Periodic Reporting for period 4 - VARIAMOLS (VAriable ResolutIon Algorithms for macroMOLecular Simulation)
Periodo di rendicontazione: 2022-07-01 al 2022-12-31
The comprehension of the fundamental underpinnings of life, in particular at the molecular and macromolecular level, has immensely benefited, during the past few decades, of computer simulations; these “virtual experiments” enable researchers to investigate the behaviour of biologically relevant molecules, such as proteins and DNA, with a level of detail that is currently, or maybe fundamentally, inaccessible to experiment. Computer simulations, in general, model the system as interacting particles, such as atoms subject to forces acting among them. Quite often, however, a fully-atomistic description of a large macromolecule can be either too intensive in terms of computing and storage resources, or too detailed and complex to analyse and comprehend, or both. Simpler models that describe the molecule at a lower resolution, the so-called coarse-grained models, offer a substantial computational advantage; however they also bear the disadvantages of a detail loss: this can be fatal for the reproduction and understanding of many phenomena of interest, which in turn depend on small-scale processes taking place in a small region of the molecule and reverberate up to the whole system.
The VARIAMOLS project overcomes this gap between overly-detailed all-atom models and efficient yet too blurred coarse-grained descriptions by means of a novel bottom-up modelling strategy, in which the physical properties of the system indicate which parts can be simplified and to what extent this complexity reduction is allowed; this information is then employed in a multiple-resolution representation. In contrast to conventional multi-scale methods, the level of detail with which the macromolecule is modelled is not uniform across the system, but rather it varies smoothly through the structure. This concurrent usage of various levels of resolution depending on the specific, local properties of the system optimises the balance between detail and efficiency. Furthermore, this method provides a deeper insight into how key biological macromolecules carry out their function, in that it highlights those specific parts that are most prominently involved in carrying out specific functional tasks. On the long timescale, the outcome of the VARIAMOLS project will boost the effectiveness of computer-aided methods in the investigation of biologically relevant macromolecules, thereby providing a major help in the development of antiviral and antibody-based drugs.
The VARIAMOLS project overcomes this gap between overly-detailed all-atom models and efficient yet too blurred coarse-grained descriptions by means of a novel bottom-up modelling strategy, in which the physical properties of the system indicate which parts can be simplified and to what extent this complexity reduction is allowed; this information is then employed in a multiple-resolution representation. In contrast to conventional multi-scale methods, the level of detail with which the macromolecule is modelled is not uniform across the system, but rather it varies smoothly through the structure. This concurrent usage of various levels of resolution depending on the specific, local properties of the system optimises the balance between detail and efficiency. Furthermore, this method provides a deeper insight into how key biological macromolecules carry out their function, in that it highlights those specific parts that are most prominently involved in carrying out specific functional tasks. On the long timescale, the outcome of the VARIAMOLS project will boost the effectiveness of computer-aided methods in the investigation of biologically relevant macromolecules, thereby providing a major help in the development of antiviral and antibody-based drugs.
The main research lines foreseen for the first period of the project focussed particularly on the algorithmic and methodological aspects, with important input coming from the fruitful collaboration established with scientists outside of the group (e.g. M. Scott Shell, UCSB (USA), and Flavio Vella, Free University of Bozen (IT)).
Various papers have been published in this period, which conveyed the main message of the project and related research lines (Diggins et al., JCTC 2019; Giulini and Potestio, Interface Focus 2019; Tarenzi et al., JCTC 2019; Erban et al., Interface Focus 2019; Riccardi et al., Interface Focus 2019; Fiorentini et al., Proteins 2020).
A key milestone of the project has been achieved with the development of the mapping entropy minimisation method (Giulini et al. JCTC 2020; Errica et al., Front. Mol. Biosci 2021), which enables the identification of biologically relevant atoms and residues of proteins through an information theory-based analysis of a molecular dynamics simulation. A manuscript reporting on a generalisation of this method was published on PRE (Holtzman et al., PRE 2022).
Further work was carried out for the development of variable resolution modelling strategies capable of preserving crucial mechanical and dynamical properties of the reference model (Tarenzi et al., Scientific Reports 2021; Tarenzi et al., Applied Sciences 2022).
A modelling strategy has been developed that produces a multiple-resolution model of the system based on user-provided instructions. This approach has been validated on two nontrivial case studies, the adenylate kinase enzyme and the pharmaceutical antibody pembrolizumab. The paper was published shortly after the end of the project (Fiorentini et al., JCIM 2023).
Recently we have employed an approach based on two measures of information content of data, namely resolution and relevance, to investigate the properties of a protein’s conformational space and to identify the optimal strategy to coarse-grain it. This work was accepted for publication in Soft Matter (Mele et al., Soft Matter 2022).
Other works have been carried out in this period, which contributed to establish important relationships among a protein’s structure, its dynamics, and its function, through the usage of the resolution level and distribution of its description as a bridge between these elements. Specifically:
Tarenzi et al., JCTC 2019
Heidari et al., JCP 2020
Baptista et al., JPCM 2021
Menichetti et al., EPJB 2021
Giulini et al., 2021
Tarenzi et al., BBA Biomembranes 2022
Luchi et al., arxiv preprint 2022
Micheloni et al., biorXiv preprint 2022
During the second half of the project we also carried out several activities aimed at communicating science to the general public. The outcomes of the project have been the following:
1. Participation in the European Researcher’s Night 2021.
2. Production of a book containing 36 images related to the group’s research activity.
3. The 36 images were exposed in a dedicated exhibition lasting until February 14, 2022 at the BUC - Central University Library in Trento, Italy.
Various papers have been published in this period, which conveyed the main message of the project and related research lines (Diggins et al., JCTC 2019; Giulini and Potestio, Interface Focus 2019; Tarenzi et al., JCTC 2019; Erban et al., Interface Focus 2019; Riccardi et al., Interface Focus 2019; Fiorentini et al., Proteins 2020).
A key milestone of the project has been achieved with the development of the mapping entropy minimisation method (Giulini et al. JCTC 2020; Errica et al., Front. Mol. Biosci 2021), which enables the identification of biologically relevant atoms and residues of proteins through an information theory-based analysis of a molecular dynamics simulation. A manuscript reporting on a generalisation of this method was published on PRE (Holtzman et al., PRE 2022).
Further work was carried out for the development of variable resolution modelling strategies capable of preserving crucial mechanical and dynamical properties of the reference model (Tarenzi et al., Scientific Reports 2021; Tarenzi et al., Applied Sciences 2022).
A modelling strategy has been developed that produces a multiple-resolution model of the system based on user-provided instructions. This approach has been validated on two nontrivial case studies, the adenylate kinase enzyme and the pharmaceutical antibody pembrolizumab. The paper was published shortly after the end of the project (Fiorentini et al., JCIM 2023).
Recently we have employed an approach based on two measures of information content of data, namely resolution and relevance, to investigate the properties of a protein’s conformational space and to identify the optimal strategy to coarse-grain it. This work was accepted for publication in Soft Matter (Mele et al., Soft Matter 2022).
Other works have been carried out in this period, which contributed to establish important relationships among a protein’s structure, its dynamics, and its function, through the usage of the resolution level and distribution of its description as a bridge between these elements. Specifically:
Tarenzi et al., JCTC 2019
Heidari et al., JCP 2020
Baptista et al., JPCM 2021
Menichetti et al., EPJB 2021
Giulini et al., 2021
Tarenzi et al., BBA Biomembranes 2022
Luchi et al., arxiv preprint 2022
Micheloni et al., biorXiv preprint 2022
During the second half of the project we also carried out several activities aimed at communicating science to the general public. The outcomes of the project have been the following:
1. Participation in the European Researcher’s Night 2021.
2. Production of a book containing 36 images related to the group’s research activity.
3. The 36 images were exposed in a dedicated exhibition lasting until February 14, 2022 at the BUC - Central University Library in Trento, Italy.
The results obtained in the course of the VARIAMOLS project have built a bridge between two apparently distinct and independent features of a macromolecular system: on the one hand, the level of resolution and detail with which its structural and dynamical features are described and encoded in simplified representations; on the other hand, the physical properties of these features and the functional role they play in the biological activity of the molecule. This bridge serves a twofold purpose: it opens access to important information about how proteins work and what kind of mechanical, physical, and chemical strategies they have developed to carry out their function; and it enables the construction of tailored multiple-resolution models to take advantage of simplified descriptions in less functionally relevant parts, while preserving high detail in key regions of the system. The approaches here developed have solid roots planted in physics and chemistry, and the gain in efficiency for practical application is always paired by an increased comprehension of the fundamental properties of biomolecules. The outcomes of the VARIAMOLS project aim at maximising understanding and efficiency at the same time, by providing researchers with tools that are not only effective and reliable for the investigation of complex biomolecules, but rather contribute themselves to comprehend the inner life of the latter. Furthermore, the methods developed in the course of the project are very general, and amenable to find broader fields of application outside of the realm in which they were conceived (see e.g. Holtzman et al., 2022); and they have been implemented in efficient and freely accessible software (see Fiorentini et al., 2023), which guarantees the reproducibility of the results as well as their capillary diffusion in the academic community and the private sector.