MISTRAL: a tool for energy-based multiple structural alignment of proteins.

Area of Science:

• Structural Biology
• Bioinformatics
• Computational Biology

Background:

• The increasing number of protein structures necessitates efficient algorithms for detecting structural correspondences.
• Identifying structural equivalences is computationally intensive due to the vast combinatorial space of possible amino acid pairings.
• Existing methods face challenges in providing reliable statistical significance for protein alignments.

Purpose of the Study:

• To introduce MISTRAL (Multiple STRuctural ALignment), a novel strategy for multiple protein alignment.
• To address the computational demands and statistical significance challenges in protein structure comparison.
• To offer a new tool for analyzing the structural relationships between proteins.

Main Methods:

• MISTRAL employs an energy function minimization approach.
• It operates in the low-dimensional space of relative rotations and translations between molecules.
• This method avoids exhaustive combinatorial searches inherent in traditional algorithms.

Main Results:

• MISTRAL successfully performs multiple protein alignment by minimizing an energy function.
• The energy minimization strategy bypasses computationally expensive combinatorial searches.
• The method yields pairwise alignment scores with reliable a priori statistical significance.

Conclusions:

• MISTRAL offers an efficient and statistically robust method for multiple protein alignment.
• The approach simplifies the detection of structural correspondences and their significance.
• MISTRAL is available as a free standalone program and web service for academic users.