PdbAlign, PdbDist and DistAlign: tools to aid in relating sequence variability to structure

Area of Science:

• Bioinformatics
• Structural Biology
• Computational Biology

Background:

• Multiple sequence alignment (MSA) is crucial for sequence analysis.
• Integrating 3D structural information with MSA enhances analysis.
• Understanding sequence variability in relation to protein structure is key for biological insights.

Purpose of the Study:

• To develop automated methods for mapping sequence variability onto known 3D protein structures.
• To annotate MSA column positions with their proximity to known ligand binding sites.
• To provide tools for analyzing sequence variability in the context of protein structure and function.

Main Methods:

• Utilizing known 3D atomic coordinates of aligned sequences.
• Mapping sequence variability (e.g., mutation data) onto the 3D structure.
• Calculating the distance of each MSA column position to the binding site.
• Developing software programs to automate these mapping and annotation processes.

Main Results:

• Successful mapping of sequence variability onto atomic coordinates.
• Annotation of MSA positions with their 'distance' from binding sites.
• Demonstration of how these annotations provide insights into drug specificity, particularly for viral mutants.

Conclusions:

• Automated analysis of sequence variability in conjunction with 3D structure offers significant advantages.
• This approach enhances understanding of molecular interactions and drug specificity.
• The described programs facilitate deeper insights into biological systems, especially in areas like virology and drug development.