caa a22 4500 60551299X CHVBK 20210128100658.0 cr unu---uuuuu 210128e20150801xx s 000 0 eng 10.1007/s00894-015-2742-x doi (NATIONALLICENCE)springer-10.1007/s00894-015-2742-x Computational design of enzyme-ligand binding using a combined energy function and deterministic sequence optimization algorithm [Elektronische Daten] [Ye Tian, Xiaoqiang Huang, Yushan Zhu] Enzyme amino-acid sequences at ligand-binding interfaces are evolutionarily optimized for reactions, and the natural conformation of an enzyme-ligand complex must have a low free energy relative to alternative conformations in native-like or non-native sequences. Based on this assumption, a combined energy function was developed for enzyme design and then evaluated by recapitulating native enzyme sequences at ligand-binding interfaces for 10 enzyme-ligand complexes. In this energy function, the electrostatic interaction between polar or charged atoms at buried interfaces is described by an explicitly orientation-dependent hydrogen-bonding potential and a pairwise-decomposable generalized Born model based on the general side chain in the protein design framework. The energy function is augmented with a pairwise surface-area based hydrophobic contribution for nonpolar atom burial. Using this function, on average, 78% of the amino acids at ligand-binding sites were predicted correctly in the minimum-energy sequences, whereas 84% were predicted correctly in the most-similar sequences, which were selected from the top 20 sequences for each enzyme-ligand complex. Hydrogen bonds at the enzyme-ligand binding interfaces in the 10 complexes were usually recovered with the correct geometries. The binding energies calculated using the combined energy function helped to discriminate the active sequences from a pool of alternative sequences that were generated by repeatedly solving a series of mixed-integer linear programming problems for sequence selection with increasing integer cuts. Springer-Verlag Berlin Heidelberg, 2015 Computational enzyme design nationallicence Protein-ligand interaction nationallicence Protein design nationallicence Energy function nationallicence Global optimization nationallicence Tian Ye Department of Chemical Engineering, Tsinghua University, 100084, Beijing, People's Republic of China aut Huang Xiaoqiang Department of Chemical Engineering, Tsinghua University, 100084, Beijing, People's Republic of China aut Zhu Yushan Department of Chemical Engineering, Tsinghua University, 100084, Beijing, People's Republic of China aut Journal of Molecular Modeling Springer Berlin Heidelberg 21/8(2015-08-01), 1-14 1610-2940 21:8<1 2015 21 894 https://doi.org/10.1007/s00894-015-2742-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00894-015-2742-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Tian Ye Department of Chemical Engineering, Tsinghua University, 100084, Beijing, People's Republic of China aut NATIONALLICENCE 700 1- Huang Xiaoqiang Department of Chemical Engineering, Tsinghua University, 100084, Beijing, People's Republic of China aut NATIONALLICENCE 700 1- Zhu Yushan Department of Chemical Engineering, Tsinghua University, 100084, Beijing, People's Republic of China aut NATIONALLICENCE 773 0- Journal of Molecular Modeling Springer Berlin Heidelberg 21/8(2015-08-01), 1-14 1610-2940 21:8<1 2015 21 894