Jul 2026· International Journal of Peptide Research and Therapeutics· Vol 32· 0 citations· 88 references
TL;DR
The combined computational and experimental approach enabled the identification of peptides with selective cytotoxic effects and favorable predicted immunogenic profiles, demonstrating that integrating computational screening with experimental validation is an effective strategy for accelerating the discovery of selective anticancer peptides.
Abstract
Breast cancer remains one of the leading causes of cancer-related mortality worldwide, highlighting the need for more selective and effective therapies. This study aimed to identify and validate novel anticancer peptides targeting Luminal A (MCF-7) and triple-negative (MDA-MB-231) breast cancer subtypes using an integrated in silico and in vitro approach. Overexpressed proteins in each cell line were identified through literature mining, followed by the construction of protein–protein interaction (PPI) networks using STRING. Conserved motifs within PPI components were identified via multiple sequence alignment using the MEME Suite. Immunogenicity and anticancer potential of the selected motifs were predicted using VaxiJen and AntiCP, respectively. Peptide–target interactions were assessed through molecular docking (PatchDock/FireDock) and refined using molecular dynamics simulations in GROMACS. Based on these analyses, two lead peptides per subtype were selected, synthesized, and experimentally evaluated for cytotoxicity and subcellular localization. Two lead peptides were identified for each breast cancer subtype. Notably, the peptides RVCGDRGFFF and WYLKMMWQW exhibited strong membrane-associated interactions and significantly reduced the viability of MDA-MB-231 cells by approximately 75% and 90%, respectively. The combined computational and experimental approach enabled the identification of peptides with selective cytotoxic effects and favorable predicted immunogenic profiles. These findings demonstrate that integrating computational screening with experimental validation is an effective strategy for accelerating the discovery of selective anticancer peptides. The identified candidates represent promising leads for the development of peptide-based therapeutics targeting specific breast cancer subtypes, with potential applications in oncology.
Breast cancer remains a leading cause of mortality among women globally, underscoring the urgent need for novel therapies that combine high efficacy with minimal adverse effects. This study examines the bioinformatic design of animal-derived therapeutic peptides targeting two key breast cancer biomarkers: matrix metalloproteinase 1 (MMP1) and epidermal growth factor receptor (EGFR). Approximately 1,500 antimicrobial peptides were retrieved from the antimicrobial peptide database 3 (APD3). They were screened for hemolytic properties using the Hemolytik database. This screening resulted in 255 non-hemolytic candidates, which were further screened through VaxiJen 2.0 and ToxinPred2 for antigenicity and allergenicity. Moreover, physicochemical properties were analyzed using the Expasy ProtParam server. We applied thresholds of molecular weight (1.7–3.1 kDa), instability index (≤ 28), and net charge (+ 2 to + 7). Five peptides met all criteria and were screened for anticancer potential using AntiCP 2.0 and ACPred, identifying three overlapping anticancer peptides (ACPs), including Metalnikowin IIA (AP00363) from Palomena prasina, Guentherin (AP00584) from Hylarana guentheri, and P-10 (AP02393) from Ciona intestinalis. Furthermore, peptide structures were modeled using Colab AlphaFold2. Tertiary structures of target proteins were obtained from UniProt, and Buserelin (FDA-approved ACP) was obtained from the DCTPep database. All peptides were docked against MMP1 and EGFR using HDock and ClusPro. AP00363 showed the highest docking affinity with MMP1 and EGFR, scoring −235.61 and −271.70, respectively. Molecular dynamics simulations supported the stability and interaction potential of these peptides. Overall, this study presents promising bioinformatically designed, animal-derived ACPs for targeted breast cancer therapy. Further in vitro and in vivo validation is necessary to assess clinical relevance.
E. K. Oladipo, Omolara Omoboye Adegboye, S. F. Adeyemo et al.· Future Journal of Pharmaceut...· 0 citations
BACKGROUND: Triple-negative breast cancer (TNBC) progression is driven by dysregulation of multiple interconnected signaling pathways rather than a single molecular abnormality, but current treatment strategies TNBC primarily rely on single-target therapy, highlighting the need for therapeutic candidates that may target multiple signaling pathway of TBNC. Tiliroside, a naturally occurring flavonoid glycoside, has demonstrated promising anticancer activity; however, its predicted effects on TNBC-associated oncogenic signaling networks remain poorly understood. Therefore, this study aimed to investigate the predicted molecular mechanisms by which tiliroside may modulate TNBC-associated oncogenic signaling networks.METHODS: Integrated computational approach combining network pharmacology, comparative molecular docking, and induced-fit docking was employed. Potential targets of tiliroside were predicted using SwissTargetPrediction and intersected with TNBC-associated genes retrieved from GeneCards. Protein–protein interaction and KEGG pathway enrichment analyses were performed to identify key molecular targets and signaling pathways. Comparative molecular docking was subsequently conducted using 19 structurally related flavonoids with reported anticancer activities against the identified hub proteins, followed by induced-fit docking to characterize the binding mechanism of tiliroside.RESULTS: Fifteen overlapping targets were identified between tiliroside and TNBC. Network analysis highlighted Akt serine/threonine kinase 1 (AKT1), sarcoma (SRC), and epidermal growth factor receptor (EGFR) as the principal hub genes, while the KEGG enrichment revealed significant involvement of phosphoinositide 3-kinase (PI3K)–AKT, erythroblastic leukemia viral oncogene B (ErbB), EGFR tyrosine kinase inhibitor resistance, focal adhesion, and vascular endothelial growth factor (VEGF) signaling pathways. Tiliroside consistently exhibited one of the most favorable binding profiles among the evaluated flavonoids, with binding energies of −9.41, −8.62, and −8.25 kcal/mol toward AKT1, SRC, and EGFR, respectively. Induced-fit docking further confirmed stable hydrogen-bond and hydrophobic interactions within the active sites of these proteins.CONCLUSION: Tiliroside exerts potential anti-TNBC activity through multitarget modulation of interconnected oncogenic signaling pathways, suggesting that tiliroside might be a promising lead compound for TNBC.KEYWORDS: tiliroside, triple-negative breast cancer, network pharmacology, induced-fit docking
T. A. Yuniarta, D. S. F. Ramadhan, Zulfikar Ali Hasan et al.· Indonesian Biomedical Journa...· 0 citations
Genistein is a promising multitarget EGFR‐modulating compound that warrants further experimental validation through in vitro and in vivo studies, according to an integrated computational approach.
N. Lonikar, Sameep Sonvane, N. B. Bavage et al.· ChemistrySelect· 0 citations
WI23-B is highlighted as a promising lead peptide with potent WWP1 inhibitory activity and synergistic antiproliferative effects when combined with PI3K inhibitors, and has the potential to reshape therapeutic strategies for BC and TNBC by enabling more effective and less toxic treatment regimens.
E. M. A. Fassi, Sara Mathlouthi, E. Maspero et al.· bioRxiv· 0 citations
Findings support the hypothesis that ICA may serve as a valuable natural compound for treating HER2‐driven breast cancer; it requires further experimental validation.
Non-small-cell lung cancer (NSCLC) remains the leading cause of lung cancer–related mortality, largely driven by aberrant activation of the epidermal growth factor receptor (EGFR). Despite the clinical success of EGFR tyrosine kinase inhibitors (TKIs), intrinsic and acquired resistance, coupled with safety concerns, highlight the need for novel, safer inhibitors. Natural products represent an underexplored source of structurally diverse bioactive compounds with favorable biocompatibility. In this study, a comprehensive in silico approach is used to evaluate phytochemicals from Adenium obesum as potential candidate EGFR-targeting compound. Initially, sixteen phytochemicals were first assessed for predicted antineoplastic activity using PASS. High-scoring molecules were docked against the EGFR kinase domain (PDB ID: 1M17), besides performed detailed protein–ligand interaction analysis, drug-likeness and ADMET profiling, toxicity prediction and 100-ns molecular dynamics (MD) simulations. PASS-based bioactivity prediction revealed strong anticancer potential among the sixteen screened compounds, with consistently high antineoplastic and antiproliferative activity probabilities (Pa > 0.79) and low inactivity scores, supporting their selection for subsequent docking, ADMET, and molecular dynamics analyses. Next, several phytochemicals exhibited strong docking affinities, with Cardenolide achieving the highest binding score (–9.9 kcal/mol) and forming stable interactions with key catalytic residues. A 100-ns MD simulation confirmed the structural stability, persistent binding, and dynamic integrity of the EGFR–Cardenolide complex under physiological conditions. Importantly, interaction mapping revealed that Cardenolide engages conserved and functionally critical regions of the EGFR kinase domain associated with catalytic activity and structural stability, supporting its mechanistic relevance as an ATP-competitive scaffold. Additionally, predicted pharmacokinetic and toxicity profiles further supported Cardenolide’s suitability as a drug-like candidate. Collectively, these results identify Cardenolide as a computationally prioritized candidate with favorable predicted EGFR-binding characteristics, structural stability, and physicochemical and toxicity profiles. However, as the present study is based entirely on computational analyses, these findings should be considered hypothesis-generating and do not establish EGFR inhibitory activity or therapeutic efficacy. Experimental validation, including biochemical kinase inhibition and cellular assays, is therefore required to determine the actual EGFR inhibitory potential and anticancer activity of Cardenolide. Nevertheless, the findings provide a rational basis for prioritizing Cardenolide for further experimental investigation and illustrate the potential of Adenium obesum phytochemicals as a source of candidate EGFR-targeting compounds for future NSCLC drug discovery.
Md. Naziur Rahman, Abu Yousuf Hossin, S. Talukder et al.· PLoS ONE· 0 citations
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