Structural Reasoning Improves Molecular Understanding of LLM

TL;DR

This paper introduces the Molecular Structural Reasoning (MSR) framework to improve large language models' ability to understand and reason about molecular structures, addressing a key gap in their comprehension of molecular properties.

Contribution

The paper proposes a novel MSR framework that explicitly incorporates molecular structural features to enhance LLMs' molecular reasoning capabilities.

Findings

MSR significantly improves molecular understanding in LLMs

Framework works for known and unknown target molecules

Extensive experiments validate the effectiveness of MSR

Abstract

Recently, large language models (LLMs) have shown significant progress, approaching human perception levels. In this work, we demonstrate that despite these advances, LLMs still struggle to reason using molecular structural information. This gap is critical because many molecular properties, including functional groups, depend heavily on such structural details. To address this limitation, we propose an approach that sketches molecular structures for reasoning. Specifically, we introduce Molecular Structural Reasoning (MSR) framework to enhance the understanding of LLMs by explicitly incorporating the key structural features. We present two frameworks for scenarios where the target molecule is known or unknown. We verify that our MSR improves molecular understanding through extensive experiments.