A Clinical Prediction Model to Estimate the Risk for Coarctation of the Aorta: From Fetal to Newborn Life

Zhu, Mei; Liang, Hao; Feng, Jiaming; Zhang, Nan; Wang, Ximing; Wang, Yue-Mei; Yu, Yonghui; Wang, An-Biao

doi:10.21203/rs.3.rs-724289/v1

Cited by 1 publication

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“…Computer-aided drug design (CADD) is an effective tool for speeding up drug discovery and development, and has become an important basis for rational drug design [11]. Quantitative structure-activity relationship (QSAR) technology is based on advanced modeling tools for drug design, which can not only provide basic information for designing more effective and safer drugs, but also predict the biological activity of drugs based on their chemical structure [12]. We selected a series of derivatives containing benzoxaborole as the core structure to construct the QSAR model.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Binding Mechanism of Novel T. Brucei Leucine tRNA Synthase Inhibitors Based on QSAR Modeling, Molecular Docking, ADMET Prediction and Molecular Dynamics Simulations

Zhang

Wang

Tong

2023

Preprint

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Leucyl-tRNA synthetase (LeuRS) has received increasing attention as a promising target for the treatment of African Trypanosomiasis. A series of new core structures containing benzoxaborole, in which boric acid is embedded in a five-membered ring, have been reported recently with potent antitrypanosomiasis activity. In this study, 47 human Trypanosoma brucei leucine tRNA synthetase inhibitors (TbLeuRS) were modeled by three-dimensional quantitative structure-activity relationship (3D-QSAR, Topomer CoMFA) and hologram quantitative structure-activity relationship (HQSAR). The constructed model was combined with calculation, including topomer search, molecular design, molecular docking, molecular dynamics (MD), free energy calculation and ADME/T prediction study, to clarify the binding mechanism and pharmacological action of inhibitors, and to design new antitrypanosomiasis drugs. The results show that the constructed QSAR model has good predictive ability (Topomer CoMFA: =q2=0.563, r2=0.906, HQSAR:q2=0.723, and r2=0.946). The skeleton of the template molecule was retained, and 70 small molecular compounds with novel structures were obtained after fragment replacement of the two groups. Ten inhibitors were obtained from these small molecule compounds after ADMET prediction, activity value prediction and ‘rule of five’ screening. Then molecular docking was performed, and four hit compounds (T10, T13, T32 and T61) were finally screened according to the score function. The docking results indicate that hydrogen bonding and hydrophobic interactions play an important role in improving the binding affinity of the inhibitor to hot residues around the binding pocket. Finally, the inhibitor was also found to be relatively stable in the binding pocket by MD simulations. This study is expected to provide new ideas for the further rational design of the activity prediction, molecular design and modification of novel and highly effective antitrypanosome drugs targeting LeuRS.

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Section: Introductionmentioning

confidence: 99%