Poxvirus targeted by RFdiffusion peptide-binders
Coll, J. M.
Show abstract
Peptide-binders were generated by computational RFdiffusion to the F13L-homodimer interface sequences of poxviruses such as vaccinia and monkeypox. Compared to small-drug screenings and/or co-evolutions, peptide-binders have the advantages of higher affinities and easier chemical / recombinant synthesis. Among the hundreds of 20-30-mer peptide-binders randomly generated by RFdiffusion, some targeted vaccinia (VACV) F13L homodimer interface predicting low nanoMolar affinities. To improve its physiological stability, additional peptide sequences were computationally generated by cyclization/ hallucination. The resulting de novo cyclic peptide sequences predicted picoMolar affinities not only targeting the VACV F13L homodimer interfaces but also inner cavities previously identified by small-drug dockings to Tecovirimat-resistant monkeypox (MPXV) mutants. Because their targeting to numerous highly-conserved amino acids among poxviruses, and improved physiological stability against proteases, cyclic peptide-binders may be more adequate against resistant mutants of VACV and MPXV poxviruses. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=174 SRC="FIGDIR/small/654163v1_ufig1.gif" ALT="Figure 1"> View larger version (72K): org.highwire.dtl.DTLVardef@148a2fborg.highwire.dtl.DTLVardef@1c4117forg.highwire.dtl.DTLVardef@158ea61org.highwire.dtl.DTLVardef@839761_HPS_FORMAT_FIGEXP M_FIG C_FIG
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Predicting the structures of cyclic peptides containing unnatural amino acids by HighFold2 94%
- OPUS-Rota4: A Gradient-Based Protein Side-Chain Modeling Framework Assisted by Deep Learning-Based Predictors 94%
- MutateX: an automated pipeline for in-silico saturation mutagenesis of protein structures and structural ensembles 94%
Similar papers in this journal
- PROTACable is an Integrative Computational Pipeline of 3-D Modeling and Deep Learning to Automate the De Novo Design of PROTACs 95%
- An Integrative Approach to Dissect the Drug Resistance Mechanism of the H172Y Mutation of SARS-CoV-2 Main Protease 94%
- Rational Prediction of PROTAC-compatible Protein-Protein Interfaces by Molecular Docking 94%
Similar papers in this journal
- De novo design of high-affinity antibody variable regions (Fv) against the SARS-CoV-2 spike protein 96%
- Molecular Dynamics Analysis of a Flexible Loop at the Binding Interface of the SARS-CoV-2 Spike Protein Receptor-Binding Domain 95%
- Prediction of protein assemblies by structure sampling followed by interface-focused scoring 94%
Similar papers in this journal
- RosettaDDGPrediction for high-throughput mutational scans: from stability to binding 94%
- ExploreTurns: A web tool for the exploration, analysis, and classification of beta turns and structured loops in proteins; application to beta-bulge and Schellman loops, Asx helix caps, beta hairpins and other hydrogen-bonded motifs 94%
- Knot or Not? Sequence-Based Identification of Knotted Proteins With Machine Learning 93%
Similar papers in this journal
- Potential Neutralizing Antibodies Discovered for Novel Corona Virus Using Machine Learning 95%
- Exploring the ability of the MD+FoldX method to predict SARS-CoV-2 antibody escape mutations using large-scale data 95%
- HTRF-based identification of small molecules targeting SARS-CoV-2 E protein interaction with ZO-1 PDZ2 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.