De Novo Design

NCE (new chemical entities) is strictly protected by patents and has substantial economic benefits. At present, major pharmaceutical companies in the world are committed to the research and development of NCE. De novo drug design technology is one of the CADD technologies applicable to NCE research and development. It is a drug molecule design method based on the three-dimensional structure of the receptor. This technology analyzes the target molecule's active site and constructs a drug molecule that matches the active site.

Process of our De novo Design services

Our simulation services

Features

The advantage of the de novo design technology is to provide new ideas for the development of new drugs, make full use of the structural information of known compounds, and to a certain extent avoid the waste of research and development resources and accelerate the speed of new drug development. It has strong feasibility and broad development prospects, and may become an important tool for new drug research and development.

Popular strategies for protein engineering:

• Rational design
• De novo design
• Directed evolution
• Semi-rational design

Related services

• Structure-based Drug Design
• Fragment-based Drug Design
• Multiple Targeting Design

CD ComputaBio is a professional and efficient team. Our experts have professional knowledge background and have cooperated with many well-known companies many times. Treating customers' projects CD ComputaBio is racing against time, mission must be reached, efficient and timely delivery of tasks, customer satisfaction and trust. If you have drug design needs, please feel free to contact us.

De Novo Design FAQs

• • Q: How are linear amino acid chains executed?

    • A:Linear chains of amino acids are adopted a unique 3D structure in the native surroundings to perform proteins. In de novo design, to identify amino acid sequences folding into proteins with desired functions is the ultimate objective. There are various approaches predicting protein structure including comparative modeling and fold recognition. In proteins, sequence similarity implies structural similarity. Accordingly, the method of comparative modeling is formed. The structure of a protein can be predicted by comparing the amino acid sequence to that of native 3D structure known. When the target and template share over 50% of sequence, the predictions are of high quality. Sequence similarity implies structural similarity but similar structures can be found for proteins with different sequence.

  • Q: What is the difference between de novo design and virtual screening?

    • A: De novo design and virtual screening are similar in the sense that they both search the chemical space for molecules that meet specific requirements. However, their processes are very different. While de novo drug design is a molecule generation approach that generates and optimizes a molecule to meet a target, virtual screening is a filter that is applied to gradually narrow down the search to an acceptable range for further validation.

  • Q: How is folding recognition performed?

    • A: As a complemental method, fold recognition aims at predicting the three-dimensional folded structure of a protein with known sequence. The structure is evolutionary more conserved than sequence. As a result, the repertoire of different folds is more limited. The methods of fold recognition mainly include advances sequence comparison and secondary structure prediction and comparison. Besides these, the prediction of loop structure including β-strands and helices is also included.

  • Q: What are the advantages of proteins designed by de novo?

    • A: The proteins designed by de novo which is consistent with the natural 3D targets with minimum energy interactions often can fold very fast. De novo protein design can promote stability of the target protein and also has been used to lock proteins into certain useful conformations. There have been numerous successes in the development of computational algorithms for protein design.

  • Q: What are the methods of de novo design?

    • A: Common approaches used by de novo design include:

      Structural motif: such as "four α-helix bundle" motif, "helix-loop-helix" motif

      Known protein structures as natural scaffolds

      Molecular templates
  • Q: What are the evaluation metrics?

    • A: The metrics for evaluating the performance of generative models can be broadly classified into 3 types depending on the object of evaluation as follows:

      Metrics that evaluate the entire molecular set, whose main goal is to evaluate the difference between the generated set G and the existing set E. This includes metrics such as the average Tanimoto similarity coefficient algorithm SNN between two molecular sets.

      Metrics for evaluating individual molecules within a molecular set. The more widely used metrics include the synthesisability score (SA Score) and the quantitative drugability prediction (QED) coefficient

      Benchmark reviews (benchmark) suites for evaluating generative models.