3D-QSAR, HQSAR, molecular docking, and new compound design study of 1,3,6-trisubstituted 1,4-diazepan-7-ones as human KLK7 inhibitors

Design of novel DABO derivatives as HIV-1 RT inhibitors using molecular docking, molecular dynamics simulations and ADMET properties

HIV-1 reverse transcriptase is an important target for developing effective anti-HIV-1 inhibitors. Different types of small molecules have been designed based on this target, showing different levels of inhibitory activity against various types of HIV-1 strains. The relationship between structure and activity of DABO derivatives was investigated by means of 3D-QSAR molecular model, molecular docking, molecular dynamics and ADMET properties. The statistical results of molecular models show that the CoMFA and CoMSIA models have good internal stability (CoMFA: q2 = 0.623, r2 = 0.946; CoMSIA: q2 = 0.668, r2 = 0.983) and external prediction ability (CoMFA: rpred2 = 0.961; CoMSIA: rpred2 = 0.961). In addition, molecular docking has explored the mechanism of action between small molecules and receptor proteins, and the results show that hydrogen bonding between amino acid Lys101 and small molecules can improve the affinity of ligands to receptor binding. A total of 12 novel molecules were designed and their activities were predicted based on the 3D-QSAR model and molecular docking results. The results showed that the designed molecules had higher predictive activity. Subsequently, 100 ns MD simulation and binding free energy verified the stability of molecular docking results. Finally, the pharmacokinetic properties of the novel designed molecule were verified by using ADMET to predict its properties. These results can provide reference for the design and development of novel and effective HIV-1 RT inhibitors, and provide new ideas for the design of subsequent drugs.Communicated by Ramaswamy H. Sarma.

Molecular docking, 3D-QASR and molecular dynamics simulations of benzimidazole Pin1 inhibitors

Pin1 (protein interacting with never-in-mitosis akinase-1) is a member of the family of peptidylprolyl cis-trans isomerases (PPIases) that specifically recognize and isomerize substrates containing phosphorylated Ser/Thr-Pro sequences. Pin1 is involved in many cellular processes and plays a key role in the cell cycle, transcriptional regulation, cell metabolism, proliferation and differentiation, and its abnormalities lead to degenerative and neoplastic diseases. Pin1 is highly expressed in human cancers and promotes the development of tumors by activating multiple oncogenes and inactivating multiple tumor suppressor genes, making it an attractive target for cancer therapy. In this study, we investigated the binding mechanism and conformational relationship between benzimidazole Pin1 inhibitors and Pin1 proteins by molecular docking, three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling, binding free energy calculations and decomposition, and molecular dynamics simulations. Molecular docking and molecular dynamics simulations disclosed the most likely binding pose of benzimidazoles with the Pin1 protein. The results of 3D-QSAR modeling indicated that electrostatic fields, hydrophobic fields and hydrogen bonding play important roles in the binding process of inhibitors to proteins. The binding free energy calculations and energy decomposition indicated that Lys63, Arg69, Cys113, Leu122, Met130, and Ser154 may be key residues in the binding of benzimidazole-based inhibitors to the Pin1 protein. This study provides an important theoretical basis for the design and optimization of benzimidazole compounds.

Structural optimization of pyrrolopyrimidine BTK inhibitors based on molecular simulation

CONTEXT

BTK is a critical regulator involved in the proliferation, differentiation, and apoptosis of B cells. BTK inhibitors can effectively alleviate various diseases such as tumors, leukemia, and asthma. During this study, a range of novel BTK inhibitors were designed using 3D-QSAR, molecular docking, and molecular dynamics (MD) simulation.

METHODS

We selected 41 pyrrolopyrimidine derivatives as BTK inhibitors to structure a 3D-QSAR model. Comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) were adopted to research the connection between the pharmacological activities and chemical structures of the compounds. The CoMFA model (q2 = 0.519, R2 = 0.971), CoMSIA model (q2 = 0.512, R2 = 0.990), and external validation demonstrated excellent predictive performance and reliability of the 3D-QSAR model. We designed eight novel molecules with higher inhibitory activities according to the three-dimensional equipotential fields and explored the interactions between the compounds and BTK by molecular docking, which showed that the novel molecules had higher binding affinities with BTK than the template molecule 18. Then, the results of molecular docking were further verified by MD simulation, which showed that amino acid residues such as Leu528, Val416, and Met477 played vital parts in the interaction, and the binding free energy analysis showed that the novel molecules had higher stability with BTK. Finally, the ADME/T properties were predicted for all of the novel compounds, and the results showed that the majority of them had favorable pharmacokinetic properties. Therefore, this study provides strong support for the development of novel BTK inhibitors.

Predicting rejection of emerging contaminants through RO membrane filtration based on ANN-QSAR modeling approach: trends in molecular descriptors and structures towards rejections

In this work, a quantitative structure-activity relationship (QSAR) study was performed on a set of emerging contaminants (ECs) to predict their rejections by reverse osmosis membrane (RO). A wide range of molecular descriptors was calculated by Dragon software for 72 ECs. The QSAR data was analyzed by an artificial neural network method (ANN), in which four out of 3000 theoretical molecular descriptors were chosen and their significance was computed based on the Garson method. The significance trends of descriptors were as follows in descending order: ESpm14u > R2e > SIC1 > EEig03d. The selected descriptors were ranked based on their importance and then an explorative study was conducted on the QSAR data to show the trends in molecular descriptors and structures toward the rejections values of ECs. The MLR algorithm was used to make a linear model and the results were compared with those of the nonlinear ANN algorithm. The comparison results revealed it is necessary to apply the ANN model to this data with non-linear properties. For the whole dataset, the correlation coefficient (R2) and residual mean squared error (RMSE) of the ANN and MLR methods were 0.9528, 6.4224; and 0.8753, 11.3400, respectively. The comparison results showed the superiority of ANN modeling in the analysis of ECs' QSAR data.

Molecular docking, 3D-QASR and molecular dynamics simulations of thiazoles Pin1 inhibitors

Pin1 (protein interacting with never-in-mitosis akinase-1) is a member of the PPIase (peptidylprolyl cis-trans isomerase) family. It can interact with a variety of carcinogenic or tumor suppressive phosphorylated proteins. The interaction results in the conformational changes of target proteins, and ultimately regulates the activity of these proteins. These activity changes play a key role in tumorigenesis. Pin1 is an attractive target for cancer therapy due to its over-expression and/or activation in various types of cancer and the disorder of Proline directed phosphorylation. In this study, molecular docking, three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular dynamics (MD) simulations were performed to investigate the structure-activity relationship and binding mechanism of 45 thiazole-class Pin1 inhibitors. Molecular docking studies predict the binding mode and the interactions between the ligand and the receptor protein. The results of the 3 D-QSAR model show that electrostatic field, hydrophobic field and hydrogen bond play important roles in the binding process of inhibitors to protein. Molecular dynamics simulation results reveal that the complex of the ligand and the receptor protein are stable at 300 K. The binding free energy calculation and energy decomposition results show that His59, Cys113, Ser114, Ser115, Leu122, Met130, Gln131, Phe134, Ser154 and His157 may be the key to the inhibitor binding to Pin1 protein. This study provides an important theoretical basis for further development of the new Pin1 inhibitor design. These results can provide more useful information for our further drug design. Communicated by Ramaswamy H. Sarma.

Molecular Design and Mechanism Analysis of Phthalic Acid Ester Substitutes: Improved Biodegradability in Processes of Sewage Treatment and Soil Remediation

Phthalic acid esters (PAEs) have the characteristics of environmental persistence. Therefore, improving the biodegradability of PAEs is the key to reducing the extent of ecological harm realized. Firstly, the scoring function values of PAEs docking with various degrading enzymes in sewage treatment were calculated. Based on this, a 3D-quantitative structure-activity relationship (3D-QSAR) model for PAE biodegradability was built, and 38 PAE substitutes were created. By predicting the endocrine-disrupting toxicity and functions of PAE substitutes, two types of PAE substitutes that are easily degraded by microorganisms, have low toxicity, and remain functional were successfully screened. Meanwhile, the differences in the mechanism of molecular degradation difference before and after PAE modification were analyzed based on the distribution characteristics of amino acid residues in the molecular docking complex. Finally, the photodegradability and microbial degradability of the PAE substitutes in the soil environment was evaluated. From the 3D-QSAR model design perspective, the modification mechanism of PAE substitutes suitable for sewage treatment and soil environment degradation was analyzed. We aim to improve the biodegradability of PAEs at the source and provide theoretical support for alleviating the environmental hazards of using PAEs.

Topomer CoMFA and HQSAR Study on Benzimidazole Derivative as NS5B Polymerase Inhibitor

Background:

In recent years, the number of people infected with the hepatitis C virus (HCV) is increasing rapidly. This has become a major threat to global health, therefore, new anti- HCV drugs are urgently needed. HCV NS5B polymerase is an RNA-dependent RNA polymerase (RdRp), which plays an important role in virus replication, and can effectively prevent the replication of HCV sub-genomic RNA in daughter cells. It is considered a very promising HCV therapeutic target for the design of anti-HCV drugs.

Methods:

In order to explore the relationship between the structure of benzimidazole derivative and its inhibitory activity on NS5B polymerase, holographic quantitative structure-activity relationship (HQSAR) and Topomer comparative molecular field analysis (CoMFA) were used to establish benzimidazole QSAR model of derivative inhibitors.

Results:

The results show that for the Topomer CoMFA model, the cross-validation coefficient q2 value is 0.883, and the non-cross-validation coefficient r2 value is 0.975. The model is reasonable, reliable, and has a good predictive ability. For the HQSAR model, the cross-validated q2 value is 0.922, and the uncross-validated r2 value is 0.971, indicating that the model data fit well and has a high predictive ability. Through the analysis of the contour map and color code diagram, 40 new benzimidazole inhibitor molecules were designed, and all of them have higher activity than template molecules, and the new molecules have significant interaction sites with protein 3SKE.

Conclusion:

The 3D-QSAR model established by Topomer CoMFA and HQSAR has good prediction results and the statistical verification is valid. The newly designed molecules and docking results provide theoretical guidance for the synthesis of new NS5B polymerase inhibitors and for the identification of key residues that the inhibitors bind to NS5B, which helps to better understand their inhibitory mechanism. These findings are helpful for the development of new anti-HCV drugs.