Accurate prediction of binding affinities from protein-ligand atomic coordinates remains a major challenge in early stages of drug discovery. Using modular message passing graph neural networks describing both the ligand and the protein in their free...
A typical drug discovery project involves identifying active compounds with significant binding potential for selected disease-specific targets. Experimental high-throughput screening (HTS) is a traditional approach to drug discovery, but is expensiv...
Natural products (NPs) constitute a large reserve of bioactive compounds useful for drug development. Recent advances in high-throughput technologies facilitate functional analysis of therapeutic effects and NP-based drug discovery. However, the larg...
Virtual screening-based approaches to discover initial hit and lead compounds have the potential to reduce both the cost and time of early drug discovery stages, as well as to find inhibitors for even challenging target sites such as protein-protein ...
Bioorganic & medicinal chemistry letters
May 12, 2022
This paper deals with a critical examination on the possibility of quantitatively predicting the in vivo activity of new chemical entities (NCEs) by making use of in silico and in vitro data including three-dimensional structure of drug-target comple...
Signal transduction and targeted therapy
May 10, 2022
Artificial intelligence is an advanced method to identify novel anticancer targets and discover novel drugs from biology networks because the networks can effectively preserve and quantify the interaction between components of cell systems underlying...
Humans are exposed to numerous compounds daily, some of which have adverse effects on health. Computational approaches for modeling toxicological data in conjunction with machine learning algorithms have gained popularity over the last few years. Mac...
In recent years, drug-induced nephrotoxicity has been one of the main reasons for the failure of drug development. Early prediction of the nephrotoxicity for drug candidates is critical to the success of clinical trials. Therefore, it is very importa...
Chemical communications (Cambridge, England)
Apr 28, 2022
The discovery of new molecules and materials helps expand the horizons of novel and innovative real-life applications. In pursuit of finding molecules with desired properties, chemists have traditionally relied on experimentation and recently on comb...
This review is focused on several machine learning approaches used in chemoinformatics. Machine learning approaches provide tools and algorithms to improve drug discovery. Many physicochemical properties of drugs like toxicity, absorption, drug-drug ...
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