![conference banner](/images/conference-banner.jpeg)
Abstract
Movement disorders are a heterogeneous group of both common and rare neurological conditions characterized by abnormalities of motor functions and movement patterns. This work overviews recent successes and ongoing studies of repositioning relating to this disease group, which underscores the challenge of integrating the voluminous and heterogeneous findings required for making suitable drug repositioning decisions. In silico drug repositioning methods hold the promise of automated fusion of heterogeneous information sources, but the controllable, flexible and transparent incorporation of the expertise of medicinal chemists throughout the repositioning process remains an open challenge. In support of a more systematic approach toward repositioning, we summarize the application of a computational repurposing method based on statistically rooted knowledge fusion. To foster the spread of this technique, we provide a step-by-step guide to the complete workflow, together with a case study in Parkinson's disease.
Keywords: Movement disorders, Parkinson’s disease, in silico drug discovery, similarity search, data fusion, multiple kernel learning, multi-aspect drug repositioning.
Current Topics in Medicinal Chemistry
Title:Drug Repositioning for Treatment of Movement Disorders: From Serendipity to Rational Discovery Strategies
Volume: 13 Issue: 18
Author(s): Bence Bolgár, Ádám Arany, Gergely Temesi, Balázs Balogh, Péter Antal and Péter Mátyus
Affiliation:
Keywords: Movement disorders, Parkinson’s disease, in silico drug discovery, similarity search, data fusion, multiple kernel learning, multi-aspect drug repositioning.
Abstract: Movement disorders are a heterogeneous group of both common and rare neurological conditions characterized by abnormalities of motor functions and movement patterns. This work overviews recent successes and ongoing studies of repositioning relating to this disease group, which underscores the challenge of integrating the voluminous and heterogeneous findings required for making suitable drug repositioning decisions. In silico drug repositioning methods hold the promise of automated fusion of heterogeneous information sources, but the controllable, flexible and transparent incorporation of the expertise of medicinal chemists throughout the repositioning process remains an open challenge. In support of a more systematic approach toward repositioning, we summarize the application of a computational repurposing method based on statistically rooted knowledge fusion. To foster the spread of this technique, we provide a step-by-step guide to the complete workflow, together with a case study in Parkinson's disease.
Export Options
About this article
Cite this article as:
Bolgár Bence, Arany Ádám, Temesi Gergely, Balogh Balázs, Antal Péter and Mátyus Péter, Drug Repositioning for Treatment of Movement Disorders: From Serendipity to Rational Discovery Strategies, Current Topics in Medicinal Chemistry 2013; 13 (18) . https://dx.doi.org/10.2174/15680266113136660164
DOI https://dx.doi.org/10.2174/15680266113136660164 |
Print ISSN 1568-0266 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-4294 |
Call for Papers in Thematic Issues
Adaptogens—History and Future Perspectives
Adaptogens are pharmacologically active compounds or plant extracts that are associated with the ability to enhance the body’s stability against stress. The intake of adaptogens is associated not only with a better ability to adapt to stress and maintain or normalise metabolic functions but also with better mental and physical ...read more
AlphaFold in Medicinal Chemistry: Opportunities and Challenges
AlphaFold, a groundbreaking AI tool for protein structure prediction, is revolutionizing drug discovery. Its near-atomic accuracy unlocks new avenues for designing targeted drugs and performing efficient virtual screening. However, AlphaFold's static predictions lack the dynamic nature of proteins, crucial for understanding drug action. This is especially true for multi-domain proteins, ...read more
Artificial intelligence for Natural Products Discovery and Development
Our approach involves using computational methods to predict the potential therapeutic benefits of natural products by considering factors such as drug structure, targets, and interactions. We also employ multitarget analysis to understand the role of drug targets in disease pathways. We advocate for the use of artificial intelligence in predicting ...read more
Chemistry Based on Natural Products for Therapeutic Purposes
The development of new pharmaceuticals for a wide range of medical conditions has long relied on the identification of promising natural products (NPs). There are over sixty percent of cancer, infectious illness, and CNS disease medications that include an NP pharmacophore, according to the Food and Drug Administration. Since NP ...read more
![Wayfinder Image](/images/wayfinder.jpg)
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
- Announcements
Related Articles
-
Synthetic and Natural Protease Inhibitors Provide Insights into Parasite Development, Virulence and Pathogenesis
Current Medicinal Chemistry Immunotherapy, Vascular Pathology, and Microhemorrhages in Transgenic Mice
CNS & Neurological Disorders - Drug Targets Recognition-induced Conformational Changes in Protein-Protein Docking
Current Pharmaceutical Biotechnology Anti-Inflammatory Effects of Triterpenoids; Naturally Occurring and Synthetic Agents
Mini-Reviews in Organic Chemistry Strategies of Functional Foods Promote Sleep in Human Being
Current Signal Transduction Therapy Regulation of Platelet Function by Acetylation/Deacetylation Mechanisms
Current Medicinal Chemistry Matrix Metalloproteinases as Potential Targets in the Venous Dilation Associated with Varicose Veins
Current Drug Targets Current Status of Tyrosine Hydroxylase in Management of Parkinson’s Disease
CNS & Neurological Disorders - Drug Targets Early Risk Factors for Nonadherence in Pediatric Type 1 Diabetes: A Review of the Recent Literature
Current Diabetes Reviews Therapeutic Trials in Human Transmissible Spongiform Encephalopathies: Recent Advances and Problems to Address
Infectious Disorders - Drug Targets Cholinergic Treatment of Traumatic Brain Injury
Current Drug Therapy Motor Complications in Parkinson’s Disease: A Comprehensive Review of Emergent Management Strategies
CNS & Neurological Disorders - Drug Targets Prevention of Cardiovascular Diseases with Anti-Inflammatory and Anti- Oxidant Nutraceuticals and Herbal Products: An Overview of Pre-Clinical and Clinical Studies
Recent Patents on Inflammation & Allergy Drug Discovery An N-terminally Truncated Mutant of Human Chemokine CXCL14 has Biological Activity
Protein & Peptide Letters Preface
Central Nervous System Agents in Medicinal Chemistry Design and Synthesis of New Selective P-gp Substrates and Inhibitors
Current Pharmaceutical Design Fatty Acid Biosynthesis: An Updated Review on KAS Inhibitors
Current Drug Discovery Technologies Targeting Tumor Microenvironment with Silibinin: Promise and Potential for a Translational Cancer Chemopreventive Strategy
Current Cancer Drug Targets An Update on the Association of Protein Kinases with Cardiovascular Diseases
Current Pharmaceutical Design Cybernetic Principles of Aging and Rejuvenation: The Buffering- Challenging Strategy for Life Extension
Current Aging Science