Current Topics in Medicinal Chemistry - Volume 13, Issue 10, 2013

In drug design and enzyme engineering, the information of interactions between receptors and ligands is crucially important. In many cases, the protein structures and drug-target complex structures are determined by a delicate balance of several weak molecular interaction types. Among these interaction forces several unconventional interactions play important roles, however, less familiar for researchers. The cation-π interaction is a unique noncovalent interaction only acting between aromatic amino acids and organic cations (protonated amino acids) and inorganic cations (proton and metallic). This article reports new study results in the interaction strength, the behaviors and the structural characters of cation-π interactions between aromatic amino acids (Phe, Tyr, and Trp) and organic and inorganic cations (Lys+, Arg+, H+, H3O+, Li+, Na+, K+, Ca2+, and Zn2+) in gas phase and in solutions (water, acetonitrile, and cyclohexane). Systematical research revealed that the cation-π interactions are point-to-plane (aromatic group) interactions, distance and orientationdependent, and the interaction energies change in a broad range. In gas phase the cation-π interaction energies between aromatic amino acids (Phe, Tyr, and Trp) and metallic cations (Li+, Na+, K+, Ca2+, and Zn2+) are in the range -12 to -160 kcal/mol, and the interaction energies of protonated amino acids (Arg+ and Lys+) are in the range from -9 to -18 kcal/mol. In solutions the cation-π energies decrease with the dielectric constant ε of solvents. However, in aqueous solution the cation-π energies of H3O+ and protonated amino acids are less affected by solvation effects. The applications of unconventional interaction forces in drug design and in protein engineering are introduced.

Transmissible spongiform encephalopathies (TSEs) are prion protein misfolding diseases that involve the accumulation of an abnormal β-sheet-rich prion protein aggregated form (PrPsc) of the normal α- helix-rich prion protein (PrPc) within the central nervous system (CNS) and other organs. On account of its large size and insolubility properties, characterization of PrPsc is quite difficult. A soluble intermediate, called PrPβ or βo, exhibiting many of the same features as PrPsc, can be generated using a combination of low pH and/or mild denaturing conditions. Here, we review the current knowledge on the following five issues relevant to the conversion mechanisms of PrPc to PrPsc : (1) How is the Stability of the Helical Structures in the Native PrPc Related to the Primary Structure of the PrPc (2) Why the Low pH Solution System is a Ideal Trigger of PrPc to PrPsc Conversion (3) How are the Structural and Dynamical Characteristics of the α-helixrich Intermediates Determined using NMR Data (4) How are the Premolten (PrPα4 and PrPαβ) and β-Oligomer (PrPβ) Intermediates Detected and Assayed, and (5) Can the Disordered N-terminal Domain be folded into the Structural Segment? Particularly, Chou's wenxiang diagram (http://en.wikipedia.org/wiki/Wenxiang_diagram) was introduced for providing an intuitive picture. This review may help to further understand the prion protein misfolding mechanism.

Members of the 17β-hydroxysteroid dehydrogenase (17β-HSD) superfamily perform distinct multiple catalyses by the same enzyme, apparently contradictory to the long-held beliefs regarding the high specificity of enzymes. Surprisingly, these multi-catalyses can combine synergistically in vitro and in vivo and their dysfunction may result in the stimulation of breast or prostate cancer. 17β-HSD1 possesses high estrogen activation activity, while its androgen inactivation is significant for decreasing the week concentration of dihydrotestosterone (DHT) in breast cancer cells, an important factor for cell proliferation. 17β-HSD5 can also carry out multiple catalyses in hormone-dependent cancer cells. In addition to 17β-HSDs 1 and 5 some other family members possess such dual-activity as well, and their inhibition decreases hormone- dependent cancer proliferation. The multi-specificity of 17β-HSD1 is structurally based on the pseudo-symmetric androgens that can accommodate the narrow enzyme substrate tunnel by both normal and alternative binding. The atypical family member 17β-HSD5 possesses a spacious binding site, which is accessible to several substrates. Expression of 17β- HSD1 can also control other estrogen-responsive elements such as pS2, and can regulate steroid-hormone receptors. The fundamental involvement of 17β-HSD1 in catalysis and gene regulation underlies its close relationship to breast cancer, attributable to its long evolutionary process. These observations stimulated detailed study of steroid-converting enzyme inhibition. The most significant efforts in designing 17β-HSD1 inhibitors in decades have progressed through structure activity relationship studies supported by the availability of both small and protein molecule structures, with the elimination of residual estrogenic activity in the inhibitors. The first non-estrogenic inhibitors of 17β-HSD1 to show activity in vivo (breast cancer animal model) are now reported.

Despite the tremendous progress in the field of drug designing, discovering a new drug molecule is still a challenging task. Drug discovery and development is a costly, time consuming and complex process that requires millions of dollar and 10-15 years to bring new drug molecules in the market. This huge investment and long-term process are attributed to high failure rate, complexity of the problem and strict regulatory rules, in addition to other factors. Given the availability of ‘big’ data with ever improving computing power, it is now possible to model systems which is expected to provide time and cost effectiveness to drug discovery process. Computer Aided Drug Designing (CADD) has emerged as a fast alternative method to bring down the cost involved in discovering a new drug. In past, numerous computer programs have been developed across the globe to assist the researchers working in the field of drug discovery. Broadly, these programs can be classified in three categories, freeware, shareware and commercial software. In this review, we have described freeware or open-source software that are commonly used for designing therapeutic molecules. Major emphasis will be on software and web services in the field of chemo- or pharmaco-informatics that includes in silico tools used for computing molecular descriptors, inhibitors designing against drug targets, building QSAR models, and ADMET properties.

Nuclear receptors (NRs) are members of a large superfamily of evolutionarily related DNA-binding transcription factors. They regulate diverse functions, such as homeostasis, reproduction, development and metabolism. As nuclear receptors bind small molecules that can easily be modified by drug design, and control functions associated with major diseases (e.g. cancer, osteoporosis and diabetes), they are promising pharmacological targets. According to their different action mechanisms or functions, NR superfamily has been classified into seven families: NR1 (thyroid hormone like), NR2 (HNF4-like), NR3 (estrogen like), NR4 (nerve growth factor IB-like), NR5 (fushi tarazu-F1 like), NR6 (germ cell nuclear factor like), and NR0 (knirps or DAX like). With the avalanche of protein sequences generated in the postgenomic age, Scientists are facing the following challenging problems. Given an uncharacterized protein sequence, how can we identify whether it is a nuclear receptor? If it is, what family even subfamily it belongs to? To address these problems, many cheminformatics tools have been developed for nuclear receptor prediction. The current review is mainly focused on this field, including the functions, computational methods and limitations of these tools.

Small molecules are involved in metabolic pathways responsible for many biological activities. Therefore it is essential to study them to uncover the unknown biological function of highly complex living systems. It is a crucial step in modern drug discovery to correctly and effectively discover small molecules’ biological function since small molecules are related to many protein functions and biological processes. This paper presents the application of cheminformatics approaches in predicting small molecule’s (ligand’s) biological function in metabolic pathway. Many examples of success in identification and prediction in the area of small molecule metabolic pathway mapping and small molecule-protein interaction prediction have been discussed.

The human angiontensin-converting enzyme I (hACEI) is a zinc metalloproteinase that hydrolytically cleaves a C-terminal dipeptide from a wide range of peptide substrates, and it plays an important role in regulating blood pressure. MD simulations and interaction energy calculations for docking and crystal structures were performed to investigate the correct conformation of the ACE with enalaprilat and nanopepetide. The analysis of root-mean-squrared fluctuation (RMSF), which is usually applied to measure the mobility and flexibility of the proteins, and dynamic correlation of residues show that the fluctuation pattern of the each two structure of the same ligand is almost the same mode. Hydrogen bond analysis shows that the correct crystal conformation is more stable than a wrong docking conformation. In addition, we are demonstrating that calculating interaction energy between protein and its ligands is an accurate and efficient way to select the correct conformation from docking conformations.

Human carboxylesterase I (hCES 1) plays an important role in the metabolism and activation of prodrugs, such as, the hydrolysis of a variety of drugs of prodrugs featuring an ester, amide or carbamate function. The bindings of the substrates of different lengths and cocaine to hCES1 at two different binding sites, catalytic site and Z-site, were studies through MD simulations. For each case, the correlation analysis has been performed to explore the binding patterns of a broad range of substrates binding to the hCES1.

Sucrose hydrolytic enzymes, widely used in a variety of food industries, employ sucrose as a substrate. In addition to their hydrolysis activities, they have other recently discovered characteristics that should make them useful for medical applications. Here, the two enzymes sucrose phosphorylase and invertase are discussed. Sucrose phosphorylase glycosylates non-carbohydrate small molecules and invertase can be used in a portable and personal biosensor to quantify a variety of analytical targets.

Owing to their ability in destroying or slowing down the growth of bacteria, antibiotics have been widely used to treat the bacterial infections. However, because of the long-term and irresponsible use of antibiotics, resistance to antibiotics has become a serious problem directly threatening the public health worldwide. To fight against and resist β- lactam antibiotics, bacteria usually employed β-lactamases, especially the metallo-β-lactamases, to hydrolyze the C-N bond of the β-lactam ring so as to inactivate the antibiotics. In this minireview, we are to summarize the structural features of the metallo-β-lactamases, as well as their antibiotic binding modes and resistance mechanisms, in hopes that the discussion and analysis presented in this paper can stimulate new strategies to overcome the resistance problem and find novel inhibitors against the metallo-β-lactamases.