Influence of Hydroxyproline on Mechanical Behavior of Collagen Mimetic Proteins Under Fraying Deformation-Molecular Dynamics Investigations.

Molecular dynamics modeling is used to simulate, model, and analyze mechanical deformation behavior and predictive properties of three different synthetic collagen proteins obtained from RSC-PDB, 1BKV, 3A08, and 2CUO, with varying concentrations of hydroxyproline (HYP). Hydroxyproline is credited with providing structural support for the collagen protein molecules. Hydroxyproline's influence on these three synthetic collagen proteins' mechanical deformation behavior and predictive properties is investigated in this paper. A detailed study and inference of the protein's mechanical characteristics associated with HYP content are investigated through fraying deformation behavior. A calculated Gibbs free energy value (ΔG) of each polypeptide α chain that corresponds with a complete unfolding of a single polypeptide α-chain from a triple-helical protein is obtained with umbrella sampling. The force needed for complete separation of the polypeptide α-chain from the triple-helical protein is analyzed for proteins to understand the influence of HYP concentration and is discussed in this paper. Along with a difference in ΔG, different unfolding pathways for the molecule and individual chains are observed. The correlation between the fraying deformation mechanical characteristics and the collagen proteins' hydroxyproline content is provided in this study via the three collagen proteins' resulting binding energies.

Molecular modeling and SPRi investigations of interleukin 6 (IL6) protein and DNA aptamers.

Interleukin 6 (IL6), an inflammatory response protein has major implications in immune-related inflammatory diseases. Identification of aptamers for the IL6 protein aids in diagnostic, therapeutic, and theranostic applications. Three different DNA aptamers and their interactions with IL6 protein were extensively investigated in a phosphate buffed saline (PBS) solution. Molecular-level modeling through molecular dynamics provided insights of structural, conformational changes and specific binding domains of these protein-aptamer complexes. Multiple simulations reveal consistent binding region for all protein-aptamer complexes. Conformational changes coupled with quantitative analysis of center of mass (COM) distance, radius of gyration (Rg), and number of intermolecular hydrogen bonds in each IL6 protein-aptamer complex was used to determine their binding performance strength and obtain molecular configurations with strong binding. A similarity comparison of the molecular configurations with strong binding from molecular-level modeling concurred with Surface Plasmon Resonance imaging (SPRi) for these three aptamer complexes, thus corroborating molecular modeling analysis findings. Insights from the natural progression of IL6 protein-aptamer binding modeled in this work has identified key features such as the orientation and location of the aptamer in the binding event. These key features are not readily feasible from wet lab experiments and impact the efficacy of the aptamers in diagnostic and theranostic applications.

Molecular Dynamics Simulation Analysis of Anti-MUC1 Aptamer and Mucin 1 Peptide Binding.

Aptasensors utilize aptamers as bioreceptors. Aptamers are highly efficient, have a high specificity and are reusable. Within the biosensor the aptamers are immobilized to maximize their access to target molecules. Knowledge of the orientation and location of the aptamer and peptide during binding could be gained through computational modeling. Experimentally, the aptamer (anti-MUC1 S2.2) has been identified as a bioreceptor for breast cancer biomarker mucin 1 (MUC1) protein. However, within this protein lie several peptide variants with the common sequence APDTRPAP that are targeted by the aptamer. Understanding orientation and location of the binding region for a peptide-aptamer complex is critical in their biosensor applicability. In this study, we investigate through computational modeling how this peptide sequence and its minor variants affect the peptide-aptamer complex binding. We use molecular dynamics simulations to study multiple peptide-aptamer systems consisting of MUC1 (APDTRPAP) and MUC1-G (APDTRPAPG) peptides with the anti-MUC1 aptamer under similar physiological conditions reported experimentally. Multiple simulations of the MUC1 peptide and aptamer reveal that the peptide interacts between 3' and 5' ends of the aptamer but does not fully bind. Multiple simulations of the MUC1-G peptide indicate consistent binding with the thymine loop of the aptamer, initiated by the arginine residue of the peptide. We find that the binding event induces structural changes in the aptamer by altering the number of hydrogen bonds within the aptamer and establishes a stable peptide-aptamer complex. In all MUC1-G cases the occurrence of binding was confirmed by systematically studying the distance distributions between peptide and aptamers. These results are found to corroborate well with experimental study reported in the literature that indicated a strong binding in the case of MUC1-G peptide and anti-MUC1 aptamer. Present MD simulations highlight the role of the arginine residue of MUC1-G peptide in initiating the binding. The addition of the glycine residue to the peptide, as in the case of MUC1-G, is shown to yield a stable binding. Our study clearly demonstrates the ability of MD simulations to obtain molecular insights for peptide-aptamer binding, and to provide details on the orientation and location of binding between the peptide-aptamer that can be instrumental in biosensor development.

Computational modeling of peptide-aptamer binding.

Evolution is the progressive process that holds each living creature in its grasp. From strands of DNA evolution shapes life with response to our ever-changing environment and time. It is the continued study of this most primitive process that has led to the advancement of modern biology. The success and failure in the reading, processing, replication, and expression of genetic code and its resulting biomolecules keep the delicate balance of life. Investigations into these fundamental processes continue to make headlines as science continues to explore smaller scale interactions with increasing complexity. New applications and advanced understanding of DNA, RNA, peptides, and proteins are pushing technology and science forward and together. Today the addition of computers and advances in science has led to the fields of computational biology and chemistry. Through these computational advances it is now possible not only to quantify the end results but also visualize, analyze, and fully understand mechanisms by gaining deeper insights. The biomolecular motion that exists governing the physical and chemical phenomena can now be analyzed with the advent of computational modeling. Ever-increasing computational power combined with efficient algorithms and components are further expanding the fidelity and scope of such modeling and simulations. This chapter discusses computational methods that apply biological processes, in particular computational modeling of peptide-aptamer binding.

Polymer micelle assisted transport and delivery of model hydrophilic components inside a biological lipid vesicle: a coarse-grain simulation study.

Understanding drug transportation and delivery mechanism from a molecular viewpoint is essential to find better treatment pathways. Despite the fact that many significant drugs such as anticancer doxorubicin and mitoxantrone are predominantly hydrophilic, an efficient methodology to deliver hydrophilic drug components is not well established. Here we explore this problem by studying "patchy" polymeric micelle assisted hydrophilic component transportation across a lipid membrane and delivery inside a biological lipid vesicle. Using the MARTINI force field as the basis, we study the interaction of polymeric micelle with DPPC lipid vesicles in detail. In order to facilitate hydrophilic drug transportation study, a primitive CG model for hydrophilic drug component is used. Extensive simulations carried out over hundreds of nanoseconds demonstrate successful encapsulation, transportation of hydrophilic components by patchy polymeric micelles. Results show the polymeric micelle releases a significant portion of hydrophilic contents inside the lipid vesicle. The present simulation study also reveals a possible mechanism for efficient hydrophilic component transportation and delivery. Insights from this study could potentially help the experimental community to design better delivery vehicles, especially for hydrophilic drug molecules.

Expression of myosin heavy-chain isoforms in the respiratory muscles following inspiratory resistive breathing.

We investigated the effect of inspiratory resistive breathing (IRB) on the expression of the genes encoding fast and slow isoforms of myosin heavy chain (MyHC) in respiratory muscles. Eleven mongrel dogs were studied for baseline MyHC messenger RNA (mRNA) expression, seven of which were also used to study the effects of IRB. For this latter objective, awake and spontaneously breathing animals were subjected to 2 h of IRB (80 cm H(2)O/L/s) per day for four consecutive days. mRNA expression was assessed in the diaphragm, external intercostal muscle, and a limb muscle, using both slot- blot and in situ hybridizations with isoform-specific probes. A current semiquantitative scoring method (from 0 to 4) was used to quantify the in situ mRNA expression levels, and slot-blot data were analyzed with densitometry. Prior to IRB, slow- and fast-MyHC mRNA expression was moderate, similar, and homogeneous throughout the different regions of the diaphragm, with scores of 1.50 +/- 0.54 (mean +/- SD) for slow and 2.13 +/- 0.35 for fast mRNAs in the costal region of the diaphragm, and of 1.81 +/- 0.37 for slow and 2. 13 +/- 0.64 for fast mRNAs in the crural region of the diaphragm. Although expression of fast-MyHC mRNA remained unchanged after IRB, the relative expression of the mRNA for the slow isoform increased in costal (+30%), crural (+12%), and external intercostal (+27%) muscles. MyHC mRNA expression did not change in limb muscles. We conclude that breathing with a moderate inspiratory resistance for a short period induces the expression of slow MyHC in respiratory muscles.