Strategies for lead discovery: application of footprint similarity targeting HIVgp41

Mutations in Mig6 reduce inhibition of the epidermal growth factor receptor

Mitogen-inducible gene 6 (Mig6) is a cellular inhibitor of epidermal growth factor receptor (EGFR) that binds directly to the EGFR kinase domain and interferes with signaling. Reduced Mig6 expression is correlated with increased EGFR activity in multiple cancer models. Here, we investigated whether disease-associated point mutations could reduce the inhibitory potency of Mig6. We show that several cancer-associated mutations, and a mutation derived from Alzheimer's Disease patients, diminish the ability of Mig6 to bind and inhibit EGFR in vitro. In mammalian cells, the mutations decreased the Mig6-induced suppression of basal and EGF-stimulated autophosphorylation, MAP kinase phosphorylation, and cell migration. To probe the mechanisms by which the mutations could lead to reduced Mig6 inhibition, we constructed atomic-level computational models of Mig6 complexed with the EGFR catalytic domain, and performed molecular dynamics simulations for wild-type and mutant complexes.

Rapid Rescoring and Refinement of Ligand-Receptor Complexes Using Replica Exchange Molecular Dynamics with a Monte Carlo Pose Reservoir

Virtual screening (VS) involves generation of poses for a library of ligands and ranking using simplified energy functions and limited flexibility. Top-scored poses are used to rank and prioritize ligands. Here, we adapt the reservoir replica exchange molecular dynamics (res-REMD) method to rerank poses generated through VS. REMD simulations are carried out but with occasional Monte Carlo jumps to alternate VS-generated poses using a Metropolis criterion. The simulations converge within 10 ns for all systems, generating populations of alternate poses in the context of fully flexible ligand and protein side chains. The protocol is applied to four model protein-ligand complexes, where DOCK resulted in two successes and two scoring failures. In all four systems, the most populated cluster from the final ensemble exhibits high similarity to the crystallographic pose with ligand RMSD values under 2.0 Å. Both DOCK failures were rescued. For one DOCK success, the protocol identified the correct pose but also sampled an alternate pose at equal probability. Opportunities for future improvements and extensions are discussed.

Neutral ceramidase-active site inhibitor chemotypes and binding modes

Ceramides impact a diverse array of biological functions and have been implicated in disease pathogenesis. The enzyme neutral ceramidase (nCDase) is a zinc-containing hydrolase and mediates the metabolism of ceramide to sphingosine (Sph), both in cells and in the intestinal lumen. nCDase inhibitors based on substrate mimetics, for example C6-urea ceramide, have limited potency, aqueous solubility, and micelle-free fraction. To identify non-ceramide mimetic nCDase inhibitors, hit compounds from an HTS campaign were evaluated in biochemical, cell based and in silico modeling approaches. A majority of small molecule nCDase inhibitors contained pharmacophores capable of zinc interaction but retained specificity for nCDase over zinc-containing acid and alkaline ceramidases, as well as matrix metalloprotease-3 and histone deacetylase-1. nCDase inhibitors were refined by SAR, were shown to be substrate competitive and were active in cellular assays. nCDase inhibitor compounds were modeled by in silico DOCK screening and by molecular simulation. Modeling data supports zinc interaction and a similar compound binding pose with ceramide. nCDase inhibitors were identified with notably improved activity and solubility in comparison with the reference lipid-mimetic C6-urea ceramide.

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.

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.

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.

Identification of Ebola Virus Inhibitors Targeting GP2 Using Principles of Molecular Mimicry

A key step in the Ebola virus (EBOV) replication cycle involves conformational changes in viral glycoprotein 2 (GP2) which facilitate host-viral membrane fusion and subsequent release of the viral genome. Ebola GP2 plays a critical role in virus entry and has similarities in mechanism and structure to the HIV gp41 protein for which inhibitors have been successfully developed. In this work, a putative binding pocket for the C-terminal heptad repeat in the N-terminal heptad repeat trimer was targeted for identification of small molecules that arrest EBOV-host membrane fusion. Two computational structure-based virtual screens of ∼1.7 M compounds were performed (DOCK program) against a GP2 five-helix bundle, resulting in 165 commercially available compounds purchased for experimental testing. Based on assessment of inhibitory activity, cytotoxicity, and target specificity, four promising candidates emerged with 50% inhibitory concentration values in the 3 to 26 μM range. Molecular dynamics simulations of the two most potent candidates in their DOCK-predicted binding poses indicate that the majority of favorable interactions involve seven highly conserved residues that can be used to guide further inhibitor development and refinement targeting EBOV.IMPORTANCE The most recent Ebola virus disease outbreak, from 2014 to 2016, resulted in approximately 28,000 individuals becoming infected, which led to over 12,000 causalities worldwide. The particularly high pathogenicity of the virus makes paramount the identification and development of promising lead compounds to serve as inhibitors of Ebola infection. To limit viral load, the virus-host membrane fusion event can be targeted through the inhibition of the class I fusion glycoprotein of Ebolavirus In the current work, several promising small-molecule inhibitors that target the glycoprotein GP2 were identified through systematic application of structure-based computational and experimental drug design procedures.

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.

Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets

De novo design can be used to explore vast areas of chemical space in computational lead discovery. As a complement to virtual screening, from-scratch construction of molecules is not limited to compounds in pre-existing vendor catalogs. Here, we present an iterative fragment growth method, integrated into the program DOCK, in which new molecules are built using rules for allowable connections based on known molecules. The method leverages DOCK's advanced scoring and pruning approaches and users can define very specific criteria in terms of properties or features to customize growth toward a particular region of chemical space. The code was validated using three increasingly difficult classes of calculations: (1) Rebuilding known X-ray ligands taken from 663 complexes using only their component parts (focused libraries), (2) construction of new ligands in 57 drug target sites using a library derived from ∼13M drug-like compounds (generic libraries), and (3) application to a challenging protein-protein interface on the viral drug target HIVgp41. The computational testing confirms that the de novo DOCK routines are robust and working as envisioned, and the compelling results highlight the potential utility for designing new molecules against a wide variety of important protein targets. © 2017 Wiley Periodicals, Inc.

Structure-based identification of inhibitors targeting obstruction of the HIVgp41 N-heptad repeat trimer

The viral protein HIVgp41 is an attractive and validated drug target that proceeds through a sequence of conformational changes crucial for membrane fusion, which facilitates viral entry. Prior work has identified inhibitors that interfere with the formation of a required six-helix bundle, composed of trimeric C-heptad (CHR) and N-heptad (NHR) repeat elements, through blocking association of an outer CHR helix or obstructing formation of the inner NHR trimer itself. In this work, we employed similarity-based scoring to identify and experimentally characterize 113 compounds, related to 2 small-molecule inhibitors recently reported by Allen et al. (Bioorg. Med. Chem Lett.2015, 25 2853-59), proposed to act via the NHR trimer obstruction mechanism. The compounds were first tested in an HIV cell-cell fusion assay with the most promising evaluated in a second, more biologically relevant viral entry assay. Of the candidates, compound #11 emerged as the most promising hit (IC50=37.81µM), as a result of exhibiting activity in both assays with low cytotoxicity, as was similarly seen with the known control peptide inhibitor C34. The compound also showed no inhibition of VSV-G pseudotyped HIV entry compared to a control inhibitor suggesting it was specific for HIVgp41. Molecular dynamics simulations showed the predicted DOCK pose of #11 interacts with HIVgp41 in an energetic fashion (per-residue footprints) similar to the four native NHR residues (IQLT) which candidate inhibitors were intended to mimic.

The Antinociceptive Agent SBFI-26 Binds to Anandamide Transporters FABP5 and FABP7 at Two Different Sites

Human FABP5 and FABP7 are intracellular endocannabinoid transporters. SBFI-26 is an α-truxillic acid 1-naphthyl monoester that competitively inhibits the activities of FABP5 and FABP7 and produces antinociceptive and anti-inflammatory effects in mice. The synthesis of SBFI-26 yields several stereoisomers, and it is not known how the inhibitor binds the transporters. Here we report co-crystal structures of SBFI-26 in complex with human FABP5 and FABP7 at 2.2 and 1.9 Å resolution, respectively. We found that only (S)-SBFI-26 was present in the crystal structures. The inhibitor largely mimics the fatty acid binding pattern, but it also has several unique interactions. Notably, the FABP7 complex corroborates key aspects of the ligand binding pose at the canonical site previously predicted by virtual screening. In FABP5, SBFI-26 was unexpectedly found to bind at the substrate entry portal region in addition to binding at the canonical ligand-binding pocket. Our structural and binding energy analyses indicate that both R and S forms appear to bind the transporter equally well. We suggest that the S enantiomer observed in the crystal structures may be a result of the crystallization process selectively incorporating the (S)-SBFI-26-FABP complexes into the growing lattice, or that the S enantiomer may bind to the portal site more rapidly than to the canonical site, leading to an increased local concentration of the S enantiomer for binding to the canonical site. Our work reveals two binding poses of SBFI-26 in its target transporters. This knowledge will guide the development of more potent FABP inhibitors based upon the SBFI-26 scaffold.

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.

Small molecule inhibitors of HIVgp41 N-heptad repeat trimer formation

Identification of mechanistically novel anti-HIV fusion inhibitors was accomplished using a computer-aided structure-based design approach with the goal of blocking the formation of the N-heptad repeat (NHR) trimer of the viral protein gp41. A virtual screening strategy that included per-residue interaction patterns (footprints) was employed to identify small molecules compatible with putative binding pockets at the internal interface of the NHR helices at the core native viral six-helix bundle. From a screen of ∼2.8 million compounds using the DOCK program, 120 with favorable energetic and footprint overlap characteristics were purchased and experimentally tested leading to two compounds with favorable cell-cell fusion (IC50) and cytotoxicity profiles. Importantly, both hits were identified on the basis of scores containing footprint overlap terms and would not have been identified using the standard DOCK energy function alone. To our knowledge, these compounds represent the first reported small molecules that inhibit viral entry via the proposed NHR-trimer obstruction mechanism.

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.

Implementation of the Hungarian algorithm to account for ligand symmetry and similarity in structure-based design

False negative docking outcomes for highly symmetric molecules are a barrier to the accurate evaluation of docking programs, scoring functions, and protocols. This work describes an implementation of a symmetry-corrected root-mean-square deviation (RMSD) method into the program DOCK based on the Hungarian algorithm for solving the minimum assignment problem, which dynamically assigns atom correspondence in molecules with symmetry. The algorithm adds only a trivial amount of computation time to the RMSD calculations and is shown to increase the reported overall docking success rate by approximately 5% when tested over 1043 receptor–ligand systems. For some families of protein systems the results are even more dramatic, with success rate increases up to 16.7%. Several additional applications of the method are also presented including as a pairwise similarity metric to compare molecules during de novo design, as a scoring function to rank-order virtual screening results, and for the analysis of trajectories from molecular dynamics simulation. The new method, including source code, is available to registered users of DOCK6 (http://dock.compbio.ucsf.edu).