Background <p>Targeting undruggable proteins and challenging binding sites, such as protein–protein interaction (PPI) interfaces and allosteric pockets, using small-molecule inhibitors is often infeasible. Peptide-based irreversible inhibitors are promising emerging strategies for the treatment of such targets. However, there is currently no systematic in silico protocol for the rational design of peptide-based covalent inhibitors.</p> Methods <p>We developed a streamlined computational framework for the de novo design of peptide-based irreversible inhibitors. Key considerations include peptide sequence optimization for binding, selection of electrophilic warheads, peptide folding, target specificity, and pharmacokinetic and toxicity profiles. Binding affinities were estimated using covalent molecular dynamics (MD<sup>cov</sup>) simulations and thermodynamic binding free energy calculations.</p> Results <p>Using KRAS<sup>G12C</sup>, a strategic drug target traditionally considered undruggable, as a case study, the protocol identified top-hit peptide inhibitors (RVKDX, HVKXR, and XLKDH) with binding free energies (BFEs) of -48.84, -48.93, and -48.67&#xa0;kcal/mol, respectively. These values are comparable to sotorasib (-50.63&#xa0;kcal/mol) and lower than adagrasib (-71.73&#xa0;kcal/mol), both FDA-approved KRAS<sup>G12C</sup> inhibitors. Benchmarking against BTK<sup>481C</sup> using zanubrutinib, an FDA-approved therapeutic agent for B-cell malignancies, further validated the protocol. Peptide inhibitors XDYMA, XDYVL, and QDWXL demonstrated BFEs of -83.40, -76.69, and -62.40&#xa0;kcal/mol, outperforming zanubrutinib (-57.00&#xa0;kcal/mol), acalabrutinib (-54.19&#xa0;kcal/mol), and ibrutinib (-55.09&#xa0;kcal/mol).</p> Discussion <p>These findings underscore the robustness and adaptability of our protocol, offering a systematic, multifaceted approach that can be integrated into drug discovery workflows to design novel peptide-based irreversible inhibitors.</p>

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De Novo Rational design of peptide-based covalent inhibitors via mapping of complementary binding site residues – technical protocol and case study on KRASG12C and BTK481C

  • Ernest Oduro-Kwateng,
  • Musab Ali,
  • Ibrahim Oluwatobi Kehinde,
  • Li Rao,
  • Mahmoud E. S. Soliman

摘要

Background

Targeting undruggable proteins and challenging binding sites, such as protein–protein interaction (PPI) interfaces and allosteric pockets, using small-molecule inhibitors is often infeasible. Peptide-based irreversible inhibitors are promising emerging strategies for the treatment of such targets. However, there is currently no systematic in silico protocol for the rational design of peptide-based covalent inhibitors.

Methods

We developed a streamlined computational framework for the de novo design of peptide-based irreversible inhibitors. Key considerations include peptide sequence optimization for binding, selection of electrophilic warheads, peptide folding, target specificity, and pharmacokinetic and toxicity profiles. Binding affinities were estimated using covalent molecular dynamics (MDcov) simulations and thermodynamic binding free energy calculations.

Results

Using KRASG12C, a strategic drug target traditionally considered undruggable, as a case study, the protocol identified top-hit peptide inhibitors (RVKDX, HVKXR, and XLKDH) with binding free energies (BFEs) of -48.84, -48.93, and -48.67 kcal/mol, respectively. These values are comparable to sotorasib (-50.63 kcal/mol) and lower than adagrasib (-71.73 kcal/mol), both FDA-approved KRASG12C inhibitors. Benchmarking against BTK481C using zanubrutinib, an FDA-approved therapeutic agent for B-cell malignancies, further validated the protocol. Peptide inhibitors XDYMA, XDYVL, and QDWXL demonstrated BFEs of -83.40, -76.69, and -62.40 kcal/mol, outperforming zanubrutinib (-57.00 kcal/mol), acalabrutinib (-54.19 kcal/mol), and ibrutinib (-55.09 kcal/mol).

Discussion

These findings underscore the robustness and adaptability of our protocol, offering a systematic, multifaceted approach that can be integrated into drug discovery workflows to design novel peptide-based irreversible inhibitors.