Large contact surfaces of protein–protein interactions (PPIs) remain to be an ongoing issue in the discovery and design of small molecule modulators. Peptides are intrinsically capable of exploring larger surfaces, stable, and bioavailable, and therefore bear a high therapeutic value in the treatment of various diseases, including cancer, infectious diseases, and neurodegenerative diseases. Given these promising properties, a long way has been covered in the field of targeting PPIs via peptide design strategies. In silico tools have recently become an inevitable approach for the design and optimization of these interfering peptides. Various algorithms have been developed to scrutinize the PPI interfaces. Moreover, different databases and software tools have been created to predict the peptide structures and their interactions with target protein complexes. High-throughput screening of large peptide libraries against PPIs; “hotspot” identification; structure-based and off-structure approaches of peptide design; 3D peptide modeling; peptide optimization strategies like cyclization; and peptide binding energy evaluation are among the capabilities of in silico tools. In the present study, the most recent advances in the field of in silico approaches for the design of interfering peptides against PPIs will be reviewed. The future perspective of the field and its advantages and limitations will also be pinpointed.

The clinical applications of therapeutic enzymes are often limited due to their immunogenicity. B-cell epitope removal is an effective approach to solve this obstacle. The identification of hot spot epitopic residues is a critical step in the removal of protein B-cell epitope. Hereof, computational approaches are a suitable alternative to costly and labor-intensive experimental approaches. Arginine deiminase, a Mycoplasma arginine-catabolizing enzyme, is in the clinical trial for treating arginine auxotrophic cancers, especially hepatocellular carcinomas and melanomas through depleting plasma arginine and causing cell starvation. In this study, arginine deiminase from Mycoplasma hominis (MhADI) was computationally analyzed for recognizing and locating its immune-reactive regions. The 3D structure of the bioactive form of MhADI was modeled. The B-cell epitope mapping of protein was performed using various servers with different algorithms. Six segments: 31-40, 48-55, 131-140, 196-206, 294-314, and 331-344 were predicted to be the consensus immunogenic regions. The modification of epitopic hot spot residue was performed to reduce immune-reactiveness. The hot spot residue was selected considering a high B-cell epitope score, convexity index, surface accessibility, flexibility, and hydrophilicity. The structure stability of native and mutant proteins was evaluated through molecular dynamics simulation. The E304L mutein was suggested as a lower antigenic and stable enzyme derivative.

Dengue, a mosquito-borne disease, is caused by four known dengue serotypes. This infection causes a range of symptoms from a mild fever to a sever homorganic fever and death. It is a serious public health problem in subtropical and tropical countries. There is no specific vaccine currently available for clinical use and study on this issue is ongoing. In this study, bioinformatics approaches were used to predict antigenic, immunogenic, non-allergenic, and conserved B and T-cell epitopes as promising targets to design an effective peptide-based vaccine against dengue virus. Molecular docking analysis indicated the deep binding of the identified epitopes in the binding groove of the most popular human MHC I allele (human leukocyte antigens [HLA] A*0201). The final vaccine construct was created by conjugating the B and T-cell identified epitopes using proper linkers and adding an appropriate adjuvant at the N-terminal. The characteristics of the new subunit vaccine demonstrated that the epitope-based vaccine was antigenic, non-toxic, stable, and soluble. Other physicochemical properties of the new designed construct including isoelectric point value, aliphatic index, and grand average of hydropathicity were biologically considerable. Molecular docking of the engineered vaccine with Toll-like receptor 2 (TLR2) model revealed the hydrophobic interaction between the adjuvant and the ligand binding regions in the hydrophobic channel of TLR2. The study results indicated the high potential capability of the new multi-epitope vaccine to induce cellular and humoral immune responses against the dengue virus. Further experimental tests are required to investigate the immune protection capacity of the new vaccine construct in animal models. Communicated by Ramaswamy H. Sarma.

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To study structure-activity relationship of antimicrobial peptides and to design novel antimicrobial peptides with selectivity for bacterial cells, we have performed molecular dynamics simulations of the interaction of Piscidin (Pis1) and its two analogues (Pis1-AA and Pis1-PG) with dipalmitoylphosphatidylcholine (DPPC) bilayer through 45 ns. Our results inform us of the detailed location and orientation of the peptide with respect to the bilayer as well as provide about hydrogen-bond-formation patterns and electrostatics interactions. Simulations show that Pis1 and Pis-AA form the most hydrogen bonds and Pis-PG forms the fewest hydrogen bonds with lipid. Thus, Pis1 and Pis-AA should have stronger interactions with the lipid head group when compared to Pis-PG. Experimental studies have shown that Pis1 and Pis1-AA have a high antimicrobial and hemolytic activities, and Pis1-PG has low hemolytic activity while keeps potent antimicrobial activity. Our results complement the previous experimental studies. According to our MD results and previous experimental studies, Pis1 and Pis1-AA are more effective at the zwitterionic bilayer comparing Pis1-PG. These properties of Pis1-PG could be accordance with its low hemolytic activities.