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Structure-Activity Relationship

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Cytotoxicity of chitosan/streptokinase nanoparticles as a function of size: An artificial neural networks study.

Nanomedicine : nanotechnology, biology, and medicine
Predicting the size and toxicity of chitosan/streptokinase nanoparticles at various values of processing parameters was the aim of this study. For the first time, a comprehensive model could be developed to determine the cytotoxicity of the nanoparti...

Multistage virtual screening and identification of novel HIV-1 protease inhibitors by integrating SVM, shape, pharmacophore and docking methods.

European journal of medicinal chemistry
The HIV-1 protease has proven to be a crucial component of the HIV replication machinery and a reliable target for anti-HIV drug discovery. In this study, we applied an optimized hierarchical multistage virtual screening method targeting HIV-1 protea...

The study of dual COX-2/5-LOX inhibitors by using electronic-topological approach based on data on the ligand-receptor interactions.

Journal of molecular graphics & modelling
Structural and electronic factors influencing selective inhibition of cyclooxygenase-2 and 5-lipoxygenase (COX-2/5-LOX) were studied by using Electronic-Topological Method combined with Neural Networks (ETM-NN), molecular docking, and Density Functio...

Machine learning assisted design of highly active peptides for drug discovery.

PLoS computational biology
The discovery of peptides possessing high biological activity is very challenging due to the enormous diversity for which only a minority have the desired properties. To lower cost and reduce the time to obtain promising peptides, machine learning ap...

Systematic artifacts in support vector regression-based compound potency prediction revealed by statistical and activity landscape analysis.

PloS one
Support vector machines are a popular machine learning method for many classification tasks in biology and chemistry. In addition, the support vector regression (SVR) variant is widely used for numerical property predictions. In chemoinformatics and ...

Types and effects of protein variations.

Human genetics
Variations in proteins have very large number of diverse effects affecting sequence, structure, stability, interactions, activity, abundance and other properties. Although protein-coding exons cover just over 1 % of the human genome they harbor an di...

Three- and four-class classification models for P-glycoprotein inhibitors using counter-propagation neural networks.

SAR and QSAR in environmental research
P-glycoprotein (P-gp) is an ATP binding cassette (ABC) transporter that helps to protect several certain human organs from xenobiotic exposure. This efflux pump is also responsible for multi-drug resistance (MDR), an issue of the chemotherapy approac...

Active-learning strategies in computer-assisted drug discovery.

Drug discovery today
High-throughput compound screening is time and resource consuming, and considerable effort is invested into screening compound libraries, profiling, and selecting the most promising candidates for further testing. Active-learning methods assist the s...

Machine Learning Techniques to Infer Protein Structure and Function from Sequences: A Comprehensive Review.

Methods in molecular biology (Clifton, N.J.)
The elucidation of protein structure and function plays a pivotal role in understanding biological processes and facilitating drug discovery. With the exponential growth of protein sequence data, machine learning techniques have emerged as powerful t...

Fighting COVID-19 with Artificial Intelligence.

Methods in molecular biology (Clifton, N.J.)
The development of vaccines for the treatment of COVID-19 is paving the way for new hope. Despite this, the risk of the virus mutating into a vaccine-resistant variant still persists. As a result, the demand of efficacious drugs to treat COVID-19 is ...