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H2020Individual fellowship2018–2020

UBioRec · Development and Testing of a Reference Computational Platform for Understanding Biomolecular Recognition

Horizon 2020 — Marie Skłodowska-Curie Actions

Duration
2018-06-01 → 2020-05-31
EU contribution
€195,455
Participants
1
Scheme
MSCA-IF-EF-ST

Lines connect the coordinator with its partners.

Results in brief

Development and Testing of a Reference Computational Platform for Understanding BiomolecularRecognition

The binding of ligands to pharmaceutical targets is a dynamical event and molecular simulations are uniquely powerful in their ability to track the behavior of ligand-target interactions at atomic resolution across different time scales. The promise of the approach has been demonstrated by the successful MD-based design of new drugs such as HIV integrase inhibitors. Nowadays, thanks to improved algorithms and hardware MD simulations are used to address the many open questions about the details of molecular recognition between protein-ligand complexes that affects the field of Drug Discovery, becoming an essential tool for the discovery of new medicines. However, accurate molecular dynamics simulations are expensive and the right balance between accuracy and time to solution has to be found to increase their usefulness in drug discovery. The aim of our project was to further develop and test simulations-based models and algorithms to find an effective balance for drug discovery. The Covid-19 pandemic has dramatically reaffirmed the importance of science in general and drug discovery in particular for the society. The UBioRec project by providing effective computational algorithms to study drug binding mechanisms and accurately quantify the binding affinity of ligands to their targets addresses a fundamental aspect of rational drug discovery. The platform that has been designed, developed and made available during the project can be used by academic and industrial groups to accelerate the development of drug candidates. The advantage of the molecular dynamics based algorithms developed in UBioRec, with respect to static (docking based) ones that are typically used is that they take into account all the structural changes that occur during the binding process, and therefore are more accurate and lead to a better understanding of the binding mechanism. This fundamental knowledge is crucial to efficiently develop potent and effective drug candidates. The overall objectives of UBioRec project were the following: • Test and combine different enhanced sampling algorithms with the most recently developed force fields and by means of QM/MM calculations. The achievement of this aim let us to comprehend the binding mechanism of the reference targets selected. • Understand the thermodynamics and kinetics of the binding mechanisms. • To make the methods and results obtained widely available to the scientific community through a platform. The data generated such as inputs, scripts and algorithms developed have been made publicly available in different repositories. Also, the benchmark data will be available through a platform where all the data will be available. The performance, maintenance and update of this platform will be carried out beyond to the finish of this project in order to become a much-needed reference for academic and industrial groups in the field.

Data: CORDIS, © European Union

Project objective

Due to its fundamental regulatory role, molecular recognition has been extensively studied by both experiments andsimulations. During the last 30 years impressive technical advances allowed significant progress in understanding molecularrecognition mechanisms. However, the matter is far from settled and contradictory reports are still appearing in the literature.Lately, I have been studying these processes using a combination of computational and experimental approaches indifferent systems. Here I propose to study several representative model systems in great details, taking advantages of new force fields, DFT functionals and enhanced sampling algorithms recently emerged. These systems are small enough to allow the use of state-of-the-art simulation techniques; still they are sufficiently complex not only to mimic the behaviour of far larger systems but also to use apparently different mechanisms. Indeed, their molecular recognition needs complex conformational changes, the re-arrangementof water molecules in the binding cavity, and an active role of the ligand in the binding/release mechanisms. The overarchingobjective of my proposal is to learn the state-of-the-art enhanced sampling techniques developed at UCL and combine themwith QM/MM approaches to: i) understand how bio-molecular recognition works in both isoforms, ii) fully characterize thethermodynamics and kinetic processes that govern them and iii) validate the computational approaches against high-qualityexperimental data. If successful, the in-depth understanding of the molecular binding mechanism will shed light on anintriguing and important biological system and provide a much needed benchmark to the computational community. Thischallenging but feasible project will have a far reaching impact on a number of H2020 priority areas, including drug discoveryand bio-molecular engineering.

Original text from CORDIS.

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Data: CORDIS, © European Union