Computational structure‐based drug design: Predicting target flexibility
Tipus de documentArticle
Condicions d'accésAccés restringit per política de l'editorial (embargat fins 2019-04-30)
The role of molecular modeling in drug design has experienced a significant revamp in the last decade. The increase in computational resources and molecular models, along with software developments, is finally introducing a competitive advantage in early phases of drug discovery. Medium and small companies with strong focus on computational chemistry are being created, some of them having introduced important leads in drug design pipelines. An important source for this success is the extraordinary development of faster and more efficient techniques for describing flexibility in three‐dimensional structural molecular modeling. At different levels, from docking techniques to atomistic molecular dynamics, conformational sampling between receptor and drug results in improved predictions, such as screening enrichment, discovery of transient cavities, etc. In this review article we perform an extensive analysis of these modeling techniques, dividing them into high and low throughput, and emphasizing in their application to drug design studies. We finalize the review with a section describing our Monte Carlo method, PELE, recently highlighted as an outstanding advance in an international blind competition and industrial benchmarks.
CitacióIglesias, J. [et al.]. Computational structure‐based drug design: Predicting target flexibility. "Wiley Interdisciplinary Reviews: Computational Molecular Science", 29 Abril 2018.
Versió de l'editorhttps://onlinelibrary.wiley.com/doi/pdf/10.1002/wcms.1367
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