degradation activity as compared to InP, which might be the effective separation of electrons and holes after Ag nanoparticles loaded on the surface of InP microspheres.In addition,the photo-catalytic performance of Ag/InP microspheres with different Ag loads was studied,and the results show that when the loading is 73.3%,the photocatalytic activity of the product is the best,and the degradation rate is 64%.

In this work, a 3D-QSAR model involving for 40 dipeptidyl boronic acid proteasome inhibitors was built based on Topomer CoMFA. The multiple correlation coefficient of fitting, cross-validation and external validation were 0.908, 0.647 and 0.703, respectively. The results indicated that the obtained Topomer CoMFA model has not only the favourable estimation stability but also the good prediction capability. Topomer Search was employed as a tool for virtual screening in lead-like compounds of ZINC database. Finally, 1 R1 group, 7 R2 groups and 6 R3 groups with higher contribution values were employed to alternately substitute the R1, R2 and R3 of the templete compound 23 with highest bioactivity. As a consequence, 33 new molecules with higher activity than that of the model molecule were designed successfully. The results showed that the Topomer Search technology could be effectively apply to screen and design new dipeptidyl boronic acid proteasome inhibitors and has good predictive capability to design new dipeptidyl boronic acid proteasome inhibitors drugs as guidance.

In this paper, a three-dimensional quantitative structure-activity relationship (3D-QSAR) study for 62 HIV-1 integrase(IN) inhibitors was established using Topomer CoMFA. The multiple correlation coefficient of fitting, cross validation and external validation were 0.942, 0.670 and 0.748, respectively. The results indicated that the Topomer CoMFA model obtained has both favorable estimation stability and good prediction capability. Topomer Search was used to search R group from ZINC database. As the result, a series of R groups with relatively high activity contribution was obtained. By filtering with the most potent molecule in the set, 1 Ra group and 21 Rb groups were selected. We employed the 1 Ra groups and 21 Rb groups to alternately substitute the Ra and Rb of sample 42. Finally, we designed 21 new compounds and further predicted their activities using the Topomer CoMFA model and there were 10 new compounds with higher activity than that of the template molecule. The results suggested the Topomer Search technology could be effectively used to screen and design new HIV-1 IN inhibitors and has good predictive capability to guide the design of new HIV/AIDS drugs.

Quantitative structure-activity relationships (QSAR) approach is used for finding the relationship between molecular structures and the activity of peptide drugs. In this work, stepwise multiple regression, was employed to select optimal subset of descriptors that have significant contribution to the drug activity of 21 oxytocin analogues, 48 bitter tasting threshold, and 58 angiotensin-converting enzyme inhibitors. A new set of descriptor, SVWGM, was used for the prediction of the drug activity of peptide drugs and then were used to build the model by partial least squares method, for it’s estimation stability and generalization ability was strictly analyzed by both internal and external validations, with cross-validation correlation coefficient, correlation coefficient and correlation coefficient of external validation.

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]

The segregation of the Fe element in Ti-10V-2Fe-3Al titanium alloy (Ti-1023) can lead to the generation of beta flecks, which seriously affects the performance of Ti-1023 products. During the heat treatment (HT) process at a high temperature, the Fe element in Ti-1023 ingots will migrate, making its distribution more uniform and reducing the segregation index. In this paper, the control of Fe micro-segregation in Ti-1023 ingots by homogenization HT was investigated. Firstly, dissection sampling and SEM-EDS analysis methods were used to study the distribution pattern of the Fe element in the equiaxed grains in the core of Ti-1023 ingots. It was found that the Fe content in the grain gradually increased along with the radial direction from the core to the grain boundary. Then, the homogenization HT experiments and numerical simulations of Ti-1023 at different HT temperatures from 1050 °C to 1200 °C were carried out. The results showed that the uniformity of Fe element distribution within grain can be significantly improved by the homogenization HT. With increasing HT temperature, Fe atoms migration ability increases, and the uniformity of Fe element distribution improves. Homogenization HT at 1150 °C and 1200 °C for 12 h can effectively reduce the degree of Fe element segregation. [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]