Computational and Experimental Approaches for Discovery and Development of New Products
A special issue of Molecules (ISSN 1420-3049).
Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 3451
Special Issue Editor
Interests: computational molecular modeling with applications to drug discovery; mechanisms of neurodegenerative diseases; neurotoxicology
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Computational and advanced experimental methods have become indispensable for the discovery and development of new products, such as pharmaceutical agents, agricultural chemicals, disinfectants, and exotic materials.
Computational tools include ligand-based and structure-based approaches, combinations of the two, and varying degrees of augmentation with quantum mechanics (QM), molecular mechanics (MM), and molecular dynamics (MD).
Ligand-based screening directs its focus toward intrinsic properties of small molecules and how to use these characteristics to predict compounds with a desired biological activity. Structure-based screening examines interactions of ligands with macromolecular targets to understand and predict the biological effect of interest.
Advanced experimental techniques include high-throughput technologies such as robotic systems to enable rapid acquisition of laboratory data and its computational analysis using modern omics methodologies.
Together, in silico and automated laboratory techniques make it possible to assess the potential of extremely large numbers of compounds at greatly reduced cost and much higher speed than would be possible with traditional wet lab procedures.
Nevertheless, the accuracy of computational approaches remains in need of improvement. To address the accuracy issue, recent advances in theory, software, and hardware appear to hold great promise. In particular, the emerging fields of artificial intelligence (AI) and machine learning (ML) are being applied to virtual screening with good effect. At the same time, commercial and open-source molecular modeling software continue to improve and to be increasingly accessible with respect to cost and ease of use. Similarly, ongoing advances in hardware, including CPUs and GPUs, are enabling compute-intensive processes such as molecular dynamics (MD) simulations to be carried out routinely on desktop workstations or on a larger scale using supercomputers or cloud-based high-performance clusters.
The goal of this Special Issue is to bring together a collection of high-quality research and review articles highlighting diverse facets of computational and/or advanced experimental approaches with applications in the discovery and development of new products.
Prof. Dr. Rudy J. Richardson
Guest Editor
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Keywords
- virtual screening
- computational molecular modeling
- ligand-based screening
- structure-based screening
- high-throughput experimental/laboratory screening
- artificial intelligence (AI)
- machine learning (ML)
- computer technology (CPUs, GPUs, connectivity)
- cheminformatics
- bioinformatics
- epigenomics, genomics, metabolomics, proteomics, transcriptomics
- similarity searching
- pharmacophore mapping
- molecular docking
- ensemble docking
- inverse docking
- molecular databases
- interference with protein–protein interactions
- proteolysis-targeting chimeras (PROTACs)
- molecular modeling software
- small-molecule databases
- macromolecular target databases
- alpha fold
- Protein Data Bank (PDB)
- cambridge crystallographic data center (CCDC)
- drug repurposing
- quantitative structure–activity relationships (QSAR)
- computational and experimental design of drugs, crop protectants, disinfectants, and exotic materials
- quantum chemistry (ab initio and semi-empirical) applied to product design
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