Mapping the conformational free energy of aspartic acid in the gas phase and in aqueous solution

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Publications associées (32)

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Machine learned interatomic interaction potentials have enabled efficient and accurate molecular simulations of closed systems. However, external fields, which can greatly change the chemical structure and/or reactivity, have been seldom included in curren ...

Nature Portfolio2023

cgNA+: A sequence-dependent coarse-grain model of double-stranded nucleic acids

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DNA mechanics plays a crucial role in many biological processes, including nucleosome positioning and protein-DNA interactions. It is believed that nature employs epigenetic modifications in DNA to further regulate gene expression. Moreover, double-strande ...

EPFL2023

Systems and methods for de novo design of protein interactions with learned surface fingerprints

Anthony Marchand, Zander Harteveld, Pablo Gainza Cirauqui, Freyr Sverrisson, Andreas Scheck, Sarah Wehrle, Alexandra Krina Van Hall-Beauvais, Michael Bronstein

The present application relates to a computer-implemented systems and methods for protein interaction design using surface fingerprints. The method comprises predicting at least one target interface site with high binding propensity, wherein, optionally, t ...

2023

Modelling of metal alloys in realistic conditions with machine learning

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Computer simulations based on statistical methods have emerged as a powerful tool for studying structure-property relationships at the atomistic level. However, to provide reliable insights into materials in realistic conditions, it is essential to accurat ...

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Factorized structure of the long-range two-electron integrals tensor and its application in quantum chemistry

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We introduce two new approximation methods for the numerical evaluation of the long-range component of the range-separated Coulomb potential and the approximation of the resulting high dimensional Two-Electron Integrals tensor (TEI) with long-range interac ...

Academic Press Inc Elsevier Science2023

Generative power of a protein language model trained on multiple sequence alignments

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Computational models starting from large ensembles of evolutionarily related protein sequences capture a representation of protein families and learn constraints associated to protein structure and function. They thus open the possibility for generating no ...

eLIFE SCIENCES PUBL LTD2023

A recipe for cracking the quantum scaling limit with machine learned electron densities

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A long-standing goal of science is to accurately simulate large molecular systems using quantum mechanics. The poor scaling of current quantum chemistry algorithms on classical computers, however, imposes an effective limit of about a few dozen atoms on tr ...

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Computer-implemented design of peptide:receptor signaling complexes for enhanced chemotaxis

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The present invention relates to a computer-implemented method for engineering the interaction between a protein and a cognate peptide that are capable of forming a molecular complex, wherein the method comprises (a) preparing in silico a library of test p ...

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Protein target highlights in CASP15: Analysis of models by structure providers

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We present an in-depth analysis of selected CASP15 targets, focusing on their biological and functional significance. The authors of the structures identify and discuss key protein features and evaluate how effectively these aspects were captured in the su ...

WILEY2023

Machine-learning the electronic density of states: electronic properties without quantum mechanics

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The electronic density of states (DOS) quantifies the distribution of the energy levels that can be occupied by electrons in a quasiparticle picture and is central to modern electronic structure theory. It also underpins the computation and interpretation ...

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Indication of 310-Helix Structure in Gas-Phase Neutral Pentaalanine

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We investigate the gas-phase structure of the neutral pentaalanine peptide. The IR spectrum in the 340-1820 cm-1 frequency range is obtained by employing supersonic jet cooling, infrared multiphoton dissociation, and vacuum-ultraviolet action spectroscopy. ...

AMER CHEMICAL SOC2023

Plane Waves Versus Correlation-Consistent Basis Sets: A Comparison of MP2 Non-Covalent Interaction Energies in the Complete Basis Set Limit

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Second-order Moller-Plesset perturbation theory (MP2) is the most expedient wave function-based method for considering electron correlation in quantum chemical calculations and, as such, provides a cost-effective framework to assess the effects of basis se ...

Amer Chemical Soc2023

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