Biomedical subjects

Michal Brylinski

Publications and source records attributed to Michal Brylinski.

6 recordsLinked to original sources

PubMed2006

Hydrophobic collapse in (in silico) protein folding.

A model of hydrophobic collapse, which is treated as the driving force for protein folding, is presented. This model is the superposition of three models commonly used in protein structure prediction: (1) 'oil-drop' model introduced by Kauzmann, (2) a lattice model introduced to decrease the number of degrees of freedom for structural changes and (3) a model of the formation of hydrophobic core as a key feature in driving the folding of proteins. These three models together helped to develop the idea of a fuzzy-oil-drop as a model for an external force field of hydrophobic character mimicking the hydrophobicity-differentiated environment for hydrophobic collapse. All amino acids in the polypeptide interact pair-wise during the folding process (energy minimization procedure) and interact with the external hydrophobic force field defined by a three-dimensional Gaussian function. The value of the Gaussian function usually interpreted as a probability distribution is treated as a normalized hydrophobicity distribution, with its maximum in the center of the ellipsoid and decreasing proportionally with the distance versus the center. The fuzzy-oil-drop is elastic and changes its shape and size during the simulated folding procedure.

Amino Acids↗

PubMed2006

Stereoselectivity of 8-OH-DPAT toward the serotonin 5-HT1A receptor: biochemical and molecular modeling study.

The great majority of pharmacological investigations of 5-HT1A receptors' reactivity has been performed using racemic 8-OH-DPAT, therefore the biochemical as well as behavioral profiles of both 8-OH-DPAT enantiomers are not circumstantiated. In the biochemical study capability of racemic 8-OH-DPAT (0.05, 0.1 mg/kg s.c.) and its counterparts R-8-OH-DPAT (0.05, 0.1 mg/kg s.c.) and S-8-OH-DPAT (0.05, 0.1 mg/kg s.c.) to influence 5-HT synthesis rate in rats' prefrontal cortex, hypothalamus, hippocampus and brainstem was evaluated by HPLC/ED technique. Biochemical results are supported by the exhaustive computational study of possible differences between R- and S-enantiomer toward the 5-HT1A receptor. A reliable 3D model of the rat 5-HT1A receptor was constructed from the amino acid sequence using the crystal structure of bovine rhodopsin as a structural template. The structure of the receptor model was validated through docking studies and molecular dynamics simulations that gave results consistent with experimental data. Docking studies and the dynamics of ligand-receptor complexes emphasized different profiles of both enantiomers at the molecular level. The results of both biochemical and computational studies confirmed that R-enantiomer in contrast to S-8-OH-DPAT acts as full and potent agonist, whilst racemic form may display similar pharmacological profile to R-8-OH-DPAT.

8-Hydroxy-2-(di-n-propylamino)tetralin↗

PubMed2006

Hydrophobic collapse in late-stage folding (in silico) of bovine pancreatic trypsin inhibitor.

Hydrophobic collapse is commonly considered as a process of significance for protein folding. Many models have been applied for description of this event. A model introducing an external force field mimicking the hydrophobic environment and simultaneously the driving force for the folding process is presented in this paper. Bovine pancreatic trypsin inhibitor (BPTI) was taken as a test protein. An early-stage folding (in silico) model presented elsewhere was used to create the starting structure for hydrophobic collapse. The resulting structure was energy-refined using molecular dynamics simulation in an explicit solvent. The similarity versus the crystal structure of BPTI is estimated using visual analysis, residue-residue contacts, phi, psi angle distributions, RMSD, accessible solvent area, radii of gyration and hydrodynamic radii. A program allowing creation of early-stage folding structural forms to be created for any protein is available from http://bioinformatics.cm-uj.krakow.pl/earlystage. The program for late-stage folding simulation is available on request.

Animals↗

PubMed2006

Fuzzy-oil-drop hydrophobic force field--a model to represent late-stage folding (in silico) of lysozyme.

A model of hydrophobic collapse (in silico), which is generally considered to be the driving force for protein folding, is presented in this work. The model introduces the external field in the form of a fuzzy-oil-drop assumed to represent the environment. The drop is expressed in the form of a three-dimensional Gauss function. The usual probability value is assumed to represent the hydrophobicity distribution in the three-dimensional space of the virtual environment. The differences between this idealized hydrophobicity distribution and the one represented by the folded polypeptide chain is the parameter to be minimized in the structure optimization procedure. The size of fuzzy-oil-drop is critical for the folding process. A strong correlation between protein length and the dimension of the native and early-stage molecular form was found on the basis of single-domain proteins analysis. A previously presented early-stage folding (in silico) model was used to create the starting structure for the procedure of late-stage folding of lysozyme. The results of simulation were found to be promising, although additional improvements for the formation of beta-structure and disulfide bonds as well as the participation of natural ligand in folding process seem to be necessary.

Computer Simulation↗

PubMed2006

Gauss-function-Based model of hydrophobicity density in proteins.

The model adopting the three-dimensional Gauss function to express the hydrophobicity distribution in proteins is presented in this paper. The tendency to create the hydrophobic center during protein folding is expressed in form of an external force field of the form of three-dimensional Gauss function which directs the folding polypeptide to locate the hydrophobic residues in a central part of the molecule and hydrophilic ones exposed toward the molecular surface. The decrease of the differences between hydrophobicity distribution as it appears at each step of the folding simulation and the expected hydrophobicity distribution (three-dimensional Gauss function) is the convergence criterion together with traditional non-bonding interaction optimization. The model was applied to fold the hypothetical membrane protein (target protein in CASP6) TA0354_69_121 from Thermoplasma acidophilum.

Computer Simulation↗

PubMed2004

SPI--structure predictability index for protein sequences.

Estimation of structure predictability for a particular protein is difficult. Many methods estimate it in an a posteriori system evaluating the final, native protein structure. The SPI scale is intended to estimate the structure predictability of a particular amino acid sequence in an a priori system. A sequence-to-structure library was created based on the complete Protein Data Bank. The tetrapeptide was selected as a unit representing a well-defined structural motif. The early-stage folding structure (a model of which was presented elsewhere) was taken as the object for protein structure classification. Seven structural forms were distinguished for structure classification. The degree of determinability was estimated for the sequence-to-structure and structure-to-sequence relations particularly interesting for threading methods. A comparative analysis of the SPI and Q7 scales with the commonly used SOV and Q3 scales is presented. The complete contingency table, supplementary materials and all the programs used are available on request.

Amino Acid Sequence↗