Analysis and prediction of hydrogen bonding in protein-DNA complexes using parallel processors

A number of essential biological functions are controlled by proteins that bind to specific sequences in genomic DNA. In this article we present a simplified model for analyzing DNA-protein interactions mediated exclusively by hydrogen bonds. Based on this model, an optimized algorithm for geometric pattern recognition was developed. The large number of local energy minima are efficiently screened by using a geometric approach to pattern matching based on a square-well potential. The second part of the algorithm represents a closed form solution for minimization based on a quadratic potential. A Monte Carlo method applied to a modified Lennard-Jones potential is used as a third step to rank DNA sequences in terms of pattern matching. Using protein structures derived from four DNA-protein complexes with three-dimensional coordinates established by X-ray diffraction analysis, all possible DNA sequences to which these proteins could bind were ranked in terms of binding energies. The algorithm predicts the correct DNA sequence when at least two hydrogen bonds per base pair are involved in binding to the protein, providing a partial solution to the three-dimensional docking problem. This study lays a framework for future refinements of the algorithm in which the number of assumptions made in the present analysis are reduced. © 1996 by John Wiley & Sons, Inc.     

A QXP-based multistep docking procedure for accurate prediction of protein-ligand complexes

The two great challenges of the docking process are the prediction of ligand poses in a protein binding site and the scoring of the docked poses. Ligands that are composed of extended chains in their molecular structure display the most difficulties, predominantly because of the torsional flexibility. On the basis of the molecular docking program QXP-Flo+0802, we have developed a procedure particularly for ligands with a high degree of rotational freedom that allows the accurate prediction of the orientation and conformation of ligands in protein binding sites. Starting from an initial full Monte Carlo docking experiment, this was achieved by performing a series of successive multistep docking runs using a local Monte Carlo search with a restricted rotational angle, by which the conformational search space is limited. The method was established by using a highly flexible acetylcholinesterase inhibitor and has been applied to a number of challenging protein-ligand complexes known from the literature.     

Scoring function based approach for locating binding sites and understanding recognition mechanism of protein-DNA complexes

Protein-DNA recognition plays an essential role in the regulation of gene expression. Understanding the recognition mechanism of protein-DNA complexes is a challenging task in molecular and computational biology. In this work, a scoring function based approach has been developed for identifying the binding sites and delineating the important residues for binding in protein-DNA complexes. This approach considers both the repulsive interactions and the effect of distance between atoms in protein and DNA. The results showed that positively charged, polar, and aromatic residues are important for binding. These residues influence the formation of electrostatic, hydrogen bonding, and stacking interactions. Our observation has been verified with experimental binding specificity of protein-DNA complexes and found to be in good agreement with experiments. The comparison of protein-RNA and protein-DNA complexes reveals that the contribution of phosphate atoms in DNA is twice as large as in protein-RNA complexes. Furthermore, we observed that the positively charged, polar, and aromatic residues serve as hotspot residues in protein-RNA complexes, whereas other residues also altered the binding specificity in protein-DNA complexes. Based on the results obtained in the present study and related reports, a plausible mechanism has been proposed for the recognition of protein-DNA complexes.     

Structural,spectroscopic, molecular docking,thermal and DFT studies on metal complexes of bidentate orthoquinone ligand

4‐Triphenylmethyl‐1,2‐benzoquinone (TPMBQ) reacted with some metal ions and the structure of the new compounds had been identified. The metal to ligand ratio was 1:2 which was revealed by elemental analysis. The complexes were found to have octahedral geometry and their thermal stability was studied using thermogravimetric analysis technique. The molar conductance measurements revealed the electrolytic nature of the synthesized chelates. The IR spectra concluded the bidentate nature of the TPMBQ ligand while the ¹H NMR revealed the presence of water molecules. The XRD spectra of Mn (II) and Fe (III) complexes concluded their crystalline structure while Co (II) and Cu (II) chelates refer to amorphous structures. The geometries of the TPMBQ ligand were optimized using Gaussian 09 W; density functional theory B3LYP method. (DFT)/basis set 6–311++G (d, p). HOMO and LUMO energy values for chelates, chemical hardness and electro‐negativity had been calculated. The ligand and its metal complexes had been examined against different kinds of bacteria such as Proteus vulgaris, Escherichia coli, Staphylococcus aurous and Bacillus subtitles to examine their antimicrobial activity. Molecular docking using Auto Dock tools were utilized.     

How proteins get in touch: interface prediction in the study of biomolecular complexes

Protein-protein interface prediction is a booming field, with a substantial growth in the number of new methods being published the last two years. The increasing number of available three-dimensional structures of protein-protein complexes has enabled large-scale statistical analyses of protein interfaces, considering evolutionary, physicochemical and structural properties. Successful combinations of these properties have led to more accurate interface predictors in recent years. In addition to parametric combination, machine learning algorithms have become popular. In the meantime, assessing the absolute and relative performance of interface predictors remains very difficult: This is due to differences in both the output of the various interface predictors, and in the evaluation criteria used by their respective authors. This review provides an overview of the state of the art in the field, and discusses the performance of existing interface predictors. The focus is mainly on protein-protein interface prediction, although most issues are also valid for other kinds of interface prediction.     

Advantages and drawbacks of nanospray for studying noncovalent protein-DNA complexes by mass spectrometry

The noncovalent complexes between the BlaI protein dimer (wild-type and GM2 mutant) and its double-stranded DNA operator were studied by nanospray mass spectrometry and tandem mass spectrometry (MS/MS). Reproducibility problems in the nanospray single-stage mass spectra are emphasized. The relative intensities depend greatly on the shape of the capillary tip and on the capillary-cone distance. This results in difficulties in assessing the relative stabilities of the complexes simply from MS(1) spectra of protein-DNA mixtures. Competition experiments using MS/MS are a better approach to determine relative binding affinities. A competition between histidine-tagged BlaIWT (BlaIWTHis) and the GM2 mutant revealed that the two proteins have similar affinities for the DNA operator, and that they co-dimerize to form heterocomplexes. The low sample consumption of nanospray allows MS/MS spectra to be recorded at different collision energies for different charge states with 1 microL of sample. The MS/MS experiments on the dimers reveal that the GM2 dimer is more kinetically stable in the gas phase than the wild-type dimer. The MS/MS experiments on the complexes shows that the two proteins require the same collision energy to dissociate from the complex. This indicates that the rate-limiting step in the monomer loss from the protein-DNA complex arises from the breaking of the protein-DNA interface rather than the protein-protein interface. The dissociation of the protein-DNA complex proceeds by the loss of a highly charged monomer (carrying about two-thirds of the total charge and one-third of the total mass). MS/MS experiments on a heterocomplex also show that the two proteins BlaIWTHis and BlaIGM2 have slightly different charge distributions in the fragments. This emphasizes the need for better understanding the dissociation mechanisms of biomolecular complexes.     

Structural models in the assessment of protein druggability based on HTS data

Insights on the potential of target proteins to bind small molecules with high affinity can be derived from the knowledge of their three-dimensional structural details especially of their binding pockets. The present study uses high-throughput screening (HTS) results on various targets, to obtain mathematical predictive models in which a minimal set of structural parameters significantly contributing to the hit rates or the affinity of the protein binding pockets for small molecular entities, is identified. An emphasis is given to focus on target variation aspect of the data by consideration of commonly tested compounds against the HTS targets. We identify ‘four-parameter’ models with R ², , SEE, and LOO q ² values of 0.70, 0.60, 0.27 and 0.50, respectively, or better. We demonstrate through cross-validation exercises that our regression models apply well on varied data sets. Thus we can use these models to estimate hit rates for HTS campaigns and thereby assign priority to drug targets before they undergo such resource intense experimental screening and follow-up.

Evaluation of artificial intelligence based models for chemical biodegradability prediction

This study presents a review of biodegradability modeling efforts including a detailed assessment of two models developed using an artificial intelligence based methodology. Validation results for these models using an independent, quality reviewed database, demonstrate that the models perform well when compared to another commonly used biodegradability model, against the same data. The ability of models induced by an artificial intelligence methodology to accommodate complex interactions in detailed systems, and the demonstrated reliability of the approach evaluated by this study, indicate that the methodology may have application in broadening the scope of biodegradability models. Given adequate data for biodegradability of chemicals under environmental conditions, this may allow for the development of future models that include such things as surface interface impacts on biodegradability for example.     

Linear models for prediction of ibuprofen crystal morphology based on hydrogen bonding propensities

Solvents have a significant impact on the final crystal form of organic solids during solution crystallization. The use of polarity scales such as Hildebrand solubility parameter and dielectric constant for solvent selection often proves too generalized and do not provide enough insights into the solvent–solute intermolecular interactions directly affecting crystal growth and morphology. This paper addresses the challenging task of selecting an appropriate single component solvent property index that most accurately and sufficiently characterizes crystal morphology. Cooling crystallization experiments were carried out in a wide range of solvents using ibuprofen as a model pharmaceutical compound. Subsequently, optical microscope images were used for quantitative characterization of morphology. Linear models that correlate ibuprofen crystal morphology with pure solvent properties were developed. Our results show that, in general, there is a negative linear correlation between crystal aspect ratio (morphology) and a given solvent index. Some correlations revealed significant deviations which were explained with the help of infrared spectroscopic measurements. The “acceptance number” was identified as an index that significantly captures the ibuprofen–solvent hydrogen bonding intermolecular interactions. Predictions, using model based on acceptance number, were found to compare very well with experimentally determined aspect ratio data from the open literature. Finally, based on insights gained from this work, a flowchart which serves as a useful solvent selection guideline for crystallization of ibuprofen is proposed.     

A virtual screening approach for thymidine monophosphate kinase inhibitors as antitubercular agents based on docking and pharmacophore models

Docking and pharmacophore screening tools were used to examine the binding of ligands in the active site of thymidine monophosphate kinase of Mycobacterium tuberculosis. Docking analysis of deoxythymidine monophosphate (dTMP) analogues suggests the role of hydrogen bonding and other weak interactions in enzyme selectivity. Water-mediated hydrogen-bond networks and a halogen-bond interaction seem to stabilize the molecular recognition. A pharmacophore model was developed using 20 dTMP analogues. The pharmacophoric features were complementary to the active site residues involved in the ligand recognition. On the basis of these studies, a composite screening model that combines the features from both the docking analysis and the pharmacophore model was developed. The composite model was validated by screening a database spiked with 47 known inhibitors. The model picked up 42 of these, giving an enrichment factor of 17. The validated model was used to successfully screen an in-house database of about 500,000 compounds. Subsequent screening with other filters gave 186 hit molecules.     

Structural variety of zinc and copper complexes based on a 2,3-disubstituted 1,2,3,4-tetrahydroquinazoline ligand

The ring-chain tautomerism of 2-(3-tosyl-1,2,3,4-tetrahydroquinazolin-2-yl)quinolin-8-ol (H(2)L(ring)) has been exploited to produce mononuclear complexes or, alternatively, dinuclear complexes, as desired, by varying the stoichiometry of the ligand. Cu(2+) and Zn(2+) stabilise the ring tautomeric form of the ligand in their mononuclear complexes M(HL(ring))(2). The structural characterisation of Zn(HL(ring))(2)·2MeOH·0.5H(2)O shows O,N-donor behaviour of the ring tautomer. The 1,2,3,4-tetrahydroquinazoline undergoes a ring-opening reaction upon formation of phenoxo-bridged dinuclear complexes M(2)(L(chain))(2) in which the chain tautomer is acting as O,N,N,N-donor. The crystal structure of Cu(2)(L(amide))(L(quinazoline))(MeOH)·2MeOH evidenced the sensitivity of H(2)L(ring) to the copper-mediated aerobic oxidation, which results in two derivatives of the ligand, a quinazoline and an amide. The quinazoline ligand is acting as monoanionic and mononucleating through its O,N,N binding site, while the amide ligand behaves as a trianionic and binucleating through its O,N,N,N and O,O binding sites in Cu(2)(L(amide))(L(quinazoline))(MeOH)·2MeOH.     

Platination of nucleobases to enhance noncovalent recognition in protein-DNA/RNA complexes

Fluorescence quenching experiments show that the stacking interaction between nucleic acid bases and l-tryptophan is enhanced significantly upon base coordination to a metal center such as Pt(II), and the biological implications of such enhancement are discussed.     

基于三联吡啶-4-羧酸的系列配合物的结构多样性和发光性质（英文）

在溶剂热条件下制备了系列新配合物：[Cr₂(tpc)₂(HCOO)₂(OH)₂]·4H₂O (1)、[Ba(tpc)₂(H₂O)₂]_n (2)、[Zn₂(tpc)₂(NO₃)₂]_n (3)、[Pb(Htpc)(NO₃)₂]·2H₂O (4)和[Rh(Htpc)Cl₃]·CH₃OH·H₂O (5)(Htpc=2,2′∶6,2″-三联吡啶-4-羧酸)。X射线单晶衍射分析表明,有机配体呈4种不同的配位方式;配合物1～5通过C—H…O/N氢键和π…π相互作用形成了新颖的超分子网络。研究了这些配合物的发光性能。在365 nm紫外辐射下,晶体2～5分别呈现绿色、蓝色...     

基于三联吡啶-4-羧酸的系列配合物的结构多样性和发光性质

在溶剂热条件下制备了系列新配合物：[Cr₂(tpc)₂(HCOO)₂(OH)₂] ·4H₂O (1)、[Ba(tpc)₂(H₂O)₂]_n (2)、[Zn₂(tpc)₂(NO₃)₂]_n (3)、[Pb(Htpc)(NO₃)₂]·2H₂O (₄)和[Rh(Htpc)Cl₃]·CH₃OH·H₂O (5)(Htpc=2,2''∶6,2″-三联吡啶-4-羧酸)。X射线单晶衍射分析表明,有机配体呈4种不同的配位方式;配合物1~5通过C—H…O/N氢键和π…π相互作用形成了新颖的超分子网络。研究了这些配合物的发光性能。在365 nm紫外辐射下,晶体2~5分别呈现绿色、蓝色、蓝紫色和金色。     

Structural studies on platinum alkene complexes and precursors

A number of platinum complexes, precursors to alkene complexes (Pt₂Cl₄(PPh₃)₂ and cis-PtCl₂(CH₃CN)(PPh₃)), alkene complexes (cis-PtCl₂(C₂H₄)(PPh₃), cis-PtCl₂(C₃H₆)(PPh₃) and cis-PtCl₂(1-C₆H₁₂)(PPh₃)), the diamination product of a 1,3-butadiene platinum complex and the 1,2,3,4-tetramethylcyclobutadiene complex resulting from dimerization of 2-butyne have been synthesized, characterized and the structures determined by X-ray diffraction. The ethylene complex, cis-PtCl₂(C₂H₄)(PPh₃), has been a useful reagent for preparing other alkene complexes. Reaction of a bound butadiene complex with diethylamine yielded a diamination product with anti-Markovnikov stereochemistry. An attempt at binding cis-butyne to the metal center resulted in metal-assisted formation of 1,2,3,4-tetramethylcyclobutadiene with previously unreported geometry.     

Quantitative distance information on protein-DNA complexes determined in polyacrylamide gels by fluorescence resonance energy transfer

In polyacrylamide gels, we have quantitatively determined Forster transfer (fluorescense resonance energy transfer, FRET) between two fluorescent dyes attached to DNA in protein-DNA complexes. The donor-dye fluorescein labeled to DNA retains its free mobility in the polyacrylamide gel, however, its fluorescence properties change. The different quantum yield of fluorescein in the gel is found to be independent of the gel concentration and can thus be quantitatively taken into account by a reduced Forster distance R0 of 46 A compared to 50 A in solution. We have determined global structural properties of two proteins binding to double-labeled DNA using a novel gel-based fluorescence resonance energy transfer assay. In polyacrylamide gels we have analyzed the binding of integration host factor (IHF) and the high mobility group protein NHP6a to their substrate DNA. The measured Forster transfer efficiency allows us to deduce information on the overall shape and the DNA bending angle in the complex.     

Deciphering common failures in molecular docking of ligand-protein complexes

Common failures in predicting crystal structures of ligand-protein complexes are investigated for three ligand-protein systems by a combined thermodynamic and kinetic analysis of the binding energy landscapes. Misdocked predictions in ligand-protein docking are classified as `soft' and `hard' failures. While a soft failure arises when the search algorithm is unable to find the global energy minimum corresponding to the crystal structure, a hard failure results from a flaw of the energy function to qualify the crystal structure as the predicted lowest energy conformation in docking simulations. We find that neither the determination of a single structure with the lowest energy nor finding the most common binding mode is sufficient to predict crystal structures of the complexes, which belong to the category of hard failures. In a proposed hierarchical approach, structural similarity clustering of the conformations, generated from equilibrium simulations with the simplified energy function, is followed by energy refinement with the AMBER force field. This protocol, that involves a hierarchy of energy functions, resolves some common failures in ligand-protein docking and detects crystallographic binding modes that were not found during docking simulations.     

Five new cobalt(II) complexes based on indazole derivatives: synthesis,DNA binding and molecular docking study

Five cobalt(II) complexes based on 1H-indazole-3-carboxylic acid (H₂L), [Co(phen)(HL)₂]·2H₂O (1), [Co(5,5′-dimethyl-2,2′-bipy)(HL)₂] (2), [Co(2,2′-bipy)₂(HL)₂]·5H₂O (3), [Co₂(2,9-dimethyl-1,10-phen)₂(L)₂] (4) and [Co₂(6,6′-dimethyl-2,2′-bipy)₂(L)₂]·H₂O (5) (2,2'-bipy = 2,2′-bipyridine, phen = 1,10-phenanthroline), have been synthesized and structurally characterized by elemental analyses, IR and UV-vis spectroscopies and single-crystal X-ray crystallography. The results indicate that 1–3 possess mononuclear Co(II) structures, while 4 and 5 exhibit binuclear structure. 1D water tape which is linked by the multiple hydrogen bonds was embedded in the 3D motif of complex 3. Complexes 4 and 5 show two orthogonal planes of motif that was constituted by phen/2,2′-bipy and indazole acid, respectively. The intermolecular interactions including hydrogen bonding and π-π stacking interactions are stabilizing these complexes. The interactions of the synthesized complexes with calf-thymus DNA (CT-DNA) have been investigated by UV-vis absorption titration, ethidium bromide displacement assay and viscosity measurements. The results reveal that the complexes could interact with CT-DNA via a groove binding mode. Their behavior rationalization was further theoretically studied by molecular docking.