The power of generative ai: A review of requirements, models, input–output formats, evaluation metrics, and challenges
A Bandi, PVSR Adapa, YEVPK Kuchi - Future Internet, 2023 - mdpi.com
Generative artificial intelligence (AI) has emerged as a powerful technology with numerous
applications in various domains. There is a need to identify the requirements and evaluation …
applications in various domains. There is a need to identify the requirements and evaluation …
An updated review on developing small molecule kinase inhibitors using computer-aided drug design approaches
L Li, S Liu, B Wang, F Liu, S Xu, P Li… - International Journal of …, 2023 - mdpi.com
Small molecule kinase inhibitors (SMKIs) are of heightened interest in the field of drug
research and development. There are 79 (as of July 2023) small molecule kinase inhibitors …
research and development. There are 79 (as of July 2023) small molecule kinase inhibitors …
Explore drug-like space with deep generative models
The process of design/discovery of drugs involves the identification and design of novel
molecules that have the desired properties and bind well to a given disease-relevant target …
molecules that have the desired properties and bind well to a given disease-relevant target …
Control of citrus blue and green molds by Actinomycin X2 and its possible antifungal mechanism
L Gao, Y Liang, Q Xiong, M Huang, Y Jiang… - Pesticide Biochemistry …, 2024 - Elsevier
Citrus blue and green molds caused by Penicillium digitatum, P. italicum, and P. polonicum,
are the major postharvest diseases of citrus fruit. In the present study, Actinomycin X 2 (Act-X …
are the major postharvest diseases of citrus fruit. In the present study, Actinomycin X 2 (Act-X …
Semi-equivariant conditional normalizing flows, with applications to target-aware molecule generation
E Rozenberg, D Freedman - Machine Learning: Science and …, 2023 - iopscience.iop.org
Learning over the domain of 3D graphs has applications in a number of scientific and
engineering disciplines, including molecular chemistry, high energy physics, and computer …
engineering disciplines, including molecular chemistry, high energy physics, and computer …
Geometric deep learning methods and applications in 3D structure-based drug design
Abstract 3D structure-based drug design (SBDD) is considered a challenging and rational
way for innovative drug discovery. Geometric deep learning is a promising approach that …
way for innovative drug discovery. Geometric deep learning is a promising approach that …
Computational exploration of the structural requirements of triazole derivatives as colchicine binding site inhibitors
Colchicine inhibits microtubule assembly by preventing tubulin polymerization, making the
colchicine binding site a promising target against cancer. The present study focuses on the …
colchicine binding site a promising target against cancer. The present study focuses on the …
Modern machine‐learning for binding affinity estimation of protein–ligand complexes: Progress, opportunities, and challenges
T Harren, T Gutermuth, C Grebner… - Wiley …, 2024 - Wiley Online Library
Abstract Structure‐based drug design is a widely applied approach in the discovery of new
lead compounds for known therapeutic targets. In most structure‐based drug design …
lead compounds for known therapeutic targets. In most structure‐based drug design …
Interface-aware molecular generative framework for protein-protein interaction modulators
Protein-protein interactions (PPIs) play a crucial role in many biochemical processes and
biological processes. Recently, many structure-based molecular generative models have …
biological processes. Recently, many structure-based molecular generative models have …
Generating potential protein-protein interaction inhibitor molecules based on physicochemical properties
Protein-protein interactions (PPIs) are associated with various diseases; hence, they are
important targets in drug discovery. However, the physicochemical empirical properties of …
important targets in drug discovery. However, the physicochemical empirical properties of …