| Abstract: | Up to about half of the atoms in biopolymers are inaccessible to solvents. If such atoms can be rapidly identified, time can be saved in the subsequent computation of atomic surface areas. A quick, approximate method, termed buried atom elimination (BAE), was developed for the detection of such atoms. Following the literature, the method makes use of a Gaussian function to calculate the neighbor density in four tetrahedral directions in 3-dimensional space, sometimes twice with different orientations. In macromolecules, our method detects between 63 and 81% of the buried atoms but also incorrectly classifies 2–8% of the exposed atoms as buried. These misidentified atoms all have small solvent-exposed (accessible) surface areas (SASAs): their surfaces sum to a maximum of 0.5% of the molecular SASA, and their maximum atomic SASA is 5.1 Å2. Using our recently reported LCPO method for computing atomic surfaces, which is one of the fastest available, the use of BAE increases the overall speed of computing the atomic SASAs by a factor of up to 1.6 for surfaces only and 1.9 when first and second derivatives are computed. BAE decreases the LCPO average absolute atomic error from about 2.3 Å2 to about 1.7 Å2 (average for larger compounds). BAE was introduced into the MacroModel molecular modeling package and tests show that it increases the efficiency of first- and second-derivative energy minimizations and molecular dynamics simulations without adversely affecting the stability or accuracy of the calculations. BAE parameters were developed for the most important atom types in biopolymers, based on a parameterization set of 18 compounds of different size (33–4346 atoms) and class (organics, proteins, DNA, and various complexes), consisting of a total of 23,186 atoms. ©1999 John Wiley & Sons, Inc. J Comput Chem 20, 586–596, 1999 |
