EncoderMap(II): Visualizing Important Molecular Motions with Improved Generation of Protein Conformations
Sign Up to like & getrecommendations! Published in 2019 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.9b00675
Abstract: Dimensionality reduction can be used to project high-dimensional molecular data into a simplified, low-dimensional map. One feature of our recently introduced dimensionality reduction technique EncoderMap, which relies on the combination of an autoencoder with multidimensional… read more here.
Keywords: high dimensional; low dimensional; protein conformations; encodermap ... See more keywords
Novel Big Data-Driven Machine Learning Models for Drug Discovery Application
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DOI: 10.3390/molecules27030594
Abstract: Most contemporary drug discovery projects start with a ‘hit discovery’ phase where small chemicals are identified that have the capacity to interact, in a chemical sense, with a protein target involved in a given disease.… read more here.
Keywords: machine learning; drug discovery; protein conformations; drug ... See more keywords
Using Big Data Analytics to “Back Engineer” Protein Conformational Selection Mechanisms
Sign Up to like & getrecommendations! Published in 2022 at "Molecules"
DOI: 10.3390/molecules27082509
Abstract: In the living cells, proteins bind small molecules (or “ligands”) through a “conformational selection” mechanism, where a subset of protein structures are capable of binding the small molecules well while most other protein structures are… read more here.
Keywords: conformational selection; big data; small molecules; protein conformations ... See more keywords