Review Article - (2022) Volume 7, Issue 1
Breast cancer is one of the most lethal cancers, estrogen receptor α Subtype (ERα) is an important target. The compounds that able to fight ERα active may be candidates for treatment of breast cancer. The drug discovery process is a very large and complex process that often requires one selected from a large number of compounds. This paper considers the independence, coupling, and relevance of bioactivity descriptors, selects the 15 most potentially valuable bioactivity descriptors from 729 bioactivity descriptors. An optimized back propagation neural network is used for ERα, The pharmacokinetics and safety of 15 selected bioactivity descriptors were verified by gradient lifting algorithm. The results showed that these 15 biological activity descriptors could not only fit well with the nonlinear relationship of ERα activity can also accurately predict its pharmacokinetic characteristics and safety, with an average accuracy of 89.92~94.80%. Therefore, these biological activity descriptors have great medical research value.
The article entitled “Retracted: Anti-breast cancer drug screening based on Neural Networks and QSAR model” had been accepted for publication in the Journal of General Dentistry considering the statements provided in the article as a personal opinion of the author to be completely unbiased. The article was published solely on the basis of the opinion provided by the reviewers. But due to some unforeseen divergences between the author and the journal, the article is being retracted.
Received: 03-Jan-2022 Published: 28-Jan-2022, DOI: 10.4172/2572-5130.10001
Copyright:This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
