Multi-tasking chemoinformatic model for the efficient discovery of potent and safer anti-bladder cancer agents

• Type: Chapter or Part of a Book
• Date: 2014

Authors

Speck Planche, A (Author) Other; Natalia N D S Cordeiro (Author) FCUP

Book

Title: Bladder Cancer: Risk Factors, Emerging Treatment Strategies and Challenges

Pages: 71-93

Indexing

Scopus - 7 Citations

Other information

Authenticus ID: P-00G-1DX

Abstract (EN): Cancers can be considered as a group of diseases, where cells undergo an uncontrolled growth, and malignant tumors are formed. Between them, bladder cancer (BLC) is an aggressive type of cancer, which can propagate from the urinary bladder to other organs in the human body. BLC is the seventh most common cancer around the world, contributing with more than 4% of all deaths caused by cancers. A very good alternative in the battle against this serious disease is the use of chemotherapy. However, for the design of efficient anti-BLC agents, it is necessary to cover a huge space in terms of molecular diversity and complexity. Consequently, chemoinformatics could be a great ally, helping to rationalize the discovery of new and versatile anti-BLC drugs in terms of diminution of financial resources and time. Current computer-aided models are able to predict anti-BLC activity against only one biological target (protein, cancer cell line) by using very limited and homogenous datasets. On the other hand, there is no information related with the possible safety of anti-BLC agents which have been tested. In this chapter, we introduce a multi-tasking (mtk) chemoinformatic model for simultaneous prediction of anti-BLC activity and safety profiles such as ADMET (absorption, distribution, metabolism, elimination, toxicity) properties. At the same time, we provide two useful insights regarding the molecular patterns that can be responsible for the anti-BLC activity and/or ADMET properties. In this sense, we give a physicochemical and/or structural explanation about the molecular descriptors which entered in our mtk-chemoinformatic model, and how a defined biological effect can be enhanced. On the other hand, we show a procedure for the calculation and analysis of quantitative contributions of molecular fragments to the biological effects, which can be a useful guide for experts working in medicinal chemistry and pharmaceutical sciences. © 2014 Nova Science Publishers, Inc.

Language: English

Type (Professor's evaluation): Scientific