EventsMOL2NET'23, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 9th ed.
Published
with-doi10.3390/mol2net-09-14209 (registering DOI)
This submission belongs to the session 03. NICE.XSM-09: North-Ibero-America Congress on Exp. & Simul. Methods, Valencia, Spain-Miami, USA, 2023. of the event MOL2NET'23, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 9th ed.
Published date
14 Mar, 2023
Academic Editor
author-avatarMOL2NET Team
Citation
Shan He, Recent Topic in Computer-aided Drug Design and Discovery in Biomedical Research, in Proceedings of MOL2NET'23, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 9th ed., 25 December–31 December 2023, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-09-14209
Share
Email
Facebook
Twitter
LinkedIn

Recent Topic in Computer-aided Drug Design and Discovery in Biomedical Research

image
1. Department of Organic and Inorganic Chemistry, Faculty of Science and Technology, University of the Basque Country UPV/EHU, P.O.Box 644, 48080 Bilbao, Spain.
2. IKERDATA S.L, ZITEK, UPV/EHU, Rectorate Building, n0 6, Leioa, Greater Bilbao, Basque Country, Spain.
Abstract

Drug design and discovery is a complex, expensive and arduous procedure taking into account the multiple existing diseases and their variants. This long process includes the identification of potential targets and the development of therapeutically safe and effective drugs.1 Computer-aided drug design (CADD) can make it less time- and resource-consuming. In recent research, computational and statistical techniques are used in an effective way to study biomedical compounds for target identification and hit hunting. The arrival of ML in this field of study offers important enhancement in the efficacy of drug design and discovery process. The success drug design, discovery and development are in concordance with the computational methods and tools. They need to be accurate and use a reliable pre-processed data. Henceforward, Artificial Intelligence/Machine Leaning (AI) approaches to data pre-processing, modeling and representative applications in drug design and discovery will be introduced.

Keywords
Drug design
Computer-aided
Artificial intelligence
Biomedical application
Manuscript
Evaluation and Investigation of Anti-diabetes profiles
using Medicinal plants by Data Visualization Techniques
Current Innovative Artificial Intelligence Approach in Neuroscience