Anticancer Peptide Design Services

On the journey to conquer cancer, CD ComputaBio consistently stays at the forefront of technology, providing you with excellent computational design services for anticancer peptides. Based on our computation-driven peptide design platform, we are committed to offering personalized and efficient anticancer peptide design solutions to clients worldwide.

Introduction to Anticancer Peptides

The limitations of cancer treatment methods have prompted the search for new unconventional cancer therapies. Among them, anticancer bioactive peptides have shown great potential in diagnostic and therapeutic applications. In terms of therapeutic applications, anticancer peptides (ACPs) have been proven to have higher specificity, sensitivity, and accuracy compared to traditional cancer therapies, and they also exhibit lower toxicity. Moreover, anticancer peptides can be used in combination therapies to enhance the sensitivity of cancer cells to other therapeutic agents. In recent years, the number of preclinical and clinical trials using peptide-based vaccines for cancer treatment has been on the rise.

Fig. 1 Mechanisms of action, production strategies, and clinical applications of anticancer peptides. (Chinnadurai R K, et al., 2023)

Computational Anticancer Peptide Design

In the field of peptide research, the rise of computational tools and artificial intelligence (AI) has significantly propelled the development of advanced computational methods and specialized databases. These advancements provide robust support for exploring these complex molecules. Over the past decade, researchers have developed various machine learning models to predict ACPs. Furthermore, specialized peptide databases, which integrate extensive peptide sequence, structure, and activity information, provide crucial data support for training machine learning models and facilitating the efficient design of anticancer peptides.

Fig. 2 Design of LASAPs and the proposed self-delivering process. (Pei P, et al., 2022)

Our Services

CD ComputaBio offers comprehensive computational anticancer peptide design services, utilizing advanced algorithms and artificial intelligence technologies to develop highly efficient and targeted therapeutic candidates. Our services cover the study of anticancer peptide mechanisms of action, sequence optimization, and the design of novel ACPs, meeting the research and development needs of our clients.

By Workflow

Approaches to Anticancer Peptide Design

• Molecular Docking

Molecular docking predicts the binding affinity between anticancer peptides and target proteins, and screens for high-activity candidate peptides. By identifying the interacting residues of proteins and peptides, it provides insights for the optimization of anticancer peptides.

• Molecular Dynamics Simulations

In anticancer peptide design, molecular dynamics simulations are used to simulate the dynamic interactions between peptides and target proteins, predict binding stability and free energy, optimize peptide structures, and enhance bioactivity.

• Machine Learning

Models are constructed using features such as amino acid composition and sequence, such as support vector machines (SVMs) and random forests (RF), to predict anticancer peptides and assist in the design of new peptides and mutants.

• Deep Learning

Deep learning methods, especially neural networks, are employed to design anticancer peptides. These advanced technologies analyze complex peptide data to predict activity, identify optimal sequences, and optimize peptide design, thereby enhancing therapeutic outcomes.

If you would like to learn more about the computational anticancer peptide design services provided by CD ComputaBio, please feel free to contact us. Our professional team is ready to offer you consultation and technical support. We look forward to working with you to advance the development of anticancer drugs.