Variational Particle Number Approach for Rational Compound Design
ABSTRACT Within density functional theory, a variational particle number approach for rational compound design (RCD) is presented. An expression for RCD is obtained in terms of minimization of a suitably defined energy penalty functional whose gradients are the nuclear and the electronic chemical potential. Using combined quantum and molecular mechanics, a nonpeptidic anticancer drug candidate is designed.
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ABSTRACT: 'Alchemical' interpolation paths, i.e. coupling systems along fictitious paths without realistic correspondence, are frequently used within materials and molecular modeling simulation protocols for the estimation of changes in state functions such as free energies. We discuss alchemical changes in the context of quantum chemistry, and present illustrative numerical results for the changes of HOMO eigenvalue of the He atom due to alchemical teleportation – the simultaneous annihilation and creation of nuclear charges at different locations. To demonstrate the predictive power of alchemical first order derivatives (Hellmann-Feynman) the covalent bond potential of hydrogen fluoride and hydrogen chloride is investigated, as well as the hydrogen bond in the water–water and water–hydrogen fluoride dimer, respectively. Based on converged electron densities for one configuration, the versatility of alchemical derivatives is exemplified for the screening of entire binding potentials with reasonable accuracy. Finally, we discuss new constraints for the identification of non-linear coupling potentials for which the energy's Hellmann-Feynman derivative will yield accurate predictions.CHIMIA International Journal for Chemistry 09/2014; 68(9):602-608. DOI:10.2533/chimia.2014.602 · 1.35 Impact Factor
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ABSTRACT: Quantum mechanical (QM) methods are becoming popular in computational drug design and development mainly because high accuracy is required to estimate (relative) binding affinities. For low-to medium-throughput in silico screening, (e.g., scoring and prioritizing a series of inhibitors sharing the same molecular scaffold) efficient approximations have been developed in the past decade, like linear scaling QM in which the computation time scales almost linearly with the number of basis functions. Furthermore, QM-based procedures have been used recently for determining protonation states of ionizable groups, evaluating energies, and optimizing molecular structures. For high-throughput in silico screening QM approaches have been employed to derive robust quantitative structure-activity relationship models. It is expected that the use of QM methods will keep growing in all phases of computer-aided drug design and development. However, extensive sampling of conformational space and treatment of solution of macromolecules are still limiting factors for the broad application of QM in drug design.Current topics in medicinal chemistry 11/2009; 10(1):33-45. DOI:10.2174/156802610790232242 · 3.45 Impact Factor
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ABSTRACT: Using Kohn-Sham (KS) density-functional theory, we have studied the interaction between various polyaromatic hydrocarbon molecules. The systems range from monocyclic benzene up to hexabenzocoronene (hbc). For several conventional exchange-correlation functionals total potential-energy curves of interaction of the pi-pi stacking hbc dimer are reported. It is found that all pure local density or generalized gradient approximated functionals yield qualitatively incorrect predictions regarding structure and interaction. Inclusion of a nonlocal, atom-centered correction to the KS Hamiltonian enables quantitative predictions. The computed potential-energy surfaces of interaction yield parameters for a coarse-grained potential, which can be employed to study discotic liquid-crystalline mesophases of derived polyaromatic macromolecules.The Journal of Chemical Physics 03/2006; 124(5):054307. DOI:10.1063/1.2162543 · 3.12 Impact Factor