Alexander Berchanski

Hydrophobic complementarity in protein–protein docking

Formation of hydrophobic contacts across a newly formed interface is energetically favorable. Based on this observation we developed a geometric–hydrophobic docking algorithm that estimates quantitatively the hydrophobic complementarity at protein–protein interfaces. Each molecule to be docked is represented as a grid of complex numbers, storing information regarding the shape of the molecule in the real part and information regarding the hydropathy of the surface in the imaginary part. The grid representations are correlated using fast Fourier transformations. The algorithm is used to compare the extent of hydrophobic complementarity in oligomers (represented by D2 tetramers) and in hetero‐dimers of soluble proteins (complexes). We also test the implication of hydrophobic complementarity in distinguishing correct from false docking solutions. We find that hydrophobic complementarity at the interface exists in oligomers and in complexes, and in both groups the extent of such complementarity depends on the size of the interface. Thus, the non‐polar portions of large interfaces are more often juxtaposed than non‐polar portions of small interfaces. Next we find that hydrophobic complementarity helps to point out correct docking solutions. In oligomers it significantly improves the ranks of nearly correct reassembled and modeled tetramers. Combining geometric, electrostatic and hydrophobic complementarity for complexes gives excellent results, ranking a nearly correct solution < 10 for 5 of 23 tested systems, < 100 for 8 systems and < 1000 for 19 systems. Proteins 2004.

Construction of molecular assemblies via docking: Modeling of tetramers with D2 symmetry

Comparative modeling methods are commonly used to construct models of homologous proteins or oligomers. However, comparative modeling may be inapplicable when the number of subunits in a modeled oligomer is different than in the modeling template. Thus, a dimer cannot be a template for a tetramer because a new monomer‐monomer interface must be predicted. We present in this study a new prediction approach, which combines protein‐protein docking with either of two tetramer‐forming algorithms designed to predict the structures of tetramers with D2 symmetry. Both algorithms impose symmetry constraints. However, one of them requires identification of two of the C2 dimers within the tetramer in the docking step, whereas the other, less demanding algorithm, requires identification of only one such dimer. Starting from the structure of one subunit, the procedures successfully reconstructed 16 known D2 tetramers, which crystallize with either a monomer, a dimer or a tetramer in the asymmetric unit. In some cases we obtained clusters of native‐like tetramers that differ in the relative rotation of the two identical dimers within the tetramer. The predicted structural pliability for concanavalin‐A, phosphofructokinase, and fructose‐1,6‐bisphosphatase agrees semiquantitatively with the observed differences between the several experimental structures of these tetramers. Hence, our procedure identifies a structural soft‐mode that allows regulation via relative rigid‐body movements of the dimers within these tetramers. The algorithm also predicted three nearly correct tetramers from model structures of single subunits, which were constructed by comparative modeling from subunits of homologous tetrameric, dimeric, or hexameric systems. Proteins 2003.

Proteopedia: A status report on the collaborative, 3D web-encyclopedia of proteins and other biomolecules

Proteopedia is a collaborative, 3D web-encyclopedia of protein, nucleic acid and other biomolecule structures. Created as a means for communicating biomolecule structures to a diverse scientific audience, Proteopedia (http://www.proteopedia.org) presents structural annotation in an intuitive, interactive format and allows members of the scientific community to easily contribute their own annotations. Here, we provide a status report on Proteopedia by describing advances in the web resource since its inception three and a half years ago, focusing on features of potential direct use to the scientific community. We discuss its progress as a collaborative 3D-encyclopedia of structures as well as its use as a complement to scientific publications and PowerPoint presentations. We also describe Proteopedias use for 3D visualization in structure-related pedagogy.

Modeling oligomers with Cn or Dn symmetry: Application to CAPRI target 10

The abundance of oligomeric proteins makes them a frequent target for structure prediction. However, homologous proteins sometimes adopt different oligomerization states, rendering the prediction of structures of whole oligomers beyond the scope of comparative modeling. This obstacle can be overcome by combining comparative modeling of the single subunit of an oligomer with docking techniques, designed for predicting subunit–subunit interfaces. We present here algorithms for predicting the structures of homo‐oligomers with Cn or Dn (n > 2) symmetry. The prediction procedure includes a symmetry‐restricted docking step followed by a Cn or Dn oligomer‐forming step, in which the dimers from the docking step are assembled to oligomers. The procedure is applied to each of the crystallographically independent subunits in 8 Cn and 3 Dn oligomers, producing very accurate predictions. It is further applied to a single monomer of the tick‐borne encephalitis virus coat protein E (Target 10 of the CAPRI experiment). The predicted trimer ranked 30, obtained via rigid‐body geometric–hydrophobic docking followed by Cn oligomer formation, is very similar to the experimentally observed trimer formed by domain II of this protein. Furthermore, the predicted trimer formed from the separated domain I is also close to the experimental structure. Proteins 2005;60:202–206.

Insight into the mechanisms of aminoglycoside derivatives interaction with HIV-1 entry steps and viral gene transcription

In recent years, based on peptide models of HIV‐1 RNA binding, NMR structures of Tat‐responsive element–ligand complexes and aminoglycoside–RNA interactions, and HIV‐1 Tat structure, we have designed and synthesized aminoglycoside–arginine conjugates (AACs) and aminoglycoside poly‐arginine conjugates (APACs), to serve as Tat mimetics. These novel molecules inhibit HIV‐1 infectivity with 50% effective concentration values in the low micromolar range, the most potent compounds being the hexa‐arginine–neomycin B and nona‐d‐arginine–neomycin conjugates. Importantly, these compounds, in addition to acting as Tat antagonists, inhibit HIV‐1 infectivity by blocking several steps in HIV‐1 cell entry. The AACs and APACs inhibit HIV‐1 cell entry by interacting with gp120 at the CD4‐binding site, by interacting with CXCR4 at the binding site of the CXCR4 mAb 12G5, and apparently by interacting with transient structures of the ectodomain of gp41. In the current review, we discuss the mechanisms of anti‐HIV‐1 activities of these AACs, APACs and other aminoglycoside derivatives in detail. Targeting several key processes in the viral life cycle by the same compound not only may increase its antiviral efficacy, but more importantly, may reduce the capacity of the virus to develop resistance to the compound. AACs and APACs may thus serve as leading compounds for the development of multitargeting novel HIV‐1 inhibitors.

Prediction of the unknown: Inspiring experience with the CAPRI experiment

We submitted predictions for all seven targets in the CAPRI experiment. For four targets, our submitted models included acceptable, medium accuracy predictions of the structures of the complexes, and for a fifth target we identified the location of the binding site of one of the molecules. We used a weighted‐geometric docking algorithm in which contacts involving specified parts of the surfaces of either one or both molecules were up‐weighted or down‐weighted. The weights were based on available structural and biochemical data or on sequence analyses. The weighted‐geometric docking proved very useful for five targets, improving the complementarity scores and the ranks of the nearly correct solutions, as well as their statistical significance. In addition, the weighted‐geometric docking promoted formation of clusters of similar solutions, which include more accurate predictions. Proteins 2003;52:41–46.

Structure–function relationship of novel X4 HIV-1 entry inhibitors – L- and D-arginine peptide-aminoglycoside conjugates

We present the design, synthesis, anti‐HIV‐1 and mode of action of neomycin and neamine conjugated at specific sites to arginine 6‐ and 9‐mers d‐ and l‐arginine peptides (APACs). The d‐APACs inhibit the infectivity of X4 HIV‐1 strains by one or two orders of magnitude more potently than their respective l‐APACs. d‐arginine conjugates exhibit significantly higher affinity towards CXC chemokine receptor type 4 (CXCR4) than their l‐arginine analogs, as determined by their inhibition of monoclonal anti‐CXCR4 mAb 12G5 binding to cells and of stromal cell‐derived factor 1α (SDF‐1α)/CXCL12 induced cell migration. These results indicate that APACs inhibit X4 HIV‐1 cell entry by interacting with CXCR4 residues common to glycoprotein 120 and monoclonal anti‐CXCR4 mAb 12G5 binding. d‐APACs readily concentrate in the nucleus, whereas the l‐APACs do not. 9‐mer‐d‐arginine analogues are more efficient inhibitors than the 6‐mer‐d‐arginine conjugates and the neomycin‐d‐polymers are better inhibitors than their respective neamine conjugates. This and further structure–function studies of APACs may provide new target(s) and lead compound(s) of more potent HIV‐1 cell entry inhibitors.

Bacterial RNase P RNA is a drug target for aminoglycoside-arginine conjugates.

The ribonuclease P (RNase P) holoenzymes are RNPs composed of RNase P RNA (PRNA) and a variable number of P protein subunits. Primary differences in structure and function between bacterial and eukaryotic RNase P and its indispensability for cell viability make the bacterial enzyme an attractive drug target. On the basis of our previous studies, aminoglycoside-arginine conjugates (AACs) bind to HIV-1 TAR and Rev responsive element (RRE) RNAs significantly more efficiently than neomycin B. Their specific inhibition of bacterial rRNA as well as the findings that the hexa-arginine neomycin derivative (NeoR6) is 500-fold more potent than neomycin B in inhibiting bacterial RNase P, led us to explore the structure-function relationships of AACs in comparison to a new set of aminoglycoside-polyarginine conjugates (APACs). We here present predicted binding modes of AACs and APACs to PRNA. We used a multistep docking approach comprising rigid docking full scans and final refinement of the obtained complexes. Our docking results suggest three possible mechanisms of RNase P inhibition by AACs and APACs: competition with the P protein and pre-tRNA on binding to P1-P4 multihelix junction and to J19/4 region (probably including displacement of Mg2+ ions from the P4 helix) of PRNA; competition with Mg2+ ions near the P15 loop; and competition with the P protein and/or pre-tRNA near the P15 helix and interfering with interactions between the P protein and pre-tRNA at this region. The APACs revealed about 10-fold lower intermolecular energy than AACs, indicating stronger interactions of APACs than AACs with PRNA.

NeoR6 inhibits HIV-1-CXCR4 interaction without affecting CXCL12 chemotaxis activity.

Aminoglycoside-arginine conjugates (AACs) are multi-target HIV-1 inhibitors. The most potent AAC is neomycin hexa-arginine conjugate, NeoR6. We here demonstrate that NeoR6 interacts with CXCR4 without affecting CXCL12-CXCR4 ordinary chemotaxis activity or loss of CXCR4 cell surface expression. Importantly, NeoR6 alone does not affect cell migration, indicating that NeoR6 interacts with CXCR4 at a distinct site that is important for HIV-1 entry and mAb 12G5 binding, but not to CXCL12 binding or signaling sites. This is further supported by our modeling studies, showing that NeoR6 and CXCL12 bind to two distinct sites on CXCR4, in contrast with other CXCR4 inhibitors, e.g. T140 and AMD3100. This complementary utilization of chemical, biology, and computation analysis provides a powerful approach for designing anti-HIV-1 drugs without interfering with the natural function of CXCL12/CXCR4 binding.

Computer-based design of novel HIV-1 entry inhibitors: neomycin conjugated to arginine peptides at two specific sites

AbstractAminoglycoside–arginine conjugates (AAC and APAC) are multi-target inhibitors of human immunodeficiency virus type-1 (HIV-1). Here, we predict new conjugates of neomycin with two arginine peptide chains binding at specific sites on neomycin [poly-arginine-neomycin-poly-arginine (PA-Neo-PA)]. The rationale for the design of such compounds is to separate two short arginine peptides with neomycin, which may extend the binding region of the CXC chemokine receptor type 4 (CXCR4). We used homology models of CXCR4 and unliganded envelope glycoprotein 120 (HIV-1IIIB gp120) and docked PA-Neo-PAs and APACs to these using a multistep docking procedure. The results indicate that PA-Neo-PAs spread over two negatively charged patches of CXCR4. PA-Neo-PA–CXCR4 complexes are energetically more favorable than AACs/APAC–CXCR4 complexes. Notably, our CXCR4 model and docking procedure can be applied to predict new compounds that are either inhibitors of gp120–CXCR4 binding without affecting stromal cell-derived factor 1α (SDF-1α) chemotaxis activity, or inhibitors of SDF-1α–CXCR4 binding resulting in an anti-metastasis effect. We also predict that PA-Neo-PAs and APACs can interfere with CD4–gp120 binding in unliganded conformation. FigureThe r5-Neo-r5-CXCR4 complex. CXCR4 is shown in CPK representation. The negatively charged residues are shown in red and positively charged residues in blue. The r5-Neo-r5 is shown in stick representation, neomycin core is colored yellow and arginine moieties are colored magenta. Two negatively charged patches separated by neutral and positively charged residues are visible.