Altun Ahmet, Neese Frank, Bistoni Giovanni
Max-Planck-Institut für Kohlenforschung, Kaiser-Wilhelm-Platz 1, D-45470 Mülheim an der Ruhr, Germany.
Department of Chemistry, Biology and Biotechnology, University of Perugia, 06123 Perugia, Italy.
J Chem Inf Model. 2025 Sep 8;65(17):8917-8923. doi: 10.1021/acs.jcim.5c01561. Epub 2025 Aug 28.
Accurate interaction energies can be obtained using high-level quantum chemical methods such as DLPNO-CCSD(T) and its HFLD variant in ORCA. The local energy decomposition (LED) scheme helps interpret these energies by breaking them down into chemically meaningful components. However, preparing LED inputs and analyzing results is often complex and error-prone. To streamline this process, we developed LEDAW (local energy decomposition analysis wizard), a Python-based tool that automates LED workflows. It supports standard and fragment-pairwise (fp)-LED, complete basis set (CBS) and Complete PNO Space (CPS) extrapolations, and analysis of N-body and cooperativity effects. With both a GUI and script-based workflow, LEDAW reduces analysis time from hours or days to just minutes, improving usability and reproducibility. It accelerates the generation of interaction energy matrices and heat maps, making advanced analysis of protein-ligand complexes, DNA assemblies, solute-solvent interactions, and molecular crystals more accessible.
使用诸如ORCA中的DLPNO-CCSD(T)及其HFLD变体等高阶量子化学方法，可以获得精确的相互作用能。局部能量分解(LED)方案通过将这些能量分解为具有化学意义的组分来帮助解释这些能量。然而，准备LED输入和分析结果通常很复杂且容易出错。为了简化这个过程，我们开发了LEDAW(局部能量分解分析向导)，这是一个基于Python的工具，它可以自动执行LED工作流程。它支持标准和片段成对(fp)-LED、完全基组(CBS)和完全PNO空间(CPS)外推，以及N体和协同效应分析。通过GUI和基于脚本的工作流程，LEDAW将分析时间从数小时或数天缩短到仅几分钟，提高了可用性和可重复性。它加速了相互作用能矩阵和热图的生成，使蛋白质-配体复合物、DNA组装体、溶质-溶剂相互作用和分子晶体的高级分析更容易实现。
