Periodic Reporting for period 4 - BioNet (Dynamical Redesign of Biomolecular Networks)
Période du rapport: 2022-01-01 au 2024-01-31
This project includes three main objectives. First and foremost, to go beyond the state-of-the-art, we develop novel enhanced sampling algorithms that enable more efficient biomolecular simulations. Biological processes take place on a much longer timescale than current molecular simulations can be afforded. Therefore, to be able to study these key biomolecular processes, enhanced sampling algorithms are necessary. Here, our objective is to use modern statistical mechanics tools to address this problem and enable our multiscale simulations to reach the required timescales. In addition, novel methods developed will be beneficial to the molecular modelling community.
Secondly, we aim to understand how mechanistic changes affect catalytic reactions. Here we focus on proton transfer coupled phosphate transfer reactions as our main objective, and aim to develop concepts based on generalized electron transfer. We also collaborate with experimental groups to understand structural and electrostatic aspects of catalysis, and here we focus on encapsulation within CBs, and light induced effects using gold nanoparticles.
Our main goal is to understand the catalytic reaction mechanisms in key phosphate catalytic enzymes. To this end, we currently investigate several examples of phosphate catalytic enzymes to identify important structural and mechanistic aspects shared by these systems. We aim to use these underlying principles to design catalytic systems aiding biomedical applications. In particular, this project had a main focus on the catalytic re-activation of oncogenic Ras.
Secondly, we aim to understand how mechanistic changes affect catalytic reactions. Here we focus on proton transfer coupled phosphate transfer reactions as our main objective, and aim to develop concepts based on generalized electron transfer. We also collaborate with experimental groups to understand structural and electrostatic aspects of catalysis, and here we focus on encapsulation within CBs, and light induced effects using gold nanoparticles.
Our main goal is to understand the catalytic reaction mechanisms in key phosphate catalytic enzymes. To this end, we currently investigate several examples of phosphate catalytic enzymes to identify important structural and mechanistic aspects shared by these systems. We aim to use these underlying principles to design catalytic systems aiding biomedical applications. In particular, this project had a main focus on the catalytic re-activation of oncogenic Ras.
WP1: Method development:
We developed methods aiding the understanding underlying the kinetic network for conformational changes in biomolecular systems. We worked in the framework of stochastic simulations that can be discretized and clustered to obtain the kinetically most representative reduced network of lower dimensionality. These types of methods help to capture long timescale behavior by building a tractable network which is computationally more efficient to study. We derived novel relationships between mean first passage times, kinetic rates, and variational properties of dynamical coarse graining approaches.
We also developed novel statistical methods to speed up Monte Carlo simulations using a framework based on irreversible samplers. Our methodology focuses on advancement of MSM-based approaches to determine molecular kinetics.
For biomolecular systems, we developed an AI-aided MLTSA protocol that enables modelling ligand unbinding and analysis of TS-driven CVs for kinetics-driven ligand design.
We published 7 peer-reviewed publications on this topic with Vladimir Koskin, Sam Martino, Pedro Buigues and other collaborators.
Ligand design pipeline was also developed for Ras, and it is currently tested experimentally.
WP2: Catalysis:
We published several joint experimental-computational studies addressing host-guest ligand complexation and molecular interactions with light. Here, one of the examples includes CO2 reduction on gold surface by electrocatalysis, aided via host-guest complexation with CBs. We also analyzed key factors in the rate enhancement for Diels-Alder reactions catalyzed by CB complexation. Here, our computational tools using multiscale quantum classical methods were able to reproduce the catalytic effects accurately for various substrates.
Biological applications:
We have demonstrated that accurate quantum-classical multiscale simulations can reveal the mechanistic details of several phosphate catalytic reactions of biomedical interest. In collaboration with the Cherepanov group at the Crick Institute, we demonstrated that computational methods can help distinguish first and second-generation viral drugs in wild type and drug resistant mutant HIV-1 integrase.
We developed an analysis method using Marcus electron transfer model, to better understand coupled proton transfer processes in phosphate biocatalysis. This work is currently in preparation, with a broad range of examples, including simple SN2 reactions as well as the catalytic reaction of Ras GTP hydrolysis.
WP3: Ras phosphate catalysis
The main focus of this project was to develop a computational framework for designing Ras catalytic activators to reenable the catalytic activity of oncogenic Ras. We established the proton transfer mechanism for Ras, and developed an ML-aided strategy to design activators. This work in published in JACS (2023). Currently, follow up work is performed to design small molecule ligands for catalytic activators, which is tested experimentally.
Additionally, a large structural database is prepared to understand the structural and electrostatic requirements for NTP hydrolysis.
We developed methods aiding the understanding underlying the kinetic network for conformational changes in biomolecular systems. We worked in the framework of stochastic simulations that can be discretized and clustered to obtain the kinetically most representative reduced network of lower dimensionality. These types of methods help to capture long timescale behavior by building a tractable network which is computationally more efficient to study. We derived novel relationships between mean first passage times, kinetic rates, and variational properties of dynamical coarse graining approaches.
We also developed novel statistical methods to speed up Monte Carlo simulations using a framework based on irreversible samplers. Our methodology focuses on advancement of MSM-based approaches to determine molecular kinetics.
For biomolecular systems, we developed an AI-aided MLTSA protocol that enables modelling ligand unbinding and analysis of TS-driven CVs for kinetics-driven ligand design.
We published 7 peer-reviewed publications on this topic with Vladimir Koskin, Sam Martino, Pedro Buigues and other collaborators.
Ligand design pipeline was also developed for Ras, and it is currently tested experimentally.
WP2: Catalysis:
We published several joint experimental-computational studies addressing host-guest ligand complexation and molecular interactions with light. Here, one of the examples includes CO2 reduction on gold surface by electrocatalysis, aided via host-guest complexation with CBs. We also analyzed key factors in the rate enhancement for Diels-Alder reactions catalyzed by CB complexation. Here, our computational tools using multiscale quantum classical methods were able to reproduce the catalytic effects accurately for various substrates.
Biological applications:
We have demonstrated that accurate quantum-classical multiscale simulations can reveal the mechanistic details of several phosphate catalytic reactions of biomedical interest. In collaboration with the Cherepanov group at the Crick Institute, we demonstrated that computational methods can help distinguish first and second-generation viral drugs in wild type and drug resistant mutant HIV-1 integrase.
We developed an analysis method using Marcus electron transfer model, to better understand coupled proton transfer processes in phosphate biocatalysis. This work is currently in preparation, with a broad range of examples, including simple SN2 reactions as well as the catalytic reaction of Ras GTP hydrolysis.
WP3: Ras phosphate catalysis
The main focus of this project was to develop a computational framework for designing Ras catalytic activators to reenable the catalytic activity of oncogenic Ras. We established the proton transfer mechanism for Ras, and developed an ML-aided strategy to design activators. This work in published in JACS (2023). Currently, follow up work is performed to design small molecule ligands for catalytic activators, which is tested experimentally.
Additionally, a large structural database is prepared to understand the structural and electrostatic requirements for NTP hydrolysis.
We developed novel methods and theoretical relationships involving the molecular kinetics of biomolecular processes. We applied our simulation methods to reveal the catalytic mechanism of wild type and oncogenic Ras, and beyond the project timelines we will continue to work on developing small molecule activators to target oncogenic Ras.