CD ComputaBio understands that each project is unique, and our team tailors the approach to address the specific requirements of our clients, ensuring that the delivered solutions are precisely aligned with their objectives and expectations.
Epitope prediction is critical for understanding immune responses, designing targeted therapeutics and developing vaccines. At CD ComputaBio, we are committed to providing state-of-the-art epitope prediction services to accelerate the discovery and development of novel immunotherapies. Our team of computational biologists and bioinformaticians have developed proprietary algorithms and software that set new standards for epitope prediction and have significantly advanced the field of immunoinformatics.
Our T cell epitope prediction service focuses on identifying peptides that bind to major histocompatibility complex (MHC) molecules to activate specific T cells. By utilizing advanced algorithms and databases, we are able to predict peptide epitopes capable of eliciting T-cell responses, which are critical for the development of therapeutic vaccines against infectious diseases, cancers, and autoimmune diseases.
Figure 2. T cell Epitope Prediction. (Schaap-Johansen A L, er al. 2021)
Based on sequence and structural analysis of T cell epitopes, direct methods rely on the presence or absence of features such as amphipathicity, MHC-binding motifs, etc.
Indirect methods use a number of elegant techniques based on statistical learning theory to predict MHC peptide binding, such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), and molecular docking simulations.
Our B-cell epitope prediction service is designed to predict regions on antigens that elicit B-cell immune responses to aid in the development of antibody-based therapies and antigen-specific diagnostics. Using state-of-the-art algorithms and modeling techniques, we can identify potential epitopes that are critical for vaccine and monoclonal antibody development. Prediction of B cell antigenicity helps to identify neutralizing antibody targets. However, predicting B cell epitopes with computational tools is complicated by the conformational basis of antibody-antigen interactions.
Figure 2. Linear and conformational B-cell epitopes. (Sanchez-Trincado, 2017)
At the core of our services lie our cutting-edge algorithms, meticulously developed and continuously optimized by our team of computational biologists and bioinformaticians.
Deep Learning Approaches
Deep learning techniques, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and more recently transformer-based models like BERT or GPT, have been employed to learn complex patterns from the protein sequences or structures to predict potential antigenic epitopes.
Support Vector Machines (SVM)
Computer-aided antigenic epitope prediction involves the use of various algorithms and computational methods to predict antigenic epitopes on proteins. SVMs are a popular choice for sequence-based epitope prediction. They are utilized to classify sequences based on their properties and have been successful in predicting epitopes.
Random Forest and Decision Trees
These tree-based models are used to capture non-linear dependencies and interactions between amino acids or structural features within proteins to predict antigenic epitopes. These algorithms typically use a variety of features such as evolutionary information to make predictions.
We employ advanced computational models to analyze large-scale sequence data, enabling precise epitope prediction for diverse MHC alleles and antigenic targets. Our models are continuously updated to incorporate the latest experimental data and ensure high predictive accuracy.
Our algorithms are integrated with comprehensive databases of MHC-peptide binding affinities and antigen-antibody interactions, providing a wealth of information for accurate epitope prediction across various species and pathogen strains.
ACD ComputaBio is dedicated to advancing immunotherapy and vaccine design through state-of-the-art computer-aided epitope prediction services. We utilize advanced algorithms, comprehensive databases, and expert support to help researchers and pharmaceutical companies accelerate discovery and development efforts, ultimately advancing the progress of novel immunotherapies and impactful medical interventions.
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