PepQSAR: a comprehensive data source and information platform for peptide quantitative structure-activity relationships

Overview and limitations of database in global traditional medicines: A narrative review

The study of traditional medicine has garnered significant interest, resulting in various research areas including chemical composition analysis, pharmacological research, clinical application, and quality control. The abundance of available data has made databases increasingly essential for researchers to manage the vast amount of information and explore new drugs. In this article we provide a comprehensive overview and summary of 182 databases that are relevant to traditional medicine research, including 73 databases for chemical component analysis, 70 for pharmacology research, and 39 for clinical application and quality control from published literature (2000-2023). The review categorizes the databases by functionality, offering detailed information on websites and capacities to facilitate easier access. Moreover, this article outlines the primary function of each database, supplemented by case studies to aid in database selection. A practical test was conducted on 68 frequently used databases using keywords and functionalities, resulting in the identification of highlighted databases. This review serves as a reference for traditional medicine researchers to choose appropriate databases and also provides insights and considerations for the function and content design of future databases.

Structure-based improvement of the binding affinity and recognition specificity of peptide competitors to target pediatric IL-5R/IL-5 interaction by gluing halogen bonds at their complex interface

Human interleukin-5 (IL-5) cytokine mediates the development of eosinophils and is involved in a variety of immune inflammatory responses that play a major role in the pathogenesis of childhood asthma, leukemia, and other pediatric allergic diseases. The immunomodulatory cytokine functions by binding to its cognate cell surface receptor IL-5R in a sheet-by-sheet manner, which can be conformationally mimicked and competitively disrupted by a double-stranded cyclic AF18748 peptide. In this study, we systematically examined the co-crystallized complex structure of human IL-5R with AF18748 peptide and rationally designed a halogen bond to glue at the protein-peptide complex interface by substituting the indole moiety of AF18748 Trp13 residue with a halogen atom (X = F, Cl, Br, or I). High-level theoretical calculations imparted presence of the halogen bond between the oxygen atom (O) of IL-5R Glu58 backbone and the halogen atom (X) of AF18748 Trp13 side chain. Experimental assays confirmed that the halogen bond can promote peptide binding moderately or considerably. More importantly, the halogen bond not only enhances peptide affinity to IL-5R, but also improves peptide selectivity for its cognate IL-5R over other noncognate IL-R proteins. As might be expected, the affinity and selectivity conferred by halogen bond increase consistently in the order: H < F < Cl < Br < I. Structural modeling revealed that the halogen bond plus its vicinal π-cation-π stacking co-define a ringed noncovalent system at the complex interface, which involves a synergistic effect to effectively improve the peptide binding potency and recognition specificity.

Bioinformatics and bioactive peptides from foods: Do they work together?

We live in the Big Data Era which affects many aspects of science, including research on bioactive peptides derived from foods, which during the last few decades have been a focus of interest for scientists. These two issues, i.e., the development of computer technologies and progress in the discovery of novel peptides with health-beneficial properties, are closely interrelated. This Chapter presents the example applications of bioinformatics for studying biopeptides, focusing on main aspects of peptide analysis as the starting point, including: (i) the role of peptide databases; (ii) aspects of bioactivity prediction; (iii) simulation of peptide release from proteins. Bioinformatics can also be used for predicting other features of peptides, including ADMET, QSAR, structure, and taste. To answer the question asked "bioinformatics and bioactive peptides from foods: do they work together?", currently it is almost impossible to find examples of peptide research with no bioinformatics involved. However, theoretical predictions are not equivalent to experimental work and always require critical scrutiny. The aspects of compatibility of in silico and in vitro results are also summarized herein.

Recent Advances on Antimicrobial Peptides from Milk: Molecular Properties, Mechanisms, and Applications

Traditional antibiotics are facing a tremendous challenge due to increased antimicrobial resistance; hence, there is an urgent need to find novel antibiotic alternatives. Milk protein-derived antimicrobial peptides (AMPs) are currently attracting substantial attention considering that they showcase an extensive spectrum of antimicrobial activities, with slower development of antimicrobial resistance and safety of raw materials. This review summarizes the molecular properties, and activity mechanisms and highlights the applications and limitations of AMPs derived from milk proteins comprehensively. Also the analytical technologies, especially bioinformatics methodologies, applied in the process of screening, identification, and mechanism illustration of AMPs were underlined. This review will give some ideas for further research and broadening of the applications of milk protein-derived AMPs in the food field.

N-substituting perturbation on the interaction affinity and recognition specificity between rheumatic immune-related Abl SH3 domain and its peptoid ligands

Abl is a nonreceptor tyrosine kinase involved in a variety of disease pathways such as rheumatic immune. Full-length Abl protein consists of a catalytic tyrosine kinase (TK) domain as well as two regulatory Src homology domains 2 and 3 (SH2 and SH3, respectively); the latter recognizes and binds to those natural proline-rich peptide segments containing a PxxP motif on the protein surface of its interacting partners. However, natural peptides cannot bind effectively to the modular domain in high affinity and strong selectivity due to their small size and broad specificity. Here, a synthetic proline-rich peptide p41 was used as template; its structural diversity was extended by combinationally replacing the Pro0 and Pro+3 residues with a number of N-substituted amino acids. Consequently, peptide affinity change upon the replacement was derived to create a systematic N-substituting perturbation profile, from which we identified several N-substitution combinations at the Pro0 and Pro+3 residues of p41 PxxP motif that may moderately or significantly improve the peptide binding potency to Abl; they represent potent peptoid binders of Abl SH3 domain, with affinity improved considerably relative to p41. More significantly, the designed potent peptoids were also found to exhibit a good SH3-selectivity for their cognate Abl over other noncognate nonreceptor tyrosine kinases, with S = 9.7-fold.

Facilitating the drug repurposing with iC/E strategy: A practice on novel nNOS inhibitor discovery

Over the past decades, many existing drugs and clinical/preclinical compounds have been repositioned as new therapeutic indication from which they were originally intended and to treat off-target diseases by targeting their noncognate protein receptors, such as Sildenafil and Paxlovid, termed drug repurposing (DRP). Despite its significant attraction in the current medicinal community, the DRP is usually considered as a matter of accidents that cannot be fulfilled reliably by traditional drug discovery protocol. In this study, we proposed an integrated computational/experimental (iC/E) strategy to facilitate the DRP within a framework of rational drug design, which was practiced on the identification of new neuronal nitric oxide synthase (nNOS) inhibitors from a structurally diverse, functionally distinct drug pool. We demonstrated that the iC/E strategy is very efficient and readily feasible, which confirmed that the phosphodiesterase inhibitor DB06237 showed a high inhibitory potency against nNOS synthase domain, while other two general drugs, i.e. DB02302 and DB08258, can also inhibit the synthase at nanomolar level. Structural bioinformatics analysis revealed diverse noncovalent interactions such as hydrogen bonds, hydrophobic forces and van der Waals contacts across the complex interface of nNOS active site with these identified drugs, conferring both stability and specificity for the complex recognition and association.

Coupled folding-upon-binding of human tumor suppressor MIG6 to lung cancer EGFR kinase domain and molecular trimming/stapling of MIG6-derived β-hairpins to target the coupling event

Human epidermal growth factor receptor (EGFR) is involved in strong association with malignant proliferation, which has been shown to play a central role in the development and progression of non-small cell lung cancer and other solid tumors. The tumor-suppressor protein MIG6 is a negative regulator of EGFR kinase activity by binding at the activation interface of asymmetric dimer of EGFR kinase domain to disrupt EGFR dimerization and then inactivate the kinase. The protein adopts two discrete fragments 1 and 2 to directly interact with EGFR. It is revealed that the MIG6 fragment 2 is intrinsically disordered in free unbound state, but would fold into a well-structured β-hairpin when binding to EGFR, thus characterized by a so-called coupled folding-upon-binding process, which can be regarded as a compromise between favorable direct readout and unfavorable indirect readout. Here, a 23-mer F2P peptide was derived from MIG6 fragment 2, trimmed into a 17-mer tF2P peptide that contains the binding hotspot region of the fragment 2, and then constrained with an ordered hairpin conformation in free unbound state by disulfide stapling, finally resulting in a rationally stapled/trimmed stF2P peptide that largely minimizes the unfavorable indirect readout effect upon its binding to EGFR kinase domain, with affinity improved considerably upon the trimming and stapling/trimming. These rationally designed β-hairpin peptides may be further exploited as potent anti-lung cancer agents to target the activation event of EGFR dimerization.