The protein folding problem is a minimization problem in which the energy function is often regarded as the fitness function. There are several models for protein folding prediction including the hydrophobic-hydrophilic (HP) model. Though this model is an elementary one, it is widely used as a test-bed for faster execution of new algorithms. Fitness computation is one of the major computational parts of the HP model. This paper proposes an efficient search (ES) approach for computing the fitness value requiring only O(n) complexity in contrast to the full search (FS) approach that requires O(n2) complexity. The efficiency of the proposed ES approach results due to its utilization of some inherent properties of the HP model. The ES approach represents residues in a Cartesian coordinate framework and then uses relative distance and coordinate polarity to reduce complexity.