Quantum Mechanics in Biomolecular Simulations: Benefits and Cost-Reduction Strategies for Integrated QM/MM Approaches

Abstract

Quantum calculations play a fundamental role in understanding biological systems at the atomic level, as they allow detailed investigation of electronic interactions, enzymatic mechanisms, and molecular recognition processes. However, the direct application of these methods to large biomolecules is limited by the high computational cost involved. An efficient alternative consists of combining classical Molecular Mechanics (MM) simulations, such as molecular dynamics, with quantum mechanical (QM) methods, enabling a more comprehensive multiscale description. This hybrid approach, however, introduces another challenge: classical simulations generate a very large number of conformations, which makes it impractical to perform quantum calculations on every frame. Therefore, the efficiency of this strategy depends on selecting a reduced and representative set of structures to be analyzed in subsequent quantum stages. In this mini-review, we present three complementary methods to achieve this selection: (1) Clustering, (2) Statistical Inefficiency (SI), and (3) Optimal Wavelet Signal Compression Analysis (OWSCA). This filtering step makes it possible to explore quantum effects with high accuracy without compromising conformational representativeness, drastically reducing the computational cost and expanding the applicability of a sequential workflow of hybrid QM/ MM methodologies to the study of complex biological systems. © 2025 Sociedade Brasileira de Química.