What We Are Doing
What We Have Done Already
BindingSIGHTS is an advanced suite of computational tools built from proprietary, open source and commercial software for both “hit” identification and drug optimization. The technology is very effective to rapidly identify novel chemical matter for challenging molecular drug targets.
BindingSIGHTS enables 1) sophisticated virtual screening for hit finding and hit-to-lead and 2) structure-based and ligand-based drug design for lead optimization.
The problem: Finding drug-like compounds that can be rapidly optimized
A critical step in any successful drug discovery program is finding a good “hit” compound. For orphan nuclear receptors, current hit finding/screening approaches have proven particularly unsatisfactory. The traditional Pharma approach of massive high throughput screens (HTS) with several million compound libraries frequently fails. Stumbling blocks to this approach include the difficultly of balancing the opposing demands of assay quality and assay throughput/cost as well as the difficulty in maintaining a large, yet high quality, compound collection. In particular, compound libraries are frequently comprised of legacy compounds designed for past drug targets or of combinatorial compounds designed for ease of synthesis and not drug-likeness. Very few Big Pharma libraries have chemical compounds that were rationally designed for specific target classes. Far too often HTS screens yield cul-de-sac compounds, chemical series with flat SAR that are not developable as drugs. Many in the Pharma industry know that the old axiom “Garbage in; Garbage out” sometimes describes an HTS campaign.
— Our solution —
Our solution to the above shortcomings was to develop a proprietary computational platform to design a small set of drug-like compounds for a target. BindingSIGHTS leverages structure information from an entire protein family to find and design drug-like compounds. For example, more than 300 nuclear receptor protein crystal structures were aligned in 3D and patterns of atomic interactions between ligands and proteins were catalogued. From this catalogue we identified patterns of atomic interactions characteristic of nuclear receptor antagonists/inverse agonists. What distinguishes BindingSIGHTS from other in silico screening approaches is that patterns of functional interactions are used to select compounds in addition to a calculated energy score. We have used these patterns to mine our MANIFOLD virtual library for compounds that make productive interactions with RAR-related orphan receptor gamma (RORγt), a nuclear receptor important in autoimmune disease and cancer. Crucially, the ultimately identified leads proved effective in inflammatory bowel disease animal models.
In summary, for targets with protein crystal structures, BindingSIGHTS can be used to select a few thousand highly relevant drug-like compounds for lab based screening instead of millions, significantly saving time and money. Since the MANIFOLD library is indexed for drug-like properties, druggable leads result from BindingSIGHTS.
MANIFOLD LIBRARY
The MANIFOLD library catalogues nearly every screening and building block compound in the world today, more than 200 million available for purchase. This is the largest indexed collection of compounds in the industry today. MANIFOLDs comprehensive listing of purchasable compounds is the raw material for our BindingSIGHTS platform. To improve the handling of such a large number compounds, MANIFOLD is indexed by chemical properties such as molecular weight and polar surface area. In effect, we create a “phonebook” for finding the right drug-like molecule. In addition to every compound in the world today, MANIFOLD is also used to assemble compounds in silico that can be readily made tomorrow with chemical “building blocks” from today. MANIFOLD has 15 million “building blocks”; small compounds with reactive chemical “connectors”. Using BindingSIGHTS algorithms, several building blocks are combined via chemical connectors into new virtual compounds. In this way we create MANIFOLD virtual libraries (MANIFOLD_Vs). Within BindingSIGHTS we create rules to ensure that only synthetically tractable, patentable, and drug-like virtual compounds are assembled by the computer. Targeting what to assemble is necessary as a quadrillion compounds could be assembled into MANIFOLD_V libraries. In this way, novel compounds that are readily synthesizable by our chemists are generated.
In effect, MANIFOLD is a catalogue of the available chemical world, a listing of compounds that can be quickly purchased or made with materials available today. Thus, MANIFOLD is prospective, containing new and novel compounds; by contrast, traditional Pharma HTS collections are retrospective, containing mostly old and historic compounds. MANIFOLD replaces expensive historic compound collections with cost efficient virtual compound collections and just-in-time ordering to collect focused sets of novel compounds for laboratory screening.
Portfolio
Retinoic Acid-Related Orphan Nuclear Receptor γ t (RORγt )
RORγt is a nuclear receptor expressed in lymphocytes. It is the key transcription factor that is both necessary and sufficient to drive the differentiation of IL-17A/F producing T-helper lymphocytes (Th17 cells). It has been shown that Th17 cells are critical mediators of the immunopathology of many human autoimmune diseases. These include rheumatoid arthritis, multiple sclerosis, psoriasis, inflammatory bowel disease, asthma, COPD and others. Furthermore, in several animal models of autoimmune diseases the reduction in the number and/or activity of Th17 cells has conferred a protective effect.
Inverse agonists of RORγt will affect three key aspects of Th17 cell-mediated disease. One is to reduce the differentiation of precursor lymphocytes to Th17 cells. Secondly, RORγt inverse agonists will reduce the expression of the IL-23 receptor and thus abrogate IL-23 mediated stabilization of Th17 cells at sites of inflammation. The third aspect is to inhibit the production of IL-17A/F, and other proinflammatory cytokines, from terminally differentiated Th17 cells. It should be noted that other immune cells including gd T-cells, innate lymphoid cells and iNKT cells also have RORγt+ sub-lineages. As such, specific oral small molecule antagonists of RORγt will confer a resolution to the inflammatory disease state that will have several important advantages over current therapies.
These current therapies, such as the recombinant biologics and broad-based immunosuppressives, suffer from many serious side effects. These include injection site reactions, increased risk of life-threatening infections, anti-DNA and anti-nuclear antibody stimulation, and kidney and liver toxicities. RORγt antagonists should ameliorate and/or eliminate many of these side effects.
More than 2% of the world population suffers from nearly 70 distinct autoimmune diseases and many patients find the current therapeutic armamentarium inadequate or ineffective to treat their disease.
Furthermore, recent studies of various cancers suggest that IL-17A/F, IL-23 and Th17 cells are key drivers of resistance to chemotherapy. In colorectal tumors chemotherapy induces stromal cells to secrete high levels of IL-17A. Cancer-initiating cells respond to the IL-17A with increased self-renewal and invasion. RORγt inverse agonists will reduce the stromally derived IL-17A/F leading to increased efficacy, especially in colorectal cancer associated within the context of inflammatory bowel disease.
Visionary Pharmaceuticals is poised to deliver a transformative first-in-class therapeutic modality to treat many of these patients in these areas of substantially unmet medical need.
Serum and Glucocorticoid Regulated Kinase 1 (SGK1)
SGK1 is a serine-threonine protein kinase expressed in lymphocytes and other cell types. SGK1 is a critical regulator of IL-23 receptor expression and Th17 cell stabilization. Salt-induced SGK1 expression promotes Th17 cell differentiation in vitro and in vivo which leads to the development of autoimmunity. Potent and selective SGK1 kinase inhibitors will be effective in reducing Th17 cell populations at sites of inflammation and thus treating autoimmune diseases.
Additionally, SGK1 is expressed in many tumor types. In colorectal cancer SGK1 expression correlates with taxol resistance. In both multiple myeloma cells and prostate cancer cells it promotes malignant growth. Approximately half of all breast tumors demonstrate highly elevated levels of SGK1. Importantly, in triple negative breast cancer SGK1 is associated with resistance to AKT inhibitors and a shorter relapse free survival.
The tumor metastasis suppressor, N-myc Downstream Regulated Gene (NDRG) 1 is a known mediator of resistance to alkylating chemotherapy in various tumors. Phosphorylation of NDRG1 by SGK1 correlates with chemoresistance.
SGK1 inhibitors will provide a significant new therapeutic opportunity in treating cancer, especially triple negative breast cancer.