Founding the Science of Inverse Chemistry: A Unified Conceptual Framework for Property-to-Structure Mapping

This conceptual paper establishes the foundational principles of Inverse Chemistry, a novel interdisciplinary field that addresses the inverse problems in chemical sciences by mapping desired properties back to molecular structures and compositions. Unlike traditional approaches that treat materials science, drug discovery, and protein engineering as separate domains, we posit a unified science of inverse mapping. Drawing upon advanced computational methodologies, we delineate a multi-dimensional approach encompassing Bayesian inference, detailed sensitivity analysis via Sobol indices, and genetic optimization. The framework is supported by precise mathematical derivations, reproducible simulations, and Python code implementations. High-fidelity TikZ visualizations, including detailed algorithmic flowcharts, illustrate the complex processes. This work integrates insights from diverse peer-reviewed sources to provide a robust, evidence-based foundation for future empirical validations and cross-disciplinary innovation.本概念性研究论文确立了逆化学 (Inverse Chemistry) 的基础原理。逆化学是一门新兴交叉学科，通过将目标属性反向映射至分子结构与组成，以解决化学科学领域中的逆问题。相较于将材料科学、药物发现与蛋白质工程视为独立研究领域的传统路径，本文提出了统一的反向映射科学范式。本文依托先进计算方法，构建了一套涵盖贝叶斯推理 (Bayesian inference)、基于索博尔指数 (Sobol indices) 的精细化灵敏度分析以及遗传优化 (genetic optimization) 的多维研究框架。该框架依托严谨的数学推导、可复现的仿真实验以及Python代码实现作为支撑。高保真的TikZ可视化成果（包含详细的算法流程图）直观呈现了整个复杂流程。本研究整合了多篇同行评议文献的核心观点，为后续的实证验证与跨学科创新提供了坚实的循证基础。