QSAR Study on Potent Derivatives with Anti-TB Activity: A Review

Tuberculosis (TB), caused by Mycobacterium tuberculosis, continues to pose significant global health challenges, exacerbated by the rise of drug-resistant strains. The development of new anti-TB agents is crucial, and Quantitative Structure-Activity Relationship (QSAR) modelling has emerged as a powerful tool in this endeavour. This review summarizes recent advances in QSAR studies focused on potent derivatives with anti-TB activity. It discusses key molecular descriptors that correlate with biological efficacy, including topological, electronic, and steric properties. The paper also highlights successful predictive models that have facilitated the identification and optimization of novel compounds. Additionally, challenges such as data quality, model validation, and the complexity of biological systems are addressed. Future directions include the integration of machine learning techniques and omit data to enhance predictive accuracy and the discovery of new anti-TB agents. Overall, QSAR methodologies represent a vital approach to accelerating drug discovery and combating tuberculosis effectively.