De novo Drug Design

Drug design

Welcome to CD ComputaBio, your premier partner in innovative de novo drug design solutions. Our cutting-edge AI analysis methods and expert team of scientists are dedicated to revolutionizing the drug discovery process, providing tailor-made services to meet the unique needs of our clients. With a commitment to excellence and a passion for pushing the boundaries of science, we are proud to be at the forefront of drug development.

Our Services

AI equips medicinal chemistry with innovative tools for small molecular design and lead discovery. AI-driven de novo drug design aims to generate new chemical entities with desired properties in a cost- and time-efficient manner. The ability of approaches provided by CD ComputaBio's AI BioX™ platform to generate innovative molecular cores has been proved, thereby exploring novel regions of the chemical space.

Analysis Methods

Neural Networks

Our neural network models enable the extraction of intricate patterns from large datasets, allowing us to uncover novel drug-target interactions and prioritize lead compounds for experimental validation.

Deep Learning

By leveraging deep learning algorithms, we can delve into the nuances of molecular structures and biological pathways, uncovering hidden correlations and accelerating the drug discovery process.

Data Mining

Through sophisticated data mining techniques, we extract critical information from diverse sources, enabling us to construct comprehensive models that guide the rational design of potent and selective drug molecules.

The AI Approach Consisted of Several Basic Steps:

Develop a generic model (utilizing a recently published deep recurrent neural network) that learns the constitution of drug-like molecules from a large unfocussed compound set.
Trained a recurrent neural network to capture the constitution of a large set of known bioactive compounds represented as SMILES strings.
Fine-tune this generic model on more specific molecular features from a small target-focused library of actives, and then transfer learning to enable the de novo drug design and generation.
Produce novel chemical entities within the training data domain from the resulting fine-tuned AI model.

Principles of De novo Drug Design

Assembling possible compounds and evaluating their quality.
Searching the sample space for novel structures with drug-like properties.

De novo drug design

Available Design Programs

Developed computerized structural design approaches utilize protein-structures and/or ligand-structures as the structure-base design and ligand-based design, respectively. Site point connection method includes LUDI. Fragment connection methods include SPLICE, NEW LEAD, and PRO-LIGAND. Sequential build up methods include LEGEND, GROW, and SPROUT. Random connection and disconnection methods include CONCEPTS, CONCERTS, MCDNLG.

Available programs for de novo drug design

Results Evaluation

Use target prediction method (SPiDER) and molecular shape and partial charge descriptors to determine the similarity of the designed compounds to known bioactive chemicals, taking into account their individual in silico ranks and building block availability.

At CD ComputaBio, we prioritize the confidentiality and security of your data throughout the drug design process. We adhere to strict data protection protocols and regulatory standards to safeguard your intellectual property and sensitive information. You can trust us to maintain the highest levels of confidentiality and compliance in all aspects of our collaboration. If you are interested in our services or have any questions, please feel free to contact us.

Services

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