Next Article in Journal
Chemopreventive and Therapeutic Effects of Edible Berries: A Focus on Colon Cancer Prevention and Treatment
Next Article in Special Issue
Design, Synthesis, and Biological Evaluation of Some Novel Pyrrolizine Derivatives as COX Inhibitors with Anti-Inflammatory/Analgesic Activities and Low Ulcerogenic Liability
Previous Article in Journal
Moving from Classical Ru-NHC to Neutral or Charged Rh-NHC Based Catalysts in Olefin Metathesis
Previous Article in Special Issue
A SILAC-Based Approach Elicits the Proteomic Responses to Vancomycin-Associated Nephrotoxicity in Human Proximal Tubule Epithelial HK-2 Cells
Article Menu
Issue 2 (February) cover image

Export Article

Open AccessArticle
Molecules 2016, 21(2), 175; doi:10.3390/molecules21020175

Self Organizing Map-Based Classification of Cathepsin k and S Inhibitors with Different Selectivity Profiles Using Different Structural Molecular Fingerprints: Design and Application for Discovery of Novel Hits

1
Pharmacognosy and Pharmaceutical Chemistry Department, College of Pharmacy, Taibah University, P. O. Box 30039, Al-Madinah Al-Munawarah 41477, Saudi Arabia
2
School of Pharmacy and Applied Science, La Trobe University, P. O. Box 199, Bendigo 3552, Australia
3
Pharmaceutical Organic Chemistry Department, Faculty of Pharmacy, Al-Azhar University, P. O. Box 11651, Cairo 11884, Egypt
4
Pharmaceutical Chemistry Department, Faculty of Pharmacy, Al-Azhar University, P. O. Box 11651, Cairo 11884, Egypt
*
Author to whom correspondence should be addressed.
Academic Editors: Shufeng Zhou and Wei-Zhu Zhong
Received: 21 December 2015 / Revised: 20 January 2016 / Accepted: 27 January 2016 / Published: 30 January 2016
(This article belongs to the Special Issue Drug Design and Discovery: Principles and Applications)
View Full-Text   |   Download PDF [4015 KB, uploaded 30 January 2016]   |  

Abstract

The main step in a successful drug discovery pipeline is the identification of small potent compounds that selectively bind to the target of interest with high affinity. However, there is still a shortage of efficient and accurate computational methods with powerful capability to study and hence predict compound selectivity properties. In this work, we propose an affordable machine learning method to perform compound selectivity classification and prediction. For this purpose, we have collected compounds with reported activity and built a selectivity database formed of 153 cathepsin K and S inhibitors that are considered of medicinal interest. This database has three compound sets, two K/S and S/K selective ones and one non-selective KS one. We have subjected this database to the selectivity classification tool ‘Emergent Self-Organizing Maps’ for exploring its capability to differentiate selective cathepsin inhibitors for one target over the other. The method exhibited good clustering performance for selective ligands with high accuracy (up to 100 %). Among the possibilites, BAPs and MACCS molecular structural fingerprints were used for such a classification. The results exhibited the ability of the method for structure-selectivity relationship interpretation and selectivity markers were identified for the design of further novel inhibitors with high activity and target selectivity. View Full-Text
Keywords: cathepsin inhibitors; fingerprints; selectivity; self-organizing map (SOM); clustering cathepsin inhibitors; fingerprints; selectivity; self-organizing map (SOM); clustering
Figures

Figure 1a

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Ihmaid, S.K.; Ahmed, H.E.A.; Zayed, M.F.; Abadleh, M.M. Self Organizing Map-Based Classification of Cathepsin k and S Inhibitors with Different Selectivity Profiles Using Different Structural Molecular Fingerprints: Design and Application for Discovery of Novel Hits. Molecules 2016, 21, 175.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]

Molecules EISSN 1420-3049 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top