De Novo Peptide Design Service

Leveraging technologies such as deep generative models and molecular dynamics simulations, CD ComputaBio has launched its de novo peptide design service. This service employs reverse engineering of the physicochemical characteristics of target binding sites, combined with multi-objective optimization algorithms, to directly generate novel peptide sequences from virtual space, providing an intelligent design platform for drug development targeting challenging drug targets.

Introduction to De Novo Peptide Design

De novo peptide design is an innovative approach that does not depend on known peptide sequences. It incrementally generates functional peptide molecules by analyzing the characteristics of the target's binding site. This method first requires identifying the binding site, then sequentially generating the peptide sequence along a selected path. Algorithms or models are used to calculate the binding energy between the peptide and the target, allowing for the selection of the optimal peptide sequence.

Fig. 1 De novo design of macrocyclic peptides. (Bhardwaj G, et al., 2022)

Computational Tools and Algorithms for De Novo Peptide Design

Tools & Algorithms	Description	References
ENPDA	An evolutionary tool for de novo peptide design based on evaluating the binding energy of peptides to user-defined protein surface patches.	Belda et al. (2005)
VitAL	An efficient method for determining the optimal state solution of a hidden Markov model based on a given observation sequence. It has been widely used in the analysis of biological data and in the field of bioinformatics.	Unal et al. (2010)
PepDRED	Simulating the natural evolutionary pipeline to generate stable apovariant (AVs) from wild-type counterparts through automated point mutations, and validating their efficiency through energy analysis.	Azmat et al. (2023)
DexDesign	An OSPREY-based algorithm primarily used for the computational de novo design of D-peptide inhibitors.	Guerin et al. (2024)

Our Services

CD ComputaBio leverages its leading computational-driven platform to provide innovative and efficient de novo peptide design services to global researchers and biopharmaceutical companies. It develops highly active and stable targeted peptides through deep learning and computer simulation technologies, covering anti-tumor, anti-infection, and immunotherapy fields.

Binding Site Identification

We systematically analyze and predict the binding pockets of target proteins by docking residue pairs or peptide fragments one by one, providing critical information for subsequent peptide design.

Peptide Sequence Design

Target-based peptide sequence design services are offered by CD ComputaBio, with peptide sequences of ideal properties being created based on information about the target's binding sites.

Peptide Conformation Prediction

CD ComputaBio predicts the three-dimensional folding structures of peptides and analyzes their stability in solution, providing strong support for drug development.

Service Highlights

AI-Driven Innovative Strategies - By integrating AI technology, De Novo peptide design enables rapid design and optimization of peptide sequences.
Highly Customized - Tailor the design of peptide sequences and structures according to the specific needs of the customer.
Overcoming Limitations - Break the constraints of natural peptide sequences, allowing exploration of a broader sequence space.

CD ComputaBio is committed to providing you with leading technical support and quality service. If you have any questions about de novo peptide design services or need further advice, please feel free to contact us. Our team of professionals will be happy to provide you with support and solutions.

References:

Bhardwaj, G.; et al. Accurate de novo design of membrane-traversing macrocycles[J]. Cell. 2022, 185(19): 3520-3532. e26.
Belda, I.; et al. ENPDA: an evolutionary structure-based de novo peptide design algorithm[J]. Journal of Computer-Aided Molecular Design. 2005, 19: 585-601.
Unal, E B.; et al. VitAL: Viterbi algorithm for de novo peptide design[J]. PLoS One. 2010, 5(6): e10926.
Azmat, M.; et al. Pepdred: De Novo peptide design with strong binding affinity for target protein[J]. Analytical Chemistry. 2023, 95(33): 12264-12272.
Guerin, N.; et al. DexDesign: an OSPREY-based algorithm for designing de novo D-peptide inhibitors[J]. Protein Engineering. Design and Selection, 2024, 37: gzae007.

For research use only. Not intended for any clinical use.

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