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How Frequently Are Pan-Assay Interference Compounds Active? Large-Scale Analysis of Screening Data Reveals Diverse Activity Profiles, Low Global Hit Frequency, and Many Consistently Inactive Compounds

Journal of medicinal chemistry, 2017-05, Vol.60 (9), p.3879-3886

2017

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Comparing predictive ability of QSAR/QSPR models using 2D and 3D molecular representations

Journal of computer-aided molecular design, 2021-02, Vol.35 (2), p.179-193

2021

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Determining the Degree of Promiscuity of Extensively Assayed Compounds

PloS one, 2016-04, Vol.11 (4), p.e0153873-e0153873

2016

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Interpretation of Ligand-Based Activity Cliff Prediction Models Using the Matched Molecular Pair Kernel

Molecules (Basel, Switzerland), 2021-08, Vol.26 (16), p.4916

2021

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Highly Promiscuous Small Molecules from Biological Screening Assays Include Many Pan-Assay Interference Compounds but Also Candidates for Polypharmacology

Journal of medicinal chemistry, 2016-11, Vol.59 (22), p.10285-10290

2016

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Activity-relevant similarity values for fingerprints and implications for similarity searching

F1000 research, 2016, Vol.5, p.591

2016

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Bridging Structure- and Ligand-Based Virtual Screening through Fragmented Interaction Fingerprint

ACS omega, 2024-09, Vol.9 (37), p.38957-38969

2024

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Extracting Compound Profiling Matrices from Screening Data

ACS omega, 2018-04, Vol.3 (4), p.4706-4712

2018

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Prediction of Compound Profiling Matrices Using Machine Learning

ACS omega, 2018-04, Vol.3 (4), p.4713-4723

2018

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Promiscuity progression of bioactive compounds over time [version 2; peer review: 3 approved]

F1000 research, 2015-06, Vol.4

2015

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Activity-relevant similarity values for fingerprints and implications for similarity searching

F1000 research, 2016-04, Vol.5, p.591

2016

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Promiscuity progression of bioactive compounds over time [version 1; peer review: 2 approved, 1 approved with reservations]

F1000 research, 2015, Vol.4 (Chem Inf Sci), p.118-118

2015

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Sparse Topological Pharmacophore Graphs for Interpretable Scaffold Hopping

Journal of chemical information and modeling, 2021-07, Vol.61 (7), p.3348-3360

2021

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Machine Learning Distinguishes with High Accuracy between Pan-Assay Interference Compounds That Are Promiscuous or Represent Dark Chemical Matter

Journal of medicinal chemistry, 2018-11, Vol.61 (22), p.10255-10264

2018

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Evaluation of different virtual screening strategies on the basis of compound sets with characteristic core distributions and dissimilarity relationships

Journal of computer-aided molecular design, 2019-08, Vol.33 (8), p.729-743

2019

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Assessing the Growth of Bioactive Compounds and Scaffolds over Time: Implications for Lead Discovery and Scaffold Hopping

Journal of chemical information and modeling, 2016-02, Vol.56 (2), p.300-307

2016

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Structure-Promiscuity Relationship Puzzles—Extensively Assayed Analogs with Large Differences in Target Annotations

The AAPS journal, 2017-05, Vol.19 (3), p.856-864

2017

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Dark chemical matter in public screening assays and derivation of target hypotheses

MedChemComm, 2017-11, Vol.8 (11), p.21-214

2017

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Screening and Validation of Odorants against Influenza A Virus Using Interpretable Regression Models

ACS pharmacology & translational science, 2023-01, Vol.6 (1), p.139-150

2023

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Analysis of multitarget activities and assay interference characteristics of pharmaceutically relevant compounds

Jasial, Swarit

2019

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Multiple comonomer concentrations prediction from FTIR spectra with quantum chemistry-based interpretation

MRS communications, 2024, Vol.14 (3), p.439-444

2024

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Computationally derived compound profiling matrices

Future science OA, 2018-09, Vol.4 (8), p.FSO327-FSO327

2018

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Determination of Meta-Parameters for Support Vector Machine Linear Combinations

Molecular informatics, 2015-02, Vol.34 (2-3), p.127-133

2015

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Chemometrics Approach Based on Wavelet Transforms for the Estimation of Monomer Concentrations from FTIR Spectra

ACS omega, 2023-06, Vol.8 (22), p.19781-19788

2023

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How Frequently Are Pan-Assay Interference Compounds Active? Large-Scale Analysis of Screening Data Reveals Diverse Activity Profiles, Low Global Hit Frequency, and Many Consistently Inactive Compounds

Comparing predictive ability of QSAR/QSPR models using 2D and 3D molecular representations

Determining the Degree of Promiscuity of Extensively Assayed Compounds

Interpretation of Ligand-Based Activity Cliff Prediction Models Using the Matched Molecular Pair Kernel

Highly Promiscuous Small Molecules from Biological Screening Assays Include Many Pan-Assay Interference Compounds but Also Candidates for Polypharmacology

Activity-relevant similarity values for fingerprints and implications for similarity searching

Bridging Structure- and Ligand-Based Virtual Screening through Fragmented Interaction Fingerprint

Extracting Compound Profiling Matrices from Screening Data

Prediction of Compound Profiling Matrices Using Machine Learning

Promiscuity progression of bioactive compounds over time [version 2; peer review: 3 approved]

Activity-relevant similarity values for fingerprints and implications for similarity searching

Promiscuity progression of bioactive compounds over time [version 1; peer review: 2 approved, 1 approved with reservations]

Sparse Topological Pharmacophore Graphs for Interpretable Scaffold Hopping

Machine Learning Distinguishes with High Accuracy between Pan-Assay Interference Compounds That Are Promiscuous or Represent Dark Chemical Matter

Evaluation of different virtual screening strategies on the basis of compound sets with characteristic core distributions and dissimilarity relationships

Assessing the Growth of Bioactive Compounds and Scaffolds over Time: Implications for Lead Discovery and Scaffold Hopping

Structure-Promiscuity Relationship Puzzles—Extensively Assayed Analogs with Large Differences in Target Annotations

Dark chemical matter in public screening assays and derivation of target hypotheses

Screening and Validation of Odorants against Influenza A Virus Using Interpretable Regression Models

Analysis of multitarget activities and assay interference characteristics of pharmaceutically relevant compounds

Multiple comonomer concentrations prediction from FTIR spectra with quantum chemistry-based interpretation

Computationally derived compound profiling matrices

Determination of Meta-Parameters for Support Vector Machine Linear Combinations

Chemometrics Approach Based on Wavelet Transforms for the Estimation of Monomer Concentrations from FTIR Spectra

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