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.

Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

Computational Study and Modified Design of Selective Dopamine D3 Receptor Agonists

Dopamine D3 receptor (D3 R) is considered as a potential target for the treatment of nervous system disorders, such as Parkinson's disease. Current research interests primarily focus on the discovery and design of potent D3 agonists. In this work, we selected 40 D3 R agonists as the research system. Comparative molecular field analysis (CoMFA) of three-dimensional quantitative structure-activity relationship (3D-QSAR), structure-selectivity relationship (3D-QSSR), and molecular docking was performed on D3 receptor agonists to obtain the details at atomic level. The results indicated that both the CoMFA model (r(2) = 0.982, q(2) = 0.503, rpred2 = 0.893, SEE  = 0.057, F = 166.308) for structure-activity and (r(2) = 0.876, q(2) = 0.436, rpred2 = 0.828, F = 52.645) for structure-selectivity have good predictive capabilities. Furthermore, docking studies on three compounds binding to D3 receptor were performed to analyze the binding modes and interactions. The results elucidate that agonists formed hydrogen bond and hydrophobic interactions with key residues. Finally, we designed six molecules under the guidance of 3D-QSAR/QSSR models. The activity and selectivity of designed molecules have been improved, and ADMET properties demonstrate they have low probability of hepatotoxicity (<0.5). These results from 3D-QSAR/QSSR and docking studies have great significance for designing novel dopamine D3 selective agonists in the future.

Molecular modeling studies, synthesis and biological evaluation of dabigatran analogues as thrombin inhibitors

In this work, 48 thrombin inhibitors based on the structural scaffold of dabigatran were analyzed using a combination of molecular modeling techniques. We generated three-dimensional quantitative structure-activity relationship (3D-QSAR) models based on three alignments for both comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) to highlight the structural requirements for thrombin protein inhibition. In addition to the 3D-QSAR study, Topomer CoMFA model also was established with a higher leave-one-out cross-validation q(2) and a non-cross-validation r(2), which suggest that the three models have good predictive ability. The results indicated that the steric, hydrophobic and electrostatic fields play key roles in QSAR model. Furthermore, we employed molecular docking and re-docking simulation explored the binding relationship of the ligand and the receptor protein in detail. Molecular docking simulations identified several key interactions that were also indicated through 3D-QSAR analysis. On the basis of the obtained results, two compounds were designed and predicted by three models, the biological evaluation in vitro (IC50) demonstrated that these molecular models were effective for the development of novel potent thrombin inhibitors.

Molecular modeling studies of [6,6,5] Tricyclic Fused Oxazolidinones as FXa inhibitors using 3D-QSAR, Topomer CoMFA, molecular docking and molecular dynamics simulations

Coagulation factor Xa (Factor Xa, FXa) is a particularly promising target for novel anticoagulant therapy. The first oral factor Xa inhibitor has been approved in the EU and Canada in 2008. In this work, 38 [6,6,5] Tricyclic Fused Oxazolidinones were studied using a combination of molecular modeling techniques including three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, molecular dynamics and Topomer CoMFA (comparative molecular field analysis) were used to build 3D-QSAR models. The results show that the best CoMFA model has q(2)=0.511 and r(2)=0.984, the best CoMSIA (comparative molecular similarity indices analysis) model has q(2)=0.700 and r(2)=0.993 and the Topomer CoMFA analysis has q(2)=0.377 and r(2)=0.886. The results indicated the steric, hydrophobic, H-acceptor and electrostatic fields play key roles in models. Molecular docking and molecular dynamics explored the binding relationship of the ligand and the receptor protein.

Probing the binding mechanism of novel dual NF-κB/AP-1 inhibitors by 3D-QSAR, docking and molecular dynamics simulations

Potent dual NF-κB/AP-1 inhibitors could effectively treat immunoinflammatory diseases. An integrated computational study was carried out to identify the most favourable binding sites, the structural features and the interaction mechanisms.