Investigating the binding mechanism of sphingosine kinase 1/2 inhibitors: Insights into subtype selectivity by homology modeling, molecular dynamics simulation and free energy calculation studies

Zhang, Maoyu; Shang, Yanguo; Jiang, Kaixuan; Jia, Yihe; Yang, Kan

doi:10.1016/j.molstruc.2020.127900

Cited by 12 publications

(4 citation statements)

References 42 publications

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“…In MMGBSA method, the binding free energy was estimated by summing the following contributions: ΔG bind = ΔE MM + ΔG polar + ΔG nonpolar − TΔS, where ΔE MM is the gas phase interaction energy including the electrostatic and the van der Waals interactions; ΔG polar is the polar contributions to the desolvation free energy, which is calculated with the GB equation; ΔG nonpolar is the nonpolar component of the desolvation free energy, which is estimated empirically by using the solvent accessible surface area; TΔS represents the change of the conformational entropy. In this study, the contribution of the conformational entropy was not considered, because the calculation of this term usually brings large errors for large-size systems like those studied in this work [48][49][50][51][52], which do not improve the calculation accuracy of the binding free energy. In order to explore the molecular mechanism for the influences of E484K mutation on the binding free energy, the MMGBSA calculation results were also decomposed into per-residue contributions.…”

Section: Molecular Mechanics-generalized Born Surface Area (Mmgbsa) C...mentioning

confidence: 99%

E484K mutation in SARS-CoV-2 RBD enhances binding affinity with hACE2 but reduces interactions with neutralizing antibodies and nanobodies: Binding free energy calculation studies

Wang

Liang

Jin

et al. 2021

Journal of Molecular Graphics and Modelling

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Section: Molecular Mechanics-generalized Born Surface Area (Mmgbsa) C...mentioning

confidence: 99%

E484K mutation in SARS-CoV-2 RBD enhances binding affinity with hACE2 but reduces interactions with neutralizing antibodies and nanobodies: Binding free energy calculation studies

Wang

Liang

Jin

et al. 2021

Journal of Molecular Graphics and Modelling

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“…is the nonpolar component of the desolvation free energy, which is estimated empirically by using the solvent accessible surface area; ∆ represents the change of the conformational entropy. In this study, the contribution of the conformational entropy was not considered, because the calculation of this term usually brings large errors for large-size systems like those studied in this work [48][49][50][51][52], which do not improve the calculation accuracy of the binding free energy. In order to explore the molecular mechanism for the influences of E484K mutation on the binding free energy, the MMGBSA calculation results were also decomposed into per-residue contributions.…”

Section: Molecular Mechanics-generalized Born Surface Area (Mmgbsa) Cmentioning

confidence: 99%

E484K mutation in SARS-CoV-2 RBD enhances binding affinity with hACE2 but reduces interactions with neutralizing antibodies and nanobodies: Binding free energy calculation studies

Wang

Liang

Jin

et al. 2021

Preprint

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The pandemic of the COVID-19 disease caused by SARS-CoV-2 has led to more than 100 million infections and over 2 million deaths worldwide. The progress in the developments of effective vaccines and neutralizing antibody therapeutics brings hopes to eliminate the threat of COVID-19. However, SARS-CoV-2 continues to mutate, and several new variants have been emerged. Among the various naturally-occurring mutations, the E484K mutation shared by both the 501Y.V2 and 501Y.V3 variants attracted serious concerns, which may potentially enhance the receptor binding affinity and reduce the immune response. In the present study, the molecular mechanism behind the impacts of E484K mutation on the binding affinity of the receptor-binding domain (RBD) with the receptor human angiotensin-converting enzyme 2 (hACE2) was investigated by using the molecular dynamics (MD) simulations combined with the molecular mechanics-generalized Born surface area (MMGBSA) method. Our results indicate that the E484K mutation results in more favorable electrostatic interactions compensating the burial of the charged and polar groups upon the binding of RBD with hACE2, which significantly improves the RBD-hACE2 binding affinity. Besides that, the E484K mutation also causes the conformational rearrangements of the loop region containing the mutant residue, which leads to more tight binding interface of RBD with hACE2 and formation of some new hydrogen bonds. The more tight binding interface and the new hydrogen bonds formation also contribute to the improved binding affinity of RBD to the receptor hACE2. In addition, six neutralizing antibodies and nanobodies complexed with RBD were selected to explore the effects of E484K mutation on the recognition of these antibodies to RBD. The simulation results show that the E484K mutation significantly reduces the binding affinities to RBD for most of the studied neutralizing antibodies, and the decrease in the binding affinities is mainly owing to the unfavorable electrostatic interactions caused by the mutation. Our studies revealed that the E484K mutation may improve the binding affinity between RBD and the receptor hACE2, implying more transmissibility of the E484K-containing variants, and weaken the binding affinities between RBD and the studied neutralizing antibodies, indicating reduced effectiveness of these antibodies. Our results provide valuable information for the effective vaccine development and antibody drugs design.

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“…Third, the CASP dataset consists of structural models predicted by both modeling methods. Structure prediction methods are often used in drug discovery [21][22][23][24][25]. However, homology modeling has mainly been used because of its reliability.…”

Section: Introductionmentioning

confidence: 99%

A Benchmark Dataset for Evaluating Practical Performance of Model Quality Assessment of Homology Models

Takei

Ishida

2022

Bioengineering

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Protein structure prediction is an important issue in structural bioinformatics. In this process, model quality assessment (MQA), which estimates the accuracy of the predicted structure, is also practically important. Currently, the most commonly used dataset to evaluate the performance of MQA is the critical assessment of the protein structure prediction (CASP) dataset. However, the CASP dataset does not contain enough targets with high-quality models, and thus cannot sufficiently evaluate the MQA performance in practical use. Additionally, most application studies employ homology modeling because of its reliability. However, the CASP dataset includes models generated by de novo methods, which may lead to the mis-estimation of MQA performance. In this study, we created new benchmark datasets, named a homology models dataset for model quality assessment (HMDM), that contain targets with high-quality models derived using homology modeling. We then benchmarked the performance of the MQA methods using the new datasets and compared their performance to that of the classical selection based on the sequence identity of the template proteins. The results showed that model selection by the latest MQA methods using deep learning is better than selection by template sequence identity and classical statistical potentials. Using HMDM, it is possible to verify the MQA performance for high-accuracy homology models.

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Investigating the binding mechanism of sphingosine kinase 1/2 inhibitors: Insights into subtype selectivity by homology modeling, molecular dynamics simulation and free energy calculation studies

Cited by 12 publications

References 42 publications

E484K mutation in SARS-CoV-2 RBD enhances binding affinity with hACE2 but reduces interactions with neutralizing antibodies and nanobodies: Binding free energy calculation studies

E484K mutation in SARS-CoV-2 RBD enhances binding affinity with hACE2 but reduces interactions with neutralizing antibodies and nanobodies: Binding free energy calculation studies

E484K mutation in SARS-CoV-2 RBD enhances binding affinity with hACE2 but reduces interactions with neutralizing antibodies and nanobodies: Binding free energy calculation studies

A Benchmark Dataset for Evaluating Practical Performance of Model Quality Assessment of Homology Models

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