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向化学（Inverse Chemistry）的基础原理——这是一门新兴交叉学科，旨在通过将目标属性反向映射至分子结构与组成，解决化学科学领域中的逆问题。与将材料科学、药物发现与蛋白质工程视作独立研究领域的传统范式不同，本文提出了统一的逆向映射科学理念。本文依托先进计算方法，阐明了一套涵盖贝叶斯推断（Bayesian inference）、基于索博尔指标（Sobol indices）的精细化敏感性分析以及遗传优化的多维研究路径。该研究框架以严谨的数学推导、可复现的模拟实验及Python代码实现作为支撑。包含详细算法流程图在内的高保真TikZ可视化图表，对上述复杂流程进行了直观阐释。本研究整合了来自多篇同行评议文献的核心洞见，旨在为后续的实证验证与跨学科创新提供坚实的循证基础。