AIMC Topic: Molecular Dynamics Simulation

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Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems.

Journal of chemical theory and computation
Machine learning encompasses tools and algorithms that are now becoming popular in almost all scientific and technological fields. This is true for molecular dynamics as well, where machine learning offers promises of extracting valuable information ...

Structural compliance: A new metric for protein flexibility.

Proteins
Proteins are the active players in performing essential molecular activities throughout biology, and their dynamics has been broadly demonstrated to relate to their mechanisms. The intrinsic fluctuations have often been used to represent their dynami...

Extending the Applicability of the ANI Deep Learning Molecular Potential to Sulfur and Halogens.

Journal of chemical theory and computation
Machine learning (ML) methods have become powerful, predictive tools in a wide range of applications, such as facial recognition and autonomous vehicles. In the sciences, computational chemists and physicists have been using ML for the prediction of ...

Insight into potent leads for alzheimer's disease by using several artificial intelligence algorithms.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
Several proteins including S-nitrosoglutathione reductase (GSNOR), complement Factor D, complement 3b (C3b) and Protein Kinase R-like Endoplasmic Reticulum Kinase (PERK), have been demonstrated to be involved in pathogenesis pathways for Alzheimer's ...

Combining Machine Learning and Enhanced Sampling Techniques for Efficient and Accurate Calculation of Absolute Binding Free Energies.

Journal of chemical theory and computation
Calculating absolute binding free energies is challenging and important. In this paper, we test some recently developed metadynamics-based methods and develop a new combination with a Hamiltonian replica-exchange approach. The methods were tested on ...

Combined Machine Learning and Molecular Modelling Workflow for the Recognition of Potentially Novel Fungicides.

Molecules (Basel, Switzerland)
Novel machine learning and molecular modelling filtering procedures for drug repurposing have been carried out for the recognition of the novel fungicide targets of Cyp51 and Erg2. Classification and regression approaches on molecular descriptors hav...

Comparison of the Performance of Machine Learning Models in Representing High-Dimensional Free Energy Surfaces and Generating Observables.

The journal of physical chemistry. B
Free energy surfaces of chemical and physical systems are often generated using a popular class of enhanced sampling methods that target a set of collective variables (CVs) chosen to distinguish the characteristic features of these surfaces. While so...

Robosample: A rigid-body molecular simulation program based on robot mechanics.

Biochimica et biophysica acta. General subjects
BACKGROUND: Compared with all-atom molecular dynamics (MD), constrained MD methods allow for larger time steps, potentially reducing computational cost. For this reason, there has been continued interest in improving constrained MD algorithms to incr...

Machine Learning Driven Analysis of Large Scale Simulations Reveals Conformational Characteristics of Ubiquitin Chains.

Journal of chemical theory and computation
Understanding the conformational characteristics of protein complexes in solution is crucial for a deeper insight in their biological function. Molecular dynamics simulations performed on high performance computing plants and with modern simulation t...