FABP5 Inhibition against PTEN-Mutant Therapy Resistant Prostate Cancer

Resistance to standard of care taxane and androgen deprivation therapy (ADT) causes the vast majority of prostate cancer (PC) deaths worldwide. We have developed RapidCaP, an autochthonous genetically engineered mouse model of PC. It is driven by the loss of PTEN and p53, the most common driver events in PC patients with life-threatening diseases. As in human ADT, surgical castration of RapidCaP animals invariably results in disease relapse and death from the metastatic disease burden. Fatty Acid Binding Proteins (FABPs) are a large family of signaling lipid carriers. They have been suggested as drivers of multiple cancer types. Here we combine analysis of primary cancer cells from RapidCaP (RCaP cells) with large-scale patient datasets to show that among the 10 FABP paralogs, FABP5 is the PC-relevant target. Next, we show that RCaP cells are uniquely insensitive to both ADT and taxane treatment compared to a panel of human PC cell lines. Yet, they share an exquisite sensitivity to the small-molecule FABP5 inhibitor SBFI-103. We show that SBFI-103 is well tolerated and can strongly eliminate RCaP tumor cells in vivo. This provides a pre-clinical platform to fight incurable PC and suggests an important role for FABP5 in PTEN-deficient PC.

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.

Fatty acid binding protein 5 regulates docetaxel sensitivity in taxane-resistant prostate cancer cells

Prostate cancer is a leading cause of cancer-related deaths in men in the United States. Although treatable when detected early, prostate cancer commonly transitions to an aggressive castration-resistant metastatic state. While taxane chemotherapeutics such as docetaxel are mainstay treatment options for prostate cancer, taxane resistance often develops. Fatty acid binding protein 5 (FABP5) is an intracellular lipid chaperone that is upregulated in advanced prostate cancer and is implicated as a key driver of its progression. The recent demonstration that FABP5 inhibitors produce synergistic inhibition of tumor growth when combined with taxane chemotherapeutics highlights the possibility that FABP5 may regulate other features of taxane function, including resistance. Employing taxane-resistant DU145-TXR cells and a combination of cytotoxicity, apoptosis, and cell cycle assays, our findings demonstrate that FABP5 knockdown sensitizes the cells to docetaxel. In contrast, docetaxel potency was unaffected by FABP5 knockdown in taxane-sensitive DU145 cells. Taxane-resistance in DU145-TXR cells stems from upregulation of the P-glycoprotein ATP binding cassette subfamily B member 1 (ABCB1). Expression analyses and functional assays confirmed that FABP5 knockdown in DU145-TXR cells markedly reduced ABCB1 expression and activity, respectively. Our study demonstrates a potential new function for FABP5 in regulating taxane sensitivity and the expression of a major P-glycoprotein efflux pump in prostate cancer cells.

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.

Descriptor-Driven de Novo Design Algorithms for DOCK6 Using RDKit

Structure-based methods that employ principles of de novo design can be used to construct small organic molecules from scratch using pre-existing fragment libraries to sample chemical space and are an important class of computational algorithms for drug-lead discovery. Here, we present a powerful new design method for DOCK6 that employs a Descriptor-Driven De Novo strategy (termed D3N) in which user-defined cheminformatics descriptors (and their target ranges) are calculated at each layer of growth using the open-source toolkit RDKit. The objective is to tailor ligand growth toward desirable regions of chemical space. The approach was extensively validated through: (1) comparison of cheminformatics descriptors computed using the new DOCK6/RDKit interface versus the standard Python/RDKit installation, (2) examination of descriptor distributions generated using D3N growth under different conditions (target ranges and environments), and (3) construction of ligands with very tight (pinpoint) descriptor ranges using clinically relevant compounds as a reference. Our testing confirms that the new DOCK6/RDKit integration is robust, showcases how the new D3N routines can be used to direct sampling around user-defined chemical spaces, and highlights the utility of on-the-fly descriptor calculations for ligand design to important drug targets.

Inhibition of mutationally activated HER2

Human epidermal growth factor receptor 2 (HER2) is an oncogenic driver and key therapeutic target for human cancers. Current therapies targeting HER2 are primarily based on overexpression of the wild-type form of HER2. However, kinase domain mutations have been identified that can increase the activity of HER2 even when expressed at basal levels. Using purified enzymes, we confirmed the hyperactivity of two HER2 mutants (D769Y and P780insGSP). To identify small molecule inhibitors against these cancer-associated variants, we used a combined approach consisting of biochemical testing, similarity-based searching, and in silico modeling. These approaches resulted in the identification of a candidate molecule that inhibits mutant forms of HER2 in vitro and in cell-based assays. Our structural model predicts that the compound takes advantage of water-mediated interactions in the HER2 kinase binding pocket.

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.

Free Energy Landscapes from SARS-CoV-2 Spike Glycoprotein Simulations Suggest that RBD Opening Can Be Modulated via Interactions in an Allosteric Pocket

The SARS-CoV-2 coronavirus is an enveloped, positive-sense single-stranded RNA virus that is responsible for the COVID-19 pandemic. The spike is a class I viral fusion glycoprotein that extends from the viral surface and is responsible for viral entry into the host cell and is the primary target of neutralizing antibodies. The receptor binding domain (RBD) of the spike samples multiple conformations in a compromise between evading immune recognition and searching for the host-cell surface receptor. Using atomistic simulations of the glycosylated wild-type spike in the closed and 1-up RBD conformations, we map the free energy landscape for RBD opening and identify interactions in an allosteric pocket that influence RBD dynamics. The results provide an explanation for experimental observation of increased antibody binding for a clinical variant with a substitution in this pocket. Our results also suggest the possibility of allosteric targeting of the RBD equilibrium to favor open states via binding of small molecules to the hinge pocket. In addition to potential value as experimental probes to quantify RBD conformational heterogeneity, small molecules that modulate the RBD equilibrium could help explore the relationship between RBD opening and S1 shedding.

Free Energy Landscapes from SARS-CoV-2 Spike Glycoprotein Simulations Suggest that RBD Opening Can Be Modulated via Interactions in an Allosteric Pocket

The SARS-CoV-2 coronavirus is an enveloped, positive-sense single-stranded RNA virus that is responsible for the COVID-19 pandemic. The spike is a class I viral fusion glycoprotein that extends from the viral surface and is responsible for viral entry into the host cell and is the primary target of neutralizing antibodies. The receptor binding domain (RBD) of the spike samples multiple conformations in a compromise between evading immune recognition and searching for the host-cell surface receptor. Using atomistic simulations of the glycosylated wild-type spike in the closed and 1-up RBD conformations, we map the free energy landscape for RBD opening and identify interactions in an allosteric pocket that influence RBD dynamics. The results provide an explanation for experimental observation of increased antibody binding for a clinical variant with a substitution in this pocket. Our results also suggest the possibility of allosteric targeting of the RBD equilibrium to favor open states via binding of small molecules to the hinge pocket. In addition to potential value as experimental probes to quantify RBD conformational heterogeneity, small molecules that modulate the RBD equilibrium could help explore the relationship between RBD opening and S1 shedding.

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.

Incarvillateine produces antinociceptive and motor suppressive effects via adenosine receptor activation

(-)-Incarvillateine (INCA) is a natural product that has garnered attention due to its purported analgesic effects and historical use as a pain reliever in China. α-Truxillic acid monoesters (TAMEs) constitute a class of inhibitors targeting fatty acid binding protein 5 (FABP5), whose inhibition produces analgesia in animal models. The structural similarity between INCA and TAMEs motivated us to assess whether INCA exerts its antinociceptive effects via FABP inhibition. We found that, in contrast to TAMEs, INCA did not exhibit meaningful binding affinities toward four human FABP isoforms (FABP3, FABP4, FABP5 and FABP7) in vitro. INCA-TAME, a putative monoester metabolite of INCA that closely resembles TAMEs also lacked affinity for FABPs. Administration of INCA to mice produced potent antinociceptive effects while INCA-TAME was without effect. Surprisingly, INCA also potently suppressed locomotor activity at the same dose that produces antinociception. The motor suppressive effects of INCA were reversed by the adenosine A2 receptor antagonist 3,7-dimethyl-1-propargylxanthine. Collectively, our results indicate that INCA and INCA-TAME do not inhibit FABPs and that INCA exerts potent antinociceptive and motor suppressive effects at equivalent doses. Therefore, the observed antinociceptive effects of INCA should be interpreted with caution.

FABP1 controls hepatic transport and biotransformation of Δ9-THC

The increasing use of medical marijuana highlights the importance of developing a better understanding of cannabinoid metabolism. Phytocannabinoids, including ∆⁹-tetrahydrocannabinol (THC), are metabolized and inactivated by cytochrome P450 enzymes primarily within the liver. The lipophilic nature of cannabinoids necessitates mechanism(s) to facilitate their intracellular transport to metabolic enzymes. Here, we test the central hypothesis that liver-type fatty acid binding protein (FABP1) mediates phytocannabinoid transport and subsequent inactivation. Using X-ray crystallography, molecular modeling, and in vitro binding approaches we demonstrate that FABP1 accommodates one molecule of THC within its ligand binding pocket. Consistent with its role as a THC carrier, biotransformation of THC was reduced in primary hepatocytes obtained from FABP1-knockout (FABP1-KO) mice. Compared to their wild-type littermates, administration of THC to male and female FABP1-KO mice potentiated the physiological and behavioral effects of THC. The stark pharmacodynamic differences were confirmed upon pharmacokinetic analyses which revealed that FABP1-KO mice exhibit reduced rates of THC biotransformation. Collectively, these data position FABP1 as a hepatic THC transport protein and a critical mediator of cannabinoid inactivation. Since commonly used medications bind to FABP1 with comparable affinities to THC, our results further suggest that FABP1 could serve a previously unrecognized site of drug-drug interactions.

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.

SAR studies on truxillic acid mono esters as a new class of antinociceptive agents targeting fatty acid binding proteins

Fatty acid binding proteins (FABPs) serve as critical modulators of endocannabinoid signaling by facilitating the intracellular transport of anandamide and whose inhibition potentiates anandamide signaling. Our previous work has identified a novel small-molecule FABP inhibitor, α-truxillic acid 1-naphthyl monoester (SB-FI-26, 3) that has shown efficacy as an antinociceptive and anti-inflammatory agent in rodent models. In the present work, we have performed an extensive SAR study on a series of 3-analogs as novel FABP inhibitors based on computer-aided inhibitor drug design and docking analysis, chemical synthesis and biological evaluations. The prediction of binding affinity of these analogs to target FABP3, 5 and 7 isoforms was performed using the AutoDock 4.2 program, using the recently determined co-crystal structures of 3 with FABP5 and FABP7. The compounds with high docking scores were synthesized and evaluated for their activities using a fluorescence displacement assay against FABP3, 5 and 7. During lead optimization, compound 3l emerged as a promising compound with the Ki value of 0.21 μM for FABP 5, 4-fold more potent than 3 (Ki, 0.81 μM). Nine compounds exhibit similar or better binding affinity than 3, including compounds 4b (Ki, 0.55 μM) and 4e (Ki, 0.68 μM). Twelve compounds are selective for FABP5 and 7 with >10 μM Ki values for FABP3, indicating a safe profile to avoid potential cardiotoxicity concerns. Compounds 4f, 4j and 4k showed excellent selectivity for FABP5 and would serve as other new lead compounds. Compound 3a possessed high affinity and high selectivity for FABP7. Compounds with moderate to high affinity for FABP5 displayed antinociceptive effects in mice while compounds with low FABP5 affinity lacked in vivo efficacy. In vivo pain model studies in mice revealed that exceeding hydrophobicity significantly affects the efficacy. Thus, among the compounds with high affinity to FABP5 in vitro, the compounds with moderate hydrophobicity were identified as promising new lead compounds for the next round of optimization, including compounds 4b and 4j. For select cases, computational analysis of the observed SAR, especially the selectivity of new inhibitors to particular FABP isoforms, by comparing docking poses, interaction map, and docking energy scores has provided useful insights.

Fatty-acid-binding protein inhibition produces analgesic effects through peripheral and central mechanisms

Background

Fatty-acid-binding proteins (FABPs) are intracellular carriers for endocannabinoids, N-acylethanolamines, and related lipids. Previous work indicates that systemically administered FABP5 inhibitors produce analgesia in models of inflammatory pain. It is currently not known whether FABP inhibitors exert their effects through peripheral or central mechanisms. Here, we examined FABP5 distribution in dorsal root ganglia and spinal cord and examined the analgesic effects of peripherally and centrally administered FABP5 inhibitors.

Results

Immunofluorescence revealed robust expression of FABP5 in lumbar dorsal root ganglia. FABP5 was distributed in peptidergic calcitonin gene-related peptide-expressing dorsal root ganglia and non-peptidergic isolectin B4-expressing dorsal root ganglia. In addition, the majority of dorsal root ganglia expressing FABP5 also expressed transient receptor potential vanilloid 1 (TRPV1) and peripherin, a marker of nociceptive fibers. Intraplantar administration of FABP5 inhibitors reduced thermal and mechanical hyperalgesia in the complete Freund’s adjuvant model of chronic inflammatory pain. In contrast to its robust expression in dorsal root ganglia, FABP5 was sparsely distributed in the lumbar spinal cord and intrathecal administration of FABP inhibitor did not confer analgesic effects. Administration of FABP inhibitor via the intracerebroventricular (i.c.v.) route reduced thermal hyperalgesia. Antagonists of peroxisome proliferator-activated receptor alpha blocked the analgesic effects of peripherally and i.c.v. administered FABP inhibitor while antagonism of cannabinoid receptor 1 blocked the effects of peripheral FABP inhibition and a TRPV1 antagonist blocked the effects of i.c.v. administered inhibitor. Although FABP5 and TRPV1 were co-expressed in the periaqueductal gray region of the brain, which is known to modulate pain, knockdown of FABP5 in the periaqueductal gray using adeno-associated viruses and pharmacological FABP5 inhibition did not produce analgesic effects.

Conclusions

This study demonstrates that FABP5 is highly expressed in nociceptive dorsal root ganglia neurons and FABP inhibitors exert peripheral and supraspinal analgesic effects. This indicates that peripherally restricted FABP inhibitors may serve as a new class of analgesic and anti-inflammatory agents.

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.

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.

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.

Inhibition of HIV Entry by Targeting the Envelope Transmembrane Subunit gp41

BACKGROUND

The transmembrane subunit of the HIV envelope protein, gp41 is a vulnerable target to inhibit HIV entry. There is one fusion inhibitor T20 (brand name: Fuzeon, generic name: enfuvirtide) available by prescription. However, it has several drawbacks such as a high level of development of drug resistance, a short-half life in vivo, rapid renal clearance, low oral bioavailability, and it is only used as a salvage therapy. Therefore, investigators have been studying a variety of different modalities to attempt to overcome these limitations.

METHODS

Comprehensive literature searches were performed on HIV gp41, inhibition mechanisms, and inhibitors. The latest structural information was collected, and multiple inhibition strategies targeting gp41 were reviewed.

RESULTS

Many of the recent advances in inhibitors were peptide-based. Several creative modification strategies have also been performed to improve inhibitory efficacy of peptides and to overcome the drawbacks of T20 treatment. Small compounds have also been an area of intense research. There is a wide variety in development from those identified by virtual screens targeting specific regions of the protein to natural products. Finally, broadly neutralizing antibodies have also been important area of research. The inaccessible nature of the target regions for antibodies is a challenge, however, extensive efforts to develop better neutralizing antibodies are ongoing.

CONCLUSION

The fusogenic protein, gp41 has been extensively studied as a promising target to inhibit membrane fusion between the virus and target cells. At the same time, it is a challenging target because the vulnerable conformations of the protein are exposed only transiently. However, advances in biochemical, biophysical, structural, and immunological studies are coming together to move the field closer to an understanding of gp41 structure and function that will lead to the development of novel drugs and vaccines.

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/.

Structural Basis for Ceramide Recognition and Hydrolysis by Human Neutral Ceramidase

Neutral ceramidase (nCDase) catalyzes conversion of the apoptosis-associated lipid ceramide to sphingosine, the precursor for the proliferative factor sphingosine-1-phosphate. As an enzyme regulating the balance of ceramide and sphingosine-1-phosphate, nCDase is emerging as a therapeutic target for cancer. Here, we present the 2.6-Å crystal structure of human nCDase in complex with phosphate that reveals a striking, 20-Å deep, hydrophobic active site pocket stabilized by a eukaryotic-specific subdomain not present in bacterial ceramidases. Utilizing flexible ligand docking, we predict a likely binding mode for ceramide that superimposes closely with the crystallographically observed transition state analog phosphate. Our results suggest that nCDase uses a new catalytic strategy for Zn(2+)-dependent amidases, and generates ceramide specificity by sterically excluding sphingolipids with bulky headgroups and specifically recognizing the small hydroxyl head group of ceramide. Together, these data provide a foundation to aid drug development and establish common themes for how proteins recognize the bioactive lipid ceramide.

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.

Inhibition of fatty acid binding proteins elevates brain anandamide levels and produces analgesia

The endocannabinoid anandamide (AEA) is an antinociceptive lipid that is inactivated through cellular uptake and subsequent catabolism by fatty acid amide hydrolase (FAAH). Fatty acid binding proteins (FABPs) are intracellular carriers that deliver AEA and related N-acylethanolamines (NAEs) to FAAH for hydrolysis. The mammalian brain expresses three FABP subtypes: FABP3, FABP5, and FABP7. Recent work from our group has revealed that pharmacological inhibition of FABPs reduces inflammatory pain in mice. The goal of the current work was to explore the effects of FABP inhibition upon nociception in diverse models of pain. We developed inhibitors with differential affinities for FABPs to elucidate the subtype(s) that contributes to the antinociceptive effects of FABP inhibitors.

Inhibition of FABPs reduced nociception associated with inflammatory, visceral, and neuropathic pain. The antinociceptive effects of FABP inhibitors mirrored their affinities for FABP5, while binding to FABP3 and FABP7 was not a predictor of in vivo efficacy. The antinociceptive effects of FABP inhibitors were mediated by cannabinoid receptor 1 (CB₁) and peroxisome proliferator-activated receptor alpha (PPARα) and FABP inhibition elevated brain levels of AEA, providing the first direct evidence that FABPs regulate brain endocannabinoid tone. These results highlight FABPs as novel targets for the development of analgesic and anti-inflammatory therapeutics.

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).

Strategies for lead discovery: application of footprint similarity targeting HIVgp41

A highly-conserved binding pocket on HIVgp41 is an important target for development of anti-viral inhibitors. Holden et al. (Bioorg. Med. Chem. Lett.2012, 22, 3011) recently reported 7 experimentally-verified leads identified through a computational screen to the gp41 pocket in conjunction with a new DOCK scoring method (termed FPS scoring) developed in our laboratory. The method employs molecular footprints based on per-residue van der Waals interactions, electrostatic interactions, or the sum. In this work, we critically examine the gp41 screening results, prioritized using different scoring methods, in terms of two main criteria: (1) ligand pose properties which include footprint and energy score decompositions, MW, number of rotatable bonds, ligand efficiency, formal charge, and volume overlap, and (2) ligand pose stability which includes footprint stability (changes in footprint overlap) and rmsd stability (changes in geometry). Relative to standard DOCK scoring, pose property analyses demonstrate how FPS scoring can be used to identify ligands that mimic a known reference (derived here from the native gp41 substrate), while pose stability analyses demonstrate how FPS scoring can be used to enrich for compounds with greater overall stability during molecular dynamics (MD) simulations. Compellingly, of the 115 compounds tested experimentally, the 7 active compounds, as a group, more closely mimic the footprints made by the reference and show greater MD stability compared to the inactive group. Extensive studies using 116 protein-ligand complexes as controls reveal that ligands in their crystallographic binding pose also maintain higher FPS scores and smaller rmsds than do accompanying decoys, confirming that native poses are indeed 'stable' under the same conditions and that monitoring FPS variability during compound prioritization is likely to be beneficial. Overall, the results suggest the new scoring method will complement current virtual screening approaches for both the identification (FPS-ranking) and prioritization (FPS-stability) of target-compatible molecules in a quantitative and logical way.

Functional convergence of structurally distinct thioesterases from cyanobacteria and plants involved in phylloquinone biosynthesis

The synthesis of phylloquinone (vitamin K1) in photosynthetic organisms requires a thioesterase that hydrolyzes 1,4-dihydroxy-2-naphthoyl-CoA (DHNA-CoA) to release 1,4-dihydroxy-2-naphthoate (DHNA). Cyanobacteria and plants contain distantly related hotdog-fold thioesterases that catalyze this reaction, although the structural basis of these convergent enzymatic activities is unknown. To investigate this, the crystal structures of hotdog-fold DHNA-CoA thioesterases from the cyanobacterium Synechocystis (Slr0204) and the flowering plant Arabidopsis thaliana (AtDHNAT1) were determined. These enzymes form distinct homotetramers and use different active sites to catalyze hydrolysis of DHNA-CoA, similar to the 4-hydroxybenzoyl-CoA (4-HBA-CoA) thioesterases from Pseudomonas and Arthrobacter. Like the 4-HBA-CoA thioesterases, the DHNA-CoA thioesterases contain either an active-site aspartate (Slr0204) or glutamate (AtDHNAT1) that are predicted to be catalytically important. Computational modeling of the substrate-bound forms of both enzymes indicates the residues that are likely to be involved in substrate binding and catalysis. Both enzymes are selective for DHNA-CoA as a substrate, but this selectivity is achieved using divergent predicted binding strategies. The Slr0204 binding pocket is predominantly hydrophobic and closely conforms to DHNA, while that of AtDHNAT1 is more polar and solvent-exposed. Considered in light of the related 4-HBA-CoA thioesterases, these structures indicate that hotdog-fold thioesterases using either an active-site aspartate or glutamate diverged into distinct clades prior to the evolution of strong substrate specificity in these enzymes.

Grid-based molecular footprint comparison method for docking and de novo design: application to HIVgp41

Scoring functions are a critically important component of computer-aided screening methods for the identification of lead compounds during early stages of drug discovery. Here, we present a new multigrid implementation of the footprint similarity (FPS) scoring function that was recently developed in our laboratory which has proven useful for identification of compounds which bind to a protein on a per-residue basis in a way that resembles a known reference. The grid-based FPS method is much faster than its Cartesian-space counterpart, which makes it computationally tractable for on-the-fly docking, virtual screening, or de novo design. In this work, we establish that: (i) relatively few grids can be used to accurately approximate Cartesian space footprint similarity, (ii) the method yields improved success over the standard DOCK energy function for pose identification across a large test set of experimental co-crystal structures, for crossdocking, and for database enrichment, and (iii) grid-based FPS scoring can be used to tailor construction of new molecules to have specific properties, as demonstrated in a series of test cases targeting the viral protein HIVgp41. The method is available in the program DOCK6.

Targeting fatty acid binding protein (FABP) anandamide transporters - a novel strategy for development of anti-inflammatory and anti-nociceptive drugs

Fatty acid binding proteins (FABPs), in particular FABP5 and FABP7, have recently been identified by us as intracellular transporters for the endocannabinoid anandamide (AEA). Furthermore, animal studies by others have shown that elevated levels of endocannabinoids resulted in beneficial pharmacological effects on stress, pain and inflammation and also ameliorate the effects of drug withdrawal. Based on these observations, we hypothesized that FABP5 and FABP7 would provide excellent pharmacological targets. Thus, we performed a virtual screening of over one million compounds using DOCK and employed a novel footprint similarity scoring function to identify lead compounds with binding profiles similar to oleic acid, a natural FABP substrate. Forty-eight compounds were purchased based on their footprint similarity scores (FPS) and assayed for biological activity against purified human FABP5 employing a fluorescent displacement-binding assay. Four compounds were found to exhibit approximately 50% inhibition or greater at 10 µM, as good as or better inhibitors of FABP5 than BMS309403, a commercially available inhibitor. The most potent inhibitor, γ-truxillic acid 1-naphthyl ester (ChemDiv 8009-2334), was determined to have K_i value of 1.19±0.01 µM. Accordingly a novel α-truxillic acid 1-naphthyl mono-ester (SB-FI-26) was synthesized and assayed for its inhibitory activity against FABP5, wherein SB-FI-26 exhibited strong binding (K_i 0.93±0.08 µM). Additionally, we found SB-FI-26 to act as a potent anti-nociceptive agent with mild anti-inflammatory activity in mice, which strongly supports our hypothesis that the inhibition of FABPs and subsequent elevation of anandamide is a promising new approach to drug discovery. Truxillic acids and their derivatives were also shown by others to have anti-inflammatory and anti-nociceptive effects in mice and to be the active component of Chinese a herbal medicine (Incarvillea sinensis) used to treat rheumatism and pain in humans. Our results provide a likely mechanism by which these compounds exert their effects.

Footprint-based identification of viral entry inhibitors targeting HIVgp41

A targeted virtual screen to the N-helix hydrophobic pocket on HIVgp41 was performed using DOCK followed by re-ranking with a new footprint-based scoring function which employed native gp41 C-helix residues as a reference. Of ca. 500,000 small molecules screened, 115 were purchased, and 7 hits were identified with favorable binding (K(i)), cell-cell fusion (IC(50)), and cytotoxicity (CC(50)) profiles. Three of the seven active compounds would not have been discovered without the use of the footprints, demonstrating the utility of the method for structure-based design when a known reference compound or substrate is available.

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

The dual kinase inhibitor lapatinib has a high affinity for EGFR and HER2 but a weak affinity for ErbB4, although the factors driving specificity for these highly homologous members of the ErbB family of receptor tyrosine kinases are not well understood. In this report, homology modeling, molecular dynamics simulations, and free energy calculations are employed with the goal of uncovering the energetic and structural molecular basis of lapatinib specificity and resistance. The results reveal a distinct network of three binding site water molecules that yield strikingly similar hydration patterns for EGFR and HER2 in contrast to that of ErbB4, which shows a different pattern with a reduced occupancy at one of the positions. The primary cause was traced to a single amino acid change in the binding site (EGFR position 775), involving a swap from C or S (EGFR and HER2) to V (ErbB4), for which the side chain is bulkier, is hydrophobic, and lacks the ability to form a H-bond with water. Notably, excellent quantitative agreement with experimental activities is obtained across the series (EGFR > HER2 > ErbB4) when key waters are included in the calculations. Quantitatively, Coulombic interactions and H-bond counts between network waters and species involved in the network are less favorable in ErbB4 by ~40% relative to those in EGFR or HER2. Additional simulations with clinically relevant EGFR (C775F, T854A, and T790M) and HER2 (T790I) mutants demonstrate that resistance can also be understood in terms of changes that occur in the binding site water network. Overall, the results of this study have yielded a physically reasonable water-based mechanism for describing lapatinib specificity and resistance.

Small-molecule anticancer compounds selectively target the hemopexin domain of matrix metalloproteinase-9

Lack of target specificity by existing matrix metalloproteinase (MMP) inhibitors has hindered antimetastatic cancer drug discovery. Inhibitors that bind to noncatalytic sites of MMPs and disrupt protease signaling function have the potential to be more specific and selective. In this work, compounds that target the hemopexin (PEX) domain of MMP-9 were identified using an in silico docking approach and evaluated using biochemical and biological approaches. Two of the selected compounds interfere with MMP-9-mediated cancer cell migration and proliferation in cells expressing exogenous or endogenous MMP-9. Furthermore, these inhibitors do not modulate MMP-9 catalytic activity. The lead compound, N-[4-(difluoromethoxy)phenyl]-2-[(4-oxo-6-propyl-1H-pyrimidin-2-yl)sulfanyl]-acetamide, specifically binds to the PEX domain of MMP-9, but not other MMPs. This interaction between the compound and the PEX domain results in the abrogation of MMP-9 homodimerization and leads to blockage of a downstream signaling pathway required for MMP-9-mediated cell migration. In a tumor xenograft model, this pyrimidinone retarded MDA-MB-435 tumor growth and inhibited lung metastasis. Thus, we have shown for the first time that a novel small-molecule interacts specifically with the PEX domain of MMP-9 and inhibits tumor growth and metastasis by reducing cell migration and proliferation.

Implementation and evaluation of a docking-rescoring method using molecular footprint comparisons

A docking-rescoring method, based on per-residue van der Waals (VDW), electrostatic (ES), or hydrogen bond (HB) energies has been developed to aid discovery of ligands that have interaction signatures with a target (footprints) similar to that of a reference. Biologically useful references could include known drugs, inhibitors, substrates, transition states, or side-chains that mediate protein-protein interactions. Termed footprint similarity (FPS) score, the method, as implemented in the program DOCK, was validated and characterized using: (1) pose identification, (2) crossdocking, (3) enrichment, and (4) virtual screening. Improvements in pose identification (6–12%) were obtained using footprint-based (FPS(VDW+ES)) vs. standard DOCK (DCE(VDW+ES)) scoring as evaluated on three large datasets (680–775 systems) from the SB2010 database. Enhanced pose identification was also observed using FPS (45.4% or 70.9%) compared with DCE (17.8%) methods to rank challenging crossdocking ensembles from carbonic anhydrase. Enrichment tests, for three representative systems, revealed FPSVDW+ES scoring yields significant early fold enrichment in the top 10% of ranked databases. For EGFR, top FPS poses are nicely accommodated in the molecular envelope defined by the reference in comparison with DCE, which yields distinct molecular weight bias toward larger molecules. Results from a representative virtual screen of ca. 1 million compounds additionally illustrate how ligands with footprints similar to a known inhibitor can readily be identified from within large commercially available databases. By providing an alternative way to rank ligand poses in a simple yet directed manner we anticipate that FPS scoring will be a useful tool for docking and structure-based design.

Docking validation resources: protein family and ligand flexibility experiments

A database consisting of 780 ligand-receptor complexes, termed SB2010, has been derived from the Protein Databank to evaluate the accuracy of docking protocols for regenerating bound ligand conformations. The goal is to provide easily accessible community resources for development of improved procedures to aid virtual screening for ligands with a wide range of flexibilities. Three core experiments using the program DOCK, which employ rigid (RGD), fixed anchor (FAD), and flexible (FLX) protocols, were used to gauge performance by several different metrics: (1) global results, (2) ligand flexibility, (3) protein family, and (4) cross-docking. Global spectrum plots of successes and failures vs rmsd reveal well-defined inflection regions, which suggest the commonly used 2 Å criteria is a reasonable choice for defining success. Across all 780 systems, success tracks with the relative difficulty of the calculations: RGD (82.3%) > FAD (78.1%) > FLX (63.8%). In general, failures due to scoring strongly outweigh those due to sampling. Subsets of SB2010 grouped by ligand flexibility (7-or-less, 8-to-15, and 15-plus rotatable bonds) reveal that success degrades linearly for FAD and FLX protocols, in contrast to RGD, which remains constant. Despite the challenges associated with FLX anchor orientation and on-the-fly flexible growth, success rates for the 7-or-less (74.5%) and, in particular, the 8-to-15 (55.2%) subset are encouraging. Poorer results for the very flexible 15-plus set (39.3%) indicate substantial room for improvement. Family-based success appears largely independent of ligand flexibility, suggesting a strong dependence on the binding site environment. For example, zinc-containing proteins are generally problematic, despite moderately flexible ligands. Finally, representative cross-docking examples, for carbonic anhydrase, thermolysin, and neuraminidase families, show the utility of family-based analysis for rapid identification of particularly good or bad docking trends, and the type of failures involved (scoring/sampling), which will likely be of interest to researchers making specific receptor choices for virtual screening. SB2010 is available for download at http://rizzolab.org .

Origins of resistance to the HIVgp41 viral entry inhibitor T20

Peptide T20, which targets the HIV protein gp41, represents the first approved member of the class of HIV drugs known as membrane fusion inhibitors. However, mechanisms which lead to resistance through clinical use of T20 are not well-understood because the structure of the bound complex remains undetermined. In this report, an atomic-level model of a T20-gp41 complex embedded in an explicit DOPC membrane was constructed, and molecular dynamics simulations, followed by binding energy analysis (MM-GBSA method), were performed to delineate structural and energetic features that contribute to drug resistance. Per-residue binding footprints for T20 with wild-type gp41 reveal strong intermolecular van der Waals, Coulombic, and H-bond interactions in striking agreement with clinically observed resistance patterns. In addition, seven deleterious gp41 point mutations (L33Q, L33S, G36V, I37K, V38E, Q40H, and Q40K) were simulated, and all correctly exhibited decreases in the level of binding, including the fact that L33Q and Q40K are most detrimental. Six of the seven simulations yield good quantitative agreement (r(2) = 0.72; N = 6) with available experimental fold resistance data. Results from energy decomposition, heat map analysis, and differential (mutant minus wild-type) footprinting indicate the following. (1) Mutations disrupt intermolecular H-bonding and reduce the level of favorable contact with gp41 at M19. (2) Charged mutations (I37K, Q40K, and V38E) lead to significant Coulombic changes that weaken favorable van der Waals interactions. (3) Q40K is more detrimental than I37K because of interaction differences with a polar/charged patch on T20 in the initial (wild-type) state. (4) Resistance for L33S versus L33Q likely involves side chain packing differences in the final (mutated) state. A valuable finding of the work involves identification of favorable interactions among the C-terminal end of T20 (WNWF motif), residues on gp41 (including the fusion peptide), and headgroups in the adjacent membrane. The results suggest a complete T20 binding site would contribute to a stable complex, which could help to explain why prior studies, which employed truncated gp41 constructs, reported that C-terminal T20 residues may not interact with gp41. A hypothesis resulting from this study is that peptides could be designed to increase the level of favorable contact with both the membrane and gp41 which would lead to enhanced activity.

Quantitative prediction of fold resistance for inhibitors of EGFR

Clinical use of ATP-competitive inhibitors of the epidermal growth factor receptor (EGFR) kinase domain can lead to an acquired drug resistant mutant L858R&T790M which dramatically reduces binding affinity relative to a prevalent cancer causing mutation L858R. In this study, we have used molecular dynamics (MD) computer simulations, free energy calculations (MM-GBSA method), and per-residue footprint analysis to characterize binding of three inhibitors (erlotinib, gefitinib, and AEE788) with wildtype EGFR and three mutants. The goal is to characterize how variation in structure and energy correlate with changes in experimental activities and to deduce origins of drug resistance. For seven fold resistance values, each computed from the difference of two independent computer simulations, excellent agreement was obtained with available experimental data (r2 = 0.84). Importantly, the results correctly predict that affinity will increase as a result of L858R and decrease due to L858R&T790M. Per-residue analysis shows an increase in favorable packing at the site of the methionine mutation reaffirming that a steric clash hypothesis is unlikely; however, large losses in van der Waals, Coulombic, and H-bond interactions strongly suggest that resistance is not due solely to changes in affinity for the native substrate ATP as recently proposed. Instead, the present results indicate that drug resistance more likely involves disruption of favorable interactions, including a water-mediated H-bond network between the ligands and residues T854, T790, and Q791, which could have important implication for guiding rational design of inhibitors with improved resistance profiles.

DOCK 6: combining techniques to model RNA-small molecule complexes

With an increasing interest in RNA therapeutics and for targeting RNA to treat disease, there is a need for the tools used in protein-based drug design, particularly DOCKing algorithms, to be extended or adapted for nucleic acids. Here, we have compiled a test set of RNA-ligand complexes to validate the ability of the DOCK suite of programs to successfully recreate experimentally determined binding poses. With the optimized parameters and a minimal scoring function, 70% of the test set with less than seven rotatable ligand bonds and 26% of the test set with less than 13 rotatable bonds can be successfully recreated within 2 A heavy-atom RMSD. When DOCKed conformations are rescored with the implicit solvent models AMBER generalized Born with solvent-accessible surface area (GB/SA) and Poisson-Boltzmann with solvent-accessible surface area (PB/SA) in combination with explicit water molecules and sodium counterions, the success rate increases to 80% with PB/SA for less than seven rotatable bonds and 58% with AMBER GB/SA and 47% with PB/SA for less than 13 rotatable bonds. These results indicate that DOCK can indeed be useful for structure-based drug design aimed at RNA. Our studies also suggest that RNA-directed ligands often differ from typical protein-ligand complexes in their electrostatic properties, but these differences can be accommodated through the choice of potential function. In addition, in the course of the study, we explore a variety of newly added DOCK functions, demonstrating the ease with which new functions can be added to address new scientific questions.

Calculation of binding free energies for non-zinc chelating pyrimidine dicarboxamide inhibitors with MMP-13

All-atom molecular dynamics (MD) simulations in both explicit and implicit solvent, followed by MM-GBSA energy analysis, have been used to estimate binding free energies of four pyrimidine dicarboxamide inhibitors with human collagenase-3 (MMP-13) for comparison with experimental activities. Energetic analysis reveals that affinity is driven primarily by favorable van der Waals interactions and burial of total surface area. The computed effects of desolvation, as a function of ligand structure, quantitatively show that hydrophilic derivatives pay greater penalties upon binding than their related more hydrophobic analogs.

Binding of antifusion peptides with HIVgp41 from molecular dynamics simulations: quantitative correlation with experiment

Peptides based on C-terminal regions of the human immunodeficiency virus (HIV) viral protein gp41 represent an important new class of antiviral therapeutics called peptide fusion inhibitors. In this study, computational methods were used to model the binding of six peptides that contain residues that pack into a conserved hydrophobic pocket on HIVgp41, an attractive target site for the development of small molecule inhibitors. Free energies of binding were computed using molecular mechanics Generalized Born surface area (MM-GBSA) methods from molecular dynamics (MD) simulations, which employed either explicit (TIP3P) or continuum Generalized Born (GB) water models and strong correlations between experimental and computational affinities were obtained in both cases. Energy decomposition of the TIP3P-MD results (r2 = 0.75) reveals that variation in experimental affinity is highly correlated with changes in intermolecular van der Waals energies (deltaE(vdw)) on both a local (residue-based, r2 = 0.94) and global (peptide-based, r2 = 0.84) scale. The results show that differential association of C-peptides with HIVgp41 is driven solely by changes within the conserved pocket supporting the hypothesis that this region is an important drug target site. Such strong agreement with experiment is notable given the large size of the ligands (34 amino-acids) relative to the small range of experimental affinities (2 kcal/mol) and demonstrates good sensitivity of this computational method for simulating peptide fusion inhibitors. Finally, inspection of simulation trajectories identified a highly populated pi-type hydrogen bond, which formed between Gln575 on the receptor and the aromatic ring of peptide ligand Phe631, which could have important implications for drug design.

Development and validation of a modular, extensible docking program: DOCK 5

We report on the development and validation of a new version of DOCK. The algorithm has been rewritten in a modular format, which allows for easy implementation of new scoring functions, sampling methods and analysis tools. We validated the sampling algorithm with a test set of 114 protein-ligand complexes. Using an optimized parameter set, we are able to reproduce the crystal ligand pose to within 2 A of the crystal structure for 79% of the test cases using our rigid ligand docking algorithm with an average run time of 1 min per complex and for 72% of the test cases using our flexible ligand docking algorithm with an average run time of 5 min per complex. Finally, we perform an analysis of the docking failures in the test set and determine that the sampling algorithm is generally sufficient for the binding pose prediction problem for up to 7 rotatable bonds; i.e. 99% of the rigid ligand docking cases and 95% of the flexible ligand docking cases are sampled successfully. We point out that success rates could be improved through more advanced modeling of the receptor prior to docking and through improvement of the force field parameters, particularly for structures containing metal-based cofactors.

HIV-1 protease flaps spontaneously close to the correct structure in simulations following manual placement of an inhibitor into the open state

We report unrestrained, all-atom molecular dynamics simulations of HIV-1 protease (HIV-PR) with a continuum solvent model that reproducibly sample closing of the active site flaps following manual placement of a cyclic urea inhibitor into the substrate binding site of the open protease. The open form was obtained from the unbound, semi-open HIV-PR crystal structure, which we recently reported (Hornak, V.; et al. Proc. Natl. Acad. Sci. U.S.A. 2006, 103, 915-920.) to have spontaneously opened during unrestrained dynamics. In those simulations, the transiently open flaps always returned to the semi-open form that is observed in all crystal structures of the free protease. Here, we show that manual docking of the inhibitor reproducibly induces spontaneous conversion to the closed form as seen in all inhibitor-bound HIV-PR crystal structures. These simulations reproduced not only the greater degree of flap closure, but also the striking difference in flap "handedness" between bound and free enzyme. In most of the simulations, the final structures were highly accurate. Root-mean-square deviations (RMSD) from the crystal structure of the complex were approximately 1.5 A (averaged over the last 100 ps) for the inhibitor and each flap despite initial RMSD of 2-5 A for the inhibitors and 6-11 A for the flaps. Key hydrogen bonds were formed between the flap tips and between flaps and inhibitor that match those seen in the crystal structure. The results demonstrate that all-atom simulations have the ability to significantly improve poorly docked ligand conformations and reproduce large-scale receptor conformational changes that occur upon binding.

HIV-1 protease flaps spontaneously open and reclose in molecular dynamics simulations

We report unrestrained, all-atom molecular dynamics simulations of HIV-1 protease that sample large conformational changes of the active site flaps. In particular, the unliganded protease undergoes multiple conversions between the "closed" and "semiopen" forms observed in crystal structures of inhibitor-bound and unliganded protease, respectively, including reversal of flap "handedness." Simulations in the presence of a cyclic urea inhibitor yield stable closed flaps. Furthermore, we observe several events in which the flaps of the unliganded protease open to a much greater degree than observed in crystal structures and subsequently return to the semiopen state. Our data strongly support the hypothesis that the unliganded protease predominantly populates the semiopen conformation, with closed and fully open structures being a minor component of the overall ensemble. The results also provide a model for the flap opening and closing that is considered to be essential to enzyme function.

A Molecular Basis for the Selectivity of Thiadiazole Urea Inhibitors with Stromelysin-1 and Gelatinase-A from Generalized Born Molecular Dynamics Simulations

Matrix metalloproteinases (MMPs) represent a potentially important class of therapeutic targets for the treatment of diseases such as cancer. Selective inhibition of MMPs will be required given the high sequence identity across the family and the discovery that individual MMPs also regulate the natural angiogenesis inhibitor angiostatin. In this study, we have used computational methods to model the selectivity for six thiadiazole urea inhibitors with stromelysin-1 and gelatinase-A, two homologous MMPs that have been implicated in breast cancer. From continuum Generalized Born molecular dynamics (GB-MD) and MM-GBSA analysis, we estimated ligand free energies of binding using 200 snapshots obtained from a short 40 ps simulation of the relevant protein-ligand complex. The MM-GBSA free energies, computed from the continuum GB-MD trajectories, show strong correlation with the experimental affinities (r(2) = 0.74); prior studies have employed explicit water MD simulations. Including estimates for changes in solute entropy in the binding calculations slightly diminishes the overall correlation with experiment (r2 = 0.71). Notably, in every case, the simulation results correctly predict that a given ligand will bind selectively to stromelysin-1 over gelatinase-A which is gratifying given the high degree of structural homology between the two proteins. The increased selectivity for stromelysin-1 appears to be driven by (1) increased favorable van der Waals interactions, (2) increased favorable Coulombic interactions, and (3) decreased unfavorable total electrostatic energies (Coulombic plus desolvation).