Small molecule structure based drug design efforts in the pharmaceutical industry have, until recently, focused on the reversible non-covalent binding of ligands with target proteins. An alternative mechanism is the covalent binding of the ligand to the target protein, with around 30% of currently marketed drugs falling into this category. However, for most of these drugs, the covalent binding mechanism was serendipitous, not a design strategy, with their mechanism of action discovered long after their clinical utility had been established. Penicillin and aspirin are prominent examples of this. Despite the inherent advantages provided by the covalent binding mechanism, such as increased potency and increased residence times, it was purposefully avoided as a design strategy due to concerns that irreversible off- target interactions would lead to increased risk of toxicity and immunological response. However, the emergence of strategies to mitigate these risks, thereby allowing development of so-called targeted covalent inhibitors (TCIs), has prompted the establishment of numerous pharmaceutical industry covalent inhibitor drug discovery programs. The basic design strategy employed by TCI discovery programs aims at achieving a two-step process that first starts with reversible non- covalent binding with the target protein, followed by covalent bond formation between an electrophile on the ligand (often called a warhead) and a nucleophilic center in the protein. This multifaceted nature of the TCI mechanism for selectivity and potency is challenging for structure based discovery efforts. Furthermore, the current absence of computational tools that can provide accurate quantitative insight means that optimization of TCIs must be done exclusively by expensive and repeated rounds of synthesis, assay, and X-ray crystallography.
The aim of this fast-track SBIR proposal, then, is to develop a novel molecular modeling software tool that can provide thermodynamic binding as well as reaction reversibility information for purposes of ranking prospective covalent inhibitor molecules. This tool will calculate free energies of covalent binding of candidate molecules to targeted protein residues, as well as free energies of binding for the pre- reactive non-covalent binding step. It will also provide a calculated free energy-based estimate of reaction reversibility. This software will be based on mining minima free energy calculation methodology and will be developed as an extension of VeraChem?s VM2 free energy software platform.
This project aims to develop a software tool that can predict how a class of drugs called targeted covalent inhibitors (TCIs) bind with their targeted proteins. Covalent inhibitors have significant advantages over more traditional non-covalent inhibitors, such as lower and less frequent dosing required due to increased potency and residency. However, when designing TCIs scientists must maximize their selectivity to avoid toxicity issues, a difficult task due to the complexity of their mechanism of binding. Because of this complexity, no currently available tools can provide accurate enough information to aid scientists in this process; therefore, the proposed project will provide a new capability useful for the development of products to treat human disease.
