Ri-Bo Huang

Guangxi Academy of Sciences, Yung-ning, Guangxi Zhuangzu Zizhiqu, China

Are you Ri-Bo Huang?

Claim your profile

Publications (46)120.81 Total impact

  • Source
    Neng-Zhong Xie · Qi-Shi Du · Jian-Xiu Li · Ri-Bo Huang
    [Show abstract] [Hide abstract]
    ABSTRACT: Objectives: Three strong interactions between amino acid side chains (salt bridge, cation-π, and amide bridge) are studied that are stronger than (or comparable to) the common hydrogen bond interactions, and play important roles in protein-protein interactions. Methods: Quantum chemical methods MP2 and CCSD(T) are used in calculations of interaction energies and structural optimizations. Results: The energies of three types of amino acid side chain interactions in gaseous phase and in aqueous solutions are calculated using high level quantum chemical methods and basis sets. Typical examples of amino acid salt bridge, cation-π, and amide bridge interactions are analyzed, including the inhibitor design targeting neuraminidase (NA) enzyme of influenza A virus, and the ligand binding interactions in the HCV p7 ion channel. The inhibition mechanism of the M2 proton channel in the influenza A virus is analyzed based on strong amino acid interactions. Conclusion: (1) The salt bridge interactions between acidic amino acids (Glu- and Asp-) and alkaline amino acids (Arg+, Lys+ and His+) are the strongest residue-residue interactions. However, this type of interaction may be weakened by solvation effects and broken by lower pH conditions. (2) The cation- interactions between protonated amino acids (Arg+, Lys+ and His+) and aromatic amino acids (Phe, Tyr, Trp and His) are 2.5 to 5-fold stronger than common hydrogen bond interactions and are less affected by the solvation environment. (3) The amide bridge interactions between the two amide-containing amino acids (Asn and Gln) are three times stronger than hydrogen bond interactions, which are less influenced by the pH of the solution. (4) Ten of the twenty natural amino acids are involved in salt bridge, or cation-, or amide bridge interactions that often play important roles in protein-protein, protein-peptide, protein-ligand, and protein-DNA interactions.
    PLoS ONE 09/2015; 10(9):e0137113. DOI:10.1371/journal.pone.0137113 · 3.23 Impact Factor
  • Sugar Tech 08/2015; DOI:10.1007/s12355-015-0401-2 · 0.58 Impact Factor
  • Guo-Ping Zhou · Dong Chen · Siming Liao · Liang Sun · Ri-Bo Huang
    [Show abstract] [Hide abstract]
    ABSTRACT: All residues in an alpha helix can be characterized and dispositioned on a 2D the wenxiang diagram, which possesses the following features: (1) the relative locations of the amino acids in the α-helix can be clearly displayed regardless how long it is; (2) direction of an alpha-helix can be indicated; and (3) more information regarding each of the constituent amino acid residues in an alpha helix. Owing to its intuitionism and easy visibility, wenxiang diagrams have had an immense influence on our understanding of protein structure, protein-protein interactions, and the effect of helical structural stability on protein conformational transitions. In this review, we summarize two recent applications of wenxiang diagrams incorporating NMR spectroscopy in the researches of the coiled-coil protein interactions related to the regulation of contraction or relaxation states of vascular smooth muscle cells, and the effects of α-helical stability on the protein misfolding in prion disease, in hopes that the gained valuable information through these studies can stimulate more and more widely applications of wenxiang diagrams in structural biology.
    Current topics in medicinal chemistry 08/2015; · 3.40 Impact Factor
  • Qi-Shi Du · Neng-Zhong Xie · Ri-Bo Huang
    [Show abstract] [Hide abstract]
    ABSTRACT: Due to the low toxicity, easy synthesis, rapid elimination, and less side effect, more and more peptide inhibitors are emerging as the effective drugs that are clinically used in therapies of a number of diseases. At the same time the computer-aided drug design (CADD) methods have remarkably developed. In this mini review the newly developed peptide inhibitors and drugs are introduced, including peptide vaccines for cancers, peptide inhibitors for HIV, Alzheimer's disease and related diseases, and the peptides as the leading compounds of drugs. The recent progress in the theory and methodology of peptide inhibitor design is reviewed. (1) The flexible protein-peptide docking model is introduced, in which the peptide structures are treated as segment-flexible chains using genetic algorithm and special force field parameters. (2) The "Wenxiang diagram" is illustrated for protein-peptide interaction analysis that has been successfully used in the coiled-coil interaction analysis. (3) The "Distorted key" theory is reviewed, which is an effective method to convert the peptide inhibitors to the small chemical drugs. (4) The amino acid property-based peptide prediction method (AABPP) is described that is a two-level QSAR prediction network for the bioactivity prediction of peptide inhibitors. (5) Finally, several types of molecular interactions between protein and peptide ligands are summarized, including cation- interactions; polar hydrogen- interactions; and - stocking interactions.
    Medicinal Chemistry 12/2014; 11(3). DOI:10.2174/1573406411666141229163355 · 1.36 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We present here the first genome sequence of a species in the genus Tumebacillus. The draft genome sequence of Tumebacillus flagellatus GST4 provides a genetic basis for future studies addressing the origins, evolution, and ecological role of Tumebacillus organisms, as well as a source of acid-resistant amylase-encoding genes for further studies. FOOTNOTES Address correspondence to Neng-Zhong Xie, xienengzhong{at}hotmail.com, or Ri-Bo Huang, rbhuang{at}gxas.ac.cn. Citation Wang Q-Y, Xie N-Z, Huang Y-Y, Song L-F, Du Q-S, Yu B, Chen D, Huang R-B. 2014. Genome sequence of Tumebacillus flagellatus GST4, the first genome sequence of a species in the genus Tumebacillus. Genome Announc. 2(6):e01189-14. doi:10.1128/genomeA.01189-14. Received 4 October 2014. Accepted 8 October 2014. Published 13 November 2014. Copyright © 2014 Wang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported license.
    Genome Announcements 11/2014; 2(6). DOI:10.1128/genomeA.01189-14
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Abstract Although not being classified as the most fundamental protein structural elements like α-helices and β-strands, the loop segment may play considerable roles for protein stability, flexibility, and dynamic activity. Meanwhile, the protein loop is also quite elusive; i.e., its interactions with the other parts of protein as well as its own shape-maintaining forces have still remained as a puzzle or at least not quite clear yet. Here we report a molecular force, the so-called polar hydrogen-π interaction (Hp-π), which may play an important role in supporting the backbones of protein loops. By conducting the potential energy surface scanning calculations on the quasi π-plane of peptide bond unit, we have observed the following intriguing phenomena: (1) when the polar hydrogen atom of a peptide unit is perpendicularly pointing to the π-plane of other peptide bond units, a remarkable Hp-π interaction occurs; (2) the interaction is distance- and orientation-dependent, acting in a broad space, and belonging to the "point-to-plane" one. The molecular force reported here may provide useful interaction concepts and insights for better understanding the loop's unique stability and flexibility feature, as well as the driving force of the protein global folding.
    Journal of biomolecular Structure & Dynamics 11/2014; 33(9):1-31. DOI:10.1080/07391102.2014.984333 · 2.92 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Paenibacillus polymyxa DSM 365, an efficient producer of (R,R)-2,3-butanediol, is known to show the highest production titer and productivity reported to date. Here, the first draft genome sequence of this promising strain may provide the genetic basis for further insights into the molecular mechanisms underlying the production of (R,R)-2,3-butanediol with high optical purity and at a high titer. It will also facilitate the design of rational strategies for further strain improvements, as well as construction of artificial biosynthetic pathways through synthetic biology for asymmetric synthesis of chiral 2,3-butanediol or acetoin in common microbial hosts.
    Journal of Biotechnology 11/2014; 195. DOI:10.1016/j.jbiotec.2014.07.441 · 2.87 Impact Factor
  • Guo-Ping Zhou · Ri-Bo Huang · Frederic A Troy
    [Show abstract] [Hide abstract]
    ABSTRACT: Synthesis of 2,8-polysialic acid (polySia) glycans are catalyzed by two highly homologous mammalian polysialyltransferases (polySTs), ST8Sia II (STX) and ST8Sia IV (PST), which are two members of the ST8Sia gene family of sialytransferases. During polysialylation, both STX and PST catalyze the transfer of multiple Sia residues from the activated sugar nucleotide precursor, CMP-Neu5Ac (Sia), to terminal Sia residues on N- and O-linked oligosaccharide chains on acceptor glycoproteins e.g. the neural cell adhesion molecule (NCAM), which is the major carrier protein of polySia. Based on our new findings and previously published studies, this review summarizes the current knowledge regarding the molecular mechanism underlying regulation of protein-specific polysialylation of NCAM that includes the following: (1) Determination of the catalytic domains and specific regions within ST8Sia IV for recognizing and catalyzing the efficient polysialylation of NCAM; (2) Identification of key amino acid residues within the PSTD motif of ST8Sia IV that are essential for polysialylation; (3) Verification of key amino acids in the PBR domain of ST8Sia IV required for NCAM-specific polysialylation; and (4) a 3D conformational study of ST8Sia IV based on the Phyre2 server to discover the relationship between the structure and its functional domains of the polyST. Based on these results, our 3D model of ST8Sia IV was used to identify and characterize the catalytic domains and amino acid residues critical for catalyzing polysialylation, providing new structural information for revealing a detailed mechanism of polyST-NCAM interaction required for polysialylation of NCAM, findings that have not been previously reported.
    Protein and Peptide Letters 10/2014; 22(2). DOI:10.2174/0929866521666141019192221 · 1.07 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: cis,cis-Muconic acid (CCMA) is used as a platform chemical for the production of several high-value compounds. For this article, an optimization strategy has been used to optimize medium composition for CCMA production from fairly cheap benzoate by Pseudomonas sp. 1167. The effect of different concentrations of medium components on CCMA production was studied. CCMA yields obtained from Plackett-Burman design (PBD) showed wide variation (3.95-5.87 g/L), and the first-order model indicated that (NH4)2SO4 (P < 0.01) and K2HPO4 · 3H2O (P < 0.02) were the significant components for CCMA production. Then the optimization was performed by steepest ascent design (SAD) and central composite design (CCD), and a validation experiment was conducted to verify the predicted value. The optimal medium composition was: 12 g/L sodium benzoate, 2.5 g/L sodium succinate, 0.7932 g/L (NH4)2SO4, 1.5612 g/L K2HPO4 · 3H2O, 1.2 g/L MgSO4 · 7H2O, 0.4 g/L yeast extract, 0.08 g/L FeCl3 · 6H2O, and 0.08 g/L ethylenediamine tetraacetic acid (EDTA). Under these conditions, a maximum of 7.18 g/L CCMA was produced per 12 g/L benzoate with a highly efficient process within 11 hr and a molecular conversion yield of 61%. Altogether, our results provide valuable insights into nutritional supplementation of CCMA production by using statistical methods, which may benefit a cost-competitive industrial fed-batch fermentation process using a cheap substrate.
    Preparative Biochemistry &amp Biotechnology 05/2014; 44(4):342-54. DOI:10.1080/10826068.2013.829497 · 0.91 Impact Factor
  • Neng-Zhong Xie · Hong Liang · Ri-Bo Huang · Ping Xu
    [Show abstract] [Hide abstract]
    ABSTRACT: Muconic acid (MA), a high value-added bio-product with reactive dicarboxylic groups and conjugated double bonds, has garnered increasing interest owing to its potential applications in the manufacture of new functional resins, bio-plastics, food additives, agrochemicals, and pharmaceuticals. At the very least, MA can be used to produce commercially important bulk chemicals such as adipic acid, terephthalic acid and trimellitic acid. Recently, great progress has been made in the development of biotechnological routes for MA production. This present review provides a comprehensive and systematic overview of recent advances and challenges in biotechnological production of MA. Various biological methods are summarized and compared, and their constraints and possible solutions are also described. Finally, the future prospects are discussed with respect to the current state, challenges, and trends in this field, and guidelines for developing high-performance microbial cell factories for MA production by systems metabolic engineering are also proposed.
    Biotechnology advances 04/2014; 32(3). DOI:10.1016/j.biotechadv.2014.04.001 · 9.02 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The recently solved solution structure of HCV (hepatitis C virus) p7 ion channel provides a solid structure basis for drug design against HCV infection. In the p7 channel the ligand amantadine (or rimantadine) was determined in a hydrophobic pocket. However the pharmocophore (-NH2) of the ligand was not assigned a specific binding site. The possible binding sites for amino group of adamantane derivatives is studied based on the NMR structure of p7 channel using QM calculation and molecular modeling. In the hydrophobic cavity and nearby three possible binding sites are proposed: His17, Phe20, and Trp21. The ligand binding energies at the three binding sites are studied using high level QM method CCSD(T)/6-311+G(d,p) and AutoDock calculations, and the interaction details are analyzed. The potential application of the binding sites for rational inhibitor design are discussed. Some useful viewpoints are concluded as follows. (1) The amino group (-NH2) of adamantane derivatives is protonated (-NH3+), and the positively charged cation may form cation-π interactions with aromatic amino acids. (2) The aromatic amino acids (His17, Phe20, and Trp21) are the possible binding sites for the protonated amino group (-NH3+) of adamantane derivatives, and the cation-π bond energies are 3 to 5 times stronger than the energies of common hydrogen bonds. (3) The higher inhibition potent of rimantadine than amantadine probably because of its higher pKa value (pKa = 10.40) and the higher positive charge in the amino group. The potential application of p7 channel structure for inhibitor design is discussed.
    PLoS ONE 04/2014; 9(4):e93613. DOI:10.1371/journal.pone.0093613 · 3.23 Impact Factor
  • Source
    Qi-Shi Du · Qing-Yan Wang · Li-Qin Du · Dong Chen · Ri-Bo Huang
    [Show abstract] [Hide abstract]
    ABSTRACT: Background In the study of biomolecular structures and interactions the polar hydrogen-π bonds (Hp-π) are an extensive molecular interaction type. In proteins 11 of 20 natural amino acids and in DNA (or RNA) all four nucleic acids are involved in this type interaction. Results The Hp-π in proteins are studied using high level QM method CCSD/6-311 + G(d,p) + H-Bq (ghost hydrogen basis functions) in vacuum and in solutions (water, acetonitrile, and cyclohexane). Three quantum chemical methods (B3LYP, CCSD, and CCSD(T)) and three basis sets (6-311 + G(d,p), TZVP, and cc-pVTZ) are compared. The Hp-π donors include R2NH, RNH2, ROH, and C6H5OH; and the acceptors are aromatic amino acids, peptide bond unit, and small conjugate π-groups. The Hp-π interaction energies of four amino acid pairs (Ser-Phe, Lys-Phe, His-Phe, and Tyr-Phe) are quantitatively calculated. Conclusions Five conclusion points are abstracted from the calculation results. (1) The common DFT method B3LYP fails in describing the Hp-π interactions. On the other hand, CCSD/6-311 + G(d,p) plus ghost atom H-Bq can yield better results, very close to the state-of-the-art method CCSD(T)/cc-pVTZ. (2) The Hp-π interactions are point to π-plane interactions, possessing much more interaction conformations and broader energy range than other interaction types, such as common hydrogen bond and electrostatic interactions. (3) In proteins the Hp-π interaction energies are in the range 10 to 30 kJ/mol, comparable or even larger than common hydrogen bond interactions. (4) The bond length of Hp-π interactions are in the region from 2.30 to 3.00 Å at the perpendicular direction to the π-plane, much longer than the common hydrogen bonds (~1.9 Å). (5) Like common hydrogen bond interactions, the Hp-π interactions are less affected by solvation effects.
    Chemistry Central Journal 05/2013; 7(1):92. DOI:10.1186/1752-153X-7-92 · 2.19 Impact Factor
  • Guo-Ping Zhou · Ri-Bo Huang
    [Show abstract] [Hide abstract]
    ABSTRACT: Transmissible spongiform encephalopathies (TSEs) are prion protein misfolding diseases that involve the accumulation of an abnormal β-sheet-rich prion protein aggregated form (PrPsc) of the normal α- helix-rich prion protein (PrPc) within the central nervous system (CNS) and other organs. On account of its large size and insolubility properties, characterization of PrPsc is quite difficult. A soluble intermediate, called PrPβ or βo, exhibiting many of the same features as PrPsc, can be generated using a combination of low pH and/or mild denaturing conditions. Here, we review the current knowledge on the following five issues relevant to the conversion mechanisms of PrPc to PrPsc : (1) How is the Stability of the Helical Structures in the Native PrPc Related to the Primary Structure of the PrPc (2) Why the Low pH Solution System is a Ideal Trigger of PrPc to PrPsc Conversion (3) How are the Structural and Dynamical Characteristics of the α-helix-rich Intermediates Determined using NMR Data (4) How are the Premolten (PrPα4 and PrPαβ) and β-Oligomer (PrPβ) Intermediates Detected and Assayed, and (5) Can the Disordered N-terminal Domain be folded into the Structural Segment? Particularly, Chou's wenxiang diagram (http://en.wikipedia.org/wiki/Wenxiang_diagram) was introduced for providing an intuitive picture. This review may help to further understand the prion protein misfolding mechanism.
    Current topics in medicinal chemistry 05/2013; 13(10). DOI:10.2174/15680266113139990003 · 3.40 Impact Factor
  • Qing-Yan Wang · Jian Lu · Si-Ming Liao · Qi-Shi Du · Ri-Bo Huang
    [Show abstract] [Hide abstract]
    ABSTRACT: In drug design and enzyme engineering, the information of interactions between receptors and ligands is crucially important. In many cases, the protein structures and drug-target complex structures are determined by a delicate balance of several weak molecular interaction types. Among these interaction forces several unconventional interactions play important roles, however, less familiar for researchers. The cation-π interaction is a unique noncovalent interaction only acting between aromatic amino acids and organic cations (protonated amino acids) and inorganic cations (proton and metallic). This article reports new study results in the interaction strength, the behaviors and the structural characters of cation-π interactions between aromatic amino acids (Phe, Tyr, and Trp) and organic and inorganic cations (Lys+, Arg+, H+, H3O+, Li+, Na+, K+, Ca2+, and Zn2+) in gas phase and in solutions (water, acetonitrile, and cyclohexane). Systematical research revealed that the cation-π interactions are point-to-plane (aromatic group) interactions, distance and orientation-dependent, and the interaction energies change in a broad range. In gas phase the cation-π interaction energies between aromatic amino acids (Phe, Tyr, and Trp) and metallic cations (Li+, Na+, K+, Ca2+, and Zn2+) are in the range -12 to -160 kcal/mol, and the interaction energies of protonated amino acids (Arg+ and Lys+) are in the range from -9 to -18 kcal/mol. In solutions the cation-π energies decrease with the dielectric constant ε of solvents. However, in aqueous solution the cation-π energies of H3O+ and protonated amino acids are less affected by solvation effects. The applications of unconventional interaction forces in drug design and in protein engineering are introduced.
    Current topics in medicinal chemistry 05/2013; 13(10). DOI:10.2174/15680266113139990002 · 3.40 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Background Among the 20 natural amino acids histidine is the most active and versatile member that plays the multiple roles in protein interactions, often the key residue in enzyme catalytic reactions. A theoretical and comprehensive study on the structural features and interaction properties of histidine is certainly helpful. Results Four interaction types of histidine are quantitatively calculated, including: (1) Cation-π interactions, in which the histidine acts as the aromatic π-motif in neutral form (His), or plays the cation role in protonated form (His+); (2) π-π stacking interactions between histidine and other aromatic amino acids; (3) Hydrogen-π interactions between histidine and other aromatic amino acids; (4) Coordinate interactions between histidine and metallic cations. The energies of π-π stacking interactions and hydrogen-π interactions are calculated using CCSD/6-31+G(d,p). The energies of cation-π interactions and coordinate interactions are calculated using B3LYP/6-31+G(d,p) method and adjusted by empirical method for dispersion energy. Conclusions The coordinate interactions between histidine and metallic cations are the strongest one acting in broad range, followed by the cation-π, hydrogen-π, and π-π stacking interactions. When the histidine is in neutral form, the cation-π interactions are attractive; when it is protonated (His+), the interactions turn to repulsive. The two protonation forms (and pKa values) of histidine are reversibly switched by the attractive and repulsive cation-π interactions. In proteins the π-π stacking interaction between neutral histidine and aromatic amino acids (Phe, Tyr, Trp) are in the range from -3.0 to -4.0 kcal/mol, significantly larger than the van der Waals energies.
    Chemistry Central Journal 03/2013; 7(1):44. DOI:10.1186/1752-153X-7-44 · 2.19 Impact Factor
  • Qi-Shi Du · Jing Gao · Yu-Tuo Wei · Li-Qin Du · Shu-Qing Wang · Ri-Bo Huang
    [Show abstract] [Hide abstract]
    ABSTRACT: The inhibitions of enzymes (proteins) are determined by the binding interactions between ligands and targeting proteins. However, traditional QSAR (quantitative structure-activity relationship) is a one-side technique, only considering the structures and physicochemical properties of inhibitors. In this study, the structure-based and multiple potential three-dimensional quantitative structure-activity relationship (SB-MP-3D-QSAR) is presented, in which the structural information of host protein is involved in the QSAR calculations. The SB-MP-3D-QSAR actually is a combinational method of docking approach and QSAR technique. Multiple docking calculations are performed first between the host protein and ligand molecules in a training set. In the targeting protein, the functional residues are selected, which make the major contribution to the binding free energy. The binding free energy between ligand and targeting protein is the summation of multiple potential energies, including van der Waals energy, electrostatic energy, hydrophobic energy, and hydrogen-bond energy, and may include nonthermodynamic factors. In the foundational QSAR equation, two sets of weighting coefficients {a(j)} and {b(p)} are assigned to the potential energy terms and to the functional residues, respectively. The two coefficient sets are solved by using iterative double least-squares (IDLS) technique in the training set. Then, the two sets of weighting coefficients are used to predict the bioactivities of inquired ligands. In an application example, the new developed method obtained much better results than that of docking calculations.
    Journal of Chemical Information and Modeling 04/2012; 52(4). DOI:10.1021/ci300066y · 3.74 Impact Factor
  • Qi-Shi Du · Jian-Zong Meng · Si-Ming Liao · Ri-Bo Huang
    [Show abstract] [Hide abstract]
    ABSTRACT: The cation-π interactions occur frequently within or between proteins due to six (Phe, Tyr, Trp, Arg, Lys, and His) of the twenty natural amino acids potentially interacting with metallic cations via these interactions. In this study, quantum chemical calculations and molecular orbital (MO) theory are used to study the energies and properties of cation-π interactions in biological structures. The cation-π interactions of H⁺ and Li⁺ are similar to hydrogen bonds and lithium bonds, respectively, in which the small, naked cations H⁺ and Li⁺ are buried deep within the π-electron density of aromatic molecules, forming stable cation-π bonds that are much stronger than the cation-π interactions of other alkali metal cations. The cation-π interactions of metallic cations with atomic masses greater than that of Li⁺ arise mainly from the coordinate bond comprising empty valence atomic orbitals (AOs) of metallic cations and π-MOs of aromatic molecules, though electrostatic interactions may also contribute to the cation-π interaction. The binding strength of cation-π interactions is determined by the charge and types of AOs in the metallic cations. Cation-π interaction energies are distance- and orientation-dependent; energies decrease with the distance (r) and the orientation angle (θ). In solution, the cation-π energies decrease with the increase of the dielectric constant (ɛ) of the solvent; however, solvation has less influence on the H⁺-π and H₃O⁺-π interactions than on interactions with other cations. The conclusions from this study provide useful theoretical insights into the nature of cation-π interactions and may contribute to the development of better force field parameters for describing the molecular dynamics of cation-π interactions within and between proteins.
    Journal of molecular graphics & modelling 04/2012; 34:38-45. DOI:10.1016/j.jmgm.2011.12.002 · 1.72 Impact Factor
  • Qi-Shi Du · Si-Yu Long · Jian-Zong Meng · Ri-Bo Huang
    [Show abstract] [Hide abstract]
    ABSTRACT: Cation-π interaction is comparable and as important as other main molecular interaction types, such as hydrogen bond, electrostatic interaction, van der Waals interaction, and hydrophobic interaction. Cation-π interactions frequently occur in protein structures, because six (Phe, Tyr, Trp, Arg, Lys, and His) of 20 natural amino acids and all metallic cations could be involved in cation-π interaction. Cation-π interactions arise from complex physicochemical nature and possess unique interaction behaviors, which cannot be modeled and evaluated by existing empirical equations and force field parameters that are widely used in the molecular dynamics. In this study, the authors present an empirical approach for cation-π interaction energy calculations in protein interactions. The accurate cation-π interaction energies of aromatic amino acids (Phe, Tyr, and Try) with protonated amino acids (Arg and Lys) and metallic cations (Li(+), Na(+), K(+), and Ca(2+)) are calculated using B3LYP/6-311+G(d,p) method as the benchmark for the empirical formulization and parameterization. Then, the empirical equations are built and the parameters are optimized based on the benchmark calculations. The cation-π interactions are distance and orientation dependent. Correspondingly, the empirical equations of cation-π interactions are functions of two variables, the distance r and the orientation angle θ. Two types of empirical equations of cation-π interactions are proposed. One is a modified distance and orientation dependent Lennard-Jones equation. The second is a polynomial function of two variables r and θ. The amino acid-based empirical equations and parameters provide simple and useful tools for evaluations of cation-π interaction energies in protein interactions.
    Journal of Computational Chemistry 01/2012; 33(2):153-62. DOI:10.1002/jcc.21951 · 3.59 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The proteins in a family, which perform the similar biological functions, may have very different amino acid composition, but they must share the similar 3D structures, and keep a stable central region. In the conservative structure region similar biological functions are performed by two or three catalytic residues with the collaboration of several functional residues at key positions. Communication signals are conducted in a position network, adjusting the biological functions in the protein family. A computational approach, namely structural position correlation analysis (SPCA), is developed to analyze the correlation relationship between structural segments (or positions). The basic hypothesis of SPCA is that in a protein family the structural conservation is more important than the sequence conservation, and the local structural changes may contain information of biology functional evolution. A standard protein P(0) is defined in a protein family, which consists of the most-frequent amino acids and takes the average structure of the protein family. The foundational variables of SPCA is the structural position displacements between the standard protein P(0) and individual proteins P(i) of the family. The structural positions are organized as segments, which are the stable units in structural displacements of the protein family. The biological function differences of protein members are determined by the position structural displacements of individual protein P(i) to the standard protein P(0). Correlation analysis is used to analyze the communication network among segments. The structural position correlation analysis (SPCA) is able to find the correlation relationship among the structural segments (or positions) in a protein family, which cannot be detected by the amino acid sequence and frequency-based methods. The functional communication network among the structural segments (or positions) in protein family, revealed by SPCA approach, well illustrate the distantly allosteric interactions, and contains valuable information for protein engineering study.
    PLoS ONE 12/2011; 6(12):e28206. DOI:10.1371/journal.pone.0028206 · 3.23 Impact Factor
  • Qi-Shi Du · Ri-Bo Huang
    [Show abstract] [Hide abstract]
    ABSTRACT: For quite a long period of time in history, many intense efforts have been made to determine the 3D (three-dimensional) structure of the M2 proton channel. The reason why the M2 proton channel has attracted so many attentions is because (1) it is the key for really understanding the life cycle of influenza viruses, and (2) it is indispensable for conducting rational drug design against the flu viruses. Recently, the long-sough 3D structures of the M2 proton channels for both influenza A and B viruses were consecutively successfully determined by the high-resolution NMR spectroscopy (Schnell J.R. and Chou, J.J., Nature, 2008, 451: 591-595; Wang, J., Pielak, R.M., McClintock, M.A., and Chou, J.J., Nature Structural & Molecular Biology, 2009,16: 1267-1271). Such a milestone work has provided a solid structural basis for in-depth understanding the action mechanism of the M2 channel and rationally designing effective drugs against influenza viruses. This review is devoted to, with the focus on the M2 proton channel of influenza A, addressing a series of relevant problems, such as how to correctly understand the novel allosteric inhibition mechanism inferred from the NMR structure that is completely different from the traditional view, what the possible impacts are to the previous functional studies in this area, and what kind of new strategy can be stimulated for drug development against influenza.
    Current Protein and Peptide Science 11/2011; 13(3):205-10. DOI:10.2174/138920312800785030 · 3.15 Impact Factor

Publication Stats

664 Citations
120.81 Total Impact Points


  • 2008–2014
    • Guangxi Academy of Sciences
      Yung-ning, Guangxi Zhuangzu Zizhiqu, China
  • 2004–2014
    • Guangxi University
      • • College of Life Science and Technology
      • • Guangxi Key Laboratory of Subtropical Bioresource Conservation and Utilization
      Yung-ning, Guangxi Zhuangzu Zizhiqu, China