@jctc_papers

New papers in J. Chem. Theory Comput. (not affiliated with ACS)

 Worldwide
pubs.acs.org/journal/jctcce
Joined April 2014
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[ASAP] Quantitatively Accounting for Protein Reorganization in Computer-Aided Drug Design ift.tt/ckpFOer

Quantitatively Accounting for Protein Reorganization in Computer-Aided Drug Design

Abstract. Structure-based drug design frequently operates under the assumption that a single holo structure is relevant. However, a large number of crystal

pubs.acs.org
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1,635
[ASAP] Interface Adsorption versus Bulk Micellization of Surfactants: Insights from Molecular Simulations ift.tt/dMKTf5g

Interface Adsorption versus Bulk Micellization of Surfactants: Insights from Molecular Simulations

Abstract. Surfactants play essential roles in many commonplace applications and industrial processes. Although significant progress has been made over the

pubs.acs.org
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1,468
[ASAP] The OpenMolcas : A Community-Driven Approach to Advancing Computational Chemistry ift.tt/dYfvXe9
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[ASAP] Constructing Diabatic Potential Energy Matrices with Neural Networks Based on Adiabatic Energies and Physical Considerations: Toward Quantum Dynamic Accuracy ift.tt/gwqZKjQ

Constructing Diabatic Potential Energy Matrices with Neural Networks Based on Adiabatic Energies...

Abstract. A permutation invariant polynomial-neural network (PIP-NN) approach for constructing the global diabatic potential energy matrices (PEMs) of the

pubs.acs.org
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1,396
[ASAP] Linearized Pair-Density Functional Theory ift.tt/8iWzCHh

Linearized Pair-Density Functional Theory

Abstract. Multiconfiguration pair-density functional theory (MC-PDFT) is a post-SCF multireference method that has been successful at computing ground- and

pubs.acs.org
20
2,271
[ASAP] Accurate Ionization Potentials, Electron Affinities, and Band Gaps from the ωLH22t Range-Separated Local Hybrid Functional: No Tuning Required ift.tt/IipwSqc
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[ASAP] Investigating the Linear Response Function under Approximations Following the Coupled-Perturbed Approach for Atoms and Molecules ift.tt/hiNyrcD

Investigating the Linear Response Function under Approximations Following the Coupled-Perturbed...

Abstract. The linear response kernel also referred to as linear response function (LRF) in the framework of conceptual density functional theory has gained

pubs.acs.org
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1,566
[ASAP] Parameterization of the miniPEG-Modified γPNA Backbone: Toward Induced γPNA Duplex Dissociation ift.tt/oeVG1Fa
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[ASAP] Improving Speed and Affordability without Compromising Accuracy: Standard Binding Free-Energy Calculations Using an Enhanced Sampling Algorithm, Multiple-Time Stepping, and Hydrogen Mass Repartitioning ift.tt/bSER3ox

Improving Speed and Affordability without Compromising Accuracy: Standard Binding Free-Energy...

Abstract. Accurate evaluation of protein–ligand binding free energies in silico is of paramount importance for understanding the mechanisms of biological r

pubs.acs.org
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1,983
[ASAP] Alchemical Free Energy and Hamiltonian Replica Exchange Molecular Dynamics to Compute Hydrofluorocarbon Isotherms in Imidazolium-Based Ionic Liquids ift.tt/iaobzYq

Alchemical Free Energy and Hamiltonian Replica Exchange Molecular Dynamics to Compute Hydrofluoro...

Abstract. Ionic liquids (ILs) have shown promise for applications that leverage differential gas solubility in an IL solvent, e.g., gas separations. Althou

pubs.acs.org
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1,575
[ASAP] Assessing the Accuracy of Density Functional Approximations for Predicting Hydrolysis Reaction Kinetics ift.tt/6GOuWMg

Assessing the Accuracy of Density Functional Approximations for Predicting Hydrolysis Reaction...

Abstract. Hydrolysis reactions are ubiquitous in biological, environmental, and industrial chemistry. Density functional theory (DFT) is commonly employed

pubs.acs.org
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1,320
[ASAP] Machine Learning Predictions of Simulated Self-Diffusion Coefficients for Bulk and Confined Pure Liquids ift.tt/P3AzXvn

Machine Learning Predictions of Simulated Self-Diffusion Coefficients for Bulk and Confined Pure...

Abstract. Diffusion properties of bulk fluids have been predicted using empirical expressions and machine learning (ML) models, suggesting that predictions

pubs.acs.org
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[ASAP] Smooth Things Come in Threes: A Diabatic Surrogate Model for Conical Intersection Optimization ift.tt/UdwnsRD
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[ASAP] Single-Point Extrapolation to the Complete Basis Set Limit through Deep Learning ift.tt/oNQlGDf

Single-Point Extrapolation to the Complete Basis Set Limit through Deep Learning

Abstract. Machine learning (ML) offers an attractive method for making predictions about molecular systems while circumventing the need to run expensive el

pubs.acs.org
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1,742
[ASAP] Understanding Virus Structure and Dynamics through Molecular Simulations ift.tt/sirqUCM
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[ASAP] Algebraic Diagrammatic Construction Theory for Simulating Charged Excited States and Photoelectron Spectra ift.tt/HY8oLCV

Algebraic Diagrammatic Construction Theory for Simulating Charged Excited States and Photoelectron...

Abstract. Charged excitations are electronic transitions that involve a change in the total charge of a molecule or material. Understanding the properties

pubs.acs.org
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1,285
[ASAP] New Methodology to Produce Sets of Valence Bond Structures with Enhanced Chemical Insights ift.tt/v0NZXTn
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[ASAP] Practical Post-Kohn–Sham Methods for Time-Reversal Symmetry Breaking References ift.tt/1wkpCd8

Practical Post-Kohn–Sham Methods for Time-Reversal Symmetry Breaking References

Abstract. The applicability of reduced scaling algorithms based on auxiliary subspace methods for the correlation energy from the random phase approximatio

pubs.acs.org
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1,532
[ASAP] AlphaFold2-RAVE: From Sequence to Boltzmann Ranking ift.tt/PyoZ9bN

AlphaFold2-RAVE: From Sequence to Boltzmann Ranking

Abstract. While AlphaFold2 is rapidly being adopted as a new standard in protein structure predictions, it is limited to single structures. This can be ins

pubs.acs.org
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[ASAP] Selecting Features for Markov Modeling: A Case Study on HP35 ift.tt/OCl5Y8E
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