Literature DB >> 16522103

Designing molecules by optimizing potentials.

Mingliang Wang1, Xiangqian Hu, David N Beratan, Weitao Yang.   

Abstract

The astronomical number of accessible discrete chemical structures makes rational molecular design extremely challenging. We formulate the design of molecules with specific tailored properties as performing a continuous optimization in the space of electron-nuclear attraction potentials. The optimization is facilitated by using a linear combination of atomic potentials (LCAP), a general framework that creates a continuous property landscape from an otherwise unlinked set of discrete molecular-property values. A demonstration of this approach is given for the optimization of molecular electronic polarizability and hyperpolarizability. We show that the optimal structures can be determined without enumerating and separately evaluating the characteristics of the combinatorial number of possible structures, a process that would be much slower. The LCAP approach may be used with quantum or classical Hamiltonians, suggesting possible applications to drug design and new materials discovery.

Entities:  

Year:  2006        PMID: 16522103     DOI: 10.1021/ja0572046

Source DB:  PubMed          Journal:  J Am Chem Soc        ISSN: 0002-7863            Impact factor:   15.419


  13 in total

1.  A gradient-directed Monte Carlo method for global optimization in a discrete space: application to protein sequence design and folding.

Authors:  Xiangqian Hu; David N Beratan; Weitao Yang
Journal:  J Chem Phys       Date:  2009-10-21       Impact factor: 3.488

2.  Computational design, synthesis and biological evaluation of para-quinone-based inhibitors for redox regulation of the dual-specificity phosphatase Cdc25B.

Authors:  Shahar Keinan; William D Paquette; John J Skoko; David N Beratan; Weitao Yang; Sunita Shinde; Paul A Johnston; John S Lazo; Peter Wipf
Journal:  Org Biomol Chem       Date:  2008-07-15       Impact factor: 3.876

3.  Accelerating self-consistent field convergence with the augmented Roothaan-Hall energy function.

Authors:  Xiangqian Hu; Weitao Yang
Journal:  J Chem Phys       Date:  2010-02-07       Impact factor: 3.488

4.  Stochastic voyages into uncharted chemical space produce a representative library of all possible drug-like compounds.

Authors:  Aaron M Virshup; Julia Contreras-García; Peter Wipf; Weitao Yang; David N Beratan
Journal:  J Am Chem Soc       Date:  2013-05-02       Impact factor: 15.419

5.  Liquid water simulations with the density fragment interaction approach.

Authors:  Xiangqian Hu; Yingdi Jin; Xiancheng Zeng; Hao Hu; Weitao Yang
Journal:  Phys Chem Chem Phys       Date:  2012-04-02       Impact factor: 3.676

6.  AutoGrow: a novel algorithm for protein inhibitor design.

Authors:  Jacob D Durrant; Rommie E Amaro; J Andrew McCammon
Journal:  Chem Biol Drug Des       Date:  2009-02       Impact factor: 2.817

7.  Pushing the boundaries of intrinsically stable radicals: inverse design using the thiadiazinyl radical as a template.

Authors:  Freija De Vleeschouwer; Artiom Chankisjijev; Weitao Yang; Paul Geerlings; Frank De Proft
Journal:  J Org Chem       Date:  2013-03-13       Impact factor: 4.354

Review 8.  Ab Initio Machine Learning in Chemical Compound Space.

Authors:  Bing Huang; O Anatole von Lilienfeld
Journal:  Chem Rev       Date:  2021-08-13       Impact factor: 60.622

9.  Simplifying inverse materials design problems for fixed lattices with alchemical chirality.

Authors:  Guido Falk von Rudorff; O Anatole von Lilienfeld
Journal:  Sci Adv       Date:  2021-05-19       Impact factor: 14.136

10.  Computational materials design of crystalline solids.

Authors:  Keith T Butler; Jarvist M Frost; Jonathan M Skelton; Katrine L Svane; Aron Walsh
Journal:  Chem Soc Rev       Date:  2016-11-07       Impact factor: 54.564

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