Novel algorithms for searching conformational space

Byrne, Deirdre G.; Li, Jin; Platt, Eric; Robson, Barry; Weiner, Paul K.

doi:10.1007/bf00124350

Cited by 21 publications

(7 citation statements)

References 7 publications

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“…Second, the search is easily frustrated due to the extreme ruggedness of this force field. Many algorithms have been published that tackle the problem of global energy optimization in rugged landscapes, such as Monte Carlo with minimization, [1] conformational space annealing, [2] potential-energy contour tracing, [ 3] replica exchange, [4] stochastic tunneling, [5] iterative looprelax (ILR), [6] and countless others (for two excellent reviews, see Berne and Straub [7] and Christen and van Gunsteren [8] )…”

Section: Introductionmentioning

confidence: 99%

Efficient sampling of protein conformational space using fast loop building and batch minimization on highly parallel computers

2012

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All-atom sampling is a critical and compute-intensive end stage to protein structural modeling. Because of the vast size and extreme ruggedness of conformational space, even close to the native structure, the high-resolution sampling problem is almost as difficult as predicting the rough fold of a protein. Here, we present a combination of new algorithms that considerably speed up the exploration of very rugged conformational landscapes and are capable of finding heretofore hidden low-energy states. The algorithm is based on a hierarchical workflow and can be parallelized on supercomputers with up to 128,000 compute cores with near perfect efficiency. Such scaling behavior is notable, as with Moore’s law continuing only in the number of cores per chip, parallelizability is a critical property of new algorithms. Using the enhanced sampling power, we have uncovered previously invisible deficiencies in the Rosetta force field and created an extensive decoy training set for optimizing and testing force fields.

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Section: Introductionmentioning

confidence: 99%

Efficient sampling of protein conformational space using fast loop building and batch minimization on highly parallel computers

2012

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“…Over the past several years, a multitude of conformational search methods have been devised for generating the low-energy (and hence relevant) conformers of both cyclic and acyclic molecules, and the practicing computational chemist can now choose from a wide variety of procedures for conformational searching − the stochastic (sometimes referred to as Monte Carlo) variation of torsion angles − (including methods that rely on the genetic algorithm − ), methods based on Metropolis Monte Carlo , (including simulated annealing − ), the stochastic variation of Cartesian coordinates, − the stochastic variation of internuclear distances (distance geometry), − methods that employ molecular dynamics, , and the flapping, , flipping, or flexing of rings or mapping of rings onto generic shapes …”

Section: Introductionmentioning

confidence: 99%

Low Mode Search. An Efficient, Automated Computational Method for Conformational Analysis: Application to Cyclic and Acyclic Alkanes and Cyclic Peptides

Dietrich¹,

Heınze²,

et al. 1996

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The location of energy minima on the conformational energy surface of molecules by computational methods (conformational searching) continues to play a key role in computer-assisted molecular modeling. Although a number of conformational search procedures have been devised over the past several years, new more efficient methods are urgently needed if molecules with increased complexity are to be treated in a quantitative manner. In this paper we describe a method, termed low-mode search (LMOD), which is based on eigenvector following (or mode following), for the exhaustive exploration of the potential energy hypersurface of molecules. It is particularly efficient at searching the conformational space of both cyclic and acyclic molecules, and we describe its effectiveness for a number of conformational search problems including acyclic, monocyclic, and bicyclic hydrocarbons and cyclic pentapeptides. No special treatment of rings in cyclic molecules is necessary, nor is it necessary to define rotatable bonds. LMOD generates structures “automatically” with minimum input from the user. We demonstrate that LMOD is one of the most efficient procedures yet devised for conformational searching of small- to medium-sized molecules.

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“…Randomized techniques are popular for conformational search problems that do not involve pharmacophore constraints (see, e.g., refs. 34, 21, 35–37).…”

Section: Randomized Conformational Search With Constraintsmentioning

confidence: 99%

A randomized kinematics-based approach to pharmacophore-constrained conformational search and database screening

et al. 2000

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Computational tools have greatly expedited the pharmaceutical drug design process in recent years. One common task in this process is the search of a large library for small molecules that can achieve both a low‐energy conformation and a prescribed pharmacophore. The pharmacophore expresses constraints on the 3D structure of the molecule by specifying relative atom positions that should be maintained to increase the likelihood that the molecule will bind with the receptor site. This article presents a pharmacophore‐based database screening system that has been designed, implemented, and tested on a molecular database. The primary focus of this article is on a simple, randomized conformational search technique that attempts to simultaneously reduce energy and maintain pharmacophore constraints. This enables the identification of molecules in a database that are likely to dock with a given protein, which can serve as a powerful aid in the search for better drug candidates. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 731–747, 2000

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Novel algorithms for searching conformational space

Cited by 21 publications

References 7 publications

Efficient sampling of protein conformational space using fast loop building and batch minimization on highly parallel computers

Efficient sampling of protein conformational space using fast loop building and batch minimization on highly parallel computers

Low Mode Search. An Efficient, Automated Computational Method for Conformational Analysis: Application to Cyclic and Acyclic Alkanes and Cyclic Peptides

A randomized kinematics-based approach to pharmacophore-constrained conformational search and database screening

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