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Results for “Molecular Docking Simulation”

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PubMed1994

Predicting molecular interactions and inducible complementarity: fragment docking of Fab-peptide complexes.

Antibody-antigen interactions are representative of a broad class of receptor-ligand interactions involving both specificity and potential inducible complementarity. To test possible mechanisms of antigen-antibody recognition and specificity computationally, we have used a Metropolis Monte Carlo algorithm to dock fragments of the epitope Glu-Val-Val-Pro-His-Lys-Lys to the X-ray structures of both the free and the complexed Fab of the antibody B13I2 (raised against the C-helix of myohemerythrin). The fragments Pro-His and Val-Pro-His, which contain residues experimentally identified as important for binding, docked correctly to both structures, but all tetrapeptide and larger fragments docked correctly only to the complexed Fab, even when torsional flexibility was added to the ligand. However, only tetrapeptide and larger fragments showed significantly more favorable energies when docked to the complexed Fab coordinates than when docked to either the free Fab or a non-specific site remote from the combining site. Comparison of the free and complexed B13I2 structures revealed that atoms within 5 A of Val-Pro-His showed little movement upon peptide binding, but atoms within 5 A of the other four epitope residues showed greater movements. These results computationally distinguished recognition and binding processes with practical implications for drug design strategies. Overall, this new fragment docking approach establishes distinct roles for the "lock-and-key" (recognition) and the "handshake" (binding) paradigms in antibody-antigen interaction, suggests an incremental approach to incorporating flexibility in computational docking, and identifies critical regions within receptor binding sites for ligand recognition.

Algorithms↗

PubMed2003

Molecular docking studies of natural cholinesterase-inhibiting steroidal alkaloids from Sarcococca saligna.

Alkaloids isolated from Sarcococca saligna significantly inhibit acetyl- and butyrylcholinesterase enzyme, suggesting discovery of inhibitors for nervous-system disorders. Studying interactions with the active site of the AChE enzyme from Torpedo californica, we have identified hydrophobic interactions inside the aromatic gorge area as the major stabilizing factor in enzyme-inhibitor complexes of these alkaloids. Molecular Dynamics simulation of a predicted complex indicates that ligand binding does not extensively alter enzyme structure, but reduces flexibility at the gorge.

Acetylcholinesterase↗

PubMed2003

Prediction of the structure of the complex between the 30S ribosomal subunit and colicin E3 via weighted-geometric docking.

Colicin E3 kills Escherichia coli cells by ribonucleolytic cleavage in the 16S rRNA. The cleavage occurs at the ribosomal decoding A-site between nucleotides A1493 and G1494. The breaking of this single phosphodiester bond results in a complete termination of protein biosynthesis leading to cell death. A model structure of the complex of the ribosomal subunit 30S and colicin E3 was constructed by means of a new weighted-geometric docking algorithm, in which interactions involving specified parts of the molecular surface can be up-weighted, allowing incorporation of experimental data in the docking search. Our model, together with available experimental data, predicts the role of the catalytic residues of colicin E3. In addition, it suggests that bound acidic immunity protein inhibits the enzymatic activity of colicin E3 by electrostatic repulsion of the negatively charged substrate.

Algorithms↗

PubMed1999

Macromolecular docking of a three-body system: the recognition of human growth hormone by its receptor.

Human growth hormone (hGH) binds to its receptor (hGHr) in a three-body interaction: one molecule of the hormone and two identical monomers of the receptor form a trimer. Curiously, the hormone-receptor interactions in the trimer are not equivalent and the formation of the complex occurs in a specific kinetic order (Cunningham BC, Ultsch M, De Vos AM, Mulkerrin MG, Clauser KR, Wells JA, 1991, Science 254:821-825). In this paper, we model the recognition of hGH to the hGHr using shape complementarity of the three-dimensional structures and macromolecular docking to explore possible binding modes between the receptor and hormone. The method, reported previously (Hendrix DK, Kuntz ID, 1998, Pacific symposium on biocomputing 1998, pp 1234-1244), is based upon matching complementary-shaped strategic sites on the molecular surface. We modify the procedure to examine three-body systems. We find that the order of binding seen experimentally is also essential to our model. We explore the use of mutational data available for hGH to guide our model. In addition to docking hGH to the hGHr, we further test our methodology by successfully reproducing 16 macromolecular complexes from X-ray crystal structures, including enzyme-inhibitor, antibody-antigen, protein dimer, and protein-DNA complexes.

Algorithms↗

PubMed2006

Modeling the ligand-receptor interaction for a series of inhibitors of the capsid protein of enterovirus 71 using several three-dimensional quantitative structure-activity relationship techniques.

The structure of enterovirus 71 (EV71) capsid protein VP1 has been constructed by using homology modeling and molecular dynamics simulation techniques. The ligand structures were a series of EV71 VP1 inhibitors synthesized by Shia et al. in 2002 and Chern et al. in 2004. The training set was selected by the VOLSURF4.1/PCA program and the IC50 values varied from 0.06 to 10.83 microm. Then, the training set was analyzed by the following three-dimensional quantitative structure-activity relationship techniques: CoMFA, CoMSIA, CATALYST4.9, and VOLSURF4.1/PCA. The model generated by a two-stage flexible docking procedure and without any structural alignment has far more significant statistics. Highly accurate activities for the test sets were then predicted by the top hypothesis of the CATALYST program and were compared with those predicted by CoMFA, CoMSIA, and VOLSURF. These studies identified some important clues for searching or making more potent inhibitors against the EV71 infection.

Binding Sites↗

PubMed1996

Molecular modelling of human gastric alcohol dehydrogenase (class IV) and substrate docking: differences towards the classical liver enzyme (class I).

A three-dimensional model of the human class IV alcohol dehydrogenase has been calculated based upon the X-ray structure of the class I enzyme. As judged from the model, the substrate-binding site is wider than in class I, compatible with the differences in substrate specificities and the large difference in Km value for ethanol. Substrate docking performed for the class I structure and the class IV model show all-trans-retinol and 11-cis-retinol to bind better to the class IV enzyme. The calculations also indicate that 16-hydroxyhexadecanoic acid binds in a different manner for the two enzyme classes. A simulation of coenzyme-binding indicates that the adenine ring of the coenzyme might be differently bound in class IV than in class I, decreasing the interactions with Asp-223 which is compatible with the higher k(cat) values for class IV.

Alcohol Dehydrogenase↗

PubMed2005

Validation of a histamine H3 receptor model through structure-activity relationships for classical H3 antagonists.

Histamine H(3) receptor is a G protein-coupled receptor whose activation inhibits the synthesis and release of histamine and other neurotransmitters from nerve endings and is involved in the modulation of different central nervous system functions. H(3) antagonists have been proposed for their potential usefulness in diseases characterized by impaired neurotransmission and they have demonstrated beneficial effects on learning and food intake in animal models. In the present work, a 3D model of the rat histamine H(3) receptor, built by comparative modeling from the crystallographic coordinates of bovine rhodopsin, is presented with the discussion of its ability to predict the potency of known and new H(3) antagonists. A putative binding site for classical, imidazole-derived H(3) antagonists was identified by molecular docking. Comparison with a known pharmacophore model and the binding affinity of a new rigid H(3) antagonist (compound 1, pK(i)=8.02) allowed the characterization of a binding scheme which could also account for the different affinities observed in a recently reported series of potent H(3) antagonists, characterized by a 2-aminobenzimidazole moiety. Molecular dynamics simulations were employed to assess the stability and reliability of the proposed binding mode. Two new conformationally constrained benzimidazole derivatives were prepared and their binding affinity was tested on rat brain membranes; compound 9, designed to reproduce the conformation of a known potent H(3) antagonist, showed higher potency than compound 8, as expected from the binding scheme hypothesized.

Amino Acid Sequence↗

PubMed2006

Towards predictive ligand design with free-energy based computational methods?

The accurate prediction of ligand-biopolymer binding affinities is of general interest to medicinal chemistry, as well as to the broader field of molecular recognition. The ability to predict computationally the thermodynamics of these molecular recognition processes has been relatively weak until recently, however, continued developments on several fronts are extending the scope of applicability of these methods. The rapid growth in the number of protein-ligand structures has initially led to the development of a range of empirical scoring functions based on relatively simple descriptions of intermolecular interactions. These methods have had some success in ranking binding affinities when tuned to particular protein systems or in rather qualitative estimates of molecular fit in fast docking calculations. However, they are too unreliable for more detailed, quantitative, assessment and comparison of binding affinities. Physics-based free energy calculations are in principle more general and have the potential to be significantly more accurate. These approaches have seen steady development over many years and rely on carefully calibrated molecular energy functions (force-fields), simulations of the systems with explicit solvent, and the coming-of-age of continuum solvation models. In addition to the initially developped Free Energy Perturbation (FEP) and Thermodynamic Integration (TI) methods, new approaches include the Molecular Mechanics-Poisson-Boltzmann Surface Area (MM-PBSA) and the Linear Interaction Energy (LIE) approaches. This review concentrates on MM-PBSA and LIE, and their variants. The routine application of these calculations is becoming possible because of enhanced computational hardware and the development of a range of computational chemistry tools. This review addresses: i) the basic principles behind free energy calculations ii) recent methodological advances iii) comparisons of predicted and experimentally determined affinities iv) the uncertainties and limitations of both the computational and experimental data v) areas where progress can be made vi) the practicality of applying the methods at the different stages of the drug discovery and optimization process.

Animals↗

PubMed1997

Inter-domain cross-linking and molecular modelling of the hairpin ribozyme.

The hairpin ribozyme is a small catalytic RNA composed of two helical domains containing a small and a large internal loop and, thus, constitutes a valuable paradigm for the study of RNA structure and catalysis. We have carried out molecular modelling of the hairpin ribozyme to learn how the two domains (A and B) might fold and approach each other. To help distinguish alternative inter-domain orientations, we have chemically synthesized hairpin ribozymes containing 2'-2' disulphide linkages of known spacing (12 or 16 A) between defined ribose residues in the internal loop regions of each domain. The abilities of cross-linked ribozymes to carry out RNA cleavage under single turnover conditions were compared to the corresponding disulphide-reduced, untethered ribozymes. Ribozymes were classed in three categories according to whether their cleavage rates were marginally, moderately, or strongly affected by cross-linking. This rank order of activity guided the docking of the two domains in the molecular modelling process. The proposed three-dimensional model of the hairpin ribozyme incorporates three different crystallographically determined structural motifs: in domain A, the 5'-GAR-3'-motif of the hammerhead ribozyme, in domain B, the J4/5 motif of group I ribozymes, and connecting the two domains, a "ribose zipper", another group I ribozyme feature, formed between the hydroxyl groups of residues A10, G11 of domain A and C25, A24 of domain B. This latter feature might be key to the selection and precise orientation of the inter-domain docking necessary for the specific phosphodiester cleavage. The model provides an important basis for further studies of hairpin ribozyme structure and function.

Computer Simulation↗

PubMed2004

Heterotrimeric type I collagen C-telopeptide conformation as docked to its helix receptor.

The amino (N-telo) and carboxyl (C-telo) telopeptides of type I collagen play crucial roles, in vivo and in vitro, in the assembly of collagen fibrils, regulating the axial alignment of the molecules within a fibril, azimuthal orientations of neighboring molecules, and cross-link formation. High-resolution structures of the telopeptides are not available from X-ray diffraction studies, but computational methods permitted prediction of the N-telo structure within a fibril. Here, using a suite of molecular modeling software, the more complex heterotrimeric C-telo of human type I collagen has been built from the correct sequences and energy minimized and the energy minimum confirmed by molecular dynamics. The receptor triple helix was modeled on the basis of the Protein Data Bank coordinates of a collagen-like sequence. Docking of the heterotrimeric C-telopeptide to its receptor showed that hydrophobic interactions involving the short alpha2 C-telopeptide are crucial determinants of its azimuthal orientation within the docked structure. A docked C-telo can interact with only one neighboring helix. The two alpha1(I) C-telo chains in the alpha1(Alpha)-alpha2-alpha1(B) chain stagger do not have identical docked conformations, and one of the alpha1(I) C-telo chains appears to be favored for formation of a cross-link between its K(16C) and a helix K87. Prior studies showed that a docked N-telopeptide can interact with two adjacent collagen monomers, forming a tightly packed region. A recent X-ray analysis showed the N- and C-telo regions pack differently, with the C-telo region being less densely packed than N-telo regions. This difference between N- and C-telopeptide docked structures demonstrates how unique and specific packing can occur in the fibril at each boundary of the type I collagen gap region.

Amino Acid Sequence↗

PubMed2005

The MPSim-Dock hierarchical docking algorithm: application to the eight trypsin inhibitor cocrystals.

To help improve the accuracy of protein-ligand docking as a useful tool for drug discovery, we developed MPSim-Dock, which ensures a comprehensive sampling of diverse families of ligand conformations in the binding region followed by an enrichment of the good energy scoring families so that the energy scores of the sampled conformations can be reliably used to select the best conformation of the ligand. This combines elements of DOCK4.0 with molecular dynamics (MD) methods available in the software, MPSim. We test here the efficacy of MPSim-Dock to predict the 64 protein-ligand combinations formed by starting with eight trypsin cocrystals, and crossdocking the other seven ligands to each protein conformation. We consider this as a model for how well the method would work for one given target protein structure. Using as a criterion that the structures within 2 kcal/mol of the top scoring include a conformation within a coordinate root mean square (CRMS) of 1 A of the crystal structure, we find that 100% of the 64 cases are predicted correctly. This indicates that MPSim-Dock can be used reliably to identify strongly binding ligands, making it useful for virtual ligand screening.

Algorithms↗

PubMed2005

Assessment of CAPRI predictions in rounds 3-5 shows progress in docking procedures.

The current status of docking procedures for predicting protein-protein interactions starting from their three-dimensional (3D) structure is reassessed by evaluating blind predictions, performed during 2003-2004 as part of Rounds 3-5 of the community-wide experiment on Critical Assessment of PRedicted Interactions (CAPRI). Ten newly determined structures of protein-protein complexes were used as targets for these rounds. They comprised 2 enzyme-inhibitor complexes, 2 antigen-antibody complexes, 2 complexes involved in cellular signaling, 2 homo-oligomers, and a complex between 2 components of the bacterial cellulosome. For most targets, the predictors were given the experimental structures of 1 unbound and 1 bound component, with the latter in a random orientation. For some, the structure of the free component was derived from that of a related protein, requiring the use of homology modeling. In some of the targets, significant differences in conformation were displayed between the bound and unbound components, representing a major challenge for the docking procedures. For 1 target, predictions could not go to completion. In total, 1866 predictions submitted by 30 groups were evaluated. Over one-third of these groups applied completely novel docking algorithms and scoring functions, with several of them specifically addressing the challenge of dealing with side-chain and backbone flexibility. The quality of the predicted interactions was evaluated by comparison to the experimental structures of the targets, made available for the evaluation, using the well-agreed-upon criteria used previously. Twenty-four groups, which for the first time included an automatic Web server, produced predictions ranking from acceptable to highly accurate for all targets, including those where the structures of the bound and unbound forms differed substantially. These results and a brief survey of the methods used by participants of CAPRI Rounds 3-5 suggest that genuine progress in the performance of docking methods is being achieved, with CAPRI acting as the catalyst.

Algorithms↗

PubMed1994

Rational automatic search method for stable docking models of protein and ligand.

An efficient automatic method has been developed for docking a ligand molecule to a protein molecule. The method can construct energetically favorable docking models, considering specific interactions between the two molecules and conformational flexibility in the ligand. In the first stage of docking, likely binding modes are searched and estimated effectively in terms of hydrogen bonds, together with conformations in part of the ligand structure that includes hydrogen bonding groups. After that part is placed in the protein cavity and is optimized, conformations in the remaining part are also examined systematically. Finally, several stable docking models are obtained after optimization of the position, orientation and conformation of the whole ligand molecule. In all the screening processes, the total potential energy including intra- and intermolecular interaction energy, consisting of van der Waals, electrostatic and hydrogen bonding energies, is used as the index. The characteristics of our docking method are high accuracy of the results, fully automatic generation of models and short computational time. The efficiency of the method was confirmed by four docking trials using two enzyme systems. In two attempts to dock methotrexate to dihydrofolate reductase and 2'-GMP to ribonuclease T1, the exact structures of complexes in crystals were reproduced as the most stable docking models, without any assumptions concerning the binding modes and ligand conformations. The most stable docking models of dihydrofolate and trimethoprim, respectively, to dihydrofolate reductase were also in good agreement with those suggested by experiment. In all test cases, it was shown that our method can accurately predict the correct docking structures, discriminating the correct model from incorrect ones. The efficiency of our method was further tested from the viewpoint of ability to predict the relative stability of the docking structures of two triazine derivatives to dihydrofolate reductase. Our docking method provides a useful tool for rational drug design and investigations of biochemical reaction mechanisms.

Algorithms↗

PubMed2006

In silico modelling of the interaction of flavonoids with human P-glycoprotein nucleotide-binding domain.

A three-dimensional model of human ABCB1 nucleotide-binding domain (NBD) was developed by homology modelling using the high-resolution human TAP1 transporter structure as template. Interactions between NBD and flavonoids were investigated using in silico docking studies. Ring-A of unmodified flavonoid was located within the NBD P-loop with the 5-hydroxyl group involved in hydrogen bonding with Lys1076. Ring-B was stabilised by hydrophobic stacking interactions with Tyr1044. The 3-hydroxyl group and carbonyl oxygen were extensively involved in hydrogen bonding interactions with amino acids within the NBD. Addition of prenyl, benzyl or geranyl moieties to ring-A (position-6) and hydrocarbon substituents (O-n-butyl to O-n-decyl) to ring-B (position-4) resulted in a size-dependent decrease in predicted docking energy which reflected the increased binding affinities reported in vitro.

ATP Binding Cassette Transporter, Subfamily B, Mem↗

PubMed2004

Electrostatic barrier to recovery of dipalmitoylphosphatidylglycerol monolayers after collapse.

The reincorporation of lipids into monolayers at the air-water interface after collapse is important to the maintenance of low surface tensions on subsequent expansion and compression cycles. For single component, anionic dipalmitoylphosphatidylglycerol monolayers, the fraction of recovered lipid is proportional to the subphase ionic strength. The collapse mechanism and structure of the collapsed materials appear unchanged with ionic strength. A simple electrostatic barrier model shows that the fractional recovery depends exponentially on the Debye length; this is verified by experiment. This simple model suggests possible catalytic roles for the cationic lung surfactant specific proteins SP-B and SP-C that induce structural changes in the monolayer that may act as charge-neutralizing docking sites for surfactant in the subphase, leading to faster and more efficient recovery.

Computer Simulation↗

PubMed2000

Computer simulations of enantioselective ester hydrolyses catalyzed by Pseudomonas cepacia lipase.

On the basis of the X-ray crystal structure of the lipase from Pseudomonas cepacia (PcL)-an enzyme representative for a whole family of Pseudomonas lipases (lipase PS, SAM-2, AK 10, and others with a high degree of homology with PcL)-a computational study was performed to rationalize both the enantioselectivity and substrate specificity (tolerance) displayed by this lipase in the enantioselective hydrolysis of racemic esters 1a-12a from various secondary aromatic alcohols. The major goal of this project was the development of a binding model for PcL which is able to rationalize the experimental findings to predict "a priori the enantioselective behavior of PcL toward a wider range of substrates. A two-step modeling procedure, namely, docking experiments followed by construction of tetrahedral intermediates, was used for the simulation of the involved enzyme-substrate recognition/hydrolysis processes. The study of the recognition process (docking experiments) led to unambiguous identification of the binding geometry for the two enantiomeric series of substrates, but did not suggest a definitive interpretation of the behavior of PcL. Taking into consideration the stereoelectronic requirements of the enzymatic hydrolysis reaction, both the enantioselectivity and tolerance of the enzyme were then explained through the study of the tetrahedral intermediates, in turn constructed from the calculated docking geometries of 1a-12a.

Burkholderia cepacia↗

PubMed2001

Brownian dynamics simulations of interaction between scorpion toxin Lq2 and potassium ion channel.

The association of the scorpion toxin Lq2 and a potassium ion (K(+)) channel has been studied using the Brownian dynamics (BD) simulation method. All of the 22 available structures of Lq2 in the Brookhaven Protein Data Bank (PDB) determined by NMR were considered during the simulation, which indicated that the conformation of Lq2 affects the binding between the two proteins significantly. Among the 22 structures of Lq2, only 4 structures dock in the binding site of the K(+) channel with a high probability and favorable electrostatic interactions. From the 4 candidates of the Lq2-K(+) channel binding models, we identified a good three-dimensional model of Lq2-K(+) channel complex through triplet contact analysis, electrostatic interaction energy estimation by BD simulation and structural refinement by molecular mechanics. Lq2 locates around the extracellular mouth of the K(+) channel and contacts the K(+) channel using its beta-sheet rather than its alpha-helix. Lys27, a conserved amino acid in the scorpion toxins, plugs the pore of the K(+) channel and forms three hydrogen bonds with the conserved residues Tyr78(A-C) and two hydrophobic contacts with Gly79 of the K(+) channel. In addition, eight hydrogen-bonds are formed between residues Arg25, Cys28, Lys31, Arg34 and Tyr36 of Lq2 and residues Pro55, Tyr78, Gly79, Asp80, and Tyr82 of K(+) channel. Many of them are formed by side chains of residues of Lq2 and backbone atoms of the K(+) channel. Thirteen hydrophobic contacts exist between residues Met29, Asn30, Lys31 and Tyr36 of Lq2 and residues Pro55, Ala58, Gly79, Asp80 and Tyr82 of the K(+) channel. These favorable interactions stabilize the association between the two proteins. These observations are in good agreement with the experimental results and can explain the binding phenomena between scorpion toxins and K(+) channels at the level of molecular structure. The consistency between the BD simulation and the experimental data indicates that our three-dimensional model of Lq2-K(+) channel complex is reasonable and can be used in further biological studies such as rational design of blocking agents of K(+) channels and mutagenesis in both toxins and K(+) channels.

Amino Acid Sequence↗

PubMed1994

Molecular surface recognition by a computer vision-based technique.

Correct docking of a ligand onto a receptor surface is a complex problem, involving geometry and chemistry. Geometrically acceptable solutions require close contact between corresponding patches of surfaces of the receptor and of the ligand and no overlap between the van der Waals spheres of the remainder of the receptor and ligand atoms. In the quest for favorable chemical interactions, the next step involves minimization of the energy between the docked molecules. This work addresses the geometrical aspect of the problem. It is assumed that we have the atomic coordinates of each of the molecules. In principle, since optimally matching surfaces are sought, the entire conformational space needs to be considered. As the number of atoms residing on molecular surfaces can be several hundred, sampling of all rotations and translations of every patch of a surface of one molecule with respect to the other can reach immense proportions. The problem we are faced with here is reminiscent of object recognition problems in computer vision. Here we borrow and adapt the geometric hashing paradigm developed in computer vision to a central problem in molecular biology. Using an indexing approach based on a transformation invariant representation, the algorithm efficiently scans groups of surface dots (or atoms) and detects optimally matched surfaces. Potential solutions displaying receptor--ligand atomic overlaps are discarded. Our technique has been applied successfully to seven cases involving docking of small molecules, where the structures of the receptor--ligand complexes are available in the crystallographic database and to three cases where the receptors and ligands have been crystallized separately. In two of these three latter tests, the correct transformations have been obtained.

Algorithms↗