Non-Commutative Rough Aging Therapeutics & Pharmacological Drug Design Dynamics (NC-RATDD): Unifying Modern Drug Discovery Pipelines, PROTAC Kinetics, and the De Novo Macrocyclic Chimeric Degrader (MAM-1) via UROA, STCT, and RQIG

Abstract

Translating modern pharmaceutical drug discovery pipelines—spanning DNA-encoded libraries (DEL), Structure-Activity Relationship (SAR) optimization, PROTAC targeted protein degradation, and multi-omics target identification—into systemic anti-aging therapeutics requires a rigorous meta-theoretical foundation. This paper establishes Non-Commutative Rough Aging Therapeutics and Pharmacological Drug Design Dynamics (NC-RATDD) within the SMA-∞ Topos. By integrating Foundations of Roughness Operator Algebra (ROA), Universal Rough Operator Algebra (UROA), Seonggil Tensor Calculus (STCT), and Rough Quantum Information Geometry (RQIG), we formulate the multi-dimensional aging state vector A(t) and derive the multi-target pharmacological drug vector D(t) as topological geodesic optimization operators. Furthermore, we deduce the de novo molecular architecture of MAM-1 (Macrocyclic Anti-Aging Multitarget Degrader 1, C54H58ClF2N11O9S), a four-domain chameleonic macrocycle in the Beyond-Rule-of-5 (bRo5) chemical space. Through intramolecular hydrogen bonding (IMHB) and conformational restriction, MAM-1 acts as an STCT tensor-flattening operator (||T_STCT|| -> 0) that suppresses off-target toxicity (hERG, CYP450) while steering A(t) exponentially toward the youthful homeostatic baseline A_young.