Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Macalino, Stephani Joy Y., Basith, Shaherin, Clavio, Nina Abigail B., Chang, Hyerim, Kang, Soosung, Choi, Sun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6222862/
https://www.ncbi.nlm.nih.gov/pubmed/30082644
http://dx.doi.org/10.3390/molecules23081963
_version_ 1783369306167312384
author Macalino, Stephani Joy Y.
Basith, Shaherin
Clavio, Nina Abigail B.
Chang, Hyerim
Kang, Soosung
Choi, Sun
author_facet Macalino, Stephani Joy Y.
Basith, Shaherin
Clavio, Nina Abigail B.
Chang, Hyerim
Kang, Soosung
Choi, Sun
author_sort Macalino, Stephani Joy Y.
collection PubMed
description 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.
format Online
Article
Text
id pubmed-6222862
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-62228622018-11-13 Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery Macalino, Stephani Joy Y. Basith, Shaherin Clavio, Nina Abigail B. Chang, Hyerim Kang, Soosung Choi, Sun Molecules Review 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. MDPI 2018-08-06 /pmc/articles/PMC6222862/ /pubmed/30082644 http://dx.doi.org/10.3390/molecules23081963 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Macalino, Stephani Joy Y.
Basith, Shaherin
Clavio, Nina Abigail B.
Chang, Hyerim
Kang, Soosung
Choi, Sun
Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery
title Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery
title_full Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery
title_fullStr Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery
title_full_unstemmed Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery
title_short Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery
title_sort evolution of in silico strategies for protein-protein interaction drug discovery
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6222862/
https://www.ncbi.nlm.nih.gov/pubmed/30082644
http://dx.doi.org/10.3390/molecules23081963
work_keys_str_mv AT macalinostephanijoyy evolutionofinsilicostrategiesforproteinproteininteractiondrugdiscovery
AT basithshaherin evolutionofinsilicostrategiesforproteinproteininteractiondrugdiscovery
AT clavioninaabigailb evolutionofinsilicostrategiesforproteinproteininteractiondrugdiscovery
AT changhyerim evolutionofinsilicostrategiesforproteinproteininteractiondrugdiscovery
AT kangsoosung evolutionofinsilicostrategiesforproteinproteininteractiondrugdiscovery
AT choisun evolutionofinsilicostrategiesforproteinproteininteractiondrugdiscovery