Machine learning in drug discovery: a review

S Dara, S Dhamercherla, SS Jadav, CHM Babu… - Artificial intelligence …, 2022 - Springer
This review provides the feasible literature on drug discovery through ML tools and
techniques that are enforced in every phase of drug development to accelerate the research …

Artificial intelligence for drug discovery: Resources, methods, and applications

W Chen, X Liu, S Zhang, S Chen - Molecular Therapy-Nucleic Acids, 2023 - cell.com
Conventional wet laboratory testing, validations, and synthetic procedures are costly and
time-consuming for drug discovery. Advancements in artificial intelligence (AI) techniques …

Artificial intelligence in drug discovery and development

KK Mak, YH Wong, MR Pichika - Drug discovery and evaluation: safety …, 2024 - Springer
This chapter comprehensively explores the pivotal role of artificial intelligence (AI) in drug
discovery and development, encapsulating its potentials, methodologies, real-world …

Machine learning methods in drug discovery

L Patel, T Shukla, X Huang, DW Ussery, S Wang - Molecules, 2020 - mdpi.com
The advancements of information technology and related processing techniques have
created a fertile base for progress in many scientific fields and industries. In the fields of drug …

Machine‐Learning‐Assisted Nanozyme Design: Lessons from Materials and Engineered Enzymes

J Zhuang, AC Midgley, Y Wei, Q Liu, D Kong… - Advanced …, 2024 - Wiley Online Library
Nanozymes are nanomaterials that exhibit enzyme‐like biomimicry. In combination with
intrinsic characteristics of nanomaterials, nanozymes have broad applicability in materials …

Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries

C Selvaraj, I Chandra, SK Singh - Molecular diversity, 2021 - Springer
The global spread of COVID-19 has raised the importance of pharmaceutical drug
development as intractable and hot research. Developing new drug molecules to overcome …

Structure-based drug repurposing: Traditional and advanced AI/ML-aided methods

C Choudhury, NA Murugan, UD Priyakumar - Drug discovery today, 2022 - Elsevier
Highlights•Repurposing existing drugs for new diseases is cost effective and time saving.•In
silico methods are crucial for rapid drug screening in the early stages.•Machine learning …

Taking the leap between analytical chemistry and artificial intelligence: A tutorial review

LB Ayres, FJV Gomez, JR Linton, MF Silva… - Analytica Chimica …, 2021 - Elsevier
The last 10 years have witnessed the growth of artificial intelligence into different research
areas, emerging as a vibrant discipline with the capacity to process large amounts of …

Fuzzy-based hunger games search algorithm for global optimization and feature selection using medical data

EH Houssein, ME Hosney, WM Mohamed… - Neural Computing and …, 2023 - Springer
Feature selection (FS) is one of the basic data preprocessing steps in data mining and
machine learning. It is used to reduce feature size and increase model generalization. In …

DeepCompoundNet: enhancing compound–protein interaction prediction with multimodal convolutional neural networks

F Palhamkhani, M Alipour, A Dehnad… - Journal of …, 2023 - Taylor & Francis
Virtual screening has emerged as a valuable computational tool for predicting compound–
protein interactions, offering a cost-effective and rapid approach to identifying potential …