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Aprotinin has been used widely in surgery as an anti-bleeding agent but is associated with a number of side effects. We report that textilinin-1, a serine protease inhibitor from Pseudonaja textilis venom with sequence relatedness to aprotinin, is a potent but reversible plasmin inhibitor and has a narrower range of protease inhibition compared to aprotinin. Like aprotinin, textilinin-1 at 5 micromol/l gave almost complete inhibition of tissue plasminogen activator-induced fibrinolysis of whole blood clots. The activated partial thromboplastin time for plasma was markedly increased by aprotinin but unaffected by textilinin-1. In a mouse tail-vein bleeding model, intravenous textilinin-1 and aprotinin caused similar decreases in blood loss but time to haemostasis in the textilinin-treated animals was significantly shorter than in aprotinin-treated mice. Based on these data, textilinin-1 merits further investigation as a therapeutic alternative to aprotinin.

Predicting the bioactivity of peptides and proteins is an important challenge in drug development and protein engineering. In this study we introduce a novel approach, the so-called "physics and chemistry-driven artificial neural network (Phys-Chem ANN)", to deal with such a problem. Unlike the existing ANN approaches, which were designed under the inspiration of biological neural system, the Phys-Chem ANN approach is based on the physical and chemical principles, as well as the structural features of proteins. In the Phys-Chem ANN model the "hidden layers" are no longer virtual "neurons", but real structural units of proteins and peptides. It is a hybridization approach, which combines the linear free energy concept of quantitative structure-activity relationship (QSAR) with the advanced mathematical technique of ANN. The Phys-Chem ANN approach has adopted an iterative and feedback procedure, incorporating both machine-learning and artificial intelligence capabilities. In addition to making more accurate predictions for the bioactivities of proteins and peptides than is possible with the traditional QSAR approach, the Phys-Chem ANN approach can also provide more insights about the relationship between bioactivities and the structures involved than the ANN approach does. As an example of the application of the Phys-Chem ANN approach, a predictive model for the conformational stability of human lysozyme is presented.

In cooperation with the fragment-based design a new drug design method, the so-called "fragment-based quantitative structure-activity relationship" (FB-QSAR) is proposed. The essence of the new method is that the molecular framework in a family of drug candidates are divided into several fragments according to their substitutes being investigated. The bioactivities of molecules are correlated with the physicochemical properties of the molecular fragments through two sets of coefficients in the linear free energy equations. One coefficient set is for the physicochemical properties and the other for the weight factors of the molecular fragments. Meanwhile, an iterative double least square (IDLS) technique is developed to solve the two sets of coefficients in a training data set alternately and iteratively. The IDLS technique is a feedback procedure with machine learning ability. The standard Two-dimensional quantitative structure-activity relationship (2D-QSAR) is a special case, in the FB-QSAR, when the whole molecule is treated as one entity. The FB-QSAR approach can remarkably enhance the predictive power and provide more structural insights into rational drug design. As an example, the FB-QSAR is applied to build a predictive model of neuraminidase inhibitors for drug development against H5N1 influenza virus., ((c) 2008 Wiley Periodicals, Inc.)

The long-sought three-dimensional structure of the M2 proton channel of influenza A virus was successfully determined recently by the high-resolution NMR [J.R. Schnell, J.J. Chou, Structure and mechanism of the M2 proton channel of influenza A virus, Nature 451 (2008) 591-595]. Such a milestone work has provided a solid structural basis for studying drug-resistance problems. However, the action mechanism revealed from the NMR structure is completely different from the traditional view and hence prone to be misinterpreted as "conflicting" with some previous biological functional studies. To clarify this kind of confusion, an in-depth analysis was performed for these functional studies, particularly for the mutations D44N, D44A and N44D on position 44, and the mutations on positions 27-38. The analyzed results have provided not only compelling evidences to further validate the NMR structure but also very useful clues for dealing with the drug-resistance problems and developing new effective drugs against H5N1 avian influenza virus, an impending threat to human beings.

The interaction potential energies of water-water and water-methane in structure-I unit cell of methane hydrate are calculated from 2.1 to 8.0A using density functional theory (DFT) B3LYP/TZVP. The curves of potential energies are corrected for basis set superposition error (BSSE) and dispersion interaction using a 4-term L-J (4,6-8,12) correction equation, which is derived from CCSD(T)/cc-pVTZ calculations of water-water and water-methane molecular pairs, using least squares curve-fitting. The methane hydrate unit cell is a regular water dodecahedron cell consisting of 20 water molecules with a methane molecule in the center. The geometries of water and methane are optimized at CCSD(T)/cc-pVTZ level. The BSSE-corrections are calculated for water-water and water-methane interaction energies as functions of the side length, l, of the dodecahedron cell at B3LYP/TZVP level in the range from 2.1 to 8.0A. The BSSE CP-corrected and dispersion-corrected potential energy surfaces (PES) of water-water and water-methane are useful for molecular dynamics simulation of gas clathrate-hydrates.

This review is to summarize three new QSAR (quantitative structure-activity relationship) methods recently developed in our group and their applications for drug design. Based on more solid theoretical models and advanced mathematical techniques, the conventional QSAR technique has been recast in the following three aspects. (1) In the fragment-based two dimensional QSAR, or abbreviated as FB-QSAR, the molecular structures in a family of drug candidates are divided into several fragments according to the substitutes being investigated. The bioactivities of drug candidates are correlated with physicochemical properties of the molecular fragments through two sets of coefficients: one is for the physicochemical properties and the other for the molecular fragments. (2) In the multiple field three dimensional QSAR, or MF-3D-QSAR, more molecular potential fields are integrated into the comparative molecular field analysis (CoMFA) through two sets of coefficients: one is for the potential fields and the other for the Cartesian three dimensional grid points. (3) In the AABPP (amino acid-based peptide prediction), the bioactivities of peptides or proteins are correlated with the physicochemical properties of all or partial residues of the sequence through two sets of coefficients: one is for the physicochemical properties of amino acids and the other for the weight factors of the residues. Meanwhile, an iterative double least square (IDLS) technique is developed for solving the two sets of coefficients in a training dataset alternately and iteratively. Using the two sets of coefficients, one can predict the bioactivity of a query peptide, protein, or drug candidate. Compared with the old methods, the new QSAR approaches as summarized in this review possess machine learning ability, can remarkably enhance the prediction power, and provide more structural information. Meanwhile, the future challenge and possible development in this area have been briefly addressed as well.

In this study the excess chemical potential of the integral equation theory, 3D-RISM-HNC [Q. Du, Q. Wei, J. Phys. Chem. B 107 (2003) 13463-13470], is visualized in three-dimensional form and localized at interaction sites of solute molecule. Taking the advantage of reference interaction site model (RISM), the calculation equations of chemical excess potential are reformulized according to the solute interaction sites s in molecular space. Consequently the solvation free energy is localized at every interaction site of solute molecule. For visualization of the 3D-RISM-HNC calculation results, the excess chemical potentials are described using radial and three-dimensional diagrams. It is found that the radial diagrams of the excess chemical potentials are more sensitive to the bridge functions than the radial diagrams of solvent site density distributions. The diagrams of average excess chemical potential provide useful information of solute-solvent electrostatic and van der Waals interactions. The local description of solvation free energy at active sites of solute in 3D-RISM-HNC may broaden the application scope of statistical mechanical integral equation theory in solution chemistry and life science.

A new drug design method, the multiple field three-dimensional quantitative structure-activity relationship (MF-3D-QSAR), is proposed. It is a combination and development of classical 2D-QSAR and traditional 3D-QSAR. In addition to the electrostatic and van der Waals potentials, more potential fields (such as lipophilic potential, hydrogen bonding potential, and nonthermodynamic factors) are integrated in the MF-3D-QSAR. Meanwhile, a principal component analysis (PCA) and iterative double least square (IDLS) technique is developed for predicting the bioactivity of query drug candidates. As an example, the MF-3D-QSAR is applied to the design of neuraminidase inhibitor and to prove its predictive power, and some useful findings are obtained for developing drugs against influenza virus., ((c) 2007 Wiley Periodicals, Inc. J Comput Chem, 2008.)

The worldwide spread of H5N1 avian influenza and the increasing reports about its resistance to the existing drugs have made a priority for the development of the new anti-influenza molecules. The crystal structure of H5N1 avian influenza neuraminidase reported recently by Russell et al. [R.J. Russell, L.F. Haire, D.J. Stevens, P.J. Collins, Y. P. Lin, G.M. Blackburn, A.J. Hay, S.J. Gamblin, J.J. Skehel, The structure of H5N1 avian influenza neuraminidase suggests new opportunities for drug design, Nature 443 (2006) 45-49] have provided new opportunities for drug design in this regard. It is revealed through the structure that the active sites of the group-1 neuraminidases, which contain the N1 subtype, have a very different three-dimensional structure from those of group-2 neuraminidases. The key difference is in the 150-loop cavity adjacent to the conserved active site in neuraminidase. Based on these findings and by modifying oseltamivir, six analog inhibitors were proposed as candidates for developing inhibitors against H5N1 virus, particularly against the oseltamivir-resistant H5N1 virus strain.

It has tremendous values for both drug discovery and basic research to develop a solid bioinformatical tool for guiding peptide reagent design. Based on the physical and chemical properties of amino acids, a new strategy for peptide reagent design, the so-called AABPD (amino acid based-peptide design), is proposed. The peptide samples in a training dataset are described by a series of HMLP (heuristic molecular lipophilicity potential) parameters and other physicochemical properties of amino acid residues that form a three-dimensional data matrix where each component is defined by three indexes: the first index refers to the peptide samples, the second to the amino acid positions, and the third to the amino acid parameters. The binding free energy between a peptide ligand and its protein receptor is calculated by a linear free energy equation through the physicochemical parameters, resulting in a set of simultaneous linear equations between the bioactivity of the peptides and the physicochemical properties of amino acids. An iterative double least square technique is developed for the solution of the three-dimensional simultaneous linear equation set to determine the amino acid position coefficients of peptide sequence and the physicochemical parameter coefficients of amino acid residues alternately. The two sets of coefficients thus obtained are used for predicting the bioactivity of other query peptide reagents. Two calculation examples, the peptide substrate specificity of the SARS coronavirus 3C-like proteinase and the affinity prediction for epitope-peptides with Class I MHC molecules are studied by using the peptide reagent design strategy., (Copyright 2007 Wiley Periodicals, Inc.)

A new peptide design strategy, the amino acid-based peptide prediction (AABPP) approach, is applied for predicting the affinity of epitope-peptides with class I MHC molecule HLA-A*0201. The AABPP approach consists of two sets of predictive coefficients. The former is the coefficients for the physicochemical properties of amino acids and the latter is the weight factors for the residue positions in a peptide sequence. An iterative double least square technique is introduced to determine the two sets of coefficients alternately through a benchmark dataset. The coefficients converged through such an iterative process are further used to predict the bioactivities of query peptides. In the AABPP algorithm, the following eight physicochemical properties are used as the descriptors of amino acids: (i) lipophilic indices, (ii) hydrophilic indices, (iii) lipophilic surface area, (iv) hydrophilic surface area, (v) alpha-potency indices, (vi) beta-potency indices, (vii) coil-potency indices and (viii) volume of amino acid side chains. In comparison with the existing methods in this area, a remakable advantage of the current approach is that there is no need to know the exact conformation of a query peptide and its alignment with a template. The two steps are indispensable but cannot always be successfully realized otherwise. It is anticipated that the AABPP approach will become a powerful tool for peptide drug design, or at least play a complemetary role to the existing methods.

It has been reported that plant virus-derived small interfering RNAs (vsiRNAs) originated predominantly from structured single-stranded viral RNA of a positive single-stranded RNA virus replicating in the cytoplasm and from the nuclear stem-loop 35S leader RNA of a double-stranded DNA (dsDNA) virus. Increasing lines of evidence have also shown that hierarchical actions of plant Dicer-like (DCL) proteins are required in the biogenesis process of small RNAs, and DCL4 is the primary producer of vsiRNAs. However, the structures of such single-stranded viral RNA that can be recognized by DCLs remain unknown. In an attempt to determine these structures, we have cloned siRNAs derived from the satellite RNA (satRNA) of Cucumber mosaic virus (CMV-satRNA) and studied the relationship between satRNA-derived siRNAs (satsiRNAs) and satRNA secondary structure. satsiRNAs were confirmed to be derived from single-stranded satRNA and are primarily 21 (64.7%) or 22 (22%) nucleotides (nt) in length. The most frequently cloned positive-strand satsiRNAs were found to derive from novel hairpins that differ from the structure of known DCL substrates, miRNA and siRNA precursors, which are prevalent stem-loop-shaped or dsRNAs. DCL4 was shown to be the primary producer of satsiRNAs. In the absence of DCL4, only 22-nt satsiRNAs were detected. Our results suggest that DCL4 is capable of accessing flexibly structured single-stranded RNA substrates (preferably T-shaped hairpins) to produce satsiRNAs. This result reveals that viral RNA of diverse structures may stimulate antiviral DCL activities in plant cells.

A general and empirical method is proposed for correction of London dispersion and other deficiencies in density functional theory (DFT). This method is based on the existing Lennard-Jones (L-J) equation and van der Waals parameters. The benchmark of energy correction is set as the energy difference between DFT and more accurate methods, for example CCSD(T). The energy correction includes all differences between CCSD(T) and DFT, dispersion energy, configuration interaction, induction interaction, residual correlation, and other effects. The energy correction is expressed as a linear combination of van der Waals potentials of nonbonded atomic pairs. The combination coefficients are determined using a least-squares approach in a training set of molecular pairs. The coefficients then can be used for the energy corrections in DFT calculations in a molecular family. Three correction equations of molecular pair interaction energy, water-water, water-methane, and methane-methane, are derived for methane hydrate simulation. The correction equation of the water-water pair is applied in the DFT calculation of water pentamer, yielding good intermolecular potential energy surfaces (PES), very close to the results of CCSD(T) over the active interaction range from 2.1 Å to 8.0 Å.

Recently Simmons et al. reported a new mechanism for SARS virus entry into target cells, where MDL28170 was identified as an efficient inhibitor of CTSL-meditated substrate cleavage with IC(50) of 2.5 nmol/l. Based on the molecule fingerprint searching method, 11 natural molecules were found in the Traditional Chinese Medicines Database (TCMD). Molecular simulation indicates that the MOL376 (a compound derived from a Chinese medicine herb with the therapeutic efficacy on the human body such as relieving cough, removing the phlegm, and relieving asthma) has not only the highest binding energy with the receptor but also the good match in geometric conformation. It was observed through docking studies that the van der Waals interactions made substantial contributions to the affinity, and that the receptor active pocket was too large for MDL21870 but more suitable for MOL736. Accordingly, MOL736 might possibly become a promising lead compound for CTSL inhibition for SARS therapy.

The spread of highly pathogenic H5N1 influenza virus in many Asian and European countries as well as its drug-resistance have raised serious worldwide concerns. In this paper, the structure-activity relationship between NA (neuraminidase) and its three inhibitors (DANA, zanamivir, and oseltamivir) was investigated. A homology model of H5N1-NA (BAE46950), which is the first reported oseltamivir-resistance virus strain, and the 108 homology-modeled 3D structures of chicken influenza H5N1 NAs downloaded from the website at , formed the molecular structural basis for the drug-resistance study. The multiple sequence and structure alignment for these NAs indicated that 11 functional residues were highly conserved except for AAF02313 with the mutated virus strain. However, the framework residues have remarkable mutations from N9-NA to H5N1-NA, and a few mutated residues were observed in different H5N1-NAs. A partially hydrophobic site S5 (formed by Ala246 and Thr247) in N9-NA is changed to a hydrophilic site (formed by Ala227 and Asn228) in H5N1-NA, while a hydrophilic site S6 (formed by Asn346 and Asn347) in N9-NA was replaced by a hydrophobic site (formed by Ala323 and Tyr324). All these mutations might be the reason for the oseltamivir-resistance by some H5N1 viruses. In order to find the possible drug-resistant H5N1 virus, similarity analysis was performed using the BAE46950 sequence as the benchmark template, and 21 sequences were found from the database of the 108 H5N1 NAs that had over 95% sequence similarity with BAE46950.

Netrins regulate axon path-finding during development, but the underlying mechanisms are not well understood. Here, we provide evidence for the involvement of the unconventional myosin X (Myo X) in netrin-1 function. We find that Myo X interacts with the netrin receptor deleted in colorectal cancer (DCC) and neogenin, a DCC-related protein. Expression of Myo X redistributes DCC to the cell periphery or to the tips of neurites, whereas its silencing prevents DCC distribution in neurites. Moreover, expression of DCC, but not neogenin, stimulates Myo X-mediated formation and elongation of filopodia, suggesting that Myo X function may be differentially regulated by DCC and neogenin. The involvement of Myo X in netrin-1 function was further supported by the effects of inhibiting Myo X function in neurons. Cortical explants derived from mouse embryos expressing a motor-less Myo X exhibit reduced neurite outgrowth in response to netrin-1 and chick commissural neurons expressing the motor-less Myo X, or in which Myo X is silenced using microRNA (miRNA), show impaired axon projection in vivo. Taken together, these results identify a novel role for Myo X in regulating netrin-1 function.

In order to find effective peptide inhibitors against SARS CoV M(pro), an analysis was performed for 11 oligo-peptides that can be cleaved by the SARS coronavirus main protease (CoV M(pro), or 3CL(pro)). Flexible molecular alignments of the 11 cleavable peptides have provided useful insights into the chemical properties of their amino acid residues close to the cleavage site. Moreover, it was found through the ligand-receptor docking studies that of the 11 cleavable peptides, NH2-ATLQ / AIAS-COOH and NH2-ATLQ / AENV-COOH had the highest affinity with SARS CoV M(pro). The two octapeptides were selected as initial templates for further chemical modification to make them become effective inhibitors against the SARS enzyme according to the "distorted key" theory [K. C. Chou, Analytical Biochemistry 233 (1996) 1-14]. The possible chemical modification methods are proposed and examined. The approach developed in this study and the findings thus obtained might stimulate new strategies and provide useful information for drug design against SARS.

Starting from a collection of 1386 druggable compounds obtained from the 3D pharmacophore search, we performed a similarity search to narrow down the scope of docking studies. The template molecule is KZ7088 (Chou et al., 2003, Biochem Biophys Res Commun 308: 148-151). The MDL MACCS keys were used to fingerprint the molecules. The Tanimoto coefficient is taken as the metric to compare fingerprints. If the similarity threshold was 0.8, a set of 50 unique hits and 103 conformers were retrieved as a result of similarity search. The AutoDock 3.011 was used to carry out molecular docking of 50 ligands to their macromolecular protein receptors. Three compounds, i.e., C(28)H(34)O(4)N(7)Cl, C(21)H(36)O(5)N(6), and C(21)H(36)O(5)N(6), were found that may be promising candidates for further investigation. The main feature shared by these three potential inhibitors as well as the information of the involved side chains of SARS Cov Mpro may provide useful insights for the development of potent inhibitors against SARS enzyme.

The highly pathogenic H5N1 influenza virus, which is rapidly mutating and becoming increasingly drug-resistant, was investigated by means of structure-activity relationship between NA (neuraminidase) and three inhibitors, i.e., DANA (2,3-didehydro-2-deoxy-N-acetylneuraminic acid), zanamivir, and oseltamivir. A homology model of the H5N1-NA from the highly pathogenic chicken H5N1 A viruses isolated during the 2003-2004 influenza outbreaks in Japan was built based on the crystal structure of N9-NA complexed with DANA (PDB code: 1F8B). It was found that the traditional constituent residues around the active site of NA family are highly conserved in the H5N1-NA. However, a partially lipophilic pocket composed by Ala248 and Thr249 in N9-NA becomes a hydrophilic pocket because the two residues in the H5N1-NA are replaced by hydrophilic residues Ser227 and Asn228, respectively. On the other hand, two hydrophilic residues Asn347 and Asn348 in the N9-NA are replaced by two lipophilic residues Ala323 and Tyr324 in the H5N1-NA, respectively, leading to the formation of a new lipophilic pocket. This kind of subtle variation not only destroys the original lipophilic environment but also changes the complement interaction between the H5N1-NA and DANA. Such a finding might provide insights into the secret why some of H5N1 strains bear high resistance for existing NA inhibitors, and stimulate new strategies for designing new drugs against these viruses.

The extremely complicated nature of many biological problems makes them bear the features of fuzzy sets, such as with vague, imprecise, noisy, ambiguous, or input-missing information For instance, the current data in classifying protein structural classes are typically a fuzzy set To deal with this kind of problem, the AAPCA (Amino Acid Principal Component Analysis) approach was introduced. In the AAPCA approach the 20-dimensional amino acid composition space is reduced to an orthogonal space with fewer dimensions, and the original base functions are converted into a set of orthogonal and normalized base functions The advantage of such an approach is that it can minimize the random errors and redundant information in protein dataset through a principal component selection, remarkably improving the success rates in predicting protein structural classes It is anticipated that the AAPCA approach can be used to deal with many other classification problems in proteins as well.

Flexible alignment and docking studies were conducted for the three octapeptides, ATLQANEV, AVLQSGFR, and ATLQAIAS, that were cleavable by SARS-CoV Mpro. It has been observed that all pharmacophores of the three peptides overlap very well, and that ATLQANEV binds best with the receptor, followed by AVLQSGFR, and then ATLQAIAS. During the process of docking the octapeptides to the SARS enzyme, the residues of the catalytic dyad, i.e., His-41 and Cys-145 are actively involved in forming the hydrogen bonds, so is the center residue (Gln) of all the three octapeptides. The findings are fully consistent with experimental observations. The present studies suggest that the octapeptides ATLQANEV and ATLQAIAS, like AVLQSGFR, might also be the good starting points for designing potential drugs against SARS.

Heuristic molecular lipophilicity potential (HMLP) is applied in the study of lipophilicity and hydrophilicity of 20 natural amino acids side chains. The HMLP parameters, surface area S(i), lipophilic indices L(i), and hydrophilic indices H(i) of amino acid side chains are derived from lipophilicity potential L(r). The parameters are correlated with the experimental data of phase-transferring free energies of vapor-to-water, vapor-to-cyclohexane, vapor-to-octanol, cyclohexane-to-water, octanol-to-water, and cyclohexane-to-octanol through a linear free energy equation DeltaG(0)(tr,i) = b(0) + b(1)S(i) (+) + b(2)S(i) (-) + b(3)L(i) + b(4)H(i). For all above six phase-transfer free energies, the HMLP parameters of 20 amino acid side chains give good calculation results using linear free energy equation. HMLP is an ab initio quantum chemical approach and a structure-based technique. Except for atomic van der Waals radii, there are no other empirical parameters used. The HMLP has clear physical and chemical meaning and provides useful lipophilic and hydrophilic parameters for the studies of proteins and peptides.

Aim: To report the preliminary result of the HIV inhibitor screening based on cheminformatics tools and the traditional Chinese medicine database., Methods: Database search was carried out with saquinavir molecule as a template, further screening was made with docking. Detailed studies using molecular dynamics simulation of 50 ps and 200 ps were made with respect to a potential leading compound, leucovorin., Results: The leucovorin molecule distinguished from other molecules as a potential drug candidate and is subject to extensive studies. The bonding profile and energy were calculated with MD simulations., Conclusion: Our results could be very helpful when we modify leucovorin or design new inhibitors against HIV.

Since the outbreak of SARS (severe acute respiratory syndrome) in November 2002 in Southern China's Guangdong Province, considerable progress has been made in the development of drugs for SARS therapy. The present mini review is focused on the area of computer-aided drug discovery, i.e., the advances achieved mainly from the approaches of structural bioinformatics, pharmacophore modeling, molecular docking, peptide-cleavage site prediction, and other computational means. It is highlighted that the compounds C(28)H(34)O(4)N(7)Cl, C(21)H(36(O)5)N(6) and C(21)H(36)O(5)N(6) (Wei et al., Amino Acids, 2006, 31: 73-80), as well as KZ7088 (Chou et al. Biochem. Biophys. Res. Commun., 2003, 308: 148-151), a derivative of AG7088, might be the promising candidates for further investigation, and that the octapeptides ATLQAIAS and ATLQAENV, as well as AVLQSGFR, might be converted to effective inhibitors against the SARS enzyme. Meanwhile, how to modify these octapeptides based on the "distorted key" theory to make them become potent inhibitors is explicitly elucidated. Finally, a brief introduction is given for how to use computer-generated graphs to rapidly diagnose SARS coronavirus.

Theoretical and molecular modeling studies have been conducted for understanding the details of how 3-[(2,4-dimethoxy)benzylidene]-anabaseine dihydrochloride (GTS-21) and its metabolism derivatives bind with the receptor of alpha7 nicotinic acetylcholine dimer. Good accordance with experimental results has been achieved. It was found that the van der Waals repulsion makes the dominant contribution to the binding energy. GTS-21 and its metabolites are apparently too large for the binding sites of the alpha7 dimer. To improve the effectiveness of the drug, a possible approach is to reduce its volume while maintaining the presence of the active groups. Our studies, in combination with experimental studies, will lead to a promising basis for practical drug design against Alzheimer's disease.

The cleavage mechanism of severe acute respiratory syndrome (SARS) coronavirus main proteinase (M(pro) or 3CL(pro)) for the octapeptide AVLQSGFR is studied using molecular mechanics (MM) and quantum mechanics (QM). The catalytic dyad His-41 and Cys-145 in the active pocket between domain I and II seem to polarize the pi-electron density of the peptide bond between Gln and Ser in the octapeptide, leading to an increase of positive charge on C(CO) of Gln and negative charge on N(NH) of Ser. The possibility of enhancing the chemical bond between Gln and Ser based on the "distorted key" theory [Anal. Biochem. 233 (1996) 1] is examined. The scissile peptide bond between Gln and Ser is found to be solidified through "hybrid peptide bond" by changing the carbonyl group CO of Gln to CH(2) or CF(2). This leads to a break of the pi-bond system for the peptide bond, making the octapeptide (AVLQSGFR) a "distorted key" and a potential starting system for the design of anti SARS drugs.

Osteoclast activation is important for bone remodeling and is altered in multiple bone disorders. This process requires cell adhesion and extensive actin cytoskeletal reorganization. Proline-rich tyrosine kinase 2 (PYK2), a major cell adhesion-activated tyrosine kinase in osteoclasts, plays an important role in regulating this event. The mechanisms by which PYK2 regulates actin cytoskeletal organization and osteoclastic activation remain largely unknown. In this paper, we provide evidence that PYK2 directly interacts with gelsolin, an actin binding, severing, and capping protein essential for osteoclastic actin cytoskeletal organization. The interaction is mediated via the focal adhesion-targeting domain of PYK2 and an LD motif in gelsolin's COOH terminus. PYK2 phosphorylates gelsolin at tyrosine residues and regulates gelsolin bioactivity, including decreasing gelsolin binding to actin monomer and increasing gelsolin binding to phosphatidylinositol lipids. In addition, PYK2 increases actin polymerization at the fibroblastic cell periphery. Finally, PYK2 interacts with gelsolin in osteoclasts, where PYK2 activation is required for the formation of actin rings. Together, our results suggest that PYK2 is a regulator of gelsolin, revealing a novel PYK2-gelsolin pathway in regulating actin cytoskeletal organization in multiple cells, including osteoclasts.

Focal adhesion kinase (FAK) and proline-rich tyrosine kinase 2 (PYK2) are structurally related tyrosine kinases. They are implicated in regulating actin cytoskeleton organization, a process critical for cell migration, mitosis and tumor metastasis. In this paper, we demonstrate that, although both PYK2 and FAK were expressed and colocalized at focal adhesions in fibroblasts, microinjection of PYK2, but not FAK, in Swiss 3T3 fibroblastic cells led to reorganization of focal adhesions and cell rounding. PYK2-mediated actin cytoskeleton reorganization required the PYK2 N terminus, the focal adhesion targeting (FAT) domain, catalytic activity and autophosphorylation. Remarkably, FAK suppressed PYK2-mediated reorganization of focal adhesions and cell rounding. In addition, FAK inhibited PYK2 autophosphorylation and focal adhesion targeting, which might contribute to FAK-mediated suppression of PYK2's phenotypes. Further analyses demonstrated that the inhibition of PYK2 autophosphorylation required the FAK N terminus but not FAK tyrosine phosphorylation. The FAK FAT domain seemed to be critical for FAK-mediated suppression of PYK2 focal adhesion targeting. Taken together, these results demonstrate that FAK could inhibit PYK2 autophosphorylation, focal adhesion targeting and actin cytoskeleton reorganization, suggesting that the balance between FAK and PYK2 tyrosine kinases is important for regulating cellular morphology, cell migration and cell growth.

Proline-rich tyrosine kinase 2 (PYK2), a tyrosine kinase structurally related to focal adhesion kinase (FAK), is implicated in regulating cytoskeletal organization. However, mechanisms by which PYK2 participates in and regulates cytoskeletal organization remain largely unknown. Here we report identification of PSGAP, a novel protein that interacts with PYK2 and FAK and contains multiple domains including a pleckstrin homology domain, a rhoGTPase-activating protein domain, and a Src homology 3 domain. PYK2 interacts with PSGAP Src homology 3 domain via the carboxyl-terminal proline-rich sequence. PSGAP is able to increase GTPase activity of CDC42 and RhoA in vitro and in vivo. Remarkably, PYK2, but not FAK, can activate CDC42 via inhibition of PSGAP-mediated GTP hydrolysis of CDC42. Moreover, PSGAP is localized at cell periphery in fibroblasts in a pleckstrin homology domain-dependent manner. Over expression of PSGAP in fibroblasts results in reorganization of cytoskeletal structures and changes of cellular morphology, which requires rhoGTPase-activating activity. Taken together, our results suggest that PSGAP is a signaling protein essential for PYK2 regulation of cytoskeletal organization via Rho family GTPases.

Neuregulins (NRGs) and their receptors, the ErbB protein tyrosine kinases, are essential for neuronal development, but their functions in the adult CNS are unknown. We report that ErbB4 is enriched in the postsynaptic density (PSD) and associates with PSD-95. Heterologous expression of PSD-95 enhanced NRG activation of ErbB4 and MAP kinase. Conversely, inhibiting expression of PSD-95 in neurons attenuated NRG-mediated activation of MAP kinase. PSD-95 formed a ternary complex with two molecules of ErbB4, suggesting that PSD-95 facilitates ErbB4 dimerization. Finally, NRG suppressed induction of long-term potentiation in the hippocampal CA1 region without affecting basal synaptic transmission. Thus, NRG signaling may be synaptic and regulated by PSD-95. A role of NRG signaling in the adult CNS may be modulation of synaptic plasticity.