[ASAP] Quantitatively Accounting for Protein Reorganization in Computer-Aided Drug Design

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

[ASAP] The OpenMolcas : A Community-Driven Approach to Advancing Computational Chemistry

[ASAP] Constructing Diabatic Potential Energy Matrices with Neural Networks Based on Adiabatic Energies and Physical Considerations: Toward Quantum Dynamic Accuracy

[ASAP] Linearized Pair-Density Functional Theory

[ASAP] Accurate Ionization Potentials, Electron Affinities, and Band Gaps from the ωLH22t Range-Separated Local Hybrid Functional: No Tuning Required

[ASAP] Investigating the Linear Response Function under Approximations Following the Coupled-Perturbed Approach for Atoms and Molecules

[ASAP] Parameterization of the miniPEG-Modified γPNA Backbone: Toward Induced γPNA Duplex Dissociation

[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

[ASAP] Alchemical Free Energy and Hamiltonian Replica Exchange Molecular Dynamics to Compute Hydrofluorocarbon Isotherms in Imidazolium-Based Ionic Liquids

[ASAP] Assessing the Accuracy of Density Functional Approximations for Predicting Hydrolysis Reaction Kinetics

[ASAP] Machine Learning Predictions of Simulated Self-Diffusion Coefficients for Bulk and Confined Pure Liquids

[ASAP] Smooth Things Come in Threes: A Diabatic Surrogate Model for Conical Intersection Optimization

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

[ASAP] Understanding Virus Structure and Dynamics through Molecular Simulations

[ASAP] Algebraic Diagrammatic Construction Theory for Simulating Charged Excited States and Photoelectron Spectra

[ASAP] New Methodology to Produce Sets of Valence Bond Structures with Enhanced Chemical Insights

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

[ASAP] AlphaFold2-RAVE: From Sequence to Boltzmann Ranking

[ASAP] Selecting Features for Markov Modeling: A Case Study on HP35