[HTML][HTML] Quantum mechanical-based strategies in drug discovery: Finding the pace to new challenges in drug design
The expansion of the chemical space to tangible libraries containing billions of
synthesizable molecules opens exciting opportunities for drug discovery, but also …
synthesizable molecules opens exciting opportunities for drug discovery, but also …
[HTML][HTML] Quantum chemical package Jaguar: A survey of recent developments and unique features
This paper is dedicated to the quantum chemical package Jaguar, which is commercial
software developed and distributed by Schrödinger, Inc. We discuss Jaguar's scientific …
software developed and distributed by Schrödinger, Inc. We discuss Jaguar's scientific …
Crash testing machine learning force fields for molecules, materials, and interfaces: model analysis in the TEA Challenge 2023
Atomistic simulations are routinely employed in academia and industry to study the behavior
of molecules, materials, and their interfaces. Central to these simulations are force fields …
of molecules, materials, and their interfaces. Central to these simulations are force fields …
Extension of the D3 and D4 London dispersion corrections to the full actinides series
Efficient dispersion corrections are an indispensable component of modern density
functional theory, semi-empirical quantum mechanical, and even force field methods. In this …
functional theory, semi-empirical quantum mechanical, and even force field methods. In this …
Efficient Composite Infrared Spectroscopy: Combining the Double-Harmonic Approximation with Machine Learning Potentials
Vibrational spectroscopy is a cornerstone technique for molecular characterization and
offers an ideal target for the computational investigation of molecular materials. Building on …
offers an ideal target for the computational investigation of molecular materials. Building on …
Tensor Train Optimization for Conformational Sampling of Organic Molecules
C Zurek, RA Mallaev, AC Paul… - Journal of Chemical …, 2024 - ACS Publications
Exploring the conformational space of molecules remains a challenge of fundamental
importance to quantum chemistry: identification of relevant conformers at ambient conditions …
importance to quantum chemistry: identification of relevant conformers at ambient conditions …
dxtb—An efficient and fully differentiable framework for extended tight-binding
Automatic differentiation (AD) emerged as an integral part of machine learning, accelerating
model development by enabling gradient-based optimization without explicit analytical …
model development by enabling gradient-based optimization without explicit analytical …
Fast and Robust Modeling of Lanthanide and Actinide Complexes, Biomolecules, and Molecular Crystals with the Extended GFN-FF Model
Lanthanides (Ln) and actinides (An) have recently become important tools in biomedical
and materials science. However, the development of computational methods able to …
and materials science. However, the development of computational methods able to …
Overcoming the Pitfalls of Computing Reaction Selectivity from Ensembles of Transition States
The prediction of reaction selectivity is a challenging task for computational chemistry, not
only because many molecules adopt multiple conformations but also due to the exponential …
only because many molecules adopt multiple conformations but also due to the exponential …
Reparameterization of GFN1-xTB for atmospheric molecular clusters: applications to multi-acid–multi-base systems
Atmospheric molecular clusters, the onset of secondary aerosol formation, are a major part
of the current uncertainty in modern climate models. Quantum chemical (QC) methods are …
of the current uncertainty in modern climate models. Quantum chemical (QC) methods are …