Structure-based discovery of potent WD repeat domain 5 inhibitors that demonstrate efficacy and safety in preclinical animal models.

WD repeat domain 5 (WDR5) is a core scaffolding component of many multiprotein complexes that perform a variety of critical chromatin-centric processes in the nucleus. WDR5 is a component of the mixed lineage leukemia MLL/SET complex and localizes MYC to chromatin at tumor-critical target genes. As a part of these complexes, WDR5 plays a role in sustaining oncogenesis in a variety of human cancers that are often associated with poor prognoses. Thus, WDR5 has been recognized as an attractive therapeutic target for treating both solid and hematological tumors. Previously, small-molecule inhibitors of the WDR5-interaction (WIN) site and WDR5 degraders have demonstrated robust in vitro cellular efficacy in cancer cell lines and established the therapeutic potential of WDR5. However, these agents have not demonstrated significant in vivo efficacy at pharmacologically relevant doses by oral administration in animal disease models. We have discovered WDR5 WIN-site inhibitors that feature bicyclic heteroaryl P7 units through structure-based design and address the limitations of our previous series of small-molecule inhibitors. Importantly, our lead compounds exhibit enhanced on-target potency, excellent oral pharmacokinetic (PK) profiles, and potent dose-dependent in vivo efficacy in a mouse MV4:11 subcutaneous xenograft model by oral dosing. Furthermore, these in vivo probes show excellent tolerability under a repeated high-dose regimen in rodents to demonstrate the safety of the WDR5 WIN-site inhibition mechanism. Collectively, our results provide strong support for WDR5 WIN-site inhibitors to be utilized as potential anticancer therapeutics.

Structure-based design and synthesis of sulfonylureas as novel NLRP3 inhibitors for Alzheimer's disease.

Alzheimer's disease (AD) remains an incurable neurodegenerative condition that poses a threat to humanity. Immune signaling in the brain, particularly the NLR family pyrin domain containing 3 (NLRP3), is currently targeted for AD treatment. Based on the crystal structure of the NACHT domain of NLRP3 and its renowned inhibitor MCC950, we designed and synthesized nineteen sulfonylurea compounds and evaluated their capacity to inhibit caspase-1 and interleukin-1ß (IL-1ß). Of these, nine were selected for measuring their IC50 for caspase-1 and cytotoxicity analysis. Finally, three compounds were chosen to assess their inhibitory effect on IL-1ß in mice. The results showed that compound 5m had a superior ability to reduce IL-1ß levels in the brain compared to MCC950 at a lower dosing concentration, indicating that 5m has the potential to penetrate the blood-brain barrier (BBB) and inhibit inflammation both in vitro and in vivo. Docking studies of compound 5m on NLRP3 revealed a binding mode similar to MCC950. These findings suggest that compound 5m holds promise as an NLRP3 inhibitor for AD treatment.

Structure-based design and optimization of a new class of small molecule inhibitors targeting the P-stalk binding pocket of ricin.

Ricin, a category-B agent for bioterrorism, and Shiga toxins (Stxs), which cause food poisoning bind to the ribosomal P-stalk to depurinate the sarcin/ricin loop. No effective therapy exists for ricin or Stx intoxication. Ribosome binding sites of the toxins have not been targeted by small molecules. We previously identified CC10501, which inhibits toxin activity by binding the P-stalk pocket of ricin toxin A subunit (RTA) remote from the catalytic site. Here, we developed a fluorescence polarization assay and identified a new class of compounds, which bind P-stalk pocket of RTA with higher affinity and inhibit catalytic activity with submicromolar potency. A lead compound, RU-NT-206, bound P-stalk pocket of RTA with similar affinity as a five-fold larger P-stalk peptide and protected cells against ricin and Stx2 holotoxins for the first time. These results validate the P-stalk binding site of RTA as a critical target for allosteric inhibition of the active site.

Structural-guided design to improve the catalytic performance of aldo-keto reductase KdAKR.

Aldo-keto reductases (AKRs) are important biocatalysts that can be used to synthesize chiral pharmaceutical alcohols. In this study, the catalytic activity and stereoselectivity of a NADPH-dependent AKR from Kluyveromyces dobzhanskii (KdAKR) toward t-butyl 6-chloro (5S)-hydroxy-3-oxohexanoate ((5S)-CHOH) were improved by mutating its residues in the loop regions around the substrate-binding pocket. And the thermostability of KdAKR was improved by a consensus sequence method targeted on the flexible regions. The best mutant M6 (Y28A/L58I/I63L/G223P/Y296W/W297H) exhibited a 67-fold higher catalytic efficiency compared to the wild-type (WT) KdAKR, and improved R-selectivity toward (5S)-CHOH (dep value from 47.6% to >99.5%). Moreover, M6 exhibited a 6.3-fold increase in half-life (t1/2 ) at 40°C compared to WT. Under the optimal conditions, M6 completely converted 200 g/L (5S)-CHOH to diastereomeric pure t-butyl 6-chloro-(3R, 5S)-dihydroxyhexanoate ((3R, 5S)-CDHH) within 8.0 h, with a space-time yield of 300.7 g/L/day. Our results deepen the understandings of the structure-function relationship of AKRs, providing a certain guidance for the modification of other AKRs.

Evaluating the druggability of TrmD, a potential antibacterial target, through design and microbiological profiling of a series of potent TrmD inhibitors.

The post-transcriptional modifier tRNA-(N1G37) methyltransferase (TrmD) has been proposed to be essential for growth in many Gram-negative and Gram-positive pathogens, however previously reported inhibitors show only weak antibacterial activity. In this work, optimisation of fragment hits resulted in compounds with low nanomolar TrmD inhibition incorporating features designed to enhance bacterial permeability and covering a range of physicochemical space. The resulting lack of significant antibacterial activity suggests that whilst TrmD is highly ligandable, its essentiality and druggability are called into question.

Peptide-based covalent inhibitors of protein-protein interactions.

Protein-protein interactions (PPI) are involved in all cellular processes and many represent attractive therapeutic targets. However, the frequently rather flat and large interaction areas render the identification of small molecular PPI inhibitors very challenging. As an alternative, peptide interaction motifs derived from a PPI interface can serve as starting points for the development of inhibitors. However, certain proteins remain challenging targets when applying inhibitors with a competitive mode of action. For that reason, peptide-based ligands with an irreversible binding mode have gained attention in recent years. This review summarizes examples of covalent inhibitors that employ peptidic binders and have been tested in a biological context.

Design and synthesis of 1H-pyrazolo[3,4-d]pyrimidine derivatives as hematopoietic progenitor kinase 1 (HPK1) inhibitors.

Despite immune checkpoint inhibitors' tremendous success in the treatment of tumors, the moderate response rate limits their widespread use. Hematopoietic progenitor kinase 1 (HPK1) is served as an essential negative regulator of T-cell receptor, which has been identified as a promising target for enhancing antitumor immunity. However, the development of a selective HPK1 inhibitor is still challenging. Herein, we reported a novel series of 1H-pyrazolo[3,4-d]pyrimidine derivatives as HPK1 inhibitors by structure-based rational design. The optimal compound 10n significantly inhibited HPK1 with an IC50 value of 29.0 nM and the phosphorylation of SLP76 at a concentration as low as 0.1 µM. Furthermore, compound 10n exhibited good selectivity over a panel of 25 kinases, including GLK from the same MAP4K family. Together, the current study provided a novel, potent, and selective HPK1 inhibitor, acting as a lead compound for the future development of cancer immunotherapy.

Homology modeling of Forkhead box protein C2: identification of potential inhibitors using ligand and structure-based virtual screening.

Overexpression of Forkhead box protein C2 (FOXC2) has been associated with different types of carcinomas. FOXC2 plays an important role in the initiation and maintenance of the epithelial-mesenchymal transition (EMT) process, which is essential for the development of higher-grade tumors with an enhanced ability for metastasis. Thus, FOXC2 has become a therapeutic target for the development of anticancer drugs. MC-1-F2, the only identified experimental inhibitor of FOXC2, interacts with the full length of FOXC2. However, only the DNA-binding domain (DBD) of FOXC2 has resolved crystal structure. In this work, a three-dimensional (3D) structure of the full-length FOXC2 using homology modeling was developed and used for structure-based drug design (SBDD). The quality of this 3D model of the full-length FOXC2 was evaluated using MolProbity, ERRAT, and ProSA modules. Molecular dynamics (MD) simulation was also carried out to verify its stability. Ligand-based drug design (LBDD) was carried out to identify similar analogues for MC-1-F2 against 15 million compounds from ChEMBL and ZINC databases. 792 molecules were retrieved from this similarity search. De novo SBDD was performed against the full-length 3D structure of FOXC2 through homology modeling to identify novel inhibitors. The combination of LBDD and SBDD helped in gaining a better insight into the binding of MC-1-F2 and its analogues against the full length of the FOXC2. The binding free energy of the top hits was further investigated using MD simulations and MM/GBSA calculations to result in eight promising hits as lead compounds targeting FOXC2.

Computational 3D Modeling-Based Identification of Inhibitors Targeting Cysteine Covalent Bond Catalysts for JAK3 and CYP3A4 Enzymes in the Treatment of Rheumatoid Arthritis.

This work aimed to find new inhibitors of the CYP3A4 and JAK3 enzymes, which are significant players in autoimmune diseases such as rheumatoid arthritis. Advanced computer-aided drug design techniques, such as pharmacophore and 3D-QSAR modeling, were used. Two strong 3D-QSAR models were created, and their predictive power was validated by the strong correlation (R2 values > 80%) between the predicted and experimental activity. With an ROC value of 0.9, a pharmacophore model grounded in the DHRRR hypothesis likewise demonstrated strong predictive ability. Eight possible inhibitors were found, and six new inhibitors were designed in silico using these computational models. The pharmacokinetic and safety characteristics of these candidates were thoroughly assessed. The possible interactions between the inhibitors and the target enzymes were made clear via molecular docking. Furthermore, MM/GBSA computations and molecular dynamics simulations offered insightful information about the stability of the binding between inhibitors and CYP3A4 or JAK3. Through the integration of various computational approaches, this study successfully identified potential inhibitor candidates for additional investigation and efficiently screened compounds. The findings contribute to our knowledge of enzyme-inhibitor interactions and may help us create more effective treatments for autoimmune conditions like rheumatoid arthritis.

A molecular evolution algorithm for ligand design in DOCK.

As a complement to virtual screening, de novo design of small molecules is an alternative approach for identifying potential drug candidates. Here, we present a new 3D genetic algorithm to evolve molecules through breeding, mutation, fitness pressure, and selection. The method, termed DOCK_GA, builds upon and leverages powerful sampling, scoring, and searching routines previously implemented into DOCK6. Three primary experiments were used during development: Single-molecule evolution evaluated three selection methods (elitism, tournament, and roulette), in four clinically relevant systems, in terms of mutation type and crossover success, chemical properties, ensemble diversity, and fitness convergence, among others. Large scale benchmarking assessed performance across 651 different protein-ligand systems. Ensemble-based evolution demonstrated using multiple inhibitors simultaneously to seed growth in a SARS-CoV-2 target. Key takeaways include: (1) The algorithm is robust as demonstrated by the successful evolution of molecules across a large diverse dataset. (2) Users have flexibility with regards to parent input, selection method, fitness function, and molecular descriptors. (3) The program is straightforward to run and only requires a single executable and input file at run-time. (4) The elitism selection method yields more tightly clustered molecules in terms of 2D/3D similarity, with more favorable fitness, followed by tournament and roulette.

Targeting non-alcoholic fatty liver disease: Design, X-ray co-crystal structure and synthesis of 'first-in-kind' inhibitors of serine/threonine kinase25.

We describe the synthesis of a series of 3-t-butyl 5-aminopyrazole p-substituted arylamides as inhibitors of serine-threonine25 (STK25), an enzyme implicated in the progression of non-alcoholic fatty liver disease (NAFLD). Appending a p-N-pyrrolidinosulphonamide group to the arylamide group led to a 'first-in kind' inhibitor with IC50 = 228 nM. A co-crystal structure with STK 25 revealed productive interactions which were also reproduced using molecular docking. A new series of triazolo dihydro oxazine carboxamides of 3-t-butyl 5-aminopyrazole was not active against STK25.

Structure-based optimization of hydroxylactam as potent, cell-active inhibitors of lactate dehydrogenase.

Structure-based design was utilized to optimize 6,6-diaryl substituted dihydropyrone and hydroxylactam to obtain inhibitors of lactate dehydrogenase (LDH) with low nanomolar biochemical and single-digit micromolar cellular potencies. Surprisingly the replacement of a phenyl with a pyridyl moiety in the chemical structure revealed a new binding mode for the inhibitors with subtle conformational change of the LDHA active site. This led to the identification of a potent, cell-active hydroxylactam inhibitor exhibiting an in vivo pharmacokinetic profile suitable for mouse tumor xenograft study.

Targeting the interaction of ß-catenin and TCF/LEF transcription factors to inhibit oncogenic Wnt signaling.

The Wnt/ß-catenin signaling pathway is crucially involved in embryonic development, stem cell maintenance and tissue renewal. Hyperactivation of this pathway is associated with the development and progression of various types of cancers. The transcriptional coactivator ß-catenin represents a pivotal component of the pathway and its interaction with transcription factors of the TCF/LEF family is central to pathway activation. Inhibition of this crucial protein-protein interaction via direct targeting of ß-catenin is considered a promising strategy for the inactivation of oncogenic Wnt signaling. This review summarizes advances in the development of Wnt antagonists that have been shown to directly bind ß-catenin.

Computational design, synthesis and biological evaluation of PDE5 inhibitors based on N2,N4-diaminoquinazoline and N2,N6-diaminopurine scaffolds.

We report the synthesis, and characterization of twenty-nine new inhibitors of PDE5. Structure-based design was employed to modify to our previously reported 2,4-diaminoquinazoline series. Modification include scaffold hopping to 2,6-diaminopurine core as well as incorporation of ionizable groups to improve both activity and solubility. The prospective binding mode of the compounds was determined using 3D ligand-based similarity methods to inhibitors of known binding mode, combined with a PDE5 docking and molecular dynamics based-protocol, each of which pointed to the same binding mode. Chemical modifications were then designed to both increase potency and solubility as well as validate the binding mode prediction. Compounds containing a quinazoline core displayed IC50s ranging from 0.10 to 9.39 µM while those consisting of a purine scaffold ranging from 0.29 to 43.16 µM. We identified 25 with a PDE5 IC50 of 0.15 µM, and much improved solubility (1.77 mg/mL) over the starting lead. Furthermore, it was found that the predicted binding mode was consistent with the observed SAR validating our computationally driven approach.

Structure-Based design of [(2-Hydroxyethoxy)methyl]-6-(phenylthio)-thymine derivatives as nonnucleoside HIV-1 reverse transcriptase Inhibitors: From HEPTs to Sulfinyl-substituted HEPTs.

The [(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine (HEPT) analogs were reported to be a kind of promising lead compounds as nonnucleoside HIV-1 reverse transcriptase inhibitors. In this work, a series of novel sulfinyl-substituted analogs were designed by structure-based design strategy with the purpose of improving the activity of HEPT, followed by evaluating their anti-HIV-1 activity in MT-4 cells. Most of the final compounds had moderate to strong activity against wild-type HIV-1 strain (IIIB) with EC50 values in the range of 0.21-1.91 µM, which were around 4 âˆ¼ 32-fold better than the reference compound HEPT. Some of them showed higher sensitivity toward clinically relevant mutant L100I and E138K viruses than NVP. Selected compounds were further evaluated for their activity against wild-type reverse transcriptase (RT), and most of them exhibited nanomolar activity, suggesting a good correlation with the cell-based activity. The compounds 11h, 11l, and 11ab displayed the best anti-HIV-1 activity against wild-type HIV-1 strain (EC50 = 0.280, 0.209, and 0.290 µM) and nanomolar activity against mutant strains (L100I and E138K), superior to HEPT and NVP. Molecular modeling studies were also performed to elucidate the biological activity, providing a structural insight for follow-up research on HEPT optimization.

Smaller, Stronger, More Stable: Peptide Variants of a SARS-CoV-2 Neutralizing Miniprotein.

Based on the structure of a de novo designed miniprotein (LCB1) in complex with the receptor binding domain (RBD) of the SARS-CoV-2 spike protein, we have generated and characterized truncated peptide variants of LCB1, which present only two of the three LCB1 helices, and which fully retained the virus neutralizing potency against different SARS-CoV-2 variants of concern (VOC). This antiviral activity was even 10-fold stronger for a cyclic variant of the two-helix peptides, as compared to the full-length peptide. Furthermore, the proteolytic stability of the cyclic peptide was substantially improved, rendering it a better potential candidate for SARS-CoV-2 therapy. In a more mechanistic approach, the peptides also served as tools to dissect the role of individual mutations in the RBD for the susceptibility of the resulting virus variants to neutralization by the peptides. As the peptides reported here were generated through chemical synthesis, rather than recombinant protein expression, they are amenable to further chemical modification, including the incorporation of a wide range of non-proteinogenic amino acids, with the aim to further stabilize the peptides against proteolytic degradation, as well as to improve the strength, as well the breadth, of their virus neutralizing capacity.

Computational Ion Channel Research: from the Application of Artificial Intelligence to Molecular Dynamics Simulations.

Although ion channels are crucial in many physiological processes and constitute an important class of drug targets, much is still unclear about their function and possible malfunctions that lead to diseases. In recent years, computational methods have evolved into important and invaluable approaches for studying ion channels and their functions. This is mainly due to their demanding mechanism of action where a static picture of an ion channel structure is often insufficient to fully understand the underlying mechanism. Therefore, the use of computational methods is as important as chemical-biological based experimental methods for a better understanding of ion channels. This review provides an overview on a variety of computational methods and software specific to the field of ion-channels. Artificial intelligence (or more precisely machine learning) approaches are applied for the sequence-based prediction of ion channel family, or topology of the transmembrane region. In case sufficient data on ion channel modulators is available, these methods can also be applied for quantitative structureactivity relationship (QSAR) analysis. Molecular dynamics (MD) simulations combined with computational molecular design methods such as docking can be used for analysing the function of ion channels including ion conductance, different conformational states, binding sites and ligand interactions, and the influence of mutations on their function. In the absence of a three-dimensional protein structure, homology modelling can be applied to create a model of your ion channel structure of interest. Besides highlighting a wide range of successful applications, we will also provide a basic introduction to the most important computational methods and discuss best practices to get a rough idea of possible applications and risks.

Structure-Based Design of Hepatitis C Virus E2 Glycoprotein Improves Serum Binding and Cross-Neutralization.

An effective vaccine for hepatitis C virus (HCV) is a major unmet need, and it requires an antigen that elicits immune responses to key conserved epitopes. Based on structures of antibodies targeting HCV envelope glycoprotein E2, we designed immunogens to modulate the structure and dynamics of E2 and favor induction of broadly neutralizing antibodies (bNAbs) in the context of a vaccine. These designs include a point mutation in a key conserved antigenic site to stabilize its conformation, as well as redesigns of an immunogenic region to add a new N-glycosylation site and mask it from antibody binding. Designs were experimentally characterized for binding to a panel of human monoclonal antibodies (HMAbs) and the coreceptor CD81 to confirm preservation of epitope structure and preferred antigenicity profile. Selected E2 designs were tested for immunogenicity in mice, with and without hypervariable region 1, which is an immunogenic region associated with viral escape. One of these designs showed improvement in polyclonal immune serum binding to HCV pseudoparticles and neutralization of isolates associated with antibody resistance. These results indicate that antigen optimization through structure-based design of the envelope glycoproteins is a promising route to an effective vaccine for HCV.IMPORTANCE Hepatitis C virus infects approximately 1% of the world's population, and no vaccine is currently available. Due to the high variability of HCV and its ability to actively escape the immune response, a goal of HCV vaccine design is to induce neutralizing antibodies that target conserved epitopes. Here, we performed structure-based design of several epitopes of the HCV E2 envelope glycoprotein to engineer its antigenic properties. Designs were tested in vitro and in vivo, demonstrating alteration of the E2 antigenic profile in several cases, and one design led to improvement of cross-neutralization of heterologous viruses. This represents a proof of concept that rational engineering of HCV envelope glycoproteins can be used to modulate E2 antigenicity and optimize a vaccine for this challenging viral target.

Computational studies of molecular pre-organization through macrocyclization: Conformational distribution analysis of closely related non-macrocyclic and macrocyclic analogs.

Macrocycles form an important compound class in medicinal chemistry due to their interesting structural and biological properties. To help design macrocycles, it is important to understand how the conformational preferences are affected upon macrocyclization of a lead compound. To address this, we collected a unique data set of protein-ligand complexes containing "non-macrocyclic" ("linear") ligands matched with macrocyclic analogs binding to the same protein in a similar pose. Out of the 39 co-crystallized ligands considered, 10 were linear and 29 were macrocyclic. To enable a more general analysis, 128 additional ligands from the publications associated with these protein data bank entries were added to the data set. Using in total 167 collected ligands, we investigated if the conformers in the macrocyclic conformational ensembles were more similar to the bioactive conformation in comparison to the conformers of their linear counterparts. Unexpectedly, in most cases the macrocycle conformational ensemble distributions were not very different from those of the linear compounds. Thus, care should be taken when designing macrocycles with the aim to focus their conformational preference towards the bioactive conformation. We also set out to investigate potential conformational flexibility differences between the two compound classes, computational energy window settings and evaluate a literature metric for approximating the conformational focusing on the bioactive conformation.

Preparation, biological & cheminformatics-based assessment of N2,N4-diphenylpyrimidine-2,4-diamine as potential Kinase-targeted antimalarials.

Twenty eight new N2,N4-diphenylpyrimidine-2,4-diamines have been prepared in order to expand our understanding of the anti-malarial SAR of the scaffold. The aim of the study was to make structural modifications to improve the overall potency, selectivity and solubility of the series by varying the anilino groups attached to the 2- and 4-position. We evaluated the activity of the compounds against Plasmodium falciparum (Pf) 3D7, cytotoxicity against HepG2, % inhibition at a panel of 10 human kinases, solubility, permeability and lipophilicity, and human and rat in vitro clearance. 11 was identified as a potent anti-malarial with an IC50 of 0.66 µM at the 3D7 strain and a selectivity (SI) of ~ 40 in terms of cytotoxicity against the HepG2 cell line. It also displayed low experimental logD7.4 (2.27), reasonable solubility (124 µg/ml), good metabolic stability, but low permeability. A proteo-chemometric workflow was employed to identify putative Pf targets of the most promising compounds. Ligand-based similarity searching of the ChEMBL database led to the identification of most probable human targets. These were then used as input for sequence-based searching of the Pf proteome. Homology modelling and molecular docking were used to evaluate whether compounds could indeed bind to these targets with valid binding modes. In vitro biological testing against close human analogs of these targets was subsequently undertaken. This allowed us to identify potential Pf targets and human anti-targets that could be exploited in future development.