Repository-wide screening for bioactivity and protein binding using small molecule mass spectrometry data

Descripción del proyecto

Espectros de masas en tándem para la detección de compuestos bioactivos y proteínas diana

La unión a proteínas es un factor clave en la bioactividad de un compuesto, ya que determina si se comportará como agente terapéutico o como toxina. Las pequeñas moléculas desconocidas en muestras biológicas se identifican mediante la anotación de compuestos utilizando la espectrometría de masas en tándem. En este contexto, el equipo del proyecto BindingShadows, financiado por el Consejo Europeo de Investigación, elaborará modelos de aprendizaje automático que predigan si una molécula pequeña desconocida es bioactiva o se une a una proteína específica basándose en los espectros de masas en tándem de la molécula. A continuación, aplicará estos modelos en el cribado de millones de espectros de masas en tándem de los conjuntos de datos disponibles. Estos métodos se compartirán a través de una plataforma en la que los usuarios podrán obtener información sobre bioactividad sin necesidad de análisis computacionales o experimentales adicionales.

Objetivo

Bioactivity and ligand binding remain central topics for understanding protein function, for drug discovery and toxicology. Mass spectrometry (MS) allows to detect thousands of small molecules in a biological sample with a single experimental run. Compound annotation is carried out using tandem MS. I will develop machine learning models that predict whether a query small molecule has a certain bioactivity or is binding to a certain protein, where the only information we have about the query molecule is its tandem mass spectra. The identity and molecular structure of the query small molecule is unknown; it is unknown to the models, to me, and potentially even to mankind. Clearly, bioactivity and binding are two flavors of the same problem, and the differentiation is solely driven by the available training data. Notably, elucidating the structure of the small molecule is not the focus of the project, and may be postponed until after experimental confirmation. Models will not predict one particular bioactivity or protein binding, but rather tens in parallel. Evolution has, through variation and selection, optimized the structure of small molecules for tasks such as communication and warfare, and the pool of natural products is enriched with bioactive compounds. My project will allow to harvest the information.

I will apply my models at a repository scale, screening millions of tandem MS spectra in thousands of datasets for small molecules that are most likely to have bioactivity or to bind. I will also make my methods available through our well-established SIRIUS platform, allowing users to derive information about bioactivity without the need of additional experiments. I will enable the worldwide community to hunt for drug leads or unknown toxic compounds, without the need of additional experiments or computational analyses. Finally, being able to find small molecules that bind to a protein can provide helpful information to understand protein function.