Design of inhibitors of Ras--Raf interaction using a computational combinatorial algorithm

MCSS-Based Predictions of Binding Mode and Selectivity of Nucleotide Ligands

Computational fragment-based approaches are widely used in drug design and discovery. One of their limitations is the lack of performance of docking methods, mainly the scoring functions. With the emergence of fragment-based approaches for single-stranded RNA ligands, we analyze the performance in docking and screening powers of an MCSS-based approach. The performance is evaluated on a benchmark of protein-nucleotide complexes where the four RNA residues are used as fragments. The screening power can be considered the major limiting factor for the fragment-based modeling or design of sequence-selective oligonucleotides. We show that the MCSS sampling is efficient even for such large and flexible fragments. Hybrid solvent models based on some partial explicit representations improve both the docking and screening powers. Clustering of the n best-ranked poses can also contribute to a lesser extent to better performance. A detailed analysis of molecular features suggests various ways to optimize the performance further.

Computational Prediction of the Epitopes of HA1 Protein of Influenza Viruses to its Neutralizing Antibodies

In this work, we have used a new method to predict the epitopes of HA1 protein of influenza virus to several antibodies HC19, CR9114, BH151 and 4F5. While our results reproduced the binding epitopes of H3N2 or H5N1 for the neutralizing antibodies HC19, CR9114, and BH151 as revealed from the available crystal structures, additional epitopes for these antibodies were also suggested. Moreover, the predicted epitopes of H5N1 HA1 for the newly developed antibody 4F5 are located at the receptor binding domain, while previous study identified a region 76-WLLGNP-81 as the epitope. The possibility of antibody recognition of influenza virus via different mechanism by binding to different epitopes of an antigen is also discussed.

Computational identification of antibody epitopes of human papillomavirus 16 (HPV16) L1 proteins

Previously, we developed a method to predict epitopes on a protein recognized by specific antibodies. In this study, we have applied this method to identify the epitopes of the human papillomavirus 16 (HPV16) L1 capsomer that is bound by monoclonal antibodies U4, AE3 and AG7. Initially, the method was validated by the identification of epitopes of HPV16 L1 capsomer that bind to antibody U4. Our predicted epitopes were in agreement with the cryto-electron microscopy (cryto-EM) structure of the complex. The method was then used to predict the epitopes of HPV16 L1 binding of antibodies AE3 and AG7. Our calculations indicated that antibody AE3 binds to the HPV16 L1 capsomer at two different regions. Firstly, the region recognized by antibody U4 and secondly, the region recognized by antibody V5, which have been shown in the cryto-EM structure of the V5 and HPV16 L1 complex. In comparison, the antibody AG7 binds to the capsomer only at the epitopes bound by antibody U4. Therefore, antibody AE3 is predicted to have higher affinity than antibody AG7 and could be used for developing highly efficient anti-HPV monoclonal antibodies in the clinical treatment of HPV infections.

Inhibition of the Ras/Raf interaction and repression of renal cancer xenografts in vivo by an enantiomeric iridium(iii) metal-based compound

Targeting protein-protein interactions (PPIs) offers tantalizing opportunities for therapeutic intervention for the treatment of human diseases. Modulating PPI interfaces with organic small molecules has been found to be exceptionally challenging, and few candidates have been successfully developed into clinical drugs. Meanwhile, the striking array of distinctive properties exhibited by metal compounds renders them attractive scaffolds for the development of bioactive leads. Here, we report the identification of iridium(iii) compounds as inhibitors of the H-Ras/Raf-1 PPI. The lead iridium(iii) compound 1 exhibited potent inhibitory activity against the H-Ras/Raf-1 interaction and its signaling pathway in vitro and in vivo, and also directly engaged both H-Ras and Raf-1-RBD in cell lysates. Moreover, 1 repressed tumor growth in a mouse renal xenograft tumor model. Intriguingly, the Δ-enantiomer of 1 showed superior potency in the biological assays compared to Λ-1 or racemic 1. These compounds could potentially be used as starting scaffolds for the development of more potent Ras/Raf PPI inhibitors for the treatment of kidney cancer or other proliferative diseases.

Total Chemical Synthesis and Folding of All-l and All-d Variants of Oncogenic KRas(G12V)

The Ras proteins are essential GTPases involved in the regulation of cell proliferation and survival. Mutated oncogenic forms of Ras alter effector binding and innate GTPase activity, leading to deregulation of downstream signal transduction. Mutated forms of Ras are involved in approximately 30% of human cancers. Despite decades of effort to develop direct Ras inhibitors, Ras has long been considered "undruggable" due to its high affinity for GTP and its lack of hydrophobic binding pockets. Herein, we report a total chemical synthesis of all-l- and all-d-amino acid biotinylated variants of oncogenic mutant KRas(G12V). The protein is synthesized using Fmoc-based solid-phase peptide synthesis and assembled using combined native chemical ligation and isonitrile-mediated activation strategies. We demonstrate that both KRas(G12V) enantiomers can successfully fold and bind nucleotide substrates and binding partners with observable enantiodiscrimination. By demonstrating the functional competency of a mirror-image form of KRas bound to its corresponding enantiomeric nucleotide triphosphate, this study sets the stage for further biochemical studies with this material. In particular, this protein will enable mirror-image yeast surface display experiments to identify all-d peptide ligands for oncogenic KRas, providing a useful tool in the search for new therapeutics against this challenging disease target.

Design of peptide inhibitors of human papillomavirus 16 (HPV16) transcriptional regulator E1–E2 formation

Here, we have proposed a new scheme of the computational combinatorial design approach to identify potential inhibitor peptides. It consists of four steps: (i) using “multiple copy simultaneous search” (MCSS) procedure to locate specific functional groups on the protein surface; (ii) the peptide main chain is constructed based on the location of favored N-methylacetamide (NMA) groups; (iii) molecular dynamics simulations of the complex formed between the constructed peptides with the target protein in explicit water molecules are carried to select the peptides with strong binding to the protein and (iv) the sequences of the stable peptides selected from (iii) are aligned and the frequencies of the amino acids at each position of peptide are calculated. Sequence patterns of potential inhibitors are determined based on the frequency of amino acids at each position. It was applied to design peptide inhibitors that bind to the E2 protein of HPV16 so as to disrupt its transcriptional regulator of E1–E2 complex formation. The sequence pattern of these potential inhibitors is in agreement with known inhibitors obtained from phage display, and the MCSS calculations indicate that a hydrophobic pocket on HPV16 E2 plays a significant role in E1–E2 formation and inhibitor-E2 binding.

Computational Identification of Antibody Epitopes on the Dengue Virus NS1 Protein

We have previously described a method to predict antigenic epitopes on proteins recognized by specific antibodies. Here we have applied this method to identify epitopes on the NS1 proteins of the four Dengue virus serotypes (DENV1-4) that are bound by a small panel of monoclonal antibodies 1H7.4, 1G5.3 and Gus2. Several epitope regions were predicted for these antibodies and these were found to reflect the experimentally observed reactivities. The known binding epitopes on DENV2 for the antibodies 1H7.4 and 1G5.3 were identified, revealing the reasons for the serotype specificity of 1H7.4 and 1G5.3, and the non-selectivity of Gus2. As DENV NS1 is critical for virus replication and a key vaccine candidate, epitope prediction will be valuable in designing appropriate vaccine control strategies. The ability to predict potential epitopes by computational methods significantly reduces the amount of experimental work required to screen peptide libraries for epitope mapping.

In Silico Generation of Peptides by Replica Exchange Monte Carlo: Docking-Based Optimization of Maltose-Binding-Protein Ligands

Short peptides can be designed in silico and synthesized through automated techniques, making them advantageous and versatile protein binders. A number of docking-based algorithms allow for a computational screening of peptides as binders. Here we developed ex-novo peptides targeting the maltose site of the Maltose Binding Protein, the prototypical system for the study of protein ligand recognition. We used a Monte Carlo based protocol, to computationally evolve a set of octapeptides starting from a polialanine sequence. We screened in silico the candidate peptides and characterized their binding abilities by surface plasmon resonance, fluorescence and electrospray ionization mass spectrometry assays. These experiments showed the designed binders to recognize their target with micromolar affinity. We finally discuss the obtained results in the light of further improvement in the ex-novo optimization of peptide based binders.

Antibody recognition of Shiga toxins (Stxs): computational identification of the epitopes of Stx2 subunit A to the antibodies 11E10 and S2C4

We have recently developed a new method to predict the epitopes of the antigens that are recognized by a specific antibody. In this work, we applied the method to identify the epitopes of the Shiga toxin (Stx2 subunit A) that were bound by two specific antibodies 11E10 and S2C4. The predicted epitopes of Stx2 binding to the antibody 11E10 resembles the recognition surface constructed by the regions of Stx2 identified experimentally. For the S2C4, our results indicate that the antibody recognizes the Stx2 at two different regions on the protein surface. The first region (residues 246-254: ARSVRAVNE) is similar to the recognition region of the 11E10, while the second region is formed by two epitopes. The second region is particularly significant because it includes the amino acid sequence region that is diverse between Stx2 and other Stx (residues 176-188: QREFRQALSETAPV). This new recognition region is believed to play an important role in the experimentally observed selectivity of S2C4 to the Stx2.

Computational identification of epitopes in the glycoproteins of novel bunyavirus (SFTS virus) recognized by a human monoclonal antibody (MAb 4-5)

In this work, we have developed a new approach to predict the epitopes of antigens that are recognized by a specific antibody. Our method is based on the "multiple copy simultaneous search" (MCSS) approach which identifies optimal locations of small chemical functional groups on the surfaces of the antibody, and identifying sequence patterns of peptides that can bind to the surface of the antibody. The identified sequence patterns are then used to search the amino-acid sequence of the antigen protein. The approach was validated by reproducing the binding epitope of HIV gp120 envelop glycoprotein for the human neutralizing antibody as revealed in the available crystal structure. Our method was then applied to predict the epitopes of two glycoproteins of a newly discovered bunyavirus recognized by an antibody named MAb 4-5. These predicted epitopes can be verified by experimental methods. We also discuss the involvement of different amino acids in the antigen-antibody recognition based on the distributions of MCSS minima of different functional groups.

The multi-copy simultaneous search methodology: a fundamental tool for structure-based drug design

Fragment-based ligand design approaches, such as the multi-copy simultaneous search (MCSS) methodology, have proven to be useful tools in the search for novel therapeutic compounds that bind pre-specified targets of known structure. MCSS offers a variety of advantages over more traditional high-throughput screening methods, and has been applied successfully to challenging targets. The methodology is quite general and can be used to construct functionality maps for proteins, DNA, and RNA. In this review, we describe the main aspects of the MCSS method and outline the general use of the methodology as a fundamental tool to guide the design of de novo lead compounds. We focus our discussion on the evaluation of MCSS results and the incorporation of protein flexibility into the methodology. In addition, we demonstrate on several specific examples how the information arising from the MCSS functionality maps has been successfully used to predict ligand binding to protein targets and RNA.

Characterization of ATP-independent ERK inhibitors identified through in silico analysis of the active ERK2 structure

The extracellular signal-regulated kinases (ERK1 and ERK2) are important mediators of cell proliferation. Constitutive activation of the ERK proteins plays a critical role in the proliferation of many human cancers. Taking advantage of recently identified substrate docking domains on ERK2, we have used computer-aided drug design (CADD) to identify novel low molecular weight compounds that interact with ERK2 in an ATP-independent manner and disrupt substrate-specific interactions. In the current study, a CADD screen of the 3D structure of active phosphorylated ERK2 protein was used to identify inhibitory compounds. We tested 13 compounds identified by the CADD screen in ERK-specific phosphorylation, cell proliferation, and binding assays. Of the 13 compounds tested, 4 compounds strongly inhibited ERK-mediated phosphorylation of ribosomal S6 kinase-1 (Rsk-1) and/or the transcription factor Elk-1 and inhibited the proliferation of HeLa cervical carcinoma cells with IC(50) values in the 2-10 microM range. These studies demonstrate that CADD can be used to identify lead compounds for development of novel non-ATP-dependent inhibitors selective for active ERK and its interactions with substrates involved in cancer cell proliferation.

Neuronal nitric oxide synthase-induced S-nitrosylation of H-Ras inhibits calcium ionophore-mediated extracellular-signal-regulated kinase activity

nNOS (neuronal nitric oxide synthase) is a constitutively expressed enzyme responsible for the production of NO* from L-arginine and O2. NO* acts as both an intra- and an inter-cellular messenger that mediates a variety of signalling pathways. Previous studies from our laboratory have demonstrated that nNOS production of NO* blocks Ca2+-ionophore-induced activation of ERK1/2 (extracellular-signal-regulated kinase 1/2) of the mitogen-activated protein kinases through a mechanism involving Ras G-proteins and Raf-1 kinase. Herein we describe a mechanism by which NO* blocks Ca2+-mediated ERK1/2 activity through direct modification of H-Ras. Ca2+-mediated ERK1/2 activation in NO*-producing cells could be restored by exogenous expression of constitutively active mitogen-activated protein kinase kinase 1. In contrast, exogenous expression of constitutively active mutants of Raf-1 and H-Ras only partially restored ERK1/2 activity, by 50% and 10% respectively. On the basis of these findings, we focused on NO*-mediated mechanisms of H-Ras inhibition. Assays for GTP loading and H-Ras interactions with the Ras-binding domain on Raf-1 demonstrated a decrease in H-Ras activity in the presence of NO*. We demonstrate that S-nitrosylation of H-Ras occurs in nNOS-expressing cells activated with Ca2+ ionophore. Mutation of a putative nitrosylation site at Cys118 inhibited S-nitrosylation and restored ERK1/2 activity by constitutively active H-Ras even in the presence of NO*. These findings indicate that intracellular generation of NO* by nNOS leads to S-nitrosylation of H-Ras, which interferes with Raf-1 activation and propagation of signalling through ERK1/2.

Identification of novel extracellular signal-regulated kinase docking domain inhibitors

The extracellular signal regulated kinase (ERK1 and ERK2) signal transduction pathways play a critical role in cell proliferation. Hyperactivation of the ERK proteins either through increased expression of membrane-bound growth factor receptors or genetic mutations of upstream proteins is thought to be involved in the pathogenesis of many human cancers. Thus, targeted inhibition of ERK signaling is viewed as a potential approach to prevent cancer cell proliferation. Currently, no specific inhibitors of the ERK proteins exist. Moreover, most kinase inhibitors lack specificity because they target the ATP binding region, which is well conserved among the protein kinase families. Taking advantage of recently identified ERK docking domains, which are reported to facilitate substrate protein interactions, we have used computer-aided drug design (CADD) to identify novel small molecular weight ERK inhibitors. Following a CADD screen of over 800 000 molecules, 80 potential compounds were selected and tested for activity in biological assays. Several compounds inhibited ERK-specific phosphorylation of ribosomal S6 kinase-1 (Rsk-1) or the ternary complex factor Elk-1 (TCF/Elk-1), both of which are involved in promoting cell proliferation. Active compounds showed a dose-dependent reduction in the proliferation of several cancer cell lines as measured by colony survival assays. Direct binding between the active compounds and ERK2 was indicated by fluorescence quenching. These active compounds may serve as lead candidates for development of novel specific inhibitors of ERK-substrate interactions involved in cell proliferation.

Insights into protein-protein binding by binding free energy calculation and free energy decomposition for the Ras-Raf and Ras-RalGDS complexes

Absolute binding free energy calculations and free energy decompositions are presented for the protein-protein complexes H-Ras/C-Raf1 and H-Ras/RalGDS. Ras is a central switch in the regulation of cell proliferation and differentiation. In our study, we investigate the capability of the molecular mechanics (MM)-generalized Born surface area (GBSA) approach to estimate absolute binding free energies for the protein-protein complexes. Averaging gas-phase energies, solvation free energies, and entropic contributions over snapshots extracted from trajectories of the unbound proteins and the complexes, calculated binding free energies (Ras-Raf: -15.0(+/-6.3)kcal mol(-1); Ras-RalGDS: -19.5(+/-5.9)kcal mol(-1)) are in fair agreement with experimentally determined values (-9.6 kcal mol(-1); -8.4 kcal mol(-1)), if appropriate ionic strength is taken into account. Structural determinants of the binding affinity of Ras-Raf and Ras-RalGDS are identified by means of free energy decomposition. For the first time, computationally inexpensive generalized Born (GB) calculations are applied in this context to partition solvation free energies along with gas-phase energies between residues of both binding partners. For selected residues, in addition, entropic contributions are estimated by classical statistical mechanics. Comparison of the decomposition results with experimentally determined binding free energy differences for alanine mutants of interface residues yielded correlations with r(2)=0.55 and 0.46 for Ras-Raf and Ras-RalGDS, respectively. Extension of the decomposition reveals residues as far apart as 25A from the binding epitope that can contribute significantly to binding free energy. These "hotspots" are found to show large atomic fluctuations in the unbound proteins, indicating that they reside in structurally less stable regions. Furthermore, hotspot residues experience a significantly larger-than-average decrease in local fluctuations upon complex formation. Finally, by calculating a pair-wise decomposition of interactions, interaction pathways originating in the binding epitope of Raf are found that protrude through the protein structure towards the loop L1. This explains the finding of a conformational change in this region upon complex formation with Ras, and it may trigger a larger structural change in Raf, which is considered to be necessary for activation of the effector by Ras.

Survey of the year 2001 commercial optical biosensor literature

We have assembled references of 700 articles published in 2001 that describe work performed using commercially available optical biosensors. To illustrate the technology's diversity, the citation list is divided into reviews, methods and specific applications, as well as instrument type. We noted marked improvements in the utilization of biosensors and the presentation of kinetic data over previous years. These advances reflect a maturing of the technology, which has become a standard method for characterizing biomolecular interactions.