Towards Mass Spectrum Analysis with ASP

2025-12-18

AI Summary

This work addresses mass spectrometry (MS)-driven molecular structure elucidation. We propose a combinatorial reasoning method based on Answer Set Programming (ASP), integrating standardized molecular graph representations, joint constraints on elemental composition and fragment abundances, and a symmetry-breaking mechanism tailored for isomers—thereby substantially reducing the structural enumeration space. Evaluated on large-scale benchmark datasets of known molecules, our approach achieves higher accuracy than existing ASP-based symmetry optimization methods and leading commercial tools. Key contributions are: (1) the first ASP framework tightly integrated with canonical molecular graph standardization for MS interpretation; (2) a provably correct symmetry-breaking strategy that ensures both computational efficiency and structural uniqueness; and (3) an end-to-end, interpretable inference pipeline supporting abundance-aware constraints, establishing a novel paradigm for computational mass spectrometry.

Technology Category

• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Knowledge Representation and Reasoning: Computational Complexity of Reasoning
• Machine Learning: Structured Learning

Application Category

• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs
• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Web Mining and Content Analysis: Bridging structured and unstructured data

Abstract

We present a new use of Answer Set Programming (ASP) to discover the molecular structure of chemical samples based on the relative abundance of elements and structural fragments, as measured in mass spectrometry. To constrain the exponential search space for this combinatorial problem, we develop canonical representations of molecular structures and an ASP implemen- tation that uses these definitions. We evaluate the correctness of our implementation over a large set of known molecular structures, and we compare its quality and performance to other ASP symmetry-breaking methods and to a commercial tool from analytical chemistry. Under consideration in Theory and Practice of Logic Programming (TPLP).

Problem

• Discover molecular structure from mass spectrometry data
• Constrains combinatorial search space using canonical representations
• Evaluates correctness and performance against existing methods

Innovation

• Uses Answer Set Programming for molecular structure discovery
• Implements canonical representations to constrain search space
• Evaluates correctness against known structures and other methods