Bioactive peptide therapeutics has been a long-standing research topic. Notably, the antimicrobial peptides (AMPs) have been extensively studied for its therapeutic potential. Meanwhile, the demand for annotating other therapeutic peptides, such as antiviral peptides (AVPs) and anticancer peptides (ACPs), also witnessed an increase in recent years. However, we conceive that the structure of peptide chains and the intrinsic information between the amino acids is not fully investigated among the existing protocols. Therefore, we develop a new graph deep learning model, namely TP-LMMSG, which offers lightweight and easy-to-deploy advantages while improving the annotation performance in a generalizable manner. The results indicate that our model can accurately predict the properties of different peptides. The model surpasses the other state-of-the-art models on AMP, AVP and ACP prediction across multiple experimental validated datasets. Moreover, TP-LMMSG also addresses the challenges of time-consuming pre-processing in graph neural network frameworks. With its flexibility in integrating heterogeneous peptide features, our model can provide substantial impacts on the screening and discovery of therapeutic peptides. The source code is available at https://github.com/NanjunChen37/TP_LMMSG.

The antimicrobial peptide database (APD) has served the antimicrobial peptide field for 18 years. Because it is widely used in research and education, this article documents database milestones and key events that have transformed it into the current form. A comparison is made for the APD peptide statistics between 2010 and 2020, validating the major database findings to date. We also describe new additions ranging from peptide entries to search functions. Of note, the APD also contains antimicrobial peptides from host microbiota, which are important in shaping immune systems and could be linked to a variety of human diseases. Finally, the database has been re-programmed to the web branding and latest security compliance of the University of Nebraska Medical Center. The reprogrammed APD can be accessed at https://aps.unmc.edu.

Although mutated HLA ligands are considered ideal cancer-specific immunotherapy targets, evidence for their presentation is lacking in hepatocellular carcinomas (HCCs). Employing a unique multi-omics approach comprising a neoepitope identification pipeline, we assessed exome-derived mutations naturally presented as HLA class I ligands in HCCs.
In-depth multi-omics analyses included whole exome and transcriptome sequencing to define individual patient-specific search spaces of neoepitope candidates. Evidence for the natural presentation of mutated HLA ligands was investigated through an in silico pipeline integrating proteome and HLA ligandome profiling data.
The approach was successfully validated in a state-of-the-art dataset from malignant melanoma, and despite multi-omics evidence for somatic mutations, mutated naturally presented HLA ligands remained elusive in HCCs. An analysis of extensive cancer datasets confirmed fundamental differences of tumor mutational burden in HCC and malignant melanoma, challenging the notion that exome-derived mutations contribute relevantly to the expectable neoepitope pool in malignancies with only few mutations.
This study suggests that exome-derived mutated HLA ligands appear to be rarely presented in HCCs, inter alia resulting from a low mutational burden as compared to other malignancies such as malignant melanoma. Our results therefore demand widening the target scope for personalized immunotherapy beyond this limited range of mutated neoepitopes, particularly for malignancies with similar or lower mutational burden.

Thrombosis represents a major cause of morbidity and mortality around the world. Peptides isolated from natural sources have been proven to have anticoagulant and antithrombotic properties. VITPOR AI, a 16-mer peptide, isolated from Porphyra yezoensis was reported to have anticoagulant property. In this study, the coagulation factor XIIa activity in the presence of VITPOR AI was determined. Molecular modelling was performed to investigate the interaction between peptide and FXIIa. The structure of the peptide was predicted using PEP-FOLD3 server and simulated by molecular dynamics (MD) using GROMACS package. Molecular docking was carried out using peptide-protein docking software, pepATTRACT and its stability was confirmed by MD simulations. The chromogenic substrate assay revealed that the peptide inhibited the amidolytic activity of FXIIa with IC50 of 70.24 μM. The docking result showed peptide interactions through hydrogen bonds with Pro 96, Tyr 99, Glu 146, Gly 193 and Ser 195 of FXIIa. The MD simulation demonstrated that the peptide\'s binding with the FXIIa was stable as it did not move away from its binding region throughout the simulation period of 100 ns Moreover, MM/PBSA analysis also indicated a stable binding between the protein and peptide. These results suggest that the inhibition of the FXIIa activity might be due to binding of the peptide to oxyanion hole of the catalytic site. Thus, VITPOR AI could be explored as a potent anticoagulant which inhibits only intrinsic pathway of coagulation cascade but does not affect the extrinsic pathway.

The bed bug Cimex lectularius is a globally distributed human ectoparasite with fascinating biology. It has recently acquired resistance against a broad range of insecticides, causing a worldwide increase in bed bug infestations. The recent annotation of the bed bug genome revealed a full complement of neuropeptide and neuropeptide receptor genes in this species. With regard to the biology of C. lectularius, neuropeptide signaling is especially interesting because it regulates feeding, diuresis, digestion, as well as reproduction and also provides potential new targets for chemical control. To identify which neuropeptides are translated from the genome-predicted genes, we performed a comprehensive peptidomic analysis of the central nervous system of the bed bug. We identified in total 144 different peptides from 29 precursors, of which at least 67 likely present bioactive mature neuropeptides. C. lectularius corazonin and myosuppressin are unique and deviate considerably from the canonical insect consensus sequences. Several identified neuropeptides likely act as hormones, as evidenced by the occurrence of respective mass signals and immunoreactivity in neurohemal structures. Our data provide the most comprehensive peptidome of a Heteropteran species so far and in comparison suggest that a hematophageous life style does not require qualitative adaptations of the insect peptidome.