Experimental and Computational Methods to Assess Central Nervous System Penetration of Small Molecules.

In CNS drug discovery, the estimation of brain exposure to lead compounds is critical for their optimization. Compounds need to cross the blood-brain barrier (BBB) to reach the pharmacological targets in the CNS. The BBB is a complex system involving passive and active mechanisms of transport and efflux transporters such as P-glycoproteins (P-gp) and breast cancer resistance protein (BCRP), which play an essential role in CNS penetration of small molecules. Several in vivo, in vitro, and in silico methods are available to estimate human brain penetration. Preclinical species are used as in vivo models to understand unbound brain exposure by deriving the Kp,uu parameter and the brain/plasma ratio of exposure corrected with the plasma and brain free fraction. The MDCK-mdr1 (Madin Darby canine kidney cells transfected with the MDR1 gene encoding for the human P-gp) assay is the commonly used in vitro assay to estimate compound permeability and human efflux. The in silico methods to predict brain exposure, such as CNS MPO, CNS BBB scores, and various machine learning models, help save costs and speed up compound discovery and optimization at all stages. These methods enable the screening of virtual compounds, building of a CNS penetrable compounds library, and optimization of lead molecules for CNS penetration. Therefore, it is crucial to understand the reliability and ability of these methods to predict CNS penetration. We review the in silico, in vitro, and in vivo data and their correlation with each other, as well as assess published experimental and computational approaches to predict the BBB penetrability of compounds.

Artificial Intelligence-Enabled De Novo Design of Novel Compounds that Are Synthesizable.

Development of computer-aided de novo design methods to discover novel compounds in a speedy manner to treat human diseases has been of interest to drug discovery scientists for the past three decades. In the beginning, the efforts were mostly concentrated to generate molecules that fit the active site of the target protein by sequential building of a molecule atom-by-atom and/or group-by-group while exploring all possible conformations to optimize binding interactions with the target protein. In recent years, deep learning approaches are applied to generate molecules that are iteratively optimized against a binding hypothesis (to optimize potency) and predictive models of drug-likeness (to optimize properties). Synthesizability of molecules generated by these de novo methods remains a challenge. This review will focus on the recent development of synthetic planning methods that are suitable for enhancing synthesizability of molecules designed by de novo methods.

Understanding allosteric interactions in hMLKL protein that modulate necroptosis and its inhibition.

Mixed Lineage Kinase domain-Like (MLKL), a key player in necroptosis, is a multi-domain protein with an N-terminal 4 helical bundle (4HB) and a pseudokinase domain (PsK) connected by brace helices. Phosphorylation of PsK domain of MLKL is a key step towards oligomerization of 4HB domain that causes cell death. Necrosulfonamide (NSA) binds to the 4HB domain of MLKL to inhibit necroptosis. To understand the molecular details of MLKL function and it's inhibition, we have performed a molecular dynamic study on hMLKL protein in apo, phosphorylated and NSA-bound states for a total 3 µs simulation time. Our simulations show increased inter-domain flexibility, increased rigidification of the activation loop and increased alpha helical content in the brace helix region revealing a form of monomeric hMLKL necessary for oligomerization upon phosphorylation as compared to apo state. NSA binding disrupts this activated form and causes two main effects on hMLKL conformation: (1) locking of the relative orientation of 4HB and PsK domains by the formation of several new interactions and (2) prevention of key 4HB residues to participate in cross-linking for oligomer formation. This new understanding of the effect of hMLKL conformations on phosphorylation and NSA binding suggest new avenues for designing effective allosteric inhibitors of hMLKL.

A Quantum-Inspired Method for Three-Dimensional Ligand-Based Virtual Screening.

Measuring similarity between molecules is an important part of virtual screening (VS) experiments deployed during the early stages of drug discovery. Most widely used methods for evaluating the similarity of molecules use molecular fingerprints to encode structural information. While similarity methods using fingerprint encodings are efficient, they do not consider all the relevant aspects of molecular structure. In this paper, we describe a quantum-inspired graph-based molecular similarity (GMS) method for ligand-based VS. The GMS method is formulated as a quadratic unconstrained binary optimization problem that can be solved using a quantum annealer, providing the opportunity to take advantage of this nascent and potentially groundbreaking technology. In this study, we consider various features relevant to ligand-based VS, such as pharmacophore features and three-dimensional atomic coordinates, and include them in the GMS method. We evaluate this approach on various datasets from the DUD_LIB_VS_1.0 library. Our results show that using three-dimensional atomic coordinates as features for comparison yields higher early enrichment values. In addition, we evaluate the performance of the GMS method against conventional fingerprint approaches. The results demonstrate that the GMS method outperforms fingerprint methods for most of the datasets, presenting a new alternative in ligand-based VS with the potential for future enhancement.

CDK12-mediated transcriptional regulation of noncanonical NF-κB components is essential for signaling.

Members of the family of nuclear factor κB (NF-κB) transcription factors are critical for multiple cellular processes, including regulating innate and adaptive immune responses, cell proliferation, and cell survival. Canonical NF-κB complexes are retained in the cytoplasm by the inhibitory protein IκBα, whereas noncanonical NF-κB complexes are retained by p100. Although activation of canonical NF-κB signaling through the IκBα kinase complex is well studied, few regulators of the NF-κB-inducing kinase (NIK)-dependent processing of noncanonical p100 to p52 and the subsequent nuclear translocation of p52 have been identified. We discovered a role for cyclin-dependent kinase 12 (CDK12) in transcriptionally regulating the noncanonical NF-κB pathway. High-content phenotypic screening identified the compound 919278 as a specific inhibitor of the lymphotoxin ß receptor (LTßR), and tumor necrosis factor (TNF) receptor superfamily member 12A (FN14)-dependent nuclear translocation of p52, but not of the TNF-α receptor-mediated nuclear translocation of p65. Chemoproteomics identified CDK12 as the target of 919278. CDK12 inhibition by 919278, the CDK inhibitor THZ1, or siRNA-mediated knockdown resulted in similar global transcriptional changes and prevented the LTßR- and FN14-dependent expression of MAP3K14 (which encodes NIK) as well as NIK accumulation by reducing phosphorylation of the carboxyl-terminal domain of RNA polymerase II. By coupling a phenotypic screen with chemoproteomics, we identified a pathway for the activation of the noncanonical NF-κB pathway that could serve as a therapeutic target in autoimmunity and cancer.

Investigating small molecules to inhibit germinal center kinase-like kinase (GLK/MAP4K3) upstream of PKCθ phosphorylation: Potential therapy to modulate T cell dependent immunity.

Germinal center kinase-like kinase (GLK, also known as MAP4K3) has been hypothesized to have an effect on key cellular activities, including inflammatory responses. GLK is required for activation of protein kinase C-θ (PKCθ) in T cells. Controlling the activity of T helper cell responses could be valuable for the treatment of autoimmune diseases. This approach circumvents previous unsuccessful approaches to target PKCθ directly. The use of structure based drug design, aided by the first crystal structure of GLK, led to the discovery of several inhibitors that demonstrate potent inhibition of GLK biochemically and in relevant cell lines.

Germinal-center kinase-like kinase co-crystal structure reveals a swapped activation loop and C-terminal extension.

Germinal-center kinase-like kinase (GLK, Map4k3), a GCK-I family kinase, plays multiple roles in regulating apoptosis, amino acid sensing, and immune signaling. We describe here the crystal structure of an activation loop mutant of GLK kinase domain bound to an inhibitor. The structure reveals a weakly associated, activation-loop swapped dimer with more than 20 amino acids of ordered density at the carboxy-terminus. This C-terminal PEST region binds intermolecularly to the hydrophobic groove of the N-terminal domain of a neighboring molecule. Although the GLK activation loop mutant crystallized demonstrates reduced kinase activity, its structure demonstrates all the hallmarks of an "active" kinase, including the salt bridge between the C-helix glutamate and the catalytic lysine. Our compound displacement data suggests that the effect of the Ser170Ala mutation in reducing kinase activity is likely due to its effect in reducing substrate peptide binding affinity rather than reducing ATP binding or ATP turnover. This report details the first structure of GLK; comparison of its activation loop sequence and P-loop structure to that of Map4k4 suggests ideas for designing inhibitors that can distinguish between these family members to achieve selective pharmacological inhibitors.

Fragment-Based Discovery of Dual JC Virus and BK Virus Helicase Inhibitors.

There are currently no treatments for life-threatening infections caused by human polyomaviruses JCV and BKV. We therefore report herein the first crystal structure of the hexameric helicase of JCV large T antigen (apo) and its use to drive the structure-based design of dual JCV and BKV ATP-competitive inhibitors. The crystal structures obtained by soaking our early inhibitors into the JCV helicase allowed us to rapidly improve the biochemical activity of our inhibitors from 18 µM for the early 6-(2-methoxyphenyl)- and the 6-(2-ethoxyphenyl)-[1,2,4]triazolo[3,4-b][1,3,4]thiadiazole hits 1a and 1b to 0.6 µM for triazolopyridine 12i. In addition, we were able to demonstrate measurable antiviral activity in Vero cells for our thiazolopyridine series in the absence of marked cytotoxicity, thus confirming the usefulness of this approach.

Cocrystalline Solids of Telaprevir with Enhanced Oral Absorption.

A combination of coformer screening and modeling, followed by characterization using calorimetry, structure elucidation, and solubility led to the identification of novel crystalline forms of the hepatitis C protease inhibitor, telaprevir. The lead crystalline form, a cocrystalline solid of telaprevir with 4-aminosalycilic acid, was identified among the list of possible cocrystals via modeling and confirmed by initial screening. It displayed the most significant aqueous solubility improvement over the neat crystalline form. Enhancement of in vivo performance was further demonstrated: a 10-fold increase in bioavailability was achieved for the cocrystal in comparison to the neat nanocrystalline telaprevir and it was found to be not statistically different from the lead amorphous spray-dried formulation.