| 1 | The Need for Continuing Blinded Pose- and Activity Prediction Benchmarks | 4.9 | 0 | Citations (PDF) |
| 2 | IMERGE-FEP: Improving Relative Free Energy Calculation Convergence with Chemical Intermediates | 2.9 | 0 | Citations (PDF) |
| 3 | A Fast, Convenient, Polarizable Electrostatic Model for Molecular Dynamics | 5.5 | 2 | Citations (PDF) |
| 4 | The SAMPL9 host–guest blind challenge: an overview of binding free energy predictive accuracy | 2.8 | 5 | Citations (PDF) |
| 5 | Impact of protein conformations on binding free energy calculations in the beta‐secretase 1 system | 4.9 | 2 | Citations (PDF) |
| 6 | Building Block-Centric Approach to DNA-Encoded Library Design | 4.9 | 1 | Citations (PDF) |
| 7 | Machine-learned molecular mechanics force fields from large-scale quantum chemical data | 7.5 | 7 | Citations (PDF) |
| 8 | Current State of Open Source Force Fields in Protein–Ligand Binding Affinity Predictions | 4.9 | 10 | Citations (PDF) |
| 9 | The Open Force Field Initiative: Open Software and Open Science for Molecular Modeling | 2.9 | 5 | Citations (PDF) |
| 10 | Benchmarking Quantum Mechanical Levels of Theory for Valence Parametrization in Force Fields | 2.9 | 1 | Citations (PDF) |
| 11 | Konnektor: A Framework for Using Graph Theory to Plan Networks for Free Energy Calculations | 4.9 | 0 | Citations (PDF) |
| 12 | Kinetics-Based State Definitions for Discrete Binding Conformations of T4 L99A in MD via Markov State Modeling | 4.9 | 0 | Citations (PDF) |
| 13 | Leveraging a Separation of States Method for Relative Binding Free Energy Calculations in Systems with Trapped Waters | 5.5 | 1 | Citations (PDF) |
| 14 | Molecular-dynamics simulation methods for macromolecular crystallography | 3.4 | 12 | Citations (PDF) |
| 15 | Enhanced Grand Canonical Sampling of Occluded Water Sites Using Nonequilibrium Candidate Monte Carlo | 5.5 | 14 | Citations (PDF) |
| 16 | To Design Scalable Free Energy Perturbation Networks, Optimal Is Not Enough | 4.9 | 11 | Citations (PDF) |
| 17 | Development and Benchmarking of Open Force Field 2.0.0: The Sage Small Molecule Force Field | 5.5 | 67 | Citations (PDF) |
| 18 | A transferable double exponential potential for condensed phase simulations of small molecules | 5.5 | 8 | Citations (PDF) |
| 19 | Broadening the Scope of Binding Free Energy Calculations Using a Separated Topologies Approach | 5.5 | 17 | Citations (PDF) |
| 20 | Building Block-Based Binding Predictions for DNA-Encoded Libraries | 4.9 | 7 | Citations (PDF) |
| 21 | Enhancing Sampling of Water Rehydration on Ligand Binding: A Comparison of Techniques | 5.5 | 29 | Citations (PDF) |
| 22 | Pre-Exascale Computing of Protein–Ligand Binding Free Energies with Open Source Software for Drug Design | 4.9 | 35 | Citations (PDF) |
| 23 | SAMPL7 protein-ligand challenge: A community-wide evaluation of computational methods against fragment screening and pose-prediction | 3.1 | 12 | Citations (PDF) |
| 24 | Improving Force Field Accuracy by Training against Condensed-Phase Mixture Properties | 5.5 | 12 | Citations (PDF) |
| 25 | Open Force Field Evaluator: An Automated, Efficient, and Scalable Framework for the Estimation of Physical Properties from Molecular Simulation | 5.5 | 25 | Citations (PDF) |
| 26 | Best Practices for Constructing, Preparing, and Evaluating Protein-Ligand Binding Affinity Benchmarks [Article v1.0] | 10.9 | 41 | Citations (PDF) |
| 27 | Absolute Binding Free Energy Calculations for Buried Water Molecules | 5.5 | 4 | Citations (PDF) |
| 28 | An overview of the SAMPL8 host–guest binding challenge | 3.1 | 34 | Citations (PDF) |
| 29 | Reversibly Sampling Conformations and Binding Modes Using Molecular Darting | 5.5 | 3 | Citations (PDF) |
| 30 | Structural and Molecular Dynamics of <i>Mycobacterium tuberculosis</i> Malic Enzyme, a Potential Anti-TB Drug Target | 3.8 | 5 | Citations (PDF) |
| 31 | Improving small molecule force fields by identifying and characterizing small molecules with inconsistent parameters | 3.1 | 15 | Citations (PDF) |
| 32 | Overview of the SAMPL6 pKa challenge: evaluating small molecule microscopic and macroscopic pKa predictions | 3.1 | 32 | Citations (PDF) |
| 33 | A Benchmark of Electrostatic Method Performance in Relative Binding Free Energy Calculations | 4.9 | 12 | Citations (PDF) |
| 34 | Challenges Encountered Applying Equilibrium and Nonequilibrium Binding Free Energy Calculations | 2.9 | 37 | Citations (PDF) |
| 35 | Evaluation of log P, pKa, and log D predictions from the SAMPL7 blind challenge | 3.1 | 56 | Citations (PDF) |
| 36 | Development and Benchmarking of Open Force Field v1.0.0—the Parsley Small-Molecule Force Field | 5.5 | 98 | Citations (PDF) |
| 37 | Temperature artifacts in protein structures bias ligand-binding predictions | 7.5 | 25 | Citations (PDF) |
| 38 | SAMPL7 Host–Guest Challenge Overview: assessing the reliability of polarizable and non-polarizable methods for binding free energy calculations | 3.1 | 55 | Citations (PDF) |
| 39 | Automated high throughput pKa and distribution coefficient measurements of pharmaceutical compounds for the SAMPL8 blind prediction challenge | 3.1 | 11 | Citations (PDF) |
| 40 | Enhancing Paraoxon Binding to Organophosphorus Hydrolase Active Site | 4.5 | 6 | Citations (PDF) |
| 41 | Optimal designs for pairwise calculation: An application to free energy perturbation in minimizing prediction variability | 4.9 | 29 | Citations (PDF) |
| 42 | Kinetics and free energy of ligand dissociation using weighted ensemble milestoning | 3.0 | 10 | Citations (PDF) |
| 43 | Insights on small molecule binding to the Hv1 proton channel from free energy calculations with molecular dynamics simulations | 3.7 | 10 | Citations (PDF) |
| 44 | Fragment Pose Prediction Using Non-equilibrium Candidate Monte Carlo and Molecular Dynamics Simulations | 5.5 | 9 | Citations (PDF) |
| 45 | Assessing the accuracy of octanol–water partition coefficient predictions in the SAMPL6 Part II log P Challenge | 3.1 | 45 | Citations (PDF) |
| 46 | Sampling Conformational Changes of Bound Ligands Using Nonequilibrium Candidate Monte Carlo and Molecular Dynamics | 5.5 | 19 | Citations (PDF) |
| 47 | The SAMPL6 SAMPLing challenge: assessing the reliability and efficiency of binding free energy calculations | 3.1 | 91 | Citations (PDF) |
| 48 | Non-bonded force field model with advanced restrained electrostatic potential charges (RESP2) | 5.8 | 163 | Citations (PDF) |
| 49 | Enhancing water sampling of buried binding sites using nonequilibrium candidate Monte Carlo | 3.1 | 21 | Citations (PDF) |
| 50 | An optimized chemical-genetic method for cell-specific metabolic labeling of RNA | 14.5 | 45 | Citations (PDF) |
| 51 | Benchmark assessment of molecular geometries and energies from small molecule force fields | 0.6 | 33 | Citations (PDF) |
| 52 | Best Practices for Alchemical Free Energy Calculations [Article v1.0] | 10.9 | 158 | Citations (PDF) |
| 53 | Binding Thermodynamics of Host–Guest Systems with SMIRNOFF99Frosst 1.0.5 from the Open Force Field Initiative | 5.5 | 24 | Citations (PDF) |
| 54 | Comparison of affinity ranking using AutoDock-GPU and MM-GBSA scores for BACE-1 inhibitors in the D3R Grand Challenge 4 | 3.1 | 55 | Citations (PDF) |
| 55 | Structure of a <i>Mycobacterium tuberculosis</i> Heme-Degrading Protein, MhuD, Variant in Complex with Its Product | 2.9 | 5 | Citations (PDF) |
| 56 | Enhancing Side Chain Rotamer Sampling Using Nonequilibrium Candidate Monte Carlo | 5.5 | 23 | Citations (PDF) |
| 57 | Binding Modes and Metabolism of Caffeine | 3.9 | 20 | Citations (PDF) |
| 58 | Biomolecular Solvation Structure Revealed by Molecular Dynamics Simulations | 15.7 | 30 | Citations (PDF) |
| 59 | Infinite Dilution Activity Coefficients as Constraints for Force Field Parametrization and Method Development | 5.5 | 14 | Citations (PDF) |
| 60 | Assessing the Conformational Equilibrium of Carboxylic Acid via Quantum Mechanical and Molecular Dynamics Studies on Acetic Acid | 4.9 | 16 | Citations (PDF) |
| 61 | Liquid-like and rigid-body motions in molecular-dynamics simulations of a crystalline protein | 2.3 | 12 | Citations (PDF) |
| 62 | Toward Learned Chemical Perception of Force Field Typing Rules | 5.5 | 30 | Citations (PDF) |
| 63 | Octanol–water partition coefficient measurements for the SAMPL6 blind prediction challenge | 3.1 | 42 | Citations (PDF) |
| 64 | D3R Grand Challenge 4: ligand similarity and MM-GBSA-based pose prediction and affinity ranking for BACE-1 inhibitors | 3.1 | 13 | Citations (PDF) |
| 65 | Challenges in the use of atomistic simulations to predict solubilities of drug-like molecules | 0.6 | 6 | Citations (PDF) |
| 66 | Why We Need the Living Journal of Computational Molecular Science | 10.9 | 2 | Citations (PDF) |
| 67 | Best Practices for Foundations in Molecular Simulations [Article v1.0] | 10.9 | 130 | Citations (PDF) |
| 68 | Best Practices for Alchemical Free Energy Calculations [Article v1.0] | 10.9 | 4 | Citations (PDF) |
| 69 | Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes via Nonequilibrium Candidate Monte Carlo | 2.9 | 56 | Citations (PDF) |
| 70 | Atomic Radius and Charge Parameter Uncertainty in Biomolecular Solvation Energy Calculations | 5.5 | 14 | Citations (PDF) |
| 71 | Refining Protein Penetration into the Lipid Bilayer Using Fluorescence Quenching and Molecular Dynamics Simulations: The Case of Diphtheria Toxin Translocation Domain | 2.6 | 17 | Citations (PDF) |
| 72 | pKa measurements for the SAMPL6 prediction challenge for a set of kinase inhibitor-like fragments | 3.1 | 39 | Citations (PDF) |
| 73 | Overview of the SAMPL6 host–guest binding affinity prediction challenge | 3.1 | 113 | Citations (PDF) |
| 74 | Reproducibility of Free Energy Calculations across Different Molecular Simulation Software Packages | 5.5 | 69 | Citations (PDF) |
| 75 | Escaping Atom Types in Force Fields Using Direct Chemical Perception | 5.5 | 116 | Citations (PDF) |
| 76 | SAMPL6 challenge results from $$pK_a$$ predictions based on a general Gaussian process model | 3.1 | 20 | Citations (PDF) |
| 77 | Hydration Free Energies in the FreeSolv Database Calculated with Polarized Iterative Hirshfeld Charges | 4.9 | 37 | Citations (PDF) |
| 78 | Challenges in the use of atomistic simulations to predict solubilities of drug-like molecules | 0.6 | 6 | Citations (PDF) |
| 79 | Predicting Binding Free Energies: Frontiers and Benchmarks | 13.3 | 274 | Citations (PDF) |
| 80 | Approaches for Calculating Solvation Free Energies and Enthalpies Demonstrated with an Update of the FreeSolv Database | 2.2 | 182 | Citations (PDF) |
| 81 | Bayesian Model Averaging for Ensemble-Based Estimates of Solvation-Free Energies | 2.9 | 7 | Citations (PDF) |
| 82 | Collaborative routes to clarifying the murky waters of aqueous supramolecular chemistry | 13.9 | 149 | Citations (PDF) |
| 83 | A Critical Review of Validation, Blind Testing, and Real- World Use of Alchemical Protein-Ligand Binding Free Energy Calculations | 2.7 | 85 | Citations (PDF) |
| 84 | Blind prediction of cyclohexane–water distribution coefficients from the SAMPL5 challenge | 3.1 | 93 | Citations (PDF) |
| 85 | Measuring experimental cyclohexane-water distribution coefficients for the SAMPL5 challenge | 3.1 | 39 | Citations (PDF) |
| 86 | Sensitivity in Binding Free Energies Due to Protein Reorganization | 5.5 | 64 | Citations (PDF) |
| 87 | Calculating Partition Coefficients of Small Molecules in Octanol/Water and Cyclohexane/Water | 5.5 | 143 | Citations (PDF) |
| 88 | Multiple binding modes of ibuprofen in human serum albumin identified by absolute binding free energy calculations | 2.8 | 80 | Citations (PDF) |
| 89 | Using MD Simulations To Calculate How Solvents Modulate Solubility | 5.5 | 39 | Citations (PDF) |
| 90 | Overview of the SAMPL5 host–guest challenge: Are we doing better? | 3.1 | 138 | Citations (PDF) |
| 91 | Lessons learned from comparing molecular dynamics engines on the SAMPL5 dataset | 3.1 | 214 | Citations (PDF) |
| 92 | Predicting the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol mixtures via molecular simulation | 3.0 | 38 | Citations (PDF) |
| 93 | Accurate and Reliable Prediction of Relative Ligand Binding Potency in Prospective Drug Discovery by Way of a Modern Free-Energy Calculation Protocol and Force Field | 15.7 | 937 | Citations (PDF) |
| 94 | Is Ring Breaking Feasible in Relative Binding Free Energy Calculations? | 4.9 | 40 | Citations (PDF) |
| 95 | Guidelines for the analysis of free energy calculations | 3.1 | 386 | Citations (PDF) |
| 96 | A Python tool to set up relative free energy calculations in GROMACS | 3.1 | 34 | Citations (PDF) |
| 97 | Interrogating HIV integrase for compounds that bind- a SAMPL challenge | 3.1 | 24 | Citations (PDF) |
| 98 | Box size effects are negligible for solvation free energies of neutral solutes | 3.1 | 19 | Citations (PDF) |
| 99 | Blind prediction of solvation free energies from the SAMPL4 challenge | 3.1 | 127 | Citations (PDF) |
| 100 | Blind prediction of HIV integrase binding from the SAMPL4 challenge | 3.1 | 48 | Citations (PDF) |
| 101 | The SAMPL4 host–guest blind prediction challenge: an overview | 3.1 | 155 | Citations (PDF) |
| 102 | FreeSolv: a database of experimental and calculated hydration free energies, with input files | 3.1 | 326 | Citations (PDF) |
| 103 | A Fixed-Charge Model for Alcohol Polarization in the Condensed Phase, and Its Role in Small Molecule Hydration | 2.9 | 55 | Citations (PDF) |
| 104 | Blind Prediction of Charged Ligand Binding Affinities in a Model Binding Site | 4.2 | 51 | Citations (PDF) |
| 105 | Lead optimization mapper: automating free energy calculations for lead optimization | 3.1 | 116 | Citations (PDF) |
| 106 | Calculating the binding free energies of charged species based on explicit-solvent simulations employing lattice-sum methods: An accurate correction scheme for electrostatic finite-size effects | 3.0 | 190 | Citations (PDF) |
| 107 | Separated topologies—A method for relative binding free energy calculations using orientational restraints | 3.0 | 30 | Citations (PDF) |
| 108 | Entropy-Enthalpy Compensation: Role and Ramifications in Biomolecular Ligand Recognition and Design | 13.3 | 412 | Citations (PDF) |
| 109 | An Introduction to Best Practices in Free Energy Calculations | 0.0 | 79 | Citations (PDF) |
| 110 | 3-Aryl-3-arylmethoxyazetidines. A new class of high affinity ligands for monoamine transporters | 2.1 | 7 | Citations (PDF) |
| 111 | Triazole–Dithiocarbamate Based Selective Lysine Specific Demethylase 1 (LSD1) Inactivators Inhibit Gastric Cancer Cell Growth, Invasion, and Migration | 6.9 | 199 | Citations (PDF) |
| 112 | Calculating the Sensitivity and Robustness of Binding Free Energy Calculations to Force Field Parameters | 5.5 | 27 | Citations (PDF) |
| 113 | Perspective: Alchemical free energy calculations for drug discovery | 3.0 | 183 | Citations (PDF) |
| 114 | Small Molecule Solvation Free Energy: Enhanced Conformational Sampling Using Expanded Ensemble Molecular Dynamics Simulation | 5.5 | 40 | Citations (PDF) |
| 115 | Alchemical free energy methods for drug discovery: progress and challenges | 7.1 | 471 | Citations (PDF) |
| 116 | Alchemical prediction of hydration free energies for SAMPL | 3.1 | 67 | Citations (PDF) |
| 117 | Predicting hydration free energies using all-atom molecular dynamics simulations and multiple starting conformations | 3.1 | 97 | Citations (PDF) |
| 118 | Synthesis and structure–activity studies of benzyl ester meperidine and normeperidine derivatives as selective serotonin transporter ligands | 2.7 | 2 | Citations (PDF) |
| 119 | Free-energy calculations in structure-based drug design 2010, , 61-86 | | 64 | Citations (PDF) |
| 120 | Synthesis and monoamine transporter affinity of 3α-arylmethoxy-3β-arylnortropanes | 2.1 | 5 | Citations (PDF) |
| 121 | Quantifying Correlations Between Allosteric Sites in Thermodynamic Ensembles | 5.5 | 187 | Citations (PDF) |
| 122 | Predictions of Hydration Free Energies from All-Atom Molecular Dynamics Simulations | 2.9 | 79 | Citations (PDF) |
| 123 | Predicting Ligand Binding Affinity with Alchemical Free Energy Methods in a Polar Model Binding Site | 4.2 | 150 | Citations (PDF) |
| 124 | Binding of Small-Molecule Ligands to Proteins: “What You See” Is Not Always “What You Get” | 3.9 | 470 | Citations (PDF) |
| 125 | Small Molecule Hydration Free Energies in Explicit Solvent: An Extensive Test of Fixed-Charge Atomistic Simulations | 5.5 | 298 | Citations (PDF) |
| 126 | Predicting Small-Molecule Solvation Free Energies: An Informal Blind Test for Computational Chemistry | 6.9 | 240 | Citations (PDF) |
| 127 | Treating Entropy and Conformational Changes in Implicit Solvent Simulations of Small Molecules | 2.9 | 104 | Citations (PDF) |
| 128 | Charge Asymmetries in Hydration of Polar Solutes | 2.9 | 93 | Citations (PDF) |
| 129 | Nonlinear scaling schemes for Lennard-Jones interactions in free energy calculations | 3.0 | 259 | Citations (PDF) |
| 130 | Predicting Absolute Ligand Binding Free Energies to a Simple Model Site | 4.2 | 255 | Citations (PDF) |
| 131 | A Mathematical Model of Glioblastoma Tumor Spheroid Invasion in a Three-Dimensional In Vitro Experiment | 0.4 | 197 | Citations (PDF) |
| 132 | Comparison of Charge Models for Fixed-Charge Force Fields: Small-Molecule Hydration Free Energies in Explicit Solvent | 2.9 | 234 | Citations (PDF) |
| 133 | Chapter 4 Alchemical Free Energy Calculations: Ready for Prime Time? | 0.0 | 170 | Citations (PDF) |
| 134 | Confine-and-Release Method: Obtaining Correct Binding Free Energies in the Presence of Protein Conformational Change | 5.5 | 160 | Citations (PDF) |
| 135 | On the use of orientational restraints and symmetry corrections in alchemical free energy calculations | 3.0 | 250 | Citations (PDF) |
| 136 | Modeling Amyloid β-Peptide Insertion into Lipid Bilayers | 0.4 | 47 | Citations (PDF) |
| 137 | Simulations of Oligomeric Intermediates in Prion Diseases | 0.4 | 9 | Citations (PDF) |
