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Antiviral Peptide Design Services
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Antiviral Peptide Design Services

Faced with the severe health challenges posed by viral infections and the limitations of existing antiviral drugs, peptide-based therapies seem very promising. CD ComputaBio offers computation-driven antiviral peptide design services, employing a variety of design strategies to develop effective antiviral peptides and bring new hope to overcoming the challenges of viral infections.

Introduction to Antiviral Peptide Design

Traditional development of effective antiviral peptides (AVPs) requires constructing libraries and conducting experimental screenings, which is both time-consuming and costly. To overcome these limitations, machine learning models have gained popularity in high-throughput peptide design and antiviral activity identification. Computational-driven approaches, such as de novo design, template-based design, and virtual screening utilizing molecular docking and molecular dynamics simulations, have significantly propelled the development of antiviral peptides.

Fig. 1 Peptide design strategy for the GCG/GLP-1 receptor coagonist.Fig. 1 The rational design of selective peptide inhibitors targeting the spike protein of SARS-CoV-2. (Chowdhury S M, et al., 2020)

Computational Tools for Antiviral Peptide Design

Tools Description References
Meta-iAVP A novel sequence-based meta-predictor with an effective feature representation for accurately predicting AVPs from given peptide sequences. Schaduangrat et al. (2019)
Deep-AVPpred A deep learning classifier for discovering AVPs in protein sequences, which utilizes the concept of transfer learning with a deep learning algorithm. Sharma et al. (2023)
DRAVP A database of antiviral peptides and proteins that provides comprehensive information, including general details, antiviral activity, structure, physicochemical properties, and literature references. Liu et al. (2023)
AVP-GPT A novel deep learning method utilizing transformer-based language models and multimodal architectures, specifically designed for AVP design. Zhao et al. (2024)

Our Services

CD ComputaBio combines rational design strategies and computational methods to provide computational design services for antiviral peptides. We are committed to developing more targeted, efficient, and low-side-effect antiviral peptides to help address the challenges of viral infections.

By Workflow

By Strategy

By Method

  • Molecular Docking
  • Machine Learning
  • Molecular Dynamics Simulation
  • Deep Learning

Why Choose Us?

Professional Team

Our team is highly knowledgeable and experienced, employing rational design strategies to ensure that our solutions are scientifically sound and efficient.

Customized Services

Tailor-made services are provided based on the specific needs of clients, offering personalized antiviral peptide design solutions.

Continuous Innovation

Staying at the forefront of scientific advancements ensures that clients can benefit from advanced technologies.

If you have requirements for antiviral peptide design, please feel free to contact CD ComputaBio. Our expert team will utilize advanced computational methods and rational design strategies to provide you with customized solutions. We are eager to collaborate with you to promote advancements in antiviral research.

References:

  1. Chowdhury, S M.; et al. Antiviral peptides as promising therapeutics against SARS-CoV-2[J]. The Journal of Physical Chemistry B. 2020, 124(44): 9785-9792.
  2. Schaduangrat, N.; et al. Meta-iAVP: a sequence-based meta-predictor for improving the prediction of antiviral peptides using effective feature representation[J]. International journal of molecular sciences. 2019, 20(22): 5743.
  3. Sharma, R.; et al. Deep-AVPpred: Artificial intelligence driven discovery of peptide drugs for viral infections[J]. IEEE Journal of Biomedical and Health Informatics. 2021, 26(10): 5067-5074.
  4. Liu, Y.; et al. DRAVP: a comprehensive database of antiviral peptides and proteins[J]. Viruses. 2023, 15(4): 820.
  5. Zhao, H.; Song G. Antiviral Peptide-Generative Pre-trained Transformer (AVP-GPT): A Deep Learning-Powered Model for Antiviral Peptide Design with High-Throughput Discovery and Exceptional Potency[J]. Viruses. 2024, 16(11): 1673.
For research use only. Not intended for any clinical use.
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CD ComputaBio offers computation-driven peptide design services to research institutions, pharmaceutical, and biotechnology companies.

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