Dataset Information

Drug target interaction energies by the kernel energy method in aminoglycoside drugs and ribosomal A site RNA targets.

ABSTRACT: It is possible to use the full power of ab initio quantum mechanics in application to the interaction of drugs and their molecular targets. This idea had barely been realized until recently, because of the well known growth in computational difficulty of the use of quantum mechanics, with the number of atoms in the molecule to be studied. Because the biochemical molecules of medicinal chemistry are so often large, containing thousands or even tens of thousands of atoms, the computational difficulty of the full quantum problem had been prohibitive. Two things have happened, however, that change this perspective: (i) the advances of parallel supercomputers, and (ii) the discovery of a quantum formalism called quantum crystallography and the use of quantum kernels, a method that is well suited for parallel computation. Such advances would allow the quantum mechanical ab initio calculation of the molecular energy of peptides, proteins, DNA, and RNA, obtaining results of high accuracy. In this approach the computational difficulty of representing a molecule increases only modestly with the number of atoms. The calculations are simplified by adopting an acceptable approximation that allows a full biological molecule to be represented by smaller "kernels" of atoms. These results suggest that problems of medicinal chemistry, such as the rational design of drugs, may be illuminated by quantum mechanical analysis. The general case is illustrated by specific examples, namely, the HF/STO-3G calculations of three aminoglycoside drugs that attach to ribosomal A-site RNA nucleotide targets.

SUBMITTER: Huang L

PROVIDER: S-EPMC1838590 | biostudies-literature | 2007 Mar

REPOSITORIES: biostudies-literature

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Drug target interaction energies by the kernel energy method in aminoglycoside drugs and ribosomal A site RNA targets.

Huang Lulu L Massa Lou L Karle Jerome J

Proceedings of the National Academy of Sciences of the United States of America 20070301 11

It is possible to use the full power of ab initio quantum mechanics in application to the interaction of drugs and their molecular targets. This idea had barely been realized until recently, because of the well known growth in computational difficulty of the use of quantum mechanics, with the number of atoms in the molecule to be studied. Because the biochemical molecules of medicinal chemistry are so often large, containing thousands or even tens of thousands of atoms, the computational difficu ...[more]

PMID: 17360512

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Project description:Several simplifications used in clinical implementations of the convolution∕superposition (C∕S) method, specifically, density scaling of water kernels for heterogeneous media and use of a single polyenergetic kernel, lead to dose calculation inaccuracies. Although these weaknesses of the C∕S method are known, it is not well known which of these simplifications has the largest effect on dose calculation accuracy in clinical situations. The purpose of this study was to generate and characterize high-resolution, polyenergetic, and material-specific energy deposition kernels (EDKs), as well as to investigate the dosimetric impact of implementing spatially variant polyenergetic and material-specific kernels in a collapsed cone C∕S algorithm.High-resolution, monoenergetic water EDKs and various material-specific EDKs were simulated using the EGSnrc Monte Carlo code. Polyenergetic kernels, reflecting the primary spectrum of a clinical 6 MV photon beam at different locations in a water phantom, were calculated for different depths, field sizes, and off-axis distances. To investigate the dosimetric impact of implementing spatially variant polyenergetic kernels, depth dose curves in water were calculated using two different implementations of the collapsed cone C∕S method. The first method uses a single polyenergetic kernel, while the second method fully takes into account spectral changes in the convolution calculation. To investigate the dosimetric impact of implementing material-specific kernels, depth dose curves were calculated for a simplified titanium implant geometry using both a traditional C∕S implementation that performs density scaling of water kernels and a novel implementation using material-specific kernels.For our high-resolution kernels, we found good agreement with the Mackie et al. kernels, with some differences near the interaction site for low photon energies (<500 keV). For our spatially variant polyenergetic kernels, we found that depth was the most dominant factor affecting the pattern of energy deposition; however, the effects of field size and off-axis distance were not negligible. For the material-specific kernels, we found that as the density of the material increased, more energy was deposited laterally by charged particles, as opposed to in the forward direction. Thus, density scaling of water kernels becomes a worse approximation as the density and the effective atomic number of the material differ more from water. Implementation of spatially variant, polyenergetic kernels increased the percent depth dose value at 25 cm depth by 2.1%-5.8% depending on the field size, while implementation of titanium kernels gave 4.9% higher dose upstream of the metal cavity (i.e., higher backscatter dose) and 8.2% lower dose downstream of the cavity.Of the various kernel refinements investigated, inclusion of depth-dependent and metal-specific kernels into the C∕S method has the greatest potential to improve dose calculation accuracy. Implementation of spatially variant polyenergetic kernels resulted in a harder depth dose curve and thus has the potential to affect beam modeling parameters obtained in the commissioning process. For metal implants, the C∕S algorithms generally underestimate the dose upstream and overestimate the dose downstream of the implant. Implementation of a metal-specific kernel mitigated both of these errors.

Dataset Information

Drug target interaction energies by the kernel energy method in aminoglycoside drugs and ribosomal A site RNA targets.

Publications

Drug target interaction energies by the kernel energy method in aminoglycoside drugs and ribosomal A site RNA targets.

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