Results 21 to 30 of about 28,587,314 (277)

Benchmarking Ligand-Based Virtual High-Throughput Screening with the PubChem Database [PDF]

Molecules, 2013
With the rapidly increasing availability of High-Throughput Screening (HTS) data in the public domain, such as the PubChem database, methods for ligand-based computer-aided drug discovery (LB-CADD) have the potential to accelerate and reduce the cost of ...
Mariusz Butkiewicz, Edward W. Lowe, Ralf Mueller, Jeffrey L. Mendenhall, Pedro L. Teixeira, C. David Weaver, Jens Meiler   +6 more
doaj   +3 more sources

VSFlow: an open-source ligand-based virtual screening tool [PDF]

, 2022
Ligand-based virtual screening is a widespread method in modern drug design. It allows for a rapid screening of large compound databases in order to identify similar structures.
Paul, Czodrowski, Helge, Vatheuer, Sascha, Jung, Helge Vatheuer, Paul Czodrowski, Sascha Jung   +5 more
core   +1 more source

A review of deep learning methods for ligand based drug virtual screening

Fundamental Research
Drug discovery is costly and time consuming, and modern drug discovery endeavors are progressively reliant on computational methodologies, aiming to mitigate temporal and financial expenditures associated with the process.
Hongjie Wu, Junkai Liu, Runhua Zhang, Yaoyao Lu, Guozeng Cui, Zhiming Cui, Yijie Ding   +6 more
doaj   +3 more sources

Virtual-Ligand-Assisted Screening Strategy to Discover Enabling Ligands for Transition Metal Catalysis [PDF]

, 2022
The ligand screening process, in which an optimal ligand for a reaction of interest is identified from an enormous and diverse set of candidate molecules, is of particular importance in the development of transition metal catalysis.
Satoshi, Maeda, Wataru, Matsuoka, Yu, Harabuchi   +2 more
core   +2 more sources

Exploring the ability of machine learning-based virtual screening models to identify the functional groups responsible for binding

Journal of Cheminformatics, 2023
Many recently proposed structure-based virtual screening models appear to be able to accurately distinguish high affinity binders from non-binders. However, several recent studies have shown that they often do so by exploiting ligand-specific biases in ...
Thomas E. Hadfield, Jack Scantlebury, Charlotte M. Deane   +2 more
doaj   +1 more source

Probabilistic Approach for Virtual Screening Based on Multiple Pharmacophores

Molecules, 2020
Pharmacophore modeling is usually considered as a special type of virtual screening without probabilistic nature. Correspondence of at least one conformation of a molecule to pharmacophore is considered as evidence of its bioactivity.
Timur I. Madzhidov, Assima Rakhimbekova, Alina Kutlushuna, Pavel Polishchuk   +3 more
doaj   +1 more source

NeuralDock: Rapid and Conformation-Agnostic Docking of Small Molecules

Frontiers in Molecular Biosciences, 2022
Virtual screening is a cost- and time-effective alternative to traditional high-throughput screening in the drug discovery process. Both virtual screening approaches, structure-based molecular docking and ligand-based cheminformatics, suffer from ...
Congzhou M. Sha, Congzhou M. Sha, Jian Wang, Nikolay V. Dokholyan, Nikolay V. Dokholyan, Nikolay V. Dokholyan, Nikolay V. Dokholyan   +6 more
doaj   +1 more source

Computational strategies for PROTAC drug discovery

Acta Materia Medica, 2023
Proteolysis-targeting chimeras (PROTACs), a novel targeted protein degradation technology for potential clinical drug discovery, is composed of a protein-targeting ligand covalently linked to an E3 ligase ligand.
Jia Wu, Wanhe Wang, Chung-Hang Leung
doaj   +1 more source

Highly Chemoselective Ligands for Suzuki–Miyaura Cross-Coupling Reaction Based on Virtual Ligand-Assisted Screening [PDF]

, 2023
Ligand screening is a crucial step in the development of transition metal catalysis, as it involves identifying the optimal ligand for a particular reaction from a large pool of candidate molecules.
Yuuya, Nagata, Satoshi, Maeda, Wataru, Matsuoka, Yu, Harabuchi, Yuuya Nagata, Satoshi Maeda, Wataru Matsuoka, Yu Harabuchi   +7 more
core   +2 more sources

BigBind: Learning from Nonstructural Data for Structure-Based Virtual Screening [PDF]

, 2023
Deep learning methods that predict protein-ligand binding have recently been used for structure-based virtual screening. Many such models have been trained using protein-ligand complexes with known crystal structures and activities from the PDBBind ...
Paul, Francoeur, Rishal, Aggarwal, Konstantin, Popov, Alexander, Tropsha, Michael, Brocidiacono, David, Koes   +5 more
core   +2 more sources