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Published on: December 1, 2020
Bridging In Silico design and experimental validation: Virtual screening and In Vitro assessment of biomimetic
Thananya Ratanachotpanich1, Aussadech Chumgate2, Kanapos Lengwehasathit2
1Department of Zoology, Faculty of Science, Kasetsart University, Bangkok, 10900, Thailand.
Background:
Colorectal cancer (CRC) remains a leading cause of cancer-related mortality, necessitating the development of more selective and safer therapeutic options. Biomimetic peptides derived from natural sources offer promising alternatives to conventional chemotherapeutics, yet their discovery through experimental screening alone is time-consuming and resource-intensive.
Objective:
To integrate computational modeling and AI-driven virtual screening with experimental validation for the discovery of novel anticancer peptides from the hemolymph of Tachypleus tridentatus.
Methods:
A multi-step in silico pipeline comprising tryptic digestion, six machine learning predictors, safety profiling (toxicity, hemolysis, allergenicity), and multi-criteria ranking was employed. Top candidates were synthesized and validated using MTT assays, AO/PI staining, and qRT-PCR. Structural analysis was performed using HeliQuest and PEP-FOLD 4.0.
Results:
Computational screening prioritized two hemocyanin-derived peptides, H10 and H22. H22 exhibited balanced amphipathicity (hydrophobicity = 0.271, hydrophobic moment = 0.278) and an extended α-helical structure. In vitro, H22 demonstrated moderate cytotoxicity against HT-29 cells (IC₅₀ = 39.83 ± 0.59 µM) with favorable selectivity (Selectivity Index = 1.83) compared to doxorubicin (SI = 0.12). Mechanistically, qRT-PCR revealed that H22 upregulated p53 (19.3-fold), Bax (4.7-fold), Caspase-9 (4.6-fold), and Caspase-7 (49.4-fold), suggesting apoptotic inductive mechanism via the intrinsic pathway.
Conclusion:
This integrated approach successfully identified H22 as a hemocyanin-derived peptide with moderately potent anticancer activity and promising selectivity. The workflow provides a reproducible proof‑of‑concept framework for computational-guided peptide, warranting further optimization and experimental validation.
Insights
Computational methods identified H22, a novel anticancer peptide from Tachypleus tridentatus hemolymph, showing moderate cytotoxicity and apoptosis induction in colorectal cancer cells.
Area of Science:
- Biochemistry
- Computational Biology
- Oncology
Background:
- Colorectal cancer (CRC) is a major cause of cancer mortality, driving the need for safer, more selective therapies.
- Biomimetic peptides offer alternatives to conventional chemotherapy, but experimental discovery is slow and costly.
Purpose of the Study:
- To integrate computational modeling and AI-driven virtual screening with experimental validation.
- To discover novel anticancer peptides from Tachypleus tridentatus hemolymph.
Main Methods:
- An in silico pipeline included tryptic digestion, machine learning prediction, and safety profiling.
- Top peptide candidates were synthesized and validated using MTT assays, AO/PI staining, and qRT-PCR.
- Structural analysis was performed using HeliQuest and PEP-FOLD 4.0.
Main Results:
- Computational screening identified two hemocyanin-derived peptides, H10 and H22.
- H22 demonstrated moderate cytotoxicity against HT-29 cells (IC50 = 39.83 µM) with favorable selectivity (SI = 1.83).
- H22 upregulated p53, Bax, Caspase-9, and Caspase-7, indicating apoptosis induction via the intrinsic pathway.
Conclusions:
- An integrated computational and experimental approach successfully identified H22 as a promising anticancer peptide.
- The workflow provides a framework for computational-guided peptide discovery, requiring further validation.
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