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Quantum chemical geometry optimizations in proteins using crystallographic raw data
Author(s) -
Ryde Ulf,
Olsen Lars,
Nilsson Kristina
Publication year - 2002
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.10093
Subject(s) - crystal structure , crystallography , chemistry , crystal structure prediction , molecule , electron density , quantum chemical , quantum chemistry , software , computer science , crystal (programming language) , quantum , function (biology) , computational science , algorithm , physics , electron , quantum mechanics , supramolecular chemistry , evolutionary biology , programming language , biology
Abstract A method is developed for the combination of quantum chemical geometry optimizations and crystallographic structure refinement. The method is implemented by integrating the quantum chemical software Turbomole with the crystallographic software Crystallography and NMR System (CNS), using three small procedures transferring information between the two programs. The program ( COMQUM‐X) is used to study the binding of the inhibitor N ‐methylmesoporphyrin to ferrochelatase, and we show that the method behaves properly and leads to an improvement of the structure of the inhibitor. It allows us to directly quantify in energy terms how much the protein distort the structure of the bound inhibitor compared to the optimum vacuum structure (4–6 kJ/mol). The approach improves the standard combined quantum chemical and molecular mechanics (QC/MM) approach by guaranteeing that the final structure is in accordance with experimental data (the reflections) and avoiding the risk of propagating errors in the crystal coordinates. The program can also be seen as an improvement of standard crystallographic refinement, providing an accurate empirical potential function for any group of interest. The results can be directly interpreted in standard crystallographic terms (e.g., R factors or electron density maps). The method can be used to interpret crystal structures (e.g., the protonation status of metal‐bound water molecules) and even to locally improve them. © 2002 Wiley Periodicals, Inc. J Comput Chem 23: 1058–1070, 2002