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Biology subjects

Foerch, P.

Publications and source records attributed to Foerch, P..

3 recordsLinked to original sources

Improving Inverse Folding models at Protein Stability Prediction without additional Training or Data

Deep learning protein sequence models have shown outstanding performance at de novo protein design and variant effect prediction. We substantially improve performance without further training or use of additional experimental data by introducing a second term derived from the models themselves which align outputs for the task of stability prediction. On a task to predict variants which increase protein stability the absolute success probabilities of PO_SCPLOWROTEINC_SCPLOWMPNN and ESMO_SCPLOWIFC_SCPLOW are improved by 11% and 5% respectively. We term these models PO_SCPLOWROTEINC_SCPLOWMPNN-O_SCPLOWDDC_SCPLOWG and ESMO_SCPLOWIFC_SCPLOW-O_SCPLOWDDC_SCPLOWG.

biophysics↗

MTHFD2 is a Metabolic Checkpoint Controlling Effector and Regulatory T Cell Fate and Function

Antigenic stimulation promotes T cells metabolic reprogramming to meet increased biosynthetic, bioenergetic, and signaling demands. We show that the one-carbon (1C) metabolism enzyme Methylenetetrahydrofolate Dehydrogenase-2 (MTHFD2) is highly expressed in inflammatory diseases and induced in activated T cells to promote proliferation and produce inflammatory cytokines. In pathogenic Th17 cells, MTHFD2 also prevented aberrant upregulation of FoxP3 and suppressive capacity. Conversely, MTHFD2-deficiency enhanced lineage stability of regulatory T (Treg) cells. Mechanistically, MTHFD2 maintained cellular 10-formyltetrahydrofolate for de novo purine synthesis and MTHFD2 inhibition led to accumulation of the intermediate 5-aminoimidazole carboxamide ribonucleotide that was associated with decreased mTORC1 signaling. MTHFD2 was also required for proper histone de-methylation in Th17 cells. Importantly, inhibiting MTHFD2 in vivo reduced disease severity in Experimental Autoimmune Encephalomyelitis and Delayed-Type Hypersensitivity. MTHFD2 induction is thus a metabolic checkpoint for pathogenic effector cells that suppresses anti-inflammatory Treg cells and is a potential therapeutic target within 1C metabolism.

immunology↗

A Systems-Level Framework For Drug Discovery Identifies Csf1R As A Novel Anti-Epileptic Drug Target

The identification of mechanistically novel drug targets is highly challenging, particularly for diseases of the central nervous system. To address this problem we developed and experimentally validated a new computational approach to drug target identification that combines gene-regulatory information with a causal reasoning framework (\"causal reasoning analytical framework for target discovery\" - CRAFT). Starting from gene expression data, CRAFT provides a predictive functional genomics framework for identifying membrane receptors with a direction-specified influence over network expression. As proof-of-concept we applied CRAFT to epilepsy, and predicted the tyrosine kinase receptor Csf1R as a novel therapeutic target for epilepsy. The predicted therapeutic effect of Csf1R blockade was validated in two pre-clinical models of epilepsy using a small molecule inhibitor of Csf1R. These results suggest Csf1R blockade as a novel therapeutic strategy in epilepsy, and highlight CRAFT as a systems-level framework for predicting mechanistically new drugs and targets. CRAFT is applicable to disease settings other than epilepsy.

systems biology↗