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<font size=5 color=#000066><center><b>Current staff:</b></center></font>
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<a href='/cgi-bin/people/cv.cgi?abagyan'><img src='../images/folder.gif' border=0 align='middle'></a>
<a href=http://abagyan.scripps.edu/ruben.htm><font size=4>Ruben Abagyan</font></a>
, <font size=4>Professor</font>
<p>
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<a href='/cgi-bin/people/cv.cgi?cclaudio'><img src='../images/folder.gif' border=0 align='middle'></a>
<a href=http://><font size=4>Claudio Cavasotto</font></a>
, <font size=4>Research Associate</font>
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<a href='/cgi-bin/people/cv.cgi?jfrecio'><img src='../images/folder.gif' border=0 align='middle'></a>
<a href=http://www.scripps.edu/~jfrecio><font size=4>Juan Fernandez-Recio</font></a>
, <font size=4>Research Associate</font>
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<font size=4>Brian Marsden, Research Associate</font>
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<a href=http://><font size=4>Sheila Silvertein</font></a>
, <font size=4></font>
<p>
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<a href=http://><font size=4>Maxim Totrov</font></a>
<p>
<a name="ruben"></a>
<!-- split><h2>Ruben Abagyan</h2>
<p>
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    <td><img src="images/Ruben.jpg" width="168" height="200" align="left" float="right"></td>
    <td><font color="white"><h1 align="center">Ruben A. Abagyan, Ph.D.</h1>
    <h2 align="center">Professor of Biochemistry and Mathematics</font></h2>
    </td>
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<p>
<p>Dr. Abagyan is a member of the faculty of The Scripps Research Institute since April
1999.</p>
<p>
<a name="ge"></a>
<h3>Graduate Education</h3>
<p> Dr. Abagyan received his Ph.D. in Theoretical Biophysics
from Moscow State University, Moscow, Russia in 1984. </p>
<p>
<a name="pt"></a>
<h3>Postdoctoral Training</h3>
<p> Dr. Abagyan completed his postdoctoral training in the
Laboratory of X-ray Crystallography at the Engelhardt Institute of Molecular Biology, the
USSR Academy of Sciences, Moscow, 1984-1986, at the Laboratory of Plant Genetic
Engineering at the same institute, 1986-1989, and at the Laboratory of Genetic
Engineering, Unviersity of Liege, Belgium, 1989-1990. </p>
<p>
<a name="pr"></a>
<h3>Prior Responsibilities</h3>
<p>Until May, 1994 Dr. Abagyan was a Staff Scientist at the
European Molecular Laboratory in Heidelberg, Germany, and then an Associate Professor of
Biochemistry and Mathematics at NYU. </p>
<p>
<br>
<p>
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<p>
<table border="1" cellpadding="0" cellspacing="0" style="border: 2 double rgb(0,0,0)">
  <tr>
    <td colspan="2"><p align="center"><font size="+1">Contact Information</font></td>
  </tr>
  <tr>
    <td><em>Address:</em></td>
    <td>The Scripps Research Institute, 10550 North Torrey Pines Rd., <br>
    La Jolla, CA 92037&nbsp; Mail TPC-28 </td>
  </tr>
  <tr>
    <td><em>Phone:</em></td>
    <td>(619)784-8595</td>
  </tr>
  <tr>
    <td><em>FAX:</em></td>
    <td>(619)784-8299</td>
  </tr>
  <tr>
    <td><em>Send E-mail to:</em></td>
    <td><a href="mailto:abagyan@scripps.edu">Ruben A. Abagyan, Ph.D.</a></td>
  </tr>
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<p>
<p align="center">[<a href="http://abagyan.scripps.edu">Abagyan Laboratory</a>]&nbsp; [<a
href="publicat.htm">Publications.</a>] </p>
<b><font size="-1">
<p>
<p><a href="http://www.scripps.edu">TSRI</a> , <a href="http://www.scripps.edu/mb">Department
of Molecular Biology</a> </font></b></p></b>
<p>
<a name="Brian"></a>
<!-- split><h2>Brian Mardsen</h2>
Brian's page!
<a name="Brianabs"></a>
<!-- split><h3>Brian's Abstracts</h3>
<p>
Abstracts here
<p>
<a name="BrianPersonal"></a>
<!-- split><h3>Personal Info</h3>
<p>
Brian's <i>personal</i> page!
<p>
<a name="research"></a>
<!-- split><h1>Research</h1>
 Our research can be divided into four major areas.
<p>
<a name="molmod"></a>
<!-- split><h2>Molecular Modeling</h2>
<p>
 Ab initio prediction of polypeptide 3D strictures;
 Loop modeling and design;
 Homology modeling;
 Energy strain in 3D structures;
 Domain motion modeling;
<p>
<a name="energystrain3d"></a>
<!-- split><h3>Energy strain in three-dimensional protein structures</h3>
<p>
<h4>Maiorov, V. and Abagyan, R.A. (1998, in press) </h4>
<p><i>Folding &amp; Design.</i> </p>
    <p align="justify">Steric strain in protein three-dimensional structures is related to
    unfavorable inter-atomic interactions and may be due to packing or functional
    requirements, or indicate an error in a structure's coordinates. Detailed energy functions
    are usually considered too noisy for error detection. After a short energy refinement a
    full-atom, detailed energy function becomes a sensitive indicator of errors. Statistics of
    energy distribution of amino acid residues in high-resolution crystal structures
    represented by models with idealized covalent geometry were calculated. Interaction energy
    of each residue with the whole protein structure and with the solvent was considered.
    Normalized deviations of amino acid residue energies from their average values were used
    for detecting energy-strained and, therefore, potentially incorrect fragments of a
    polypeptide chain. Protein three-dimensional structures of different origin (X-ray
    crystallography, nuclear magnetic resonance spectroscopy, theoretical models and
    deliberately misfolded decoys) were compared. Examples of the applications to loop and
    homology modeling are given. Elevated level of energy strain may point at a problematic
    fragment in a protein three-dimensional structure of either experimental or theoretical
    origin. The approach may be useful in model building and refinement, modeling by homology,
    protein design, folding calculations, and protein structure analysis. </p>
<p>
<a name="crystalstruct1.8a"></a>
<!-- split><h3>The 1.8 A crystal structure of the dimeric peroxisomal 3-ketoacyl-CoA thiolase of Saccharomyces cerevisiae: implications for substrate binding and reaction mechanism.</h3>
<p>
    <h4>M., Modis, Y., Zeelen, J.P., Engel, C.K., Abagyan, R.A., Ahlberg, A., Rasmussen, B.,
    Lamzin, V.S., Kunau, W.H., Wierenga, R.K.</h4>
    <p>The dimeric, peroxisomal 3-ketoacyl-CoA thiolase catalyses the conversion of
    3-ketoacyl-CoA into acyl-CoA, which is shorter by two carbon atoms. This reaction is the
    last step of the beta-oxidation pathway. The crystal structure of unliganded peroxisomal
    thiolase of the yeast Saccharomyces cerevisiae has been refined at 1.8 A resolution. An
    unusual feature of this structure is the presence of two helices, completely buried in the
    dimer and sandwiched between two beta-sheets. The analysis of the structure shows that the
    sequences of these helices are not hydrophobic, but generate two amphipathic helices. The
    helix in the N-terminal domain exposes the polar side-chains to a cavity at the dimer
    interface, filled with structured water molecules. The central helix in the C-terminal
    domain exposes its polar residues to an interior polar pocket. The refined structure has
    also been used to predict the mode of binding of the substrate molecule acetoacetyl-CoA,
    as well as the reaction mechanism. From previous studies it is known that Cys125, His375
    and Cys403 are important catalytic residues. In the proposed model the acetoacetyl group
    fits near the two catalytic cysteine residues, such that the oxygen atoms point towards
    the protein interior. The distance between SG(Cys125) and C3(acetoacetyl-CoA) is 3.7 A.
    The O2 atom of the docked acetoacetyl group makes a hydrogen bond to N(Gly405), which
    would favour the formation of the covalent bond between SG(Cys125) and C3(acetoacetyl-CoA)
    of the intermediate complex of the two-step reaction. The CoA moiety is proposed to bind
    in a groove on the surface of the protein molecule. Most of the interactions of the CoA
    molecule are with atoms of the loop domain. The three phosphate groups of the CoA moiety
    are predicted to interact with side-chains of lysine and arginine residues, which are
    conserved in the dimeric thiolases. Copyright 1997 Academic Press Limited.</p>
    <p><i>Journal of Molecular Biology. 273(3):714-28, 1997 Oct 31.</i></p>
<p>
<a name="mmdsb"></a>
<!-- split><h3>Molecular Modeling of the Domain Shared Between CED-4 and its Mammalian Homologue Apaf-1: A Structural Relationship to the G-proteins.</h3>
<p>
 <h4>Cardozo, T.J., Abagyan, R. (1998) </h4>
    <p><i>J.Mol.Model.</i>, <b>4</b>, 83-93. </p>
    <p align="justify">Apoptosis (programmed cell death, PCD) is a characteristic type of cell
    death in which a regulated cellular response pathway mediated by cysteine proteases of the
    caspase family and Bcl-2 family proteins results in ordered and non-inflammatory
    involution of the cell. The CED-4 protein and its recently identified mammalian homologue
    Apaf-1 are critical but functionally uncharacterized components of the cell death
    machinery. We present here a three-dimensional molecular model for the central domain of
    CED-4, its alternatively spliced transcript (CED-4l) and Apaf-1. A novel protein family is
    identified and structure prediction for the family identifies a G-protein-like fold with
    high reliability. The three-dimensional model provides a potential structural explanation
    for the alternatively spliced variant as well as the known point mutations in CED-4.
    Regions of the CED-4 and Apaf-1 sequences which may interact with caspases and the Bcl-2
    family are proposed. This new information provides a structural molecular framework for
    the interaction of CED-4-like proteins with the caspases and the Bcl-2 family in the
    regulation of apoptosis which is analogous to G-protein mediated interactions in
    well-defined signal transduction pathways. </p>
<p>
<a name="homomodelwicm"></a>
<!-- split><h3>Homology Modeling with Internal Coordinate Mechanics: Deformation Zone Mapping and Improvements of Models via Conformational Search.</h3>
<p>
<h4>Abagyan, R., Batalov, S., Cardozo, T., Totrov, M., Webber, J. and Zhou, Y. (1997) </h4>
    <p>Five models by homology containing insertions and deletions and ranging from 33% to 48%
    sequence identity to the known homologue, and one high sequence identity (85%) model were
    built for the CASP2 meeting. For all five low identity targets: (i) our starting models
    were improved by the Internal Coordinate Mechanics (ICM) energy optimization, (ii) the
    refined models were consistently better than those built with the automatic SWISS-MODEL
    program, and (iii) the refined models differed by less than 2% from the best model
    submitted, as judged by the residue contact area difference (CAD) measure [Abagyan, R.A.,
    Totrov, M.J. Mol. Biol. 268:678-685, 1997]. The CAD measure is proposed for ranking models
    built by homology instead of global root-mean-square deviation, which is frequently
    dominated by insignificant yet large contributions from incorrectly predicted fragments or
    side chains. We demonstrate that the precise identification of regions of local backbone
    deviation is an independent and crucial step in the homology modeling procedure after
    alignment, since aligned fragments can strongly deviate from the template at various
    distances from the alignment gap or even in the ungapped parts of the alignment. We show
    that a local alignment score can be used as an indicator of such local deviation. While
    four short loops of the meeting targets were predicted by database search, the best loop 1
    target T0028, for which the correct database fragment was not found, was predicted by
    Internal Coordinate Mechanics global energy optimization at 1.2 A accuracy. A
    classification scheme for errors in homology modeling is proposed. </p>
    <p><i>Proteins: Struct. Funct. &amp; Gen.</i>, <b>Suppl. 1</b>, 29-37. </p>
<p>
<a name="mappingcd59"></a>
<!-- split><h3>Mapping the active site of CD59</h3>
<p>
<h4>Yu J, Dong S, Rushmere NK, Morgan BP, Abagyan R, Tomlinson S., (1997) <i>Biochemistry</i>
    <b>36</b>, 9423-9428. </h4>
    <p align="justify">CD59 is a widely distributed membrane-bound glycoprotein that inhibits
    the formation of the cytolytic membrane attack complex (MAC) of complement on host cells.
    CD59 from different species varies in its capacity to inhibit heterologous complement, and
    this species selective function of CD59 contributes to the phenomenon of homologous
    restriction. Here, we demonstrate that human CD59 is not an effective inhibitor of rat
    complement, although rat CD59 inhibits rat and human complement equally well. By
    constructing human-rat CD59 chimeric proteins, we have mapped the residues important in
    conferring human CD59 species selectivity to two regions; 40-47 and 47-66 in the primary
    structure. Analysis of a model of the molecular surface of human CD59 revealed that
    residues 40-66 mapped to a region in the three-dimensional structure that surrounds
    residues previously identified as important for CD59 function. </p>
<p>

<a name="pewithmonoTIM"></a>
<!-- split><h3>Protein engineering with monomeric triosephosphate isomerase (monoTIM): the modelling and structure verification of a seven residue loop.</h3>
<p>
<h4>M., Modis, Y., Zeelen, J.P., Engel, C.K., Abagyan, R.A., Ahlberg, A., Rasmussen, B.,
    Lamzin, V.S., Kunau, W.H., Wierenga, R.K.</h4>
    <p>The dimeric, peroxisomal 3-ketoacyl-CoA thiolase catalyses the conversion of
    3-ketoacyl-CoA into acyl-CoA, which is shorter by two carbon atoms. This reaction is the
    last step of the beta-oxidation pathway. The crystal structure of unliganded peroxisomal
    thiolase of the yeast Saccharomyces cerevisiae has been refined at 1.8 A resolution. An
    unusual feature of this structure is the presence of two helices, completely buried in the
    dimer and sandwiched between two beta-sheets. The analysis of the structure shows that the
    sequences of these helices are not hydrophobic, but generate two amphipathic helices. The
    helix in the N-terminal domain exposes the polar side-chains to a cavity at the dimer
    interface, filled with structured water molecules. The central helix in the C-terminal
    domain exposes its polar residues to an interior polar pocket. The refined structure has
    also been used to predict the mode of binding of the substrate molecule acetoacetyl-CoA,
    as well as the reaction mechanism. From previous studies it is known that Cys125, His375
    and Cys403 are important catalytic residues. In the proposed model the acetoacetyl group
    fits near the two catalytic cysteine residues, such that the oxygen atoms point towards
    the protein interior. The distance between SG(Cys125) and C3(acetoacetyl-CoA) is 3.7 A.
    The O2 atom of the docked acetoacetyl group makes a hydrogen bond to N(Gly405), which
    would favour the formation of the covalent bond between SG(Cys125) and C3(acetoacetyl-CoA)
    of the intermediate complex of the two-step reaction. The CoA moiety is proposed to bind
    in a groove on the surface of the protein molecule. Most of the interactions of the CoA
    molecule are with atoms of the loop domain. The three phosphate groups of the CoA moiety
    are predicted to interact with side-chains of lysine and arginine residues, which are
    conserved in the dimeric thiolases. Copyright 1997 Academic Press Limited.</p>
    <p><i>Journal of Molecular Biology. 273(3):714-28, 1997 Oct 31.</i></p>
<p>
<a name="rearpd"></a>
<!-- split><h3>A new method for modeling large-scale rearrangements of protein domains</h3>
<p>
<h4>Maiorov, V.N., Abagyan, R.A. (1997) </h4>
    <p><i>Proteins</i>, <b>27</b>, 410-424. </p>
    <p align="justify">A method for modeling large-scale rearrangements of protein domains
    connected by a single- or a double-stranded linker is proposed. Multidomain proteins may
    undergo substantial domain displacements while their intra-domain structure remains
    essentially unchanged. The method allows automatic identification of an inter-domain
    linker and builds an all-atom model of a protein structure in internal coordinates.
    Torsion angles belonging to the inter-domain linkers and side-chains potentially able to
    form domain interfaces are set free while all remaining torsions, bond lengths and bond
    angles are fixed. Large-scale sampling of the reduced torsion conformational subspace is
    effected with the &quot;biased probability Monte Carlo-minimization&quot; method (Abagyan,
    R. A. &amp; Totrov, M. M. (1994) J. Mol. Biol. 235, 983-1002). Solvation and side-chain
    entropic contributions are added to the energy function. A special procedure has been
    developed to generate concerted deformations of a double-stranded inter-domain linker in
    such a way that the polypeptide chain continuity is preserved. The method was tested on
    Bence-Jones protein with a single-stranded linker and lysine/arginine/ornithine-binding
    (LAO) protein with a double-stranded linker. For each protein, structurally diverse low
    energy conformations with ideal covalent geometry were generated, and an overlap between
    two sets of conformations generated starting from the crystallographically determined
    &quot;closed&quot; and &quot;open&quot; forms was found. One of the low energy
    conformations generated in a run starting from the LAO &quot;closed&quot; form was only
    2.2 A away from the structure of the &quot;open&quot; form. The method can be useful in
    predicting the scope of possble domain rearrangements of a multidomain protein. </p>
<p>
<a name="hmbyicm"></a>
<!-- split><h3>Homology modeling by the ICM method</h3>
<p>
<h4>Cardozo, T., Totrov, M.M. &amp; Abagyan, R.A (1995) </h4>
    <p><i>Proteins</i>, <b>23</b>, 403-414. </p>
    <p align="justify">Five models have been built by the ICM method for the Comparative
    Modeling section of the Meeting on the Critical Assessment of Techniques for Protein
    Structure Prediction. The targets have homologous proteins with known three-dimensional
    structure with sequence identity ranging from 25 to 77%. After alignment of the target
    sequence with the related three-dimensional structure, the modeling procedure consists of
    two subproblems: side-chain prediction and loop prediction. The ICM method approaches
    these problems with the following steps: (1) a starting model is created based on the
    homologous structure with the conserved portion fixed and the nonconserved portion having
    standard covalent geometry and free torsion angles; (2) the Biased Probability Monte Carlo
    (BPMC) procedure is applied to search the subspaces of either all the nonconservative
    side-chain torsion angles or torsion angles in a loop backbone and surrounding side
    chains. A special algorithm was designed to generate low-energy loop deformations. The
    BPMC procedure globally optimizes the energy function consisting of ECEPP/3 and solvation
    energy terms. Comparison of the predictions with the NMR or crystallographic solutions
    reveals a high proportion of correctly predicted side chains. The loops were not correctly
    predicted because imprinted distortions of the backbone increased the energy of the
    near-native conformation and thus made the solution unrecognizable. Interestingly, the
    energy terms were found to be reliable and the sampling of conformational space
    sufficient. The implications of this finding for the strategies of future comparative
    modeling are discussed. </p>
<p>
<a name="monoTIMloops"></a>
<!-- split><h3>Three new crystal structures of point mutation variants of monoTIM: conformational flexibility of loop-1, loop-4 and loop-8</h3>
<p>
  <h4>Borchert, T.V., Kishan, K.V., Zeelen, J.P., Schliebs, W., Thanki, N., Abagyan, R.,
    Jaenicke, R. &amp; Wierenga, R.K. (1995) </h4>
    <p><i>Structure</i>, <b>3</b>, 669-679. </p>
    <p align="justify">Wild-type triosephosphate isomerase (TIM) is a very stable dimeric
    enzyme. This dimer can be converted into a stable monomeric protein (monoTIM) by replacing
    the 15-residue interface loop (loop-3) by a shorter, 8-residue, loop. The crystal
    structure of monoTIM shows that two active-site loops (loop-1 and loop-4), which are at
    the dimer interface in wild-type TIM, have acquired different rather different structural
    properties. Nevertheless, monoTIM gas residual catalytic activity.</p>
    <p>Three new structures of variants of monoTIM are presented, a double-point mutant
    crystallized in the presence and absence of bound inhibitor, and a single-point mutant in
    the presence of a different inhibitor. These new structures show large structural
    variability for the active-site loops, loop-1, loop-4 and loop-8. In the structures with
    inhibitor bound, the catalytic lysine (Lys13 in loop-1) and the catalytic histidine (His95
    in loop-4) adopt conformations similar to those observed in wild-type TIM, but very
    different from the monoTIM structure.</p>
    <p>The residual catalytic activity of monoTIM can now be rationalized. In the presence of
    substrate analogues the active-site loops, loop-1, loop-4 and loop-8, as well as the the
    catalytic residues, adopt conformations similar to those seen in the wild-type protein.
    These loops lack conformational flexibility in wild-type TIM. The data suggest that the
    rigidity of these loops in wild-type TIM, resulting from subunit-subunit contacts at the
    dimer interface, is important for optimal catalysis.</p>
<p>
<a name="mti"></a>
<!-- split><h3>Design, creation, and characterization of a stable, monomeric triosephosphate isomerase</h3>
<p>
<h4>Borchert, T.V., Abagyan, R.A., Jaenicke, R., &amp; Wierenga, R.K. (1994) </h4>
    <p><i>Proc. Natl. Acad. Sci USA</i> <b>91</b>, 1515-1518. </p>
    <p align="justify">Protein engineering on trypanosomal triosephosphate isomerase (TIM)
    converted this oligomeric enzyme into a stable, monomeric protein that is enzymatically
    active. Wild-type TIM consists of two identical subunits that form a very tight dimer
    involving interactions of 32 residues of each subunit. By replacing 15 residues of the
    major interface loop by another 8-residue fragment, a variant was constructed that is a
    stable and monomeric protein with TIM activity. The length, sequence, and conformation of
    the designed fragment were suggested by extensive modeling.</p>
<p>
<a name="montecarlo"></a>
<!-- split><h3>Biased probability Monte Carlo conformational searches and electrostatic calculations for peptides and proteins</h3>
<p>
<h4>Abagyan, R.A. &amp; Totrov, M.M. (1994) </h4>
    <p><i>J. Mol. Biol.</i> <b>235</b>, 983-1002. </p>
    <p align="justify">Two major components are required for a successful prediction of the
    three-dimensional structure of peptides and proteins: an efficient global optimization
    procedure which is capable of finding an appropriate local minimum for the strongly
    anisotropic function of hundreds of variables, and a set of free energy components for a
    protein molecule in solution which are computationally inexpensive enough to be used in
    the search procedure, yet sufficiently accurate to ensure the uniqueness of the native
    conformation. We here found an efficient way to make a random step in a Monte Carlo
    procedure given knowledge of the energy or statistical properties of conformational
    subspaces (e.g. phi-psi zones or side-chain torsion angles). This biased probability Monte
    Carlo (BPMC) procedure randomly selects the subspace first, then makes a step to a new
    random position independent of the previous position, but according to the predefined
    continuous probability distribution. The random step is followed by a local minimization
    in torsion angle space. The positions, sizes and preferences for high-probability zones on
    phi-psi maps and chi-angle maps were calculated for different residue types from the
    representative set of 191 and 161 protein 3D-structures, respectively. A fast and precise
    method to evaluate the electrostatic energy of a protein in solution is developed and
    combined with the BPMC procedure. The method is based on the modified spherical image
    charge approximation, efficiently projected onto a molecule of arbitrary shape. Comparison
    with the finite-difference solutions of the Poisson-Boltzmann equation shows high accuracy
    for our approach. The BPMC procedure is applied successfully to the structure prediction
    of 12- and 16-residue synthetic peptides and the determination of protein structure from
    NMR data, with the immunoglobulin binding domain of streptococcal protein G as an example.
    The BPMC runs display much better convergence properties than the non-biased simulations.
    The advantage of a true global optimization procedure for NMR structure determination is
    its ability to cope with local minima originating from data errors and ambiguities in NMR
    data. </p>
<p>
<a name="monoTim8loop"></a>
<!-- split><h3>The crystal structure of an engineered monomeric triosephosphate isomerase, monoTIM: the correct modelling of an eight-residue loop</h3>
<p>
<h4>Borchert, T.V., Abagyan, R.A., Kishan, K.V.R., Zeelen, J.Ph., &amp; Wierenga, R.K.
    (1994) </h4>
    <p><i>Structure</i> <b>1</b>, 205-213. </p>
    <p align="justify">The triosephosphate isomerase (TIM) fold is found in several different
    classes of enzymes, most of which are oligomeric. TIM itself always functions as a very
    tight dimer. It has recently been shown that a monomeric form of TIM (monoTIM) can be
    constructed by replacing a 15-residue interface loop, loop-3, with an eight-residue
    fragments; modeling suggests that this should result in a short strain-free turn,
    resulting in the subsequence helix, helix-A3, having an additional turn at its amino
    terminus. The crystal structure of monoTIM shows that it retains the characteristic
    TIM-barrel (beta/alpha)8 fold and that the new loop has a structure very close to that
    predicted. Two other interface loops, loop-1 ad loop-4, which contain the active site
    residue Lys13 and His95, respectively show significant changes in structure in monoTIM
    compared with dimeric wild-type TIM. The observed structural differences between monoTIM
    and wild-type TIM indicate that the dimeric appearance if TIM determines the location and
    conformation of two of the four catalytic residues .</p>
<p>
<a name="bioinform"></a>
<!-- split><h2>Bioinformatics</h2>
<p>
 Recognition of distant similarities;
 Prediction of structural similarities;
 Functional annotations of structural data;
 Sequence database searches;
<p>
<a name="alignseq"></a>
<!-- split><h3>Do aligned sequences share the same fold?</h3>
<p>
<h4>Abagyan, R.A. &amp; Batalov, S. (1997) </h4>
    <p><i>J. Mol. Biol.</i> <b>273</b>, 355-368. </p>
    <p align="justify">Sequence comparison remains a powerful tool to assess the structural
    relatedness of two proteins. To improve reliability of recognition in the twilight zone of
    sequence identities between 15 and 35%, we performed an exhaustive alignment of sequences
    of protein domains with known 3D folds and derived a set of functions which represent
    structural significance and positional accuracy of any sequence alignment. The subset of
    1,347,037 alignments between sequences of structurally unrelated domains was used to
    derived accurate probability functions of a structurally insignificant alignment at a
    given sequence identity, sequence similarity and alignment score. It is shown that
    sequence identity and sequence similarity measures are poor indicators of structural
    relatedness in the twilight zone, while the alignment score allows much better
    discrimination between alignments of structurally related sequences and unrelated ones,
    with the expected recognition error being three times lower. The derived functions can be
    used for fold recognition. </p>
<p>
<a name="energcalc"></a>
<!-- split><h3>Recognition of distantly related proteins through energy calculations</h3>
<p>

    <h4>Abagyan, R.A., Frishman, D., &amp; Argos, P. (1994) </h4>
    <p><i>Proteins</i> <b>19</b>, 132-140. </p>
    <p align="justify">A new method to detect remote relationships between protein sequences
    and known three-dimensional structures based on direct energy calculations and without
    reliance on statistics has been developed. The likelihood of a residues to occupy a given
    position on the structural template was represented by an estimate of the stabilization
    free energy mad after explicit prediction of the substituted side chain conformation. The
    profile matrix derive from these energy values and modified by increasing the residue
    self-exchange values successfully predicted compatibility of heat-shock protein and globin
    sequences with the three-dimensional structures of actin and phycocyanin, respectively,
    from a full protein sequence databank search. The high sensitivity of the method makes it
    a unique tool for predicting the three-dimensional fold for the rapidly growing number of
    protein sequences. </p>
<p>
<a name="drgdsgn"></a>
<!-- split><h2>Drug design and flexible docking</h2>
<p>
 Flexible protein-ligand docking
 Virtual screening
 Flexible protein-protein docking
<p>

<a name="pldock"></a>
<!-- split><h3>Flexible protien-ligand docking by global energy optimization in internal coordinates</h3>
<p>
<h4>Totrov, M. &amp; Abagyan, R., (1997) </h4>
    <p>Eight protein-ligand complexes were simulated by using global optimization of a complex
    energy function, including solvation, surface tension, and side-chain entropy in the
    internal coordinate space of the flexible ligand and the receptor side chains [Abagyan,
    R.A., Totrov, M.M. J. Mol. Biol. 235: 983-1002, 1994]. The procedure uses two types of
    efficient random moves, a pseudobrownian positional move [Abagyan, R.A., Totrov, M.M.,
    Kuznetsov, D.A. J. Comp. Chem. 15:488-506, 1994] and a Biased-Probability multitorsion
    move [Abagyan, R.A., Totrov, M.M. J. Mol. Biol. 235: 983-1002, 1994], each accompanied by
    full local energy minimization. The best docking solutions were further ranked according
    to the interaction energy, which included intramolecular deformation energies of both
    receptor and ligand, the interaction energy, surface tension, side-chain entropic
    contribution, and an electrostatic term evaluated as a boundary element solution of the
    Poisson equation with the molecular surface as a dielectric boundary. The geometrical
    accuracy of the docking solutions ranged from 30% to 70% according to the relative
    displacement error measure at a 1.5 A scale. Similar results were obtained when the
    explicit receptor atoms were replaced with a grid potential. </p>
    <p><i>Proteins</i>, <b>Suppl. 1</b>, 215-220 . </p>
<p>

<a name="tem1bl"></a>
<!-- split><h3>Molecular docking programs successfully predict the binding of a beta-lactamase inhibitory protein to TEM-1 beta-lactamase</h3>
<p>
<h4>Strynadka N.C., Eisenstein, M., Katchalski-Katzir, E., Shoichet, B.K., Kuntz, I.D.,
    Abagyan, R.A., Totrov, M., Janin, J., Cherfils, J., Zimmerman, F., Olson A., Duncan, B.,
    Rao, M, &amp; Jackson, R. Sternberg, M., James, M.N. (1996) </h4>
    <p><i>Nat. Struct. Biol.</i>, <b>3</b>, 233-239. </p>
    <p align="justify">Crystallization of the 1:1 molecular complex between the beta-lactamase
    TEM-1 and the beta-lactamase inhibitory protein BLIP has provided an opportunity to put a
    stringent test on current protein-docking algorithms. Prior to the successful
    determination of the structure of the complex, nine laboratory groups were given the
    refined atomic coordinates of each of the native molecules. Other than the fact that BLIP
    is an effective inhibitor of a number of beta-lactamase enzymes (KI for TEM-1
    approximately 100 pM) no other biochemical or structural data were available to assist the
    practitioners in their molecular docking. In addition, it was not known whether the
    molecules underwent conformational changes upon association or whether the inhibition was
    competitive or non-competitive. All six of the groups that accepted the challenge
    correctly predicted the general mode of association of BLIP and TEM-1. </p>
<p>
<a name="lacomp"></a>
<!-- split><h3>Detailed ab initio prediction of lysozyme-antibody complex with 1.6 A accuracy</h3>
<p>
<h4>Totrov, M.M. &amp; Abagyan, R.A. (1994) </h4>
    <p><i>Nat. Struct. Biol.</i> <b>1</b>, 259-263. </p>
    <p align="justify">The fundamental event in biological assembly is association of two
    biological macromolecules. Here we present a successful, accurate ab initio prediction of
    the binding of uncomplexed lysozyme to the HyHel5 antibody. The prediction combines pseudo
    Brownian Monte Carlo minimization with a biased-probability global side-chain placement
    procedure. It was effected in an all-atom representation, with ECEPP/2 potentials
    complemented with the surface energy, side-chain entropy and electrostatic polarization
    free energy. The near-native solution found was surprisingly close to the crystallographic
    structure (root-mean-square deviation of 1.57 A for all backbone atoms of lysozyme) and
    had a considerably lower energy (by 20 kcal/mol) than any other solution.</p>
<p>
<a name="manda"></a>
<!-- split><h2>Methods and algorithms</h2>
 Modeling in internal coordinates;
 Protein electrostatics and solvation;
 Monte-Carlo simulations;
 Detailed full-atom energy calculations;
 High-quality molecular visualization;
 Molecular animations;
<p>
<a name="cd59"></a>
<!-- split><h3>Identification of the individual residues that determine human CD59 species selective activity.</h3>
<p>
<h4>Zhang HF, Yu J, Chen S, Morgan BP, Abagyan R, Tomlinson S.
<p><i>J Biol Chem 1999 Apr 16;274(16):10969-74 </i></p>
<p>Formation of the cytolytic membrane attack complex of complement on host cells is inhibited by the membrane-bound
glycoprotein, CD59. The inhibitory activity of CD59 is species restricted, and human CD59 is not effective against rat
complement. Previous functional analysis of chimeric human/rat CD59 proteins indicated that the residues responsible for
the species selective function of human CD59 map to a region contained between positions 40 and 66 in the primary
structure. By comparative analysis of rat and human CD59 models and by mutational analysis of candidate residues, we
now identify the individual residues within the 40-66 region that confer species selective function on human CD59. All
nonconserved residues within the 40-66 sequence were substituted from human to rat residues in a series of chimeric
human/rat CD59 mutant proteins. Functional analysis revealed that the individual human to rat residue substitutions F47A,
T51L, R55E, and K65Q each produced a mutant human CD59 protein with enhanced rat complement inhibitory activity
with the single F47A substitution having the most significant effect. Interestingly, the side chains of the residues at
positions 47, 51, and 55 are all located on the short single helix (residues 47-55) of CD59 and form an exposed continuous
strip parallel to the helix axis. A single human CD59 mutant protein containing rat residue substitutions at all three helix
residues produced a protein with species selective activity comparable to that of rat CD59. We further found that synthetic
peptides spanning the human CD59 helix sequence were able to inhibit the binding of human CD59 to human C8, but had
little effect on the binding of rat CD59 to rat C8. </p>
<p>

<p>
<a name="globularproteins"></a>
<!-- split><h3>The hydration of globular proteins as derived from volume and compressibility measurements: cross correlating thermodynamic and structural data</h3>
<p>
<h4>Chalikian, T.V., Totrov, M.M., Abagyan, R.A., &amp; Breslauer, K.J. (1996) </h4>
    <p><i>J. Mol. Biol.</i>, <b>260</b>, 588-603. </p>
    <p align="justify">We report the first thermodynamic characterization of protein hydration
    that does not depend on model compound data but rather is based exclusively on macroscopic
    (volumetric) and microscopic (X-ray) measurements on protein molecules themselves. By
    combining these macroscopic and microscopic characterizations, we describe a quantitative
    model that allows one for the first time to predict the partial specific volumes, v(zero),
    and the partial specific adiabatic compressibilities, ks(zero), of globular proteins from
    the crystallographic coordinates of the constituent atoms, without using data derived from
    studies on low-molecular-mass model compounds. Specifically, we have used acoustic and
    densimetric techniques to determine v(zero) and ks(zero) for 15 globular proteins over a
    temperature range from 18 to 55 degrees C. For the subset of the 12 proteins with known
    three-dimensional structures, we calculated the molecular volumes as well as the
    solvent-accessible surface areas of the constituent charged, polar and nonpolar atomic
    groups. By combining these measured and calculated properties and applying linear
    regression analysis, we determined, as a function of temperature, the average hydration
    contributions to v(zero) and ks(zero) of 1 A2 of the charged, polar, and nonpolar
    solvent-accessible protein surfaces. We compared these results with those derived from
    studies on low-molecular-mass compounds to assess the validity of existing models of
    protein hydration based on small molecule data. This comparison revealed the following
    features: the hydration contributions to v(zero) and ks(zero) of charged protein surface
    groups are similar to those of charged groups in small organic molecules. By contrast, the
    hydration contributions to v(zero) and ks(zero) of polar protein surface groups are
    qualitatively different from those of polar groups in low-molecular-mass compounds. We
    suggest that this disparity may reflect the presence of networks of water molecules
    adjacent to polar protein surface areas, with these networks involving waters from second
    and third coordination spheres. For nonpolar protein surface groups, we find the ability
    of low-molecular-mass compounds to model successfully protein properties depends on the
    temperature domain being examined. Specifically, at room temperatures and below, the
    hydration contribution to ks(zero) of protein nonpolar surface atomic groups is close to
    that of nonpolar groups in small organic molecules. By contrast, at higher temperatures,
    the hydration contribution to ks(zero) of protein nonpolar surface groups becomes more
    negative than that of nonpolar groups in small organic molecules. We suggest that this
    behaviour may reflect nonpolar groups on protein surfaces being hydrated independently at
    low temperatures, while at higher temperatures some of the solvating waters become
    influenced by neighboring polar groups. We discuss the implications of our aggregate
    results in terms of various approaches currently being used to describe the hydration
    properties of globular proteins, particularly focusing on the limitations of existing
    additive models based on small molecule data. </p>
<p>

<a name="countourbuild"></a>
<!-- split><h3>The contour-buildup algorithm to calculate the analytical molecular surface</h3>
<p>
<h4>Totrov, M.M. &amp; Abagyan, R.A. (1996) </h4>
    <p><i>J. Struct. Biol.</i>, <b>115</b>, 1-6. </p>
    <p align="justify">A new algorithm is presented to calculate the analytical molecular
    surface defined as a smooth envelope traced out by the surface of a probe sphere rolled
    over the molecule. The core of the algorithm is the sequential build up of multi-arc
    contours on the van der Waals spheres. This algorithm yields substantial reduction in both
    memory and time requirements of surface calculations. Further, the contour-buildup
    principle is intrinsically &quot;local&quot;, which makes calculations of the partial
    molecular surfaces even more efficient. Additionally, the algorithm is equally applicable
    not only to convex patches, but also to concave triangular patches which may have complex
    multiple intersections. The algorithm permits the rigorous calculation of the full
    analytical molecular surface for a 100-residue protein in about 2 seconds on an SGI indigo
    with R4400++ processor at 150 Mhz, with the performance scaling almost linearly with the
    protein size. The contour-buildup algorithm is faster than the original Connolly algorithm
    an order of magnitude. </p>
<p>
<a name="biasedmontecarlo"></a>
<!-- split><h3>Biased probability Monte Carlo conformational searches and electrostatic calculations for peptides and proteins</h3>
<p>
<h4>Abagyan, R.A. &amp; Totrov, M.M. (1994) </h4>
    <p><i>J. Mol. Biol.</i> <b>235</b>, 983-1002. </p>
    <p align="justify">Two major components are required for a successful prediction of the
    three-dimensional structure of peptides and proteins: an efficient global optimization
    procedure which is capable of finding an appropriate local minimum for the strongly
    anisotropic function of hundreds of variables, and a set of free energy components for a
    protein molecule in solution which are computationally inexpensive enough to be used in
    the search procedure, yet sufficiently accurate to ensure the uniqueness of the native
    conformation. We here found an efficient way to make a random step in a Monte Carlo
    procedure given knowledge of the energy or statistical properties of conformational
    subspaces (e.g. phi-psi zones or side-chain torsion angles). This biased probability Monte
    Carlo (BPMC) procedure randomly selects the subspace first, then makes a step to a new
    random position independent of the previous position, but according to the predefined
    continuous probability distribution. The random step is followed by a local minimization
    in torsion angle space. The positions, sizes and preferences for high-probability zones on
    phi-psi maps and chi-angle maps were calculated for different residue types from the
    representative set of 191 and 161 protein 3D-structures, respectively. A fast and precise
    method to evaluate the electrostatic energy of a protein in solution is developed and
    combined with the BPMC procedure. The method is based on the modified spherical image
    charge approximation, efficiently projected onto a molecule of arbitrary shape. Comparison
    with the finite-difference solutions of the Poisson-Boltzmann equation shows high accuracy
    for our approach. The BPMC procedure is applied successfully to the structure prediction
    of 12- and 16-residue synthetic peptides and the determination of protein structure from
    NMR data, with the immunoglobulin binding domain of streptococcal protein G as an example.
    The BPMC runs display much better convergence properties than the non-biased simulations.
    The advantage of a true global optimization procedure for NMR structure determination is
    its ability to cope with local minima originating from data errors and ambiguities in NMR
    data. </p>
<p>
<a name="ICMmethod"></a>
<!-- split><h3>ICM - a new method for protein modelling and design. Applications to docking and structure prediction from the distorted native conformation</h3>
<p>
<h4>Abagyan, R.A., Totrov, M.M. &amp; Kuznetsov, D.N. (1994) </h4>
    <p><i>J. Comp. Chem.</i> <b>15</b>, 488-506. </p>
    <p align="justify">An efficient methodology, further referred to as ICM, for versatile
    modeling operations and global energy optimization on arbitrarily fixed multimolecular
    system is described. It is aimed at protein structure prediction, homology modeling,
    molecular docking, nuclear magnetic resonance (NMR) structure determination, and protein
    design. The method uses and further develops a previously introduced approach to model
    biomolecular structures in which bond lengths, bond angles, and torsion angles are
    considered as independent variables, any subset of them being fixed. Here we simplify and
    generalize the basic description of the system, introduce the variable dihedral phase
    angle, and allow arbitrary connections of the molecules and conventional definitions of
    the torsion angles. Algorithms for calculation of energy derivatives with respect to
    internal variables in the topological tree of the system and for rapid evaluation of
    accessible surface are presented. Multidimensional variable restraints are proposed to
    represent the statistical information about the torsion angle distributions in proteins.
    To incorporate complex energy terms as solvation energy and electrostatics into a
    structure prediction procedure, a &quot;double-energy&quot; Monte Carlo minimization
    procedure in which these terms are omitted diring the minimization stage of the random
    step and included for the comparison with the previous conformation in a Markov chain is
    proposed and justified. The ICM method is applied successfully to a molecular docking
    problem. The procedure finds the correct parallel arrangement of two rigid helices from a
    leucine zipper domain as the lowest-energy conformation (0.5 A root mean square, rms,
    deviation from the native structure) starting from completely random configuration.
    Structures with antiparallel helices or helices staggered by one helix turn had energies
    higher by about 7 or 9 kcal/mol, respectively. Soft docking was also attempted. A docking
    procedure allowing side-chain flexibility also converged to the parallel configuration
    starting from the helices optimize individually. To justify an internal coordinate
    approach to the structure prediction as opposed to a Cartesian one, energy hypersurfaces
    around the native structure of the squash seeds trypsin inhibitor were studied. Torsion
    angle minimization from the optimal conformation randomly distorted up to the rms
    deviation of 2.2 A or angular rms deviation of 10 degrees restored the native conformation
    in most cases. In contrast, Cartesian coordinate minimization did not reach the minimum
    from deviations as small as 0.3 A or 2 degrees. We conclude that the most promising
    detailed approach to the protein folding problem would consist of some coarse global
    sampling strategy combined with the local energy minimization in the torsion coordinate
    space. </p>
<p>

<p>
<a name="icmparalel"></a>
<!-- split><h3>Efficient parallelization of the energy, surface and derivative calculations for internal coordinate mechanics</h3>
<p>
<h4>Totrov, M.M. &amp; Abagyan, R.A. (1994) </h4>
    <p><i>J. Comp. Chem</i> <b>15</b>, 1105-1112. </p>
    <p align="justify">An efficient algorithm for parallelization of a molecular mechanics
    program operation in the space of internal coordinates such as dihedral angles, bond
    angles, and bond length, is described. The iterative procedure to calculate analytical
    energy derivatives with respect to the internal coordinates was modified to allow
    parallelization. Computationally intensive modules that calculate energy and its
    derivatives, solvent-accessible surface, electrostatic polarization energy and that update
    lists of interactions were parallelized with nearly 100% efficiency. The proposed strategy
    for the shared-memory computer architecture is easily scalable and requires minimum
    changes in a program code. The overall speedup for a realistic calculation minimizing the
    energy of a myoglobin reaches a factor of 3 for 4 processors. </p>
<p>
<a name="pf"></a>
<!-- split><h3>Towards protein folding by global energy optimization</h3>
<p>
<h4>Abagyan, R.A. (1993) </h4>
    <p><i>FEBS Letters</i> <b>325</b>, 17-22. </p>
    <p align="justify">Different components of the theoretical protein folding problem are
    evaluated critically. It is argued that : (i) as a rule, small- and medium-sized proteins
    are in the free energy minimum; (ii) long-living metastable states may either appear
    occasionally with growing protein size, or be selected by evolution for a specific
    function; (iii) functions discriminating against incorrect folds would fail if they were
    used directly in the global optimization, unless they approximate the true free energy
    accurately; (iv) surface and electrostatic free energies should be treated separately; (v)
    conformational entropy (of side chain in particular) should be taken into account; (vi)
    Monte Carlo procedure considering all free energy terms and combining global
    knowledge-based random moves with local optimization have the largest potential for
    success. </p>
<p>
<a name="psc"></a>
<!-- split><h3>A method to configure protein side-chains from the main-chain trace in homology modelling</h3>
<p>
<h4>Eisenmenger, F., Argos, P. &amp; Abagyan,R.A. (1993) </h4>
    <p><i>J. Mol. Biol.</i> <b>231</b>, 849-860. </p>
    <p align="justify">Protein homology modelling typically involves the prediction of
    side-chain conformations in the modelled protein while assuming a main-chain trace taken
    from a known tertiary structure of a protein with homologous sequence. It is generally
    believed that the need to examine all possible combinations of side-chain conformations
    poses the major obstacle to accurate homology modelling. Methods proposed heretofore use
    only discrete or limited searches of the side-chain torsion angle space to mitigate the
    combinatorial problem and also rely on simplified energy functions for calculational
    speed. The configurational constraints are typically based upon use of frequently observed
    torsion angles, fixed steps in torsion angles, or oligopeptide segments taken from
    tertiary structural databanks that are similar in sequence and conformation with the
    target structure. In the present work, a more fundamental approach is explored for several
    protein structures and it is demonstrated that the combinatorial barrier in side-chain
    placement hardly exists. Each side-group can be configured individually in the environment
    of only the backbone atoms using a systematic search procedure combined with extensive
    local energy minimization. Tests, using the main-chain or both the main-chain and
    remaining side-chain atoms to calculate low energy geometries for each residue,
    established the dominance of the main-chain contribution. The final structure is achieved
    by combining the individually placed side-chains followed by a full energy refinement of
    the structure. The prediction accuracy of the present homology modelling technique was
    assessed relative to other automated procedures and was found to yield improved
    predictions relative to the known side-chain conformations determined by X-ray
    crystallography. </p>
<p>

<a name="confsearch"></a>
<!-- split><h3>Optimal protocol and trajectory visualization for conformational searches of peptides and protein</h3>
<p>
<h4>Abagyan, R.A. &amp; Argos, P. (1992) </h4>
    <p><i>J. Mol. Biol.</i> <b>225</b>, 519-532. </p>
    <p align="justify">Conformational searches by molecular dynamics and different types of
    Monte Carlo or build-up methods usually aim to find the lowest-energy conformation.
    However, this is often misleading, as the energy functions used in conformational
    calculations are imprecise. For instance, though positions of local minima defined by the
    repulsive part of the Lennard-Jones potential are usually altered only slightly by
    functional modification, the relative depths of the minima could change significantly.
    Thus, the purpose of conformational searches and, correspondingly, performance criteria
    should be reformulated and appropriate methods found to extract different local minima
    from the search trajectory and allow visualization in the search space. Attempts at
    convergence to the lowest-energy structure should be replaced with efforts to visit a
    maximum number of different local energy minima with energies within a certain range. We
    use this quantitative criterion consistently to evaluate performances of different search
    procedures. To utilize information generated in the course of simulation, a
    &quot;stack&quot; of low energy conformations is created and stored. It keeps track of
    variables and visit numbers for the best representatives of different conformational
    families. To visualize the search, projection of multidimensional walks onto a principal
    plane defined by a set of reference structures is used. With Met-enkephalin as a
    structural example and a Monte Carlo procedure combined with energy minimization (MCM) as
    a basic search method, we analyzed the influence on search efficiency of different
    characteristics as temperature schedules, the step size for variable modification,
    constrained random step and response mechanisms to search difficulties. Simulated
    annealing MCM had comparable efficiency with MCM at constant and elevated temperature
    (about 600 K). Constraining the randomized choice of side-chain chi angles to optimal
    values (rotamers) on every MCM step did not improve, but rather worsened, the search
    efficiency. Two low-energy Met-enkephalin conformations with parallel Tyr1 and Phe4 rings,
    a gamma-turn around the Gly2 residue, and Phe4 and Met5 side-chains forming together a
    compact hydrophobic cluster were found and are suggested as possible structural candidates
    for interaction with a receptor or a membrane.</p>
<p>
<a name="projects"></a>
<!-- split><h1>Projects</h1>
<p>
<a name="Abinit"></a>
<!-- split><h2>Ab initio peptide folding by global energy optimization</h2>
<p>
Prodiction of a polypeptide 3D structure from amino acid sequence
<p>
<a name="Abinit"></a>
<!-- split><h2>Combined Approach to the Inverse Protein Folding Problem</h2>
<p>
Accurate evaluation of structural significance of a sequence alignment;
recognition of distant structural similarities via sequence database searches
<p>
<a name="mbh"></a>
<!-- split><h2>Modeling by Homology</h2>
<p>
Internal coordinate mechanics applyed to homology modeling
<p>
<a name="docking"></a>
<!-- split><h2>Docking</h2>
<p>
Flexible high resolutoin protein-protein docking and protein ligand docking
<p>
<a name="PD"></a>
<!-- split><h2>Protein Design</h2>
<p>
Loop Design
<p>
<a name="mopdr"></a>
<!-- split><h2>Modeling of protein domain rearrangements</h2>
<p>
Internal coordinate mechanics used to model protein domain motions
<p>
<a name="Cadprotmod"></a>
<!-- split><h2>Structure analysis: CAD Measure for the comparison of protein models</h2>
<p>
CAD Measure for the comparison of protein models;
protein 3D structure strain analysis, error detection
<p>
<a name="job"></a>
<!-- split><h1>Jobs</h1>
<p>
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<hr noshade>
<h3 align="center"><font color="blue">POSTDOCTORAL POSITIONS</h2></font>
<p>
              <H4 align="center">available as of 10/99</H3>
    <p> There are several openings in our research group for Postdoctoral
Associates in the area of computational biology and chemistry.
Applicants are encouraged to apply for support from various sources (see
list below) although independent support is not a requirement.  Specific
areas of research include:
<ul><li>
         Better alignments and profiles for functional annotation of the
genomic sequences
 <li>        Flexible protein-protein and protein-peptide docking.
 <li>        Computational methods for drug design, docking and ligand
ranking.
 <li>        Mathematical models of cells, derivation of biochemical
pathways.
  <li>       Prediction of protein three-dimensional structure by global
energy optimization.</ul>
<p>
 <p>  Please send a CV and two letters of recommendation by mail or email
to:<br>
<p>
 <p align="left">Dr. Ruben Abagyan<br>
                  Department of Molecular Biology, MB-37<br>
                  The Scripps Research Institute<br>
                  10550 North Torrey Pines Road<br>
                  La Jolla, California 92037<br>
                  Email: <mailto:ahref="abagyan@scripps.edu">abagyan@scripps.edu</a>
<p>
<hr>
<h2>There is an immediate postdoctoral fellowship opportunity from <br>
 Cancer Research Institute: </h2>
<b> DEADLINE:  April 1 </b><p>
<p>
<a href="http://www.sciencewise.com/swalert/fnd/opp/crin02020001.htm">
 POSTDOCTORAL FELLOWSHIP IN CANCER IMMUNOLOGY OR GENERAL IMMUNOLOGY
</a>
<p>
  ELIGIBILITY:<br>
 Applicants for the CRI Fellowship Program must have a doctoral degree
 and must conduct their proposed research under a sponsor who holds a
 formal appointment at the host institution. <b>Note that there are no citizenship
 restrictions</b> for this fellowship.
<p>
<p>
Please contact <a href="mailto:abagyan@scripps.edu">
Ruben Abagyan </a> for additional information.
<a href="http://www.scripps.edu/grad/chmgrads/facilities.html">
On this page</a> you can also find a useful piece of information on
COMPUTER FACILITIES (usually applications contain a section like this
to show that the work can be done).
<p>
<hr>
<h2> A research grant from NCI: </h2>
TITLE: MOLECULAR TARGET DRUG DISCOVERY FOR CANCER - NIH <p>
<p>
Letter of Intent Receipt Date:  June 6, 2000 <br>
Application Receipt Date:       July 18, 2000 <p>
<a href=http://www.sciencewise.com/foaalert/nih/nci/opp/02180001.htm>
 <a href="http://www.sciencewise.com/foaalert/nih/nci/opp/02180001.htm">http://www.sciencewise.com/foaalert/nih/nci/opp/02180001.htm</a></a>
<hr>
<p>
<P>Links to other postdoctoral funding opportunities:
<p>
<p><a href="http://www.sloan.org/main.htm">Alfred P. Sloan Foundation</a><br>
<a href="http://www.aacr.org">American Association for Cancer Research</a><br>
<a href="http://www.cancer.org/research/index.htm">American Cancer Society</a><br>
<a href="http://www.bwfund.org">Burroughs Wellcome Fund</a><br>
<a href="http://www.cancerresearchfund.org">Cancer Research Fund</a><br>
<a href="http://www.capcure.org">CapCURE Fund</a><br>
<a href="http://mrmc-rad6.army.mil/index.html">Department of Defense</a><br>
<a href="http://www.grantsnet.org">GrantsNet</a><br>
<a href="http://www.hhmi.org">Howard Hughes Medical Institute</a><br>
<a href="http://www.hfsp.org">Human Frontier Science Program</a><br>
<a href="http://www.nih.gov">National Institutes of Health</a><br>
<a href="http://www.nsf.gov">National Science Foundation</a><br>
<p>

<p>Training fellowships through the La Jolla Interfaces in Science
Interdisciplinary Training Program may be available to appropriate
candidates.
<p>
    <hr>
<h3 align="center"><font color="blue">OPPORTUNITY FOR GRADUATE STUDY AND RESEARCH</h2></font>
<P>Tha application deadline for TSRI Graduate Programs is January 1st of each year.</p>
<p>For program and application information click here:<br>
<a href="http://www.scripps.edu/grad/">www.scripps.edu/grad/</a>
<hr>
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