This document presents a method for dimensionality reduction in protein structure prediction using an automated alphabet reduction approach guided by evolutionary algorithms. The proposed method reduces the traditional 20-letter amino acid alphabet to as few as three letters while maintaining predictive accuracy, validated through a genetics-based machine learning system. The results indicate that significant alphabet reduction can yield interpretable rules for predicting protein structures without a substantial loss in accuracy.