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  1. Home
  2. Investigations On Multiple Protein Scaffold Filling.
  1. Home
  2. Investigations On Multiple Protein Scaffold Filling.

Related Experiment Video

Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions
08:07

Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions

Published on: August 2, 2015

Investigations on Multiple Protein Scaffold Filling.

Ismoiljon Muzaffarov1, Xiaowen Liu2, Letu Qingge3

  • 1Gianforte School of Computing, Montana State University, Bozeman, Montana, USA.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|June 19, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

This study addresses protein scaffold filling challenges. We developed algorithms to optimize Blosum62 scores for sequence filling, with promising heuristic results for specific protein types.

Keywords:
colinear chaininggreedy algorithmslower boundprotein scaffold fillingprotein sequencingsimulated annealingtop-down and bottom-up methods

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Structural Studies of Macromolecules in Solution using Small Angle X-Ray Scattering
07:19

Structural Studies of Macromolecules in Solution using Small Angle X-Ray Scattering

Published on: November 5, 2018

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Proteomics

Background:

  • Protein scaffold filling is crucial for sequence reconstruction and analysis.
  • Optimizing Blosum62 scores is key for accurate sequence alignment and comparison.

Purpose of the Study:

  • To investigate computational problems in multiple protein scaffold filling.
  • To develop algorithms for maximizing Blosum62 scores in sequence filling, with or without references.

Main Methods:

  • Theoretical analysis of algorithmic complexity, including lower bounds based on the Strong Exponential Time Hypothesis (SETH).
  • Development of a dynamic programming approach for solving the optimization problem in polynomial time for two or more scaffolds.
  • Implementation of heuristic algorithms for the specific case of three scaffolds.

Main Results:

  • A lower bound of Ω(n^(k-ε)) is established for finding k scaffolds, assuming SETH.
  • A polynomial-time dynamic programming solution is presented for the general case with two or more scaffolds.
  • Heuristic algorithms demonstrated promising empirical results on diverse protein datasets (antibody, myoglobin, etc.).

Conclusions:

  • The computational complexity of protein scaffold filling is significant, with theoretical lower bounds established.
  • Dynamic programming offers an efficient solution for multiple scaffolds, while heuristics provide practical approaches for specific cases.
  • The developed methods and heuristics show potential for applications in protein sequence analysis and reconstruction.