Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
The improvement in the ability of the pharmaceutical industry to predict human pharmacokinetic behavior are attributable to major technological shifts from 1990 to the present day. The opportunity for the application of AI/ML based approaches in the ...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
ADMET (absorption, distribution, metabolism, excretion, and toxicity) describes a drug molecule's pharmacokinetics and pharmacodynamics properties. ADMET profile of a bioactive compound can impact its efficacy and safety. Moreover, efficacy and safet...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
Deep learning applied to antibody development is in its adolescence. Low data volumes and biological platform differences make it challenging to develop supervised models that can predict antibody behavior in actual commercial development steps. But ...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
Machine learning (ML) already accelerates discoveries in many scientific fields and is the driver behind several new products. Recently, growing sample sizes enabled the use of ML approaches in larger omics studies. This work provides a guide through...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
Development of computer-aided de novo design methods to discover novel compounds in a speedy manner to treat human diseases has been of interest to drug discovery scientists for the past three decades. In the beginning, the efforts were mostly concen...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
The discovery and development of drugs is a long and expensive process with a high attrition rate. Computational drug discovery contributes to ligand discovery and optimization, by using models that describe the properties of ligands and their intera...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
Artificial intelligence has seen an incredibly fast development in recent years. Many novel technologies for property prediction of drug molecules as well as for the design of novel molecules were introduced by different research groups. These artifi...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
Artificial intelligence (AI) consists of a synergistic assembly of enhanced optimization strategies with wide application in drug discovery and development, providing advanced tools for promoting cost-effectiveness throughout drug life cycle. Specifi...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
Ultrahigh-throughput virtual screening (uHTVS) is an emerging field linking together classical docking techniques with high-throughput AI methods. We outline mechanistic docking models' goals and successes. We present different AI accelerated workflo...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
In the latest years, the application of deep generative models to suggest virtual compounds is becoming a new and powerful tool in drug discovery projects. The idea behind this review is to offer an updated view on de novo design approaches based on ...