Machine Learning for Sequence and Structure-Based Protein–Ligand Interaction Prediction

Y Zhang, S Li, K Meng, S Sun - Journal of chemical information …, 2024‏ - ACS Publications
Develo** new drugs is too expensive and time-consuming. Accurately predicting the
interaction between drugs and targets will likely change how the drug is discovered …

[HTML][HTML] A review on compound-protein interaction prediction methods: data, format, representation and model

S Lim, Y Lu, CY Cho, I Sung, J Kim, Y Kim… - Computational and …, 2021‏ - Elsevier
There has recently been a rapid progress in computational methods for determining protein
targets of small molecule drugs, which will be termed as compound protein interaction (CPI) …

Comparing structural fingerprints using a literature-based similarity benchmark

NM O'Boyle, RA Sayle - Journal of cheminformatics, 2016‏ - Springer
Background The concept of molecular similarity is one of the central ideas in
cheminformatics, despite the fact that it is ill-defined and rather difficult to assess objectively …

pySiRC”: Machine Learning Combined with Molecular Fingerprints to Predict the Reaction Rate Constant of the Radical-Based Oxidation Processes of Aqueous …

FO Sanches-Neto, JR Dias-Silva… - Environmental …, 2021‏ - ACS Publications
We developed a web application structured in a machine learning and molecular fingerprint
algorithm for the automatic calculation of the reaction rate constant of the oxidative …

Drug—drug interaction through molecular structure similarity analysis

S Vilar, R Harpaz, E Uriarte, L Santana… - Journal of the …, 2012‏ - academic.oup.com
Abstract Background Drug–drug interactions (DDIs) are responsible for many serious
adverse events; their detection is crucial for patient safety but is very challenging. Currently …

iDrug-Target: predicting the interactions between drug compounds and target proteins in cellular networking via benchmark dataset optimization approach

X **ao, JL Min, WZ Lin, Z Liu, X Cheng… - Journal of Biomolecular …, 2015‏ - Taylor & Francis
Information about the interactions of drug compounds with proteins in cellular networking is
very important for drug development. Unfortunately, all the existing predictors for identifying …

Metabolite identification and molecular fingerprint prediction through machine learning

M Heinonen, H Shen, N Zamboni, J Rousu - Bioinformatics, 2012‏ - academic.oup.com
Motivation: Metabolite identification from tandem mass spectra is an important problem in
metabolomics, underpinning subsequent metabolic modelling and network analysis. Yet …

Crystal Structure-Based Virtual Screening for Fragment-like Ligands of the Human Histamine H1 Receptor

C De Graaf, AJ Kooistra, HF Vischer… - Journal of medicinal …, 2011‏ - ACS Publications
The recent crystal structure determinations of druggable class AG protein-coupled receptors
(GPCRs) have opened up excellent opportunities in structure-based ligand discovery for this …

[HTML][HTML] A brief review of protein–ligand interaction prediction

L Zhao, Y Zhu, J Wang, N Wen, C Wang… - Computational and …, 2022‏ - Elsevier
The task of identifying protein–ligand interactions (PLIs) plays a prominent role in the field of
drug discovery. However, it is infeasible to identify potential PLIs via costly and laborious in …

Similarity searching using 2D structural fingerprints

P Willett - Chemoinformatics and computational chemical biology, 2011‏ - Springer
This chapter reviews the use of molecular fingerprints for chemical similarity searching. The
fingerprints encode the presence of 2D substructural fragments in a molecule, and the …