AIMC Topic: Structure-Activity Relationship

Clear Filters Showing 61 to 70 of 259 articles

1,3,4-oxadiazole derivatives: synthesis, characterization, antifungal activity, DNA binding investigations, TD-DFT calculations, and molecular modelling.

Journal of biomolecular structure & dynamics
1,3,4-Oxadiazole-based heterocyclic analogs (3a-3m) were synthesized cyclization of Schiff bases with substituted aldehydes in the presence of bromine and acetic acid. The structural clarification of synthesized molecules was carried out with variou...

Identification of active compounds as novel dipeptidyl peptidase-4 inhibitors through machine learning and structure-based molecular docking simulations.

Journal of biomolecular structure & dynamics
The enzyme dipeptidyl peptidase 4 (DPP4) is a potential therapeutic target for type 2 diabetes (T2DM). Many synthetic anti-DPP4 medications are available to treat T2DM. The need for secure and efficient medicines has been unmet due to the adverse sid...

Anatomy of Potency Predictions Focusing on Structural Analogues with Increasing Potency Differences Including Activity Cliffs.

Journal of chemical information and modeling
Potency predictions are popular in compound design and optimization but are complicated by intrinsic limitations. Moreover, even for nonlinear methods, activity cliffs (ACs, formed by structural analogues with large potency differences) represent cha...

One-pot multicomponent synthesis of novel pyridine derivatives for antidiabetic and antiproliferative activities.

Future medicinal chemistry
Due to the close relationship of diabetes with hypertension reported in various research, a set of pyridine derivatives with US FDA-approved drug cores were designed and integrated by artificial intelligence. Novel pyridines were designed and synth...

Classification of FLT3 inhibitors and SAR analysis by machine learning methods.

Molecular diversity
FMS-like tyrosine kinase 3 (FLT3) is a type III receptor tyrosine kinase, which is an important target for anti-cancer therapy. In this work, we conducted a structure-activity relationship (SAR) study on 3867 FLT3 inhibitors we collected. MACCS finge...

Introduction to artificial intelligence and deep learning using interactive electronic programming notebooks.

Archiv der Pharmazie
Artificial intelligence (AI), or deep learning (DL), approaches have already found their way into our everyday lives. Furthermore, these methods are a central part of research in the life and natural sciences and have been applied in the form of mach...

Prediction and Structure-Activity Relationship Analysis on Ready Biodegradability of Chemical Using Machine Learning Method.

Chemical research in toxicology
Persistent contaminants from different industries have already caused significant risks to the environment and public health. In this study, a data set containing 1306 not readily biodegradable (NRB) and 622 readily biodegradable (RB) chemicals was c...

Rational design of stapled antimicrobial peptides.

Amino acids
The global increase in antimicrobial drug resistance has dramatically reduced the effectiveness of traditional antibiotics. Structurally diverse antibiotics are urgently needed to combat multiple-resistant bacterial infections. As part of innate immu...

Research progress on the structure and biological diversities of 2-phenylindole derivatives in recent 20 years.

Bioorganic chemistry
The privileged structure binds to multiple receptors with high affinity, which is helpful to the development of new bioactive compounds. Indole is classified as a privileged structure, which may be one of the most important structural categories in d...