A comparative study of topological entropy characterization and graph energy prediction for Marta variants of covalent organic frameworks DOI Creative Commons
Zahid Raza, Micheal Arockiaraj,

Aravindan Maaran

et al.

Frontiers in Chemistry, Journal Year: 2024, Volume and Issue: 12

Published: Dec. 20, 2024

Covalent organic frameworks are a novel class of porous polymers, notable for their crystalline structure, intricate frameworks, defined pore sizes, and capacity structural design, synthetic control, functional customization. This paper provides comprehensive analysis graph entropies hybrid topological descriptors, derived from geometric, harmonic, Zagreb indices. These descriptors applied to study two variations Marta covalent based on contorted hexabenzocoronenes. We also conduct comparative using scaled entropies, offering refined tools assessing the intrinsic topologies these networks. Additionally, used develop statistical models predicting energy in higher-dimensional Marta-COFs.

Language: Английский

Predictive analysis of vitiligo treatment drugs using degree and neighborhood degree-based topological descriptors DOI Creative Commons
Xiujun Zhang, Deepa Balasubramaniyan, C. Natarajan

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 12, 2025

Vitiligo is a chronic autoimmune condition that leads to the loss of skin pigmentation in certain areas due destruction melanocytes, which produce pigment. A topological index numerical value obtained from structure chemical graph and useful for studying theoretical characteristics organic molecules. It can also help determine physico-chemical biological aspects various drugs. This article uses novel neighborhood degree-based indices study vitiligo drugs demonstrates strong correlation with properties. Additionally, results are compared those through indices.

Language: Английский

Citations

0
Computational Analysis of Benzenoid Systems Using Valency‐Based Entropy Metrics and Topological Indices DOI Creative Commons
Muhammad Kamran, Muhammad Nadeem, Manal Elzain Mohamed Abdalla

et al.

Complexity, Journal Year: 2025, Volume and Issue: 2025(1)

Published: Jan. 1, 2025

Nanomaterials find application in electronics, drugs, and biology among other disciplines. Benzenoid systems with their homogeneous structures are especially fit for computer study because of predictable geometries. This work investigates computational analysis benzenoid using valency‐based entropy measurements degree‐based topological indices. Knowing these indices helps one to anticipate the reactivity stability related compounds. The main focus is on thermodynamic parameter entropy, which reveals how can modify hydrocarbon improve characteristics. In this work, combined facilitates prediction enhancement system physicochemical features. grasp possible applications nanotechnology medicine.

Language: Английский

Citations

0
Comparative analysis of topological entropy levels in covalent organic radical frameworks and mathematical models for predicting graph energy DOI
Xiujun Zhang, Micheal Arockiaraj,

Aravindan Maaran

et al.

Chemical Papers, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 11, 2025

Language: Английский

Citations

0
Eccentric indices based QSPR evaluation of drugs for schizophrenia treatment DOI Creative Commons

Muneeba Mansha,

Sarfraz Ahmad, Zahid Raza

et al.

Heliyon, Journal Year: 2025, Volume and Issue: 11(2), P. e42222 - e42222

Published: Jan. 1, 2025

Schizophrenia is a long-term, serious mental health condition that affects how person thinks, perceives, and behaves. This disorder often results in substantial difficulties social interactions work performance. Individuals with schizophrenia might appear disconnected from reality, causing significant distress both for themselves their Friends. Although symptoms of can vary to person, they typically fall into three main categories: cognitive, negative, psychotic. Creating computational tools find develop drugs has more interest the past few years. Regardless developments drug design, fundamental approach still uses topological descriptors. Topological indices are used estimate bioactivity chemical compounds QSAR/QSPR studies. In general, use quantitative structure-property relationship (QSPR), numerical values connected structures predict reactivity, stability, properties. focuses on calculating different eccentric (EIs), developing regression model thirteen anti-schizophrenia drugs, applying statistical methods establish linear between QSPR correlating properties indices. Statistical analysis shows p-values less than equals 0.05, f-test value (>2.5) , correlation r greater 0.7 validate calculations. The coefficient (r2) convenient tool evaluating models' quality. r2>0.7 essential good model. show significance results, while accuracy results. order fit models calculated index values, eight physicochemical examined. Drug like molar refractivity (cm3), refractive enthalpy (kJ/mol), melting, boiling flash points (°C), complexity, molecular weight all effectively estimated by By examining actual verified.

Language: Английский

Citations

0
On QSPR analysis of glaucoma drugs using machine learning with XGBoost and regression models DOI

Lina Huang,

Khawlah Alhulwah,

Muhammad Farhan Hanif

et al.

Computers in Biology and Medicine, Journal Year: 2025, Volume and Issue: 187, P. 109731 - 109731

Published: Jan. 28, 2025

Language: Английский

Citations

0
Predicting glass transition temperatures for structurally diverse polymers DOI
Xinliang Yu

Colloid & Polymer Science, Journal Year: 2025, Volume and Issue: unknown

Published: April 8, 2025

Language: Английский

Citations

0
Predicting Antibacterial Drugs Properties Using Graph Topological Indices and Machine Learning DOI Creative Commons
Muhammad Shafii Abubakar, Ejima Ojonugwa, Ridwan A. Sanusi

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 181420 - 181435

Published: Jan. 1, 2024

Language: Английский

Citations

1
QSAR Models for Predicting ERPG Toxicity Index of Aliphatic Compounds DOI
Xiutang Yuan, Wei Xing Zheng, Jianbo Shi

et al.

Russian Journal of General Chemistry, Journal Year: 2024, Volume and Issue: 94(5), P. 1167 - 1178

Published: May 1, 2024

Language: Английский

Citations

0
Application of machine learning in developing a quantitative structure–property relationship model for predicting the thermal decomposition temperature of nitrogen-rich energetic ionic salts DOI Creative Commons
Yunling Zhang, Fan Liang, Chao Su

et al.

RSC Advances, Journal Year: 2024, Volume and Issue: 14(51), P. 37737 - 37751

Published: Jan. 1, 2024

A reliable QSPR model of thermal decomposition temperature ( T d ) was built and developed using support vector machine (SVM) learning technology to predict the property newly designed nitrogen-rich energetic ionic salts.

Language: Английский

Citations

0
A comparative study of topological entropy characterization and graph energy prediction for Marta variants of covalent organic frameworks DOI Creative Commons
Zahid Raza, Micheal Arockiaraj,

Aravindan Maaran

et al.

Frontiers in Chemistry, Journal Year: 2024, Volume and Issue: 12

Published: Dec. 20, 2024

Covalent organic frameworks are a novel class of porous polymers, notable for their crystalline structure, intricate frameworks, defined pore sizes, and capacity structural design, synthetic control, functional customization. This paper provides comprehensive analysis graph entropies hybrid topological descriptors, derived from geometric, harmonic, Zagreb indices. These descriptors applied to study two variations Marta covalent based on contorted hexabenzocoronenes. We also conduct comparative using scaled entropies, offering refined tools assessing the intrinsic topologies these networks. Additionally, used develop statistical models predicting energy in higher-dimensional Marta-COFs.

Language: Английский

Citations

0