CD ComputaBio is a leading bioinformatics company specializing in providing cutting-edge services and solutions in the field of structure-activity relationship (SAR) research. Our dedicated team of experienced scientists and bioinformatics experts is committed to optimizing drug discovery efforts by elucidating the complex relationships between a compound's structure and its biological activity. With advanced algorithms, innovative methodologies, and state-of-the-art tools, CD ComputaBio empowers researchers and pharmaceutical companies to make informed decisions, streamline the drug development process, and maximize success.
Our Services
SAR Analysis and Prediction
We provide in-depth SAR analysis services utilizing advanced computational methods to identify key structure-activity relationships.
Our team performs comprehensive analyses of structural features, fragment contributions, and physicochemical properties to reveal key insights into target compound interactions.
We employ a suite of cutting-edge algorithms to predict and optimize compound properties such as binding affinity, selectivity, and drug similarity.
SAR Modeling and Virtual Screening
CD ComputaBio specializes in SAR modeling and builds powerful predictive models using various machine learning and statistical methods.
We utilize state-of-the-art virtual screening tools to accelerate the identification of potential drug candidates from large compound libraries.
Our in-house designed SAR database facilitates the building of customized models, saving time and resources for drug development efforts.
Applications
Drug Discovery and Design
CD ComputaBio helps clients effectively identify promising drug candidates and optimize their structures based on SAR studies.
We can understand and predict the activity, toxicity profile, and therapeutic potential of compounds.
ADME-Tox Optimization
Our SAR services provide valuable insights into the absorption, distribution, metabolism, excretion, and toxicity (ADME-Tox) properties of compounds.
By analyzing the structure-activity relationship, we help clients optimize drug molecules to enhance their pharmacokinetic and safety profiles.
Algorithm
CD ComputaBio employs advanced quantitative structure-activity relationship (QSAR) modeling techniques to predict compound activities based on their chemical structures.
We utilize machine learning algorithms, such as random forest, support vector machines, and deep learning, coupled with feature selection and cross-validation methods.
Sample Requirements
Sample Requirements
Descriptions
Molecular structures
Molecular structures in standard formats (e.g. SDF, PDB, or MOL files)
Detailed biological activity data
Detailed biological activity data, including known activities, IC50, EC50, Ki, or pIC50 values
Supporting information
Additional relevant compound information (e.g. ADMET data, toxicology profiles, or intended therapeutic target)
Deliverables
Sample Requirements
Descriptions
Comprehensive SAR Analysis Reports:
Summary of SAR findings, highlighting the critical factors influencing compound activity
Detailed analysis of physicochemical properties, fragment contributions, and molecular interactions
Visualization of SAR relationships, including activity cliffs and structure-activity landscapes
Accurate Predictive Models:
QSAR models encompassing various performance metrics, such as R2, Q2, and predictive accuracy
Predictions of compound activities, including compound ranking and prioritization for further experimental validation
Why Choose Us?
CD ComputaBio's Structure-Activity Relationship services offer comprehensive solutions to propel drug discovery programs towards success. By leveraging advanced algorithms and cutting-edge methodologies, we assist clients in unraveling the complex relationship between compound structures and their biological activities. Contact us today to learn more about our service information.
For research use only. Not intended for any clinical use.
