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iScore: A ML-Based Scoring Function for de novo Drug Discovery

https://doi.org/10.1101/2024.04.02.587723

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/wcms.1429openalex-snapshot

From machine learning to deep learning: Advances in scoring functions for protein–ligand docking

inferredcites →https://doi.org/10.1007/978-1-4939-9608-7_9openalex-snapshot

Protein–Ligand Binding Free Energy Calculations with FEP+

inferredcites →https://doi.org/10.1007/978-1-59745-177-2_19openalex-snapshot

Molecular Docking

inferredcites →https://doi.org/10.1007/s10822-007-9133-zopenalex-snapshot

Epik: a software program for pK a prediction and protonation state generation for drug-like molecules

inferredcites →https://doi.org/10.1007/s11749-016-0481-7openalex-snapshot

A random forest guided tour

inferredcites →https://doi.org/10.1021/acs.accounts.6b00491openalex-snapshot

Forging the Basis for Developing Protein–Ligand Interaction Scoring Functions

inferredcites →https://doi.org/10.1021/acs.jcim.7b00650openalex-snapshot

K DEEP : Protein–Ligand Absolute Binding Affinity Prediction via 3D-Convolutional Neural Networks

inferredcites →https://doi.org/10.1021/acs.jcim.8b00545openalex-snapshot

Comparative Assessment of Scoring Functions: The CASF-2016 Update

inferredcites →https://doi.org/10.1021/acs.jctc.1c00302openalex-snapshot

OPLS4: Improving Force Field Accuracy on Challenging Regimes of Chemical Space

inferredcites →https://doi.org/10.1021/acsomega.9b04162openalex-snapshot

graphDelta: MPNN Scoring Function for the Affinity Prediction of Protein–Ligand Complexes

inferredcites →https://doi.org/10.1021/ar500432kopenalex-snapshot

The Chemical Space Project

inferredcites →https://doi.org/10.1021/ci4000486openalex-snapshot

CSAR Data Set Release 2012: Ligands, Affinities, Complexes, and Docking Decoys

inferredcites →https://doi.org/10.1021/ct100578zopenalex-snapshot

PROPKA3: Consistent Treatment of Internal and Surface Residues in Empirical p K a Predictions

inferredcites →https://doi.org/10.1021/jm0203783openalex-snapshot

Comparative Evaluation of 11 Scoring Functions for Molecular Docking

inferredcites →https://doi.org/10.1021/jm050362nopenalex-snapshot

A Critical Assessment of Docking Programs and Scoring Functions

inferredcites →https://doi.org/10.1038/nature14539openalex-snapshot

Deep learning

inferredcites →https://doi.org/10.1073/pnas.2000585117openalex-snapshot

Machine learning classification can reduce false positives in structure-based virtual screening

inferredcites →https://doi.org/10.1093/bib/bbac051openalex-snapshot

Improving protein–ligand docking and screening accuracies by incorporating a scoring function correction term

inferredcites →https://doi.org/10.1109/jproc.2015.2494218openalex-snapshot

Taking the Human Out of the Loop: A Review of Bayesian Optimization

inferredcites →https://doi.org/10.1186/1471-2105-10-1openalex-snapshot

Regularized gene selection in cancer microarray meta-analysis

inferredcites →https://doi.org/10.1371/journal.pone.0075992openalex-snapshot

Ligand Pose and Orientational Sampling in Molecular Docking

inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot

Scikit-learn: Machine Learning in Python

inferredcites →https://doi.org/10.48550/arxiv.1803.08375openalex-snapshot

Deep Learning using Rectified Linear Units (ReLU)

inferredcites →https://doi.org/10.55011/staiqc.2021.1104openalex-snapshot

Hyperparameter Tuning of Deep learning Models in Keras

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1021/acs.jcim.5c00491openalex-snapshot

MolAI: A Deep Learning Framework for Data-Driven Molecular Descriptor Generation and Advanced Drug Discovery Applications

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