PROSTATA: a framework for protein stability assessment using transformers.

MOTIVATION: Accurate prediction of change in protein stability due to point mutations is an attractive goal that remains unachieved. Despite the high interest in this area, little consideration has been given to the transformer architecture, which is dominant in many fields of machine learning. RESULTS: In this work, we introduce PROSTATA, a predictive model built in a knowledge-transfer fashion on a new curated dataset. PROSTATA demonstrates advantage over existing solutions based on neural networks. We show that the large improvement margin is due to both the architecture of the model and the quality of the new training dataset. This work opens up opportunities to develop new lightweight and accurate models for protein stability assessment. AVAILABILITY AND IMPLEMENTATION: PROSTATA is available at https://github.com/AIRI-Institute/PROSTATA and https://prostata.airi.net.

SEMA: Antigen B-cell conformational epitope prediction using deep transfer learning.

One of the primary tasks in vaccine design and development of immunotherapeutic drugs is to predict conformational B-cell epitopes corresponding to primary antibody binding sites within the antigen tertiary structure. To date, multiple approaches have been developed to address this issue. However, for a wide range of antigens their accuracy is limited. In this paper, we applied the transfer learning approach using pretrained deep learning models to develop a model that predicts conformational B-cell epitopes based on the primary antigen sequence and tertiary structure. A pretrained protein language model, ESM-1v, and an inverse folding model, ESM-IF1, were fine-tuned to quantitatively predict antibody-antigen interaction features and distinguish between epitope and non-epitope residues. The resulting model called SEMA demonstrated the best performance on an independent test set with ROC AUC of 0.76 compared to peer-reviewed tools. We show that SEMA can quantitatively rank the immunodominant regions within the SARS-CoV-2 RBD domain. SEMA is available at https://github.com/AIRI-Institute/SEMAi and the web-interface http://sema.airi.net.

ROS Generation and Antioxidant Defense Systems in Normal and Malignant Cells.

Reactive oxygen species (ROS) are by-products of normal cell activity. They are produced in many cellular compartments and play a major role in signaling pathways. Overproduction of ROS is associated with the development of various human diseases (including cancer, cardiovascular, neurodegenerative, and metabolic disorders), inflammation, and aging. Tumors continuously generate ROS at increased levels that have a dual role in their development. Oxidative stress can promote tumor initiation, progression, and resistance to therapy through DNA damage, leading to the accumulation of mutations and genome instability, as well as reprogramming cell metabolism and signaling. On the contrary, elevated ROS levels can induce tumor cell death. This review covers the current data on the mechanisms of ROS generation and existing antioxidant systems balancing the redox state in mammalian cells that can also be related to tumors.

The Dysregulation of Polyamine Metabolism in Colorectal Cancer Is Associated with Overexpression of c-Myc and C/EBPß rather than Enterotoxigenic Bacteroides fragilis Infection.

Colorectal cancer is one of the most common cancers in the world. It is well known that the chronic inflammation can promote the progression of colorectal cancer (CRC). Recently, a number of studies revealed a potential association between colorectal inflammation, cancer progression, and infection caused by enterotoxigenic Bacteroides fragilis (ETBF). Bacterial enterotoxin activates spermine oxidase (SMO), which produces spermidine and H2O2 as byproducts of polyamine catabolism, which, in turn, enhances inflammation and tissue injury. Using qPCR analysis, we estimated the expression of SMOX gene and ETBF colonization in CRC patients. We found no statistically significant associations between them. Then we selected genes involved in polyamine metabolism, metabolic reprogramming, and inflammation regulation and estimated their expression in CRC. We observed overexpression of SMOX, ODC1, SRM, SMS, MTAP, c-Myc, C/EBPß (CREBP), and other genes. We found that two mediators of metabolic reprogramming, inflammation, and cell proliferation c-Myc and C/EBPß may serve as regulators of polyamine metabolism genes (SMOX, AZIN1, MTAP, SRM, ODC1, AMD1, and AGMAT) as they are overexpressed in tumors, have binding site according to ENCODE ChIP-Seq data, and demonstrate strong coexpression with their targets. Thus, increased polyamine metabolism in CRC could be driven by c-Myc and C/EBPß rather than ETBF infection.

Mitochondrial dysfunction and oxidative stress in aging and cancer.

Aging and cancer are the most important issues to research. The population in the world is growing older, and the incidence of cancer increases with age. There is no doubt about the linkage between aging and cancer. However, the molecular mechanisms underlying this association are still unknown. Several lines of evidence suggest that the oxidative stress as a cause and/or consequence of the mitochondrial dysfunction is one of the main drivers of these processes. Increasing ROS levels and products of the oxidative stress, which occur in aging and age-related disorders, were also found in cancer. This review focuses on the similarities between ageing-associated and cancer-associated oxidative stress and mitochondrial dysfunction as their common phenotype.