AIMC Topic: Drug Design

Clear Filters Showing 461 to 470 of 632 articles

Convex-PL: a novel knowledge-based potential for protein-ligand interactions deduced from structural databases using convex optimization.

Journal of computer-aided molecular design Sep 18, 2017
We present a novel optimization approach to train a free-shape distance-dependent protein-ligand scoring function called Convex-PL. We do not impose any functional form of the scoring function. Instead, we decompose it into a polynomial basis and ded...
Protein Conformation Binding Sites Molecular Structure Knowledge Bases Ligands Molecular Docking Simulation Drug Design Protein Binding Proteins Databases, Protein Structure-Activity Relationship Humans Machine Learning Algorithms
View on PubMed DOI

From machine learning to deep learning: progress in machine intelligence for rational drug discovery.

Drug discovery today Sep 4, 2017
Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional...
Humans Drug Discovery Models, Theoretical Quantitative Structure-Activity Relationship Artificial Intelligence Machine Learning Drug Design
View on PubMed DOI

Novel Method Proposing Chemical Structures with Desirable Profile of Activities Based on Chemical and Protein Spaces.

Molecular informatics Aug 30, 2017
Active molecules among numerous chemical structures in a chemical database can be searched easily by statistical prediction of compound-protein interactions. However, constructing a simple prediction model against one protein does not aid drug design...
Humans Neural Networks, Computer Drug Design Protein Kinases Databases, Chemical
View on PubMed DOI

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

Bioorganic & medicinal chemistry Jul 8, 2017
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...
Peptides Computer-Aided Design Drug Design Antimicrobial Cationic Peptides Models, Molecular Machine Learning Anti-Infective Agents Animals Humans
View on PubMed DOI

Medical capsule robots: A renaissance for diagnostics, drug delivery and surgical treatment.

Journal of controlled release : official journal of the Controlled Release Society Jul 8, 2017
The advancements in electronics and the progress in nanotechnology have resulted in path breaking development that will transform the way diagnosis and treatment are carried out currently. This development is Medical Capsule Robots, which has emerged...
Drug Design Robotics Equipment Design Drug Delivery Systems Animals Drug Liberation Gastrointestinal Tract Capsule Endoscopes Humans
View on PubMed DOI

Influence of Varying Training Set Composition and Size on Support Vector Machine-Based Prediction of Active Compounds.

Journal of chemical information and modeling Apr 10, 2017
Support vector machine (SVM) modeling is one of the most popular machine learning approaches in chemoinformatics and drug design. The influence of training set composition and size on predictions currently is an underinvestigated issue in SVM modelin...
Support Vector Machine Drug Design
View on PubMed DOI

Bayesian molecular design with a chemical language model.

Journal of computer-aided molecular design Mar 9, 2017
The aim of computational molecular design is the identification of promising hypothetical molecules with a predefined set of desired properties. We address the issue of accelerating the material discovery with state-of-the-art machine learning techni...
Machine Learning Bayes Theorem Computer-Aided Design Software Models, Chemical Monte Carlo Method Computer Simulation Drug Design Pharmaceutical Preparations Small Molecule Libraries Molecular Structure
View on PubMed DOI

Creating the New from the Old: Combinatorial Libraries Generation with Machine-Learning-Based Compound Structure Optimization.

Journal of chemical information and modeling Feb 15, 2017
The growing computational abilities of various tools that are applied in the broadly understood field of computer-aided drug design have led to the extreme popularity of virtual screening in the search for new biologically active compounds. Most ofte...
Small Molecule Libraries Machine Learning Databases, Pharmaceutical Computer-Aided Design Combinatorial Chemistry Techniques Drug Design
View on PubMed DOI

Predicting DPP-IV inhibitors with machine learning approaches.

Journal of computer-aided molecular design Feb 2, 2017
Dipeptidyl peptidase IV (DPP-IV) is a promising Type 2 diabetes mellitus (T2DM) drug target. DPP-IV inhibitors prolong the action of glucagon-like peptide-1 (GLP-1) and gastric inhibitory peptide (GIP), improve glucose homeostasis without weight gain...
Diabetes Mellitus, Type 2 Bayes Theorem Dipeptidyl Peptidase 4 Small Molecule Libraries Dipeptidyl-Peptidase IV Inhibitors Molecular Docking Simulation Computer-Aided Design Drug Design Humans Machine Learning
View on PubMed DOI

Machine learning and docking models for Mycobacterium tuberculosis topoisomerase I.

Tuberculosis (Edinburgh, Scotland) Jan 20, 2017
There is a shortage of compounds that are directed towards new targets apart from those targeted by the FDA approved drugs used against Mycobacterium tuberculosis. Topoisomerase I (Mttopo I) is an essential mycobacterial enzyme and a promising target...
Mycobacterium smegmatis DNA Topoisomerases, Type I Topoisomerase I Inhibitors Dose-Response Relationship, Drug Molecular Targeted Therapy Molecular Docking Simulation Structure-Activity Relationship Humans Protein Conformation Antitubercular Agents Computer-Aided Design Bayes Theorem Machine Learning Tuberculosis Drug Design Mycobacterium tuberculosis
View on PubMed DOI
Popular Topics
Recent Journals