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Small Molecule Libraries

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Multiple Machine Learning Based-Chemoinformatics Models for Identification of Histone Acetyl Transferase Inhibitors.

Molecular informatics
The histone acetyl transferase (HAT) are involved in acetylation of histones that lead to transcription activation in numerous gene regulatory mechanisms. There are very few GCN5 HAT inhibitors reported despite of their role in cancer progression. In...

Chemogenomic Active Learning's Domain of Applicability on Small, Sparse qHTS Matrices: A Study Using Cytochrome P450 and Nuclear Hormone Receptor Families.

ChemMedChem
Computational models for predicting the activity of small molecules against targets are now routinely developed and used in academia and industry, partially due to public bioactivity databases. While models based on bigger datasets are the trend, rec...

Hit Dexter: A Machine-Learning Model for the Prediction of Frequent Hitters.

ChemMedChem
False-positive assay readouts caused by badly behaving compounds-frequent hitters, pan-assay interference compounds (PAINS), aggregators, and others-continue to pose a major challenge to experimental screening. There are only a few in silico methods ...

Inner and Outer Recursive Neural Networks for Chemoinformatics Applications.

Journal of chemical information and modeling
Deep learning methods applied to problems in chemoinformatics often require the use of recursive neural networks to handle data with graphical structure and variable size. We present a useful classification of recursive neural network approaches into...

De Novo Design of Bioactive Small Molecules by Artificial Intelligence.

Molecular informatics
Generative artificial intelligence offers a fresh view on molecular design. We present the first-time prospective application of a deep learning model for designing new druglike compounds with desired activities. For this purpose, we trained a recurr...

In silico toxicity profiling of natural product compound libraries from African flora with anti-malarial and anti-HIV properties.

Computational biology and chemistry
This paper describes an analysis of the diversity and chemical toxicity assessment of three chemical libraries of compounds from African flora (the p-ANAPL, AfroMalariaDb, and Afro-HIV), respectively containing compounds exhibiting activities against...

Prediction of Collision Cross-Section Values for Small Molecules: Application to Pesticide Residue Analysis.

Analytical chemistry
The use of collision cross-section (CCS) values obtained by ion mobility high-resolution mass spectrometry has added a third dimension (alongside retention time and exact mass) to aid in the identification of compounds. However, its utility is limite...

Improving virtual screening predictive accuracy of Human kallikrein 5 inhibitors using machine learning models.

Computational biology and chemistry
The readily available high throughput screening (HTS) data from the PubChem database provides an opportunity for mining of small molecules in a variety of biological systems using machine learning techniques. From the thousands of available molecular...

Identification of small molecules using accurate mass MS/MS search.

Mass spectrometry reviews
Tandem mass spectral library search (MS/MS) is the fastest way to correctly annotate MS/MS spectra from screening small molecules in fields such as environmental analysis, drug screening, lipid analysis, and metabolomics. The confidence in MS/MS-base...

Bayesian molecular design with a chemical language model.

Journal of computer-aided molecular design
The aim of computational molecular design is the identification of promising hypothetical molecules with a predefined set of desired properties. We address the issue of accelerating the material discovery with state-of-the-art machine learning techni...