Computer-aided design of amino acid-based therapeutics: a review

Farhadi, Tayebeh; Hashemian, Seyed MohammadReza

Computer-aided design of amino acid-based therapeutics to model peptide binding to targets of interest. 76, 77 Finally, a model was built to estimate peptide ΔG values for binding to the class I major histocompatibility complex (MHC) protein HLA-A*0201. 78 Furthermore, in a wide range of studies, antimicrobial peptides were successfully analyzed by using the property-based approach. 79 For example, a machinelearning method was employed to design novel antimicrobial peptides. 80 The victory of the property-based methods with antimicrobial peptides may be explained by the fact that the desired biologic activity of membrane disruption is relatively nonspecific. 13 In the case of conformation-based peptide design, computational techniques were developed to predict the conformational ensembles or structure of peptides and analyze the SARs. 81,82 PEP-FOLD is an online tool used to predict the 3D structures of peptides of length 9-36 residues. 81 A remarkable suggestion from the data is that PEP-FOLD seems to solve the conformational sampling problem. 13, 81 In order to search conformational spaces of a peptide, long timescale molecular dynamic simulations have been employed. 83, 84 Besides, quantum mechanical calculations are promising to address the scoring deficiency in the peptide conformational examination. 85 Apparently, to affect the peptide design processes positively, improving the major theoretical and technical issues is necessary before such computationally sophisticated and costly procedures.