In the proposed study, a novel approach which has already generated multiple commercial sales for SilcsBio, LLC, Site-Identification by Ligand Competitive Saturation (SILCS), will be further developed to address customer requests and concerns around SILCS utility. Successful commercial application of computational methods for ligand design require a platform that provides both qualitative data to direct the design process and rapid production of quantitative data to allow for rigorous evaluation of specific ligand possibilities Both of those attributes form the core of SILCS technology. However, it is necessary to extend the SILCS technology to be accessible to a wide range of computational software packages and to be readily used in database screenings. Most importantly, while customers report large improvements in predictive capacity using SILCS technology (reduced time to lead from 12 months to 6 months, identification of unique scaffolds for an 'undruggable target, better matches of scoring to actual performance), modest improvements in accuracy are requested by customers in order to have a large impact on the development of new therapeutics. For a given target, SILCS involves a one-time up-front preconditioning step where the target protein, RNA or any macromolecule target of interest, in the absence of any drug-like ligands, is immersed in an aqueous solution of small organic solutes and subjected to exhaustive molecular dynamics (MD) simulations. From these simulations 3D probability distributions of different chemical functional classes on the entire surface of the target are generated based on rigorous free energy criteria, including protein flexibility. These probability distributions are then converted to free energies based on a Boltzmann distribution yielding Grid Free Energies (GFE). The probability distributions are normalized with respect to the organic solutes in pure aqueous solution, such that the GFEs include energetic contributions from desolvation of both the solutes and the protein surface, as well as interactions of the solutes with the protein. The GFE distributions, termed FragMaps, may then be used in a qualitative fashion to identify regions on the protein surface that interact favorably with differet classes of functional groups (hot spots), thereby directing ligand design. The GFEs may also be used to estimate ligand relative free energies of binding thereby facilitating quantitative evaluation of specific design outcomes. As the SILCS method is based on one-time preconditioning simulations of the target molecule, a process that can be completed in several days on commodity computer clusters, the quantitative free energy binding estimates based on the FragMaps can be performed on large numbers of compounds in a matter seconds allowing for wide ranges of ligand modifications to be evaluated. Specific goals for the proposed SBIR include 1) extending SILCS technology and GFE FragMaps to formats accessible to computational chemistry software packages, 2) improving the accuracy of SILCS GFE FragMaps and 3) extending SILCS GFEs for use in database screening. Success of the Phase I aspect of the proposal will be based on the following milestones: i) SILCS computational platform: Ability to generate, read and visualize SILCS GFE FragMaps using publically and commercially available computational chemistry software, 2) SILCS accuracy: Improved prediction of relative binding energies of known ligand-protein complexes, and 3) SILCS database screening: Ability to identify known ligands from database screening using pharmacophore models based on SILCS GFEs. Commercialization of these substantial improvements to the SILCS technology will occur through SilcsBio's existing marketing channels which include partnering with computational chemistry software vendors to make the technology available for licensing for in-house use by pharmaceutical companies and SilcsBio acting as a contract research organization (CRO) performing structure-based ligand design. CRO work includes supplying and interpreting GFE FragMaps to customers, a product that can, importantly, be supplied without customers revealing their IP as the Fragmaps are generated in the absence of ligands. Successful completion of this Phase I proposal is anticipated to lay the foundation for a Phase II SBIR to improve and expand the SILCS platform by 1) extending the technology to occluded target ligand binding sites not accessible to the surrounding aqueous environment, such as those commonly found in many GPCRs, 2) extending SILCS into a product that will be marketable for in-house use by pharmaceutical companies and 3) developing the necessary infrastructure required for SilcsBio to be a successful CRO.
The existent SILCS technology has proven three critical elements to the drug development process, each of which can be dramatically improved under this research proposal and will alter the manner/costs with which new drugs are brought to market. 1) Reduction in time/effort to develop lead candidates caused by a reduction of wet lab work that would remove hundreds of thousands of dollars from each lead development. 2) Identification of unique scaffolds not otherwise obvious in other modeling technologies and unlikely to have been identified through wet lab process. By providing broader lead generating opportunities, the probability of designing a viable drug greatly increases resulting in a better chance of curing serious diseases. 3) Better scoring functions allow better qualitative assessment of toxicology concerns, synthesis concerns and other downstream development considerations.
