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Sperling, M.

Publications and source records attributed to Sperling, M..

7 recordsLinked to original sources

AI-guided pipeline for protein-protein interaction drug discovery identifies a SARS-CoV-2 inhibitor

Protein-protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays and AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways.

systems biology↗

A quantitative mapping approach to identify direct interactions within complexomes

Complementary methods are required to fully characterize all protein complexes, or the complexome, of a cell. Affinity purification coupled to mass-spectrometry (AP-MS) can identify the composition of complexes at proteome-scale. However, information on direct contacts between subunits is often lacking. In contrast, solving the 3D structure of protein complexes can provide this information, but structural biology techniques are not yet scalable for systematic, proteome-wide efforts. Here, we optimally combine two orthogonal high-throughput binary interaction assays, LuTHy and N2H, and demonstrate that their quantitative readouts can be used to differentiate direct interactions from indirect associations within multiprotein complexes. We also show that LuTHy allows accurate distance measurements between proteins in live cells and apply these findings to study the impact of the polyglutamine expansion mutation on the structurally unresolved N-terminal domain of Huntingtin. Thus, we present a new framework based on quantitative interaction assays to complement structural biology and AP-MS techniques, which should help to provide first-approximation contact maps of multiprotein complexes at proteome-scale. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC="FIGDIR/small/457734v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1cc7cf1org.highwire.dtl.DTLVardef@1eed9borg.highwire.dtl.DTLVardef@8197b2org.highwire.dtl.DTLVardef@e5cb8_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

Computational Support, Not Primacy, Distinguishes Compensatory Memory Reorganization in Epilepsy

Temporal lobe epilepsy (TLE) is associated with impairment in episodic memory. A substantial sub-group, however, is able to maintain adequate memory despite temporal lobe pathology. What has been missing from prior work in the cognitive reorganization is a direct comparison of TLE patients with intact/compensated status from those who are memory impaired and uncompensated. Little is known about the particular regional activations, functional connectivities (FCs), and/or network reconfigurations that implement changes in the primary computations or the support functions that drive adaptive plasticity and compensated memory. We utilized task fMRI on 54 unilateral TLE patients and 24 matched healthy controls (HC) during performance of a paired-associate memory (PAM) task to address three questions: 1) what regions implement PAM in TLE, and do such regions vary as a function of good versus poor performance, 2) are there unique FCs present during memory encoding that accounts for intact status through the preservation of primary memory computations or the supportive computations that allow for compensated memory responses, and 3) what features during memory encoding are most distinctive: is it the magnitude and location of regional activations, or the presence of enhanced functional connections to key structures such as the hippocampus? Results revealed a unique profile of non-ictal, non-dominant hemisphere regions (e.g., right posterior temporal regions) were most important to intact/compensated status in LTLE, involving both increased regional activity and increased modulatory communication with the hippocampi, all feature that was missing in impaired/uncompensated LTLE. The profile involved areas that are neither contralateral homologues to left hemisphere memory areas, nor regions traditionally considered computationally primary for episodic memory. None of these areas of increased activation or functional connectivity were associated with advantaged memory in HCs. Our emphasis on different performance levels yielded insight into two forms of cognitive reorganization. Computational primacy, where LTLE showed little change relative to HCs, and computational support where Intact/Compensated LTLE patients showed adaptive abnormalities. The analyses isolated the unique regional activations and mediating FCs that implement truly compensatory reorganization in LTLE. The results provided a new perspective on memory deficits by making clear that memory deficits arise not just from knockout of a functional hub, but from the failure to instantiate a complex set of reorganization responses. Such responses provided computational support to ensure successful memory. The findings demonstrated that by keeping track of performance levels, we can increase our understanding of adaptive brain responses and neuroplasticity in epilepsy.

neuroscience↗

Time cells in the human hippocampus and entorhinal cortex support episodic memory

The organization of temporal information is critical for the encoding and retrieval of episodic memories. In the rodent hippocampus and entorhinal cortex, recent evidence suggests that temporal information is encoded by a population of "time cells." We identify time cells in humans using intracranial microelectrode recordings obtained from 27 human epilepsy patients who performed an episodic memory task. We show that time cell activity predicts the temporal organization of episodic memories. A significant portion of these cells exhibits phase precession, a key phenomenon not previously seen in human recordings. These findings establish a cellular mechanism for the representation of temporal information in the human brain needed to form episodic memories.

neuroscience↗

Intracranial EEG reveals bihemispheric parietal and extra parietal brain networks supporting mental arithmetic

Mathematical reasoning is central to everyday life. Lesion data and functional MRI studies suggest that even simple arithmetic involves the coordination of multiple spatially diverse brain regions, but to date, math processing has not been well characterized using direct brain recordings, especially outside of the parietal cortex. To address this, we utilized an unparalleled data set of 310 subjects implanted with intracranial electrodes to investigate the spatial and temporal dynamics of arithmetic reasoning. Our data support the importance of regions previously implicated in numerosity such as the superior parietal lobule and intraparietal sulcus. However, we also identify contributions to arithmetic processing from regions such as the entorhinal cortex and temporal pole. Using the excellent bihemispheric coverage afforded by our data set and the precise temporal resolution of intracranial recordings, we characterize in detail the spatial and temporal characteristics of an arithmetic processing network, quantifying subtle hemispheric differences for selected regions. We also examine how activity in these regions predicts arithmetic ability and look for gender differences in the pattern of network activation. Our findings further define the complex network of regions involved in human arithmetical reasoning.

neuroscience↗

Electrophysiological signatures of spatial boundaries in the human subiculum

Environmental boundaries play a crucial role in spatial navigation and memory across a wide range of distantly-related species. In rodents, boundary representations have been identified at the single-cell level in the subiculum and entorhinal cortex of the hippocampal formation. While studies of hippocampal function and spatial behavior suggest that similar representations might exist in humans, boundary-related neural activity has not been identified electrophysiologically in humans until now. Here we present direct intracranial recordings from the hippocampal formation of surgical epilepsy patients while they performed a virtual spatial navigation task. Our results suggest that encoding target locations near boundaries elicited stronger theta oscillations than for target locations near the center of the environment and that this difference cannot be explained by variables such as trial length, speed, or movement. These findings provide the first direct evidence of boundary-dependent neural activity localized in humans to the subiculum, the homologue of the hippocampal subregion in which most rodent boundary cells are found.\n\nSignificance StatementSpatial computations using environmental boundaries are an integral part of the brains spatial mapping system. In rodents, border/boundary cells in the subiculum and entorhinal cortex reveal boundary coding at the single-neuron level. Although there is good reason to believe that such representations also exist in humans, the evidence has thus far been limited to fMRI studies that broadly implicate the hippocampus in boundary-based navigation. By combining intracranial recordings with high-resolution imaging of hippocampal subregions we identified, for the first time in humans, a neural marker of boundary representation in the subiculum.

neuroscience↗

The medial temporal lobe organizes memory across time and space: Causal evidence from brain stimulation

The medial temporal lobe (MTL) is widely implicated in supporting episodic memory and navigation, but its precise functional role in organizing memory across time and space remains elusive. Here we examine the specific cognitive processes implemented by MTL structures (hippocampus and entorhinal cortex) to organize memory by using electrical brain stimulation, leveraging its ability to establish causal links between brain regions and features of behavior. We studied neurosurgical patients who performed spatial-navigation and verbal-episodic memory tasks while brain stimulation was applied in various regions during learning. During the verbal memory task, stimulation in the MTL disrupted the temporal organization of encoded memories such that items learned with stimulation tended to be recalled in a more randomized order. During the spatial task, MTL stimulation impaired subjects abilities to remember items using view-independent (allocentric) navigation strategies. These stimulation effects were specific to the MTL. Our findings thus provide the first causal demonstration in humans of the specific memory processes that are performed by the MTL to encode when and where events occurred.\n\nSignificance StatementNumerous studies have implicated the medial temporal lobe (MTL) in encoding spatial and temporal memories, but they have not been able to causally demonstrate the nature of the cognitive processes by which this occurs in real-time. Electrical brain stimulation is able to demonstrate causal links between a brain region and a given function with high temporal precision. By examining behavior in a memory task as subjects received MTL stimulation, we provide the first causal evidence demonstrating the role of the MTL in organizing the spatial and temporal aspects of episodic memory.

neuroscience↗