Efficient double hybrid density functional theory algorithms for conformational a
DESCRIPTION (provided by applicant): Double hybrid (DH) density functionals are one of the most promising new developments in quantum mechanical methods for simulating biomolecules. DH functionals have been reported to yield much more accurate intermolecular interaction energies than previous generation functionals. They are therefore on the threshold of becoming widely used. However, there are still practical obstacles blocking widespread use of DH functionals, apart from lack of familiarity to users. ThisSBIR proposal aims to embrace the opportunity of greater accuracy offered by the DH approach by directly addressing the key known limitations. These limitations and our proposed remedies are as follows. (i) DH functionals are more computationally expensive to evaluate than conventional functionals because the cost scales as the 5th power, rather than the 3rd power of molecular size. We will implement and benchmark a novel 3rd order method for evaluating the DH energy without explicit two-electron integrals. The computational savings for biophysically useful accuracy will be assessed on conformational relative energies. (ii) DH functionals require larger atomic orbital basis sets to yield converged relative energies, but doubling the basis requires 16 timesmore computation. We will significantly ameliorate this slow convergence by augmenting the basis to explicitly include interelectronic coordinates, via F12 techniques that have proven successful for wave function methods. This first use of F12 methods to evaluate the DH energy will be benchmarked to assess the reduction in basis set size that is possible without sacrificing accuracy for conformational energies and intermolecular interactions. PUBLIC HEALTH RELEVANCE: to implement a new DFT method ina computationally efficient manner. DFT is at the core of molecular modeling and is applied widely in biological research/development and in drug discovery. The improved DFT will significantly increase researchers' quality of work and extend the application scope of DFT.
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