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In-silico Evaluation of Pyrrolopyrimidine Derivatives as Novel Bruton's Tyrosine Kinase (BTK) Inhibitors for B-Cell Malignancies
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DOI：10.1142/S2737416526300014.png)
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Abstract
En 中文
Aberrant expression of Bruton's tyrosine kinase (BTK) plays a major role in the progression of B-cell malignancies and autoimmune disorders, highlighting the need for effective and selective BTK inhibitors. A series of 45 pyrrolopyrimidine derivatives were selected for in-silico study from the literature. A 3D-QSAR and pharmacophore model was utilized to design novel compounds; they were subsequently generated through R-group enumeration based on the QSAR data and further evaluated through molecular docking and virtual screening. The model AADHR_1 was chosen as the best pharmacophore model. The 3D-QSAR analysis yielded statistically robust models. The atom-based model exhibited an excellent correlation coefficient (R2 = 0.8831) and cross-validation coefficient (Q2 = 0.8675), while the field-based model demonstrated a correlation coefficient of R2 = 0.8498 and Q2 = 0.855. A total of 1752 compounds were generated through R-group enumeration for the production of new compounds. Among them, R1 demonstrated the best binding affinity (-7.87 kcal/mol, PDB ID: 5P9J) with key binding interactions at TYR551, GLN412 and LYS430. Molecular dynamics (MD) simulations further confirmed the stability of these interactions under dynamic conditions. Furthermore, ADME and physiochemical properties confirmed drug likeness, bioavailability and a favorable pharmacokinetic profile of the designed compounds. Among the designed compounds, R1 exhibited the highest binding affinity, superior interaction stability in MD simulations and balanced ADME characteristics, making it the most potent. Overall, this study provides considerable insights into the rational computational design of pyrrolopyrimidine-based BTK inhibitors for advancing these candidates into experimental validation and clinical advancement.
Keywords:
BTK inhibitors
pyrrolopyrimidine
3D-QSAR
molecular dynamics
Journal
J
IF:
2.3
Papers:
98
Citations:
0
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Cited Papers