Energy minimum theorem based on AGA, Lyapunov and force field for CADD techniques

This paper employs the energy minimum to enhance drug docking efficiency in a computer aided drug design (CADD) system. The energy minimum application is used to enhance CADD docking performance. The proposed method is discussed in three aspects, adaptive genetic algorithms (AGA), Lyapunov stability theorem and molecular force field. As in previous researches, docking is the crucial component in drug development. The number of docking sites affects the drug docking speed. Reducing the scope of the geometric search is the key task. This paper proposes AGA to improve geometric molecular docking search efficiency. The Lyapunov stability theorem forwards the stability state identification. Protein folding intention generally finds the most appropriate stability state when the thermodynamic and molecular mechanical free energy has reached the lowest point. The AMBER force field simulation is used to discover the molecular statistical mechanics in a drug-ligand. AGA was found better in terms of processing the geometric graphic search operation. The AGA and Lyapunov algorithms were utilized to sieve out the global energy minimum approach from the numerous, raw docking sites.