# | Title | Journal | Year | Citations |
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1 | Extended-Connectivity Fingerprints | Journal of Chemical Information and Modeling | 2010 | 4,447 |
2 | SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules | Journal of Chemical Information and Modeling | 1988 | 4,217 |
3 | LigPlot+: Multiple Ligand–Protein Interaction Diagrams for Drug Discovery | Journal of Chemical Information and Modeling | 2011 | 4,148 |
4 | ZINC − A Free Database of Commercially Available Compounds for Virtual Screening | Journal of Chemical Information and Modeling | 2005 | 3,366 |
5 | g_mmpbsa—A GROMACS Tool for High-Throughput MM-PBSA Calculations | Journal of Chemical Information and Modeling | 2014 | 3,304 |
6 | Basis Set Exchange: A Community Database for Computational Sciences | Journal of Chemical Information and Modeling | 2007 | 2,685 |
7 | ZINC 15 – Ligand Discovery for Everyone | Journal of Chemical Information and Modeling | 2015 | 2,194 |
8 | Assessing the Performance of the MM/PBSA and MM/GBSA Methods. 1. The Accuracy of Binding Free Energy Calculations Based on Molecular Dynamics Simulations | Journal of Chemical Information and Modeling | 2011 | 2,005 |
9 | ZINC: A Free Tool to Discover Chemistry for Biology | Journal of Chemical Information and Modeling | 2012 | 1,985 |
10 | LigandScout: 3-D Pharmacophores Derived from Protein-Bound Ligands and Their Use as Virtual Screening Filters | Journal of Chemical Information and Modeling | 2005 | 1,576 |
11 | AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings | Journal of Chemical Information and Modeling | 2021 | 1,481 |
12 | admetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties | Journal of Chemical Information and Modeling | 2012 | 1,439 |
13 | Automation of the CHARMM General Force Field (CGenFF) I: Bond Perception and Atom Typing | Journal of Chemical Information and Modeling | 2012 | 1,409 |
14 | Improved Docking of Polypeptides with Glide | Journal of Chemical Information and Modeling | 2013 | 1,407 |
15 | Identifying and Characterizing Binding Sites and Assessing Druggability | Journal of Chemical Information and Modeling | 2009 | 1,308 |
16 | Conformer Generation with OMEGA: Algorithm and Validation Using High Quality Structures from the Protein Databank and Cambridge Structural Database | Journal of Chemical Information and Modeling | 2010 | 1,302 |
17 | Automation of the CHARMM General Force Field (CGenFF) II: Assignment of Bonded Parameters and Partial Atomic Charges | Journal of Chemical Information and Modeling | 2012 | 1,278 |
18 | New Basis Set Exchange: An Open, Up-to-Date Resource for the Molecular Sciences Community | Journal of Chemical Information and Modeling | 2019 | 1,244 |
19 | DataWarrior: An Open-Source Program For Chemistry Aware Data Visualization And Analysis | Journal of Chemical Information and Modeling | 2015 | 1,111 |
20 | Empirical Scoring Functions for Advanced Protein−Ligand Docking with PLANTS | Journal of Chemical Information and Modeling | 2009 | 1,033 |
21 | Atomic physicochemical parameters for three dimensional structure directed quantitative structure-activity relationships. 4. Additional parameters for hydrophobic and dispersive interactions and their application for an automated superposition of certain naturally occurring nucleoside antibiotics | Journal of Chemical Information and Modeling | 1989 | 1,029 |
22 | TRAVIS - A Free Analyzer and Visualizer for Monte Carlo and Molecular Dynamics Trajectories | Journal of Chemical Information and Modeling | 2011 | 930 |
23 | Enumeration of 166 Billion Organic Small Molecules in the Chemical Universe Database GDB-17 | Journal of Chemical Information and Modeling | 2012 | 871 |
24 | Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships | Journal of Chemical Information and Modeling | 2015 | 840 |
25 | Analyzing Learned Molecular Representations for Property Prediction | Journal of Chemical Information and Modeling | 2019 | 773 |
26 | y-Randomization and Its Variants in QSPR/QSAR | Journal of Chemical Information and Modeling | 2007 | 706 |
27 | Lessons Learned in Empirical Scoring with smina from the CSAR 2011 Benchmarking Exercise | Journal of Chemical Information and Modeling | 2013 | 675 |
28 | Evaluating Virtual Screening Methods: Good and Bad Metrics for the “Early Recognition” Problem | Journal of Chemical Information and Modeling | 2007 | 667 |
29 | Trust, But Verify: On the Importance of Chemical Structure Curation in Cheminformatics and QSAR Modeling Research | Journal of Chemical Information and Modeling | 2010 | 611 |
30 | FRED Pose Prediction and Virtual Screening Accuracy | Journal of Chemical Information and Modeling | 2011 | 606 |
31 | Computation of Octanol−Water Partition Coefficients by Guiding an Additive Model with Knowledge | Journal of Chemical Information and Modeling | 2007 | 601 |
32 | On Outliers and Activity CliffsWhy QSAR Often Disappoints | Journal of Chemical Information and Modeling | 2006 | 597 |
33 | Real External Predictivity of QSAR Models: How To Evaluate It? Comparison of Different Validation Criteria and Proposal of Using the Concordance Correlation Coefficient | Journal of Chemical Information and Modeling | 2011 | 589 |
34 | KDEEP: Protein–Ligand Absolute Binding Affinity Prediction via 3D-Convolutional Neural Networks | Journal of Chemical Information and Modeling | 2018 | 586 |
35 | Protein–Ligand Scoring with Convolutional Neural Networks | Journal of Chemical Information and Modeling | 2017 | 578 |
36 | iLOGP: A Simple, Robust, and Efficient Description of n-Octanol/Water Partition Coefficient for Drug Design Using the GB/SA Approach | Journal of Chemical Information and Modeling | 2014 | 560 |
37 | Omicron Variant (B.1.1.529): Infectivity, Vaccine Breakthrough, and Antibody Resistance | Journal of Chemical Information and Modeling | 2022 | 507 |
38 | Beware of R2: Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models | Journal of Chemical Information and Modeling | 2015 | 495 |
39 | Comments on the Definition of the Q2 Parameter for QSAR Validation | Journal of Chemical Information and Modeling | 2009 | 483 |
40 | External Validation and Prediction Employing the Predictive Squared Correlation Coefficient — Test Set Activity Mean vs Training Set Activity Mean | Journal of Chemical Information and Modeling | 2008 | 461 |
41 | Relative Binding Free Energy Calculations in Drug Discovery: Recent Advances and Practical Considerations | Journal of Chemical Information and Modeling | 2017 | 458 |
42 | Comparative Assessment of Scoring Functions on a Diverse Test Set | Journal of Chemical Information and Modeling | 2009 | 444 |
43 | MCPB.py: A Python Based Metal Center Parameter Builder | Journal of Chemical Information and Modeling | 2016 | 416 |
44 | A Common Reference Framework for Analyzing/Comparing Proteins and Ligands. Fingerprints for Ligands And Proteins (FLAP): Theory and Application | Journal of Chemical Information and Modeling | 2007 | 410 |
45 | Real External Predictivity of QSAR Models. Part 2. New Intercomparable Thresholds for Different Validation Criteria and the Need for Scatter Plot Inspection | Journal of Chemical Information and Modeling | 2012 | 408 |
46 | Deep Architectures and Deep Learning in Chemoinformatics: The Prediction of Aqueous Solubility for Drug-Like Molecules | Journal of Chemical Information and Modeling | 2013 | 408 |
47 | Managing the Computational Chemistry Big Data Problem: The ioChem-BD Platform | Journal of Chemical Information and Modeling | 2015 | 403 |
48 | Comparative Studies on Some Metrics for External Validation of QSPR Models | Journal of Chemical Information and Modeling | 2012 | 399 |
49 | Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition | Journal of Chemical Information and Modeling | 2018 | 398 |
50 | Comparison of Several Molecular Docking Programs: Pose Prediction and Virtual Screening Accuracy | Journal of Chemical Information and Modeling | 2009 | 387 |