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Alkali Metals

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Group 1 elements are soft and shiny metallic solids. They are malleable, ductile, and good conductors of heat and electricity. The melting points of the alkali metals are unusually low for metals and decrease going down the group, while the density increases going down the group with the exception of potassium (Table 1).
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Related Experiment Video

Updated: Jul 17, 2025

Author Spotlight: Accelerating Discovery in Microporous Material Chemistry

Author Spotlight: Accelerating Discovery in Microporous Material Chemistry

Published on: October 6, 2023

On the Path to Optimal Alchemistry.

Magnus Lundborg¹, Jack Lidmar², Berk Hess³

¹ERCO Pharma AB, 11439, Stockholm, Sweden.

The Protein Journal

|August 31, 2023

Summary

This summary is machine-generated.

Alchemical free energy calculations can be improved by optimizing the path between states. A new metric enhances sampling efficiency and path selection, boosting calculation speed up to 16-fold.

Keywords:

Accelerated weight histogram method Alchemical free energy calculations Lambda path optimization

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Area of Science:

Computational chemistry
Drug discovery
Molecular modeling

Background:

Alchemical free energy calculations are crucial for drug binding affinity prediction.
Current methods often use suboptimal paths for calculations, limiting efficiency.
Path parametrization in these calculations has remained largely unchanged for years.

Purpose of the Study:

To introduce a novel approach for optimizing path selection in alchemical free energy calculations.
To demonstrate the utility of a path metric for improving sampling efficiency.
To enhance the overall efficiency of drug binding affinity predictions.

Main Methods:

Utilized a recently introduced path metric within the accelerated weight histogram method.
Applied the metric to optimize sampling along existing paths.
Employed the metric to guide the selection of more efficient calculation paths.

Main Results:

The introduced metric significantly improves sampling efficiency on a given path.
The metric enables a more informed and efficient choice of paths for calculations.
Combined improvements led to efficiency gains of up to a factor of 16 in use cases.

Conclusions:

Optimizing path selection is critical for enhancing alchemical free energy calculations.
The path metric offers a powerful tool for both sampling and path optimization.
This approach substantially increases the efficiency of predicting drug binding affinities.