Alanine scanning benchmarks for protein design in DNASTAR Lasergene

With Lasergene 16, we introduced alanine and serine hot spot scanning for protein design. These methods allow you allow you to identify important residues in protein folding and are an important first step in many protein design experiments. Hot spot scanning in Lasergene can be completed via a simple point-and-click workflow, and usually takes a few seconds to a few minutes to complete, depending on your parameter settings.

In this article, we explore accuracy of alanine hot spot scanning in multiple software applications, and show you how to perform this workflow with your own data in Protean 3D, part of the Lasergene Protein package.

 

How accurately does alanine scanning in Lasergene predict changes in protein fold stability?

To answer this question, we compared experimentally determined thermodynamic stability data for alanine substitution mutations at nearly every position in the β1 domain of Streptococcal protein G (G β1) to in silico calculations in Lasergene Protein, as well as calculations from five other software tools. Our results show that these tools vary widely in the accuracy of hot spot detection, especially at low error thresholds.

Compared to PopMuSic, FoldX, and three Rosetta methods, Lasergene has the most correct predictions within all error tolerances at or below 1.5 kcal/mol.

 

The Lasergene Protein alanine hot spot scanning method provides the most accurate prediction of energy change in the G β1 protein, with the tightest tolerance of any tool studied

Based on our error tolerance analysis, DNASTAR’s Lasergene Protein produces the most predictions within the lowest error tolerances compared to the experimentally calculated change in energy value. This error analysis considers absolute error: the magnitude of the difference between the predicted and actual change in fold stability.

DNASTAR predictions from Lasergene Protein (Figure 1; top in blue), are the most accurate across all tolerances, even at the lowest error thresholds.

Variant Analysis

In Figure 2, Alanine variants at each of 44 positions within the G β1 are sorted by the experimental energy change value, with the most stabilizing mutations at the top. The magnitude of absolute error for each of the scanning tools is indicated by color, green being lowest error and red being the highest error. The color representing absolute error for DNASTAR hotspot predictions is also mapped onto the G β1 structure shown in Figure 3.