QSAR Evaluations to Unravel the Structural Features in Lysine-Specific Histone Demethylase 1A Inhibitors for Novel Anticancer Lead Development Supported by Molecular Docking, MD Simulation and MMGBSA
Using 84 structurally diverse and experimentally validated LSD1/KDM1A inhibitors, quantitative structure–activity relationship (QSAR) models were built by OECD requirements. In the QSAR analysis, certainly significant and understated pharmacophoric features were identified as critical for LSD1 inhib...
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MDPI AG
2022-07-01
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| Series: | Molecules |
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| Online Access: | https://www.mdpi.com/1420-3049/27/15/4758 |
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| author | Rahul D. Jawarkar Ravindra L. Bakal Nobendu Mukherjee Arabinda Ghosh Magdi E. A. Zaki Sami A. AL-Hussain Aamal A. Al-Mutairi Abdul Samad Ajaykumar Gandhi Vijay H. Masand |
| author_facet | Rahul D. Jawarkar Ravindra L. Bakal Nobendu Mukherjee Arabinda Ghosh Magdi E. A. Zaki Sami A. AL-Hussain Aamal A. Al-Mutairi Abdul Samad Ajaykumar Gandhi Vijay H. Masand |
| author_sort | Rahul D. Jawarkar |
| collection | DOAJ |
| description | Using 84 structurally diverse and experimentally validated LSD1/KDM1A inhibitors, quantitative structure–activity relationship (QSAR) models were built by OECD requirements. In the QSAR analysis, certainly significant and understated pharmacophoric features were identified as critical for LSD1 inhibition, such as a ring Carbon atom with exactly six bonds from a Nitrogen atom, partial charges of lipophilic atoms within eight bonds from a ring Sulphur atom, a non-ring Oxygen atom exactly nine bonds from the amide Nitrogen, etc. The genetic algorithm–multi-linear regression (GA-MLR) and double cross-validation criteria were used to create robust QSAR models with high predictability. In this study, two QSAR models were developed, with fitting parameters like R<sup>2</sup> = 0.83–0.81, F = 61.22–67.96, internal validation parameters such as Q<sup>2</sup><sub>LOO</sub> = 0.79–0.77, Q<sup>2</sup><sub>LMO</sub> = 0.78–0.76, CCC<sub>cv</sub> = 0.89–0.88, and external validation parameters such as, R2ext = 0.82 and CCCex = 0.90. In terms of mechanistic interpretation and statistical analysis, both QSAR models are well-balanced. Furthermore, utilizing the pharmacophoric features revealed by QSAR modelling, molecular docking experiments corroborated with the most active compound’s binding to the LSD1 receptor. The docking results are then refined using Molecular dynamic simulation and MMGBSA analysis. As a consequence, the findings of the study can be used to produce LSD1/KDM1A inhibitors as anticancer leads. |
| first_indexed | 2024-03-09T05:10:49Z |
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| id | doaj.art-33c24f28429b457cb18ad11f3a4b7291 |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-03-09T05:10:49Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
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| series | Molecules |
| spelling | doaj.art-33c24f28429b457cb18ad11f3a4b72912023-12-03T12:49:30ZengMDPI AGMolecules1420-30492022-07-012715475810.3390/molecules27154758QSAR Evaluations to Unravel the Structural Features in Lysine-Specific Histone Demethylase 1A Inhibitors for Novel Anticancer Lead Development Supported by Molecular Docking, MD Simulation and MMGBSARahul D. Jawarkar0Ravindra L. Bakal1Nobendu Mukherjee2Arabinda Ghosh3Magdi E. A. Zaki4Sami A. AL-Hussain5Aamal A. Al-Mutairi6Abdul Samad7Ajaykumar Gandhi8Vijay H. Masand9Department of Medicinal Chemistry and Drug Discovery, Dr Rajendra Gode Institute of Pharmacy, University Mardi Road, Amravati 444603, IndiaDepartment of Medicinal Chemistry and Drug Discovery, Dr Rajendra Gode Institute of Pharmacy, University Mardi Road, Amravati 444603, IndiaDepartment of Microbiology, Ramakrishna Mission Vivekananda Centenary College, Kolkata 700118, IndiaMicrobiology Division, Department of Botany, Gauhati University, Guwahati 781014, IndiaDepartment of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 13318, Saudi ArabiaDepartment of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 13318, Saudi ArabiaDepartment of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 13318, Saudi ArabiaDepartment of Pharmaceutical Chemistry, Faculty of Pharmacy, Tishk International University, Erbil 44001, IraqDepartment of Chemistry, Government Arts and Science College, Karur 639005, IndiaDepartment of Chemistry, Vidyabharati Mahavidyalalya, Camp, Amravati 444602, IndiaUsing 84 structurally diverse and experimentally validated LSD1/KDM1A inhibitors, quantitative structure–activity relationship (QSAR) models were built by OECD requirements. In the QSAR analysis, certainly significant and understated pharmacophoric features were identified as critical for LSD1 inhibition, such as a ring Carbon atom with exactly six bonds from a Nitrogen atom, partial charges of lipophilic atoms within eight bonds from a ring Sulphur atom, a non-ring Oxygen atom exactly nine bonds from the amide Nitrogen, etc. The genetic algorithm–multi-linear regression (GA-MLR) and double cross-validation criteria were used to create robust QSAR models with high predictability. In this study, two QSAR models were developed, with fitting parameters like R<sup>2</sup> = 0.83–0.81, F = 61.22–67.96, internal validation parameters such as Q<sup>2</sup><sub>LOO</sub> = 0.79–0.77, Q<sup>2</sup><sub>LMO</sub> = 0.78–0.76, CCC<sub>cv</sub> = 0.89–0.88, and external validation parameters such as, R2ext = 0.82 and CCCex = 0.90. In terms of mechanistic interpretation and statistical analysis, both QSAR models are well-balanced. Furthermore, utilizing the pharmacophoric features revealed by QSAR modelling, molecular docking experiments corroborated with the most active compound’s binding to the LSD1 receptor. The docking results are then refined using Molecular dynamic simulation and MMGBSA analysis. As a consequence, the findings of the study can be used to produce LSD1/KDM1A inhibitors as anticancer leads.https://www.mdpi.com/1420-3049/27/15/4758LSD1KDM1AQSARanticancermolecular dockingMD simulation |
| spellingShingle | Rahul D. Jawarkar Ravindra L. Bakal Nobendu Mukherjee Arabinda Ghosh Magdi E. A. Zaki Sami A. AL-Hussain Aamal A. Al-Mutairi Abdul Samad Ajaykumar Gandhi Vijay H. Masand QSAR Evaluations to Unravel the Structural Features in Lysine-Specific Histone Demethylase 1A Inhibitors for Novel Anticancer Lead Development Supported by Molecular Docking, MD Simulation and MMGBSA Molecules LSD1 KDM1A QSAR anticancer molecular docking MD simulation |
| title | QSAR Evaluations to Unravel the Structural Features in Lysine-Specific Histone Demethylase 1A Inhibitors for Novel Anticancer Lead Development Supported by Molecular Docking, MD Simulation and MMGBSA |
| title_full | QSAR Evaluations to Unravel the Structural Features in Lysine-Specific Histone Demethylase 1A Inhibitors for Novel Anticancer Lead Development Supported by Molecular Docking, MD Simulation and MMGBSA |
| title_fullStr | QSAR Evaluations to Unravel the Structural Features in Lysine-Specific Histone Demethylase 1A Inhibitors for Novel Anticancer Lead Development Supported by Molecular Docking, MD Simulation and MMGBSA |
| title_full_unstemmed | QSAR Evaluations to Unravel the Structural Features in Lysine-Specific Histone Demethylase 1A Inhibitors for Novel Anticancer Lead Development Supported by Molecular Docking, MD Simulation and MMGBSA |
| title_short | QSAR Evaluations to Unravel the Structural Features in Lysine-Specific Histone Demethylase 1A Inhibitors for Novel Anticancer Lead Development Supported by Molecular Docking, MD Simulation and MMGBSA |
| title_sort | qsar evaluations to unravel the structural features in lysine specific histone demethylase 1a inhibitors for novel anticancer lead development supported by molecular docking md simulation and mmgbsa |
| topic | LSD1 KDM1A QSAR anticancer molecular docking MD simulation |
| url | https://www.mdpi.com/1420-3049/27/15/4758 |
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