Article
Multidisciplinary Sciences
Mayank Agarwal, Vishal Deshpande, David Katoshevski, Bimlesh Kumar
Summary: P-SAT is a lightweight Python framework that automates statistical analysis of turbulence and spectra computation. It can efficiently process velocity data for steady and unsteady flows, with customizable threshold values and output in a .csv file. The framework, developed in Python, is versatile and can be deployed on various operating systems.
SCIENTIFIC REPORTS
(2021)
Article
Chemistry, Multidisciplinary
Koen Heijmans, Ionut C. Tranca, Ming-Wen Chang, Thijs J. H. Vlugt, Silvia Gaastra-Nedea, David M. J. Smeulders
Summary: In this study, a new GCMC tool was developed and combined with ReaxFF molecular dynamics to investigate the hydration of salts. The simulation results showed good agreement with experimental data, demonstrating the effectiveness of the approach in studying complex salt reactions.
Article
Chemistry, Physical
Gyuseung Han, In Won Yeu, Kun Hee Ye, Seungjae Yoon, Taeyoung Jeong, Seung-Cheol Lee, Cheol Seong Hwang, Jung-Hae Choi
Summary: P5Grand is an open-source program for calculating the properties of solid solutions, using random configuration sampling and separate calculations of strain energy to improve efficiency. It can efficiently predict the thermodynamic properties and any desired properties of arbitrary solid solutions.
CHEMICAL PHYSICS LETTERS
(2022)
Article
Chemistry, Physical
Amin Bakhshandeh, Yan Levin
Summary: This paper discusses the problems associated with the notion of pH in heterogeneous systems. While standardization protocols lead to a well-defined quantity for homogeneous systems, pH defined in terms of the chemical part of the electrochemical activity is thermodynamically inconsistent for heterogeneous systems. This problem is particularly relevant for modern simulation methods involving charge regulation of various substances.
JOURNAL OF PHYSICAL CHEMISTRY B
(2023)
Article
Biochemical Research Methods
Xiaoliang Ren, Yanwen Shao, Yiwen Zhang, Ying Ni, Yu Bi, Runsheng Li
Summary: The primerdiffer pipeline is introduced as a large-scale primer design tool that can differentiate haplotypes with precise false priming checking. It includes steps like greedy primer search, in silico PCR-based false priming checking, and automated best primer selection. The pipeline provides a command-line interface and flexibility for users to design primers with their own genome sequences and specific parameters.
Article
Chemistry, Multidisciplinary
Mingtian Zhao, Abhishek A. Kognole, Sunhwan Jo, Aoxiang Tao, Anthony Hazel, Alexander D. MacKerell Jr
Summary: In this study, the sampling efficiency of the GCMC method was improved by applying known cavity-bias and configurational-bias algorithms on GPU architecture. The method was parallelized using CUDA and OpenCL, resulting in simultaneous sampling of a large number of configurations during insertion attempts. The partitioning scheme allowed for simultaneous insertion attempts for large systems, significantly improving efficiency. The algorithm was shown to be useful in the application of the site-identification by ligand competitive saturation (SILCS) co-solvent sampling approach for the protein CDK2.
JOURNAL OF COMPUTATIONAL CHEMISTRY
(2023)
Article
Chemistry, Physical
Xi Chen, Muammar El Khatib, Per Lindgren, Adam Willard, Andrew J. Medford, Andrew A. Peterson
Summary: This article presents a strategy for machine-learning emulation of electronic structure calculations in the electronically grand-canonical ensemble. The approach uses a dual-learning scheme to predict both system charge and system energy for each image. The scheme has been shown to successfully emulate basic electrochemical reactions at various potentials and combining it with a bootstrap-ensemble approach gives reasonable estimates of prediction uncertainty. The method also accelerates saddle-point searches and extrapolates to systems with different numbers of water layers. This method is expected to enable larger length- and time-scale simulations necessary for electrochemical simulations.
NPJ COMPUTATIONAL MATERIALS
(2023)
Article
Biochemistry & Molecular Biology
Yunhui Ge, Oliver J. Melling, Weiming Dong, Jonathan W. Essex, David L. Mobley
Summary: Water plays a crucial role in protein-ligand interactions, but its slow rearrangement during binding can often hinder accurate free energy calculations. Previous studies have shown that grand canonical Monte Carlo (GCMC) simulations outperform normal molecular dynamics (MD) simulations in water sampling, but there is still room for improvement. In this work, we applied GCMC to evaluate its performance in rehydrating buried water sites in 21 protein-ligand systems. We found that while GCMC was successful in most systems, it failed in five systems due to protein/ligand motions obstructing water insertion. To overcome this, we extended our simulations and introduced a new technique called grand canonical nonequilibrium candidate Monte Carlo (GCNCMC), which showed promising results in rehydrating all target water sites in three out of the five problematic systems.
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
(2022)
Article
Physics, Fluids & Plasmas
Philipp Stroeker, Karsten Meier
Summary: The methodology developed by Lustig is applied to derive rigorous expressions for thermodynamic properties of fluids in the grand canonical ensemble, which are expressed by phase-space functions related to derivatives of the grand canonical potential. The derived expressions are validated by Monte Carlo simulations, providing more reliable results compared to previous literature and becoming equivalent to corresponding expressions in the canonical ensemble in the thermodynamic limit.
Article
Chemistry, Physical
Arihant Bhandari, Chao Peng, Jacek Dziedzic, Lucian Anton, John R. Owen, Denis Kramer, Chris-Kriton Skylaris
Summary: Progress in electrochemical technologies relies on improving charged interfaces between electrodes and electrolytes, which can be achieved through first-principles simulations and a new hybrid computational method. This method allows for simulating electrochemistry under experimental conditions and provides insights into predicting electrochemical properties under constant potential.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Chemistry, Medicinal
Martin Floor, Kengjie Li, Miquel Estevez-Gay, Luis Agullo, Pau Marc Munoz-Torres, Jenn K. Hwang, Silvia Osuna, Jordi Villa-Freixa
Summary: Conventional MD simulations face challenges in obtaining converged results, leading to the widespread use of structure-based models (SBMs) as an alternative. SBMs simplify and focus on relevant aspects of physical processes, allowing for modification of force field definitions and parameters to cater to specific biophysical simulations.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2021)
Article
Chemistry, Physical
Oliver J. Melling, Marley L. Samways, Yunhui Ge, David L. Mobley, Jonathan W. Essex
Summary: Water molecules are crucial in biomolecular systems, especially at protein-ligand interfaces. However, simulating such systems is challenging due to slow water exchange between protein and solvent. To overcome this, the authors combine grand canonical Monte Carlo (GCMC) with nonequilibrium candidate Monte Carlo (NCMC) to develop grand canonical nonequilibrium candidate Monte Carlo (GCNCMC). This approach improves water sampling efficiency and enables the exploration of new ligand-binding geometries mediated by water.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2023)
Article
Physics, Fluids & Plasmas
Jules Guioth, Eric Bertin
Summary: The article introduces a nonequilibrium grand-canonical ensemble by considering the stationary state of a driven system of particles in contact with a particle reservoir. A chemical potential of the reservoir can be defined if the additivity assumption for the large deviation function of density holds, resulting in a grand-canonical distribution similar to the equilibrium one. The probability weight is renormalized by a contribution coming from the contact, illustrating formal grand-canonical potential and static fluctuation-response relations.
Article
Chemistry, Physical
Jun Huang, Yufan Zhang, Mengru Li, Axel Gross, Sung Sakong
Summary: The theoretical modeling of metal/water interfaces focuses on the configuration of the electric double layer (EDL) under grand canonical conditions. Ab initio molecular dynamics (AIMD) simulations are ideal for treating water-metal interactions but are limited by small ensembles and short simulation times. Semiclassical approaches can efficiently handle the EDL model by averaging microscopic details. By combining AIMD and semiclassical methods, an improved description of the EDL can be obtained. Comparing these approaches using the Pt(111)/water interface, we analyze the differences in electric field, water configuration, and double-layer capacitance, and discuss their contributions to EDL theory.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2023)
Article
Chemistry, Physical
Ludwig Schneider, Marcus Schwarting, Joshua Mysona, Heyi Liang, Ming Han, Phillip M. Rauscher, Jeffrey M. Ting, Shruti Venkatram, Richard B. Ross, K. J. Schmidt, Ben Blaiszik, Ian Foster, Juan J. de Pablo
Summary: Machine learning is a promising technology for accelerating materials discovery. By providing a reliable, reproducible, and automated simulation pipeline, users with different backgrounds can easily generate thermodynamic data and further drive chemical exploration through active learning methods.
MOLECULAR SYSTEMS DESIGN & ENGINEERING
(2022)
Article
Chemistry, Physical
Miroslav Suruzhon, Michael S. Bodnarchuk, Antonella Ciancetta, Russell Viner, Ian D. Wall, Jonathan W. Essex
Summary: This study investigated the impact of initial crystal structures on binding free energy values in alchemical free energy calculations, finding that the initial structure can significantly affect values obtained at short timescales. Rare events, such as torsional ligand motions, became important factors at longer timescales, leading to higher uncertainty in the obtained values. Optimal protocols should focus on achieving convergence in the alchemical coupling parameter space, as well as longer simulations and multiple repeats.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2021)
Article
Chemistry, Medicinal
Joao Morado, Paul N. Mortenson, Marcel L. Verdonk, Richard A. Ward, Jonathan W. Essex, Chris-Kriton Skylaris
Summary: The quality of force field parameterization plays a crucial role in determining the accuracy of observable properties computed from molecular mechanics simulations. ParaMol is a Python package focused on parameterizing bonded and nonbonded terms of druglike molecules by fitting to ab initio data. Through case studies, ParaMol demonstrates the ability to derive near-ideal parameters within the constraints of the functional form, while also discussing best practices and weighting methods for parameterization routes.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2021)
Article
Biochemistry & Molecular Biology
Jessica L. Thomaston, Marley L. Samways, Athina Konstantinidi, Chunlong Ma, Yanmei Hu, Hannah E. Bruce Macdonald, Jun Wang, Jonathan W. Essex, William F. DeGrado, Antonios Kolocouris
Summary: Studies have shown that there are slight differences in the way (R)- and (S)-rimantadine bind to the M2 WT channel, but this does not affect the drug's efficacy or binding kinetics.
Review
Chemistry, Medicinal
Pietro G. A. Aronica, Lauren M. Reid, Nirali Desai, Jianguo Li, Stephen J. Fox, Shilpa Yadahalli, Jonathan W. Essex, Chandra S. Verma
Summary: The evolution of antibiotic-resistant bacteria has led to an increase in untreatable diseases, highlighting the urgent need for alternative treatment methods. Antimicrobial peptides (AMPs) have attracted significant interest, with their design and development aided by molecular models and computational approaches can aid experimental studies in this area.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2021)
Article
Chemistry, Physical
Joao Morado, Paul N. Mortenson, J. Willem M. Nissink, Marcel L. Verdonk, Richard A. Ward, Jonathan W. Essex, Chris-Kriton Skylaris
Summary: Conformational analysis is crucial in drug design, and molecular mechanics simulation methods are used to generate ensembles of structures to provide reliable structural information. Reparameterizing the force field can generate FFs that closely reproduce QM results, and the MC acceptance rate is strongly correlated with various phase space overlap measurements, serving as a robust metric to evaluate the similarity between MM and QM levels of theory.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2021)
Article
Chemistry, Physical
Yunhui Ge, David C. Wych, Marley L. Samways, Michael E. Wall, Jonathan W. Essex, David L. Mobley
Summary: This study focuses on the accuracy and efficiency of several molecular dynamics (MD simulation-based methods) in rehydrating buried water sites. The results suggest that BLUES and grand methods enhance water sampling relative to normal MD, with grand being more robust than BLUES.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2022)
Article
Chemistry, Physical
Miroslav Suruzhon, Michael S. Bodnarchuk, Antonella Ciancetta, Ian D. Wall, Jonathan W. Essex
Summary: The sampling problem is a widely studied topic in computational chemistry. In this work, an alchemical variation of adaptive sequential Monte Carlo (SMC) is presented, and it is applied to various test cases, showing efficient exploration of targeted degrees of freedom. Alchemical SMC is a promising tool for preparatory exploration of systems.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2022)
Article
Genetics & Heredity
Eleanor G. Seaby, Steven Turner, David J. Bunyan, Fariba Seyed-Rezai, Jonathan Essex, Rodney D. Gilbert, Sarah Ennis
Summary: This study discusses a case of a 10-year-old girl who presented with leg pain and elevated creatinine. Further investigations confirmed renal Fanconi syndrome (RFS) in the girl and identified a novel pathogenic variant in the GATM gene. The findings suggest the importance of screening the GATM gene in children with RFS, in addition to adults.
Article
Chemistry, Medicinal
Marley L. Samways, Hannah E. Bruce Macdonald, Richard D. Taylor, Jonathan W. Essex
Summary: Water molecules at protein-ligand interfaces play a crucial role in drug design. Predicting the location of water molecules in the absence of a crystal structure is important, and GCMC has shown promise in accurately predicting water binding locations. This study demonstrates that GCMC can correctly predict a significant proportion of nonbulk crystallographic water sites, and the number of hydrogen bonds and electron density of the water molecules are factors that influence the accuracy of prediction.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Chemistry, Physical
Oliver J. Melling, Marley L. Samways, Yunhui Ge, David L. Mobley, Jonathan W. Essex
Summary: Water molecules are crucial in biomolecular systems, especially at protein-ligand interfaces. However, simulating such systems is challenging due to slow water exchange between protein and solvent. To overcome this, the authors combine grand canonical Monte Carlo (GCMC) with nonequilibrium candidate Monte Carlo (NCMC) to develop grand canonical nonequilibrium candidate Monte Carlo (GCNCMC). This approach improves water sampling efficiency and enables the exploration of new ligand-binding geometries mediated by water.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2023)
Article
Multidisciplinary Sciences
Xiaojie Yu, Christian M. Orr, H. T. Claude Chan, Sonya James, Christine A. Penfold, Jinny Kim, Tatyana Inzhelevskaya, C. Ian Mockridge, Kerry L. Cox, Jonathan W. Essex, Ivo Tews, Martin J. Glennie, Mark S. Cragg
Summary: Low affinity of immunomodulatory antibodies leads to greater activity through increased clustering, resulting in higher immune cell activation, T cell expansion, and antitumor activity. This discovery reveals a new mechanism for enhancing receptor activation across diverse receptor families and sheds light on the mechanism of antibody-mediated receptor signaling. Affinity engineering offers a rational, efficient, and tunable solution for delivering antibody-mediated receptor activity for the treatment of human disease.
Article
Chemistry, Medicinal
Joao Morado, Paul N. Mortenson, J. Willem M. Nissink, Jonathan W. Essex, Chris-Kriton Skylaris
Summary: We present a comparative study on the performance of different molecular models in simulating the stability and properties of 10 gamma-fluorohydrins. The results show that the ANI-2x model tends to predict stronger hydrogen bonding and overstabilize global minima, while conventional force fields still play an important role in condensed-phase simulations. This study provides guidelines for the future development and application of force fields and machine learning potentials.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Chemistry, Physical
Vilhelm Ekberg, Marley L. Samways, Majda Misini Ignjatovic, Jonathan W. Essex, Ulf Ryde
Summary: Water molecules play crucial roles in biochemical processes, so it is vital to understand their structure and properties around proteins. This study compares different computational methods for modeling water molecules and their energetics. The results show that GCMC/MD simulations accelerate the sampling and equilibration of water molecules, while GIST analysis improves the precision of energy calculations.
ACS PHYSICAL CHEMISTRY AU
(2022)
Article
Chemistry, Physical
Javier Caceres-Delpiano, Lee-Ping Wang, Jonathan W. Essex
Summary: Atomistic models provide detailed representation of molecular systems, but may not be sufficient for simulating large systems over long timescales. Coarse-grained models accelerate simulations by reducing degrees of freedom, with some loss in accuracy. New optimization processes for parameterizing these models could improve their quality and applicability range.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2021)
Review
Chemistry, Multidisciplinary
Marley L. Samways, Richard D. Taylor, Hannah E. Bruce Macdonald, Jonathan W. Essex
Summary: The review highlights the fundamental importance of water molecules at drug-protein interfaces and discusses the challenges and advantages of experimental and computational methods to analyze their role in drug binding. It provides a critical analysis of experimental data used to validate computational methods and suggests directions for future research to address the fundamental difficulties of each method.
CHEMICAL SOCIETY REVIEWS
(2021)
