Biology subjects

Martinovic, J.

Publications and source records attributed to Martinovic, J..

3 recordsLinked to original sources

bioRxiv2024

Prediction of Aggregation Prone Regions in Proteins Using Deep Neural Networks and Their Suppression by Computational Design

Identification of aggregation-prone regions in proteins and their suppression through mutations is a powerful strategy to enhance protein solubility and yield, significantly expanding their application potential. Here, we developed a deep neural network-based predictor AggreProt, that generates a residue-level aggregation profile for protein sequences. The model outperformed or matched current state-of-the-art algorithms, as validated on two independent datasets comprising hexapeptides and full-length proteins with annotated aggregation-prone regions. We further validated the model experimentally using a set of 34 hexapeptides identified in the model protein haloalkane dehalogenase LinB, along with seven proteins from the AmyPro database. Experimental results agreed with our predictions in 79% of cases and also revealed inaccuracies in some database annotations. Finally, the algorithms utility was demonstrated by identifying aggregation-prone regions in the LinB enzyme and designing mutations to suppress aggregation in its exposed regions. The resulting variants exhibited reduced aggregation propensity, improved solubility, and up to a 100% increase in yield compared to the wild type. AggreProt is freely available to the scientific community via a user- friendly web server: https://loschmidt.chemi.muni.cz/aggreprot.

bioinformatics↗

bioRxiv2023

Attention to Colour: Spotlight in Hue Space

Biological systems must allocate limited perceptual resources to relevant elements in their environment. This often requires simultaneous selection of multiple elements from the same feature dimension (e.g., colour). To establish the determinants of divided attentional selection of colour, we conducted an experiment that used multicoloured displays with four overlapping random dot kinematograms that differed only in hue. We manipulated (1) requirement to focus attention to a single colour or divide it between two colours; (2) distances of distractor hues from target hues in a perceptual colour space. We conducted a behavioural and an electroencephalographic experiment, in which each colour was tagged by a specific flicker frequency and driving its own steady-state visual evoked potential. Behavioural and neural indices of attention showed several major consistencies. Concurrent selection halved the neural signature of target enhancement observed for single targets, consistent with an approximately equal division of limited resources between two hue-selective foci. Distractors interfered with behavioural performance in a context-dependent fashion but their effects were asymmetric, indicating that perceptual distance did not adequately capture attentional distance. These asymmetries point towards an important role of higher-level mechanisms such as categorisation and grouping-by-colour in determining the efficiency of attentional allocation in complex, multi-coloured scenes.

neuroscience↗

bioRxiv2021

Decoding of EEG signals reveals non-uniformities in the neural geometry of colour

The idea of colour opponency maintains that colour vision arises through the comparison of two chromatic mechanisms, red versus green (RG) and yellow versus blue (YB). The four unique hues, red, green, blue, and yellow, are assumed to appear at the null points of these the two chromatic systems. However, whether unique hues have a distinct signature that can be reliably discerned in neural activity is still an open question. Here we hypothesise that, if unique hues represent a tractable cortical state, they should elicit more robust activity compared to non-unique hues. We use a spatiotemporal decoding approach to reconstruct an activation space for a set of unique and intermediate hues across a range of luminance values. We show that electroencephalographic (EEG) responses carry robust information about isoluminant unique hues within a 100-300 ms window from stimulus onset. Decoding is possible in both passive and active viewing tasks, but is compromised when concurrent high luminance contrast is added to the colour signals. The efficiency of hue decoding is not entirely predicted by their mutual distance in a nominally uniform perceptual colour space. Instead, the encoding space shows pivotal non-uniformities which suggest that anisotropies in neurometric hue-spaces are likely to represent perceptual unique hues. Furthermore, the neural code for hue temporally coincides with the neural code for luminance contrast, thus explaining why potential neural correlates of unique hues have remained so elusive until now.

neuroscience↗