Dataset Information

MR-REX: molecular replacement by cooperative conformational search and occupancy optimization on low-accuracy protein models.

ABSTRACT: Molecular replacement (MR) has commonly been employed to derive the phase information in protein crystal X-ray diffraction, but its success rate decreases rapidly when the search model is dissimilar to the target. MR-REX has been developed to perform an MR search by replica-exchange Monte Carlo simulations, which enables cooperative rotation and translation searches and simultaneous clash and occupancy optimization. MR-REX was tested on a set of 1303 protein structures of different accuracies and successfully placed 699 structures at positions that have an r.m.s.d. of below 2?Å to the target position, which is 10% higher than was obtained by Phaser. However, cases studies show that many of the models for which Phaser failed and MR-REX succeeded can be solved by Phaser by pruning them and using nondefault parameters. The factors effecting success and the parts of the methodology which lead to success are studied. The results demonstrate a new avenue for molecular replacement which outperforms (and has results that are complementary to) the state-of-the-art MR methods, in particular for distantly homologous proteins.

SUBMITTER: Virtanen JJ

PROVIDER: S-EPMC6038387 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Publications

MR-REX: molecular replacement by cooperative conformational search and occupancy optimization on low-accuracy protein models.

Virtanen Jouko J JJ Zhang Yang Y

Acta crystallographica. Section D, Structural biology 20180608 Pt 7

Molecular replacement (MR) has commonly been employed to derive the phase information in protein crystal X-ray diffraction, but its success rate decreases rapidly when the search model is dissimilar to the target. MR-REX has been developed to perform an MR search by replica-exchange Monte Carlo simulations, which enables cooperative rotation and translation searches and simultaneous clash and occupancy optimization. MR-REX was tested on a set of 1303 protein structures of different accuracies an ...[more]

PMID: 29968671

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Project description:The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS) is introduced. It is inspired by the natural behavior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emitted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and validations were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of convergence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive) and exploitation (intensive) of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be used in global optimization problems.

Dataset Information

MR-REX: molecular replacement by cooperative conformational search and occupancy optimization on low-accuracy protein models.

Publications

MR-REX: molecular replacement by cooperative conformational search and occupancy optimization on low-accuracy protein models.

Similar Datasets

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