Helix-based screening with structure prediction using artificial intelligence has potential for the rapid development of peptide inhibitors targeting class I viral fusion.

The rapid development of drugs against emerging and re-emerging viruses is required to prevent future pandemics. However, inhibitors usually take a long time to optimize. Here, to improve the optimization step, we used two heptad repeats (HR) in the spike protein (S protein) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a model and established a screening system for peptide-based inhibitors containing an α-helix region (SPICA). SPICA can be used to identify critical amino acid regions and evaluate the inhibitory effects of peptides as decoys. We further employed an artificial intelligence structure-prediction system (AlphaFold2) for the rapid analysis of structure-activity relationships. Here, we identified that critical amino acid regions, DVDLGD (amino acids 1163-1168 in the S protein), IQKEIDRLNE (1179-1188), and NLNESLIDL (1192-1200), played a pivotal role in SARS-CoV-2 fusion. Peptides containing these critical amino acid regions efficiently blocked viral replication. We also demonstrated that AlphaFold2 could successfully predict structures similar to the reported crystal and cryo-electron microscopy structures of the post-fusion form of the SARS-CoV-2 S protein. Notably, the predicted structures of the HR1 region and the peptide-based fusion inhibitors corresponded well with the antiviral effects of each fusion inhibitor. Thus, the combination of SPICA and AlphaFold2 is a powerful tool to design viral fusion inhibitors using only the amino-acid sequence of the fusion protein.

Helical peptides with disordered regions for measles viruses provide new generalized insights into fusion inhibitors.

Despite effective vaccines, measles virus (MeV) outbreaks occur sporadically. Therefore, developing anti-MeV agents remains important for suppressing MeV infections. We previously designed peptide-based MeV fusion inhibitors, M1 and M2, that target MeV class I fusion protein (F protein). Here, we developed a novel fusion inhibitor, MEK35, that exerts potent activity against M1/M2-resistant MeV variants. Comparing MEK35 to M1 derivatives revealed that combining disordered and helical elements was essential for overcoming M1/M2 resistance. Moreover, we propose a three-step antiviral process for peptide-based fusion inhibitors: (i) disordered peptides interact with F protein; (ii) the peptides adopt a partial helical conformation and bind to F protein through hydrophobic interactions; and (iii) subsequent interactions involving the disordered region of the peptides afford a peptide-F protein with a high-affinity peptide-F protein interaction. An M1-resistant substitution blocks the second step. These results should aid the development of novel viral fusion inhibitors targeting class I F protein.

Identification of SARS-CoV-2 Mpro inhibitors containing P1' 4-fluorobenzothiazole moiety highly active against SARS-CoV-2.

COVID-19 caused by SARS-CoV-2 has continually been serious threat to public health worldwide. While a few anti-SARS-CoV-2 therapeutics are currently available, their antiviral potency is not sufficient. Here, we identify two orally available 4-fluoro-benzothiazole-containing small molecules, TKB245 and TKB248, which specifically inhibit the enzymatic activity of main protease (Mpro) of SARS-CoV-2 and significantly more potently block the infectivity and replication of various SARS-CoV-2 strains than nirmatrelvir, molnupiravir, and ensitrelvir in cell-based assays employing various target cells. Both compounds also block the replication of Delta and Omicron variants in human-ACE2-knocked-in mice. Native mass spectrometric analysis reveals that both compounds bind to dimer Mpro, apparently promoting Mpro dimerization. X-ray crystallographic analysis shows that both compounds bind to Mpro's active-site cavity, forming a covalent bond with the catalytic amino acid Cys-145 with the 4-fluorine of the benzothiazole moiety pointed to solvent. The data suggest that TKB245 and TKB248 might serve as potential therapeutics for COVID-19 and shed light upon further optimization to develop more potent and safer anti-SARS-CoV-2 therapeutics.

Serine hydroxymethyltransferase as a potential target of antibacterial agents acting synergistically with one-carbon metabolism-related inhibitors.

Serine hydroxymethyltransferase (SHMT) produces 5,10-methylenetetrahydrofolate (CH2-THF) from tetrahydrofolate with serine to glycine conversion. SHMT is a potential drug target in parasites, viruses and cancer. (+)-SHIN-1 was developed as a human SHMT inhibitor for cancer therapy. However, the potential of SHMT as an antibacterial target is unknown. Here, we show that (+)-SHIN-1 bacteriostatically inhibits the growth of Enterococcus faecium at a 50% effective concentration of 10-11 M and synergistically enhances the antibacterial activities of several nucleoside analogues. Our results, including crystal structure analysis, indicate that (+)-SHIN-1 binds tightly to E. faecium SHMT (efmSHMT). Two variable loops in SHMT are crucial for inhibitor binding, and serine binding to efmSHMT enhances the affinity of (+)-SHIN-1 by stabilising the loop structure of efmSHMT. The findings highlight the potency of SHMT as an antibacterial target and the possibility of developing SHMT inhibitors for treating bacterial, viral and parasitic infections and cancer.