Biomedical subjects

James M Briggs

Publications and source records attributed to James M Briggs.

25 records · Page 2Linked to original sources

PubMed2002

Charge-charge interactions are the primary determinants of the pK values of the ionizable groups in Ribonuclease T1.

Coulomb's law and a finite difference Poisson-Boltzmann based analysis are used to predict the pK values for 15 ionizable side chains (6 Asp, 6 Glu and 3 His) in ribonuclease T1. These predicted values are compared to the measured pK values to gain insight into the most important factors that influence the pK values of the ionizable groups in proteins. Charge-charge interactions are clearly the most important factor that determines the pK values of most ionizable groups in ribonuclease T1. However, pK values can be shifted by several pK units by the Born self energy associated with burying ionizable groups and by favorable intramolecular hydrogen bonding.

Ions↗

PubMed2002

Molecular docking and 3D-QSAR studies on gag peptide analogue inhibitors interacting with human cyclophilin A.

The interaction of a series gag peptide analogues with human cyclophilin A (hCypA) have been studied employing molecular docking and 3D-QSAR approaches. The Lamarckian Genetic Algorithm (LGA) and divide-and-conquer methods were applied to locate the binding orientations and conformations of the inhibitors interacting with hCypA. Good correlations between the calculated interaction free energies and experimental inhibitory activities suggest that the binding conformations of these inhibitors are reasonable. A novel interaction model was identified for inhibitors 11, 15, and 17 whose N-termini were modified by addition of the deaminovaline (Dav) group and the C-termini of 15 and 17 were modified by addition of a benzyl group. Accordingly, two new binding sites (sites A and D in Figure 1) were revealed, which show a strong correlation with inhibitor potency and thus can be used as a starting point for new inhibitor design. In addition, two predictive 3D-QSAR models were obtained by CoMFA and CoMSIA analyses based on the binding conformations derived from the molecular docking calculations. The reasonable r(cross)(2) (cross-validated) values 0.738 and 0.762 were obtained for CoMFA and CoMSIA models, respectively. The predictive ability of these models was validated by four peptide analogues test set. The CoMFA and CoMSIA field distributions are in general agreement with the structural characteristics of the binding groove of hCypA. This indicates the reasonableness of the binding model of the inhibitors with hCypA. Considering all these results together with the valuable clues of binding from references published recently, reasonable pharmacophore elements have been suggested, demonstrating that the 3D-QSAR models about peptide analogue inhibitors are expected to be further employed in predicting activities of the novel compounds for inhibiting hCypA.

Binding Sites↗

PubMed2002

Brownian dynamics simulations of the recognition of the scorpion toxin P05 with the small-conductance calcium-activated potassium channels.

The recognition of the scorpion toxin P05 and the small-conductance, calcium-activated potassium (SK) channels, rsk1, rsk2, and rsk3, has been studied by means of the Brownian dynamics (BD) method. All of the 25 available structures of P05 in the RCSB Protein Data Bank determined by NMR were considered during the simulation, which indicated that the conformation of P05 affects both the recognition and binding between the two proteins significantly. Comparing the top four high-frequency structures of P05 binding to the SK channels, we found that the rsk2 channel, with high frequencies and lowest electrostatic interaction energies (E (int)(ES)), is the most favorable for P05 binding, while rsk3 is intermediate, and rsk1 is the least favorable. Among the 25 structures of P05, the 13th structure docks into the binding site of the rsk2 channel with the highest probability and most favorable electrostatic interactions. From the P05-rsk2 channel binding model, we identified the residues critical for the recognition of these two proteins through triplet contact analyses. P05 locates around the extracellular mouth of the SK channels and contacts the SK channels using its alpha-helix rather than beta-sheets. The critical triplet contacts for recognition between P05 and the rsk2 channel are Arg6 (P05)-Asp364 (SK), Arg7 (P05)-Asn368 (SK), and Arg13 (P05)-Asp341 (SK). The structure of the P05-rsk2 complex with the most favorable electrostatic interaction energy was further refined by molecular mechanics, showing that six hydrogen bonding interactions exist between P05 and the rsk2 channel: one hydrogen bond is formed between Arg6 (P05) and Asp364(D) (rsk2); Arg7 (P05) forms three hydrogen bonds with Asp341(B) (rsk2)) and Asp364(C) (rsk2); two hydrogen bonds are formed by Arg13 (P05) with Asp341(A) (rsk2) and Asp364(B) (rsk2). The simulation results are in good agreement with the previous molecular biological experiments and can explain the binding phenomena between P05 and SK channels at the level of molecular structure. The consistency between the results of the BD simulations and the experimental data indicated that our 3D model of the P05-rsk2 channel complex is reasonable and can be employed in further biological studies, such as rational design of the novel therapeutic agents blocking the small-conductance, calcium-activated and apamin-sensitive potassium channels, and for mutagenesis studies in both toxins and SK channels. In particular, both the BD simulations and the molecular mechanics refinements indicate that residue Asp364 of the rsk2 channel is critical for its recognition and binding functionality towards P05. This phenomenon has not been appreciated in the previous mutagenesis experiments, indicating that this might be a new clue for further functional study of SK channels.

Amino Acid Sequence↗

PubMed2002

The association between a negatively charged ligand and the electronegative binding pocket of its receptor.

Many examples exist of charged amino acids that play a role in attracting or holding a charged ligand toward or inside an oppositely charged binding pocket of the protein. For example, the enzymes superoxide dismutase, triose-phosphate isomerase, and acetylcholinesterase can steer ligands toward their oppositely charged binding pockets or gorges. Interestingly, in our Brownian dynamics simulations of a phosphate-binding protein, we discovered that negatively charged phosphate (HPO(2-)(4)) could make its way into the negatively charged binding pocket. In fact, the phosphate-binding protein exhibits counterintuitive kinetics of association. That is, one would expect that the rate of association would increase on increases to the ionic strength since the interaction between the ligand, with a charge of -2, and the electronegative binding pocket would be repulsive and greater screening should reduce this repulsion and increase the rate of association. However, the opposite is seen-i.e., the rate of association decreases on increases in the ionic strength. We used Brownian dynamics techniques to compute the diffusion limited association rate constants between the negatively charged phosphate ligand and several open forms of PBP (wild-type and several mutants based on an x-ray structure of open-form PBP, mutant T141D). With the appropriate choices of reaction criteria and molecular parameters, the ligand was able to diffuse into the binding pocket. A number of residues influence binding of the ligand within the pocket via hydrogen bonds or salt bridges. Arg135 partially neutralizes the charges on the HPO(2-)(4) ligand in the binding pocket, allowing it to enter. It is also found that the positive electrostatic patches above and below the binding entrance of PBP contribute the major attractive forces that direct the ligand toward the surface of the protein near the binding site.

Bacterial Proteins↗

PubMed2002

Brownian dynamics simulations of the recognition of the scorpion toxin maurotoxin with the voltage-gated potassium ion channels.

The recognition of the scorpion toxin maurotoxin (MTX) by the voltage-gated potassium (Kv1) channels, Kv1.1, Kv1.2, and Kv1.3, has been studied by means of Brownian dynamics (BD) simulations. All of the 35 available structures of MTX in the Protein Data Bank (http://www.rcsb.org/pdb) determined by nuclear magnetic resonance were considered during the simulations, which indicated that the conformation of MTX significantly affected both the recognition and the binding between MTX and the Kv1 channels. Comparing the top five highest-frequency structures of MTX binding to the Kv1 channels, we found that the Kv1.2 channel, with the highest docking frequencies and the lowest electrostatic interaction energies, was the most favorable for MTX binding, whereas Kv1.1 was intermediate, and Kv1.3 was the least favorable one. Among the 35 structures of MTX, the 10th structure docked into the binding site of the Kv1.2 channel with the highest probability and the most favorable electrostatic interactions. From the MTX-Kv1.2 binding model, we identified the critical residues for the recognition of these two proteins through triplet contact analyses. MTX locates around the extracellular mouth of the Kv1 channels, making contacts with its beta-sheets. Lys23, a conserved amino acid in the scorpion toxins, protrudes into the pore of the Kv1.2 channel and forms two hydrogen bonds with the conserved residues Gly401(D) and Tyr400(C) and one hydrophobic contact with Gly401(C) of the Kv1.2 channel. The critical triplet contacts for recognition between MTX and the Kv1.2 channel are Lys23(MTX)-Asp402(C)(Kv1), Lys27(MTX)-Asp378(D)(Kv1), and Lys30(MTX)-Asp402(A)(Kv1). In addition, six hydrogen-bonding interactions are formed between residues Lys23, Lys27, Lys30, and Tyr32 of MTX and residues Gly401, Tyr400, Asp402, Asp378, and Thr406 of Kv1.2. Many of them are formed by side chains of residues of MTX and backbone atoms of the Kv1.2 channel. Five hydrophobic contacts exist between residues Pro20, Lys23, Lys30 and Tyr32 of MTX and residues Asp402, Val404, Gly401, and Arg377 of the Kv1.2 channel. The simulation results are in agreement with the previous molecular biology experiments and explain the binding phenomena between MTX and Kv1 channels at the molecular level. The consistency between the results of the BD simulations and the experimental data indicated that our three-dimensional model of the MTX-Kv1.2 channel complex is reasonable and can be used in additional biological studies, such as rational design of novel therapeutic agents blocking the voltage-gated channels and in mutagenesis studies in both the toxins and the Kv1 channels. In particular, both the BD simulations and the molecular mechanics refinements indicate that residue Asp378 of the Kv1.2 channel is critical for its recognition and binding functionality toward MTX. This phenomenon has not been appreciated in the previous mutagenesis experiments, indicating this might be a new clue for additional functional study of Kv1 channels.

Amino Acid Motifs↗

PubMed2002

A structure-based design approach for the identification of novel inhibitors: application to an alanine racemase.

We report a new structure-based strategy for the identification of novel inhibitors. This approach has been applied to Bacillus stearothermophilus alanine racemase (AlaR), an enzyme implicated in the biosynthesis of the bacterial cell wall. The enzyme catalyzes the racemization of L- and D-alanine using pyridoxal 5'-phosphate (PLP) as a cofactor. The restriction of AlaR to bacteria and some fungi and the absolute requirement for D-alanine in peptidoglycan biosynthesis make alanine racemase a suitable target for drug design. Unfortunately, known inhibitors of alanine racemase are not specific and inhibit the activity of other PLP-dependent enzymes, leading to neurological and other side effects. This article describes the development of a receptor-based pharmacophore model for AllaR, taking into account receptor flexibility (i.e. a 'dynamic' pharmacophore model). In order to accomplish this, molecular dynamics (MD) simulations were performed on the full AlaR dimer from Bacillus stearothermophilus (PDB entry, 1 sft) with a D-alanine molecule in one active site and the non-covalent inhibitor, propionate, in the second active site of this homodimer. The basic strategy followed in this study was to utilize conformations of the protein obtained during MD simulations to generate a dynamic pharmacophore model using the property mapping capability of the LigBuilder program. Compounds from the Available Chemicals Directory that fit the pharmacophore model were identified and have been submitted for experimental testing. The approach described here can be used as a valuable tool for the design of novel inhibitors of other biomolecular targets.

Alanine Racemase↗

PubMedDate not supplied

Efficient 3D database screening for novel HIV-1 IN inhibitors.

We describe the use of pharmacophore modeling as an efficient tool in the discovery of novel HIV-1 integrase (IN) inhibitors. A three-dimensional hypothetical model for the binding of diketo acid analogues to the enzyme was built by means of the Catalyst program. Using these models as a query for virtual screening, we found several compounds that contain the specified 3D patterns of chemical functions. Biological testing shows that our strategy was successful in searching for new structural leads as HIV-1 IN inhibitors.

Computer Simulation↗