A water-based mechanism of specificity and resistance for lapatinib with ErbB family kinases

Design, Synthesis, biological Evaluation, and molecular docking studies of novel Pyrazolo[3,4-d]Pyrimidine derivative scaffolds as potent EGFR inhibitors and cell apoptosis inducers

A series of novel hybrid pyrazolo[3,4-d]pyramidine derivatives was designed and chemically synthesized in useful yields. The synthesized compounds were structurally characterized by the usual techniques. All the new synthesized compounds were biologically screened in vitro for their antiproliferative activities against a panel of four cancer cell lines, namely HepG-2, MCF-7, HCT-116, and Hela. The results of cytotoxic evaluation indicated that compound 14d was appeared to be the most prominent broad-spectrum cytotoxic activity and significantly more potent than sorafenib with IC₅₀ values of 4.28, 5.18, 3.97, and 9.85 µM against four cell lines (HePG2, Hela, HCT-116 and MCF-7). In addition, compound 15 was displayed promising antiproliferative effect against all tested cell lines with IC₅₀ value less than 11 µM compared with sorafenib as a control drug. Besides, structurally pharmacophoric features indicated that pyrazolo[3,4-d]pyrimidine scaffold having an amide linker and substituted with phenyl moiety at the 5-position was more potent than those possessing azomethine methyl, azomethine proton and carbomethene linkers, which lead to significant decrease in antiproliferative activity. The most potent compounds were further selected and evaluated for their activities against epidermal growth factor receptor (EGFR) kinase inhibitors according to homogenous time resolved fluorescence (HTRF) assay. The most potent compound 14d exhibited the most promising inhibitory activity against EGFR^WT with IC₅₀ value of 56.02 ± 1.38 µM compared with gefitinib as control drug with IC₅₀ value of 41.79 ± 1.07 µM. Moreover, the inhibition of cell cycle progression and induction of apoptosis in the A549 cell line at G2/M and pre-G1 phases of cell cycle might contribute to cancer treatment that evaluated by Annexin V-FITC/PI double staining detection method. Finally, molecular docking studies were conducted to investigate that probable binding conformations of these anticancer agents and ADME properties were calculated to predict pharmacokinetics and toxic properties of the target compounds.

Identification of Zika Virus Inhibitors Using Homology Modeling and Similarity-Based Screening to Target Glycoprotein E

The World Health Organization has designated Zika virus (ZIKV) as a dangerous, mosquito-borne pathogen that can cause severe developmental defects. The primary goal of this work was identification of small molecules as potential ZIKV inhibitors that target the viral envelope glycoprotein (ZIKV E) involved in membrane fusion and viral entry. A homology model of ZIKV E containing the small molecule β-octyl glucoside (BOG) was constructed, on the basis of an analogous X-ray structure from dengue virus, and >4 million commercially available compounds were computationally screened using the program DOCK6. A key feature of the screen involved the use of similarity-based scoring to identify inhibitor candidates that make similar interaction energy patterns (molecular footprints) as the BOG reference. Fifty-three prioritized compounds underwent experimental testing using cytotoxicity, cell viability, and tissue culture infectious dose 50% (TCID50) assays. Encouragingly, relative to a known control (NITD008), six compounds were active in both the cell viability assay and the TCID50 infectivity assay, and they showed activity in a third caspase activity assay. In particular, compounds 8 and 15 (tested at 25 μM) and compound 43 (tested at 10 μM) appeared to provide significant protection to infected cells, indicative of anti-ZIKV activity. Overall, the study highlights how similarity-based scoring can be leveraged to computationally identify potential ZIKV E inhibitors that mimic a known reference (in this case BOG), and the experimentally verified hits provide a strong starting point for further refinement and optimization efforts.

A Mechanistic Study of a Potent and Selective Epidermal Growth Factor Receptor Inhibitor against the L858R/T790M Resistance Mutation

Covalent targeting is a promising strategy for increasing the potency and selectivity of potential drug candidates. This therapeutic approach was recently reported for the epidermal growth factor receptor (EGFR), wherein a covalent binder, 20g [N-(3-{7-[2-methoxy-4-(4-methylpiperazin-1-yl)phenylamino]-3,4-dihydro-3-isopropyl-2,4-dioxopyrimido[4,5-d]pyrimidin-1(2H)-yl}phenyl)acrylamide], demonstrated significant selectivity and inhibitory activity toward the EGFR L858R/T790M double mutant (EGFR^DM) relative to the EGFR wild-type form (EGFR^WT). The enhanced therapeutic potency of 20g against EGFR^DM is 263 times greater than that against EGFR^WT, which necessitates a rational explanation for the underlying selective and inhibitory mechanisms. In this work, we investigate the differential binding modes of 20g with EGFR^WT and EGFR^DM using molecular dynamics simulations coupled with free energy calculations and further identify key residues involved in the selective targeting, binding, and inhibitory mechanisms mediated by 20g. We find that systematic orientational and conformational changes in the α-loop, p-loop, active loop, and αC-helix are responsible for the disparate binding mechanisms and inhibitory prowess of 20g with respect to EGFR^WT and EGFR^DM. The calculated binding free energies show good correlation with the experimental biological activity. The total binding free energy difference between EGFR^WT-20g and EGFR^DM-20g is -11.47 kcal/mol, implying that 20g binds more strongly to EGFR^DM. This enhanced binding affinity of 20g for EGFR^DM is a result of a large increase in the van der Waals and electrostatic interactions with three critical residues (Met790, Gln791, and Met793) that are chiefly responsible for the high-affinity interactions mediated by 20g with EGFR^DM relative to EGFR^WT.

Identification of Fatty Acid Binding Protein 5 Inhibitors Through Similarity-Based Screening

Fatty acid binding protein 5 (FABP5) is a promising target for development of inhibitors to help control pain and inflammation. In this work, computer-based docking (DOCK6 program) was employed to screen ∼2 M commercially available compounds to FABP5 based on an X-ray structure complexed with the small molecule inhibitor SBFI-26 previously identified by our group (also through virtual screening). The goal was discovery of additional chemotypes. The screen resulted in the purchase of 78 candidates, which led to the identification of a new inhibitor scaffold (STK-0) with micromolar affinity and apparent selectivity for FABP5 over FABP3. A second similarity-based screen resulted in three additional hits (STK-15, STK-21, STK-22) from which preliminary SAR could be derived. Notably, STK-15 showed comparable activity to the SBFI-26 reference under the same assay conditions (1.40 vs 0.86 μM). Additional molecular dynamics simulations, free energy calculations, and structural analysis (starting from DOCK-generated poses) revealed that R enantiomers (dihydropyrrole scaffold) of STK-15 and STK-22 have a more optimal composition of functional groups to facilitate additional H-bonds with Arg109 of FABP5. This observation suggests enantiomerically pure compounds could show enhanced activity. Overall, our study highlights the utility of using similarity-based screening methods to discover new inhibitor chemotypes, and the identified FABP5 hits provide a strong starting point for future efforts geared to improve activity.

Cross-Database Analysis Reveals Sensitive Biomarkers for Combined Therapy for ERBB2+ Gastric Cancer

Exploring ERBB2-related pathways will help us finding sensitive molecules and potential combined therapeutic targets of ERBB2-targeted therapy for ERBB2+ gastric cancer (GC). In this study, we performed a cross-databases study focused on ERBB2+ GC. The data of ERBB2+ GC deposited in the cancer genome atlas (TCGA), gene expression omnibus (GEO), InBio MapTM, cancer cell line encyclopedia (CCLE), and cancer therapeutics response portal (CTRP) were analyzed. The correlation of expression levels of candidate and IC50 of candidate genes-targeted drugs were verified on NCI-N87 and MKN-45 GC cell lines. We found that RARA, THRA, CACNB1, and TOP2A are drug sensitive biomarkers of ERBB2-targeted treatment with FDA-approved drugs. All these genes act through Myc signaling pathway. Myc is the downstream hub gene of both ERBB2 and RARA. The expression of RARA, THRA, and CACNB1 were negatively correlated with Myc activation, while ERBB2 and TOP2A positively correlated with Myc activation. SH3BGRL3, SH3BGRL, and NRG2 were identified as potential ligands of ERBB2. The ERBB2+ GC with RARA amplification demonstrated better prognosis than those without RARA amplification, while overexpression of NRG2 and SH3BGRL correlated with poor prognosis in ERBB2+ GC. About 90% of ERBB2+ GC was compatible with chromosome instability (CIN) subtype of TCGA, which overlaps with intestinal-type GC in Lauren classification. In validating experiments, combination of Lapatinib and all-trans retinoic acid (ATRA) synergistically suppresses cell growth, and accompanied by decreased expression of MYC. In conclusions, we identified several predicting biomarkers for ERBB2-targeted therapy and corresponding histological features of ERBB2+ GC. Combination of ERBB2 antagonist or RARA agonist may be effective synergistic regimens for ERBB2+ GC.

Identification of a Water-Coordinating HER2 Inhibitor by Virtual Screening Using Similarity-Based Scoring

Human epidermal growth factor receptor 2 (HER2) is a validated breast cancer drug target for small molecule inhibitors that target the ATP-binding pocket of the kinase domain. In this work, a large-scale virtual screen was performed to a novel homology model of HER2, in a hypothesized “fully active” state, that considered water-mediated interactions during the prioritization of compounds for experimental testing. This screen led to the identification of a new inhibitor with micro molar affinity and potency (K_d = 7.0 μM, IC₅₀ = 4.6 μM). Accompanying molecular dynamics simulations showed that inhibitor binding likely involves water coordination through an important water-mediated network previously identified in our laboratory. The predicted binding geometry also showed a remarkable overlap with the crystallographic poses for two previously reported inhibitors of the related Chk1 kinase. Concurrent with the HER2 studies, we developed formalized computational protocols that leverage solvated footprints (per-residue interaction maps that include bridging waters) to identify ligands that can “coordinate” or “displace” key binding site waters. Proof-of-concept screens targeting HIVPR and PARP1 demonstrate that molecules with high footprint overlap can be effectively identified in terms of their coordination or displacement patterns relative to a known reference. Overall, the procedures developed as a result of this study should be useful for researchers targeting HER2 and, more generally, for any protein in which the identification of compounds that exploit binding site waters is desirable.

Identification of small molecule inhibitors of botulinum neurotoxin serotype E via footprint similarity

Botulinum neurotoxins (BoNT) are among the most poisonous substances known, and of the 7 serotypes (A-G) identified thus far at least 4 can cause death in humans. The goal of this work was identification of inhibitors that specifically target the light chain catalytic site of the highly pathogenic but lesser-studied E serotype (BoNT/E). Large-scale computational screening, employing the program DOCK, was used to perform atomic-level docking of 1.4 million small molecules to prioritize those making favorable interactions with the BoNT/E site. In particular, 'footprint similarity' (FPS) scoring was used to identify compounds that could potentially mimic features on the known substrate tetrapeptide RIME. Among 92 compounds purchased and experimentally tested, compound C562-1101 emerged as the most promising hit with an apparent IC₅₀ value three-fold more potent than that of the first reported BoNT/E small molecule inhibitor NSC-77053. Additional analysis showed the predicted binding pose of C562-1101 was geometrically and energetically stable over an ensemble of structures generated by molecular dynamic simulations and that many of the intended interactions seen with RIME were maintained. Several analogs were also computationally designed and predicted to have further molecular mimicry thereby demonstrating the potential utility of footprint-based scoring protocols to help guide hit refinement.

DOCK 6: Impact of new features and current docking performance

This manuscript presents the latest algorithmic and methodological developments to the structure-based design program DOCK 6.7 focused on an updated internal energy function, new anchor selection control, enhanced minimization options, a footprint similarity scoring function, a symmetry-corrected root-mean-square deviation algorithm, a database filter, and docking forensic tools. An important strategy during development involved use of three orthogonal metrics for assessment and validation: pose reproduction over a large database of 1043 protein-ligand complexes (SB2012 test set), cross-docking to 24 drug-target protein families, and database enrichment using large active and decoy datasets (Directory of Useful Decoys [DUD]-E test set) for five important proteins including HIV protease and IGF-1R. Relative to earlier versions, a key outcome of the work is a significant increase in pose reproduction success in going from DOCK 4.0.2 (51.4%) → 5.4 (65.2%) → 6.7 (73.3%) as a result of significant decreases in failure arising from both sampling 24.1% → 13.6% → 9.1% and scoring 24.4% → 21.1% → 17.5%. Companion cross-docking and enrichment studies with the new version highlight other strengths and remaining areas for improvement, especially for systems containing metal ions. The source code for DOCK 6.7 is available for download and free for academic users at http://dock.compbio.ucsf.edu/.

Understanding drugs in breast cancer through drug sensitivity screening

With substantial numbers of breast tumors showing or acquiring treatment resistance, it is of utmost importance to develop new agents for the treatment of the disease, to know their effectiveness against breast cancer and to understand their relationships with other drugs to best assign the right drug to the right patient. To achieve this goal drug screenings on breast cancer cell lines are a promising approach. In this study a large-scale drug screening of 37 compounds was performed on a panel of 42 breast cancer cell lines representing the main breast cancer subtypes. Clustering, correlation and pathway analyses were used for data analysis. We found that compounds with a related mechanism of action had correlated IC50 values and thus grouped together when the cell lines were hierarchically clustered based on IC50 values. In total we found six clusters of drugs of which five consisted of drugs with related mode of action and one cluster with two drugs not previously connected. In total, 25 correlated and four anti-correlated drug sensitivities were revealed of which only one drug, Sirolimus, showed significantly lower IC50 values in the luminal/ERBB2 breast cancer subtype. We found expected interactions but also discovered new relationships between drugs which might have implications for cancer treatment regimens.

Fatty acid-binding proteins (FABPs) are intracellular carriers for Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD)

Δ(9)-Tetrahydrocannabinol (THC) and cannabidiol (CBD) occur naturally in marijuana (Cannabis) and may be formulated, individually or in combination in pharmaceuticals such as Marinol or Sativex. Although it is known that these hydrophobic compounds can be transported in blood by albumin or lipoproteins, the intracellular carrier has not been identified. Recent reports suggest that CBD and THC elevate the levels of the endocannabinoid anandamide (AEA) when administered to humans, suggesting that phytocannabinoids target cellular proteins involved in endocannabinoid clearance. Fatty acid-binding proteins (FABPs) are intracellular proteins that mediate AEA transport to its catabolic enzyme fatty acid amide hydrolase (FAAH). By computational analysis and ligand displacement assays, we show that at least three human FABPs bind THC and CBD and demonstrate that THC and CBD inhibit the cellular uptake and catabolism of AEA by targeting FABPs. Furthermore, we show that in contrast to rodent FAAH, CBD does not inhibit the enzymatic actions of human FAAH, and thus FAAH inhibition cannot account for the observed increase in circulating AEA in humans following CBD consumption. Using computational molecular docking and site-directed mutagenesis we identify key residues within the active site of FAAH that confer the species-specific sensitivity to inhibition by CBD. Competition for FABPs may in part or wholly explain the increased circulating levels of endocannabinoids reported after consumption of cannabinoids. These data shed light on the mechanism of action of CBD in modulating the endocannabinoid tone in vivo and may explain, in part, its reported efficacy toward epilepsy and other neurological disorders.

The PAKs come of age: Celebrating 18 years of discovery

Protein kinases are versatile signaling molecules that are involved in the regulation most physiological responses. The p21-activated kinases (PAKs) can be activated directly by the small GTPases Rac and Cdc42 and are among the best characterized downstream effectors of these Rho proteins. The structure, substrate specificity and functional role of PAKS are evolutionarily conserved from protozoa to mammals. Vertebrate PAKs are particularly important for cytoskeletal remodeling and focal adhesion assembly, thereby contributing to dynamic processes such as cell migration and synaptic plasticity. This issue of Cellular Logistics focuses on the PAK family of kinases, with ten reviews written by researchers currently working in the field. Here in this introductory overview we highlight some of the most interesting recent discoveries regarding PAK biochemistry and biology. The reviews in this issue cover a range of topics including the atomic structures of PAK1 and PAK4, their role in animals as assessed by knockout studies, and how PAKs are likely to contribute to cancer and neurodegenerative diseases. The promise remains that PAK inhibitors will emerge that validate current pre-clinical studies suggesting that blocking PAK activity will positively contribute to human health.

Pharmacophore-based similarity scoring for DOCK

Pharmacophore modeling incorporates geometric and chemical features of known inhibitors and/or targeted binding sites to rationally identify and design new drug leads. In this study, we have encoded a three-dimensional pharmacophore matching similarity (FMS) scoring function into the structure-based design program DOCK. Validation and characterization of the method are presented through pose reproduction, crossdocking, and enrichment studies. When used alone, FMS scoring dramatically improves pose reproduction success to 93.5% (∼20% increase) and reduces sampling failures to 3.7% (∼6% drop) compared to the standard energy score (SGE) across 1043 protein-ligand complexes. The combined FMS+SGE function further improves success to 98.3%. Crossdocking experiments using FMS and FMS+SGE scoring, for six diverse protein families, similarly showed improvements in success, provided proper pharmacophore references are employed. For enrichment, incorporating pharmacophores during sampling and scoring, in most cases, also yield improved outcomes when docking and rank-ordering libraries of known actives and decoys to 15 systems. Retrospective analyses of virtual screenings to three clinical drug targets (EGFR, IGF-1R, and HIVgp41) using X-ray structures of known inhibitors as pharmacophore references are also reported, including a customized FMS scoring protocol to bias on selected regions in the reference. Overall, the results and fundamental insights gained from this study should benefit the docking community in general, particularly researchers using the new FMS method to guide computational drug discovery with DOCK.

Differences in the binding affinities of ErbB family: heterogeneity in the prediction of resistance mutants

The pressure exerted by drugs targeted to a protein in any therapy inevitably leads to the emergence of drug resistance. One major mechanism of resistance involves the mutation of key residues in the target protein. Drugs that competitively replace a natural substrate are often made ineffective by mutations that reduce the drug’s affinity relative to that of the natural substrate. Hence atomic level understanding of the mechanisms that underlie this behavior is of utmost importance in efforts to design new drugs that can target such mutant proteins. Methods that can predict these mutations before they appear in clinic would be a major advance in the selection of the appropriate treatment strategy in patients. The present computational approach aims to model this emergence in EGFR and ErbB2 after treatment with the drug lapatinib, by investigating the structural, dynamic and energetic effects on these kinases when bound to the natural substrate ATP and to lapatinib. The study reveals binding modes and subpopulations that are presumably normally cryptic and these have been analyzed extensively here with respect to sites that are predicted to be hotspots for resisting mutations. These positions are compared in the context of currently available data from laboratory-based experiments and mechanistic details, at the atomistic level, of the origin of resistance are developed. The prediction of novel mutations, if validated by their emergence in the clinic, will make these methods as a powerful predictive tool which can be used in the design of new kinase inhibitors.

deltaGseg: macrostate estimation via molecular dynamics simulations and multiscale time series analysis

SUMMARY

Binding free energy calculations obtained through molecular dynamics simulations reflect intermolecular interaction states through a series of independent snapshots. Typically, the free energies of multiple simulated series (each with slightly different starting conditions) need to be estimated. Previous approaches carry out this task by moving averages at certain decorrelation times, assuming that the system comes from a single conformation description of binding events. Here, we discuss a more general approach that uses statistical modeling, wavelets denoising and hierarchical clustering to estimate the significance of multiple statistically distinct subpopulations, reflecting potential macrostates of the system. We present the deltaGseg R package that performs macrostate estimation from multiple replicated series and allows molecular biologists/chemists to gain physical insight into the molecular details that are not easily accessible by experimental techniques.

AVAILABILITY

deltaGseg is a Bioconductor R package available at http://bioconductor.org/packages/release/bioc/html/deltaGseg.html.

In silico design: extended molecular dynamic simulations of a new series of dually acting inhibitors against EGFR and HER2

Based on the hit structures that have been identified in our previous studies against EGFR and HER2, new potential inhibitors that share the same scaffold of the hit structures are designed and screened in silico. Insights into understanding the potential inhibitory effect of the new inhibitors against both EGFR and HER2 receptors is obtained using extended molecular dynamics (MD) simulations and different scoring techniques. The binding mechanisms and dynamics are detailed with respect to two approved inhibitors against EGFR (lapatinib) and HER2 (SYR127063). The best scoring inhibitor (T9) is chosen for additional in silico investigation against both the wild-type and T790M mutant strain of EGFR and the wild-type HER2. The results reveal that certain substitution patterns increase the stability and assure stronger binding and higher H-bond occupancy of the conserved water molecule that is commonly observed with kinase crystal structures. Furthermore, the new inhibitor (T9) forms stable interactions with the mutant strain as a direct consequence of the enhanced ability to form additional hydrogen bonding interactions with binding site residues.