Results 61 to 70 of about 21,282 (192)

From Membrane Composition to Antimicrobial Strategies: Experimental and Computational Approaches to AMP Design and Selectivity

Small, EarlyView.
Antimicrobial peptides (AMPs) are promising candidates for next‐generation antibiotics, acting through mechanisms such as membrane disruption and intracellular targeting. This review examines how variations in bacterial membrane composition critically influence AMP activity.
Paolo Rossetti, Marius F.W. Trollmann, Christina Wichmann, Thomas Gutsmann, Christian Eggeling, Rainer A. Böckmann   +5 more
wiley   +1 more source

The application of chemical similarity measures in an unconventional modeling framework c-RASAR along with dimensionality reduction techniques to a representative hepatotoxicity dataset

Scientific Reports
With the exponential progress in the field of cheminformatics, the conventional modeling approaches have so far been to employ supervised and unsupervised machine learning (ML) and deep learning models, utilizing the standard molecular descriptors, which
Arkaprava Banerjee, Kunal Roy
doaj   +1 more source

Multifunctional polyimide performance prediction based on explainable machine learning

Smart Molecules, EarlyView.
Utilizing interpretable machine learning algorithms to develop predictive models for the glass transition temperature, cut‐off wavelength, and coefficient of thermal expansion of polyimides can assist in the design of novel high‐performance polyimides.
Suisui Wang, Tianyong Zhang, Han Zhang, Wenxuan Zhu, Zixu Gu, Xufeng Huang, Hande Zhang, Bin Li, Jianhua Zhang   +8 more
wiley   +1 more source

Machine learning assisted classification RASAR modeling for the nephrotoxicity potential of a curated set of orally active drugs

Scientific Reports
We have adopted the classification Read-Across Structure–Activity Relationship (c-RASAR) approach in the present study for machine-learning (ML)-based model development from a recently reported curated dataset of nephrotoxicity potential of orally active
Arkaprava Banerjee, Kunal Roy
doaj   +1 more source

Crystallographic fragment screening against SARS‐CoV‐2 nonstructural protein 1 using the F2X‐Entry Screen and a newly developed fragment library

Acta Crystallographica Section D, EarlyView.
Two crystallographic fragment screening campaigns against SARS‐CoV‐2 nonstructural protein 1 resulted in the identification of 21 new hits.Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) continues to threaten global health. This underpins the need for novel therapeutics against this virus.
Frank Lennartz, Jan Wollenhaupt, Melanie Oelker, Paula Fröling, Uwe Mueller, Anke Deckers, Christoph Grathwol, Stefan Bräse, Nicole Jung, Manfred S. Weiss   +9 more
wiley   +1 more source

Artificial intelligence streamlines scientific discovery of drug–target interactions

British Journal of Pharmacology, EarlyView.
Abstract Drug discovery is a complicated process through which new therapeutics are identified to prevent and treat specific diseases. Identification of drug–target interactions (DTIs) stands as a pivotal aspect within the realm of drug discovery and development. The traditional process of drug discovery, especially identification of DTIs, is marked by
Yuxin Yang, Feixiong Cheng
wiley   +1 more source

A comprehensive review of cluster methods for drug–drug interaction network

Quantitative Biology, Volume 14, Issue 1, March 2026.
Abstract The detection of drug–drug interaction (DDI) is crucial to the rational use of drug combinations. Experimentally, DDI detection is time‐consuming and laborious. Currently, researchers have developed a variety of computational methods to predict DDI.
Shuyuan Cao, Guixia Liu, Xiangrun Zhou, Ji Lv   +3 more
wiley   +1 more source

Chemoinformatics and Drug Discovery

Molecules, 2002
This article reviews current achievements in the field of chemoinformatics and their impact on modern drug discovery processes. The main data mining approaches used in cheminformatics, such as descriptor computations, structural similarity matrices, and ...
Arnold Hagler, Jun Xu
doaj   +1 more source

The Generated Databases (GDBs) as a Source of 3D-shaped Building Blocks for Use in Medicinal Chemistry and Drug Discovery

CHIMIA, 2020
Drug discovery is in constant need of new molecules to develop drugs addressing unmet medical needs. To assess the chemical space available for drug design, our group investigates the generated databases (GDBs) listing all possible organic molecules up ...
Kris Meier, Sven Bühlmann, Josep Arus-Pous, Jean-Louis Reymond   +3 more
doaj   +1 more source

Most Ligand-Based Classification Benchmarks Reward Memorization Rather than Generalization

, 2018
Undetected overfitting can occur when there are significant redundancies between training and validation data. We describe AVE, a new measure of training-validation redundancy for ligand-based classification problems that accounts for the similarity ...
Heifets, Abraham, Wallach, Izhar
core   +3 more sources