Molecular dynamics-driven drug discovery: leaping forward with confidence

Aravindhan Ganesan, Michelle L. Coote, Khaled Barakat
2017 Drug Discovery Today  
1 Given the high costs and time in developing a commercial drug, it remains important to 2 constantly reform the drug discovery pipeline with novel technologies that can narrow 3 down on the most promising lead compounds for clinical testing. The past decade has 4 witnessed tremendous growth in computational capabilities that allow in silico approaches 5 to expedite drug discovery processes. Molecular dynamics (MD) has become a particularly 6 important tool in drug design and discovery. From
more » ... ssical MD methods to more 7 sophisticated hybrid classical/quantum mechanical approaches, MD simulations are now 8 able to offer extraordinary insights into ligand-receptor interactions. In this review, we 9 discuss how the applications of MD approaches are significantly transforming the current 10 drug discovery and development efforts. 11 12 13 14 15 combinatorial chemistry field. For instance, some of the schemes for addressing the lack 1 of diversity were developed; and this includes diversity-oriented synthesis[7], which 2 employs a "build/couple/pair strategy" [8]. In addition, strategies, such as 'split and pool 3 solid phase synthesis', were developed as more powerful approach for synthesizing huge 4 combinatorial chemistry. Despite many efforts, the field of combinatorial chemistry has 5 still not reached its full capacity. Kodadek[9] discusses various recent advances in the 6 combinatorial chemistry. This has led to a focus on computational methods as low-cost 7 tools for driving the early search process for compounds with desired biological activity 8 and pharmacological profiles, before initiating experiments. 9 10 Structure-based drug design (SBDD) is one of the vital computational approaches that has 11 been found to be very effective in the identification of hits for in-vitro testing. As the name 12 indicates, in principle, knowledge of the three-dimensional structures of proteins and the 13 ligands are mandatory to perform SBDD. Recently, there has been dramatic accumulation 14 of biological data, from gene sequences to three-dimensional structures of proteins and 15 compound databases, which offers excellent support to SBDD research. As of June 2016, 16 the Protein Data Bank (PDB) (www.pdb.org) contains more than one hundred thousand 17 experimentally-determined (e.g., via X-ray, NMR and electron microscopy) protein 18 structures, of which almost 26% correspond to human proteins. The UniProtKB/Swiss-Prot 19 genome database (www.uniprot.org) contains ~540,000 amino acid sequences. These huge 20 databases offer a gamut of potential targets for several human diseases. Moreover, when 21 the experimentally-determined 3D structures of any proteins (or enzymes) are not available 22
doi:10.1016/j.drudis.2016.11.001 pmid:27890821 fatcat:k4hkw2mklfbg5dle24vsy5r5me