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Identifying peptide targets helps to gain a deeper understanding of the complex protein-peptide interaction networks within biological systems, providing crucial information for drug design and disease treatment. CD ComputaBio offers peptide target identification services with its advanced computational methods and professional technical team, dedicated to solving this challenge for researchers and pharmaceutical companies.
Chemoinformatics tools hold immense potential in advancing computer-aided drug discovery and design, as they integrate multi-level information to enhance the reliability of data outcomes. Methods such as inverse virtual screening and pharmacophore modeling have been successfully employed to predict potential drug targets. Peptide target identification, as a crucial component of drug discovery and design, including the discovery of new drug targets and the development of peptide-based therapeutics, can also benefit from these advanced computational tools, facilitating accelerated new drug discovery and advancements in human medicine.
Fig. 1 Using DeepPurpose for DTI prediction. (Huang K, et al., 2020)
| Databases & Tools | Description | References |
| PDTD | A web-accessible protein database for in silico target identification, which currently contains >1100 protein entries with 3D structures presented in the Protein Data Bank. | Gao et al. (2008) |
| PharmMapper | A web-based tool for potential drug target prediction against any given small molecules via a 'reverse' pharmacophore mapping approach. | Liu et al. (2010) |
| SwissTargetPrediction | A web server to accurately predict the targets of bioactive molecules based on a combination of 2D and 3D similarity measures with known ligands. | Gfeller et al. (2014) |
| CODD-Pred | An online web server with well-curated datasets from the GOSTAR database, designed for the dual purpose of predicting potential protein drug targets and computing bioactivity values of small molecules. | Yin et al. (2023) |
As a leading computational biology service provider, CD ComputaBio is committed to offering peptide target identification services to global research institutions, pharmaceutical companies, and biotechnology firms. We specialize in identifying specific biologically functional peptide-protein interactions, providing a theoretical foundation for subsequent drug design.
Screening Model Construction
CD ComputaBio leverages known peptide-target interaction data and employs advanced machine learning algorithms to construct high-precision screening models, laying the foundation for subsequent target prediction.
Peptide Target Screening
Based on these screening models, we conduct initial screening of potential targets in protein databases for the target peptides and perform multi-dimensional precise screening using diverse computational methods, ultimately identifying the most promising target molecules.
Utilizing large-scale biological data, such as genomics, transcriptomics, proteomics, and compound activity data, potential targets for peptides can be predicted through bioinformatics and machine learning algorithms.
By utilizing the structural or property information of known active peptide ligands, potential targets with high affinity to the target peptide can be predicted through methods such as similarity searches and pharmacophore modeling.
Leveraging the three-dimensional structural information of peptide molecules and potential targets, novel targets for peptide drugs can be discovered through computational methods like reverse docking.
Target identification is a critical step in peptide drug design and determines the success of subsequent studies. CD ComputaBio has the technology and experience to support your research. If you are interested in our services, please feel free to contact us to jointly advance the design and development of peptide drugs.
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CD ComputaBio offers computation-driven peptide design services to research institutions, pharmaceutical, and biotechnology companies.
