Discovery of a novel class of non-ATP site DFG-out state p38 inhibitors utilizing computationally assisted virtual fragment-based drug design (vFBDD)

Fragment-based design of small molecule PCSK9 inhibitors using simulated annealing of chemical potential simulations

PCSK9 is a protein secreted by the liver that binds to the low-density lipoprotein receptor (LDLR), causing LDLR internalization, decreasing the clearance of circulating LDL particles. Mutations in PCSK9 that strengthen its interactions with LDLR result in familial hypercholesterolemia (FH) and early onset atherosclerosis, while nonsense mutations of PCSK9 result in cardio-protective hypocholesterolemia. These observations led to PCSK9 inhibition for cholesterol lowering becoming a high-interest therapeutic target, with antibody drugs reaching the market. An orally-available small molecule drug is highly desirable, but inhibiting the PCSK9/LDLR protein-protein interaction (PPI) has proven challenging. Alternate approaches to finding good lead candidates are needed. Motivated by the FH mutation data on PCSK9, we found that modeling the PCSK9/LDLR interface revealed extensive electron delocalization between and within the protein partners. Based on this, we hypothesized that compounds assembled from chemical fragments could achieve the affinity required to inhibit the PCSK9/LDLR PPI if they were selected to interact with PCSK9 in a way that, like LDLR, also involves significant fractional charge transfer to form partially covalent bonds. To identify such fragments, Simulated Annealing of Chemical Potential (SACP) fragment simulations were run on multiple PCSK9 structures, using optimized partial charges for the protein. We designed a small molecule, composed of several fragments, predicted to interact at two sites on the PCSK9. This compound inhibits the PPI with 1 μM affinity. Further, we designed two similar small molecules where one allows charge delocalization though a linker and the other doesn’t. The first inhibitor with charge delocalization enhances LDLR surface expression by 60% at 10 nM, two orders of magnitude more potent than the EGF domain of LDLR. The other enhances LDLR expression by only 50% at 1 μM. This supports our conjecture that fragments can have surprisingly outsized efficacy in breaking PPI’s by achieving fractional charge transfer leading to partially covalent bonding.

Fragment-Based Ligand Designing

Fragment-based drug design strategies have been used in drug discovery since it was first demonstrated using experimental structural biology techniques such as nuclear magnetic resonance (NMR) and X-ray crystallography. The underlying idea is that existing or new chemical entities with known desirable properties may serve both as tool compounds and as starting points for hit-to-lead expansion. Despite the recent advancements, there remain challenges to overcome, such as assembly of the synthetically feasible structures, development of scoring functions to correlate structure and their activities, and fine tuning of the promising molecules. This chapter first covers the theoretical background needed to understand the concepts and the challenges related to the field of study, followed by the description of important protocols and related software. Case studies are presented to demonstrate practical applications.

2-Aminothiophene scaffolds: Diverse biological and pharmacological attributes in medicinal chemistry

2-Aminothiophenes are important five-membered heterocyclic building blocks in organic synthesis, and the chemistry of these small molecules is still developing based on the discovery of cyclization by Gewald. Another attractive feature of 2-aminothiophene scaffolds is their ability to act as synthons for the synthesis of biological active thiophene-containing heterocycles, conjugates and hybrids. Currently, the biological actions of 2-aminothiophenes or their 2-N-substituted analogues are still being investigated because of their various mechanisms of action (e.g., pharmacophore and pharmacokinetic properties). Likewise, the 2-aminothiophene family is used as diverse promising selective inhibitors, receptors, and modulators in medicinal chemistry, and these compounds even exhibit effective pharmacological properties in the various clinical phases of appropriate diseases. In this review, major biological and pharmacological reports on 2-aminothiophenes and related compounds have been highlighted; most perspective drug-candidate hits were selected for discussion and described, along with additional synthetic pathways. In addition, we focused on the literature dedicated to 2-aminothiophenes and 2-N-substituted derivatives, which have been published from 2010 to 2017.

Hot-spot identification on a broad class of proteins and RNA suggest unifying principles of molecular recognition

Chemically diverse fragments tend to collectively bind at localized sites on proteins, which is a cornerstone of fragment-based techniques. A central question is how general are these strategies for predicting a wide variety of molecular interactions such as small molecule-protein, protein-protein and protein-nucleic acid for both experimental and computational methods. To address this issue, we recently proposed three governing principles, (1) accurate prediction of fragment-macromolecule binding free energy, (2) accurate prediction of water-macromolecule binding free energy, and (3) locating sites on a macromolecule that have high affinity for a diversity of fragments and low affinity for water. To test the generality of these concepts we used the computational technique of Simulated Annealing of Chemical Potential to design one small fragment to break the RecA-RecA protein-protein interaction and three fragments that inhibit peptide-deformylase via water-mediated multi-body interactions. Experiments confirm the predictions that 6-hydroxydopamine potently inhibits RecA and that PDF inhibition quantitatively tracks the water-mediated binding predictions. Additionally, the principles correctly predict the essential bound waters in HIV Protease, the surprisingly extensive binding site of elastase, the pinpoint location of electron transfer in dihydrofolate reductase, the HIV TAT-TAR protein-RNA interactions, and the MDM2-MDM4 differential binding to p53. The experimental confirmations of highly non-obvious predictions combined with the precise characterization of a broad range of known phenomena lend strong support to the generality of fragment-based methods for characterizing molecular recognition.

Computational solvent mapping in structure-based drug design

Over the past two decades, solvent mapping has emerged as a useful tool for identifying hot spots within binding sites on proteins for drug-like molecules and suggesting properties of potential binders. While the experimental technique requires solving multiple crystal structures of a protein in different solvents, computational solvent mapping allows for fast analysis of a protein for potential binding sites and their druggability. Recent advances in genomics, systems biology and interactomics provide a multitude of potential targets for drug development and solvent mapping can provide useful information to help prioritize targets for drug discovery projects. Here, we review various approaches to computational solvent mapping, highlight some key advances and provide our opinion on future directions in the field.

Designing an orally available nontoxic p38 inhibitor with a fragment-based strategy

The MAPK p38 became a focal point of inflammatory research when it was recognized that it played a key role in the production of the pro-inflammatory molecules TNF-alpha, IL-beta, and cyclooxygenase-2 (COX-2). The pharmaceutical industry devoted enormous efforts to creating p38 inhibitors, because blocking p38 had the potential of downregulating a group of pro-inflammatory mediators, and thus, one drug could have a cocktail effect. The market potential seemed to be clearly established (Bonafede et al., Clinicoecon Outcomes Res 6:381-388, 2014) with a multiplicity of TNF-alpha antibodies and a soluble receptor (Mewar and Wilson, Br J Pharmacol 162:785-791, 2011) already on the market, although the relationship between TNF-alpha production and p38 activation is a complicated two-way (Sabio and Davis, Semin Immunol 26:237-245, 2014) signal transduction process. With the discovery that activated p38 stabilizes (Mancini and Di Battista, Inflamm Res 60:1083-1092, 2011) COX-2 mRNA and upregulates expression of IL-beta (Bachstetter and Van Eldik, Aging Dis 1:199-211, 2010) probably in a similar manner, inhibiting p38 appeared to be a way of blocking TNF-alpha, COX-2, and IL-beta simultaneously. At Locus Pharmaceuticals we jumped on this opportunity, because we believed that our fragment-based drug discovery approach was ideally suited for making a potent small molecule p38 inhibitor that did not bind in the ATP site, but also had the solubility, lack of planarity, and low molecular weight required of a clinical candidate. Just to be clear, in our experience highly planar compounds often result in poor pharmacokinetics, because they tend to bind strongly to plasma proteins. At Locus we typically repeated assays by adding increasing amounts of plasma to check for potency degradation in the presence of blood. We found this to be a useful early indicator of pharmacokinetics and in vivo behavior. It became clear from our work and the work of others that binding to the ATP site resulted in nonspecific isoform toxicities, but binding in the adjacent allosteric DFG-site resulted in molecules that were too planar and too hydrophobic. Applying the computational method of Simulated Annealing of Chemical Potential (SACP) to this problem, we at Locus were able to come up with surprising fragment substitution patterns that led to potent non-ATP p38 inhibitors with the solubility and lack of planarity that resulted in potent in vivo efficacy in rodents with 33 % oral bioavailability. By using the simulations, we made only a small number of molecules and created a high quality clinical candidate. We also did extensive co-crystallography work, which demonstrated that the compounds bound in the mode predicted by the simulations. Unfortunately, all p38 programs ultimately shut down, because compelling evidence emerged that inhibiting p38 had no long-term clinical (Genovese, Arthritis Rheum 60:317-320, 2009) benefit. Devoting a large amount of limited resources to a target that ultimately turns out to be a mistake because it was not properly validated is a fatal error for a small company, and this is one of the reasons that Locus ultimately failed.

Protein binding site analysis for drug discovery using a computational fragment-based method

One of the most powerful tools for designing drug molecules is an understanding of the target protein's binding site. Identifying key amino acids and understanding the electronic, steric, and solvation properties of the site enables the design of potent ligands. Of equal importance for the success of a drug discovery program is the evaluation of binding site druggability. Determining, a priori, if a particular binding site has the appropriate character to bind drug-like ligands saves research time and money.While there are a variety of experimental and computational techniques to identify and characterize binding sites, the focus of this chapter is on Binding Site Analysis (BSA) using virtual fragment simulations. The methodology of the technique is described, along with examples of successful application to drug discovery programs. BSA both indicates if a protein is a viable target for drug discovery and provides a roadmap for designing ligands. Using a computational fragment-based method is a effective means of understanding of a binding site.

Characterization of interactions and pharmacophore development for DFG-out inhibitors to RET tyrosine kinase

RET (rearranged during transfection) tyrosine kinase is a promising target for several human cancers. Abt-348, Birb-796, Motesanib and Sorafenib are DFG-out multi-kinase inhibitors that have been reported to inhibit RET activity with good IC50 values. Although the DFG-out conformation has attracted great interest in the design of type II inhibitors, the structural requirements for binding to the RET DFG-out conformation remains unclear. Herein, the DFG-out conformation of RET was determined by homology modelling, the four inhibitors were docked, and the binding modes investigated by molecular dynamics simulation. Binding free energies were calculated using the molecular mechanics/Poisson-Bolzmann surface area (MM/PBSA) method. The trends in predicted binding free affinities correlated well with experimental data and were used to explain the activity difference of the studied inhibitors. Per-residue energy decomposition analyses provided further information on specific interaction properties. Finally, we also conducted a detailed e-pharmacophore modelling of the different RET-inhibitor complexes, explaining the common and specific pharmacophore features of the different complexes. The results reported herein will be useful in future rational design of novel DFG-out RET inhibitors.

Virtual fragment preparation for computational fragment-based drug design

Fragment-based drug design (FBDD) has become an important component of the drug discovery process. The use of fragments can accelerate both the search for a hit molecule and the development of that hit into a lead molecule for clinical testing. In addition to experimental methodologies for FBDD such as NMR and X-ray Crystallography screens, computational techniques are playing an increasingly important role. The success of the computational simulations is due in large part to how the database of virtual fragments is prepared. In order to prepare the fragments appropriately it is necessary to understand how FBDD differs from other approaches and the issues inherent in building up molecules from smaller fragment pieces. The ultimate goal of these calculations is to link two or more simulated fragments into a molecule that has an experimental binding affinity consistent with the additive predicted binding affinities of the virtual fragments. Computationally predicting binding affinities is a complex process, with many opportunities for introducing error. Therefore, care should be taken with the fragment preparation procedure to avoid introducing additional inaccuracies.This chapter is focused on the preparation process used to create a virtual fragment database. Several key issues of fragment preparation which affect the accuracy of binding affinity predictions are discussed. The first issue is the selection of the two-dimensional atomic structure of the virtual fragment. Although the particular usage of the fragment can affect this choice (i.e., whether the fragment will be used for calibration, binding site characterization, hit identification, or lead optimization), general factors such as synthetic accessibility, size, and flexibility are major considerations in selecting the 2D structure. Other aspects of preparing the virtual fragments for simulation are the generation of three-dimensional conformations and the assignment of the associated atomic point charges.

Novel approaches for targeting kinases: allosteric inhibition, allosteric activation and pseudokinases

Protein kinases are involved in many essential cellular processes and their deregulation can lead to a variety of diseases, including cancer. The pharmaceutical industry has invested heavily in the identification of kinase inhibitors to modulate these disease-promoting pathways, resulting in several successful drugs. However, the field is challenging as it is difficult to identify novel selective inhibitors with good pharmacokinetic/pharmacodynamic properties. In addition, resistance to kinase inhibitor treatment frequently arises. The identification of non-ATP site targeting ('allosteric') inhibitors, the identification of kinase activators and the expansion of kinase target space to include the less studied members of the family, including atypical- and pseudo-kinases, are potential avenues to overcome these challenges. In this perspective, the opportunities and challenges of following these approaches and others will be discussed.

Fragment-based approaches to the discovery of kinase inhibitors

Protein kinases are one of the most important families of drug targets, and aberrant kinase activity has been linked to a large number of disease areas. Although eminently targetable using small molecules, kinases present a number of challenges as drug targets, not least obtaining selectivity across such a large and relatively closely related target family. Fragment-based drug discovery involves screening simple, low-molecular weight compounds to generate initial hits against a target. These hits are then optimized to more potent compounds via medicinal chemistry, usually facilitated by structural biology. Here, we will present a number of recent examples of fragment-based approaches to the discovery of kinase inhibitors, detailing the construction of fragment-screening libraries, the identification and validation of fragment hits, and their optimization into potent and selective lead compounds. The advantages of fragment-based methodologies will be discussed, along with some of the challenges associated with using this route. Finally, we will present a number of key lessons derived both from our own experience running fragment screens against kinases and from a large number of published studies.

Protein crystallography and fragment-based drug design

Crystallography is a major tool for structure-driven drug design, as it allows knowledge of the 3D structure of protein targets and protein-ligand complexes. However, the route for crystal structure determination involves many steps, some of which may hamper its high-throughput use. Recent efforts have produced significant advances in experimental and computational tools and protocols. They include automatic crystallization tools, faster data collection devices, more efficient phasing methods and improved ligand-fitting procedures. The timescales of drug-discovery processes have been also reduced by using a fragment-based screening approach. Herein, the achievements in protein crystallography over the last 5 years are reviewed, and advantages and disadvantages of the fragment-based approaches to drug discovery that make use of x-ray crystallography as a primary screening method are examined. In particular, in some detail, five recent case studies pertaining to the development of new hits or leads in relevant therapeutic areas, such as cancer, immune response, inflammation, metabolic syndrome and neurology are described.

The future of molecular dynamics simulations in drug discovery

Molecular dynamics simulations can now track rapid processes—those occurring in less than about a millisecond—at atomic resolution for many biologically relevant systems. These simulations appear poised to exert a significant impact on how new drugs are found, perhaps even transforming the very process of drug discovery. We predict here future results we can expect from, and enhancements we need to make in, molecular dynamics simulations over the coming 25 years, and in so doing set out several Grand Challenges for the field. In the context of the problems now facing the pharmaceutical industry, we ask how we can best address drug discovery needs of the next quarter century using molecular dynamics simulations, and we suggest some possible approaches.