Free energy calculations based on molecular dynamics simulations show considerable promise for applications ranging from drug discovery to prediction of physical properties and structure-function ...studies. But these calculations are still difficult and tedious to analyze, and best practices for analysis are not well defined or propagated. Essentially, each group analyzing these calculations needs to decide how to conduct the analysis and, usually, develop its own analysis tools. Here, we review and recommend best practices for analysis yielding reliable free energies from molecular simulations. Additionally, we provide a Python tool,
alchemical-analysis.py
, freely available on GitHub as part of the pymbar package (located at
http://github.com/choderalab/pymbar
), that implements the analysis practices reviewed here for several reference simulation packages, which can be adapted to handle data from other packages. Both this review and the tool covers analysis of alchemical calculations generally, including free energy estimates via both thermodynamic integration and free energy perturbation-based estimators. Our Python tool also handles output from multiple types of free energy calculations, including expanded ensemble and Hamiltonian replica exchange, as well as standard fixed ensemble calculations. We also survey a range of statistical and graphical ways of assessing the quality of the data and free energy estimates, and provide prototypes of these in our tool. We hope this tool and discussion will serve as a foundation for more standardization of and agreement on best practices for analysis of free energy calculations.
This work provides a curated database of experimental and calculated hydration free energies for small neutral molecules in water, along with molecular structures, input files, references, and ...annotations. We call this the Free Solvation Database, or FreeSolv. Experimental values were taken from prior literature and will continue to be curated, with updated experimental references and data added as they become available. Calculated values are based on alchemical free energy calculations using molecular dynamics simulations. These used the GAFF small molecule force field in TIP3P water with AM1-BCC charges. Values were calculated with the GROMACS simulation package, with full details given in references cited within the database itself. This database builds in part on a previous, 504-molecule database containing similar information. However, additional curation of both experimental data and calculated values has been done here, and the total number of molecules is now up to 643. Additional information is now included in the database, such as SMILES strings, PubChem compound IDs, accurate reference DOIs, and others. One version of the database is provided in the Supporting Information of this article, but as ongoing updates are envisioned, the database is now versioned and hosted online. In addition to providing the database, this work describes its construction process. The database is available free-of-charge via
http://www.escholarship.org/uc/item/6sd403pz
.
•The preferential adsorption of CO2 over CH4 improves with coal rank.•Pore structure of coal affects the thermodynamics of adsorption of CO2 and CH4.•Adsorbed CO2 has a more ordered configuration ...than CH4 on different rank coals.
In this paper, the pore structures of three different rank coals sampled from China (anthracite, bituminous coal and lignite) were characterized by CO2 and N2 adsorption. The isothermal adsorption curves of CO2 and CH4 on three samples were measured by gravimetric method and fitted by Langmuir model. The preferential selectivity (αCO2/CH4) was calculated using the Langmuir parameters of CO2 and CH4, and the Henry’s coefficient (KH) was obtained with the help of virial equation. More importantly, a comparative analysis of adsorption thermodynamics of CO2 and CH4 on three different rank coals, including surface potential (Ω), Gibbs free energy change (ΔG) and entropy loss (ΔS), was presented according to the adsorption data. It is found that the uptakes of CO2 and CH4 on anthracite are the largest, followed by lignite and bituminous coal in sequence. αCO2/CH4 increases with the increase of coal rank. Low temperature helps injected CO2 to displace pre-adsorbed CH4. The KH values on anthracite are the biggest, while KH values on bituminous coal are the smallest. Ω, ΔG and ΔS of CO2 and CH4 all exhibit a U-shaped function with maturity. Anthracite has the highest Ω, ΔG and ΔS, while bituminous coal has the lowest Ω, ΔG and ΔS. The thermodynamics parameters of Ω, ΔG and ΔS are affected by pore size distributions of three coals. Ω, ΔG and ΔS of CH4 are smaller than those of CO2. CO2 adsorption on coal is more favorable and spontaneous, and adsorbed CO2 molecules form a more efficient packing on coal.
Shelley Claridge
Angewandte Chemie International Edition,
November 22, 2021, Letnik:
60, Številka:
48
Journal Article
Recenzirano
Odprti dostop
“My favorite equation is the equation for Gibbs free energy. It tells us that things happen for a good reason … I can never resist going back as far as I can through the literature to understand ...where an idea first started …” Find out more about Shelley Claridge in her Introducing … Profile.
Metallic phase (1T) MoS2 has been regarded as an appealing material for hydrogen evolution reaction. In this work, a novel interface‐induced strategy is reported to achieve stable and high‐percentage ...1T MoS2 through highly active 1T‐MoS2/CoS2 hetero‐nanostructure. Herein, a large number of heterointerfaces can be obtained by interlinked 1T‐MoS2 and CoS2 nanosheets in situ grown from the molybdate cobalt oxide nanorod under moderate conditions. Owing to the strong interaction between MoS2 and CoS2, high‐percentage of metallic‐phase (1T) MoS2 of 76.6% can be achieved, leading to high electroconductivity and abundant active sites compared to 2H MoS2. Furthermore, the interlinked MoS2 and CoS2 nanosheets can effectively disperse the nanosheets so as to enlarge the exposed active surface area. The near zero free energy of hydrogen adsorption at the heterointerface can also be achieved, indicating the fast kinetics and excellent catalytic activity induced by heterojunction. Therefore, when applied in hydrogen evolution reaction (HER), 1T‐MoS2/CoS2 heterostructure delivers low overpotential of 71 and 26 mV at the current density of 10 mA cm−2 with low Tafel slops of 60 and 43 mV dec−1, respectively in alkaline and acidic conditions.
A novel interface‐induced strategy is reported to achieve stable and high‐percentage 1T MoS2 by modifying the intrinsic electronic/phase structure at the heterointerface of 1T‐MoS2/CoS2. Owing to the high electroconductivity, largely exposed active surface area and excellent structural stability, 1T‐MoS2/CoS2, with the near zero Gibbs free‐energy, exhibits outstanding electrocatalytic properties for hydrogen evolution reaction (HER) in both alkaline and acidic electrolytes.
Reliable prediction of free energy changes upon amino acid substitutions (ΔΔGs) is crucial to investigate their impact on protein stability and protein–protein interaction. Advances in experimental ...mutational scans allow high‐throughput studies thanks to multiplex techniques. On the other hand, genomics initiatives provide a large amount of data on disease‐related variants that can benefit from analyses with structure‐based methods. Therefore, the computational field should keep the same pace and provide new tools for fast and accurate high‐throughput ΔΔG calculations. In this context, the Rosetta modeling suite implements effective approaches to predict folding/unfolding ΔΔGs in a protein monomer upon amino acid substitutions and calculate the changes in binding free energy in protein complexes. However, their application can be challenging to users without extensive experience with Rosetta. Furthermore, Rosetta protocols for ΔΔG prediction are designed considering one variant at a time, making the setup of high‐throughput screenings cumbersome. For these reasons, we devised RosettaDDGPrediction, a customizable Python wrapper designed to run free energy calculations on a set of amino acid substitutions using Rosetta protocols with little intervention from the user. Moreover, RosettaDDGPrediction assists with checking completed runs and aggregates raw data for multiple variants, as well as generates publication‐ready graphics. We showed the potential of the tool in four case studies, including variants of uncertain significance in childhood cancer, proteins with known experimental unfolding ΔΔGs values, interactions between target proteins and disordered motifs, and phosphomimetics. RosettaDDGPrediction is available, free of charge and under GNU General Public License v3.0, at https://github.com/ELELAB/RosettaDDGPrediction.
García-Pintos, Hamma, and del Campo Reply García-Pintos, Luis Pedro; Hamma, Alioscia; del Campo, Adolfo
Physical review letters,
07/2021, Letnik:
127, Številka:
2
Journal Article
Recenzirano
We acknowledge that a derivation reported in Phys. Rev. Lett. 125, 040601 (2020) is incorrect as pointed out by Cusumano and Rudnicki. We respond by giving a correct proof of the claim "fluctuations ...in the free energy operator upper bound the charging power of a quantum battery" that we made in the Letter.
Collective variable (CV)‐based enhanced sampling techniques are widely used today for accelerating barrier‐crossing events in molecular simulations. A class of these methods, which includes ...temperature accelerated molecular dynamics (TAMD)/driven‐adiabatic free energy dynamics (d‐AFED), unified free energy dynamics (UFED), and temperature accelerated sliced sampling (TASS), uses an extended variable formalism to achieve quick exploration of conformational space. These techniques are powerful, as they enhance the sampling of a large number of CVs simultaneously compared to other techniques. Extended variables are kept at a much higher temperature than the physical temperature by ensuring adiabatic separation between the extended and physical subsystems and employing rigorous thermostatting. In this work, we present a computational platform to perform extended phase space enhanced sampling simulations using the open‐source molecular dynamics engine OpenMM. The implementation allows users to have interoperability of sampling techniques, as well as employ state‐of‐the‐art thermostats and multiple time‐stepping. This work also presents protocols for determining the critical parameters and procedures for reconstructing high‐dimensional free energy surfaces. As a demonstration, we present simulation results on the high dimensional conformational landscapes of the alanine tripeptide in vacuo, tetra‐N‐methylglycine (tetra‐sarcosine) peptoid in implicit solvent, and the Trp‐cage mini protein in explicit water.
Molecular dynamics simulations employing enhanced sampling of collective variables are used widely today to study physicochemical phenomena ranging from protein folding, peptide conformational exploration, and drug binding to structural transitions in materials. This work presents UFEDMM, a modular and interoperable open‐source framework for implementing powerful combinations of enhanced sampling schemes. The article also discusses protocols for setting up and carrying out simulations using these advanced methods.
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