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Ghods, Masoud, Esmaeili, Arezo, Ramezani Tousi, Jaber. (1405). Modeling Structure-Property Relationships of Respiratory Drugs: A QSPR Investigation Using Topological indices. پژوهشنامه مدیریت اجرایی, (), -. doi: 10.22080/cjms.2026.31578.1840
Masoud Ghods; Arezo Esmaeili; Jaber Ramezani Tousi. "Modeling Structure-Property Relationships of Respiratory Drugs: A QSPR Investigation Using Topological indices". پژوهشنامه مدیریت اجرایی, , , 1405, -. doi: 10.22080/cjms.2026.31578.1840
Ghods, Masoud, Esmaeili, Arezo, Ramezani Tousi, Jaber. (1405). 'Modeling Structure-Property Relationships of Respiratory Drugs: A QSPR Investigation Using Topological indices', پژوهشنامه مدیریت اجرایی, (), pp. -. doi: 10.22080/cjms.2026.31578.1840
Ghods, Masoud, Esmaeili, Arezo, Ramezani Tousi, Jaber. Modeling Structure-Property Relationships of Respiratory Drugs: A QSPR Investigation Using Topological indices. پژوهشنامه مدیریت اجرایی, 1405; (): -. doi: 10.22080/cjms.2026.31578.1840

Modeling Structure-Property Relationships of Respiratory Drugs: A QSPR Investigation Using Topological indices

Caspian Journal of Mathematical Sciences
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 08 مرداد 1405
نوع مقاله: Research Articles
شناسه دیجیتال (DOI): 10.22080/cjms.2026.31578.1840
نویسندگان
Masoud Ghods* 1؛ Arezo Esmaeili2؛ Jaber Ramezani Tousi3
1Department of Mathematics, Statistics, and Computer Science Semnan University Semnan, Iran
2Department of Applied Mathematics, Semnan University, Semnan 35131-19111, Iran
3Department of Mathematics, University of Mazandaran, Babolsar, 4741613534, Iran
تاریخ دریافت: 01 اردیبهشت 1405،  تاریخ بازنگری: 10 خرداد 1405،  تاریخ پذیرش: 11 خرداد 1405 
چکیده
Topological indices (TIs) are quantitative descriptors derived from molecular graphs that encode structural information relevant to physicochemical and pharmacological behavior of drug compounds. Within Quantitative Structure–Property Relationship (QSPR) frameworks, they provide an efficient and interpretable route for rational drug design. Here, a QSPR study is reported for twelve anti-asthma and anti-allergy drug candidates using seventeen degree-based topological indices. Molecular structures were modeled as vertex-weighted graphs, and the indices were assessed for predicting eight key physicochemical properties: boiling point (BP), enthalpy of vaporization (EV), flash point (FP), refractive index (IR), molar refractivity (MR), polar surface area (PSA), polarizability (PO), and molar volume (MV). Linear regression models were developed and validated by leave-one-out cross-validation (LOOCV). The harmonic index (H) provided the strongest correlations with MR and PO (r = 0.988; R² = 0.975; Q² = 0.961), whereas the symmetric division index (SDD) best predicted MV (r = 0.873; R² = 0.763). All models were statistically significant (p < 0.05), with coefficients of determination from 0.659 to 0.975. Cross-validation supported robustness and generalizability (Q² > 0.70 for principal endpoints). Overall, degree-based indices achieve accuracy comparable to complex machine-learning methods while retaining transparency and low computational cost for virtual screening in respiratory pharmacotherapy.
کلیدواژه‌ها
QSPR؛ topological indices؛ degree-based descriptors؛ anti-asthma drugs
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تعداد مشاهده مقاله: 6


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