Expanding FTMap for Fragment-Based Identification of Pharmacophore Regions in Ligand Binding Sites

The knowledge of ligand binding hot spots and of the important interactions within such hot spots is crucial for the design of lead compounds in the early stages of structure-based drug discovery. The computational solvent mapping server FTMap can reliably identify binding hot spots as consensus clusters, free energy minima that bind a variety of organic probe molecules. However, in its current implementation, FTMap provides limited information on regions within the hot spots that tend to interact with specific pharmacophoric features of potential ligands. E-FTMap is a new server that expands on the original FTMap protocol. E-FTMap uses 119 organic probes, rather than the 16 in the original FTMap, to exhaustively map binding sites, and identifies pharmacophore features as atomic consensus sites where similar chemical groups bind. We validate E-FTMap against a set of 109 experimentally derived structures of fragment-lead pairs, finding that highly ranked pharmacophore features overlap with the corresponding atoms in both fragments and lead compounds. Additionally, comparisons of mapping results to ensembles of bound ligands reveal that pharmacophores generated with E-FTMap tend to sample highly conserved protein-ligand interactions. E-FTMap is available as a web server at https://eftmap.bu.edu.

Computational identification of antibody-binding epitopes from mimotope datasets

Introduction: A fundamental challenge in computational vaccinology is that most B-cell epitopes are conformational and therefore hard to predict from sequence alone. Another significant challenge is that a great deal of the amino acid sequence of a viral surface protein might not in fact be antigenic. Thus, identifying the regions of a protein that are most promising for vaccine design based on the degree of surface exposure may not lead to a clinically relevant immune response. Methods: Linear peptides selected by phage display experiments that have high affinity to the monoclonal antibody of interest ("mimotopes") usually have similar physicochemical properties to the antigen epitope corresponding to that antibody. The sequences of these linear peptides can be used to find possible epitopes on the surface of the antigen structure or a homology model of the antigen in the absence of an antigen-antibody complex structure. Results and Discussion: Herein we describe two novel methods for mapping mimotopes to epitopes. The first is a novel algorithm named MimoTree that allows for gaps in the mimotopes and epitopes on the antigen. More specifically, a mimotope may have a gap that does not match to the epitope to allow it to adopt a conformation relevant for binding to an antibody, and residues may similarly be discontinuous in conformational epitopes. MimoTree is a fully automated epitope detection algorithm suitable for the identification of conformational as well as linear epitopes. The second is an ensemble approach, which combines the prediction results from MimoTree and two existing methods.

Identification of a druggable site on GRP78 at the GRP78-SARS-CoV-2 interface and virtual screening of compounds to disrupt that interface

SARS-CoV-2, the virus that causes COVID-19, led to a global health emergency that claimed the lives of millions. Despite the widespread availability of vaccines, the virus continues to exist in the population in an endemic state which allows for the continued emergence of new variants. Most of the current vaccines target the spike glycoprotein interface of SARS-CoV-2, creating a selection pressure favoring viral immune evasion. Antivirals targeting other molecular interactions of SARS-CoV-2 can help slow viral evolution by providing orthogonal selection pressures on the virus. GRP78 is a host auxiliary factor that mediates binding of the SARS-CoV-2 spike protein to human cellular ACE2, the primary pathway of cell infection. As GRP78 forms a ternary complex with SARS-CoV-2 spike protein and ACE2, disrupting the formation of this complex is expected to hinder viral entry into host cells. Here, we developed a model of the GRP78-Spike RBD-ACE2 complex. We then used that model together with hot spot mapping of the GRP78 structure to identify the putative binding site for spike protein on GRP78. Next, we performed structure-based virtual screening of known drug/candidate drug libraries to identify binders to GRP78 that are expected to disrupt spike protein binding to the GRP78, and thereby preventing viral entry to the host cell. A subset of these compounds has previously been shown to have some activity against SARS-CoV-2. The identified hits are starting points for the further development of novel SARS-CoV-2 therapeutics, potentially serving as proof-of-concept for GRP78 as a potential drug target for other viruses.

Vaccines Alone Cannot Slow the Evolution of SARS-CoV-2

The rapid emergence of immune-evading viral variants of SARS-CoV-2 calls into question the practicality of a vaccine-only public-health strategy for managing the ongoing COVID-19 pandemic. It has been suggested that widespread vaccination is necessary to prevent the emergence of future immune-evading mutants. Here, we examined that proposition using stochastic computational models of viral transmission and mutation. Specifically, we looked at the likelihood of emergence of immune escape variants requiring multiple mutations and the impact of vaccination on this process. Our results suggest that the transmission rate of intermediate SARS-CoV-2 mutants will impact the rate at which novel immune-evading variants appear. While vaccination can lower the rate at which new variants appear, other interventions that reduce transmission can also have the same effect. Crucially, relying solely on widespread and repeated vaccination (vaccinating the entire population multiple times a year) is not sufficient to prevent the emergence of novel immune-evading strains, if transmission rates remain high within the population. Thus, vaccines alone are incapable of slowing the pace of evolution of immune evasion, and vaccinal protection against severe and fatal outcomes for COVID-19 patients is therefore not assured.

No magic bullet: Limiting in-school transmission in the face of variable SARS-CoV-2 viral loads

In the face of a long-running pandemic, understanding the drivers of ongoing SARS-CoV-2 transmission is crucial for the rational management of COVID-19 disease burden. Keeping schools open has emerged as a vital societal imperative during the pandemic, but in-school transmission of SARS-CoV-2 can contribute to further prolonging the pandemic. In this context, the role of schools in driving SARS-CoV-2 transmission acquires critical importance. Here we model in-school transmission from first principles to investigate the effectiveness of layered mitigation strategies on limiting in-school spread. We examined the effect of masks and air quality (ventilation, filtration and ionizers) on steady-state viral load in classrooms, as well as on the number of particles inhaled by an uninfected person. The effectiveness of these measures in limiting viral transmission was assessed for variants with different levels of mean viral load (ancestral, Delta, Omicron). Our results suggest that a layered mitigation strategy can be used effectively to limit in-school transmission, with certain limitations. First, poorly designed strategies (insufficient ventilation, no masks, staying open under high levels of community transmission) will permit in-school spread even if some level of mitigation is present. Second, for viral variants that are sufficiently contagious, it may be difficult to construct any set of interventions capable of blocking transmission once an infected individual is present, underscoring the importance of other measures. Our findings provide practical recommendations; in particular, the use of a layered mitigation strategy that is designed to limit transmission, with other measures such as frequent surveillance testing and smaller class sizes (such as by offering remote schooling options to those who prefer it) as needed.

From SARS-CoV-2 infection to COVID-19 morbidity: an in silico projection of virion flow rates to the lower airway via nasopharyngeal fluid boluses

Background: While the nasopharynx is initially the dominant upper airway infection site for SARS-CoV-2, the physiologic mechanism launching the infection at the lower airway is still not well-understood. Based on the rapidity of infection progression to the lungs, it has been hypothesized that the nasopharynx may be acting as the primary seeding zone for subsequent contamination of the lower airway via aspiration of virus-laden boluses of nasopharyngeal fluids. Methodology: To examine the plausibility of the aspiration-driven mechanism, we have computationally tracked the inhalation process in three anatomic airway reconstructions and have quantified the nasopharyngeal liquid volume transmitted to the lower airspace during each aspiration. Results: Extending the numerical trends on aspiration volume to earlier records on aspiration frequencies indicates a total aspirated nasopharyngeal liquid volume of 0.3 – 0.76 ml/day. Subsequently, for mean sputum viral load, our modeling projects that the number of virions reaching the lower airway will range over 2.1×106 – 5.3×106 /day; for peak viral load, the corresponding number hovers between 7.1×108 – 1.8×109. Conclusions: The virion transmission findings fill in a key piece of the mechanistic puzzle on the systemic progression of SARS-CoV-2, and subjectively point to health conditions like dysphagia, with proclivity to increased aspiration, as some of the potential underlying risk factors for aggressive lung infections.

Rapid relaxation of pandemic restrictions after vaccine rollout favors growth of SARS-CoV-2 variants: A model-based analysis

The development and deployment of several SARS-CoV-2 vaccines in a little over a year is an unprecedented achievement of modern medicine. The high levels of efficacy against transmission for some of these vaccines makes it feasible to use them to suppress SARS-CoV-2 altogether in regions with high vaccine acceptance. However, viral variants with reduced susceptibility to vaccinal and natural immunity threaten the utility of vaccines, particularly in scenarios where a return to pre-pandemic conditions occurs before the suppression of SARS-CoV-2 transmission. In this work we model the situation in the United States in May-June 2021, to demonstrate how pre-existing variants of SARS-CoV-2 may cause a rebound wave of COVID-19 in a matter of months under a certain set of conditions. A high burden of morbidity (and likely mortality) remains possible, even if the vaccines are partially effective against new variants and widely accepted. Our modeling suggests that variants that are already present within the population may be capable of quickly defeating the vaccines as a public health intervention, a serious potential limitation for strategies that emphasize rapid reopening before achieving control of SARS-CoV-2.

Controlling long-term SARS-CoV-2 infections can slow viral evolution and reduce the risk of treatment failure

The rapid emergence and expansion of novel SARS-CoV-2 variants threatens our ability to achieve herd immunity for COVID-19. These novel SARS-CoV-2 variants often harbor multiple point mutations, conferring one or more evolutionarily advantageous traits, such as increased transmissibility, immune evasion and longer infection duration. In a number of cases, variant emergence has been linked to long-term infections in individuals who were either immunocompromised or treated with convalescent plasma. In this paper, we used a stochastic evolutionary modeling framework to explore the emergence of fitter variants of SARS-CoV-2 during long-term infections. We found that increased viral load and infection duration favor emergence of such variants. While the overall probability of emergence and subsequent transmission from any given infection is low, on a population level these events occur fairly frequently. Targeting these low-probability stochastic events that lead to the establishment of novel advantageous viral variants might allow us to slow the rate at which they emerge in the patient population, and prevent them from spreading deterministically due to natural selection. Our work thus suggests practical ways to achieve control of long-term SARS-CoV-2 infections, which will be critical for slowing the rate of viral evolution.

Risk of rapid evolutionary escape from biomedical interventions targeting SARS-CoV-2 spike protein

The spike protein receptor-binding domain (RBD) of SARS-CoV-2 is the molecular target for many vaccines and antibody-based prophylactics aimed at bringing COVID-19 under control. Such a narrow molecular focus raises the specter of viral immune evasion as a potential failure mode for these biomedical interventions. With the emergence of new strains of SARS-CoV-2 with altered transmissibility and immune evasion potential, a critical question is this: how easily can the virus escape neutralizing antibodies (nAbs) targeting the spike RBD? To answer this question, we combined an analysis of the RBD structure-function with an evolutionary modeling framework. Our structure-function analysis revealed that epitopes for RBD-targeting nAbs overlap one another substantially and can be evaded by escape mutants with ACE2 affinities comparable to the wild type, that are observed in sequence surveillance data and infect cells in vitro. This suggests that the fitness cost of nAb-evading mutations is low. We then used evolutionary modeling to predict the frequency of immune escape before and after the widespread presence of nAbs due to vaccines, passive immunization or natural immunity. Our modeling suggests that SARS-CoV-2 mutants with one or two mildly deleterious mutations are expected to exist in high numbers due to neutral genetic variation, and consequently resistance to vaccines or other prophylactics that rely on one or two antibodies for protection can develop quickly -and repeatedly- under positive selection. Predicted resistance timelines are comparable to those of the decay kinetics of nAbs raised against vaccinal or natural antigens, raising a second potential mechanism for loss of immunity in the population. Strategies for viral elimination should therefore be diversified across molecular targets and therapeutic modalities.

Ensemble-based docking using biased molecular dynamics

Proteins are dynamic molecules, and understanding their movements, especially as they relate to molecular recognition and protein-ligand interactions, poses a significant challenge to structure-based drug discovery. In most instances, protein flexibility is underrepresented in computer-aided drug design due to uncertainties on how it should be accurately modeled as well as the computational cost associated with attempting to incorporate flexibility in the calculations. One approach that aims to address these issues is ensemble-based docking. With this technique, ligands are docked to an ensemble of rigid protein conformations. Molecular dynamics (MD) simulations can be used to generate the ensemble of protein conformations for the subsequent docking. Here we present a novel approach that uses biased-MD simulations to generate the docking ensemble. The MD simulations are biased toward an initial protein-ligand X-ray complex structure. The biasing maintains some of the original crystallographic pocket-ligand information and thereby enhances sampling of the more relevant conformational space of the protein. Resulting trajectories are clustered to select a representative set of protein conformations, and ligands are docked to that reduced set of conformations. Cross-docking to this ensemble and then selecting the lowest scoring pose enables reliable identification of the correct binding mode. Various levels of biasing are investigated, and the method is validated for cyclin-dependent kinase 2 and factor Xa.

All-atom empirical potential for molecular modeling and dynamics studies of proteins

New protein parameters are reported for the all-atom empirical energy function in the CHARMM program. The parameter evaluation was based on a self-consistent approach designed to achieve a balance between the internal (bonding) and interaction (nonbonding) terms of the force field and among the solvent-solvent, solvent-solute, and solute-solute interactions. Optimization of the internal parameters used experimental gas-phase geometries, vibrational spectra, and torsional energy surfaces supplemented with ab initio results. The peptide backbone bonding parameters were optimized with respect to data for N-methylacetamide and the alanine dipeptide. The interaction parameters, particularly the atomic charges, were determined by fitting ab initio interaction energies and geometries of complexes between water and model compounds that represented the backbone and the various side chains. In addition, dipole moments, experimental heats and free energies of vaporization, solvation and sublimation, molecular volumes, and crystal pressures and structures were used in the optimization. The resulting protein parameters were tested by applying them to noncyclic tripeptide crystals, cyclic peptide crystals, and the proteins crambin, bovine pancreatic trypsin inhibitor, and carbonmonoxy myoglobin in vacuo and in crystals. A detailed analysis of the relationship between the alanine dipeptide potential energy surface and calculated protein φ, χ angles was made and used in optimizing the peptide group torsional parameters. The results demonstrate that use of ab initio structural and energetic data by themselves are not sufficient to obtain an adequate backbone representation for peptides and proteins in solution and in crystals. Extensive comparisons between molecular dynamics simulations and experimental data for polypeptides and proteins were performed for both structural and dynamic properties. Energy minimization and dynamics simulations for crystals demonstrate that the latter are needed to obtain meaningful comparisons with experimental crystal structures. The presented parameters, in combination with the previously published CHARMM all-atom parameters for nucleic acids and lipids, provide a consistent set for condensed-phase simulations of a wide variety of molecules of biological interest.

In vivo validation of thymidylate kinase (TMK) with a rationally designed, selective antibacterial compound

There is an urgent need for new antibacterials that pinpoint novel targets and thereby avoid existing resistance mechanisms. We have created novel synthetic antibacterials through structure-based drug design that specifically target bacterial thymidylate kinase (TMK), a nucleotide kinase essential in the DNA synthesis pathway. A high-resolution structure shows compound TK-666 binding partly in the thymidine monophosphate substrate site, but also forming new induced-fit interactions that give picomolar affinity. TK-666 has potent, broad-spectrum Gram-positive microbiological activity (including activity against methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus), bactericidal action with rapid killing kinetics, excellent target selectivity over the human ortholog, and low resistance rates. We demonstrate in vivo efficacy against S. aureus in a murine infected-thigh model. This work presents the first validation of TMK as a compelling antibacterial target and provides a rationale for pursuing novel clinical candidates for treating Gram-positive infections through TMK.

Identification and characterization of acidic mammalian chitinase inhibitors

Acidic mammalian chitinase (AMCase) is a member of the glycosyl hydrolase 18 family (EC 3.2.1.14) that has been implicated in the pathophysiology of allergic airway disease such as asthma. Small molecule inhibitors of AMCase were identified using a combination of high-throughput screening, fragment screening, and virtual screening techniques and characterized by enzyme inhibition and NMR and Biacore binding experiments. X-ray structures of the inhibitors in complex with AMCase revealed that the larger more potent HTS hits, e.g. 5-(4-(2-(4-bromophenoxy)ethyl)piperazine-1-yl)-1H-1,2,4-triazol-3-amine 1, spanned from the active site pocket to a hydrophobic pocket. Smaller fragments identified by FBS occupy both these pockets independently and suggest potential strategies for linking fragments. Compound 1 is a 200 nM AMCase inhibitor which reduced AMCase enzymatic activity in the bronchoalveolar lavage fluid in allergen-challenged mice after oral dosing.

Triad of polar residues implicated in pH specificity of acidic mammalian chitinase

Acidic mammalian chitinase (AMCase) is a mammalian chitinase that has been implicated in allergic asthma. One of only two active mammalian chinases, AMCase, is distinguished from other chitinases by several unique features. Here, we present the novel structure of the AMCase catalytic domain, both in the apo form and in complex with the inhibitor methylallosamidin, determined to high resolution by X-ray crystallography. These results provide a structural basis for understanding some of the unique characteristics of this enzyme, including the low pH optimum and the preference for the beta-anomer of the substrate. A triad of polar residues in the second-shell is found to modulate the highly conserved chitinase active site. As a novel target for asthma therapy, structural details of AMCase activity will help guide the future design of specific and potent AMCase inhibitors.

Identification, characterization and initial hit-to-lead optimization of a series of 4-arylamino-3-pyridinecarbonitrile as protein kinase C theta (PKCtheta) inhibitors

The protein kinase C (PKC) family of serine/threonine kinases is implicated in a wide variety of cellular processes. The PKC theta (PKCtheta) isoform is involved in TCR signal transduction and T cell activation and regulates T cell mediated diseases, including lung inflammation and airway hyperresponsiveness. Thus inhibition of PKCtheta enzyme activity by a small molecule represents an attractive strategy for the treatment of asthma. A PKCtheta high-throughput screening (HTS) campaign led to the identification of 4-(3-bromophenylamino)-5-(3,4-dimethoxyphenyl)-3-pyridinecarbonitrile 4a, a low microM ATP competitive PKCtheta inhibitor. Structure based hit-to-lead optimization led to the identification of 5-(3,4-dimethoxyphenyl)-4-(1H-indol-5-ylamino)-3-pyridinecarbonitrile 4p, a 70 nM PKCtheta inhibitor. Compound 4p was selective for inhibition of novel PKC isoforms over a panel of 21 serine/threonine, tyrosine, and phosphoinositol kinases, in addition to the conventional and atypical PKCs, PKCbeta, and PKCzeta, respectively. Compound 4p also inhibited IL-2 production in antiCD3/anti-CD28 activated T cells enriched from splenocytes.

Inhibitors of Tumor Progression Loci-2 (Tpl2) Kinase and Tumor Necrosis Factor α (TNF-α) Production: Selectivity and in Vivo Antiinflammatory Activity of Novel 8-Substituted-4-anilino-6-aminoquinoline-3-carbonitriles

Tumor progression loci-2 (Tpl2) (Cot/MAP3K8) is a serine/threonine kinase in the MAP3K family directly upstream of MEK. Recent studies using Tpl2 knockout mice have indicated an important role for Tpl2 in the lipopolysaccharide (LPS) induced production of tumor necrosis factor alpha (TNF-alpha) and other proinflammatory cytokines involved in diseases such as rheumatoid arthritis. Initial 4-anilino-6-aminoquinoline-3-carbonitrile leads showed poor selectivity for Tpl2 over epidermal growth factor receptor (EGFR) kinase. Using molecular modeling and crystallographic data of the EGFR kinase domain with and without an EGFR kinase-specific 4-anilinoquinazoline inhibitor (erlotinib, Tarceva), we hypothesized that we could diminish the inhibition of EGFR kinase by substitution at the C-8 position of our 4-anilino-6-aminoquinoline-3-carbonitrile leads. The 8-substituted-4-anilino-6-aminoquinoline-3-carbonitriles were prepared from the appropriate 2-substituted 4-nitroanilines. Modifications to the C-6 and C-8 positions led to the identification of compounds with increased inhibition of TNF-alpha release from LPS-stimulated rat and human blood, and these analogues were also highly selective for Tpl2 kinase over EGFR kinase. Further structure-activity based modifications led to the identification of 8-bromo-4-(3-chloro-4-fluorophenylamino)-6-[(1-methyl-1H-imidazol-4-yl)methylamino]quinoline-3-carbonitrile, which demonstrated in vitro as well as in vivo efficacy in inhibition of LPS-induced TNF-alpha production.

Structure-Based Optimization of Protein Tyrosine Phosphatase 1B Inhibitors: From the Active Site to the Second Phosphotyrosine Binding Site

Protein tyrosine phosphatase 1B (PTP1B) is a negative regulator of the insulin and leptin receptor pathways and thus an attractive therapeutic target for diabetes and obesity. Starting with a high micromolar lead compound, structure-based optimization of novel PTP1B inhibitors by extension of the molecule from the enzyme active site into the second phosphotyrosine binding site is described. Medicinal chemistry, guided by X-ray complex structure and molecular modeling, has yielded low nanomolar PTP1B inhibitors in an efficient manner. Compounds from this chemical series were found to be actively transported into hepatocytes. This active uptake into target tissues could be one of the possible avenues to overcome the poor membrane permeability of PTP1B inhibitors.

Design and synthesis of 3,3-piperidine hydroxamate analogs as selective TACE inhibitors

Structure-based methods were used to design beta-sulfone 3,3-piperidine hydroxamates as TACE inhibitors with the aim of improving selectivity for TACE versus MMP-13. Several compounds in this series were synthesized and evaluated in enzymatic and cell-based assays. These analogs exhibit excellent in vitro potency against isolated TACE enzyme and show good selectivity for TACE over the related metalloproteases MMP-2, -13, and -14.

Ligand design by a combinatorial approach based on modeling and experiment: application to HLA-DR4

Combinatorial synthesis and large scale screening methods are being used increasingly in drug discovery, particularly for finding novel lead compounds. Although these "random" methods sample larger areas of chemical space than traditional synthetic approaches, only a relatively small percentage of all possible compounds are practically accessible. It is therefore helpful to select regions of chemical space that have greater likelihood of yielding useful leads. When three-dimensional structural data are available for the target molecule this can be achieved by applying structure-based computational design methods to focus the combinatorial library. This is advantageous over the standard usage of computational methods to design a small number of specific novel ligands, because here computation is employed as part of the combinatorial design process and so is required only to determine a propensity for binding of certain chemical moieties in regions of the target molecule. This paper describes the application of the Multiple Copy Simultaneous Search (MCSS) method, an active site mapping and de novo structure-based design tool, to design a focused combinatorial library for the class II MHC protein HLA-DR4. Methods for the synthesizing and screening the computationally designed library are presented; evidence is provided to show that binding was achieved. Although the structure of the protein-ligand complex could not be determined, experimental results including cross-exclusion of a known HLA-DR4 peptide ligand (HA) by a compound from the library. Computational model building suggest that at least one of the ligands designed and identified by the methods described binds in a mode similar to that of native peptides.

Structure-based design of TACE selective inhibitors: manipulations in the S1'-S3' pocket

A series of beta-sulfonyl hydroxamate TACE inhibitors, bearing a butynylamino or a butynyloxy P1' group, was designed and synthesized. Of the compounds investigated, 22 has excellent potency against isolated TACE enzyme, shows good selectivity over MMP-2 and MMP-13, and oral activity in an in vivo mouse model of TNF-alpha production.

Probing acid replacements of thiophene PTP1B inhibitors

The following account describes our systematic effort to replace one of the carboxylate groups of our diacid thiophene PTP1B inhibitors. Active hits were validated using enzymatic assays before pursuing efforts to improve the potency. Only when the C2 carboxylic acid was replaced with another ionizable functional group was reversible and competitive inhibition retained. Use of a tetrazole ring or 1,2,5-thiadiazolidine-3-one-1,1-dioxide as a carboxylate mimetic led to the discovery of two unique starting series that showed improved permeability (PAMPA) and potency of the order of 300nM. The SAR from these efforts underscores some of the major challenges in developing small molecule inhibitors for PTP1B.

Lead optimization via high-throughput molecular docking

Structure-based lead optimization approaches are increasingly playing a role in the drug-discovery process. Recent advances in 'high-throughput' molecular docking methods and examples of their successful use in lead optimization are reviewed. Measures of docking accuracy, scoring function comparisons, and consensus approaches are discussed. Differences in docking protocols typically used for lead optimization versus lead generation are highlighted; this section includes a discussion of the latest methods for the incorporation of protein flexibility. New approaches developed specifically for the design of combinatorial libraries as well as those designed or used for 'fragment' versus lead optimization are presented. Finally, potential future improvements to the technology are outlined.

Identification of potent and selective TACE inhibitors via the S1 pocket

By focusing on the P1 portion of the piperidine beta-sulfone ligands we identified a motif that induces selectivity and resulted in a series of TACE inhibitors that demonstrated excellent in vitro potency against isolated TACE enzyme and excellent selectivity over MMPs 1, 2, 9, 13, and 14.

Monocyclic thiophenes as protein tyrosine phosphatase 1B inhibitors: Capturing interactions with Asp48

A series of monocyclic thiophenes was designed and synthesized as PTP1B inhibitors. Guided by X-ray co-crystal structural information and computational modeling, rational design led to key interactions with Asp48 and improved inhibitory potency against PTP1B.

1,2,4-Oxadiazolidin-3,5-diones and 1,3,5-triazin-2,4,6-triones as cytosolic phospholipase A2α inhibitors

1,2,4-Oxadiazolidin-3,5-dione and 1,3,5-triazin-2,4,6-trione scaffolds were employed as templates to incorporate the pharmacophore requirements of cytosolic phospholipase A2alpha substrate mimetics. Inhibitors that are active in both enzyme, and cell-based assays were identified from both classes. From the SAR work carried out and modeling efforts around these templates, the triazinetrione scaffold with an additional substitution point was found to be more favorable.

Use of structure-based drug design approaches to obtain novel anthranilic acid acyl carrier protein synthase inhibitors

Acyl carrier protein synthase (AcpS) catalyzes the transfer of the 4'-phosphopantetheinyl group from the coenzyme A to a serine residue in acyl carrier protein (ACP), thereby activating ACP, an important step in cell wall biosynthesis. The structure-based design of novel anthranilic acid inhibitors of AcpS, a potential antibacterial target, is presented. An initial high-throughput screening lead and numerous analogues were modeled into the available AcpS X-ray structure, opportunities for synthetic modification were identified, and an iterative process of synthetic modification, X-ray complex structure determination with AcpS, biological testing, and further modeling ultimately led to potent inhibitors of the enzyme. Four X-ray complex structures of representative anthranilic acid ligands bound to AcpS are described in detail.

Bicyclic and tricyclic thiophenes as protein tyrosine phosphatase 1B inhibitors

A novel pyridothiophene inhibitor of PTP1B was discovered by rational screening of phosphotyrosine mimics at high micromolar concentrations. The potency of this lead compound has been improved significantly by medicinal chemistry guided by X-ray crystallography and molecular modeling. Excellent consistency has been observed between structure-activity relationships and structural information from PTP1B-inhibitor complexes.

Catalytic domain crystal structure of protein kinase C-theta (PKCtheta)

A member of the novel protein kinase C (PKC) subfamily, PKC, is an essential component of the T cell synapse and is required for optimal T cell activation and interleukin-2 production. Selective involvement of PKC in TCR signaling makes this enzyme an attractive therapeutic target in T cell-mediated disease processes. In this report we describe the crystal structure of the catalytic domain of PKC at 2.0-A resolution. Human recombinant PKC kinase domain was expressed in bacteria as catalytically active phosphorylated enzyme and co-crystallized with its subnanomolar, ATP site inhibitor staurosporine. The structure follows the classic bilobal kinase fold and shows the enzyme in its active conformation and phosphorylated state. Inhibitory interactions between conserved features of staurosporine and the ATP-binding cleft are accompanied by closing of the glycine-rich loop, which also maintains an inhibitory arrangement by blocking the phosphate recognition subsite. The two major phosphorylation sites, Thr-538 in the activation loop and Ser-695 in the hydrophobic motif, are both occupied in the structure, playing key roles in stabilizing active conformation of the enzyme and indicative of PKC autocatalytic phosphorylation and activation during bacterial expression. The PKC-staurosporine complex represents the first kinase domain crystal structure of any PKC isotypes to be determined and as such should provide valuable insight into PKC specificity and into rational drug design strategies for PKC selective leads.

Anthranilate 4H-oxazol-5-ones: novel small molecule antibacterial acyl carrier protein synthase (AcpS) inhibitors

D-optimal design and Projection to Latent Structures (PLS) analysis were used to optimize screening hit 5 (B. subtilis AcpS IC(50): 15 microM, B. subtilis MIC: >200 microM) into a series of 4H-oxazol-5-one, small molecule, antibacterial, AcpS inhibitors. Specifically, 15, 16 and 18 show microM or sub-microM AcpS inhibition (IC(50)s: 15: 1.1 microM, 16: 1.5 microM, 18: 0.27 microM) and moderate antibacterial activity (MICs: 12.5-50 microM) against B. subtilis, E. faecalis ATCC, E. faecalis VRE and S. pneumo+.

Structure–activity relationships of indole cytosolic phospholipase A 2 α inhibitors: substrate mimetics

An SAR effort focused on generating cPLA(2)alpha inhibitors using a substrate mimetic approach is reported. Indole inhibitors of cPLA(2)alpha with promising pharmacokinetic parameters that were active in both an isolated enzyme assay and in cell-based assays were discovered. Modeling these compounds into the cPLA(2)alpha structure validated the assumptions made at the start of the SAR effort.

Pharmacophore-based molecular docking to account for ligand flexibility

Rapid computational mining of large 3D molecular databases is central to generating new drug leads. Accurate virtual screening of large 3D molecular databases requires consideration of the conformational flexibility of the ligand molecules. Ligand flexibility can be included without prohibitively increasing the search time by docking ensembles of precomputed conformers from a conformationally expanded database. A pharmacophore-based docking method whereby conformers of the same or different molecules are overlaid by their largest 3D pharmacophore and simultaneously docked by partial matches to that pharmacophore is presented. The method is implemented in DOCK 4.0.

Automated generation of MCSS-derived pharmacophoric DOCK site points for searching multiconformation databases

All docking methods employ some sort of heuristic to orient the ligand molecules into the binding site of the target structure. An automated method, MCSS2SPTS, for generating chemically labeled site points for docking is presented. MCSS2SPTS employs the program Multiple Copy Simultaneous Search (MCSS) to determine target-based theoretical pharmacophores. More specifically, chemically labeled site points are automatically extracted from selected low-energy functional-group minima and clustered together. These pharmacophoric site points can then be directly matched to the pharmacophoric features of database molecules with the use of either DOCK or PhDOCK to place the small molecules into the binding site. Several examples of the ability of MCSS2SPTS to reproduce the three-dimensional pharmacophoric features of ligands from known ligand-protein complex structures are discussed. In addition, a site-point set calculated for one human immunodeficiency virus 1 (HIV1) protease structure is used with PhDOCK to dock a set of HIV1 protease ligands; the docked poses are compared to the corresponding complex structures of the ligands. Finally, the use of an MCSS2SPTS-derived site-point set for acyl carrier protein synthase is compared to the use of atomic positions from a bound ligand as site points for a large-scale DOCK search. In general, MCSS2SPTS-generated site points focus the search on the more relevant areas and thereby allow for more effective sampling of the target site.

Use of MCSS to design small targeted libraries: application to picornavirus ligands

Computational methods were used to design structure-based combinatorial libraries of antipicornaviral capsid-binding ligands. The multiple copy simultaneous search (MCSS) program was employed to calculate functionality maps for many diverse functional groups for both the poliovirus and rhinovirus capsid structures in the region of the known drug binding pocket. Based on the results of the MCSS calculations, small combinatorial libraries consisting of 10s or 100s of three-monomer compounds were designed and synthesized. Ligand binding was demonstrated by a noncell-based mass spectrometric assay, a functional immuno-precipitation assay, and crystallographic analysis of the complexes of the virus with two of the candidate ligands. The P1/Mahoney poliovirus strain was used in the experimental studies. A comparison showed that the MCSS calculations had correctly identified the observed binding site for all three monomer units in one ligand and for two out of three in the other ligand. The correct central monomer position in the second ligand was reproduced in calculations in which the several key residues lining the pocket were allowed to move. This study validates the computational methodology. It also illustrates that subtle changes in protein structure can lead to differences in docking results and points to the importance of including target flexibility, as well as ligand flexibility, in the design process.

Functional group placement in protein binding sites: a comparison of GRID and MCSS

One approach to combinatorial ligand design begins by determining optimal locations (i.e., local potential energy minima) for functional groups in the binding site of a target macromolecule. MCSS and GRID are two methods, based on significantly different algorithms, which are used for this purpose. A comparison of the two methods for the same functional groups is reported. Calculations were performed for nonpolar and polar functional groups in the internal hydrophobic pocket of the poliovirus capsid protein, and on the binding surface of the src SH3 domain. The two approaches are shown to agree qualitatively; i.e., the global characteristics of the functional group maps generated by MCSS and GRID are similar. However, there are significant differences in the relative interaction energies of the two sets of minima, a consequence of the different functional form used to evaluate polar interactions (electrostatics and hydrogen bonding) in the two methods. The single sphere representation used by GRID affords only positional information, supplemented by the identification of hydrogen bonding interactions. By contrast, the multi-atom representation of most MCSS groups yields in both positional and orientational information. The two methods are most similar for small functional groups, while for larger functional groups MCSS yields results consistent with GRID but superior in detail. These results are in accord with the somewhat different purposes for which the two methods were developed. GRID has been used mainly to introduce functionalities at specific positions in lead compounds, in which case the orientation is predetermined by the structure of the latter. The orientational information provided by MCSS is important for its use in the de novo design of large, multi-functional ligands, as well as for improving lead compounds.

A structurally biased combinatorial approach for discovering new anti-picornaviral compounds

BACKGROUND

Picornaviruses comprise a family of small, non-enveloped RNA viruses. A common feature amongst many picornaviruses is a hydrophobic pocket in the core of VP1, one of the viral capsid proteins. The pocket is normally occupied by a mixture of unidentified, fatty acid-like moieties, which can be competed out by a family of capsid-binding, antiviral compounds. Many members of the Picornaviridae family are pathogenic to both humans and livestock, yet no adequate therapeutics exist despite over a decade's worth of research in the field. To address this challenge, we developed a strategy for rapid identification of capsid-binding anti-picornaviral ligands. The approach we took involved synthesizing structurally biased combinatorial libraries that had been targeted to the VP1 pocket of poliovirus and rhinovirus. The libraries are screened for candidate ligands with a high throughput mass spectrometry assay.

RESULTS

Using the mass spectrometry assay, we were able to identify eight compounds from a targeted library of 75 compounds. The antiviral activity of these candidates was assessed by (i) measuring the effect on the kinetics of viral uncoating and (ii) the protective effect of each drug in traditional cell-based assays. All eight of the candidates exhibited antiviral activity, but three of them were particularly effective against poliovirus and rhinovirus.

CONCLUSIONS

The results illustrate the utility of combining structure-based design with combinatorial chemistry. The success of our approach suggests that assessment of small, targeted libraries, which query specific chemical properties, may be the best strategy for surveying all of chemical space for ideal anti-picornaviral compounds.

Computational design of D-peptide inhibitors of hepatitis delta antigen dimerization

Hepatitis delta virus (HDV) encodes a single polypeptide called hepatitis delta antigen (DAg). Dimerization of DAg is required for viral replication. The structure of the dimerization region, residues 12 to 60, consists of an anti-parallel coiled coil [Zuccola et al., Structure, 6(1998)821]. Multiple Copy Simultaneous Searches (MCSS) of the hydrophobic core region formed by the bend in the helix of one monomer of this structure were carried out for many diverse functional groups. Six critical interaction sites were identified. The Protein Data Bank was searched for backbone templates to use in the subsequent design process by matching to these sites. A 14 residue helix expected to bind to the D-isomer of the target structure was selected as the template. Over 200,000 mutant sequences of this peptide were generated based on the MCSS results. A secondary structure prediction algorithm was used to screen all sequences. and in general only those that were predicted to be highly helical were retained. Approximately 100 of these 14-mers were model built as D-peptides and docked with the L-isomer of the target monomer. Based on calculated interaction energies, predicted helicity, and intrahelical salt bridge patterns, a small number of peptides were selected as the most promising candidates. The ligand design approach presented here is the computational analogue of mirror image phage display. The results have been used to characterize the interactions responsible for formation of this model anti-parallel coiled coil and to suggest potential ligands to disrupt it.

Structural and kinetic analysis of Escherichia coli GDP-mannose 4,6 dehydratase provides insights into the enzyme's catalytic mechanism and regulation by GDP-fucose

BACKGROUND

GDP-mannose 4,6 dehydratase (GMD) catalyzes the conversion of GDP-(D)-mannose to GDP-4-keto, 6-deoxy-(D)-mannose. This is the first and regulatory step in the de novo biosynthesis of GDP-(L)-fucose. Fucose forms part of a number of glycoconjugates, including the ABO blood groups and the selectin ligand sialyl Lewis X. Defects in GDP-fucose metabolism have been linked to leukocyte adhesion deficiency type II (LADII).

RESULTS

The structure of the GDP-mannose 4,6 dehydratase apo enzyme has been determined and refined using data to 2.3 A resolution. GMD is a homodimeric protein with each monomer composed of two domains. The larger N-terminal domain binds the NADP(H) cofactor in a classical Rossmann fold and the C-terminal domain harbors the sugar-nucleotide binding site. We have determined the GMD dissociation constants for NADP, NADPH and GDP-mannose. Each GMD monomer binds one cofactor and one substrate molecule, suggesting that both subunits are catalytically competent. GDP-fucose acts as a competitive inhibitor, suggesting that it binds to the same site as GDP-mannose, providing a mechanism for the feedback inhibition of fucose biosynthesis.

CONCLUSIONS

The X-ray structure of GMD reveals that it is a member of the short-chain dehydrogenase/reductase (SDR) family of proteins. We have modeled the binding of NADP and GDP-mannose to the enzyme and mutated four of the active-site residues to determine their function. The combined modeling and mutagenesis data suggests that at position 133 threonine substitutes serine as part of the serine-tyrosine-lysine catalytic triad common to the SDR family and Glu 135 functions as an active-site base.

Computational approaches to structure-based ligand design

The first computational structure-based drug design methods came into existence in the early 1980s and are, to an extent, still in their infancy. There have been a few successes to date. With dramatic increases in computer speed, improved accuracy in ligand scoring functions, and the advent of combinatorial chemistry, there promises to be many more. In addition, the virtual explosion in the amount of available sequence and structural information has increased the need to develop these computational techniques to exploit this vast body of information. In this review, recent advances in computational methods for database searching and docking, de novo drug design, and estimation of ligand binding affinities are discussed.

Use of the multiple copy simultaneous search (MCSS) method to design a new class of picornavirus capsid binding drugs

A combinatorial ligand design approach based on the multiple copy simultaneous search (MCSS) method and a simple scheme for joining MCSS functional group sites was applied to the binding pocket of P3/Sabin poliovirus and rhinovirus 14. The MCSS method determines where specific functional (chemical) groups have local potential energy minima in the binding site. Before the virus application, test calculations were run to determine the optimal set of input parameters to be used in evaluating the MCSS results. The MCSS minima are analysed and selected minima are connected with (CH2)n linkers to form candidate ligands, whose structures are optimized in the binding site. Estimates of the binding strength were made for the ligands and compared with those for known drugs. The results indicate that the proposed ligands should bind to P3/Sabin poliovirus at least as well as the best of the existing drugs, and that they should also bind to P1/Mahoney poliovirus and rhinovirus 14. A detailed comparison of the poliovirus and rhinovirus binding pockets and an analysis of drug binding specificity is presented.