Biology subjects

Montepietra, D.

Publications and source records attributed to Montepietra, D..

3 recordsLinked to original sources

bioRxiv2025

Structural determinants for red-shifted absorption in higher-plants Photosystem I

- Higher plants Photosystem I absorbs near-infrared light through long-wavelength chlorophylls, enriched under vegetation canopies, to enhance photon capture. Far-red absorption originates from chlorophylls pairs within the Lhca3 and Lhca4 subunits of the LHCI antenna, known as the "red cluster" composed of chlorophylls a603 and a609. - We used reverse genetics to produce an Arabidopsis mutant devoid of red-shifted absorption, and we obtained high-resolution cryo-EM structures from purified PSI-LHCI complexes in both wild-type and mutant plants. - Computed excitonic coupling values suggested a possible contribution of additional nearby pigment molecules, namely chlorophyll a615 and violaxanthin in L2 site, to far-red absorption. Therefore, we investigated the structural determinants of far-red absorption and analyzed the spectroscopic effects of these additional pigments by producing further Arabidopsis transgenic lines. The two experimental structures were used for quantum mechanics calculations, revealing that excitonic interactions alone cannot explain far-red absorption, while charge transfer states were needed for accurate spectral simulations. - Our findings demonstrate that the molecular mechanisms of light-harvesting under shaded conditions rely on very precise tuning of chromophore interactions, an understanding of which is crucial for designing light-harvesting complexes with engineered absorption spectra

plant biology↗

bioRxiv2023

FRETpredict: A Python package for FRET efficiency predictions using rotamer libraries

Here, we introduce FRETpredict, a Python software program to predict FRET efficiencies from ensembles of protein conformations. FRETpredict uses an established Rotamer Library Approach to describe the FRET probes covalently bound to the protein. The software efficiently operates on large conformational ensembles such as those generated by molecular dynamics simulations to facilitate the validation or refinement of molecular models and the interpretation of experimental data. We demonstrate the performance and accuracy of the software for different types of systems: a relatively structured peptide (polyproline 11), an intrinsically disordered protein (ACTR), and three folded proteins (HiSiaP, SBD2, and MalE). We also describe a general approach to generate new rotamer libraries for FRET probes of interest. FRETpredict is open source (GPLv3) and is available at github.com/KULL-Centre/FRETpredict and as a Python PyPI package at pypi.org/project/FRETpredict. Author SummaryWe present FRETpredict, an open-source software to calculate FRET observables from protein structures. Using a previously developed Rotamer Library Approach, FRETpredict helps place multiple conformations of the selected FRET probes at the labeled sites, and use these to calculate FRET efficiencies. Through several case studies, we illustrate the ability of FRETpredict to interpret experimental results and validate protein conformations. We also explain a methodology for generating new rotamer libraries of FRET probes of interest.

biophysics↗

bioRxiv2020

Modeling the photosynthetic system I as complex interacting network

In this paper we model the excitation energy transfer (EET) of the photosynthetic system I (PSI) of the common pea plant Pisum Sativum as complex interacting network. The magnitude of the link energy transfer between nodes-chromophores is computed by Forster Resonant Energy Transfer (FRET) using the pairwise physical distances between chromophores from the PDB (Protein Data Bank). We measure the global PSI network EET efficiency adopting well-known network theory indicators: the network efficiency (Eff) and the largest connected component (LCC). We find that when progressively removing the weak links of lower EET, the network efficiency (Eff) decreases while the EET paths integrity (LCC) is still preserved. This finding would show that the PSI is a resilient system owning a large window of functioning feasibility and it is completely impaired only when removing most of the network links. Furthermore, we perform nodes removal simulations to understand how the nodes-chromophores malfunctioning may affect the PSI functioning. We discover that the removal of the core chlorophylls triggers the fastest decrease in the network efficiency (Eff), unveiling them as the key component boosting the high EET efficiency. Our outcomes open new perspectives of research, such comparing the PSI energy transfer efficiency of different natural and agricultural plant species and investigating the light-harvesting mechanisms of artificial photosynthesis both in plant agriculture and in the field of solar energy applications.

bioinformatics↗