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Protein Structure Prediction Service

Welcome to CD ComputaBio, where cutting-edge artificial intelligence meets the intricate world of protein structure prediction. Our advanced AI algorithms, coupled with expert bioinformatics analysis, offer a unique and powerful solution for understanding protein structures with unprecedented accuracy and efficiency. With a commitment to driving innovation in the field of computational biology, we stand ready to assist you in unlocking the mysteries hidden within protein structures.

Applications of Protein Structure Prediction

  • Enzyme Engineering - Our AI algorithms facilitate the design and optimization of enzymes for various industrial applications, such as biocatalysis and biofuel production, by predicting the structure-function relationships critical for enzyme performance.
  • Biological Function Prediction - We decipher the functional implications of protein structures, shedding light on protein-protein interactions, ligand binding sites, and molecular mechanisms, essential for understanding biological processes.
  • Personalized Medicine - Through precise protein structure prediction, we support personalized medicine initiatives by identifying genetic variations and mutations that influence protein functionality, guiding tailored treatment strategies for individual patients.

Our Services

Protein motif prediction service

Protein Motif Prediction

CD ComputaBio focuses on protein motif prediction services and is committed to contributing to more customers, we provide all services related to protein motif prediction services flexibly and comprehensively.

Peptide prediction service

Signal Peptide Prediction

CD ComputaBio can provide you with professional signal peptide prediction services to meet your scientific research needs.

Transmembrane prediction service

Transmembrane Prediction

We provide a variety of transmembrane prediction methods for flexible choices. We will tailor an exclusive solution for you according to your testing purpose and budget.

Binding site prediction

Ligand Binding Site Prediction

CD ComputaBio has a mature platform for ligand binding site prediction. We have a first-class expert technical team, which is professional and experienced.

Analysis Methods

Deep Learning Algorithms

We leverage deep neural networks to analyze large datasets of protein sequences and structures, learning complex patterns and features to predict protein folding pathways and structural motifs with high fidelity.

Validation and Optimization

We rigorously validate our predictions using experimental data and feedback loops to continuously optimize our models, ensuring the highest standards of accuracy and reliability in our results.

Ab Initio Modeling

In cases where homology modeling is not feasible, our AI algorithms perform ab initio modeling, predicting protein structures from scratch based on fundamental physical principles and energy calculations.

Accuracy and Reliability

At CD ComputaBio, we prioritize accuracy and reliability in our predictions, employing rigorous validation processes and quality control measures to ensure the integrity of our results. Researchers can trust our data to guide their investigations with confidence and precision.

Our Capabilities

Tertiary Structure Visualization

Visual representations of the predicted protein structure in 3D space, highlighting key structural features and functional domains.

Structural Annotations

Identification of secondary structures, ligand-binding sites, active sites, and other important structural elements critical for biological function.

Quality Assessment Metrics

Evaluation of the predicted structure's quality based on scoring functions, energy calculations, and comparison to experimental structures if available.

At CD ComputaBio, we are at the forefront of AI-aided protein structure prediction, driving innovation, discovery, and progress in biotechnology and life sciences. Through the synergy of artificial intelligence, computational biology, and domain expertise, we unlock the mysteries of protein structures with unparalleled precision and insight, revolutionizing how researchers approach drug discovery, enzyme engineering, and personalized medicine. If you are interested in our services or have any questions, please feel free to contact us.

Reference:

  • Pan X, Rijnbeek P, Yan J, et al. Prediction of RNA-protein sequence and structure binding preferences using deep convolutional and recurrent neural networks[J]. BMC genomics, 2018, 19: 1-11.

Services

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