Breast cancer is a significant global concern, with tamoxifen, the standard treatment, raising long-term safety issues due to side effects. In this study, we evaluated the potential of five onoceranoid triterpenes from Lansium domesticum Corr. cv. kokosan against estrogen receptor alpha (ERα) using in silico techniques. Utilizing molecular docking, Lipinski’s rule of five, in silico ADMET, and molecular dynamics simulations, we assessed the potency of five onoceranoid triterpenes against ERα. Molecular docking indicated competitive binding energies for these triterpenes relative to the active form of tamoxifen (4OHT) and estradiol, an ERα native ligand. Three triterpenes met drug-likeness criteria with favorable ADMET profiles. Notably, 2 demonstrated superior binding affinity in molecular dynamics simulations, outperforming estradiol, closely followed by 3 and 4. Hierarchical clustering on principal components (HCPC) and the spatial distribution of contact surface area (CSA) analyses suggest that these triterpenes, especially 2, may act as antagonist ligands akin to 4OHT. These findings highlight the potential of onoceranoid triterpenes in treating ERα-related breast cancer.

LL-37 is a membrane-active antimicrobial peptide (AMP) that could disrupt the integrity of bacterial membranes due to its inherent cationic and amphipathic nature. Developing a shorter derivative of a long peptide such as LL-37 is of great interest, as it can reduce production costs and cytotoxicity. However, more detailed information about the residual interaction between LL-37 and the membrane is required for further optimization. Previously, molecular dynamics simulation using mixed all-atom and united-atom force fields showed that LL-37 could penetrate the bilayer membrane. This study aimed to perform all-atom molecular dynamics simulations, highlighting the residual interaction of LL-37 with the simplest model of the bacterial membrane, POPE:POPG (2:1), and compare its interaction with the POPC, which represents the eukaryotic membrane. The result showed leucine–leucine as the leading residues of LL-37 that first contact the membrane surface. Then, the cationic peptide of LL-37 started to penetrate the membrane by developing salt bridges between positively charged amino acids, Lys–Arg, and the exposed phosphate group of POPE:POPG, which is shielded in POPC. Residues 18 to 29 are suggested as the core region of LL-37, as they actively interact with the POPE:POPG membrane, not POPC. These results could provide a basis for modifying the amino acid sequence of LL-37 and developing a more efficient design for LL-37 derivatives.

Epitope-based peptide vaccine can elicit T-cell immunity against SARS-CoV-2 to clear the infection. However, finding the best epitope from the whole antigen is challenging. A peptide screening using immunoinformatics usually starts from MHC-binding peptide, immunogenicity, cross-reactivity with the human proteome, to toxicity analysis. This pipeline classified the peptides into three categories, i.e., strong-, weak-, and non-binder, without incorporating the structural aspect. For this reason, the molecular detail that discriminates the binders from non-binder is interesting to be investigated. In this study, five CTL epitopes against HLA-A*02:01 were identified from the coarse-grained molecular dynamics-guided immunoinformatics screening. The strong binder showed distinctive activities from the non-binder in terms of structural and energetic properties. Furthermore, the second residue from the nonameric peptide was most important in the interaction with HLA-A*02:01. By understanding the nature of MHC-peptide interaction, we hoped to improve the chance of finding the best epitope for a peptide vaccine candidate.

Therapeutic antibodies face on-target/off-tumor toxicity, causing adverse effects such as cardiotoxicity, skin rashes, and organ inflammation.