AIMC Topic: Drug Discovery

Clear Filters Showing 721 to 730 of 1558 articles

Machine learning and deep learning in data-driven decision making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry.

Future medicinal chemistry Dec 23, 2021
Predicting novel small molecule bioactivities for the target deconvolution, hit-to-lead optimization in drug discovery research, requires molecular representation. Previous reports have demonstrated that machine learning (ML) and deep learning (DL) h...
Deep Learning Decision Making Drug Repositioning Drug Industry Blood-Brain Barrier Drug Delivery Systems Drug Discovery Humans Artificial Intelligence Machine Learning
View on PubMed DOI

Machine learning prediction of antiviral-HPV protein interactions for anti-HPV pharmacotherapy.

Scientific reports Dec 21, 2021
Persistent infection with high-risk types Human Papillomavirus could cause diseases including cervical cancers and oropharyngeal cancers. Nonetheless, so far there is no effective pharmacotherapy for treating the infection from high-risk HPV types, a...
Humans Machine Learning Viral Proteins Papillomaviridae Papillomavirus Infections Area Under Curve Algorithms Bayes Theorem Drug Discovery Antiviral Agents
View on PubMed DOI

Wet-dry-wet drug screen leads to the synthesis of TS1, a novel compound reversing lung fibrosis through inhibition of myofibroblast differentiation.

Cell death & disease Dec 17, 2021
Therapies halting the progression of fibrosis are ineffective and limited. Activated myofibroblasts are emerging as important targets in the progression of fibrotic diseases. Previously, we performed a high-throughput screen on lung fibroblasts and s...
Lung Diseases Transfection High-Throughput Screening Assays Myofibroblasts Drug Screening Assays, Antitumor Cell Differentiation Mice Idiopathic Pulmonary Fibrosis Bleomycin Humans Machine Learning Animals Drug Discovery
View on PubMed DOI

Can Generative-Model-Based Drug Design Become a New Normal in Drug Discovery?

Journal of medicinal chemistry Dec 16, 2021
It is still rare that AI application examples with full DMTA (Design, Make, Test, Analysis) outcomes are reported. A recent study highlights that a generative model could be applied in the drug discovery process through an example in which ideas gene...
Drug Design Drug Discovery Deep Learning Humans Neural Networks, Computer Artificial Intelligence
View on PubMed DOI

Explainable Machine Learning for Property Predictions in Compound Optimization.

Journal of medicinal chemistry Dec 13, 2021
The prediction of compound properties from chemical structure is a main task for machine learning (ML) in medicinal chemistry. ML is often applied to large data sets in applications such as compound screening, virtual library enumeration, or generati...
Machine Learning Algorithms Drug Discovery Chemistry, Pharmaceutical Libraries, Digital
View on PubMed DOI

Optimization: Molecular Communication Networks for Viral Disease Analysis Using Deep Leaning Autoencoder.

Computational and mathematical methods in medicine Dec 13, 2021
Developing new treatments for emerging infectious diseases in infectious and noninfectious diseases has attracted a particular attention. The emergence of viral diseases is expected to accelerate; these data indicate the need for a proactive approach...
Communicable Diseases, Emerging Drug Delivery Systems Humans Antiviral Agents Drug Discovery Synthetic Biology Neural Networks, Computer Deep Learning Computational Biology Computer Simulation Microtechnology Epidemics Virus Diseases
View on PubMed DOI

Updated Prediction of Aggregators and Assay-Interfering Substructures in Food Compounds.

Journal of agricultural and food chemistry Dec 8, 2021
Positive outcomes in biochemical and biological assays of food compounds may appear due to the well-described capacity of some compounds to form colloidal aggregates that adsorb proteins, resulting in their denaturation and loss of function. This phe...
Databases, Factual Machine Learning Drug Discovery Proteins Biological Assay
View on PubMed DOI

ACP-MHCNN: an accurate multi-headed deep-convolutional neural network to predict anticancer peptides.

Scientific reports Dec 8, 2021
Although advancing the therapeutic alternatives for treating deadly cancers has gained much attention globally, still the primary methods such as chemotherapy have significant downsides and low specificity. Most recently, Anticancer peptides (ACPs) h...
Deep Learning ROC Curve Computational Biology Peptides Humans Drug Discovery Amino Acid Sequence Neural Networks, Computer Antineoplastic Agents Chemical Phenomena Algorithms Reproducibility of Results
View on PubMed DOI

Drug-Target Interaction Prediction: End-to-End Deep Learning Approach.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2021
The discovery of potential Drug-Target Interactions (DTIs) is a determining step in the drug discovery and repositioning process, as the effectiveness of the currently available antibiotic treatment is declining. Although putting efforts on the tradi...
Machine Learning Algorithms Drug Discovery Humans Neural Networks, Computer Deep Learning Drug Repositioning Computational Biology Pharmaceutical Preparations Proteins Amino Acid Sequence
View on PubMed DOI

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 Dec 2, 2021
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 Reproducibility of Results Drug Discovery Machine Learning Protozoan Proteins Databases, Pharmaceutical Drug Evaluation, Preclinical Antimalarials Markov Chains Models, Theoretical Plasmodium falciparum Genome, Protozoan
View on PubMed DOI
Popular Topics
Recent Journals