ABSTRACT Determining the electronic structure of long chain molecules is essential to the underst... more ABSTRACT Determining the electronic structure of long chain molecules is essential to the understanding of many biological processes, notably those involving molecular receptors in cells. Finding minimum energy conformers and thus electronic structure of long-chain molecules by exhaustive search quickly becomes infeasible as the chain length increases. Typically, resources required are proportional to the number of possible conformers (shapes), which scales as O(3^L) where L is the length. An optimized genetic algorithm that can determine the minimum energy conformer of an arbitrary long-chain molecule in a feasible time is described, using the tool, PyEvolve. The method is to first solve a generic problem for a long chain by exhaustive search, then by using the predetermined results in a look-up table, to make use of a Meta-GA to optimize parameters of a simple GA through an evolutionary process to solve that same problem. By comparing the results using the tuned parameters obtained by this method with the results from exhaustive search on several molecules of comparable chain length we have obtained quantitative measurements of an increase in speed by a factor of three over standard parameter settings, and a factor of ten over exhaustive search.
Determining the electronic structure of long chain molecules is essential to the understanding of... more Determining the electronic structure of long chain molecules is essential to the understanding of many biological processes, notably those involving molecular receptors in cells. Finding minimum energy conformers and thus electronic structure of long-chain molecules by exhaustive search quickly becomes infeasible as the chain length increases. Typically, resources required are proportional to the number of possible conformers (shapes), which scales as O(3^L) where L is the length. An optimized genetic algorithm that can determine the minimum energy conformer of an arbitrary long-chain molecule in a feasible time is described, using the tool, PyEvolve. The method is to first solve a generic problem for a long chain by exhaustive search, then by using the pre-determined results in a look-up table, to make use of a Meta-GA to optimize parameters of a simple GA through an evolutionary process to solve that same problem. By comparing the results using the tuned parameters obtained by thi...
Molecules can have different shapes, yet the same chemical formula. These shapes – conformers – h... more Molecules can have different shapes, yet the same chemical formula. These shapes – conformers – have different energies. The molecule will tend to adopt the shape with the lowest energy. A molecule's shape determines how it fits with chemical receptors in cells, so determines some of its pharmaceutical properties. So it's really useful to know what that minimum-energy shape is. One problem: a molecule of length 12 has nearly 180,000 possible shapes. To calculate the energy of just one shape takes about an hour on the National Computing Infrastructure. At 20c an hour, that's $90,000. And a molecule of length 14 has over ten times as many... *
With the ever—increasing speed of supercomputers, the size of molecules amenable to study with ab... more With the ever—increasing speed of supercomputers, the size of molecules amenable to study with ab initio quantum chemistry methods has increased to include molecules with thousands or even millions of possible conformations. For such molecules, the conformational search represents the computational bottleneck, making studies of such molecules challenging and expensive. Genetic Algorithms (GA) are a type of stochastic algorithm that work analogously to Darwinian evolution to locate the fittest individual in a population. We have previously used a meta-GA to optimize a GA [1] for a conformational search [2]. The optimized GA is not dependent on crossover, thus reducing to an Evolutionary Algorithm (EA). We apply this optimized EA to several large molecules and show that the global minimum structure of a molecule with 20 rotatable bonds can be reliably found with less than 2000 ab initio calculations representing only 3 x 10-4 % of the total search space. Fig 1. a) Size of molecule (nu...
... 1. INTRODUCTION The TAIL (Transport Airlift Integrated Logistics) project was conducted as a ... more ... 1. INTRODUCTION The TAIL (Transport Airlift Integrated Logistics) project was conducted as a proof of concept to determine if substantial simulation capability could be developed in a short time frame using xtUML (and BridgePoint tools) with an agile development perspective. ...
We present two sets of tunings that are broadly applicable to conformer searches of isolated mole... more We present two sets of tunings that are broadly applicable to conformer searches of isolated molecules using a genetic algorithm (GA). In order to find the most efficient tunings for the GA, a second GA--a meta-genetic algorithm--was used to tune the first genetic algorithm to reliably find the already known a priori correct answer with minimum computational resources. It is shown that these tunings are appropriate for a variety of molecules with different characteristics, and most importantly that the tunings are independent of the underlying model chemistry but that the tunings for rigid and relaxed surfaces differ slightly. It is shown that for the problem of molecular conformational search, the most efficient GA actually reduces to an evolutionary algorithm.
ABSTRACT Determining the electronic structure of long chain molecules is essential to the underst... more ABSTRACT Determining the electronic structure of long chain molecules is essential to the understanding of many biological processes, notably those involving molecular receptors in cells. Finding minimum energy conformers and thus electronic structure of long-chain molecules by exhaustive search quickly becomes infeasible as the chain length increases. Typically, resources required are proportional to the number of possible conformers (shapes), which scales as O(3^L) where L is the length. An optimized genetic algorithm that can determine the minimum energy conformer of an arbitrary long-chain molecule in a feasible time is described, using the tool, PyEvolve. The method is to first solve a generic problem for a long chain by exhaustive search, then by using the predetermined results in a look-up table, to make use of a Meta-GA to optimize parameters of a simple GA through an evolutionary process to solve that same problem. By comparing the results using the tuned parameters obtained by this method with the results from exhaustive search on several molecules of comparable chain length we have obtained quantitative measurements of an increase in speed by a factor of three over standard parameter settings, and a factor of ten over exhaustive search.
Determining the electronic structure of long chain molecules is essential to the understanding of... more Determining the electronic structure of long chain molecules is essential to the understanding of many biological processes, notably those involving molecular receptors in cells. Finding minimum energy conformers and thus electronic structure of long-chain molecules by exhaustive search quickly becomes infeasible as the chain length increases. Typically, resources required are proportional to the number of possible conformers (shapes), which scales as O(3^L) where L is the length. An optimized genetic algorithm that can determine the minimum energy conformer of an arbitrary long-chain molecule in a feasible time is described, using the tool, PyEvolve. The method is to first solve a generic problem for a long chain by exhaustive search, then by using the pre-determined results in a look-up table, to make use of a Meta-GA to optimize parameters of a simple GA through an evolutionary process to solve that same problem. By comparing the results using the tuned parameters obtained by thi...
Molecules can have different shapes, yet the same chemical formula. These shapes – conformers – h... more Molecules can have different shapes, yet the same chemical formula. These shapes – conformers – have different energies. The molecule will tend to adopt the shape with the lowest energy. A molecule's shape determines how it fits with chemical receptors in cells, so determines some of its pharmaceutical properties. So it's really useful to know what that minimum-energy shape is. One problem: a molecule of length 12 has nearly 180,000 possible shapes. To calculate the energy of just one shape takes about an hour on the National Computing Infrastructure. At 20c an hour, that's $90,000. And a molecule of length 14 has over ten times as many... *
With the ever—increasing speed of supercomputers, the size of molecules amenable to study with ab... more With the ever—increasing speed of supercomputers, the size of molecules amenable to study with ab initio quantum chemistry methods has increased to include molecules with thousands or even millions of possible conformations. For such molecules, the conformational search represents the computational bottleneck, making studies of such molecules challenging and expensive. Genetic Algorithms (GA) are a type of stochastic algorithm that work analogously to Darwinian evolution to locate the fittest individual in a population. We have previously used a meta-GA to optimize a GA [1] for a conformational search [2]. The optimized GA is not dependent on crossover, thus reducing to an Evolutionary Algorithm (EA). We apply this optimized EA to several large molecules and show that the global minimum structure of a molecule with 20 rotatable bonds can be reliably found with less than 2000 ab initio calculations representing only 3 x 10-4 % of the total search space. Fig 1. a) Size of molecule (nu...
... 1. INTRODUCTION The TAIL (Transport Airlift Integrated Logistics) project was conducted as a ... more ... 1. INTRODUCTION The TAIL (Transport Airlift Integrated Logistics) project was conducted as a proof of concept to determine if substantial simulation capability could be developed in a short time frame using xtUML (and BridgePoint tools) with an agile development perspective. ...
We present two sets of tunings that are broadly applicable to conformer searches of isolated mole... more We present two sets of tunings that are broadly applicable to conformer searches of isolated molecules using a genetic algorithm (GA). In order to find the most efficient tunings for the GA, a second GA--a meta-genetic algorithm--was used to tune the first genetic algorithm to reliably find the already known a priori correct answer with minimum computational resources. It is shown that these tunings are appropriate for a variety of molecules with different characteristics, and most importantly that the tunings are independent of the underlying model chemistry but that the tunings for rigid and relaxed surfaces differ slightly. It is shown that for the problem of molecular conformational search, the most efficient GA actually reduces to an evolutionary algorithm.
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Papers by Zoe E Brain