Abstract: The present invention provides synthetic peptides comprising an amino acid sequence of any one of SEQ ID NOs: 1-17 or an amino acid sequence having at least 80%, 85%, 90%, or 95% sequence identity to the amino acid sequence of any one of SEQ ID NOs:1-17. Also described herein are solid supports including peptides and methods of using such peptides and solid supports.

Abstract: Disclosed are peptides that exhibit good binding to the anticodon stem and loop of human lysine tRNA species, tRNALys3. The starting point was the 15-amino-acid sequence, RVTHHAFLGAHRTVG, found to bind selectively to hypermodified tRNALys3. The peptide backbone conformation was determined via atomistic simulation of the peptide-ASLLys3complex and then held fixed throughout the search. Analysis of the binding structure and the various contributions to the binding energy shows that: 1) two hydrophilic residues (asparagine (ASN) at site 11 and the cysteine (CYS) at site 12) “recognize” the ASLLys3 due to the VDW energy, and thereby contribute to its binding specificity, and 2) the positively-charged arginines (ARG) at sites 4 and 13 preferentially attract the negatively-charged sugar rings and the phosphate linkages, and thereby contribute to the binding affinity.

Abstract: Disclosed are peptides that exhibit good binding to the anticodon stem and loop (ASL) of human lysine tRNA species, tRNALys3. Using a search algorithm combining Monte Carlo (MC) and self-consistent mean field (SCMF) techniques, the peptides were evolved a with the ultimate purpose of using them to break the replication cycle of HIV-1 virus. The starting point was the 15-amino-acid sequence, RVTHHAFLGAHRTVG, found experimentally to bind selectively to hypermodified tRNALys3. The peptide backbone conformation was determined via atomistic simulation of the peptide-ASLLys3 complex and then held fixed throughout the search. The proportion of amino acids of various types (hydrophobic, polar, charged, etc.) was varied to mimic different peptide hydration properties. Three different sets of hydration properties were examined in the search algorithm to see how this affects evolution to the best-binding peptide sequences.