Molecular Similarity Based on Functional Groups: Subtree Kernels for Virtual Screening in Drug Discovery
Main Article Content
Abstract
Current developments in computer-aided drug design (CADD) reduces the time and cost of drug discovery process. Using various computational techniques, large number of compounds in the chemical database are analyzed and screened. Virtual screening can be classified into structure based and ligand based methods. The amount of information required for structure based virtual screening is too high when compared to ligand based method. In ligand based methods, classification of active and inactive drugs can be done using Hidden Markov Model, Support Vector Machine (SVM), Clustering etc. SVM is widely used nowadays. Classification using SVM and graph kernel function is introduced recently and shows good accuracy over the other existing methods. Different graph kernel functions are used for finding similarity measure in SVM. Here, we propose a new method for finding the similarity based on the functional groups present in the molecules. The accuracy is compared with that of existing graph kernel methods using standard data sets (PTC and MUTAG). , Coimbatore, India
Â
Keywords: drug discovery; virtual screening; SVM; molecular graph similarity functional group; tree kernel.
Downloads
Article Details
COPYRIGHT
Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
- The journal allows the author(s) to retain publishing rights without restrictions.
- The journal allows the author(s) to hold the copyright without restrictions.