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Comparative Assessment of Scoring Functions on an Updated Benchmark: 1. Compilation of the Test Set

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What this work says

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

inferredcites →https://doi.org/10.1002/0471224413.ch1openalex-snapshot

Small Molecule Docking and Scoring

inferredcites →https://doi.org/10.1002/0471466638openalex-snapshot

Reviews in Computational Chemistry

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Evaluation of library ranking efficacy in virtual screening

inferredcites →https://doi.org/10.1002/jcc.20893openalex-snapshot

Assessment of programs for ligand binding affinity prediction

inferredcites →https://doi.org/10.1002/prot.20088openalex-snapshot

A detailed comparison of current docking and scoring methods on systems of pharmaceutical relevance

inferredcites →https://doi.org/10.1002/prot.20149openalex-snapshot

Comparative evaluation of eight docking tools for docking and virtual screening accuracy

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Binding MOAD (Mother Of All Databases)

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The interpretation of protein structures: Estimation of static accessibility

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A geometric approach to macromolecule-ligand interactions

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Getting that hit: 3D database searching in drug discovery

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Scoring functions for protein–ligand interactions: a critical perspective

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Ligand efficiency and fragment-based drug discovery

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Essential considerations for using protein–ligand structures in drug discovery

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Structural Basis of Substrate Binding Specificity Revealed by the Crystal Structures of Polyamine Receptors SpuD and SpuE from Pseudomonas aeruginosa

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Exploring protein–ligand recognition with Binding MOAD

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Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings

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Ligand efficiency indices as guideposts for drug discovery

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Carbonic Anhydrase Activators: X-ray Crystallographic and Spectroscopic Investigations for the Interaction of Isozymes I and II with Histamine,

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On Evaluating Molecular-Docking Methods for Pose Prediction and Enrichment Factors

inferredcites →https://doi.org/10.1021/ci200082topenalex-snapshot

CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes

inferredcites →https://doi.org/10.1021/ci200269qopenalex-snapshot

CSAR Benchmark Exercise of 2010: Combined Evaluation Across All Submitted Scoring Functions

inferredcites →https://doi.org/10.1021/ci200612fopenalex-snapshot

Biophysical Limits of Protein–Ligand Binding

inferredcites →https://doi.org/10.1021/ci400025fopenalex-snapshot

CSAR Benchmark Exercise 2011–2012: Evaluation of Results from Docking and Relative Ranking of Blinded Congeneric Series

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/ci4004249openalex-snapshot

Check Your Confidence: Size Really Does Matter

inferredcites →https://doi.org/10.1021/ci500081mopenalex-snapshot

Comparative Assessment of Scoring Functions on an Updated Benchmark: 2. Evaluation Methods and General Results

inferredcites →https://doi.org/10.1021/ci6003527openalex-snapshot

Analysis of Ligand-Bound Water Molecules in High-Resolution Crystal Structures of Protein−Ligand Complexes

inferredcites →https://doi.org/10.1021/ci700028wopenalex-snapshot

Automatic Perception of Organic Molecules Based on Essential Structural Information

inferredcites →https://doi.org/10.1021/ci7000346openalex-snapshot

Comparative Performance of Several Flexible Docking Programs and Scoring Functions: Enrichment Studies for a Diverse Set of Pharmaceutically Relevant Targets

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Computation of Octanol−Water Partition Coefficients by Guiding an Additive Model with Knowledge

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Comparative Assessment of Scoring Functions on a Diverse Test Set

inferredcites →https://doi.org/10.1021/ci900056copenalex-snapshot

Comparison of Several Molecular Docking Programs: Pose Prediction and Virtual Screening Accuracy

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Molecular Recognition of Protein−Ligand Complexes: Applications to Drug Design

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van der Waals Volumes and Radii

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Classification of Water Molecules in Protein Binding Sites

inferredcites →https://doi.org/10.1021/jm0003992openalex-snapshot

Detailed Analysis of Scoring Functions for Virtual Screening

inferredcites →https://doi.org/10.1021/jm001044lopenalex-snapshot

Protein-Based Virtual Screening of Chemical Databases. 1. Evaluation of Different Docking/Scoring Combinations

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

Comparative Evaluation of 11 Scoring Functions for Molecular Docking

inferredcites →https://doi.org/10.1021/jm0302997openalex-snapshot

Evaluation of Docking Performance: Comparative Data on Docking Algorithms

inferredcites →https://doi.org/10.1021/jm030580lopenalex-snapshot

The PDBbind Database: Collection of Binding Affinities for Protein−Ligand Complexes with Known Three-Dimensional Structures

inferredcites →https://doi.org/10.1021/jm048957qopenalex-snapshot

The PDBbind Database: Methodologies and Updates

inferredcites →https://doi.org/10.1021/jm049798dopenalex-snapshot

Comparison of Automated Docking Programs as Virtual Screening Tools

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

A Critical Assessment of Docking Programs and Scoring Functions

inferredcites →https://doi.org/10.1021/jm060999mopenalex-snapshot

Prediction of Protein−Ligand Interactions. Docking and Scoring: Successes and Gaps

inferredcites →https://doi.org/10.1021/jm061277yopenalex-snapshot

Diverse, High-Quality Test Set for the Validation of Protein−Ligand Docking Performance

inferredcites →https://doi.org/10.1021/jm300131xopenalex-snapshot

The Experimental Uncertainty of Heterogeneous Public Ki Data

inferredcites →https://doi.org/10.1021/jm701023hopenalex-snapshot

Robust Classification of “Relevant” Water Molecules in Putative Protein Binding Sites

inferredcites →https://doi.org/10.1021/jm701255bopenalex-snapshot

Ligand Binding Efficiency: Trends, Physical Basis, and Implications

inferredcites →https://doi.org/10.1021/jm8006504openalex-snapshot

Differences between High- and Low-Affinity Complexes of Enzymes and Nonenzymes

inferredcites →https://doi.org/10.1021/jm8016464openalex-snapshot

Structural Artifacts in Protein−Ligand X-ray Structures: Implications for the Development of Docking Scoring Functions

inferredcites →https://doi.org/10.1023/b:jcam.0000017496.76572.6fopenalex-snapshot

Comparative study of several algorithms for flexible ligand docking

inferredcites →https://doi.org/10.1023/b:jcam.0000047812.39758.abopenalex-snapshot

Evaluation and application of multiple scoring functions for a virtual screening experiment

inferredcites →https://doi.org/10.1038/nrd1549openalex-snapshot

Docking and scoring in virtual screening for drug discovery: methods and applications

inferredcites →https://doi.org/10.1073/pnas.96.18.9997openalex-snapshot

The maximal affinity of ligands

inferredcites →https://doi.org/10.1093/bioinformatics/btq003openalex-snapshot

CD-HIT Suite: a web server for clustering and comparing biological sequences

inferredcites →https://doi.org/10.1093/nar/28.1.235openalex-snapshot

The Protein Data Bank

inferredcites →https://doi.org/10.1093/nar/gkq1126openalex-snapshot

DrugBank 3.0: a comprehensive resource for 'Omics' research on drugs

inferredcites →https://doi.org/10.1107/s0108767390010224openalex-snapshot

Improved methods for building protein models in electron density maps and the location of errors in these models

inferredcites →https://doi.org/10.1107/s0907444902003931openalex-snapshot

Rearrangement of Cruickshank's formulae for the diffraction-component precision index

inferredcites →https://doi.org/10.1107/s0907444998012645openalex-snapshot

Remarks about protein structure precision

inferredcites →https://doi.org/10.1126/science.1096361openalex-snapshot

The Many Roles of Computation in Drug Discovery

inferredcites →https://doi.org/10.1126/science.257.5073.1078openalex-snapshot

Structure-Based Strategies for Drug Design and Discovery

inferredcites →https://doi.org/10.1128/aac.01594-10openalex-snapshot

Structural and Binding Analysis of Pyrimidinol Carboxylic Acid and N -Hydroxy Quinazolinedione HIV-1 RNase H Inhibitors

inferredcites →https://doi.org/10.1146/annurev.biophys.32.110601.142532openalex-snapshot

Molecular Recognition and Docking Algorithms

inferredcites →https://doi.org/10.2174/156802610790232251openalex-snapshot

Successful Applications of Computer Aided Drug Discovery: Moving Drugs from Concept to the Clinic

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

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Empirical Scoring Functions for Affinity Prediction of Protein‐ligand Complexes

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Deep GIST: Deep Learning Models for Predicting the Distribution of Hydration Thermodynamics around Proteins

inferred← citeshttps://doi.org/10.1021/acs.jcim.5c02921openalex-snapshot

LigandExplorer: An Automated Tool for Ligand Extraction from PDB Structures

inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00001openalex-snapshot

PBSA_E: A PBSA-Based Free Energy Estimator for Protein–Ligand Binding Affinity

inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00163openalex-snapshot

PL-PatchSurfer2: Improved Local Surface Matching-Based Virtual Screening Method That Is Tolerant to Target and Ligand Structure Variation

inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00182openalex-snapshot

Lessons Learned over Four Benchmark Exercises from the Community Structure–Activity Resource

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A Hybrid Knowledge-Based and Empirical Scoring Function for Protein–Ligand Interaction: SMoG2016

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High-Quality Dataset of Protein-Bound Ligand Conformations and Its Application to Benchmarking Conformer Ensemble Generators

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Persistent Local Laplacian Prediction of Protein–Ligand Binding Affinities

inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00309openalex-snapshot

Task-Specific Scoring Functions for Predicting Ligand Binding Poses and Affinity and for Screening Enrichment

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Descriptor Data Bank (DDB): A Cloud Platform for Multiperspective Modeling of Protein–Ligand Interactions

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Estimating Electron Density Support for Individual Atoms and Molecular Fragments in X-ray Structures

inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00418openalex-snapshot

Predictive Power of Different Types of Experimental Restraints in Small Molecule Docking: A Review

inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00650openalex-snapshot

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

inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00312openalex-snapshot

Evaluation of AutoDock and AutoDock Vina on the CASF-2013 Benchmark

inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00545openalex-snapshot

Comparative Assessment of Scoring Functions: The CASF-2016 Update

inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00582openalex-snapshot

Converging a Knowledge-Based Scoring Function: DrugScore2018

inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00214openalex-snapshot

Revisiting the Relationship Between Correlation Coefficient, Confidence Level, and Sample Size

inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00346openalex-snapshot

Comparative Assessment of Seven Docking Programs on a Nonredundant Metalloprotein Subset of the PDBbind Refined

inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00356openalex-snapshot

Random Forest Refinement of Pairwise Potentials for Protein–Ligand Decoy Detection

inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00403openalex-snapshot

Predicting the Affinity of Peptides to Major Histocompatibility Complex Class II by Scoring Molecular Dynamics Simulations

inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00645openalex-snapshot

Incorporating Explicit Water Molecules and Ligand Conformation Stability in Machine-Learning Scoring Functions

inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00714openalex-snapshot

Tapping on the Black Box: How Is the Scoring Power of a Machine-Learning Scoring Function Dependent on the Training Set?

inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00927openalex-snapshot

Combining Docking Pose Rank and Structure with Deep Learning Improves Protein–Ligand Binding Mode Prediction over a Baseline Docking Approach

inferred← citeshttps://doi.org/10.1021/acs.jcim.9b01212openalex-snapshot

Predicting Binding from Screening Assays with Transformer Network Embeddings

inferred← citeshttps://doi.org/10.1021/acs.jctc.5c00074openalex-snapshot

Persistent Directed Flag Laplacian (PDFL)-Based Machine Learning for Protein–Ligand Binding Affinity Prediction

inferred← citeshttps://doi.org/10.1021/acs.jmedchem.8b00760openalex-snapshot

Polypharmacology by Design: A Medicinal Chemist’s Perspective on Multitargeting Compounds

inferred← citeshttps://doi.org/10.1021/acsomega.2c02822openalex-snapshot

Machine-Learning- and Knowledge-Based Scoring Functions Incorporating Ligand and Protein Fingerprints

inferred← citeshttps://doi.org/10.1021/acsomega.7b00503openalex-snapshot

Superior Performance of the SQM/COSMO Scoring Functions in Native Pose Recognition of Diverse Protein–Ligand Complexes in Cognate Docking

inferred← citeshttps://doi.org/10.1021/acsomega.7b01194openalex-snapshot

A Diverse Benchmark Based on 3D Matched Molecular Pairs for Validating Scoring Functions

inferred← citeshttps://doi.org/10.1021/ci500081mopenalex-snapshot

Comparative Assessment of Scoring Functions on an Updated Benchmark: 2. Evaluation Methods and General Results

inferred← citeshttps://doi.org/10.1021/ci5003735openalex-snapshot

Improving Docking Results via Reranking of Ensembles of Ligand Poses in Multiple X-ray Protein Conformations with MM-GBSA

inferred← citeshttps://doi.org/10.1021/ci500406kopenalex-snapshot

Beware of Machine Learning-Based Scoring Functions—On the Danger of Developing Black Boxes

inferred← citeshttps://doi.org/10.1021/ci500731aopenalex-snapshot

Classification of Current Scoring Functions

inferred← citeshttps://doi.org/10.1021/jacs.4c04670openalex-snapshot

When Do Quantum Mechanical Descriptors Help Graph Neural Networks to Predict Chemical Properties?

inferred← citeshttps://doi.org/10.1021/jacs.6b02682openalex-snapshot

Interaction Entropy: A New Paradigm for Highly Efficient and Reliable Computation of Protein–Ligand Binding Free Energy

inferred← citeshttps://doi.org/10.1038/nprot.2017.114openalex-snapshot

Assessing protein–ligand interaction scoring functions with the CASF-2013 benchmark

inferred← citeshttps://doi.org/10.1038/s41597-024-03997-4openalex-snapshot

PPB-Affinity: Protein-Protein Binding Affinity dataset for AI-based protein drug discovery

inferred← citeshttps://doi.org/10.1038/s41598-021-82410-1openalex-snapshot

New machine learning and physics-based scoring functions for drug discovery

inferred← citeshttps://doi.org/10.1038/srep40053openalex-snapshot

Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme

inferred← citeshttps://doi.org/10.1039/c6cp01555gopenalex-snapshot

Comprehensive evaluation of ten docking programs on a diverse set of protein–ligand complexes: the prediction accuracy of sampling power and scoring power

inferred← citeshttps://doi.org/10.1039/d2cp04671gopenalex-snapshot

Hierarchical analysis of the target-based scoring function modification for the example of selected class A GPCRs

inferred← citeshttps://doi.org/10.1039/d3ra08650jopenalex-snapshot

Exploring protein–ligand binding affinity prediction with electron density-based geometric deep learning

inferred← citeshttps://doi.org/10.1039/d4dd00357hopenalex-snapshot

A workflow to create a high-quality protein–ligand binding dataset for training, validation, and prediction tasks

inferred← citeshttps://doi.org/10.1039/d4sc01029aopenalex-snapshot

A physics-aware neural network for protein–ligand interactions with quantum chemical accuracy

inferred← citeshttps://doi.org/10.1039/d5dd00317bopenalex-snapshot

MSIGN: A deep learning framework based on multi-scale interaction graph neural networks for predicting binding of synthetic cannabinoids to receptors

inferred← citeshttps://doi.org/10.1080/17460441.2021.1858793openalex-snapshot

The latest automated docking technologies for novel drug discovery

inferred← citeshttps://doi.org/10.1080/17460441.2021.1979514openalex-snapshot

Guided structure-based ligand identification and design via artificial intelligence modeling

inferred← citeshttps://doi.org/10.1080/17568919.2024.2419350openalex-snapshot

Machine learning-based prediction of bioactivity in HIV-1 protease: insights from electron density analysis

inferred← citeshttps://doi.org/10.1093/bib/bbaa070openalex-snapshot

Beware of the generic machine learning-based scoring functions in structure-based virtual screening

inferred← citeshttps://doi.org/10.1093/bib/bbab231openalex-snapshot

A comprehensive comparative assessment of 3D molecular similarity tools in ligand-based virtual screening

inferred← citeshttps://doi.org/10.1093/bib/bbag421openalex-snapshot

Structure-aware artificial intelligence for next-generation drug discovery: from protein–ligand modeling to generative biomolecular design

inferred← citeshttps://doi.org/10.1093/bib/bbz143openalex-snapshot

Comprehensive evaluation of the MM-GBSA method on bromodomain-inhibitor sets

inferred← citeshttps://doi.org/10.1093/bib/bbz173openalex-snapshot

Can machine learning consistently improve the scoring power of classical scoring functions? Insights into the role of machine learning in scoring functions

inferred← citeshttps://doi.org/10.1093/bioadv/vbad155openalex-snapshot

Multi-shelled ECIF: improved extended connectivity interaction features for accurate binding affinity prediction

inferred← citeshttps://doi.org/10.1093/bioinformatics/btaa982openalex-snapshot

Extended connectivity interaction features: improving binding affinity prediction through chemical description

inferred← citeshttps://doi.org/10.1093/bioinformatics/btad502openalex-snapshot

Protein–ligand binding affinity prediction exploiting sequence constituent homology

inferred← citeshttps://doi.org/10.1093/bioinformatics/btu626openalex-snapshot

PDB-wide collection of binding data: current status of the PDBbind database

inferred← citeshttps://doi.org/10.1093/bioinformatics/btz665openalex-snapshot

Learning from the ligand: using ligand-based features to improve binding affinity prediction

inferred← citeshttps://doi.org/10.1093/database/baaf061openalex-snapshot

The impact of curation errors in the PDBBind Database on machine learning predictions of protein–protein binding affinity

inferred← citeshttps://doi.org/10.1093/nar/gku1088openalex-snapshot

Recent improvements to Binding MOAD: a resource for protein–ligand binding affinities and structures

inferred← citeshttps://doi.org/10.1093/nar/gkw390openalex-snapshot

CSM-lig: a web server for assessing and comparing protein–small molecule affinities

inferred← citeshttps://doi.org/10.1098/rsos.211745openalex-snapshot

A simple spatial extension to the extended connectivity interaction features for binding affinity prediction

inferred← citeshttps://doi.org/10.1101/2024.02.29.582674openalex-snapshot

The widely used cymoxanil fungicide impairs respiration in Saccharomyces cerevisiae via cytochrome c oxidase inhibition

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DeepAtom: A Framework for Protein-Ligand Binding Affinity Prediction

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DPLA: prediction of protein-ligand binding affinity by integrating multi-level information

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Machine Learning for Drug Discovery: Predicting Drug-Protein Binding Affinities using Graph Convolutional Networks

inferred← citeshttps://doi.org/10.1109/jac-ecc61002.2023.10479635openalex-snapshot

Deep Learning is Competing with Random Forest in Computational Docking

inferred← citeshttps://doi.org/10.1109/tcbb.2020.3046945openalex-snapshot

Deep Learning in Drug Design: Protein-Ligand Binding Affinity Prediction

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A New, Improved Hybrid Scoring Function for Molecular Docking and Scoring Based on AutoDock and AutoDock Vina

inferred← citeshttps://doi.org/10.1111/cbdd.13764openalex-snapshot

GWOVina: A grey wolf optimization approach to rigid and flexible receptor docking

inferred← citeshttps://doi.org/10.1134/s0006297922010059openalex-snapshot

Computer simulation of the Receptor–Ligand Interactions of Mannose Receptor CD206 in Comparison with the Lectin Concanavalin A Model

inferred← citeshttps://doi.org/10.1142/s0219720021500037openalex-snapshot

An evaluation of combined strategies for improving the performance of molecular docking

inferred← citeshttps://doi.org/10.1142/s2737416524500613openalex-snapshot

Mayer-Homology Learning Prediction of Protein-Ligand Binding Affinities

inferred← citeshttps://doi.org/10.1177/1094342017697471openalex-snapshot

METADOCK: A parallel metaheuristic schema for virtual screening methods

inferred← citeshttps://doi.org/10.1186/s12859-017-1750-5openalex-snapshot

Enhance the performance of current scoring functions with the aid of 3D protein-ligand interaction fingerprints

inferred← citeshttps://doi.org/10.1186/s12859-021-04466-0openalex-snapshot

Binding affinity prediction for protein–ligand complex using deep attention mechanism based on intermolecular interactions

inferred← citeshttps://doi.org/10.1186/s13321-018-0320-9openalex-snapshot

Chaos-embedded particle swarm optimization approach for protein-ligand docking and virtual screening

inferred← citeshttps://doi.org/10.1186/s13321-019-0373-4openalex-snapshot

DLIGAND2: an improved knowledge-based energy function for protein–ligand interactions using the distance-scaled, finite, ideal-gas reference state

inferred← citeshttps://doi.org/10.1186/s13321-019-0394-zopenalex-snapshot

ACID: a free tool for drug repurposing using consensus inverse docking strategy

inferred← citeshttps://doi.org/10.1186/s13321-021-00486-3openalex-snapshot

ASFP (Artificial Intelligence based Scoring Function Platform): a web server for the development of customized scoring functions

inferred← citeshttps://doi.org/10.1186/s13321-021-00536-wopenalex-snapshot

Learning protein-ligand binding affinity with atomic environment vectors

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Comparative evaluation of methods for the prediction of protein–ligand binding sites

inferred← citeshttps://doi.org/10.1186/s13321-026-01224-3openalex-snapshot

PL-PatchSurfer3: improved structure-based virtual screening for structure variation using 3D Zernike descriptors

inferred← citeshttps://doi.org/10.1248/yakushi.19-00006openalex-snapshot

Identifying Inhibitors of USP7-HDM2 Protein-Protein Interaction (PPI) by the in Silico Fragment-mapping Method

inferred← citeshttps://doi.org/10.13005/bpj/3298openalex-snapshot

Computational Investigation of Pinocembrin as a Multi-Target Ligand: A Molecular Docking Study

inferred← citeshttps://doi.org/10.13140/rg.2.2.30339.73765openalex-snapshot

ATOM3D: Tasks On Molecules in Three Dimensions

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Development of a high-quality benchmark for scoring function assessment

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GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing

inferred← citeshttps://doi.org/10.1371/journal.pone.0249404openalex-snapshot

Development of a graph convolutional neural network model for efficient prediction of protein-ligand binding affinities

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CBSF: A New Empirical Scoring Function for Docking Parameterized by Weights of Neural Network

inferred← citeshttps://doi.org/10.21203/rs.3.rs-1454132/v1openalex-snapshot

Accurate Protein-Ligand Complex Structure Prediction using Geometric Deep Learning

inferred← citeshttps://doi.org/10.2147/idr.s407891openalex-snapshot

Synthesis, Anti-Bacterial and Molecular Docking Studies of Arylated Butyl 2-Bromoisonicotinate Against Clinical Isolates of ESBL-Producing Escherichia coli ST405 and Methicillin-Resistant Staphylococcus aureus

inferred← citeshttps://doi.org/10.2174/0115672050386924250930184405openalex-snapshot

Innovative Approaches in Molecular Docking for the Discovery of Novel Inhibitors Against Alzheimer's Disease

inferred← citeshttps://doi.org/10.2174/1874104501913010040openalex-snapshot

Evaluation of Scoring Function Performance on DNA-ligand Complexes

inferred← citeshttps://doi.org/10.26434/chemrxiv.13469625openalex-snapshot

Learning Protein-Ligand Binding Affinity with Atomic Environment Vectors

inferred← citeshttps://doi.org/10.31857/s0320972522010055openalex-snapshot

Компьютерное моделирование лиганд-рецепторных взаимодействий маннозного рецептора CD206 в сравнении с модельным лектином конканавалином А

inferred← citeshttps://doi.org/10.32469/10355/90175openalex-snapshot

Theoretical and computational modeling of rna-ligand interactions

inferred← citeshttps://doi.org/10.3389/fbinf.2022.1065703openalex-snapshot

Machine learning methods for protein-protein binding affinity prediction in protein design

inferred← citeshttps://doi.org/10.3389/fbinf.2022.885983openalex-snapshot

Scoring Functions for Protein-Ligand Binding Affinity Prediction Using Structure-based Deep Learning: A Review

inferred← citeshttps://doi.org/10.3389/fchem.2021.753002openalex-snapshot

OnionNet-2: A Convolutional Neural Network Model for Predicting Protein-Ligand Binding Affinity Based on Residue-Atom Contacting Shells

inferred← citeshttps://doi.org/10.3389/fgene.2020.607824openalex-snapshot

SE-OnionNet: A Convolution Neural Network for Protein–Ligand Binding Affinity Prediction

inferred← citeshttps://doi.org/10.3389/fphar.2020.00069openalex-snapshot

Predicting or Pretending: Artificial Intelligence for Protein-Ligand Interactions Lack of Sufficiently Large and Unbiased Datasets

inferred← citeshttps://doi.org/10.3390/books978-3-03897-615-8openalex-snapshot

Molecular Modeling in Drug Design

inferred← citeshttps://doi.org/10.3390/ijms18010137openalex-snapshot

A Thoroughly Validated Virtual Screening Strategy for Discovery of Novel HDAC3 Inhibitors

inferred← citeshttps://doi.org/10.3390/ijms22084023openalex-snapshot

A Cascade Graph Convolutional Network for Predicting Protein–Ligand Binding Affinity

inferred← citeshttps://doi.org/10.3390/ijms23031620openalex-snapshot

Virtual Combinatorial Chemistry and Pharmacological Screening: A Short Guide to Drug Design

inferred← citeshttps://doi.org/10.3390/ijms242216120openalex-snapshot

The Impact of Data on Structure-Based Binding Affinity Predictions Using Deep Neural Networks

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