In-Silico Analysis of Electronic Structures of Model Polypeptide Chains using Particle Swarm Optimization

Objective: Particle swarm optimization (PSO) algorithm has been clubbed with two numerical methods viz., negative factor counting (NFC) technique and inverse iteration method to investigate the electronic structures and properties of model polypeptide chains. Method: Band structures of polyglycine, polyalanine and polythreonine obtained from abinitio Hartree-Fock crystal orbital method using minimal basis (MB) set, double zeta (DZ) set and quasi-particle (DZ+QP) set respectively have been used as input to obtain the electronic properties of the model peptide sequences using the proposed computational procedure. Results: The results obtained indicate threonine to have strong influence over properties in comparison to alanine and glycine. Ternary sequences offer better electronic delocalization to the chain in comparison to the binary combinations. Better electronic properties are obtained with DZ basis set than with MB basis set. Also, it is found that with better electron correlation, the fundamental band gap value decreases by 3-4 eV. Conclusion: The density of states curves obtained using NFC technique is in good agreement with the PSO results. In all, coupling PSO algorithm with the otherwise computationally expensive quantum calculations not only fastens the process but also brings out useful output worthy of experimental investigations.