Topomer CoMFA Research Articles

QSAR Modeling, Molecular Docking and ADMET Study of Aryl Fluorosulfate Derivatives as Potential Anti-TB Agents

Tuberculosis (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: q 2 = 0.659, r 2 = 0.969, F = 102.877, N = 6, SEE = 0.138; HQSAR model parameters: q 2 = 0.705, r 2 = 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.

Novel α-glucosidase Inhibitors Designed as Type 2 Diabetes Drugs by QSAR, Molecular Docking and Molecular Dynamics Simulation Methods.

Diabetes mellitus is a globally prevalent disease of significant concern. Alpha-glucosidase has emerged as a prominent target for the treatment of type 2 diabetes. In this study, 39 α-glucosidase inhibitors (AGIs) of tetrahydrobenzo[b]thiophene-2-ylurea derivatives to establish a stable and valid Topomer CoMFA model, with a cross-validation coefficient (q²) of 0.766 and a non-cross-validation coefficient (r²) of 0.960. Subsequently, the ZINC15 database was used to screen the fragments, based on which 13 novel inhibitor molecules with theoretically potentially high activity were designed. Molecular docking and molecular dynamics simulations to understand the binding status of the inhibitor molecules to the target proteins showed that amino acids ASP215, GLN279 and ARG442 may form hydrogen bonds with the ligands and therefore enhance the inhibitory effect of the small molecules. Additionally, MM/PBSA calculations suggest that the newly designed molecules demonstrate more stable binding modes, and these newly designed molecules showed good ADMET properties with potential as AGIs. The findings would provide valuable guidance and a theoretical foundation for the design and development of novel AGIs.

Computational Studies of Novel Aniline Pyrimidine WDR5‐MLL1 Inhibitors: QSAR, Molecular Docking, and Molecular Dynamics Simulation

AbstractWD 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.

Design, synthesis and antimicrobial activity of novel berberine derivatives.

The threats to the safety of humans and the environment and the resistance of agricultural chemicals to plant pathogenic fungi and bacteria highlight an urgent need to find safe and efficient alternatives to chemical fungicides and bactericides. In this study, a series of Berberine (BBR) derivatives were designed, synthesized and evaluated for in vitro and in vivo antimicrobial activity against plant pathogenic fungi and bacteria. Bioassay results indicated that compounds A11, A14, A20, A21, A22, A25, A26, E1, E2, E3, Z1 and Z2 showed high inhibitory activity against Sclerotinia sclerotiorum and Botrytis cinerea. Especially, A25 showed a broad spectrum and the highest antifungal activity among these compounds. Its EC50 value against Botrytis cinerea was 1.34 μg mL-1. Compound E6 possessed high inhibitory activity against Xanthomonas oryzae and Xanthomonas Campestris, with MIC90 values of 3.12 μg mL-1 and 1.56 μg mL-1. A Topomer CoMFA model was generated for 3D-QSAR studies based on anti-B. cinerea effects, with high predictive accuracy, showed that the addition of an appropriate substituent group at the para-position of benzyl of BBR derivatives could effectively improve the anti-B. cinerea activity. In addition, compound A25 could significantly inhibit the spore germination of Botrytis cinerea at low concentration, and compound F4 exhibited remarkable curative and protective efficiencies on rice bacterial leaf blight. This study indicates that the BBR derivatives are hopeful for further exploration as the lead compound with novel antimicrobial agents. © 2024 Society of Chemical Industry.

Discovery of New Heteroaryldihydropyrimidine Compounds as HBV Capsid Protein Inhibitors Based on QSAR, Molecular Docking and Molecular Dynamics Simulations**

AbstractHepatitis 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.

Computational Simulation Study of Potential Inhibition of c-Met Kinase Receptor by Phenoxy pyridine Derivatives: Based on QSAR, Molecular Docking, Molecular Dynamics.

The mesenchymal-epithelial transition factor (c-Met) is a tyrosine kinase receptor protein, and excessive cell transformation can lead to cancer. Therefore, there is an urgent need to develop novel receptor tyrosine kinase inhibitors by inhibiting the activity of c-Met protein. In this study, 41 compounds are selected from the reported literature, and the interactions between phenoxy pyridine derivatives and tumor-associated proteins are systematically investigated using a series of computer-assisted drug design (CADD) methods, aiming to predict potential c-Met inhibitors with high activity. The Topomer CoMFA (q2=0.620, R2=0.837) and HQSAR (q2=0.684, R2=0.877) models demonstrate a high level of robustness. Further internal and external validation assessments show high applicability and accuracy. Based on the results of the Topomer CoMFA model, structural fragments with higher contribution values are identified and randomly combined using a fragment splice technique, result in a total of 20 compounds with predicted activities higher than the template molecules. Molecular docking results show that these compounds have good interactions and van der Waals forces with the target proteins. The results of molecular dynamics and ADMET predictions indicate that compounds Y4, Y5, and Y14 have potential as c-Met inhibitors. Among them, compound Y14 exhibits superior stability with a binding free energy of -165.18 KJ/mol. These studies provide a reference for the future design and development of novel compounds with c-Met inhibitory activity.

Design and evaluation of piperidine carboxamide derivatives as potent ALK inhibitors through 3D-QSAR modeling, artificial neural network and computational analysis

Tumor stands as one of the principal contributors to global mortality. As research into tumor treatments advances, tumor inhibitors emerge as pivotal milestones in tumor therapy. Among these inhibitors, Anaplastic Lymphoma Kinase (ALK), a receptor tyrosine kinase, is critical owing to its close association with tumor cell proliferation and growth, which renders it a critical therapeutic target. This work systematically explores the relationship between the chemical structures of 36 piperidine carboxamide derivatives and their efficacy in inhibiting Karpas-299 tumor cell activity by employing a rigorous 3D-QSAR modeling approach. A robust Topomer CoMFA model was generated and was meticulously validated through ANN neural network analysis (q2 = 0.597, r2 = 0.939, F = 84.401, N = 4, SEE = 0.268). Based on the model, 60 new compounds with desirable inhibitory activities were successfully designed. Combined with Lipinski’s rule and ADMET criteria alongside molecular docking and dynamics simulations, a lead compound with high inhibitory activity and good drug-likeness was selected. Further computational analyses, encompassing free energy landscape and binding free energy calculations, provided compelling evidence of the stable binding conformation of the lead compound and the superior affinity with the target protein at the active site, underscoring its potential therapeutic utility. In summary, this investigation offers valuable insights and methodological guidance for advancing tumor therapy and underscores the promise of piperidine carboxamide derivatives as prospective ALK inhibitors.

Molecular modeling studies of Indoline Scaffold derivatives as PD‐1/PD‐L1 pathway inhibitors by QSAR, molecular docking and molecular dynamics simulation techniques

AbstractIn 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.

Chelation of the Optimal Antifungal Pogostone Analogue with Copper(II) to Explore the Dual Antifungal and Antibacterial Agent.

In an ongoing effort to explore more potent antifungal pogostone (Po) analogues, we maintained the previously identified 3-acetyl-4-hydroxy-2-pyrone core motif while synthesizing a series of Po analogues with variations in the alkyl side chain. The in vitro bioassay results revealed that compound 21 was the most potent antifungal analogue with an EC50 value of 1.1 μg/mL against Sclerotinia sclerotiorum (Lib.) de Bary. Meanwhile, its Cu(II) complex 34 manifested significantly enhanced antibacterial activity against Xanthomonas campestris pv campestris (Xcc) with a minimum inhibitory concentration (MIC) value of 300 μg/mL compared with 21 (MIC = 700 μg/mL). Complex 34 exhibited a striking preventive effect against S. sclerotiorum and Xcc in rape leaves, with control efficacies of 98.8% (50 μg/mL) and 80.7% (1000 μg/mL), respectively. The 3D-QSAR models generated using Topomer comparative molecular field analysis indicated that a shorter alkyl chain (carbon atom number <8), terminal rings, or electron-deficient groups on the alkyl side chain are beneficial for antifungal potency. Further, bioassay results revealed that the component of 21 in complex 34 dominated the antifungal activity, but the introduction of Cu(II) significantly enhanced its antibacterial activity. The toxicological observations demonstrated that 21 could induce abnormal mitochondrial morphology, loss of mitochondrial membrane potential, and reactive oxygen species (ROS) accumulation in S. sclerotiorum. The enzyme assay results showed that 21 is a moderate promiscuous inhibitor of mitochondrial complexes II and III. Besides, the introduction of Cu(II) to 34 could promote the disruption of the cell membrane and intracellular proteins and the ROS level in Xcc compared with 21. In summary, these results highlight the potential of 34 as a dual antifungal and antibacterial biocide for controlling rape diseases or as a promising candidate for further optimization.

Design of vilazodone-donepezil chimeric derivatives as acetylcholinesterase inhibitors by QSAR, molecular docking and molecular dynamics simulations.

Alzheimer's disease (AD) is a disease that affects the cognitive abilities of older adults, and it is one of the biggest global medical challenges of the 21st century. Acetylcholinesterase (AChE) can increase acetylcholine concentrations and improve cognitive function in patients, and is a potential target to develop small molecule inhibitors for the treatment of Alzheimer's disease (AD). In this study, 29 vilazodone-donepezil chimeric derivatives are systematically studied using 3D-QSAR modeling, and a robust and reliable Topomer CoMFA model was obtained with: q2 = 0.720, r2 = 0.991, F = 287.234, N = 6, and SEE = 0.098. Based on the established model and combined with the ZINC20 database, 33 new compounds with ideal inhibitory activity are successfully designed. Molecular docking and ADMET property prediction also show that these newly designed compounds have a good binding ability to the target protein and can meet the medicinal conditions. Subsequently, four new compounds with good comprehensive ability are selected for molecular dynamics simulation, and the simulation results confirm that the newly designed compounds have a certain degree of reliability and stability. This study provides guidance for vilazodone-donepezil chimeric derivatives as a potential AChE inhibitor and has certain theoretical value.

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 (= 0.715, = 0.984) and the Holographic Quantitative Structure-Activity Relationship (HQSAR) model (= 0.707, = 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

Mechanistic insights into the selectivity of bicyclophosphorothionate antagonists for housefly versus rat GABA receptors.

γ-Aminobutyric acid (GABA) receptors (GABARs) are validated targets of insecticides. Bicyclophosphorothionates are a group of insecticidal compounds that act as noncompetitive antagonists of GABARs. We previously reported that the analogs exhibit various degrees of selectivity for housefly versus rat GABARs, depending on substitutions at the 3- and 4-positions. We here sought to elucidate the unsolved mechanisms of the receptor selectivity using quantitative structure-activity relationship (QSAR), molecular docking, and molecular dynamics approaches. Three-dimensional (3D)-QSAR studies using Topomer comparative molecular field analysis quantitatively demonstrated how the introduction of a small alkyl group at the 3-position of bicyclophosphorothionates contributes to the housefly versus rat GABAR selectivity. To investigate the molecular mechanisms of the selective action, bicyclophosphorothionates were docked into housefly Resistance to dieldrin (RDL) GABAR and rat α1β2γ2 GABAR homology models built using the published 3D-structures of human GABARs as templates. The results of molecular docking and molecular dynamics simulations revealed that the 2'Ala and 6'Thr residues of the RDL subunit within the channel are the key amino acids for binding to the housefly GABARs, whereas the 2'Ser residue of γ2 subunit plays a crucial role in binding to rat GABARs. We revealed the molecular mechanisms underlying the selective antagonistic action of bicyclophosphorothionates on housefly versus rat GABARs. The information presented should help design and develop novel, safe GABAR-targeting insecticides. © 2023 Society of Chemical Industry.

Exploration of anti-tumour inhibitors from colchicine derivatives based on 3D-QSAR, molecular docking and molecular dynamics simulations

ABSTRACT 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 = 0.737 and = 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.

Structure-odor relationship in pyrazines and derivatives: A physicochemical study using 3D-QSPR, HQSPR, Monte Carlo, molecular docking, ADME-Tox and molecular dynamics

In this study, using both 2D-QSPR and 3D-QSPR approaches, to understand the structure-odor relationship of 78 1–4-pyrazine odorant molecules and to use this knowledge for the design of new food and flavor products. According to our results, the developed models have good predictability such as the HQSPR/BC model with QLOO2=0.832, R2 = 0.916, CoMSIA/SEH model with Q2 = 0.624, Rcv2 = 0.590, Rncv2 = 0.932, Rbs2 = 0.963, and Topomer CoMFA model withRtraining2 = 0.899, Rtest2 = 0.916. The Monte Carlo method was used in the creation of a Quantitative Structure-Property Relationship (QSPR) model. The molecular structure is represented using optimized Simplified Molecular Input Line Entry System (SMILES) and molecular descriptors. The performance of the model is evaluated using the Correlation Ideality Index (IIC) and the Correlation Contradiction Index (CCI). The best model, designated as TF2, boasts excellent statistical properties with a training R-squared value of 0.957 and a test R-squared value of 0.834. The model was then used to determine promoter activity levels, which formed the basis for the design of 36 new odorant molecules. Molecular docking and pharmacokinetic properties were used to explain the mode of binding between the proposed compounds and the active site of the Porcine Odorant Binding Protein complexed with pyrazine (2-isobutyl-3-methoxypyrazine). Molecular dynamic simulation was used to assess and justify the stability of the ligand in the active site of the receptor. The results of this study provide a basis for the discovery of new compounds with lower olfactory thresholds and diverse pharmacological properties.

QSAR Study on the Antitumor Activity of Novel 1,2, 3-Triazole Compounds based on Topomer Comfa Method

Background: The high mortality rate of cancer is endangering human health, and the research and development of new anticancer drugs have the attention of scientists worldwide. Sulfonamides have become the focus of anticancer drug research. 1,2,3-triazole compounds can inhibit the formation of a variety of tumor cells. Based on the excellent antitumor activity exhibited by the 1,2,3-triazole compound skeleton, the sulfonamide moiety in the sulfonamide structure can be introduced into the triazole compound skeleton to obtain highly active anticancer drugs. Methods: The Topomer CoMFA method was used to study the three-dimensional quantitative structureactivity relationship of 58 new 1,2,3-triazole compounds with sulfa groups, and a 3D-QSAR model was obtained. Results: The cross-validation coefficient q2 is 0.545, the non-cross-correlation coefficient r2 is 0. 754, r_pred2 is 0.930, the optimal number of principal components N is 4, and the standard estimation error SEE is 0.319. These results show that the model has good internal and external forecasting capabilities. By searching for the R group in the Topomer search module and combining with the more active groups in the existing molecules, 6 new compounds with theoretically higher anti-HL-60 (leukemia cell line) activity are obtained. Conclusion: The prediction result of the Topomer CoMFA model is good, and the statistical verification is effective. The prediction results of ADMET show that the 6 new compounds meet the drug requirements and are expected to become potential anti-HL-60 inhibitors, providing guidance for the synthesis of anti-tumor drugs.

Drug Design, Molecular Docking and Molecular Dynamics Simulations of Indole Class HIV‐1 NNRTIs Explored with QSAR and Topomer Search

AbstractHIV reverse transcriptase (RT) as one of the key targets for the treatment of HIV, and in recent years a series of indole class non‐nucleoside reverse transcriptase inhibitors (NNRTIs) with potent anti‐HIV‐1 properties have been reported. In this paper, Topomer CoMFA model with reliable validation results (q2=0.809, R2=0.983, R2pred=0.870) for exploring the quantitative structure‐activity relationship (QSAR) of the inhibitors. And the relationship between molecular structures and activities were further analysed using the contour plots. The Topomer search technique was employed to search and then designed novel compounds with stronger inhibitory effects. Molecular docking showed that the residue LYS101, GLU138 and ILE180 played a key role, meanwhile, the stability of the docking results was verified by molecular dynamics simulations (MD). Finally, the calculated results of the binding free energy calculations agree with the predictions of the model, further validating the reliability of the proposed model.

Identification of 4-hydroxyphenylpyruvate dioxygenase inhibitors by virtual screening, molecular docking, molecular dynamic simulation.

4-Hydroxyphenylpyruvate dioxygenase (HPPD) herbicides control broadleaf and gramineous weeds with better crop safety for corn, sorghum and wheat. Multiple screening models in silico have been established to obtain novel lead compounds as HPPD inhibition herbicides. Topomer comparative molecular field analysis (CoMFA) combined with topomer search technology and Bayesian, genetic approximation functions (GFA) and multiple linear regression (MLR) models generated by calculating different descriptors were constructed for the quinazolindione derivatives of HPPD inhibitors. The coefficient of determination (r2 ) of topomer CoMFA, MLR and GFA were 0.975, 0.970 and 0.968, respectively; all the models established displayed excellent accuracy and high predictive capacity. Five compounds with potential HPPD inhibition were obtained via screening fragment library combined with the validation of the above models and molecular docking studies. After molecular dynamics (MD) validation and absorption, distribution, metabolism, excretion and toxicity (ADMET) prediction, the compound 2-(2-amino-4-(4H-1,2,4-triazol-4-yl) benzoyl)-3-hydroxycyclohex-2-en-1-one not only exhibited stable interactions with the protein but also high solubility and low toxicity, and has potential as a novel HPPD inhibition herbicide. In this study, five compounds were obtained through multiple quantitative structure-activity relationship screening. Molecular docking and MD experiments showed that the constructed approach had good screening ability for HPPD inhibitors. This work provided molecular structural information for developing novel, highly efficient and low-toxicity HPPD inhibitors. © 2023 Society of Chemical Industry.

Discovery of novel BRD4-BD2 inhibitors via in silico approaches: QSAR techniques, molecular docking, and molecular dynamics simulations.

Bromodomain-containing protein 4(BRD4) plays an important role in the occurrence and development of various malignant tumors, which has attracted the attention of scientific research institutions and pharmaceutical companies. The structural modification of most currently available BRD4 inhibitors is relatively simple, but the drug effectiveness is limited. Research has found that the inhibition of BD1 may promote the differentiation of oligodendrocyte progenitor cell; however, the inhibition of BD2 will not cause this outcome. Therefore, newly potential drugs which target BRD4-BD2 need further research. Herein, we initially built QSAR models out of 49 compounds using HQSAR, CoMFA, CoMSIA, and Topomer CoMFA technology. All of the models have shown suitable reliabilities (q2 = 0.778, 0.533, 0.640, 0.702, respectively) and predictive abilities (r2pred = 0.716, 0.6289, 0.6153, 0.7968, respectively) for BRD4-BD2 inhibitors. On the basis of QSAR results and the search of the R-group in the topomer search module, we designed 20 new compounds with high activity that showed appropriate docking score and suitable ADMET. Docking studies and MD simulation were carried out to reveal the amino acid residues (Asn351, Cys347, Tyr350, Pro293, and Asp299) at the active site of BRD4-BD2. Free energy calculations and free energy landscapes verified the stable binding results and indicated stable conformations of the complexes. These theoretical studies provide guidance and theoretical basis for designing and developing novel BRD4-BD2 inhibitors.

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 of novel anti-cancer drugs targeting TRKs inhibitors based 3D QSAR, molecular docking and molecular dynamics simulation

Tropomyosin receptor kinase (TRK) enzymes are responsible for different types of tumors caused by neurotrophic tyrosine receptor kinase gene fusion and have been identified as an effective target for anticancer therapy. The study of the mechanism between polo-like kinase (PLKs) and pyrazol inhibitors was performed using 3D-QSAR modeling, molecular docking, and MD simulations in order to design high-activity inhibitors. The HQSAR (Q 2 = 0.793, R 2 = 0.917, R 2 ext = 0.961), CoMFA (Q 2 = 0.582, R 2 = 0.722, R 2 ext = 0.951), CoMSIA/SE (Q 2 = 0.603, R 2 = 0.801, R 2 ext = 0.849), and Topomer CoMFA (Q 2 = 0.726, R 2 = 0.992, R 2 ext = 0.717) showed good reliability and predictability. All models have been successfully tested by external validation, so all five established models are reliable. The analysis of the different contour maps of different models gives structural information to improve the inhibitory function. Molecular docking results show that the amino acids Met 592, GLU 590, LEU 657, VAL 524, and PHE 589 are the active sites of the tropomyosin receptor TRKs. The results obtained by MD showed that compound 19i could form a more stable complex protein (PDB id: 5KVT). Based on these results, we developed new compounds and their expected inhibitory activities. The results of physicochemical and ADME-Tox properties showed that the four proposed molecules are orally bioavailable, and they are not toxic in the Ames test. Thus, these results would provide modeling information that could help experimental researchers find TRK type I inhibitors more efficiently. Communicated by Ramaswamy H. Sarma