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Biomass represents the total organic mass of a biological entity, ranging from individual cells to entire microbial populations. In the context of drug discovery and systems biology, it is primarily used as a 'biomass objective function' (BOF) in genome-scale metabolic models (GEMs) to simulate and predict cellular growth rates [1, 3]. This mathematical representation incorporates the stoichiometric requirements of all essential metabolites—such as amino acids, nucleotides, lipids, and carbohydrates—needed for cell replication [2, 7]. While the reduction of cellular biomass is the ultimate goal of many therapeutic strategies in oncology and infectious diseases, biomass itself is not a specific molecular target like a protein or receptor [15, 16]. Instead, drugs interact with specific molecular entities in metabolic or signaling pathways to disrupt the production of the components that constitute biomass [2]. Consequently, while biomass is a critical phenotypic endpoint for evaluating the efficacy of anti-proliferative agents, it lacks the structural properties and specificity required for direct pharmacological targeting.
Not applicable; biomass is a physiological outcome or modeling parameter rather than a molecular drug target.
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