Next Article in Journal
Changes in Nutrient Profile and Antioxidant Activities of Different Fish Soups, Before and After Simulated Gastrointestinal Digestion
Previous Article in Journal
Atriplex mollis Desf. Aerial Parts: Extraction Procedures, Secondary Metabolites and Color Analysis
Previous Article in Special Issue
Fingerprint-Based Machine Learning Approach to Identify Potent and Selective 5-HT2BR Ligands
Article Menu

Export Article

Open AccessReview
Molecules 2018, 23(8), 1963; https://doi.org/10.3390/molecules23081963

Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery

College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea
These authors contributed equally to this work.
*
Authors to whom correspondence should be addressed.
Academic Editor: F. Javier Luque
Received: 17 July 2018 / Revised: 3 August 2018 / Accepted: 4 August 2018 / Published: 6 August 2018
(This article belongs to the Special Issue Frontiers in Computational Chemistry for Drug Discovery)
View Full-Text   |   Download PDF [5805 KB, uploaded 8 August 2018]   |  

Abstract

The advent of advanced molecular modeling software, big data analytics, and high-speed processing units has led to the exponential evolution of modern drug discovery and better insights into complex biological processes and disease networks. This has progressively steered current research interests to understanding protein-protein interaction (PPI) systems that are related to a number of relevant diseases, such as cancer, neurological illnesses, metabolic disorders, etc. However, targeting PPIs are challenging due to their “undruggable” binding interfaces. In this review, we focus on the current obstacles that impede PPI drug discovery, and how recent discoveries and advances in in silico approaches can alleviate these barriers to expedite the search for potential leads, as shown in several exemplary studies. We will also discuss about currently available information on PPI compounds and systems, along with their usefulness in molecular modeling. Finally, we conclude by presenting the limits of in silico application in drug discovery and offer a perspective in the field of computer-aided PPI drug discovery. View Full-Text
Keywords: protein-protein interaction; peptidomimetics; hot spots; network analysis; machine learning; docking; virtual screening; fragment-based design; molecular dynamics protein-protein interaction; peptidomimetics; hot spots; network analysis; machine learning; docking; virtual screening; fragment-based design; molecular dynamics
Figures

Figure 1

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

Share & Cite This Article

MDPI and ACS Style

Macalino, S.J.Y.; Basith, S.; Clavio, N.A.B.; Chang, H.; Kang, S.; Choi, S. Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery. Molecules 2018, 23, 1963.

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