Results 131 to 140 of about 36,144 (247)
<p>QMRF and QPRF reporting extension to OpenTox ruby modules and lazar.<br> The QSAR-report gem was developed to extend the lazar and nano-lazar toxicity prediction application with QMRF and QPRF reporting features.<br> The library gem ...
Rautenberg, Micha +5 more
core +1 more source
AI is reshaping the design and modeling of organic electrochemical energy materials, from redox‐active molecules to polymer electrolytes. Progress across data‐driven prediction, machine‐learning interatomic potentials, generative models, and agentic workflows is assessed, while persistent challenges in data quality, polymer representation, validation ...
Zhan‐Yun Zhang +7 more
wiley +1 more source
Smart Design: Integrating Artificial Intelligence and Gene Editing for Advanced mRNA Therapeutics
The challenges of mRNA therapy and the application of artificial intelligence and gene editing in the field of mRNA drugs. ABSTRACT Artificial intelligence (AI) and gene editing are increasingly being applied to the design and evaluation of mRNA therapeutics.
Haixing Shi +11 more
wiley +1 more source
Little is known about the estrogenic activities of polycyclic aromatic hydrocarbons (PAHs) and the underlying mechanisms on estrogenic activities are still unclear.
core +1 more source
Preventing and reducing the spread of HIV (HIV) has always been a concern in medical science. One of the most common ways to control the virus is using enzyme-blocking drugs. In this study, we attempted to predict the biological activity (PKi) of organic
Zakiyeh Bayat +1 more
doaj
IDH mutation is an important event in hematological malignancies. This review systematically integrates the basic mechanism of IDH mutations and combines it with the clinical translation of related research progress. It also discusses the application strategies of IDH inhibitors and feasible research directions, with the aim of providing a theoretical ...
Jinkun Xu, Haiying Bai, Lijuan Hu
wiley +1 more source
A literature review of QSPR approaches to predict jet fuel properties. It exposes the fundamental principles of QSPR and illustrates pure‐compound QSPR through examples of applications for jet fuel components. Mixture‐QSPR (M‐QSPR) modeling specificities are addressed: mixtures representation, design of descriptors for mixtures, and impact on internal ...
Erik Yeghyan +3 more
wiley +1 more source
Predicting the Toxicity of Chemical Compounds via Hyperdimensional Computing
Hyperdimensional computing converts text representations of chemical structures (SMILES) into high‐dimensional vectors. New compounds are classified by comparison with learned toxic and nontoxic reference patterns; across 12 Tox21 targets, overlapping four‐character SMILES patterns performed best among tested representations, supporting fast ...
Fabio Cumbo +6 more
wiley +1 more source
Artificial Intelligence-enabled cheminformatics approaches in Ayurveda-based drug discovery
Ayurveda contains a vast and diverse collection of botanicals, minerals, and classical formulations. Each Ayurvedic medicine often includes multiple components that act together on different biological pathways. This holistic approach naturally fits with
Aviral Apurva, Abhimanyu Kumar
doaj +1 more source
This narrative review analyzes DENV molecular targets, including structural proteins (C, prM/M, E), non‐structural components (NS1NS5), and host factors, alongside small‐molecule candidates in preclinical and clinical phases. Owing to high structural conservation, the NS2B‐NS3 protease and NS5 (RdRp/MTase) remain primary drug discovery focuses, while ...
Aryane Lucia da Silva Aguiar De Oliveira +8 more
wiley +1 more source

