Databases, Pharmaceutical

A multi-conformational virtual screening approach based on machine learning targeting PI3Kγ.

Molecular diversity 34160714

Nowadays, more and more attention has been attracted to develop selective PI3Kγ inhibitors, but the unique structural features of PI3Kγ protein make it a very big challenge. In the present study, a virtual screening strategy based on machine learning...

Binding Sites Class Ib Phosphatidylinositol 3-Kinase Databases, Pharmaceutical Drug Discovery Ligands Machine Learning Models, Molecular Molecular Conformation Molecular Docking Simulation Molecular Dynamics Simulation Molecular Structure Phosphoinositide-3 Kinase Inhibitors Protein Binding ROC Curve Structure-Activity Relationship

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Machine learning models to select potential inhibitors of acetylcholinesterase activity from SistematX: a natural products database.

Molecular diversity 34132933

Alzheimer's disease is the most common form of dementia, representing 60-70% of dementia cases. The enzyme acetylcholinesterase (AChE) cleaves the ester bonds in acetylcholine and plays an important role in the termination of acetylcholine activity a...

Acetylcholinesterase Algorithms Area Under Curve Biological Products Cheminformatics Cholinesterase Inhibitors Databases, Pharmaceutical Drug Discovery Humans Machine Learning Models, Molecular Molecular Docking Simulation Molecular Dynamics Simulation ROC Curve Structure-Activity Relationship Workflow

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Applications of artificial intelligence to drug design and discovery in the big data era: a comprehensive review.

Molecular diversity 34110579

Artificial intelligence (AI) renders cutting-edge applications in diverse sectors of society. Due to substantial progress in high-performance computing, the development of superior algorithms, and the accumulation of huge biological and chemical data...

Algorithms Artificial Intelligence Big Data Data Mining Databases, Pharmaceutical Drug Design Drug Discovery Humans Models, Molecular Models, Theoretical Protein Binding Protein Folding Protein Interaction Mapping Proteins Structure-Activity Relationship Workflow

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Support Vector Machine as a Supervised Learning for the Prioritization of Novel Potential SARS-CoV-2 Main Protease Inhibitors.

International journal of molecular sciences 34299333

In the last year, the COVID-19 pandemic has highly affected the lifestyle of the world population, encouraging the scientific community towards a great effort on studying the infection molecular mechanisms. Several vaccine formulations are nowadays a...

Antiviral Agents Coronavirus Protease Inhibitors COVID-19 COVID-19 Drug Treatment Databases, Pharmaceutical Drug Evaluation, Preclinical Humans Molecular Docking Simulation Molecular Dynamics Simulation Pandemics SARS-CoV-2 Small Molecule Libraries Supervised Machine Learning Support Vector Machine Viral Nonstructural Proteins Viral Proteases

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Identification of kinase inhibitors that rule out the CYP27B1-mediated activation of vitamin D: an integrated machine learning and structure-based drug designing approach.

Molecular diversity 34272637

CYP27B1, a cytochrome P450-containing hydroxylase enzyme, converts vitamin D precursor calcidiol (25-hydroxycholecalciferol) to its active form calcitriol (1α,25(OH)D). Tyrosine kinase inhibitor such as imatinib is reported to interfere with the acti...

25-Hydroxyvitamin D3 1-alpha-Hydroxylase Algorithms Amino Acid Sequence Animals Binding Sites Databases, Pharmaceutical Drug Design Enzyme Inhibitors Humans Machine Learning Metabolic Networks and Pathways Models, Molecular Molecular Docking Simulation Molecular Dynamics Simulation Neural Networks, Computer Phosphotransferases Protein Binding Reproducibility of Results Small Molecule Libraries Structure-Activity Relationship Support Vector Machine Vitamin D

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Ensemble learning application to discover new trypanothione synthetase inhibitors.

Molecular diversity 34264440

Trypanosomatid-caused diseases are among the neglected infectious diseases with the highest disease burden, affecting about 27 million people worldwide and, in particular, socio-economically vulnerable populations. Trypanothione synthetase (TryS) is ...

Algorithms Amide Synthases Antiprotozoal Agents Databases, Pharmaceutical Drug Discovery Drug Evaluation, Preclinical Enzyme Inhibitors Humans Machine Learning Metabolic Networks and Pathways Models, Theoretical ROC Curve Structure-Activity Relationship

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Prediction of Anti-Glioblastoma Drug-Decorated Nanoparticle Delivery Systems Using Molecular Descriptors and Machine Learning.

International journal of molecular sciences 34768951

The theoretical prediction of drug-decorated nanoparticles (DDNPs) has become a very important task in medical applications. For the current paper, Perturbation Theory Machine Learning (PTML) models were built to predict the probability of different ...

Antineoplastic Agents Brain Neoplasms Databases, Chemical Databases, Pharmaceutical Drug Carriers Drug Delivery Systems Drug Design Drug Screening Assays, Antitumor Glioblastoma Humans Machine Learning Nanoparticles User-Computer Interface

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Classification of beta-site amyloid precursor protein cleaving enzyme 1 inhibitors by using machine learning methods.

Chemical biology & drug design 34592057

The beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) is a transmembrane aspartyl-protease, that cleaves amyloid precursor protein (APP) at the β-site. The sequential proteolytic cleavage of APP, first by β-secretase and then by γ-secreta...

Amyloid Precursor Protein Secretases Aspartic Acid Endopeptidases Bayes Theorem Databases, Pharmaceutical Humans Machine Learning Models, Theoretical Molecular Structure Protease Inhibitors Reproducibility of Results

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De novo generation of dual-target ligands using adversarial training and reinforcement learning.

Briefings in bioinformatics 34410338

Artificial intelligence, such as deep generative methods, represents a promising solution to de novo design of molecules with the desired properties. However, generating new molecules with biological activities toward two specific targets remains an ...

Algorithms Artificial Intelligence Biomarkers Chemical Phenomena Databases, Pharmaceutical Deep Learning Drug Design Drug Discovery Ligands Proteins Structure-Activity Relationship

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IFPTML Mapping of Drug Graphs with Protein and Chromosome Structural Networks vs. Pre-Clinical Assay Information for Discovery of Antimalarial Compounds.

International journal of molecular sciences 34884870

The parasite species of genus causes Malaria, which remains a major global health problem due to parasite resistance to available Antimalarial drugs and increasing treatment costs. Consequently, computational prediction of new Antimalarial compounds...

Algorithms Antimalarials Databases, Pharmaceutical Drug Discovery Drug Evaluation, Preclinical Genome, Protozoan Machine Learning Markov Chains Models, Theoretical Plasmodium falciparum Protozoan Proteins Reproducibility of Results

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AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

A multi-conformational virtual screening approach based on machine learning targeting PI3Kγ.

Machine learning models to select potential inhibitors of acetylcholinesterase activity from SistematX: a natural products database.

Applications of artificial intelligence to drug design and discovery in the big data era: a comprehensive review.

Support Vector Machine as a Supervised Learning for the Prioritization of Novel Potential SARS-CoV-2 Main Protease Inhibitors.

Identification of kinase inhibitors that rule out the CYP27B1-mediated activation of vitamin D: an integrated machine learning and structure-based drug designing approach.

Ensemble learning application to discover new trypanothione synthetase inhibitors.

Prediction of Anti-Glioblastoma Drug-Decorated Nanoparticle Delivery Systems Using Molecular Descriptors and Machine Learning.

Classification of beta-site amyloid precursor protein cleaving enzyme 1 inhibitors by using machine learning methods.

De novo generation of dual-target ligands using adversarial training and reinforcement learning.

IFPTML Mapping of Drug Graphs with Protein and Chromosome Structural Networks vs. Pre-Clinical Assay Information for Discovery of Antimalarial Compounds.

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