Publications by authors named "E Hantz"

Machine learning (ML) has revolutionised the field of structure-based drug design (SBDD) in recent years. During the training stage, ML techniques typically analyse large amounts of experimentally determined data to create predictive models in order to inform the drug discovery process. Deep learning (DL) is a subfield of ML, that relies on multiple layers of a neural network to extract significantly more complex patterns from experimental data, and has recently become a popular choice in SBDD.

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Despite large investments from academia and industry, heart failure, which results from a disruption of the contractile apparatus, remains a leading cause of death. Cardiac muscle contraction is a calcium-dependent mechanism, which is regulated by the troponin protein complex (cTn) and specifically by the N-terminal domain of its calcium-binding subunit (cNTnC). There is an increasing need for the development of small molecules that increase calcium sensitivity without altering the systolic calcium concentration, thereby strengthening the cardiac function.

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Despite large investments from academia and industry, heart failure, which results from a disruption of the contractile apparatus, remains a leading cause of death. Cardiac muscle contraction is a calcium-dependent mechanism, which is regulated by the troponin protein complex (cTn) and specifically by the N-terminal domain of its calcium binding subunit (cNTnC). There is an increasing need for the development of small molecules that increase calcium sensitivity without altering systolic calcium concentration, thereby strengthening cardiac function.

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Calcium-dependent heart muscle contraction is regulated by the cardiac troponin protein complex (cTn) and specifically by the N-terminal domain of its calcium binding subunit (cNTnC). cNTnC contains one calcium binding site (site II), and altered calcium binding in this site has been studied for decades. It has been previously shown that cNTnC mutants, which increase calcium sensitization may have therapeutic benefits, such as restoring cardiac muscle contractility and functionality post-myocardial infarction events.

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Computer-aided drug design, an important component of the early stages of the drug discovery pipeline, routinely identifies large numbers of false positive hits that are subsequently confirmed to be experimentally inactive compounds. We have developed a methodology to improve true positive prediction rates in structure-based drug design and have successfully applied the protocol to twenty target systems and identified the top three performing conformers for each of the targets. Receptor performance was evaluated based on the area under the curve of the receiver operating characteristic curve for two independent sets of known actives.

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