AIMC Topic: Crystallization

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Graph Neural Networks with Multi-features for Predicting Cocrystals using APIs and Coformers Interactions.

Current medicinal chemistry Jan 1, 2024
INTRODUCTION: Active pharmaceutical ingredients (APIs) have gained direct pharmaceutical interest, along with their in vitro properties, and thus utilized as auxiliary solid dosage forms upon FDA guidance and approval on pharmaceutical cocrystals whe...
Pharmaceutical Preparations Crystallization Neural Networks, Computer
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Sequence-based prediction model of protein crystallization propensity using machine learning and two-level feature selection.

Briefings in bioinformatics Sep 20, 2023
Protein crystallization is crucial for biology, but the steps involved are complex and demanding in terms of external factors and internal structure. To save on experimental costs and time, the tendency of proteins to crystallize can be initially det...
Computational Biology Amino Acid Sequence Algorithms Machine Learning Crystallization
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Combining machine learning and molecular simulations to predict the stability of amorphous drugs.

The Journal of chemical physics Jul 7, 2023
Amorphous drugs represent an intriguing option to bypass the low solubility of many crystalline formulations of pharmaceuticals. The physical stability of the amorphous phase with respect to the crystal is crucial to bring amorphous formulations into...
Solubility Machine Learning Drug Stability Crystallization Drug Design
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Binary salt structure classification with convolutional neural networks: Application to crystal nucleation and melting point calculations.

The Journal of chemical physics Nov 28, 2022
Convolutional neural networks are constructed and validated for the crystal structure classification of simple binary salts such as the alkali halides. The inputs of the neural network classifiers are the local bond orientational order parameters of ...
Sodium Chloride Crystallization Neural Networks, Computer Molecular Dynamics Simulation Alkalies
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SADeepcry: a deep learning framework for protein crystallization propensity prediction using self-attention and auto-encoder networks.

Briefings in bioinformatics Sep 20, 2022
The X-ray diffraction (XRD) technique based on crystallography is the main experimental method to analyze the three-dimensional structure of proteins. The production process of protein crystals on which the XRD technique relies has undergone multiple...
Crystallization Crystallography, X-Ray Attention Deep Learning Proteins
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Machine learning on ligand-residue interaction profiles to significantly improve binding affinity prediction.

Briefings in bioinformatics Sep 2, 2021
Structure-based virtual screenings (SBVSs) play an important role in drug discovery projects. However, it is still a challenge to accurately predict the binding affinity of an arbitrary molecule binds to a drug target and prioritize top ligands from ...
Ligands Crystallization Drug Evaluation, Preclinical Protein Kinases Molecular Structure Humans Deep Learning Protein Binding Databases, Protein Receptors, G-Protein-Coupled Molecular Docking Simulation Drug Discovery Algorithms
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DeepCrystal: a deep learning framework for sequence-based protein crystallization prediction.

Bioinformatics (Oxford, England) Jul 1, 2019
MOTIVATION: Protein structure determination has primarily been performed using X-ray crystallography. To overcome the expensive cost, high attrition rate and series of trial-and-error settings, many in-silico methods have been developed to predict cr...
Proteins Deep Learning Amino Acid Sequence Computational Biology Crystallization
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Formulation and solid state characterization of carboxylic acid-based co-crystals of tinidazole: An approach to enhance solubility.

Polimery w medycynie Jan 1, 2018
BACKGROUND: Tinidazole (TNZ) is an anti-parasite drug used in the treatment of a variety of amebic and parasitic infections. It has low solubility in aqueous media and is categorized under Class II of the Biopharmaceutical Classification System.
Carboxylic Acids Solubility Tinidazole Crystallization Spectroscopy, Fourier Transform Infrared Calorimetry, Differential Scanning
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Crystallization and X-ray diffraction of an ectoine hydroxylase from Bacillus pseudofirmus OF4.

Wei sheng wu xue bao = Acta microbiologica Sinica Nov 4, 2015
OBJECTIVE: To study crystallization and X-Ray diffraction of ectoine hydroxylase from Bacillus pseudofirmus OF4.
Crystallization Sequence Alignment Bacillus Bacterial Proteins Amino Acid Sequence X-Ray Diffraction Molecular Sequence Data Amino Acids, Diamino Mixed Function Oxygenases
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