An explainability framework for deep learning on chemical reactions exemplified by enzyme-catalysed reaction classification

Publications associées (29)

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Physics-Inspired Structural Representations for Molecules and Materials

Michele Ceriotti, Félix Benedito Clément Musil, Andrea Grisafi

The first step in the construction of a regression model or a data-driven analysis, aiming to predict or elucidate the relationship between the atomic-scale structure of matter and its properties, involves transforming the Cartesian coordinates of the atom ...

AMER CHEMICAL SOC2021

NICEdrug.ch, a workflow for rational drug design and systems-level analysis of drug metabolism

Vassily Hatzimanikatis, Jasmin Maria Hafner, Homa Mohammadi Peyhani, Noushin Hadadi, Anush Chiappino-Pepe

The discovery of a drug requires over a decade of intensive research and financial investments – and still has a high risk of failure. To reduce this burden, we developed the NICEdrug.ch resource, which incorporates 250,000 bioactive molecules, and studied ...

2021

Pharmacological and genetic perturbation establish SIRT5 as a promising target in breast cancer

Johan Auwerx, Bo Li

SIRT5 is a member of the sirtuin family of NAD(+)-dependent protein lysine deacylases implicated in a variety of physiological processes. SIRT5 removes negatively charged malonyl, succinyl, and glutaryl groups from lysine residues and thereby regulates mul ...

SPRINGERNATURE2021

Fast end-to-end learning on protein surfaces

Bruno Emanuel Ferreira De Sousa Correia, Freyr Sverrisson

Proteins' biological functions are defined by the geometric and chemical structure of their 3D molecular surfaces. Recent works have shown that geometric deep learning can be used on mesh-based representations of proteins to identify potential functional s ...

IEEE COMPUTER SOC2021

The Genesis of Molecular Volcano Plots

Matthew Wodrich, Anne-Clémence Corminboeuf, Michael Markus Busch, Boodsarin Sawatlon

For the past two decades, linear free energy scaling relationships and volcano plots have seen frequent use as computational tools that aid in understanding and predicting the catalytic behavior of heterogeneous and electrocatalysts. Based on Sabatier's pr ...

2021

Modeling, predicting and mining metabolism at atom-level resolution

Jasmin Maria Hafner

Living organisms can catalyze many thousands of biochemical reactions that they use to convert energy and matter, which provides them with the essentials for life. The sum of these chemical reactions happening in an organism is called metabo-lism. Understa ...

EPFL2020

Algorithms and flowchart for the design of synthetic biochemical networks

Homa Mohammadi Peyhani

New drugs are needed to assure effective therapies for previously untreated diseases, emerging diseases, and personalized medicine, but the process of drug development is complex, costly, and time-consuming. This is especially problematic considering that ...

EPFL2020

Evaluation of the NAD(+) biosynthetic pathway in ALS patients and effect of modulating NAD(+) levels in hSOD1-linked ALS mouse models

Johan Auwerx

Amyotrophic lateral sclerosis (ALS) is characterized by progressive degeneration of motor neurons. Astrocytes from diverse ALS models induce motor neuron death in co-culture. Enhancing NAD(+) availability, or increasing the expression of the NAD(+)-depende ...

2020

The more the merrier: how homo-oligomerization alters the interactome and function of ribonucleotide reductase

Yimon Aye, Alexandra Krina Van Hall-Beauvais

Stereotyped as a nexus of dNTP synthesis, the dual-subunit enzyme - ribonucleotide reductase (RNR) - is coming into view as a paradigm of oligomerization and moonlighting behavior. In the present issue of `omics', we discuss what makes the larger subunit o ...

ELSEVIER SCI LTD2020

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Evaluation of the NAD(+) biosynthetic pathway in ALS patients and effect of modulating NAD(+) levels in hSOD1-linked ALS mouse models

Johan Auwerx

2020