Biomedical subjects

Buddhadeb Mallik

Publications and source records attributed to Buddhadeb Mallik.

5 recordsLinked to original sources

PubMed2005

Implicit solvent simulations of DPC micelle formation.

The formation of micelles by dodecylphosphocholine (DPC) is modeled by treating the surfactants in atomic detail and the solvent implicitly, in the spirit of the EEF1 solvation model for proteins. The solvation parameters of the DPC atoms are carried over from those of similar atoms in proteins. A slight adjustment of the parameters for the headgroup was found necessary for obtaining an aggregation number consistent with experiment. Molecular dynamics simulations of 960 DPC molecules at different concentrations are used to obtain the aggregation number, the micelle size distribution, and the CMC. At 20 mM concentration we obtain an aggregation number of 53-56 and a CMC of 1.25 mM, values close to the experimental ones. At 100 mM the aggregation number increases to 90. Simulations of individual micelles of varying size show that the effective energy per surfactant molecule is initially a decreasing function of aggregation number but stabilizes at about 60 molecules. The van der Waals term and the desolvation of nonpolar groups contribute to micellization, whereas the desolvation of polar groups opposes it. From the difference between the effective energy and the free energy (calculated from the CMC), the translational and rotational entropy contributions to the free energy are estimated at about 7 kcal/mol per monomer. The micelles obtained here are more irregular than those obtained in explicit water simulations. This modeling approach allows the study of larger surfactant aggregates for longer times and the extraction of thermodynamic in addition to structural information.

Computer Simulation↗

PubMed2005

Development of a quasi-dynamic pharmacophore model for anti-complement peptide analogues.

Three quasi-dynamic pharmacophore models have been constructed for the complement inhibitor peptide compstatin, using first principles. Uniform sampling along 5-ns molecular dynamics trajectories provided dynamic conformers that are thought to represent the entire conformational space for nine training set molecules, compstatin, four active analogues, and four inactive analogues. The pharmacophore models were built using mixed physicochemical and structural properties of residues indispensable for structural stability and activity. Owing to the size and flexibility of compstatin, one-dimensional probability distributions of intrapharmacophore point distances, angles, and dihedral angles of different analogues spread over wide and overlapping ranges. More robust two-dimensional distance-angle probability distributions for two pharmacophore models discriminated individual analogues in terms of specific distance-angle pairs, but overall failed to identify the active and the inactive analogues as two distinct groups. Two-dimensional distance-dihedral angle probability distributions in a third pharmacophore model allowed discrimination of the groups of active and inactive analogues more effectively, with the highest-activity analogue having distinct behavior. The present study indicates that more stringent structural constraints should be used for a set of structurally similar but flexible peptides, as opposed to organic molecules, to convert dynamic conformers into pharmacophore models. Flexibility is a general aspect of the structure and function of peptides and should be taken into account in ligand-based pharmacophore design. However, the discrimination of activity using multidimensional probability surfaces depends on the peptide system, the selection of the training set, the molecular dynamics protocol, and the selection of the type and number of pharmacophore points.

Complement System Proteins↗

PubMed2005

Design and NMR characterization of active analogues of compstatin containing non-natural amino acids.

We present new findings in our drug discovery effort to develop an anticomplement therapeutic. We have designed several active analogues of compstatin by altering its amino acid composition at positions 4 and 9. The most effective analogues have tryptophan or fused-ring non-natural amino acids at position 4 and alanine or an unbranched single-methyl amino acid at position 9. Twenty-one of these analogues have 2-99-fold higher activities compared to the parent peptide compstatin. The analogue Ac-V4(2Nal)/H9A-NH(2) has the highest inhibitory activity with IC(50) 500 nM. NMR data, through NOE and chemical shift analysis, suggest the presence of interconverting conformers spanning the extended and helical regions of the Ramachandran plot, and they detect a predominant averaged conformer with coil structure and at least one flexible beta-turn, of type I. The fused-ring non-natural amino acids at position 4 contribute to the formation of the hydrophobic cluster of compstatin, which has been previously proposed, together with the beta-turn and a disulfide bridge, to be essential for binding to the target of compstatin, complement component C3. We propose that additional mechanisms may contribute to the structural stability of the analogues and to binding to C3, involving intra- and intermolecular electrostatic interactions of the pi-electron system of side chain aromatic rings. The presence of pi-pi interactions for Trp4-Trp7 was confirmed with a molecular dynamics simulation for the most active analogue with natural amino acids, Ac-V4W/H9A-NH(2). Alanine or aminobutyric acid at position 9 contribute to the weak propensity for helical structure of the residue segment 4-10 of the analogues, which may also play a role in increased activity.

Amino Acids↗

PubMed2003

Conformational interconversion in compstatin probed with molecular dynamics simulations.

Compstatin is a 13-residue cyclic peptide that has the potential to become a therapeutic agent against unregulated complement activation. In our effort to understand the structural and dynamic characteristics of compstatin that form the basis for rational and combinatorial optimization of structure and activity, we performed 1-ns molecular dynamics (MD) simulations. We used as input in the MD simulations the ensemble of 21 lowest energy NMR structures, the average minimized structure, and a global optimization structure. At the end of the MD simulations we identified five conformations, with populations ranging between 9% and 44%. These conformations are as follows: 1) coil with alphaR-alphaR beta-turn, as was the conformation of the initial ensemble of NMR structures; 2) beta-hairpin with epsilon-alphaR beta-turn; 3) beta-hairpin with alphaR-alphaR beta-turn; 4) beta-hairpin with alphaR-beta beta-turn; and 5) alpha-helical. Conformational switch was possible with small amplitude backbone motions of the order of 0.1-0.4 A and free energy barrier crossing of 2-11 kcal/mol. All of the 21 MD structures corresponding to the NMR ensemble possessed a beta-turn, with 14 structures retaining the alphaR-alphaR beta-turn type, but the average minimized structure and the global optimization structures were converted to alpha-helical conformations. Overall, the MD simulations have aided to gain insight into the conformational space sampled by compstatin and have provided a measure of conformational interconversion. The calculated conformers will be useful as structural and possibly dynamic templates for optimization in the design of compstatin using structure-activity relations (SAR) or dynamics-activity relations (DAR).

Computer Simulation↗

PubMed2002

Distance and exposure dependent effective dielectric function.

In an effort to develop a dielectric screening function for molecular dynamics simulations of biomolecules in implicit solvent, effective dielectric constants (D(eff)) for a large number of atom pairs in a typical globular protein are calculated by continuum electrostatics. Plots of D(eff) versus the intercharge distance are in general sigmoidal with the characteristics of the curve depending on the distance of the two charges from the dielectric boundary and, secondarily, on the extent to which the area surrounding each charge is occupied by solvent (the "exposure"). The D(eff) values were fitted to an empirical, analytical function of these parameters that reproduces the data reasonably well, although considerable scatter exists in the range of D(eff) from 30 to 80. In the system used for parameterization, the mean square deviation of electrostatic interaction energies with this function is 0.48 kcal/mol, compared to 1.45 for an analytical Generalized Born model and 1.52 for the linear distance-dependent dielectric model. When tested in other proteins of varying size and compactness, the present function is superior to both of the above models, except for a fully unfolded polypeptide chain, where the Generalized Born model is superior.

Journal Article↗