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Computer-based de novo design of drug-like molecules

Key Points

  • Molecular de novo design, which involves incremental construction of a ligand model within a model of the receptor or enzyme active site, produces novel molecular structures with desired pharmacological properties from scratch.

  • De novo molecule-design software is confronted with a virtually infinite search space. As such a large space prohibits exhaustive searching, navigation in the de novo design process relies on the principle of local optimization.

  • Basically, three questions have to be addressed by a de novo design program: how to assemble the candidate compounds; how to evaluate their potential quality; and how to sample the search space effectively.

  • This review gives an overview of computer-based molecular de novo design methods on a conceptual level, considering these three questions, and focusing on the design of small, drug-like molecules. Successful examples of de novo design in the hit- and lead-finding stages of the drug discovery process are used to show that de novo design provides a method for lead identification.

  • De novo design can therefore be regarded as a complement to other virtual techniques, such as database searching, and non-virtual techniques such as high-throughput screening. We also accentuate strengths and weaknesses of current de novo design approaches.


Ever since the first automated de novo design techniques were conceived only 15 years ago, the computer-based design of hit and lead structure candidates has emerged as a complementary approach to high-throughput screening. Although many challenges remain, de novo design supports drug discovery projects by generating novel pharmaceutically active agents with desired properties in a cost- and time-efficient manner. In this review, we outline the various design concepts and highlight current developments in computer-based de novo design.

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Figure 1: How drug-like chemical space might be structured.
Figure 2: Principles of structure-based ligand assembly.
Figure 3: Tree model of search space exploration by an automated structure-generation method.
Figure 4: Progress of a de novo design exercise following the concept of the design software TOPAS48 for assembling drug-like structures.
Figure 5
Figure 6: Experimentally determined binding mode of benzamidine within the S1 substrate-recognition pocket of thrombin (by X-ray, resolution 3.16 Å, PDB identifier: 1DWB).
Figure 7: Experimentally determined binding mode of compound 7 within an X-ray model of the thrombin active site (resolution 1.67 Å, PDB identifier: 1OYT).

Accession codes


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H. Kubinyi is thanked for helpful discussion and kind support. This work was supported by the Beilstein-Institut zur Förderung der Chemischen Wissenschaften, Frankfurt am Main. U.F. is thankful for a fellowship granted by Aventis Pharma Deutschland GmbH, a company of the Sanofi-Aventis group.

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Correspondence to Gisbert Schneider.

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The authors declare no competing financial interests.

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Glossary of terms used in medicinal chemistry



The design of bioactive compounds by incremental construction of a ligand model within a model of the receptor or enzyme active site, the structure of which is known from X-ray or NMR data106.


The identification of isofunctional structures with different backbone architectures.


All information that is related to the ligand–receptor interaction — that is, the binding affinity of a ligand to the particular biological target.


A position in space that is not occupied by the receptor and in which a ligand atom favourably interacts with the receptor.


The ensemble of steric and electronic features that is necessary to ensure the optimal supramolecular interactions with a specific biological target structure and to trigger (or to block) its biological response106.


(QSAR). Mathematical relationships linking chemical structure and pharmacological activity in a quantitative manner for a series of compounds. Methods that can be used in QSAR include various regression and pattern-recognition techniques106.


Non-deterministic polynomial-time hard (NP-hard) refers to a class of decision problems of which current knowledge provides no way to obtain or derive a solution time that is less than exponential in problem size.


Application of probabilistic rules grounded on knowledge of a particular problem domain to obtain an algorithm that performs 'reasonably well' in many cases, but without proof that it is always fast.


Essential drug properties apart from the binding affinity to a biological target — for example, absorption, distribution, metabolism, excretion and toxicity properties, or binding selectivity.

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Schneider, G., Fechner, U. Computer-based de novo design of drug-like molecules. Nat Rev Drug Discov 4, 649–663 (2005).

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