Computational approaches in drug chemistry leveraging python powered QSPR study of antimalaria compounds by using artificial neural networks

The application of Machine Learning has become a revolutionary instrument in the domain of pharmaceutical research. Machine learning enables the modelling of Quantitative Structure Property Relationship, a crucial task in forecasting the physiochemical characteristics of drugs. In this study we util...

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Bibliographic Details
Published in:	Scientific reports Vol. 15; no. 1; pp. 19307 - 18
Main Authors:	Ahmed, Wakeel, Ashraf, Tamseela, Saleem, Maliha Tehseen, Mahmoud, Emad E., Ali, Kashif, Zaman, Shahid, Belay, Melaku Berhe
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 02.06.2025 Nature Publishing Group Nature Portfolio
Subjects:	631/154 631/45 639/638 692/699 Algorithms Anti-malaria drugs Antimalarial agents Antimalarials - chemistry Antimalarials - pharmacology Antiparasitic agents Artificial Neural Networks Drug development Enzymes Humanities and Social Sciences Humans Learning algorithms Machine Learning Malaria multidisciplinary Neural networks Neural Networks, Computer Observational learning Pharmacokinetics Physicochemical properties Python Algorithm QSPR analysis Quantitative Structure-Activity Relationship Random Forest Regression analysis Science Science (multidisciplinary) Vector-borne diseases QSPR analysis Python Algorithm Artificial Neural Networks Machine Learning Anti-malaria drugs Random Forest
ISSN:	2045-2322, 2045-2322
Online Access:	Get full text
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