Project Summary: The global pharmaceutical industry relies heavily on structure-based and computer- aided drug design where the prediction of relative binding free energies (RBFEs) of ligands is a key step in lead optimization. Pharmaceutical companies leverage “free energy simulations” to predict RBFEs to drug targets and design selectivity to circumvent off-target effects. However, the extraordinarily large number of candidate compounds in the chemical design space, and the lack of affordable software that has both the required advanced features and high-throughput GPU-accelerated work?ows that enable effective use at scale, taken together, make it extremely challenging to perform these calculations in practice. Further, the technology itself is rapidly evolving and new methods that increase predictive capability are eagerly sought after. The AMBER software suite is an academic code that has had a sustained worldwide developer and user base (currently ?30K) for 40 years, and is available for commercial use through a low-cost single site license that makes it a potentially attractive tool if it's capabilities could be made to meet the needs of industry drug discovery applications. The York Lab at Rutgers has developed the GPU-accelerated free energy simulation capability introduced in the latest release of AMBER, supported by a contract grant with Merck and Co., Inc., and has very recently extended these capabilities in the AMBER Drug Discovery (DD) Boost package. The DD Boost package has gained attention from several pharmaceutical companies that are interested to potentially provide support to accelerate the implementation of high-priority new technology and to participate in beta testing in advance of it's full integration into the of?cial AMBER software suite which occurs on a 2-year cycle. Unfortunately, the direct subcontract mechanism used previously with Merck was greatly hindered by lengthy Rutgers-Merck negotiations, and is not one that is easily repeatable or attractive to the broader pharma industries. Hence, a critical barrier to progress is that there is currently no framework for pharma companies to guide and support the advancement of AMBER for drug discovery. This SBIR proposal will create a sustainable mechanism to develop powerful new industry-guided enabling technologies for drug design in AMBER. In Phase I, we will enhance the capabilities of the AMBER DD Boost by integrating newly developed technology with robust work?ows to streamline throughput for real-world industry applications at scale - in essence creating a prototype software product that companies can beta test and evaluate. This will set the stage for Phase II, where we will work to fully implement our business model to develop custom methods for drug discovery in AMBER DD Boost that are guided by an Industry Advisory Board and supported by a consortium of big pharma companies.
