We have long known that the characterization of protein three-dimensional structure is key to obtaining a detailed understanding of protein function. Computational approaches to protein structure characterization have largely addressed a narrow formulation of the problem, where the goal is the determination of one structure, also known as the native structure, from a given protein amino-acid sequence. However, many researchers over the years have argued for broadening our view of proteins to account for the multiplicity of native structures.

Instructions: 

The .zip file contains 3 folders when unzipped. We provide the details of each folder below.

 

“monomorphic_benchmark_targets” folder: Contains 20 protein targets organized into 20 subfolders. Data for each protein is provided in a subfolder named with its pdb id. Each such subfolder contains the following 4 files.

  1. A .fasta file containing the amino-acid sequence of the protein.

  2. A .pdb file containing the native tertiary conformation coordinates. Detailed format for a .pdb file can be found in http://www.wwpdb.org/documentation/file-format

  3. A .frag3 file containing the fragments of length 3 for the protein sequence generated from http://old.robetta.org/

  4. A .frag9 file containing the fragments of length 9 for the protein sequence generated from http://old.robetta.org/

 

“monomorphic_casp_targets” folder: Contains 10 protein targets organized into 10 subfolders. Data for each protein is provided in a subfolder named with its casp id. Each such subfolder contains the following 4 files.

  1. A .fasta file containing the amino-acid sequence of the protein.

  2. A .pdb file containing the native tertiary conformation coordinates.

  3. A .frag3 file containing the fragments of length 3 for the protein sequence generated from http://old.robetta.org/

  4. A .frag9 file containing the fragments of length 9 for the protein sequence generated from http://old.robetta.org/

 

“metamorphic_benchmark_targets” folder: Contains 18 pairs of protein targets organized into 18 subfolders. Data for each target pair is provided in a subfolder named with its pair id (as indicated in the paper). Each such subfolder contains the following 5 files.

  1. A .fasta file containing the amino-acid sequence common to the pair of target proteins.

  2. A .pdb file containing the native tertiary conformation coordinates for the first target in the target pair.

  3. A .pdb file containing the native tertiary conformation coordinates for the second target in the target pair.

  4. A .frag3 file containing the fragments of length 3 for the protein sequence generated from http://old.robetta.org/

  5. A .frag9 file containing the fragments of length 9 for the protein sequence generated from http://old.robetta.org/

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The metaheuristic optimization algorithms are relatively the new kinds of optimization algorithms which are widely used for difficult optimization problems in which the classic methods cannot be applied and are considered as known and very broad methods for crucial optimization problems. Here, a new metaheuristic optimization algorithm is presented for which the main idea is extracted from a kind of motion in physics and is expected to have better results compared to other optimization algorithms in this field to present a novel method for achieving a more desirable point.

Instructions: 

Please Download From HERE. (Source Code & Paper)

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