[HTML][HTML] Quantum mechanical-based strategies in drug discovery: Finding the pace to new challenges in drug design

T Ginex, J Vázquez, C Estarellas, FJ Luque - Current Opinion in Structural …, 2024 - Elsevier
The expansion of the chemical space to tangible libraries containing billions of
synthesizable molecules opens exciting opportunities for drug discovery, but also …

[HTML][HTML] Quantum chemical package Jaguar: A survey of recent developments and unique features

Y Cao, T Balduf, MD Beachy, MC Bennett… - The Journal of …, 2024 - pubs.aip.org
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 …

Crash testing machine learning force fields for molecules, materials, and interfaces: model analysis in the TEA Challenge 2023

I Poltavsky, A Charkin-Gorbulin, M Puleva… - Chemical …, 2025 - pubs.rsc.org
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 …

Extension of the D3 and D4 London dispersion corrections to the full actinides series

L Wittmann, I Gordiy, M Friede… - Physical Chemistry …, 2024 - pubs.rsc.org
Efficient dispersion corrections are an indispensable component of modern density
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

P Pracht, Y Pillai, V Kapil, G Csányi… - Journal of Chemical …, 2024 - ACS Publications
Vibrational spectroscopy is a cornerstone technique for molecular characterization and
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 …

dxtb—An efficient and fully differentiable framework for extended tight-binding

M Friede, C Hölzer, S Ehlert, S Grimme - The Journal of Chemical …, 2024 - pubs.aip.org
Automatic differentiation (AD) emerged as an integral part of machine learning, accelerating
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

T Rose, M Bursch, JM Mewes, S Grimme - Inorganic Chemistry, 2024 - ACS Publications
Lanthanides (Ln) and actinides (An) have recently become important tools in biomedical
and materials science. However, the development of computational methods able to …

Overcoming the Pitfalls of Computing Reaction Selectivity from Ensembles of Transition States

R Laplaza, MD Wodrich… - The journal of physical …, 2024 - ACS Publications
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 …

Reparameterization of GFN1-xTB for atmospheric molecular clusters: applications to multi-acid–multi-base systems

Y Knattrup, J Kubečka, H Wu, F Jensen, J Elm - RSC Advances, 2024 - pubs.rsc.org
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 …