Artificial intelligence-aided protein engineering: from topological data analysis to deep protein language models
Protein engineering is an emerging field in biotechnology that has the potential to
revolutionize various areas, such as antibody design, drug discovery, food security, ecology …
revolutionize various areas, such as antibody design, drug discovery, food security, ecology …
Methodology-centered review of molecular modeling, simulation, and prediction of SARS-CoV-2
Despite tremendous efforts in the past two years, our understanding of severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2), virus–host interactions, immune …
respiratory syndrome coronavirus 2 (SARS-CoV-2), virus–host interactions, immune …
Chemistry-informed molecular graph as reaction descriptor for machine-learned retrosynthesis planning
Infusing “chemical wisdom” should improve the data-driven approaches that rely exclusively
on historical synthetic data for automatic retrosynthesis planning. For this purpose, we …
on historical synthetic data for automatic retrosynthesis planning. For this purpose, we …
[HTML][HTML] Combination of linear solvation energy and linear free-energy relationships to aid the prediction of reaction kinetics: application to the solvolysis of 5-HMF by …
EE Munoz, DDM Di Bucchianico… - … Research and Design, 2024 - Elsevier
In the context of cellulose valorization, we studied the kinetics of levulinates synthesis via the
solvolysis of 5-HMF by alcohol over Amberlite IR-120. The alcohol plays a double role; it is a …
solvolysis of 5-HMF by alcohol over Amberlite IR-120. The alcohol plays a double role; it is a …
A Fast and Interpretable Deep Learning Approach for Accurate Electrostatics-Driven pKa Predictions in Proteins
Existing computational methods for estimating p K a values in proteins rely on theoretical
approximations and lengthy computations. In this work, we use a data set of 6 million …
approximations and lengthy computations. In this work, we use a data set of 6 million …
Methods for Theoretical Treatment of Local Fields in Proteins and Enzymes
Electric fields generated by protein scaffolds are crucial in enzymatic catalysis. This review
surveys theoretical approaches for detecting, analyzing, and comparing electric fields …
surveys theoretical approaches for detecting, analyzing, and comparing electric fields …
Calculation of solvation force in molecular dynamics simulation by deep-learning method
J Liao, M Wu, J Gao, C Chen - Biophysical Journal, 2024 - cell.com
Electrostatic calculations are generally used in studying the thermodynamics and kinetics of
biomolecules in solvent. Generally, this is performed by solving the Poisson-Boltzmann …
biomolecules in solvent. Generally, this is performed by solving the Poisson-Boltzmann …
Bridging eulerian and lagrangian poisson–boltzmann solvers by eses
Abstract The Poisson–Boltzmann (PB) model is a widely used electrostatic model for
biomolecular solvation analysis. Formulated as an elliptic interface problem, the PB model …
biomolecular solvation analysis. Formulated as an elliptic interface problem, the PB model …
Optimized parallelization of boundary integral Poisson-Boltzmann solvers
Abstract The Poisson-Boltzmann (PB) model governs the electrostatics of solvated
biomolecules, ie, potential, field, energy, and force. These quantities can provide useful …
biomolecules, ie, potential, field, energy, and force. These quantities can provide useful …
SurfPB: A GPU-Accelerated Electrostatic Calculation and Visualization Tool for Biomolecules
J Liao, Z Shu, J Gao, M Wu, C Chen - Journal of Chemical …, 2023 - ACS Publications
In this work, we present SurfPB as a useful tool for the study of biomolecules. It can do many
typical calculations, including the molecular surface, electrostatic potential, solvation free …
typical calculations, including the molecular surface, electrostatic potential, solvation free …