Literature DB >> 14531052

Ab initio quality properties for macromolecules using the ADMA approach.

Thomas E Exner1, Paul G Mezey.   

Abstract

We describe new developments of an earlier linear scaling algorithm for ab initio quality macromolecular property calculations based on the adjustable density matrix assembler (ADMA) approach. In this approach, a large molecule is divided into fuzzy fragments, for which quantum chemical calculations can easily be done using moderate-size "parent molecules" that contain all the local interactions within a selected distance. If greater accuracy is required, a larger distance is chosen. With the present extension of this approximation, properties of the large molecules, like the electron density, the electrostatic potential, dipole moments, partial charges, and the Hartree-Fock energy are calculated. The accuracy of the method is demonstrated with test cases of medium size by comparing the ADMA results with direct quantum chemical calculations. Copyright 2003 Wiley Periodicals, Inc. J Comput Chem 24: 1980-1986, 2003

Year:  2003        PMID: 14531052     DOI: 10.1002/jcc.10340

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  9 in total

1.  Elongation cutoff technique: low-order scaling SCF method.

Authors:  Jacek Korchowiec; Jakub Lewandowski
Journal:  J Mol Model       Date:  2008-04-02       Impact factor: 1.810

Review 2.  The MOD-QM/MM Method: Applications to Studies of Photosystem II and DNA G-Quadruplexes.

Authors:  M Askerka; J Ho; E R Batista; J A Gascón; V S Batista
Journal:  Methods Enzymol       Date:  2016-07-15       Impact factor: 1.600

3.  Divide-and-Conquer Hartree-Fock Calculations on Proteins.

Authors:  Xiao He; Kenneth M Merz
Journal:  J Chem Theory Comput       Date:  2010-01-07       Impact factor: 6.006

4.  The Kernel Energy Method: Construction of 3 & 4 tuple Kernels from a List of Double Kernel Interactions.

Authors:  Lulu Huang; Lou Massa
Journal:  Theochem       Date:  2010-12

5.  MoD-QM/MM Structural Refinement Method: Characterization of Hydrogen Bonding in the Oxytricha nova G-Quadruplex.

Authors:  Junming Ho; Michael B Newcomer; Christina M Ragain; Jose A Gascon; Enrique R Batista; J Patrick Loria; Victor S Batista
Journal:  J Chem Theory Comput       Date:  2014-10-08       Impact factor: 6.006

Review 6.  Computational and data driven molecular material design assisted by low scaling quantum mechanics calculations and machine learning.

Authors:  Wei Li; Haibo Ma; Shuhua Li; Jing Ma
Journal:  Chem Sci       Date:  2021-11-08       Impact factor: 9.825

7.  Intermediate electrostatic field for the elongation method.

Authors:  Piotr Kuźniarowicz; Kai Liu; Yuriko Aoki; Feng Long Gu; Anna Stachowicz; Jacek Korchowiec
Journal:  J Mol Model       Date:  2014-05-31       Impact factor: 1.810

8.  Using quantum mechanical approaches to study biological systems.

Authors:  Kenneth M Merz
Journal:  Acc Chem Res       Date:  2014-06-06       Impact factor: 22.384

9.  Electron density learning of non-covalent systems.

Authors:  Alberto Fabrizio; Andrea Grisafi; Benjamin Meyer; Michele Ceriotti; Clemence Corminboeuf
Journal:  Chem Sci       Date:  2019-09-09       Impact factor: 9.825

  9 in total

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