Matthew B. Frieman

This paper describes a trimeric inhibitor, S22, that stabilizes the SARS-CoV-2 spike protein in a closed conformation, preventing ACE2 binding and viral entry.

This study evaluates CMX990, a coronavirus Mpro inhibitor, showing broad antiviral activity against multiple coronaviruses and superior pharmacologic properties compared to existing inhibitors.

This study shows that SARS-CoV-2 ORF8 enhances upper respiratory tract inflammation and virus shedding, promoting transmission by modulating type-I interferon signaling.

This paper describes the development of orally bioavailable SARS-CoV-2 protease inhibitors with a hydroxymethyl ketone warhead, showing improved potency and bioavailability compared to previous compounds.

This study evaluates a novel TLR4 adjuvant, BECC470s, in enhancing rHA vaccination against H5N1 influenza in mice, showing improved antibody responses but limited cross-neutralizing activity.

The paper develops a phage display library, C-Spike, to profile antibody responses to coronavirus spike proteins and identifies binding motifs using alanine-scanned peptides.

This paper identifies the SKI complex as a broad-spectrum antiviral target, showing that UMB18 increases cellular cholesterol via the mevalonate pathway to inhibit viral replication.

This study evaluates BECC adjuvants' ability to enhance HA-based influenza vaccine efficacy in mice, showing improved immune responses and viral clearance.

This study identifies critical human host factors involved in SARS-CoV-2 multicycle replication through a genome-scale siRNA screen and validates potential antiviral targets.

This study uses Perturb-seq to functionally interrogate SARS-CoV-2 host factors in human lung epithelial cells, identifying key factors that influence infection and host response.

The paper compares SARS-CoV-2 antigenicity across assays and in human and animal model sera, finding similar immunodominance patterns and antigenic maps but differences in titer magnitude and assay-specific fold change.

The paper identifies intra-host single nucleotide variants (iSNVs) in influenza samples to track transmission links, finding that technical and systematic errors affect iSNV calling and that self-reference reduces noise.