Guiding a language-model based protein design method towards MHC Class-I immune-visibility targets in vaccines and therapeutics

Proteins have an arsenal of medical applications that include disrupting protein interactions, acting as potent vaccines, and replacing genetically deficient proteins. While therapeutics must avoid triggering unwanted immune-responses, vaccines should support a robust immune-reaction targeting a broad range of pathogen variants. Therefore, computational methods modifying proteins’ immunogenicity without disrupting function are needed. While many components of the immune-system can be involved in a reaction, we focus on Cytotoxic T-lymphocytes (CTLs). These target short peptides presented via the MHC Class I (MHC-I) pathway. To explore the limits of modifying the visibility of those peptides to CTLs within the distribution of naturally occurring sequences, we developed a novel machine learning technique, CAPE-XVAE. It combines a language model with reinforcement learning to modify a protein’s immune-visibility. Our results show that CAPE-XVAE effectively modifies the visibility of the HIV Nef protein to CTLs. We contrast CAPE-XVAE to CAPE-Packer, a physics-based method we also developed. Compared to CAPE-Packer, the machine learning approach suggests sequences that draw upon local sequence similarities in the training set. This is beneficial for vaccine development, where the sequence should be representative of the real viral population. Additionally, the language model approach holds promise for preserving both known and unknown functional constraints, which is essential for the immune-modulation of therapeutic proteins. In contrast, CAPE-Packer, emphasizes preserving the protein’s overall fold and can reach greater extremes of immune-visibility, but falls short of capturing the sequence diversity of viral variants available to learn from. Source code: https://github.com/hcgasser/CAPE (Branch: CAPE_1.1

Sampling the proteome by emerging single-molecule and mass-spectrometry methods

Mammalian cells have about 30,000-fold more protein molecules than mRNA molecules. This larger number of molecules and the associated larger dynamic range have major implications in the development of proteomics technologies. We examine these implications for both liquid chromatography-tandem mass spectrometry (LC-MS/MS) and single-molecule counting and provide estimates on how many molecules are routinely measured in proteomics experiments by LC-MS/MS. We review strategies that have been helpful for counting billions of protein molecules by LC-MS/MS and suggest that these strategies can benefit single-molecule methods, especially in mitigating the challenges of the wide dynamic range of the proteome. We also examine the theoretical possibilities for scaling up single-molecule and mass spectrometry proteomics approaches to quantifying the billions of protein molecules that make up the proteomes of our cells.Comment: Recorded presentation: https://youtu.be/w0IOgJrrvN

Vaxformer:Antigenicity-controlled transformer for vaccine design against SARS-CoV-2

The SARS-CoV-2 pandemic has emphasised the importance of developing a universal vaccine that can protect against current and future variants of the virus. The present study proposes a novel conditional protein Language Model architecture, called Vaxformer, which is designed to produce natural-looking antigenicity-controlled SARS-CoV-2 spike proteins. We evaluate the generated protein sequences of the Vaxformer model using DDGun protein stability measure, netMHCpan antigenicity score, and a structure fidelity score with AlphaFold to gauge its viability for vaccine development. Our results show that Vaxformer outperforms the existing state-of-the-art Conditional Variational Autoencoder model to generate antigenicity-controlled SARS-CoV-2 spike proteins. These findings suggest promising opportunities for conditional Transformer models to expand our understanding of vaccine design and their role in mitigating global health challenges. The code used in this study is available at https://github.com/aryopg/vaxformer

Relationships between Lower-body Power, Sprint and Change of Direction Speed among Collegiate Basketball Players by Sex

International Journal of Exercise Science 15(6): 974-984, 2022. The purpose of this study was to determine if significant relationships exist between absolute and relative lower-body power and selected measures of speed among male and female collegiate basketball players. Archived performance testing data from 29 (male = 14; female = 15) NCAA division II collegiate basketball players were used for this analysis. These measures included lane agility, 10-yard sprint, and shuttle run time (sec). A Pearson’s correlation coefficient was used to determine if significant relationships existed between measures of lower-body power and linear sprint time, change of direction speed (CODS), and shuttle performance. Statistical significance was set a priori at p ≤ 0.05. A significant large correlation was found between absolute power and lane agility (r = 0.54, p = 0.05) among male players. No significant correlations were found between absolute or relative power for 10-yard sprint times, lane agility, or shuttle run performance (p \u3e 0.05). Females showed no significant correlations between relative power and lane agility (r = -0.25, p = 0.37) or 10-yard sprint (r = -0.47, p = 0.08), but did show a significant large correlation (r = -0.64, p = 0.01) between relative power and shuttle run performance. Generating high amounts of relative power is vital in intermittent team sports such as basketball. In particular, this study provided evidence that relative power in female collegiate basketball players is significantly related to shuttle run ability

Promoter Methylation of RASSF1A Associates to Adult Secondary Glioblastomas and Pediatric Glioblastomas

While allelic losses and mutations of tumor suppressor genes implicated in the etiology of astrocytoma have been widely assessed, the role of epigenetics is still a matter of study. We analyzed the frequency of promoter hypermethylation by methylation-specific PCR (MSP) in five tumor suppressor genes (PTEN, MGMT, RASSF1A, p14ARF, and p16INK4A), in astrocytoma samples and cell lines. RASSF1A was the most frequently hypermethylated gene in all grades of astrocytoma samples, in cell lines, and in adult secondary GBM. It was followed by MGMT. PTEN showed a slight methylation signal in only one GBM and one pilocytic astrocytoma, and in two cell lines; while p14ARF and p16INK4A did not show any evidence of methylation in primary tumors or cell lines. In pediatric GBM, RASSF1A was again the most frequently altered gene, followed by MGMT; PTEN, p14 and p16 showed no alterations. Lack or reduced expression of RASSF1A in cell lines was correlated with the presence of methylation. RASSF1A promoter hypermethylation might be used as a diagnostic marker for secondary GBM and pediatric GBM. Promoter hypermethylation might not be an important inactivation mechanism in other genes like PTEN, p14ARF and p16INK4A, in which other alterations (mutations, homozygous deletions) are prevalent

IAA : Información y actualidad astronómica (13)

Sumario : Las galaxias anfitrionas de los GRBs.-- Marte: una historia de descubrimientos.-- Programa Ramón y Cajal: ¿recuperación o catapulta de cerebros?.-- CHARLAS CON...Fernando Cornet.-- El problema de la distancia a las Pléyades.-- Un bólido sobre nuestras cabezas.-- Actividades IAA.-- Agenda.Esta revista se publica con la ayuda de la Acción Especial DIS 2003-10261-E del Programa Nacional de Difusión y divulgación de la Ciencia y la Tecnología, del Ministerio de Ciencia y Tecnología.N