AIMC Topic: Hydrophobic and Hydrophilic Interactions

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Physics-based surface patch analysis for prediction of hydrophobic contribution to viscosity of mAbs.

mAbs
The viscosity of monoclonal antibody solutions is critical in their biopharmaceutical application, as it directly influences the ease of subcutaneous injection. Although many descriptors have been developed to enable the prediction of viscosity, the...

Data-Driven Machine Learning Framework for the Regulation of Protein Adsorption on Surfaces.

Langmuir : the ACS journal of surfaces and colloids
Protein adsorption on surfaces is a highly complex process, governed by intricate interactions between protein, surface and surrounding environment. However, accurately predicting protein adsorption amounts and precisely controlling adsorption behavi...

Magnetically Controlled Pollen Microrobots for Underwater Bubble Manipulation-Adhesion, Transport, and Photocontrolled Release.

ACS applied materials & interfaces
The traditional approach has significant limitations in designing and manufacturing high-performance micro-nanorobots with complex three-dimensional structures and response characteristics at the micro-nanoscale, making it difficult to meet practical...

From Liquid SNEDDS to Solid SNEDDS: A Comprehensive Review of Their Development and Pharmaceutical Applications.

The AAPS journal
The liquid and solid formulations of self-nano-emulsifying drug delivery systems (SNEDDS) have garnered significant attention in the pharmaceutical field for their ability to enhance the solubility and absorption of hydrophobic drugs. While both liqu...

Glycolysis-compatible urethanases for polyurethane recycling.

Science (New York, N.Y.)
Recycling thermoset polyurethanes is hindered by their cross-linked structures and chemically stable urethane bonds. Although chemo-enzymatic approaches offer promise, known urethanases remain inefficient under industrial glycolysis conditions. Here,...

AI-Guided Hydrophobic Core Design of Robust Six-Helix Bundle Proteins.

ACS nano
α-Helical domains are widespread and versatile, yet typically fail under low mechanical load because backbone hydrogen bonds unzip sequentially, limiting their use in force-bearing nanomaterials and molecular devices. We present an AI-guided strategy...

Ultrasensitive Detection of m A-Modified RNA Using CRISPR/Cas12a-Integrated Iontronic Biosensor with Hydrophobized Nanochannels: Toward Early Cancer Diagnosis by Machine Learning.

Analytical chemistry
N -methyladenosine (m A), the most prevalent internal modification in eukaryotic RNAs, has emerged as a focal point of intensive research in recent years owing to its pivotal regulatory roles in carcinogenesis, progression, and metastasis. However, c...

Investigate the potential inhibitors of sphingosine kinase 1 (SphK1) with molecular dynamics and artificial intelligence drug design methods.

Journal of molecular modeling
CONTEXT: Sphingosine kinase 1 (SphK1) is a sphingosine kinase that can catalyze the phosphorylation of sphingosine to generate sphingosine-1-phosphate. The J-type channel of SPHK1 plays an important role in processes such as cell signaling. Therefore...

A Machine Learning Model for the Proteome-Wide Prediction of Lipid-Interacting Proteins.

Journal of chemical information and modeling
Lipids are essential metabolites that play critical roles in multiple cellular pathways. Like many primary metabolites, mutations that disrupt lipid synthesis can be lethal. Proteins involved in lipid synthesis, trafficking, and modification, are tar...

Prediction of aggregation in monoclonal antibodies from molecular surface curvature.

Scientific reports
Protein aggregation is one of the key challenges in the biopharmaceutical industry as its control is crucial in achieving long-term stability and efficacy of biopharmaceuticals. Attempts have been made to develop regression models for predicting the ...