Alexander D. MacKerell Jr.
Orcid: 0000-0001-8287-6804
According to our database1,
Alexander D. MacKerell Jr.
authored at least 66 papers
between 1988 and 2023.
Collaborative distances:
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Bibliography
2023
Non-β Lactam Inhibitors of the Serine β-Lactamase blaCTX-M15 in Drug-Resistant <i>Salmonella typhi</i>.
J. Chem. Inf. Model., November, 2023
Combining SILCS and Artificial Intelligence for High-Throughput Prediction of the Passive Permeability of Drug Molecules.
J. Chem. Inf. Model., September, 2023
GPU-specific algorithms for improved solute sampling in grand canonical Monte Carlo simulations.
J. Comput. Chem., 2023
2022
CHARMM-GUI Drude prepper for molecular dynamics simulation using the classical Drude polarizable force field.
J. Comput. Chem., 2022
2021
PLoS Comput. Biol., 2021
J. Chem. Inf. Model., 2021
2020
Assessing hERG1 Blockade from Bayesian Machine-Learning-Optimized Site Identification by Ligand Competitive Saturation Simulations.
J. Chem. Inf. Model., 2020
Improved Modeling of Cation-π and Anion-Ring Interactions Using the Drude Polarizable Empirical Force Field for Proteins.
J. Comput. Chem., 2020
FFParam: Standalone package for CHARMM additive and Drude polarizable force field parametrization of small molecules.
J. Comput. Chem., 2020
2019
Optimization and Evaluation of Site-Identification by Ligand Competitive Saturation (SILCS) as a Tool for Target-Based Ligand Optimization.
J. Chem. Inf. Model., 2019
Improved Modeling of Halogenated Ligand-Protein Interactions Using the Drude Polarizable and CHARMM Additive Empirical Force Fields.
J. Chem. Inf. Model., 2019
Prediction of Membrane Permeation of Drug Molecules by Combining an Implicit Membrane Model with Machine Learning.
J. Chem. Inf. Model., 2019
2018
J. Chem. Inf. Model., 2018
J. Comput. Chem., 2018
Molecular dynamics simulations using the drude polarizable force field on GPUs with OpenMM: Implementation, validation, and benchmarks.
J. Comput. Chem., 2018
Combining the polarizable Drude force field with a continuum electrostatic Poisson-Boltzmann implicit solvation model.
J. Comput. Chem., 2018
2017
Estimation of relative free energies of binding using pre-computed ensembles based on the single-step free energy perturbation and the site-identification by Ligand competitive saturation approaches.
J. Comput. Chem., 2017
Drude polarizable force field for aliphatic ketones and aldehydes, and their associated acyclic carbohydrates.
J. Comput. Aided Mol. Des., 2017
2016
J. Comput. Chem., 2016
DIRECT-ID: An automated method to identify and quantify conformational variations - application to β<sub>2</sub>-adrenergic GPCR.
J. Comput. Chem., 2016
2015
Pharmacophore Modeling Using Site-Identification by Ligand Competitive Saturation (SILCS) with Multiple Probe Molecules.
J. Chem. Inf. Model., 2015
Mapping Functional Group Free Energy Patterns at Protein Occluded Sites: Nuclear Receptors and G-Protein Coupled Receptors.
J. Chem. Inf. Model., 2015
Implementation of extended Lagrangian dynamics in GROMACS for polarizable simulations using the classical Drude oscillator model.
J. Comput. Chem., 2015
2014
All-atom polarizable force field for DNA based on the classical drude oscillator model.
J. Comput. Chem., 2014
Site-Identification by Ligand Competitive Saturation (SILCS) assisted pharmacophore modeling.
J. Comput. Aided Mol. Des., 2014
2013
Impact of Ribosomal Modification on the Binding of the Antibiotic Telithromycin Using a Combined Grand Canonical Monte Carlo/Molecular Dynamics Simulation Approach.
PLoS Comput. Biol., 2013
Inclusion of Multiple Fragment Types in the Site Identification by Ligand Competitive Saturation (SILCS) Approach.
J. Chem. Inf. Model., 2013
Impact of Substrate Protonation and Tautomerization States on Interactions with the Active Site of Arginase I.
J. Chem. Inf. Model., 2013
Conformational Determinants of the Activity of Antiproliferative Factor Glycopeptide.
J. Chem. Inf. Model., 2013
Estimation of Ligand Efficacies of Metabotropic Glutamate Receptors from Conformational Forces Obtained from Molecular Dynamics Simulations.
J. Chem. Inf. Model., 2013
(Ala)<sub>4</sub>-X-(Ala)<sub>4</sub> as a model system for the optimization of the χ<sub>1</sub> and χ<sub>2</sub> amino acid side-chain dihedral empirical force field parameters.
J. Comput. Chem., 2013
CHARMM36 all-atom additive protein force field: Validation based on comparison to NMR data.
J. Comput. Chem., 2013
2012
J. Chem. Inf. Model., 2012
Automation of the CHARMM General Force Field (CGenFF) II: Assignment of Bonded Parameters and Partial Atomic Charges.
J. Chem. Inf. Model., 2012
Automation of the CHARMM General Force Field (CGenFF) I: Bond Perception and Atom Typing.
J. Chem. Inf. Model., 2012
Extension of the CHARMM general force field to sulfonyl-containing compounds and its utility in biomolecular simulations.
J. Comput. Chem., 2012
Balancing target flexibility and target denaturation in computational fragment-based inhibitor discovery.
J. Comput. Chem., 2012
2011
Reproducing Crystal Binding Modes of Ligand Functional Groups Using Site-Identification by Ligand Competitive Saturation (SILCS) Simulations.
J. Chem. Inf. Model., 2011
Automated Selection of Compounds with Physicochemical Properties To Maximize Bioavailability and Druglikeness.
J. Chem. Inf. Model., 2011
Glycan reader: Automated sugar identification and simulation preparation for carbohydrates and glycoproteins.
J. Comput. Chem., 2011
Impact of 2′-hydroxyl sampling on the conformational properties of RNA: Update of the CHARMM all-atom additive force field for RNA.
J. Comput. Chem., 2011
2010
Polarizable empirical force field for sulfur-containing compounds based on the classical Drude oscillator model.
J. Comput. Chem., 2010
CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields.
J. Comput. Chem., 2010
2009
Computational Fragment-Based Binding Site Identification by Ligand Competitive Saturation.
PLoS Comput. Biol., 2009
Polarizable empirical force field for nitrogen-containing heteroaromatic compounds based on the classical Drude oscillator.
J. Comput. Chem., 2009
2008
J. Comput. Chem., 2008
2007
Binding Response: A Descriptor for Selecting Ligand Binding Site on Protein Surfaces.
J. Chem. Inf. Model., 2007
CHARMM force field parameters for simulation of reactive intermediates in native and thio-substituted ribozymes.
J. Comput. Chem., 2007
2005
Lead Validation and SAR Development via Chemical Similarity Searching; Application to Compounds Targeting the pY+3 Site of the SH2 Domain of p56<sup>lck</sup>.
J. Chem. Inf. Model., 2005
CH/ interactions involving aromatic amino acids: Refinement of the CHARMM tryptophan force field.
J. Comput. Chem., 2005
2004
CHARMM fluctuating charge force field for proteins: II Protein/solvent properties from molecular dynamics simulations using a nonadditive electrostatic model.
J. Comput. Chem., 2004
Extending the treatment of backbone energetics in protein force fields: Limitations of gas-phase quantum mechanics in reproducing protein conformational distributions in molecular dynamics simulations.
J. Comput. Chem., 2004
J. Comput. Chem., 2004
2003
Consideration of Molecular Weight during Compound Selection in Virtual Target-Based Database Screening.
J. Chem. Inf. Comput. Sci., 2003
2002
Combined ab initio/empirical approach for optimization of Lennard-Jones parameters for polar-neutral compounds.
J. Comput. Chem., 2002
2000
Nucleic Acids Res., 2000
All-atom empirical force field for nucleic acids: II. Application to molecular dynamics simulations of DNA and RNA in solution.
J. Comput. Chem., 2000
All-atom empirical force field for nucleic acids: I. Parameter optimization based on small molecule and condensed phase macromolecular target data.
J. Comput. Chem., 2000
1998
J. Comput. Chem., 1998
1997
A molecular mechanics force field for NAD+ NADH, and the pyrophosphate groups of nucleotides.
J. Comput. Chem., 1997
1988