AI Medical Compendium Journal:
Bioorganic & medicinal chemistry

Showing 1 to 10 of 10 articles

Rational design and synthesis of pyrazole derivatives as potential SARS-CoV-2 M inhibitors: An integrated approach merging combinatorial chemistry, molecular docking, and deep learning.

Bioorganic & medicinal chemistry
The global impact of SARS-CoV-2 has highlighted the urgent need for novel antiviral therapies. This study integrates combinatorial chemistry, molecular docking, and deep learning to design, evaluate and synthesize new pyrazole derivatives as potentia...

Effects of data quality and quantity on deep learning for protein-ligand binding affinity prediction.

Bioorganic & medicinal chemistry
Prediction of protein-ligand binding affinities is crucial for computational drug discovery. A number of deep learning approaches have been developed in recent years to improve the accuracy of such affinity prediction. While the predicting power of t...

A computer-aided drug design approach to discover tumour suppressor p53 protein activators for colorectal cancer therapy.

Bioorganic & medicinal chemistry
Colorectal cancer (CRC) is the third most detected cancer and the second foremost cause of cancer deaths in the world. Intervention targeting p53 provides potential therapeutic strategies, but thus far no p53-based therapy has been successfully trans...

CYPlebrity: Machine learning models for the prediction of inhibitors of cytochrome P450 enzymes.

Bioorganic & medicinal chemistry
The vast majority of approved drugs are metabolized by the five major cytochrome P450 (CYP) isozymes, 1A2, 2C9, 2C19, 2D6 and 3A4. Inhibition of CYP isozymes can cause drug-drug interactions with severe pharmacological and toxicological consequences....

Identification of SARS-CoV-2 viral entry inhibitors using machine learning and cell-based pseudotyped particle assay.

Bioorganic & medicinal chemistry
In response to the pandemic caused by SARS-CoV-2, we constructed a hybrid support vector machine (SVM) classification model using a set of publicly posted SARS-CoV-2 pseudotyped particle (PP) entry assay repurposing screen data to identify novel pote...

Machine learning-enabled discovery and design of membrane-active peptides.

Bioorganic & medicinal chemistry
Antimicrobial peptides are a class of membrane-active peptides that form a critical component of innate host immunity and possess a diversity of sequence and structure. Machine learning approaches have been profitably employed to efficiently screen s...

Highly predictive and interpretable models for PAMPA permeability.

Bioorganic & medicinal chemistry
Cell membrane permeability is an important determinant for oral absorption and bioavailability of a drug molecule. An in silico model predicting drug permeability is described, which is built based on a large permeability dataset of 7488 compound ent...

Synthesis of new analogs of AKBA and evaluation of their anti-inflammatory activities.

Bioorganic & medicinal chemistry
A new series of 11-keto-β-boswellic acid and 3-O-acetyl-11-keto-β-boswellic acid analogs (5, 7, 8, 10, 13, 18a-d, 27a-c, 28a-d) were synthesized by modification of hydroxyl and acid functional moieties of boswellic acids. The structures of these anal...

Bayesian models trained with HTS data for predicting β-haematin inhibition and in vitro antimalarial activity.

Bioorganic & medicinal chemistry
A large quantity of high throughput screening (HTS) data for antimalarial activity has become available in recent years. This includes both phenotypic and target-based activity. Realising the maximum value of these data remains a challenge. In this r...