Geometry Optimization Using the Frozen Domain and Partial Dimer Approaches in the Fragment Molecular Orbital Method: Implementation, Benchmark, and Applications to Protein Ligand-Binding Sites.

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL Journal of Chemical Information and Modeling Pub Date : 2024-12-02 DOI:10.1021/acs.jcim.4c01280
Koji Okuwaki, Naoki Watanabe, Koichiro Kato, Chiduru Watanabe, Naofumi Nakayama, Akifumi Kato, Yuji Mochizuki, Tatsuya Nakano, Teruki Honma, Kaori Fukuzawa
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Abstract

The frozen domain (FD) approximation with the fragment molecular orbital (FMO) method is efficient for partial geometry optimization of large systems. We implemented the FD formulation (FD and frozen domain dimer [FDD] methods) already proposed by Fedorov, D. G. et al. (J. Phys. Chem. Lett. 2011, 2, 282-288); proposed a variation of it, namely frozen domain and partial dimer (FDPD) method; and applied it to several protein-ligand complexes. The computational time for geometry optimization at the FDPD/HF/6-31G* level for the active site (six fragments) of the largest β2-adrenergic G-protein-coupled receptor (440 residues) was almost half that of the conventional partial geometry optimization method. In the human estrogen receptor, the crystal structure was refined by FDPD geometry optimization of estradiol, surrounding hydrogen-bonded residues and a water molecule. The rather polarized ligand binding site of influenza virus neuraminidase was also optimized by FDPD optimization, which relaxed steric repulsion around the ligand in the crystal structure and optimized hydrogen bonding. For Serine-Threonine Kinase Pim1 and six inhibitors, the structures of the ligand binding site, Lys67, Glu121, Arg122, and benzofuranone ring and indole/azaindole ring of the ligand, were optimized at FDPD/HF/6-31G* and the ligand binding energy was estimated at the FMO-MP2/6-31G* level. As a result of examining three different optimization regions, the correlation coefficient between pIC50 and ligand binding energy was considerably improved by expanding the optimized region; in other words, better structure-activity relationships was obtained. Thus, this approach is promising as a high-precision structure refinement method for structure-based drug discovery.

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CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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