AIMC Topic: Thermodynamics

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A deep learning approach for the blind logP prediction in SAMPL6 challenge.

Journal of computer-aided molecular design Jan 30, 2020
Water octanol partition coefficient serves as a measure for the lipophilicity of a molecule and is important in the field of drug discovery. A novel method for computational prediction of logarithm of partition coefficient (logP) has been developed u...
Solubility Thermodynamics Octanols Water Molecular Structure Models, Chemical Machine Learning Drug Discovery Deep Learning
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Quantification of interfacial energies associated with membrane fouling in a membrane bioreactor by using BP and GRNN artificial neural networks.

Journal of colloid and interface science Jan 7, 2020
Interfacial energy between sludge foulants and rough membrane surface critically determines adhesive fouling in membrane bioreactors (MBRs). As a current available method, the advanced extensive Derjaguin-Landau-Verwey-Overbeek (XDLVO) approach canno...
Surface Properties Neural Networks, Computer Membranes, Artificial Particle Size Thermodynamics Bioreactors
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Robust Prediction of Single and Multiple Point Protein Mutations Stability Changes.

Biomolecules Dec 31, 2019
Accurate prediction of protein stability changes resulting from amino acid substitutions is of utmost importance in medicine to better understand which mutations are deleterious, leading to diseases, and which are neutral. Since conducting wet lab ex...
Proteins Databases, Protein Amino Acids Neural Networks, Computer Machine Learning Point Mutation Protein Stability Thermodynamics
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Predicting RNA secondary structure via adaptive deep recurrent neural networks with energy-based filter.

BMC bioinformatics Dec 24, 2019
BACKGROUND: RNA secondary structure prediction is an important issue in structural bioinformatics, and RNA pseudoknotted secondary structure prediction represents an NP-hard problem. Recently, many different machine-learning methods, Markov models, a...
Nucleic Acid Conformation Base Pairing Thermodynamics Neural Networks, Computer RNA
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Latest trends in structure based drug design with protein targets.

Advances in protein chemistry and structural biology Dec 18, 2019
Structure based drug designing is an important endeavor in the field of structural bioinformatics. Previously the entire process was dependent on the wet-lab experiments to build libraries of ligand molecules. And the molecules used to be tested to d...
Ligands Binding Sites Thermodynamics Structure-Activity Relationship Molecular Dynamics Simulation Drugs, Investigational Antineoplastic Agents Anti-HIV Agents Protein Binding Computational Biology Neuroprotective Agents Proteins Anti-Bacterial Agents Molecular Docking Simulation Drug Design Humans Machine Learning
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Finding Reactive Configurations: A Machine Learning Approach for Estimating Energy Barriers Applied to Sirtuin 5.

Journal of chemical theory and computation Nov 25, 2019
Sirtuin 5 is a class III histone deacetylase that, unlike its classification, mainly catalyzes desuccinylation and demanoylation reactions. It is an interesting drug target that we use here to test new ideas for calculating reaction pathways of large...
Thermodynamics Molecular Dynamics Simulation Sirtuins Quantum Theory Humans Protein Conformation Machine Learning
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Convolutional Neural Networks for the Design and Analysis of Non-Fullerene Acceptors.

Journal of chemical information and modeling Nov 21, 2019
Convolutional neural network (CNN) is employed to construct generative and prediction models for the design and analysis of non-fullerene acceptors (NFAs) in organic solar cells. It is demonstrated that the dilated causal CNN can be trained as a good...
Neural Networks, Computer Drug Design Organic Chemicals Solar Energy Thermodynamics Electric Power Supplies
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Prediction of P-glycoprotein inhibitors with machine learning classification models and 3D-RISM-KH theory based solvation energy descriptors.

Journal of computer-aided molecular design Nov 19, 2019
Development of novel in silico methods for questing novel PgP inhibitors is crucial for the reversal of multi-drug resistance in cancer therapy. Here, we report machine learning based binary classification schemes to identify the PgP inhibitors from ...
Small Molecule Libraries Humans Solvents Machine Learning Drug Discovery ATP Binding Cassette Transporter, Subfamily B, Member 1 Thermodynamics
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MathDL: mathematical deep learning for D3R Grand Challenge 4.

Journal of computer-aided molecular design Nov 16, 2019
We present the performances of our mathematical deep learning (MathDL) models for D3R Grand Challenge 4 (GC4). This challenge involves pose prediction, affinity ranking, and free energy estimation for beta secretase 1 (BACE) as well as affinity ranki...
Humans Molecular Docking Simulation Ligands Small Molecule Libraries Cathepsins Amyloid Precursor Protein Secretases Drug Design Binding Sites Aspartic Acid Endopeptidases Deep Learning Thermodynamics Protein Binding
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Exploring fragment-based target-specific ranking protocol with machine learning on cathepsin S.

Journal of computer-aided molecular design Nov 15, 2019
Cathepsin S (CatS), a member of cysteine cathepsin proteases, has been well studied due to its significant role in many pathological processes, including arthritis, cancer and cardiovascular diseases. CatS inhibitors have been included in D3R-GC3 for...
Machine Learning Molecular Docking Simulation Computer-Aided Design Protein Binding Databases, Protein Ligands Binding Sites Humans Crystallography, X-Ray Thermodynamics Protein Conformation Cathepsins
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