Tubulin inhibitors(University of Stellenbosch)

Leukemia is a type of cancer that affects the blood and bone marrow and characterized by the uncontrolled production and accumulation of blood cells. According to the World Health Organization (WHO), leukemia is among the fifteen most commonly diagnosed cancers worldwide and the eleventh leading cause of mortality. Tyrosine kinase inhibitors are the first-line choice for the treatment of acute or chronic leukemia. However, mutations in tyrosine kinase proteins are the major cause of resistance. Therefore, the discovery of new targeted antileukemic molecules is essential for the treatment of leukemia. Amongst the various tyrosine kinase inhibitors, tubulin inhibitors displayed promising results in preventing the proliferation of cancer cells. Microtubule targeting agents (MTAs) bind with tubulin protein and affect their functionalities in leukemia cells. In this context, recently reported antileukemic tubulin inhibitors viz., synthetic, natural, dual/multi-inhibitors, antibody-drug conjugates etc. have been summarized (2018 to present) in this manuscript. Structure activity relationship (SAR) analysis depicted that the presence of trimethoxy phenyl, chalcone, quinoline, and oxadiazole scaffolds improved the tubulin inhibitory activity against acute lymphoblastic leukemia. The present review also reported the recent patents and clinical trial data related to antileukemic tubulin inhibitors.

Antibody-drug conjugates are a rapidly evolving class of cancer therapeutics that combine the specificity of monoclonal antibodies with the potency of cytotoxic drugs. This review explores experimental and computational advances in ADC design, focusing on structural elements and optimization strategies.

We examined recent developments in the mechanisms of action, antibody engineering, linker chemistries, and payload selection. Emphasis was placed on experimental strategies and computational tools, including molecular modeling and AI-driven structure prediction.

ADCs function through both internalization-dependent and -independent mechanisms, enabling targeted drug delivery and bystander effects. The therapeutic efficacy of ADCs depends on key factors: antigen specificity, linker stability, and payload potency. Linkers are categorized as cleavable or non-cleavable, each with distinct advantages. Payloads-mainly tubulin inhibitors and DNA-damaging agents-require extreme potency to be effective. Computational methods have become essential for antibody modeling, developability assessment, and in silico optimization of ADC components, accelerating candidate selection and reducing experimental labor.

The integration of experimental and in silico approaches enhances ADC design by improving selectivity, stability, and efficacy. These strategies are critical for advancing next-generation ADCs with broader applicability and improved therapeutic indices.