Global Optimization of Clusters, Crystals, and Biomolecules

Wales, David J.; Scheraga, Harold A.

doi:10.1126/science.285.5432.1368

Cited by 1,049 publications

(936 citation statements)

References 95 publications

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“…Indeed, even more powerful approaches like the "basin-hopping" 39 or GAs 30, 40 have difficulties to find minima for those double-funnel clusters. 41 Since there is no table of putative global minima for the potential functions applied in this work, we have used for comparison those obtained by local minimization of the corresponding LJ clusters. The putative global minimum for a given argon cluster modeled by each potential function is not reached in the GA optimization whenever the energy of the optimum so obtained is higher than that arising from the local minimization of the corresponding LJ structure.…”

Section: Difficult Cases For Global Optimizationmentioning

confidence: 99%

On the Use of Different Potential Energy Functions in Rare-Gas Cluster Optimization by Genetic Algorithms: Application to Argon Clusters

Marques¹,

Pereira²,

Leitão³

2008

J. Phys. Chem. A

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We study the effect of the potential energy function on the global minimum structures of argon clusters arising in the optimization performed by genetic algorithms (GAs). We propose a robust and efficient GA which allows for the calculation of all of the putative global minima of Ar N (N ) 3-78) clusters modeled with four different potentials. Both energetic and structural properties of such minima are compared among each other and with those previously obtained for the Lennard-Jones function. In addition, the possibility of obtaining global minima of one potential through local optimization over the corresponding cluster geometry given by other potentials was associated with some structural parameters. The influence of the contribution from the three-body (Axilrod-Teller-Muto) triple-dipole potential (including or not a damping function to describe its correct behavior at smaller interatomic distances) has also been analyzed.

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Section: Difficult Cases For Global Optimizationmentioning

confidence: 99%

On the Use of Different Potential Energy Functions in Rare-Gas Cluster Optimization by Genetic Algorithms: Application to Argon Clusters

Marques¹,

Pereira²,

Leitão³

2008

J. Phys. Chem. A

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“…[13][14][15][16] Basin-hopping has been succesfully applied for locating the global minima in a wide range of problems, including atomic and molecular clusters, glass-formers, and biomolecules. As our interest turns to larger systems, all-atom representations become prohibitively expensive after more than a few thousand atoms.…”

Section: Introductionmentioning

confidence: 99%

A Local Rigid Body Framework for Global Optimization of Biomolecules

Kusumaatmaja

Whittleston

Wales

2012

J. Chem. Theory Comput.

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Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractWe present a local rigid body framework for simulations of biomolecules. In this framework, arbritrary sets of atoms may be treated as rigid bodies. Such groupings reduce the number of degrees of freedom, which can result in a significant reduction of computational time.As benchmarks, we consider global optimization for the tryptophan zipper (trpzip 1, 1LE0; using the CHARMM force field) and chignolin (1UAO; using the AMBER force field). We use a basin-hopping algorithm to find the global minima and compute the mean first encounter time from random starting configurations with and without the local rigid body framework.Minimal groupings are used, where only peptide bonds, termini and side chain rings are considered rigid. Finding the global minimum is 4.2 and 2.5 times faster, respectively, for trpzip 1 and chignolin, within the local rigid body framework. We further compare O(10 5 ) low-lying local minima to the fully relaxed unconstrained representation for trpzip 1 at different levels of rigidification. The resulting Pearson correlation coefficients, and thus the apparent intrinsic rigidity of the various groups, appear in the following order: side chain rings > termini > trigonal planar centres ≥ peptide bonds side chains. This approach is likely to be even more beneficial for structure prediction in larger biomolecules.

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“…The latter category of methods includes algorithms that explore the topography of the conformational energy surface aiming to find energy minima corresponding to stable states and probable transition paths between such states. Methods to find energy minima [13] usually combine conformational sampling and energy minimization. The most widely used methods are based on genetic algorithms [14], the simulated annealing procedure [15], the basin hopping strategy [16], and taboo search [17].…”

Section: Introductionmentioning

confidence: 99%

Randomized tree construction algorithm to explore energy landscapes

et al. 2011

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We report in the present work a new method for exploring conformational energy landscapes. The method, called T-RRT, combines ideas from statistical physics and robot path planning algorithms. A search tree is constructed on the conformational space starting from a given state. The tree expansion is driven by a double strategy: on the one hand, it is naturally biased towards yet unexplored regions of the space; on the other, a Monte Carlo-like transition test guides the expansion toward energetically favorable regions. The balance between these two strategies is automatically achieved thanks to a self-tuning mechanism. The method is able to efficiently find both, energy minima and transition paths between them. As a proof of concept, the method is applied to two academic benchmarks and to the alanine dipeptide.

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Global Optimization of Clusters, Crystals, and Biomolecules

Cited by 1,049 publications

References 95 publications

On the Use of Different Potential Energy Functions in Rare-Gas Cluster Optimization by Genetic Algorithms: Application to Argon Clusters

On the Use of Different Potential Energy Functions in Rare-Gas Cluster Optimization by Genetic Algorithms: Application to Argon Clusters

A Local Rigid Body Framework for Global Optimization of Biomolecules

Randomized tree construction algorithm to explore energy landscapes

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