Background Nowadays, conventional medical treatments such as surgery, radiotherapy, and chemotherapy cannot cure all types of cancer. A promising approach to treat solid tumors is the use of tumor-targeting peptides to deliver drugs or active agents selectively. Result Introducing beneficial therapeutic approaches, such as therapeutic peptides and their varied methods of action against tumor cells, can aid researchers in the discovery of novel peptides for cancer treatment. The biomedical applications of therapeutic peptides are highly interesting. These peptides, owing to their high selectivity, specificity, small dimensions, high biocompatibility, and easy modification, provide good opportunities for targeted drug delivery. In recent years, peptides have shown considerable promise as therapeutics or targeting ligands in cancer research and nanotechnology. Conclusion  This study reviews a variety of therapeutic peptides and targeting ligands in cancer therapy. Initially, three types of tumor-homing and cell-penetrating peptides (CPPs) are described, and then their applications in breast, glioma, colorectal, and melanoma cancer research are discussed.

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.

Background Breast cancer is defined as a biological and molecular heterogeneous disorder that originates from breast cells. Genetic predisposition is the most important factor giving rise to this malignancy. The most notable mutations in breast cancer occur in the BRCA1 and BRCA2 genes. Owing to disease heterogeneity, lack of therapeutic target, anti-cancer drug resistance, residual disease, and recurrence, researchers are faced with challenges in developing strategies to treat patients with breast cancer. Results It has recently been reported that epigenetic processes such as DNA methylation and histone modification, as well as microRNAs (miRNAs), have potently contributed to the pathophysiology, diagnosis, and treatment of breast cancer. These observations have persuaded researchers to move their therapeutic approaches beyond the genetic framework toward the epigenetic concept. Conclusion Herein we discuss the molecular and epigenetic mechanisms underlying breast cancer progression and resistance as well as various aspects of epigenetic-based therapies as monotherapy and combined with immunotherapy.

Autoimmune diseases (ADs) could occur due to infectious diseases and vaccination programs. Since millions of people are expected to be infected with SARS-CoV-2 and vaccinated against it, autoimmune consequences seem inevitable. Therefore, we have investigated the whole proteome of the SARS-CoV-2 for its ability to trigger ADs. In this regard, the entire proteome of the SARS-CoV-2 was chopped into more than 48000 peptides. The produced peptides were searched against the entire human proteome to find shared peptides with similar experimentally confirmed T-cell and B-cell epitopes. The obtained peptides were checked for their ability to bind to HLA molecules. The possible population coverage was calculated for the most potent peptides. The obtained results indicated that the SARS-CoV-2 and human proteomes share 23 peptides originated from ORF1ab polyprotein, nonstructural protein NS7a, Surface glycoprotein, and Envelope protein of SARS-CoV-2. Among these peptides, 21 peptides had experimentally confirmed equivalent epitopes. Amongst, only nine peptides were predicted to bind to HLAs with known global allele frequency data, and three peptides were able to bind to experimentally confirmed HLAs of equivalent epitopes. Given the HLAs which have already been reported to be associated with ADs, the ESGLKTIL, RYPANSIV, NVAITRAK, and RRARSVAS were determined to be the most harmful peptides of the SARS-CoV-2 proteome. It would be expected that the COVID-19 pandemic and the vaccination against this pathogen could significantly increase the ADs incidences, especially in populations harboring HLA-B*08:01, HLA-A*024:02, HLA-A*11:01 and HLA-B*27:05. The Southeast Asia, East Asia, and Oceania are at higher risk of AD development.

No abstract