Design of novel BRC1A target inhibitors: Docking simulation, QSAR modeling, MD simulation and Pharmacokinetics profiling

Breast cancer is the leading recurrent cancer in female, second in mortality, with 1.3 million annual cases, demanding effective interventions. In this study, novel benzoylhydrazone analogs as BRC1A target inhibitors were proposed based on the structure-based design approach. Compound 26 emerged as the template, exhibiting the highest binding affinities of -102.47 and -87.059 kcal/mol. The inhibitive activity of the molecules was predicted using a developed QSAR model, which demonstrated strong statistical performance. The model achieved an internal correlation coefficient (R²) of 0.823, an adjusted R² (R²adj) of 0.779, a cross-validation coefficient (Q²cv) of 0.508, and an external prediction correlation coefficient (R²pred) of 0.643. Seven novel compounds were designed by incorporating amide, hydroxyl, unsubstituted, and methyl-substituted amino groups into the core structure. These new derivatives exhibited better affinities, ranging from -112.148 to -124.542 kcal/mol and -87.627 to -99.128 kcal/mol, surpassing the template. Furthermore, these compounds showed enhanced activity, with pIC 50 values ranging from 7.480 to 10.499, compared to the template's pIC 50 of 6.138. Molecular dynamics simulations confirmed better interactions of these molecules to the BRC1A target. Pharmacological assessments suggested compliance with the drug-like filters, indicating favorable pharmacological and oral safety profiles. Overall, these compounds exhibit promising characteristics as potential BRC1A inhibitors, warranting further investigation.

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Publication Details

Journal
Scientific African
Published
2024-12-27
DOI
https://doi.org/10.1016/j.sciaf.2024.e02522
Citations
2
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.72
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article

Design of novel BRC1A target inhibitors: Docking simulation, QSAR modeling, MD simulation and Pharmacokinetics profiling

Zakari Ya’u Ibrahim, Anshuman Chandra, Sagiru Hamza Abdullahi, Nainee Goyal et al.
2 citations
Scientific African
Computational Drug Discovery Methods
0.72
article

Design of novel BRC1A target inhibitors: Docking simulation, QSAR modeling, MD simulation and Pharmacokinetics profiling

Zakari Ya’u Ibrahim, Anshuman Chandra, Sagiru Hamza Abdullahi, Nainee Goyal, Fabian Audu Ugbe, Saudatu Ja'afaru Chinade
article en
2 citations

Abstract

Breast cancer is the leading recurrent cancer in female, second in mortality, with 1.3 million annual cases, demanding effective interventions. In this study, novel benzoylhydrazone analogs as BRC1A target inhibitors were proposed based on the structure-based design approach. Compound 26 emerged as the template, exhibiting the highest binding affinities of -102.47 and -87.059 kcal/mol. The inhibitive activity of the molecules was predicted using a developed QSAR model, which demonstrated strong statistical performance. The model achieved an internal correlation coefficient (R²) of 0.823, an adjusted R² (R²adj) of 0.779, a cross-validation coefficient (Q²cv) of 0.508, and an external prediction correlation coefficient (R²pred) of 0.643. Seven novel compounds were designed by incorporating amide, hydroxyl, unsubstituted, and methyl-substituted amino groups into the core structure. These new derivatives exhibited better affinities, ranging from -112.148 to -124.542 kcal/mol and -87.627 to -99.128 kcal/mol, surpassing the template. Furthermore, these compounds showed enhanced activity, with pIC 50 values ranging from 7.480 to 10.499, compared to the template's pIC 50 of 6.138. Molecular dynamics simulations confirmed better interactions of these molecules to the BRC1A target. Pharmacological assessments suggested compliance with the drug-like filters, indicating favorable pharmacological and oral safety profiles. Overall, these compounds exhibit promising characteristics as potential BRC1A inhibitors, warranting further investigation.

Scientific AfricanVol. 27
Ahmadu Bello University (NG), Jawaharlal Nehru University (IN), Gautam Buddha University (IN), University of Abuja (NG)
Openalex Percentile: Top 24%
Computational Drug Discovery Methods
0.72
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