Determination of ligand-binding sites on proteins using long-range hydrophobic potential

Theoretical Studies on the Effect of Isomerized Aspartic Acid Residues on the Three-Dimensional Structures of Bovine Pancreatic Ribonucleases A

Isomerized aspartic acid (Asp) residues have previously been identified in various aging tissues, and are suspected to contribute to age-related diseases. Asp-residue isomerization occurs nonenzymatically under physiological conditions, resulting in the formation of three types of isomerized Asp (i.e., L-isoAsp, D-Asp, and D-isoAsp) residues. Asp-residue isomerization often accelerates protein aggregation and insolubilization, making structural biology analyses difficult. Recently, Sakaue et al. reported the synthesis of a ribonuclease A (RNase A) in which Asp121 was artificially replaced with different isomerized Asp residues, and experimentally demonstrated that the enzymatic activities of these artificial mutants were completely lost. However, their structural features have not yet been elucidated. In the present study, the three-dimensional (3D) structures of these artificial-mutant RNases A were predicted using molecular dynamics (MD) simulations. The 3D structures of wild-type and artificial-mutant RNases A were converged by 3000-ns MD simulations. Our computational data show that the structures of the active site and the formation frequencies of the appropriate catalytic dyad structures in the artificial-mutant RNases A were quite different from wild-type RNase A. These computational findings may provide an explanation for the experimental data which show that artificial-mutant RNases A lack enzymatic activity. Herein, MD simulations have been used to evaluate the influences of isomerized Asp residues on the 3D structures of proteins.

Development of Force Field Parameters for p-Carborane to Investigate the Structural Influence of Carborane Derivatives on Drug Targets by Complex Formation

Androgen receptor (AR) has a key role in the development and progression of prostate cancer, and AR antagonists are used for its remedy. Recently, carborane derivatives, which are carbon-containing boron clusters have attracted attention as new AR ligands. Here we determined the force field parameters of 10-vertex and 12-vertex p-carborane to facilitate in silico drug design of boron clusters. Then, molecular dynamics (MD) simulations of complexes of AR-carborane derivatives were performed to evaluate the parameters and investigate the influences of carborane derivatives on the three-dimensional structure of AR. Energy profiles were obtained using quantum chemical calculations, and the force-field parameters were determined by curve fitting of the energy profiles. The results of MD simulations indicated that binding of the antagonist-BA341 changed some hydrogen-bond formations involved in the structure and location of helix 12. Those results were consistent with previously reported data. The determined parameters are also useful for refining the structure of the carborane-receptor complex obtained by docking simulations and development of new ligands with carborane cages not only for AR but also for various receptors.

In silico fragment-mapping method: a new tool for fragment-based/structure-based drug discovery

Here, we propose an in silico fragment-mapping method as a potential tool for fragment-based/structure-based drug discovery (FBDD/SBDD). For this method, we created a database named Canonical Subsite-Fragment DataBase (CSFDB) and developed a knowledge-based fragment-mapping program, Fsubsite. CSFDB consists of various pairs of subsite-fragments derived from X-ray crystal structures of known protein-ligand complexes. Using three-dimensional similarity-matching between subsites on one protein and another, Fsubsite compares the surface of a target protein with all subsites in CSFDB. When a local topography similar to the subsite is found on the surface, Fsubsite places a fragment combined with the subsite in CSFDB on the target protein. For validation purposes, we applied the method to the apo-structure of cyclin-dependent kinase 2 (CDK2) and identified four compounds containing three mapped fragments that existed in the list of known inhibitors of CDK2. Next, the utility of our fragment-mapping method for fragment-growing was examined on the complex structure of tRNA-guanine transglycosylase with a small ligand. Fsubsite mapped appropriate fragments on the same position as the binding ligand or in the vicinity of the ligand. Finally, a 3D-pharmacophore model was constructed from the fragments mapped on the apo-structure of heat shock protein 90-α (HSP90α). Then, 3D pharmacophore-based virtual screening was carried out using a commercially available compound database. The resultant hit compounds were very similar to a known ligand of HSP90α. As a result of these findings, this in silico fragment-mapping method seems to be a useful tool for computational FBDD and SBDD.

Investigation of substrate recognition for cytochrome P450 1A2 mediated by water molecules using docking and molecular dynamics simulations

The role of water molecules in the active site of cytochrome P450 1A2 (CYP1A2) was investigated using an explicit water model to simulate biological environments. Moreover, differences in ligand recognition between the inhibitor α-naphthoflavone (ANF) and the substrate 7-ethoxyresorufin (7ER) in the CYP1A2 complex were examined. More than 200-ns molecular dynamics (MD) simulations were performed for each complex structure of CYP1A2. In the complex structure with 7ER obtained after MD simulation, some water molecules existed in the active site and formed hydrogen bonds between 7ER and some residues. However, in the complex structure with ANF, the hydrogen bond network differed. These results suggest that CYP1A2 requires water molecules in its active site for substrate recognition. The observed differences in the hydrogen bond network in the complex with ANF or 7ER may be due to the fact that ANF is an inhibitor.

Predicting three-dimensional conformations of peptides constructed of only glycine, alanine, aspartic acid, and valine

The GADV hypothesis is a form of the protein world hypothesis, which suggests that life originated from proteins (Lacey et al. 1999; Ikehara 2002; Andras 2006). In the GADV hypothesis, life is thought to have originated from primitive proteins constructed of only glycine, alanine, aspartic acid, and valine ([GADV]-proteins). In this study, the three-dimensional (3D) conformations of randomly generated short [GADV]-peptides were computationally investigated using replica-exchange molecular dynamics (REMD) simulations (Sugita and Okamoto 1999). Because the peptides used in this study consisted of only 20 residues each, they could not form certain 3D structures. However, the conformational tendencies of the peptides were elucidated by analyzing the conformational ensembles generated by REMD simulations. The results indicate that secondary structures can be formed in several randomly generated [GADV]-peptides. A long helical structure was found in one of the hydrophobic peptides, supporting the conjecture of the GADV hypothesis that many peptides aggregated to form peptide multimers with enzymatic activity in the primordial soup. In addition, these results indicate that REMD simulations can be used for the structural investigation of short peptides.

Mapping hydrophobicity on the protein molecular surface at atom-level resolution

A precise representation of the spatial distribution of hydrophobicity, hydrophilicity and charges on the molecular surface of proteins is critical for the understanding of the interaction with small molecules and larger systems. The representation of hydrophobicity is rarely done at atom-level, as this property is generally assigned to residues. A new methodology for the derivation of atomic hydrophobicity from any amino acid-based hydrophobicity scale was used to derive 8 sets of atomic hydrophobicities, one of which was used to generate the molecular surfaces for 35 proteins with convex structures, 5 of which, i.e., lysozyme, ribonuclease, hemoglobin, albumin and IgG, have been analyzed in more detail. Sets of the molecular surfaces of the model proteins have been constructed using spherical probes with increasingly large radii, from 1.4 to 20 Å, followed by the quantification of (i) the surface hydrophobicity; (ii) their respective molecular surface areas, i.e., total, hydrophilic and hydrophobic area; and (iii) their relative densities, i.e., divided by the total molecular area; or specific densities, i.e., divided by property-specific area. Compared with the amino acid-based formalism, the atom-level description reveals molecular surfaces which (i) present an approximately two times more hydrophilic areas; with (ii) less extended, but between 2 to 5 times more intense hydrophilic patches; and (iii) 3 to 20 times more extended hydrophobic areas. The hydrophobic areas are also approximately 2 times more hydrophobicity-intense. This, more pronounced "leopard skin"-like, design of the protein molecular surface has been confirmed by comparing the results for a restricted set of homologous proteins, i.e., hemoglobins diverging by only one residue (Trp37). These results suggest that the representation of hydrophobicity on the protein molecular surfaces at atom-level resolution, coupled with the probing of the molecular surface at different geometric resolutions, can capture processes that are otherwise obscured to the amino acid-based formalism.

Evaluation of influence of single nucleotide polymorphisms in cytochrome P450 2B6 on substrate recognition using computational docking and molecular dynamics simulation

In this study, we investigated the influence of single nucleotide polymorphisms on the conformation of mutated cytochrome P450 (CYP) 2B6 proteins using molecular dynamics (MD) simulation. Some of these mutations influence drug metabolism activities, leading to individual variations in drug efficacy and pharmacokinetics. Using computational docking, we predicted the structure of the complex between the antimalarial agent artemether and CYP2B6 whose conformations were obtained by MD simulation. The simulation demonstrated that the entire structure of the protein changes even when a single residue is mutated. Moreover, the structural flexibility is affected by the mutations and it may influence the enzyme activity. The results suggest that some of the inactive mutants cannot recognize artemether due to structural changes caused by the mutation.

[Development and validation of programs for ligand-binding-pocket search]

Searching for the ligand-binding pockets of proteins plays an important role in structure-based drug design (SBDD), which is based on knowledge of the three-dimensional structures of target proteins. In SBDD, small molecules that can interact with the target protein are designed. SBDD methods require the identification of ligand-binding pockets, in which ligand molecules interact with protein atoms. The computer programs for the detection of ligand-binding pockets are categorized into two types: one is programs using only geometric properties; and the other is programs using the physicochemical properties of proteins as well as geometry. This paper describes the development and evaluation of a program for ligand-binding pocket search. The program HBOP (Hydropho Bicity On a Protein) searches for ligand-binding pockets using hydrophobic potentials derived from experimentally determined functions. This is based on the fact that hydrophobicity plays a significant role in protein-ligand binding. The results of evaluation indicate that programs using physicochemical properties can discover actual ligand-binding pockets more efficiently than those using only geometric properties.

Structure-based CoMFA as a predictive model - CYP2C9 inhibitors as a test case

In this study, we tried to establish a general scheme to create a model that could predict the affinity of small compounds to their target proteins. This scheme consists of a search for ligand-binding sites on a protein, a generation of bound conformations (poses) of ligands in each of the sites by docking, identifications of the correct poses of each ligand by consensus scoring and MM-PBSA analysis, and a construction of a CoMFA model with the obtained poses to predict the affinity of the ligands. By using a crystal structure of CYP 2C9 and the twenty known CYP inhibitors as a test case, we obtained a CoMFA model with a good statistics, which suggested that the classification of the binding sites as well as the predicted bound poses of the ligands should be reasonable enough. The scheme described here would give a method to predict the affinity of small compounds with a reasonable accuracy, which is expected to heighten the value of computational chemistry in the drug design process.

Scaling and self-organized criticality in proteins I

The complexity of proteins is substantially simplified by regarding them as archetypical examples of self-organized criticality (SOC). To test this idea and elaborate on it, this article applies the Moret-Zebende SOC hydrophobicity scale to the large-scale scaffold repeat protein of the HEAT superfamily, PR65/A. Hydrophobic plasticity is defined and used to identify docking platforms and hinges from repeat sequences alone. The difference between the MZ scale and conventional hydrophobicity scales reflects long-range conformational forces that are central to protein functionality.