ABSTRACT
Peptides and proteins have great potential as therapeutics. Peptides are considered highly selective and efficacious and, at the same time, are recognized for being relatively safe and well tolerated. For this reason, peptides promise to be the starting point for drug development. The biological function and activity of peptides and proteins are correlated using conformational properties. Peptide activity is related to both the presence of functionally active groups that are bound to a target protein and the conformational properties of the whole peptide. Conformational flexibility, which is investigated by computational methods, gives substantial opportunities for new rational drug design. The behavior of molecular systems is simulated by various computational methods through conformational analysis, molecular dynamics (MDs), potential energy surface (PES), etc., and performed by theoretical molecular modeling methods. The conformational analysis method is a preferred technique for 124analyzing the peptide structure, which is carried out by conformational energy calculations concerning the spatial location of the peptide side and backbone chains. MD techniques determine not only the conformational variation of peptide molecules, which are used as an ingredient of a drug, but also the information where drug molecules bind together, and how they exert their effects. MD is also an applicable tool in understanding solvent effects on peptide conformation. Because of the information derived from simulations of MDs, it can ensure new insights at the molecular level for different biological systems. The present and future of structure-based drug discovery will make use of the advantages of MD.
PES is a method that determines the relationship between molecular structure and energy and has a key role in molecular structure studies. Molecular docking, which comprises different types of algorithms such as MDs and Monte Carlo simulations, is another technique used to explain the preferred binding modes of ligand–receptor complexes, where the ligand is usually a small molecule and the receptor is a protein. Since the interaction between the ligand and the receptor allows us to predict the activation or inhibition of protein, such information may be used for drug design.
