Abstract

Urea concentration dependent denaturation of proteins and nucleic acids has been widely used in obtaining (un)folding pathways and in calculating the free energies. Molecular dynamics simulations were performed on a 22-nt RNA hairpin in aqueous solution environment and in different concentrations (1-8M) of urea. The energetic and structural aspects of the role of urea in denaturating the RNA hairpin were investigated. In agreement with experimental studies, the RNA undergoes denaturation at higher concentrations of urea (> 6M). Surprisingly, the hairpin was observed to be more stable at lower concentrations of urea (1-2M) even compared to the RNA in aqueous environment. Various structural, energetic and solvation properties were analyzed to understand the mechanism of the interaction of urea with the hairpin. It was observed that urea does not directly facilitate the opening of the base pairs that leads to denaturation at higher concentrations. Instead, the open states of the RNA are stabilized by via hydrogen bonding interactions and stacking interactions thereby stabilizing the denatured form of the RNA.

Abstract

Transannular Diels-Alder reaction (TADA) combines traditional pericyclic and intramolecular reactions, and has been shown to be one of the most efficient chemical transformations for synthesizing complicated natural products. TADA reactions occur in (x+y+2)-membered triene macrocycles, which contain both the diene and the dienophile, to form A.B.C[x.6.y] type tricyclic compounds. In addition, these macrocycles were shown to interconvert among its isomers via [1,5]-sigmatropic hydrogen shifts. The stereochemical outcome of the TADA reactions depends on the energetics of various possible transition states. Initially, a validation study was undertaken to assess the performance of various ab initio (HF, MPx, and CC) and hybrid density functional B3LYP methods using a variety of basis sets. Comparison of the reaction barriers, and reaction energies from various methods indicate that B3LYP/6-31G* level is appropriate enough for accurately modeling this class of reactions. All possible reaction pathways involving the TADA and 1,5-sigmatropic reactions of six different 14-membered triene molecules were studied using B3LYP/cc-pVTZ were calculated. Based on the reaction energy barriers and conformational properties of the reactants, the reactivities of these molecules will be discussed.

Abstract

Proteins, which are the most common drug targets, are flexible and can exist in various conformers that are energetically competitive. Hence, it is crucial to consider its dynamic behavior. Most notable methods that incorporate flexibility of protein are discussed here. Structural knowledge of molecular targets (or drug receptors), usually proteins, has transformed the drug design process in the last three decades or so. While most of the drugs that were discovered 30 years ago are by serendipity and ‘trial and error’, rational drug design approaches are more focused. Rational drug design techniques use structure of the drug receptor or structure of ligands that are shown to bind to the target to identify potential drug candidates. Approaches that use the structure of drug receptor for drug discovery are referred to as structure based drug design (SBDD). X-ray crystallography and NMR spectroscopy have been in the forefront in protein structure determination. Several computational methods have been developed and new methods are being proposed for protein structure prediction from the primary sequence (for eg. homology modeling); however, they suffer from several caveats. Currently, use of SBDD has become a standard exercise as part of drug discovery and development both in industry and academia. Typically, the process involves obtaining the structure of the target protein; identification of active site; virtual screening of a small molecule database (containing chemically diverse structures of small molecules in the order of a million) and identification of potential ligands based on a chosen scoring function. Ideally, docking process involved in virtual screening and calculating the binding energy should allow the protein and the ligand to change their conformations to effectively bind to each other. Ligands being smaller compounds (typically containing tens of nonhydrogen atoms), their conformational changes can be modeled with reasonable accuracy. However, explicit modeling of protein flexibility involves a lot of computer time especially considering that a million compounds have to be screened and hence is not feasible. In short, a compromise between ‘quick answer’ and ‘right answer’ is made in docking calculations for practical applications. Recently, allowing protein to be flexible at least partially has become possible, thanks to development of efficient algorithms and, availability of faster processors, larger storage and RAM. Several approximations have been proposed to accommodate protein flexibility of which few of the notable ones are discussed in the article. The readers are suggested to refer additional resources on structure based drug design, which are given at the end.

Abstract

Proteins from hyperthermophilic microorganisms possess unique structurefunction properties for surviving high temperatures and for exhibiting optimal activity. In an attempt to understand the structural and energetic factors that are responsible for the thermal stability, molecular dynamics (MD) simulations were performed on Sso7d and Sac7d chromosomal proteins from S. solfataricus and S. acidocaldarius respectively. Consistent with experimental data, the proteins are quite stable at 300 and 360 K, but were found to undergo denaturation at higher temperature. Both proteins exhibit similar hierarchical unfolding pathways, which is explained based on the calculated intramolecular interaction energies. Differential dynamic behaviors of these proteins were examined, and possible roles of enzymatic activity of Sso7d are proposed. Structural, energetic, dynamic and solvation properties that influence the stability of these proteins will be discussed. The importance of hydrophobic interactions on their thermal stability will be presented using calculations on a mutant (F31A in Sso7d). These proteins are also capable of binding to DNA in a nonspecific fashion, and upon binding, melting temperature of the DNA was found to increase by about 40 K. MD simulations were also performed on protein-DNA complexes to investigate the stability of the oligonucleotide. Possible factors that facilitate the stability of these binary complexes in extraordinary thermal conditions will be discussed based on intra- and intermolecular interaction energies, correlated movements between the protein and DNA, solvation properties, and other structural parameters.

Abstract

Computational approaches are being successfully utilized for the design of small molecules that could be potential substrates for various biological targets both in academia and pharmaceutical industry. Over the past two decades or so, various computational techniques have been developed and improvements on the existing methodologies were proposed to accomplish high accuracy/ predictability of molecular properties. Consideration of the flexible nature of proteins in structure based drug design studies has been a bottleneck mainly due to the huge demand of computational and actual time. Hence most of the docking studies consider the biological macromolecules to be rigid and allow only the conformational changes of the small molecules. Similarly, the ligand based drug design approaches tend to focus more on the global minima of the small molecules. This could lead to incorrect model and hence false predictions since this approximation may not be true in cases where the global minima essentially is not the bioactive conformer – the conformer that binds to the target. Recently, advanced methods have been proposed to consider the flexible nature of the molecules. Molecular dynamics (MD) simulations have been shown to be a straightforward means to include the flexibility of both ligands and biomolecular targets. MD simulations are invaluable computational methods that are extensively used for deriving information of the structure, dynamics and energetic properties of various biomolecules including proteins, nucleic acids and lipids. The need for consideration of dynamic nature of the biomolecular targets will be demonstrated and the advantages of MD simulations to overcome this limitation will be discussed. Basic principles of MD simulations will be discussed and an introduction to biomolecular force fields will be given. Illustrated examples of the applications of MD simulations to ligand based and structure based drug design approaches will be presented.