Structure-Based Drug Design

Structure-based drug design is the design and optimization of a chemical structure with the goal of identifying a compound suitable for clinical testing-a drug candidate. Structure-based drug design (or direct drug design) relies on knowledge of the three dimensional structure of the biological target obtained through methods such as x-ray crystallography or NMR spectroscopy. If an experimental structure of a target is not available, it may be possible to create a homology model of the target based on the experimental structure of a related protein. Using the structure of the biological target, candidate drugs that are predicted to bind with high affinity and selectivity to the target may be designed using interactive graphics and the intuition of a medicinal chemist. Alternatively various automated computational procedures may be used to suggest new drug candidates.

Figure 1. Drug design cycle based on protein structure. (Christophe LMJ Verlinde, Structure ,1994)

Figure 1. Drug design cycle based on protein structure. (Christophe LMJ Verlinde, Structure ,1994)

Overall solutions

  • Traditional structure-based drug design method
    Compared with the screening of macromolecules, structure screening has its practical advantages: First, it is easier to collect, maintain, and screen thousands of structure libraries than millions of macromolecule databases, which enables companies and academic institutions to do it. The discovery of the lead; secondly, a higher screening hit rate can achieve the processing of complex targets, especially those involving protein-protein interactions; in addition, the size of the structure is small, the solubility is high, and it usually has better drug properties, easy to optimize the structure in the later stage, and have the potential to become drug molecules.
    Figure 2. Method of drug design based on protein structure. (Christophe LMJ Verlinde, Structure ,1994)

    Figure 2. Method of drug design based on protein structure. (Christophe LMJ Verlinde, Structure ,1994)

  • AI-based drug design method
    The application of artificial intelligence in drug discovery benefits from an open source implementation that has access to software libraries and allows the implementation of complex neural networks. In recent years, the application range of artificial intelligence systems has been greatly expanded, including structure-based drug design or reverse synthesis analysis, which indicates that we will see more and more applications in fields with large data sets. With advances in these different fields, we can expect that more and more computers will be used for automated drug discovery. Especially the huge progress in robotics technology will accelerate this progress. However, artificial intelligence is far from perfect. Other technologies with a good theoretical background are still important. In particular, because they benefit from enhanced computing power, they can use more accurate methods to simulate large systems.
    Binding site recognition
    Binding site recognition is the first step based on structural design. If the structure of the target or a sufficiently similar homologue is determined in the presence of the bound ligand, the ligand should be observed in that structure, in which case the position of the binding site is small. However, there may not be an allosteric binding site of interest.
    Docking scoring function
    Structure-based drug design attempts to use the principle of molecular recognition to use the structure of a protein as the basis for designing new ligands. Selective high-affinity binding to the target is generally desired because it leads to more effective drugs with fewer side effects. Therefore, one of the most important principles for designing or obtaining potential new ligands is to predict the binding affinity of a certain ligand to its target (and known anti-targets) and use the predicted affinity as a selection criterion.

Services items

Project name Structure-Based Drug Design
  • High-throughput screening and active compound discovery based on structural design.
  • Discovery of active compounds to lead compounds.
  • Optimization of lead compounds to determination of preclinical drug candidates.
  • Research on structure-activity relationship.
Samples requirements
  • Excellent steric and electronic complementarity to the target biomacromolecule is required.
  • A fair amount of hydrophobic surface should be buried in the complex for tight binding.
  • Sufficient conformational rigidity is essential to ensure that the loss of entropy upon ligand binding is acceptable.
  • At least three additional criteria have to be taken into account in the drug design cycle.
  • Chemical stability.
  • Sufficient solubility in water for inhibition tests and structural studies.
  • Ease of synthesis, including the avoidance of chiral centers and of 'dead-end leads' (i.e. compounds which are synthetically not easily amenable to many variations).
Product delivery mode The simulation results provide you with the raw data and analysis results of molecular dynamics.
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CD ComputaBio have cooperated with many universities or research institutions and can consult industry experts for their opinions and suggestions on some complex issues. Our structure-based drug design uses available data to generate hypotheses and design molecules, then synthesize the designed compounds and test them with appropriate testing methods.


  • Christophe LMJ Verlinde , Structure-based drug design: progress, results and challenges. Structure, 1994, 2(7): 577-587


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