3D-QSAR, molecular docking, and molecular dynamics simulation study of thieno[3,2-<i>b</i>]pyrrole-5-carboxamide derivatives as LSD1 inhibitors

Xu, Yongtao; He, Zihao; Liu, Hongyi; Chen, Yifan; Gao, Yunzhen; Zhang, Songjie; Wang, Meiting; Lü, Xiaoyuan; Wang, Chang; Zhao, Zongya; Liu, Yan; Zhao, Junqiang; Yu, Yi; Yang, Min

doi:10.1039/c9ra10085g

“…In Equation ( 2 ), the SD index shows the squared deviation sum for molecules amongst the test group biological activities and training group mean activities [ 51 ]. Also, the PRESS index indicates the squared deviation summation amongst actual and predicted activity values for molecules individually in the test group.…”

Section: Methodsmentioning

confidence: 99%

“…The 3D-QSAR model with the sixth component of the PLS factor was considered as the best for 1,2,4-oxadiazole derivatives. This model was approved for its precision in the ligand activity estimate in the training group [ 51 ]. Scatter plots for experimental and predicted activities of ligands showed a notable linear correlation.…”

Section: Methodsmentioning

confidence: 99%

3D-QSAR Studies of 1,2,4-Oxadiazole Derivatives as Sortase A Inhibitors

Shakour

¹

,

Hadizadeh

²

,

Kesharwani

³

et al. 2021

BioMed Research International

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Sortase A (SrtA) is an enzyme that catalyzes the attachment of proteins to the cell wall of Gram-positive bacterial membrane, preventing the spread of pathogenic bacterial strains. Here, one class of oxadiazole compounds was distinguished as an efficient inhibitor of SrtA via the “S. aureus Sortase A” substrate-based virtual screening. The current study on 3D-QSAR was done by utilizing preparation of the structure in the Schrödinger software suite and an assessment of 120 derivatives with the crystal structure of 1,2,4-oxadiazole which was extracted from the PDB data bank. The docking operation of the best compound in terms of pMIC ( pMIC = 2.77 ) was done to determine the drug likeliness and binding form of 1,2,4-oxadiazole derivatives as antibiotics in the active site. Using the kNN-MFA way, seven models of 3D-QSAR were created and amongst them, and one model was selected as the best. The chosen model based on q 2 (pred_ r 2 ) and R 2 values related to the sixth factor of PLS illustrates better and more acceptable external and internal predictions. Values of crossvalidation (pred_ r 2 ), validation ( q 2 ), and F were observed 0.5479, 0.6319, and 179.0, respectively, for a test group including 24 molecules and the training group including 96 molecules. The external reliability outcomes showed that the acceptable and the selective 3D-QSAR model had a high predictive potential ( R 2 = 0.9235 ) which was confirmed by the Y -randomization test. Besides, the model applicability domain was described successfully to validate the estimation of the model.

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“…The strategy of combining molecular docking, molecular dynamics simulation, and QSAR analysis has emerged as a practical tool in the process of drug development through computational techniques. Its main advantage lies in improving the success rate of drug screening in less time and at a lower cost [ 10 ]. Molecular docking simulations are designed to determine the best ligand/target binding mode that generates the biological response.…”

Section: Introductionmentioning

confidence: 99%

Investigation of [3H]diazepam derivatives as allosteric modulators of GABAA receptor α1β2γ2 subtypes: combination of molecular docking/dynamic simulations, pharmacokinetics/drug-likeness prediction, and QSAR analysis

Djebaïli

¹

,

Kenouche

²

,

Daoud

³

et al. 2022

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In this paper, a data set of [ 3 H] diazepam derivatives was analyzed using various computational methods: molecular docking/dynamic simulations, and QSAR analysis. The main aims of these studies are to understand the binding mechanisms by which benzodiazepines allosterically modulate GABA A receptor α 1 β 2 γ 2 subtypes, from inducing neuronal inhibition at lower doses to the anesthetic effect at higher doses, and also, to define the structural requirements that contribute to improving the response of GABA A /α 1 β 2 γ 2 receptor to benzodiazepine drugs. The results of the molecular docking study allowed selecting Ro12-6377 and proflazepam as the best modulators for the four binding sites simultaneously. Subsequently, the stability of the selected complexes was investigated by performing molecular dynamics simulation. The latter confirmed the features of both modulators to exert direct effects on the chloride-channel lining residues. Pharmacokinetics and drug-likeness profile were assessed through in silico tool. Furthermore, a QSAR analysis was conducted using an improved vemolecular dynamics simulations proposed byrsion of PLS regression. The goodness of fit and the predictive power of the resulting PLS model were estimated according to internal and external validation parameters: R 2 = 0.632, R 2 adj = 0.584, F = 12.806; p- value = 6.2050e − 07, Q 2 loo = 0.639, and Q 2 F3 = 0.813. Clearly, the obtained results ensure the predictive ability of the developed QSAR model for the design of new high-potency benzodiazepine drugs. Supplementary Information The online version contains supplementary material available at 10.1007/s11224-022-02029-4.

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“…Another interesting subject in the drug discovery area is the prediction of designed compounds. The activity of these newly designed compounds could be predicted with QSAR, and their interactions with proteins of desired signaling pathways are predictable with molecular docking and molecular dynamics (MD) 26 . A crucial thing about newly designed compounds is the evaluation of their toxicity.…”

Section: Introductionmentioning

confidence: 99%

3D‐QSAR, molecular docking, molecular dynamics, and ADME/T analysis of marketed and newly designed flavonoids as inhibitors of Bcl‐2 family proteins for targeting U‐87 glioblastoma

Poustforoosh

¹

,

Faramarz

²

,

Nematollahi

³

et al. 2021

J of Cellular Biochemistry

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Glioblastoma is the most common and destructive brain tumor with increasing complexity. Flavonoids are versatile natural compounds with the approved anticancer activity, which could be considered as a potential treatment for glioblastoma. A quantitative structure‐activity relationship (QSAR) can provide adequate data for understanding the role of flavonoids structure against glioblastoma. The IC50 of various flavonoids for the U‐87 cell line was used to prepare an adequate three‐dimensional QSAR (3D‐QSAR) model. The validation of the model was carried out using some statistical parameters such as R2 and Q2. Based on the QSAR model, the activities of other marketed and newly designed flavonoids were predicted. Molecular docking study and molecular dynamics (MD) simulation were conducted for better recognition of the interactions between the most active compounds and Bcl‐2 family proteins. Moreover, an AMDE/T analysis was performed for the most active flavonoids. A reliable 3D‐QSAR was performed with R2 and Q2 of 0.91 and 0.82. The molecular docking study revealed that BCL‐XL has a higher binding affinity with the most active compounds, and the MD simulation showed that some residues of the BH3 domain, such as Phe97, Tyr101, Arg102, and Phe105 create remarkable hydrophobic interactions with the ligands. ADME/T analysis also showed the potential of the active compounds for further investigation. 3D‐QSAR study is a beneficial method to evaluate and design anticancer compounds. Considering the results of the molecular docking study, MD simulation, and ADME/T analysis, the designed compound 54 could be considered as a potential treatment for glioblastoma.

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3D-QSAR, molecular docking, and molecular dynamics simulation study of thieno[3,2-b]pyrrole-5-carboxamide derivatives as LSD1 inhibitors

Abstract: Novel LSD1 inhibitors with potential activity are designed using a series of computer-aided drug design methods.

Cited by 22 publications

References 51 publications

3D-QSAR Studies of 1,2,4-Oxadiazole Derivatives as Sortase A Inhibitors

3D-QSAR Studies of 1,2,4-Oxadiazole Derivatives as Sortase A Inhibitors

Investigation of [3H]diazepam derivatives as allosteric modulators of GABAA receptor α1β2γ2 subtypes: combination of molecular docking/dynamic simulations, pharmacokinetics/drug-likeness prediction, and QSAR analysis

3D‐QSAR, molecular docking, molecular dynamics, and ADME/T analysis of marketed and newly designed flavonoids as inhibitors of Bcl‐2 family proteins for targeting U‐87 glioblastoma

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