The In Sitico Drug Discovery Toolbox: Applications in Lead Discovery and Optimization

Background: Discovery and development of a new drug is a long lasting and expensive journey that takes around 20 years from starting idea to approval and marketing of new medication. Despite R&D expenditures have been constantly increasing in the last few years, the number of new drugs introduced into market has been steadily declining This is mainly due to preclinical and clinical safety issues, which still represent about 40% of drug discontinuation. To cope with this issue, a number of in silica techniques are currently being used for an early stage evaluation/prediction of potential safety issues, allowing to increase the drug-discovery success rate and reduce costs associated with the development of a new drug. Methods: In the present review, we will analyse the early steps of the drug-discovery pipeline, describing the sequence of steps from disease selection to lead optimization and focusing on the most common in silica tools used to assess attrition risks and build a mitigation plan. Results: A comprehensive list of widely used in silica tools, databases, and public initiatives that can he effectively implemented and used in the drug discovery pipeline has been provided. A few examples of how these tools can he problem-solving and how they may increase the success rate of a drug discovery and development program have been also provided. Finally, selected examples where the application of in silica tools had effectively contributed to the development of marketed drugs or clinical candidates will he given. Conclusion: The in silica toolbox finds great application in every step of early drug discovery: (i) target identification and validation; (ii) hit identification; (iii) hit-to-lead; and (iv) lead optimization. Each of these steps has been described in details, providing a useful overview on the role played by in silica tools in the decision-making process to speed-up the discovery of new drugs.