AI-Based Drug Design: Revolutionizing Drug Discovery through in Silico Analysis
The convergence of artificial intelligence (AI) and drug design has catalyzed a tectonic shift within the pharmaceutical arena, illuminating a new path towards rapid and efficient drug discovery. This review embarks on an odyssey through the transformative landscape of AI-based drug design, de...
Saved in:
Main Authors: | , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
INTI International University
2023
|
Subjects: | |
Online Access: | http://eprints.intimal.edu.my/1812/1/ij2023_56.pdf http://eprints.intimal.edu.my/1812/ https://intijournal.intimal.edu.my |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | INTI International University |
Language: | English |
id |
my-inti-eprints.1812 |
---|---|
record_format |
eprints |
spelling |
my-inti-eprints.18122023-11-08T04:06:02Z http://eprints.intimal.edu.my/1812/ AI-Based Drug Design: Revolutionizing Drug Discovery through in Silico Analysis Yamini Priya, Deepthimahanthi Prakash, Balu Wong, Ling Shing Kumar, Krishnan J., Manjunathan K., Ashokkumar M., Jayanthi M., Suganthi G., Abirami Q Science (General) QA75 Electronic computers. Computer science R Medicine (General) RS Pharmacy and materia medica The convergence of artificial intelligence (AI) and drug design has catalyzed a tectonic shift within the pharmaceutical arena, illuminating a new path towards rapid and efficient drug discovery. This review embarks on an odyssey through the transformative landscape of AI-based drug design, delving into its multifaceted applications and profound implications. By harnessing AI's virtuosity, drug discovery processes are imbued with unprecedented speed and precision. Machine learning algorithms harmonize with intricate biological datasets, unraveling patterns and relationships previously enshrouded in complexity. Deep learning models, akin to modern-day alchemists, sculpt molecular structures and decode binding affinities, accelerating the quest for viable drug candidates. The symphony of AI resonates across the stages of drug discovery, from in silico screening to the hallowed realm of de novo drug design. Virtual libraries become a realm of possibility as AI orchestrates the virtual ballet of compound screening, whittling down the ensemble to a chorus of promising candidates. Moreover, AI's creative fervor burgeons in the crucible of de novo design, forging novel molecules with desired properties. The predictive mastery extends to the realm of absorption, distribution, metabolism, excretion, and toxicity (ADMET) modeling, where AI's crystal ball reveals the fate of molecules based on their molecular signatures. The harmonious confluence of AI and drug design unfolds as a symphony of innovation, orchestrating the metamorphosis of drug discovery into an elegant and efficacious masterpiece INTI International University 2023-11 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/1812/1/ij2023_56.pdf Yamini Priya, Deepthimahanthi and Prakash, Balu and Wong, Ling Shing and Kumar, Krishnan and J., Manjunathan and K., Ashokkumar and M., Jayanthi and M., Suganthi and G., Abirami (2023) AI-Based Drug Design: Revolutionizing Drug Discovery through in Silico Analysis. INTI JOURNAL, 2023 (56). pp. 1-6. ISSN e2600-7320 https://intijournal.intimal.edu.my |
institution |
INTI International University |
building |
INTI Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
INTI International University |
content_source |
INTI Institutional Repository |
url_provider |
http://eprints.intimal.edu.my |
language |
English |
topic |
Q Science (General) QA75 Electronic computers. Computer science R Medicine (General) RS Pharmacy and materia medica |
spellingShingle |
Q Science (General) QA75 Electronic computers. Computer science R Medicine (General) RS Pharmacy and materia medica Yamini Priya, Deepthimahanthi Prakash, Balu Wong, Ling Shing Kumar, Krishnan J., Manjunathan K., Ashokkumar M., Jayanthi M., Suganthi G., Abirami AI-Based Drug Design: Revolutionizing Drug Discovery through in Silico Analysis |
description |
The convergence of artificial intelligence (AI) and drug design has catalyzed a tectonic shift within
the pharmaceutical arena, illuminating a new path towards rapid and efficient drug discovery. This
review embarks on an odyssey through the transformative landscape of AI-based drug design,
delving into its multifaceted applications and profound implications. By harnessing AI's virtuosity,
drug discovery processes are imbued with unprecedented speed and precision. Machine learning
algorithms harmonize with intricate biological datasets, unraveling patterns and relationships
previously enshrouded in complexity. Deep learning models, akin to modern-day alchemists,
sculpt molecular structures and decode binding affinities, accelerating the quest for viable drug
candidates. The symphony of AI resonates across the stages of drug discovery, from in silico
screening to the hallowed realm of de novo drug design. Virtual libraries become a realm of
possibility as AI orchestrates the virtual ballet of compound screening, whittling down the
ensemble to a chorus of promising candidates. Moreover, AI's creative fervor burgeons in the
crucible of de novo design, forging novel molecules with desired properties. The predictive
mastery extends to the realm of absorption, distribution, metabolism, excretion, and toxicity
(ADMET) modeling, where AI's crystal ball reveals the fate of molecules based on their molecular
signatures. The harmonious confluence of AI and drug design unfolds as a symphony of
innovation, orchestrating the metamorphosis of drug discovery into an elegant and efficacious
masterpiece |
format |
Article |
author |
Yamini Priya, Deepthimahanthi Prakash, Balu Wong, Ling Shing Kumar, Krishnan J., Manjunathan K., Ashokkumar M., Jayanthi M., Suganthi G., Abirami |
author_facet |
Yamini Priya, Deepthimahanthi Prakash, Balu Wong, Ling Shing Kumar, Krishnan J., Manjunathan K., Ashokkumar M., Jayanthi M., Suganthi G., Abirami |
author_sort |
Yamini Priya, Deepthimahanthi |
title |
AI-Based Drug Design: Revolutionizing Drug Discovery through in Silico
Analysis |
title_short |
AI-Based Drug Design: Revolutionizing Drug Discovery through in Silico
Analysis |
title_full |
AI-Based Drug Design: Revolutionizing Drug Discovery through in Silico
Analysis |
title_fullStr |
AI-Based Drug Design: Revolutionizing Drug Discovery through in Silico
Analysis |
title_full_unstemmed |
AI-Based Drug Design: Revolutionizing Drug Discovery through in Silico
Analysis |
title_sort |
ai-based drug design: revolutionizing drug discovery through in silico
analysis |
publisher |
INTI International University |
publishDate |
2023 |
url |
http://eprints.intimal.edu.my/1812/1/ij2023_56.pdf http://eprints.intimal.edu.my/1812/ https://intijournal.intimal.edu.my |
_version_ |
1783884482141487104 |