Geometry Optimization of Kringle 1 of Plasminogen Using the PM3 Semiempirical Method

The results of a geometry optimization on the 1226 atom Kringle 1 of plasminogen are presented. The energy and gradients were calculated using a linear- scaling PM3 semiempirical method with a conjugate gradient density matrix search replacing the diagonalization step. The geometry was optimized with the rational function optimization technique combined with a modified version of the direct inversion in the iterative subspace procedure. The optimization required 362 geometry update steps to reach a local minimum. An analysis is given of the optimization and timing results using a single processor on the SGI Origin2000. Q 2000 John Wiley & Sons, Inc. Int J

[1]  F. Castellino,et al.  Amino acids of the recombinant kringle 1 domain of human plasminogen that stabilize its interaction with omega-amino acids. , 1993, Biochemistry.

[2]  James J. P. Stewart,et al.  Application of localized molecular orbitals to the solution of semiempirical self‐consistent field equations , 1996 .

[3]  H. Bernhard Schlegel,et al.  Methods for geometry optimization of large molecules. I. An O(N2) algorithm for solving systems of linear equations for the transformation of coordinates and forces , 1998 .

[4]  David E. Manolopoulos,et al.  Canonical purification of the density matrix in electronic-structure theory , 1998 .

[5]  M. Teter,et al.  Tight-binding electronic-structure calculations and tight-binding molecular dynamics with localized orbitals. , 1994, Physical review. B, Condensed matter.

[6]  J. Stewart.  Optimization of parameters for semiempirical methods II. Applications , 1989 .

[7]  Gustavo E. Scuseria,et al.  Semiempirical methods with conjugate gradient density matrix search to replace diagonalization for molecular systems containing thousands of atoms , 1997 .

[8]  Calculation of the geometry of a small protein using semiempirical methods , 1997 .

[9]  Steven L. Dixon,et al.  Parallel implementation of a divide and conquer semiempirical algorithm , 1998 .

[10]  Gustavo E. Scuseria,et al.  What is the Best Alternative to Diagonalization of the Hamiltonian in Large Scale Semiempirical Calculations , 1999 .

[11]  J. Stewart.  Optimization of parameters for semiempirical methods I. Method , 1989 .

[12]  C. Carter,et al.  Active Species for the Ground-State Complex of Cytidine Deaminase: A Linear-Scaling Quantum Mechanical Investigation , 1998 .