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Thermodynamics

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Recent developments in multiscale free energy simulations.

Current opinion in structural biology
Physics-based free energy simulations enable the rigorous calculation of properties, such as conformational equilibria, solvation or binding free energies. While historically most applications have occurred at the atomistic level of resolution, a ran...

Machine-Learning-Assisted Free Energy Simulation of Solution-Phase and Enzyme Reactions.

Journal of chemical theory and computation
Despite recent advances in the development of machine learning potentials (MLPs) for biomolecular simulations, there has been limited effort on developing stable and accurate MLPs for enzymatic reactions. Here we report a protocol for performing mach...

In silico screening of ssDNA aptamer against Escherichia coli O157:H7: A machine learning and the Pseudo K-tuple nucleotide composition based approach.

Computational biology and chemistry
This study was planned to in silico screening of ssDNA aptamer against Escherichia coli O157:H7 by combination of machine learning and the PseKNC approach. For this, firstly a total numbers of 47 validated ssDNA aptamers as well as 498 random DNA seq...

Rosetta:MSF:NN: Boosting performance of multi-state computational protein design with a neural network.

PloS one
Rational protein design aims at the targeted modification of existing proteins. To reach this goal, software suites like Rosetta propose sequences to introduce the desired properties. Challenging design problems necessitate the representation of a pr...

Machine Learning Directed Optimization of Classical Molecular Modeling Force Fields.

Journal of chemical information and modeling
Accurate force fields are necessary for predictive molecular simulations. However, developing force fields that accurately reproduce experimental properties is challenging. Here, we present a machine learning directed, multiobjective optimization wor...

Multitask machine learning models for predicting lipophilicity (logP) in the SAMPL7 challenge.

Journal of computer-aided molecular design
Accurate prediction of lipophilicity-logP-based on molecular structures is a well-established field. Predictions of logP are often used to drive forward drug discovery projects. Driven by the SAMPL7 challenge, in this manuscript we describe the steps...

Machine Learning and Enhanced Sampling Simulations for Computing the Potential of Mean Force and Standard Binding Free Energy.

Journal of chemical theory and computation
Computational capabilities are rapidly increasing, primarily because of the availability of GPU-based architectures. This creates unprecedented simulative possibilities for the systematic and robust computation of thermodynamic observables, including...

Autonomous Low-Reynolds-Number Soft Robots with Structurally Encoded Motion and Their Thermodynamic Efficiency.

Langmuir : the ACS journal of surfaces and colloids
Soft low-Reynolds-number robotics hold the potential to significantly impact numerous fields including drug delivery, sensing, and diagnostics. Realizing this potential is predicated upon the ability to design soft robots tailored to their intended f...

Valorization of groundnut shell via pyrolysis: Product distribution, thermodynamic analysis, kinetic estimation, and artificial neural network modeling.

Chemosphere
Pyrolysis of agricultural biomass is a promising technique for producing renewable energy and effectively managing solid waste. In this study, groundnut shell (GNS) was processed at 500 °C in an inert gas atmosphere with a gas flow rate and a heating...

VirtualFlow Ants-Ultra-Large Virtual Screenings with Artificial Intelligence Driven Docking Algorithm Based on Ant Colony Optimization.

International journal of molecular sciences
The docking program PLANTS, which is based on ant colony optimization (ACO) algorithm, has many advanced features for molecular docking. Among them are multiple scoring functions, the possibility to model explicit displaceable water molecules, and th...