Premium
ESCASA : Analytical estimation of atomic coordinates from coarse‐grained geometry for nuclear‐magnetic‐resonance ‐assisted protein structure modeling. I. Backbone and H β protons
Author(s) -
Lubecka Emilia A.,
Liwo Adam
Publication year - 2021
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.26695
Subject(s) - proton , chemistry , standard deviation , parameterized complexity , geometry , nuclear magnetic resonance , crystallography , analytical chemistry (journal) , physics , algorithm , mathematics , nuclear physics , statistics , chromatography
A method for the estimation of coordinates of atoms in proteins from coarse‐grained geometry by simple analytical formulas (ESCASA), for use in nuclear‐magnetic‐resonance (NMR) data‐assisted coarse‐grained simulations of proteins is proposed. In this paper, the formulas for the backbone H α and amide (H N ) protons, and the side‐chain H β protons, given the C α ‐trace, have been derived and parameterized, by using the interproton distances calculated from a set of 140 high‐resolution non‐homologous protein structures. The mean standard deviation over all types of proton pairs in the set was 0.44 Å after fitting. Validation against a set of 41 proteins with NMR‐determined structures, which were not considered in parameterization, resulted in average standard deviation from average proton–proton distances of the NMR‐determined structures of 0.25 Å, compared to 0.21 Å obtained with the PULCHRA all‐atom‐chain reconstruction algorithm and to the 0.12 Å standard deviation of the average‐structure proton–proton distance of NMR‐determined ensembles. The formulas provide analytical forces and can, therefore, be used in coarse‐grained molecular dynamics.