Biomedical subjects

A Tropsha

Publications and source records attributed to A Tropsha.

At least 37 records · Page 2Linked to original sources

PubMed1996

Energetic decomposition of the alpha-helix-coil equilibrium of a dynamic model system.

Using molecular dynamics simulations to calculate free energies of molecular transformation, we have computed helix-coil transition free energies for alanine oligomers up to 14 residues long. The simulations have been done on the model in vacuo with dielectric constant, epsilon = 1, 5, 25, and infinity and on the model in solution with explicit representation of water molecules and with partial charges on the oligomer set to zero. (The analogous simulations of the solvated model with full charges on the oligomer were reported elsewhere [L. Wang et al. (1995) Proceedings of the National Academy of Science USA 92, 10924-10928]). In vacuo, both entropic and electrostatic contributions oppose formation of a 3-residue helical nucleus in the helix initiation step. The entropy change opposing helix growth is found to be 3 e.u., van der Waals interactions favor helix growth by 1.9 kcal/mol, and electrostatic interactions favor helix growth by 3 kcal/mol (for epsilon = 1; all these values are per residue). In water, helix stability is slightly greater for the zero-charge model than for the full-charge model, i.e., the polypeptide's electrostatic interactions, which include hydrogen bonds, slightly destabilize the helix. The helix stabilizing contribution of the hydrophobic effect was found to be identical to that of the van der Waals interactions in vacuo (i.e., 1.9 kcal/mol per residue). The zero-charge model has nearly identical helix stability in vacuo and in water, the almost identical free energies of transfer of helix and coil state of the zero-charge oligomer from vacuum to water are found to be small. Thus, the results of this systematic variation of the force field afford a meaningful decomposition of the free energies for helix initiation and growth.

Entropy↗

PubMed1996

Delaunay tessellation of proteins: four body nearest-neighbor propensities of amino acid residues.

Delaunay tessellation is applied for the first time in the analysis of protein structure. By representing amino acid residues in protein chains by C alpha atoms, the protein is described as a set of points in three-dimensional space. Delaunay tessellation of a protein structure generates an aggregate of space-filling irregular tetrahedra, or Delaunay simplices. The vertices of each simplex define objectively four nearest neighbor C alpha atoms, i.e., four nearest-neighbor residues. A simplex classification scheme is introduced in which simplices are divided into five classes based on the relative positions of vertex residues in protein primary sequence. Statistical analysis of the residue composition of Delaunay simplices reveals nonrandom preferences for certain quadruplets of amino acids to be clustered together. This nonrandom preference may be used to develop a four-body potential that can be used in evaluating sequence-structure compatibility for the purpose of inverted structure prediction.

Amino Acids↗

PubMed1996

Statistical geometry analysis of proteins: implications for inverted structure prediction.

The topology of folded proteins from the representative dataset of well-defined three-dimensional protein structures is studied using a statistical geometry approach. Amino acid residues in protein chains are represented by C alpha atoms, thus reducing the protein three-dimensional structure to a set of points in three dimensional space. The Delaunay tessellation of a protein structure generates an aggregate of space-filling irregular tetrahedra, or Delaunay simplices. Each simplex objectively defines four nearest neighbor C alpha atoms, i.e. four nearest neighbor residues. The statistical analysis of residue composition of Delaunay simplices reveals nonrandom preferences for certain quadruplets of amino acids. These nonrandom preferences are used to develop a fitness function that evaluates sequence-structure compatibility. Using this fitness function, several tested native proteins score the highest among 100,000 random sequences with average protein amino acid composition. The statistical geometry approach, based solely on first principles, provides a unique means for protein structure analysis and has direct implications for inverted protein structure prediction.

Amino Acid Sequence↗

PubMed1995

Thermodynamic parameters for the helix-coil transition of oligopeptides: molecular dynamics simulation with the peptide growth method.

The helix-coil transition equilibrium of polypeptides in aqueous solution was studied by molecular dynamics simulation. The peptide growth simulation method was introduced to generate dynamic models of polypeptide chains in a statistical (random) coil or an alpha-helical conformation. The key element of this method is to build up a polypeptide chain during the course of a molecular transformation simulation, successively adding whole amino acid residues to the chain in a predefined conformation state (e.g., alpha-helical or statistical coil). Thus, oligopeptides of the same length and composition, but having different conformations, can be incrementally grown from a common precursor, and their relative conformational free energies can be calculated as the difference between the free energies for growing the individual peptides. This affords a straightforward calculation of the Zimm-Bragg sigma and s parameters for helix initiation and helix growth. The calculated sigma and s parameters for the polyalanine alpha-helix are in reasonable agreement with the experimental measurements. The peptide growth simulation method is an effective way to study quantitatively the thermodynamics of local protein folding.

Alanine↗

PubMed1995

Cross-validated R2-guided region selection for comparative molecular field analysis: a simple method to achieve consistent results.

Comparative Molecular Field Analysis (CoMFA) is one of the most powerful modern tools for quantitative structure-activity relationship studies. The CoMFA predictability is conventionally characterized by a cross-validated correlation coefficient R2 (q2). Our CoMFA investigation of 4 datasets, including 7 cephalotaxine esters, 20 5-HT1A receptor ligands, 59 inhibitors of HIV protease, and 21 steroids reveals that the q2 value is sensitive to the overall orientation of superimposed molecules on a computer terminal and can vary by as much as 0.5q2 units when the orientation is varied by systematic rotation. To optimize CoMFA, we have developed a new routine, cross-validated R2-guided region selection (q2-GRS). We first subdivide the rectangular lattice obtained initially with conventional CoMFA into 125 small boxes and perform 125 independent analyses using probe atoms placed within each box with the step size of 1.0 A. We then select only those small boxes for which a q2 is higher than a specified optimal cutoff value. Finally, we repeat CoMFA with the union of small boxes selected at the previous step. Four datasets described above were used to validate this new q2-GRS routine. In each case we have obtained an orientation-independent, high q2, exceeding the one obtained with the conventional CoMFA. This method shall be used routinely in the future CoMFA studies to guarantee the reproducibility of the reported q2 values.

Algorithms↗

PubMed1995

Relative binding free energies of peptide inhibitors of HIV-1 protease: the influence of the active site protonation state.

Hydrogen bonding plays an important role in the stabilization of complexes between HIV-1 protease (HIV-1 PR) and its inhibitors. The adequate treatment of the protease active site protonation state is important for accurate molecular simulations of the protonation state is important for accurate molecular simulations of the protease-inhibitor complexes. We have applied the free energy simulation/thermodynamic cycle approach to evaluate the relative binding affinities of the S vs R isomers of the U85548E inhibitor of the protease. Several mono- and diprotonation states of the catalytic aspartic acid residues of the protease active site were considered in the course of molecular simulations. The calculated difference in binding free energy of the S vs R isomers strongly depended on the location of proton(s), but in all cases the binding free energy of the S inhibitor was higher. On the basis of our calculations, we propose that in the HIV-1 PR-inhibitor complex only one catalytic aspartic acid residue is protonated and that the binding free energy of the S isomer is ca. 2.8 kcal/mol higher than that of the R isomer. The accuracy of these predictions shall be evaluated when binding affinities of both isomers become available.

Amino Acid Sequence↗

PubMed1995

Pseudotorsional OCCO backbone angle as a single descriptor of protein secondary structure.

Protein secondary structure is conventionally identified using characteristic ranges of two backbone torsional angles phi and psi. We suggest that the secondary structure can be adequately characterized by a single descriptor, the Oi-1Ci-1CiOi (where i is the residue number) pseudotorsional backbone angle. A set of 102 structurally distinct protein chains from the Protein Data Bank was used to evaluate the adequacy of this descriptor. We find that a specific range of OCCO angles corresponds to each major secondary structure. The complete range of OCCO angles (-180 degrees to 179 degrees) was broken into 18 consecutive subranges of 20 degrees each, and each subrange was assigned a letter. Thus, the OCCO profiles for each protein in the database were "translated" into a sequence of letters. The Needleman-Wunsch primary sequence alignment algorithm was then used for secondary/tertiary structure comparison and alignment. Preliminary results indicate that this new approach has a significant potential for rapid identification of fold families in the Protein Data Bank.

Amino Acid Sequence↗

PubMed1995

Rapid protein structure classification using one-dimensional structure profiles on the bioSCAN parallel computer.

Rapid growth of protein structures database in recent years requires an effective approach for objective comparison and classification of deposited protein structures. We describe a novel method for structure comparison and classification based on the alignment of one-dimensional structure profiles. These profiles are obtained by calculating the OCCO pseudodihedral angles (formed by O-C-C-O atoms of carbonyl groups of consecutive amino acid residues) from protein three-dimensional coordinates. These angle measurements are then converted into a 24 letter alphabet, and the protein structures are represented by sequences of letter from this alphabet. The BioSCAN parallel computer, designed for primary sequence alignment, is used to rapidly align and classify these one-dimensional structure profiles. We have developed and implemented weighted scoring matrix to identify structural classes based on commonly found structural motifs. The results of our experiments are in good agreement with the traditional protein structure classification schemes. One-dimensional structure profiles significantly improve efficiency of structure comparison and classification.

Algorithms↗

PubMed1994

Antitumor agents. 152. In vitro inhibitory activity of etoposide derivative NPF against human tumor cell lines and a study of its conformation by X-ray crystallography, molecular modeling, and NMR spectroscopy.

NPF, the title compound, was studied for its in vitro antitumor activity against 56 human tumor cell lines derived from seven cancer types. In general, NPF is about 100 times more active as compared to its parent compound, etoposide, toward all the tumor cell lines and can be considered as a lead structure for further development of anticancer agents. In order to facilitate future computer-assisted design of NPF analogs, NPF was characterized by X-ray crystallography. This crystal structure was used as the starting point for conformational analysis of this compound using several commercially available software packages, including SYBYL (Tripos Associates; Tripos force field), INSIGHT/DISCOVER (Biosym Technologies; CVFF force field), and semiempirical package MOPAC as implemented in SYBYL. The lowest energy conformation generated with the Tripos force field disagreed with the X-ray structure. On the other hand, semiempirical MOPAC/AM1 calculations showed that the X-ray structure had a lower energy than the Tripos lowest energy conformation. Subsequent NMR studies agreed well with the X-ray structure. Furthermore, conformational analysis of NPF using the DISCOVER force field identified the X-ray structure as the lowest energy conformation. Thus, the latter force field is adequate for future molecular modeling of NPF and its analogs.

Antineoplastic Agents↗

PubMed1994

Rational design of a three-heptad coiled-coil protein and comparison by molecular dynamics simulation with the GCN4 coiled coil: presence of interior three-center hydrogen bonds.

alpha-Helical coiled coils have a 7-residue repeating pattern (abcdefg) where a and d are usually hydrophobic. We have designed a 2-stranded 44-residue coiled-coil protein (P44) consisting of 2 22-residue alpha-helices linked by 2 terminal disulfide groups to test whether the disulfide bridges could stabilize a 3-heptad coiled coil. P44 should be stabilized by intrahelical hydrogen bonds, interhelical disulfide and salt bridges, and interior hydrophobic interactions. A computer model of P44 was built and its stability was studied by molecular dynamics simulation with explicit water. This doubly crosslinked 3-heptad coiled coil did not unfold during a 300-ps simulation with explicit water. This doubly crosslinked 3-heptad coiled coil did not unfold during a 300-ps simulation. But reduced P44 with 4 thiol groups did unfold. For comparison, the 62-residue crystal structure of the 4-heptad coiled coil of transcription activator GCN4 did not unfold during a 300-ps simulation. Thus P44 may be a stable folded protein in aqueous solution. These simulations revealed the presence of 2 local hydrogen bond networks involving intra-helical 3-center hydrogen bonds in the hydrophobic interior of the coiled coils of GCN4 and P44. The NH hydrogen at d makes a 3-center hydrogen bond whose major component is to the i - 4 C = O oxygen at g and minor component is to the solvent-inaccessible i - 3 C = O oxygen at a. Likewise, the NH hydrogen at g makes a 3-center hydrogen bond with the i - 4 C = O oxygen at c and the buried i - 3 C = O oxygen at d.

Amino Acid Sequence↗

PubMed1993

Free energies for refolding of the common beta turn into the inverse-common beta turn: simulation of the role of D/L chirality.

Quantitative estimates of the Gibbs free-energy change (delta G) for refolding of one beta-turn conformation into another would assist rational protein design. For beta-turn models, we studied a chirally representative set of nine peptides of the form CH3CO-L1-L2-NHCH3, where loop residues L1 (i + 1) and L2 (i + 2) are achiral Gly (G), L-Ala (A), or D-Ala (a). The stabilities of their common (type I) and inverse-common (type I') beta-turn conformers (GGI is the type-I GG conformer, etc.) were estimated by free-energy simulations using explicit water molecules. An alpha-hydrogen atom of a Gly residue at L1 or L2 was replaced by a methyl group by slow growth. The resulting conformers were less stable than GGI and GGI' by about 1-3 kcal/mol (delta G = 0.9 kcal/mol for AGI and aGI', 1.0 kcal/mol for GAI and GaI', 2.1 kcal/mol for aGI and AGI', and 2.8 kcal/mol for GaI and GAI'; 1 kcal = 4.18 kJ). The delta G value for simultaneous growth of one methyl group at L1 and another at L2 was the sum of the two component delta G values. The delta G values for I-->I' refolding of the common beta-turn conformer into the inverse-common beta-turn conformer ranged over 6 kcal/mol (-3.0 for aa, -1.8 for Ga, -1.1 for aG, -0.7 for Aa, 0 for GG, 0.7 for aA, 1.1 for AG, 1.8 for GA, and 3.0 for AA). Thus, replacing L-Ala by D-Ala at both L1 and L2 of a common beta turn may contribute as much as 6 kcal/mol toward its refolding as an inverse-common beta turn.

Amino Acid Sequence↗

PubMed1992

Making sense from antisense: a review of experimental data and developing ideas on sense--antisense peptide recognition.

Peptides encoded in the antisense strand of DNA have been predicted and found experimentally to bind to sense peptides and proteins with significant selectivity and affinity. Such sense--antisense peptide recognition has been observed in many systems, most often by detecting binding between immobilized and soluble interaction partners. Data obtained so far on sequence and solvent dependence of interaction support a hydrophobic-hydrophilic (amphipathic) model of peptide recognition. Nonetheless, the mechanistic understanding of this type of molecular recognition remains incomplete. Improving this understanding likely will require expanding the types of characteristics measured for sense--antisense peptide complexes and hence the types of analytical methods applied to such interactions. Understanding the mechanism of sense--antisense peptide recognition also may provide insights into mechanisms of native (sense) peptide and protein interactions and protein folding. Such insight may be helpful to learn how to design macromolecular recognition agents in technology for separation, diagnostics and therapeutics.

Amino Acid Sequence↗

PubMed1992

Application of free energy simulations to the binding of a transition-state-analogue inhibitor to HIV protease.

Free energy simulations (slow-change method) have been used to estimate quantitatively the ratio of the binding constants of (S) and (R) isomers of a novel HIV protease inhibitor, JG365. As a starting geometry, we used the X-ray crystallographic structure of a complex of HIV protease and JG365 provided by A. Wlodawer. According to our results the (S) configuration, i.e. the form previously identified experimentally, binds considerably more tightly to the protease (delta delta G degrees = 2.9 kcal/mol). When the (S) inhibitor is bound, there is a very strong preference for protonation of the Asp125 (rather than the Asp25) residue of the protease. This study is the first to apply a new method for quantitatively assessing the precision of free energies calculated by the slow-change method.

Binding Sites↗

PubMed1991

Do interhelical side chain-backbone hydrogen bonds participate in formation of leucine zipper coiled coils?

The leucine zipper proteins are a group of transcriptional regulators that dimerize to form a DNA binding domain. It has been proposed that this dimerization results from the hydrophobic association of the alpha-helices of two leucine zipper monomers into a coiled coil. We propose a model for a coiled coil based on a periodic hydrophobic-hydrophilic amino acid motif found in the leucine zipper regions of 11 transcriptional regulatory proteins. This model predicts the symmetrical formation of secondary hydrogen bonds between the polar side chains of one helix and the peptide carbonyls of the opposite chain, supplementing the interactions between hydrophobic side chains. Physical modeling (CPK) and in vacuo molecular mechanics calculations of the stability of the GCN4 leucine zipper coiled coil configured in accordance with this model demonstrate a greater stability for this conformer than for a conformer configured according to a current hydrophobic model. Molecular dynamics simulations show similar stability of the two models in vacuo but a higher stability of the hydrophobic model in water.

Amino Acid Sequence↗

PubMed1991

A motif found in propeptides and prohormones that may target them to secretory vesicles.

Sorting of prohormones and propeptides into secretory vesicles at the trans-Golgi face probably depends on a signal contained within the amino acid sequence of the peptide. To date no consensus sequence has been identified in prohormones or propeptides that might serve such a targeting function. In this report, we have analyzed the amino acid sequences and secondary structures of 15 prohormones and propeptides that have been shown experimentally to be sorted to secretory vesicles when the corresponding cDNA is transfected into mouse pituitary AtT20 cells. From these analyses, we have identified a motif that is shared by all of these diverse propeptides and might serve as a vesicular targeting sequence. This motif is degenerate and consists of two or more leucines occupying one side of a highly amphipattic alpha helix with a serine (or rarely threonine) positioned N-terminal to the leucines and projecting to the same side of the helix.

Algorithms↗

PubMedDate not supplied

Novel chirality descriptors derived from molecular topology.

Several series of novel chirality descriptors of chemical organic molecules have been introduced. The descriptors have been developed on the basis of conventional topological descriptors of molecular graphs. They include modified molecular connectivity indices, Zagreb group indices, extended connectivity, overall connectivity, and topological charge indices. These modified descriptors make use of an additional term called chirality correction, which is added to the vertex degrees of asymmetric atoms in a molecular graph. Chirality descriptors can be real or complex numbers. Advantages and drawbacks of different series of chirality descriptors are discussed. These descriptors circumvent the inability of conventional topological indices to distinguish chiral or enantiomeric isomers, which so far has been the major drawback of 2D descriptors as compared to true 3D descriptors (e.g., shape, molecular fields) of molecular structure. These novel chirality descriptors have been implemented in a quantitative structure-activity releationship (QSAR) study of a set of ecdysteroids with a high content of chiral and enantiomeric compounds using the k nearest neighbor QSAR method (kNN) recently developed in this laboratory. We show that the results of this study compare favorably with those obtained with the comparative molecular field analysis (CoMFA) applied to the same dataset. The novel chirality descriptors of molecular structure should find their applications in QSAR studies and related investigations of molecular sdatasets.

Models, Chemical↗

PubMedDate not supplied

Diversity and coverage of structural sublibraries selected using the SAGE and SCA algorithms.

It is often impractical to synthesize and test all compounds in a large exhaustive chemical library. Herein, we discuss rational approaches to selecting representative subsets of virtual libraries that help direct experimental synthetic efforts for diverse library design. We compare the performance of two stochastic sampling algorithms, Simulating Annealing Guided Evaluation (SAGE; Zheng, W.; Cho, S. J.; Waller, C. L.; Tropsha, A. J. Chem. Inf. Comput. Sci. 1999, 39, 738-746.) and Stochastic Cluster Analysis (SCA; Reynolds, C. H.; Druker, R.; Pfahler, L. B. Lead Discovery Using Stochastic Cluster Analysis (SCA): A New Method for Clustering Structurally Similar Compounds J. Chem. Inf. Comput. Sci. 1998, 38, 305-312.) for their ability to select both diverse and representative subsets of the entire chemical library space. The SAGE and SCA algorithms were compared using u- and s-optimal metrics as an independent assessment of diversity and coverage. This comparison showed that both algorithms were capable of generating sublibraries in descriptor space that are diverse and give reasonable coverage (i.e. are representative) of the original full library. Tests were carried out using simulated two-dimensional data sets and a 27 000 compound proprietary structural library as represented by computed Molconn-Z descriptors. One of the key observations from this work is that the algorithmically simple SCA method is capable of selecting subsets that are comparable to the more computationally intensive SAGE method.

Journal Article↗

PubMedDate not supplied

Rational combinatorial library design. 2. Rational design of targeted combinatorial peptide libraries using chemical similarity probe and the inverse QSAR approaches.

We have developed a novel strategy for rational design of targeted peptide libraries. The goal of this method is to select a subset of natural amino acids that are most likely to be present in active peptides for the synthesis of library. Two different protocols are employed where chemical structures of peptides are described either by topological indices or by a combination of physicochemical descriptors for individual amino acids. The selection of a peptide as a candidate for the targeted library is based either on its chemical similarity to a biologically active probe or on its biological activity predicted from a preconstructed quantitative structure-activity (QSAR) equation. The optimization of the library is achieved by means of genetic algorithms (GA). This method was tested by rational design of the library with bradykinin-potentiating activity. Twenty-eight bradykinin-potentiating pentapeptides were used as a training set for the development of a QSAR equation, and, alternatively, two active pentapeptides, VEWAK and VKWAP, were used as probe molecules. In each case, the frequency distribution of amino acids in the top 100 peptides suggested by the method resembles the frequency distribution of amino acids found in the active peptides. The results obtained after GA optimization also compared favorably with those obtained by the exhaustive analysis of all possible 3.2 million pentapeptides.

Algorithms↗