Protein unfolding by SDS: the microscopic mechanisms and the properties of the SDS-protein assembly.

The effects of detergent sodium dodecyl sulfate (SDS) on protein structure and dynamics are fundamental to the most common laboratory technique used to separate proteins and determine their molecular weights: polyacrylamide gel electrophoresis. However, the mechanism by which SDS induces protein unfolding and the microstructure of protein-SDS complexes remain largely unknown. Here, we report a detailed account of SDS-induced unfolding of two proteins-I27 domain of titin and ß-amylase-obtained through all-atom molecular dynamics simulations. Both proteins were found to spontaneously unfold in the presence of SDS at boiling water temperature on the time scale of several microseconds. The protein unfolding was found to occur via two distinct mechanisms in which specific interactions of individual SDS molecules disrupt the protein's secondary structure. In the final state of the unfolding process, the proteins are found to wrap around SDS micelles in a fluid necklace-and-beads configuration, where the number and location of bound micelles changes dynamically. The global conformation of the protein was found to correlate with the number of SDS micelles bound to it, whereas the number of SDS molecules directly bound to the protein was found to define the relaxation time scale of the unfolded protein. Our microscopic characterization of SDS-protein interactions sets the stage for future refinement of SDS-enabled protein characterization methods, including protein fingerprinting and sequencing using a solid-state nanopore.

SDS-assisted protein transport through solid-state nanopores.

Using nanopores for single-molecule sequencing of proteins - similar to nanopore-based sequencing of DNA - faces multiple challenges, including unfolding of the complex tertiary structure of the proteins and enforcing their unidirectional translocation through nanopores. Here, we combine molecular dynamics (MD) simulations with single-molecule experiments to investigate the utility of SDS (Sodium Dodecyl Sulfate) to unfold proteins for solid-state nanopore translocation, while simultaneously endowing them with a stronger electrical charge. Our simulations and experiments prove that SDS-treated proteins show a considerable loss of the protein structure during the nanopore translocation. Moreover, SDS-treated proteins translocate through the nanopore in the direction prescribed by the electrophoretic force due to the negative charge impaired by SDS. In summary, our results suggest that SDS causes protein unfolding while facilitating protein translocation in the direction of the electrophoretic force; both characteristics being advantageous for future protein sequencing applications using solid-state nanopores.

New insights in the activation of human cholesterol esterase to design potent anti-cholesterol drugs.

Primary hypercholesterolemia is the root cause for major health issues like coronary heart disease and atherosclerosis. Regulating plasma cholesterol level, which is the product of biosynthesis as well as dietary intake, has become one of the major therapeutic strategies to effectively control these diseases. Human cholesterol esterase (hCEase) is an interesting target involved in the regulation of plasma cholesterol level and thus inhibition of this enzyme is highly effective in the treatment of hypercholesterolemia. This study was designed to understand the activation mechanism that enables the enzyme to accommodate long chain fatty acids and to identify the structural elements for the successful catalysis. Primarily the activation efficiencies of three different bile salts were studied and compared using molecular dynamics simulations. Based on the conformations of major surface loops, hydrogen bond interactions, and distance analyses, taurocholate was concluded as the preferred activator of the enzyme. Furthermore, the importance of two bile salt binding sites (proximal and remote) and the crucial role of 7α-OH group of the bile salts in the activation of hCEase was examined and evidenced. The results of our study explain the structural insights of the activation mechanism and show the key features of the bile salts responsible for the enzyme activation which are very useful in hypolipidemic drug designing strategies.

Development of predictive quantitative structure-activity relationship model and its application in the discovery of human leukotriene A4 hydrolase inhibitors.

BACKGROUND: Human LTA4H catalyzes the conversion of LTA4 to LTB4 and plays a key role in innate immune responses. Inhibition of this enzyme can be a valid method in the treatment of inflammatory response exhibited through LTB4. RESULTS & DISCUSSION: The quantitative structure-activity relationship (QSAR) models were developed using genetic function approximation and validated. A training set of 26 diverse compounds and their molecular descriptors were used to develop highly correlating QSAR models. A six-descriptor model explaining the biological activity of the training and test sets with correlation values of 0.846 and 0.502, respectively, was selected as the best model and used in a database screening of drug-like Maybridge database followed by molecular docking. CONCLUSION: Based on the predicted potent inhibitory activities, expected binding mode and molecular interactions at the active site of hLTA4H final leads were selected as to be utilized in designing future hLTA4H inhibitors.

Exploration of virtual candidates for human HMG-CoA reductase inhibitors using pharmacophore modeling and molecular dynamics simulations.

3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) is a rate-controlling enzyme in the mevalonate pathway which involved in biosynthesis of cholesterol and other isoprenoids. This enzyme catalyzes the conversion of HMG-CoA to mevalonate and is regarded as a drug target to treat hypercholesterolemia. In this study, ten qualitative pharmacophore models were generated based on chemical features in active inhibitors of HMGR. The generated models were validated using a test set. In a validation process, the best hypothesis was selected based on the statistical parameters and used for virtual screening of chemical databases to find novel lead candidates. The screened compounds were sorted by applying drug-like properties. The compounds that satisfied all drug-like properties were used for molecular docking study to identify their binding conformations at active site of HMGR. The final hit compounds were selected based on docking score and binding orientation. The HMGR structures in complex with the hit compounds were subjected to 10 ns molecular dynamics simulations to refine the binding orientation as well as to check the stability of the hits. After simulation, binding modes including hydrogen bonding patterns and molecular interactions with the active site residues were analyzed. In conclusion, four hit compounds with new structural scaffold were suggested as novel and potent HMGR inhibitors.

Molecular modeling study on tunnel behavior in different histone deacetylase isoforms.

Histone deacetylases (HDACs) have emerged as effective therapeutic targets in the treatment of various diseases including cancers as these enzymes directly involved in the epigenetic regulation of genes. However the development of isoform-selective HDAC inhibitors has been a challenge till date since all HDAC enzymes possess conserved tunnel-like active site. In this study, using molecular dynamics simulation we have analyzed the behavior of tunnels present in HDAC8, 10, and 11 enzymes of class I, II, and IV, respectively. We have identified the equivalent tunnel forming amino acids in these three isoforms and found that they are very much conserved with subtle differences to be utilized in selective inhibitor development. One amino acid, methionine of HDAC8, among six tunnel forming residues is different in isoforms of other classes (glutamic acid (E) in HDAC10 and leucine (L) in HDAC 11) based on which mutations were introduced in HDAC11, the less studied HDAC isoform, to observe the effects of this change. The HDAC8-like (L268M) mutation in the tunnel forming residues has almost maintained the deep and narrow tunnel as present in HDAC8 whereas HDAC10-like (L268E) mutation has changed the tunnel wider and shallow as observed in HDAC10. These results explained the importance of the single change in the tunnel formation in different isoforms. The observations from this study can be utilized in the development of isoform-selective HDAC inhibitors.

Structural origins for the loss of catalytic activities of bifunctional human LTA4H revealed through molecular dynamics simulations.

Human leukotriene A4 hydrolase (hLTA4H), which is the final and rate-limiting enzyme of arachidonic acid pathway, converts the unstable epoxide LTA4 to a proinflammatory lipid mediator LTB4 through its hydrolase function. The LTA4H is a bi-functional enzyme that also exhibits aminopeptidase activity with a preference over arginyl tripeptides. Various mutations including E271Q, R563A, and K565A have completely or partially abolished both the functions of this enzyme. The crystal structures with these mutations have not shown any structural changes to address the loss of functions. Molecular dynamics simulations of LTA4 and tripeptide complex structures with functional mutations were performed to investigate the structural and conformation changes that scripts the observed differences in catalytic functions. The observed protein-ligand hydrogen bonds and distances between the important catalytic components have correlated well with the experimental results. This study also confirms based on the structural observation that E271 is very important for both the functions as it holds the catalytic metal ion at its location for the catalysis and it also acts as N-terminal recognition residue during peptide binding. The comparison of binding modes of substrates revealed the structural changes explaining the importance of R563 and K565 residues and the required alignment of substrate at the active site. The results of this study provide valuable information to be utilized in designing potent hLTA4H inhibitors as anti-inflammatory agents.

Computational studies of novel chymase inhibitors against cardiovascular and allergic diseases: mechanism and inhibition.

To provide a new idea for drug design, a computational investigation is performed on chymase and its novel 1,4-diazepane-2,5-diones inhibitors that explores the crucial molecular features contributing to binding specificity. Molecular docking studies of inhibitors within the active site of chymase were carried out to rationalize the inhibitory properties of these compounds and understand their inhibition mechanism. The density functional theory method was used to optimize molecular structures with the subsequent analysis of highest occupied molecular orbital, lowest unoccupied molecular orbital, and molecular electrostatic potential maps, which revealed that negative potentials near 1,4-diazepane-2,5-diones ring are essential for effective binding of inhibitors at active site of enzyme. The Bayesian model with receiver operating curve statistic of 0.82 also identified arylsulfonyl and aminocarbonyl as the molecular features favoring and not favoring inhibition of chymase, respectively. Moreover, genetic function approximation was applied to construct 3D quantitative structure-activity relationships models. Two models (genetic function approximation model 1 r(2) = 0.812 and genetic function approximation model 2 r(2) = 0.783) performed better in terms of correlation coefficients and cross-validation analysis. In general, this study is used as example to illustrate how combinational use of 2D/3D quantitative structure-activity relationships modeling techniques, molecular docking, frontier molecular orbital density fields (highest occupied molecular orbital and lowest unoccupied molecular orbital), and molecular electrostatic potential analysis may be useful to gain an insight into the binding mechanism between enzyme and its inhibitors.

Molecular dynamics simulation study and hybrid pharmacophore model development in human LTA4H inhibitor design.

Human leukotriene A4 hydrolase (hLTA4H) is a bi-functional enzyme catalyzes the hydrolase and aminopeptidase functions upon the fatty acid and peptide substrates, respectively, utilizing the same but overlapping binding site. Particularly the hydrolase function of this enzyme catalyzes the rate-limiting step of the leukotriene (LT) cascade that converts the LTA4 to LTB4. This product is a potent pro-inflammatory activator of inflammatory responses and thus blocking this conversion provides a valuable means to design anti-inflammatory agents. Four structurally very similar chemical compounds with highly different inhibitory profile towards the hydrolase function of hLTA4H were selected from the literature. Molecular dynamics (MD) simulations of the complexes of hLTA4H with these inhibitors were performed and the results have provided valuable information explaining the reasons for the differences in their biological activities. Binding mode analysis revealed that the additional thiophene moiety of most active inhibitor helps the pyrrolidine moiety to interact the most important R563 and K565 residues. The hLTA4H complexes with the most active compound and substrate were utilized in the development of hybrid pharmacophore models. These developed pharmacophore models were used in screening chemical databases in order to identify lead candidates to design potent hLTA4H inhibitors. Final evaluation based on molecular docking and electronic parameters has identified three compounds of diverse chemical scaffolds as potential leads to be used in novel and potent hLTA4H inhibitor design.

Potential human cholesterol esterase inhibitor design: benefits from the molecular dynamics simulations and pharmacophore modeling studies.

Human pancreatic cholesterol esterase (hCEase) is one of the lipases found to involve in the digestion of large and broad spectrum of substrates including triglycerides, phospholipids, cholesteryl esters, etc. The presence of bile salts is found to be very important for the activation of hCEase. Molecular dynamic simulations were performed for the apoform and bile salt complexed form of hCEase using the co-ordinates of two bile salts from bovine CEase. The stability of the systems throughout the simulation time was checked and two representative structures from the highly populated regions were selected using cluster analysis. These two representative structures were used in pharmacophore model generation. The generated pharmacophore models were validated and used in database screening. The screened hits were refined for their drug-like properties based on Lipinski's rule of five and ADMET properties. The drug-like compounds were further refined by molecular docking simulation using GOLD program based on the GOLD fitness score, mode of binding, and molecular interactions with the active site amino acids. Finally, three hits of novel scaffolds were selected as potential leads to be used in novel and potent hCEase inhibitor design. The stability of binding modes and molecular interactions of these final hits were re-assured by molecular dynamics simulations.

Molecular dynamics simulation study explaining inhibitor selectivity in different class of histone deacetylases.

Histone deacetylases (HDACs) are key regulators of gene expression and thereby compelling targets in the treatment of various cancers. Class- and isoform-selective HDAC inhibitors targeting the particular isoform to treat cancers without affecting the normal expression of other isoforms are highly desirable. Molecular dynamics simulations were performed with the set of selective inhibitors and HDAC isoforms of three different classes. The results were compared both within and across the isoforms. The hydrogen bonds between protein and inhibitors are directly correlated with the selective experimental activity. The calculated distances between important amino acids and the metal binding part of inhibitors have disclosed the optimal distance to be maintained by a selective inhibitor. In addition, the calculated non-bonded interaction energies between inhibitor and catalytic residues revealed that the subtle difference in the amino acids at the highly conserved active sites of HDAC isoforms effectively scripts the selectivity story observed experimentally. The results of this study provide valuable information in designing highly selective HDAC inhibitors.

Discovery and evaluation of potential sonic hedgehog signaling pathway inhibitors using pharmacophore modeling and molecular dynamics simulations.

Sonic hedgehog (Shh) plays an important role in the activation of Shh signaling pathway that regulates preservation and rebirth of adult tissues. An abnormal activation of this pathway has been identified in hyperplasia and various tumorigenesis. Hence the inhibition of this pathway using a Shh inhibitor might be an efficient way to treat a wide range of malignancies. This study was done in order to develop a lead chemical candidate that has an inhibitory function in the Shh signaling pathway. We have generated common feature pharmacophore models using three-dimensional (3D) structural information of robotnikinin, an inhibitor of the Shh signaling pathway, and its analogs. These models have been validated with fit values of robotnikinin and its analogs, and the best model was used as a 3D structural query to screen chemical databases. The hit compounds resulted from the screening docked into a proposed binding site of the Shh named pseudo-active site. Molecular dynamics (MD) simulations were performed to investigate detailed binding modes and molecular interactions between the hit compounds and functional residues of the pseudo-active site. The results of the MD simulation analyses revealed that the hit compounds can bind the pseudo-active site with high affinity than robotnikinin. As a result of this study, a candidate inhibitor (GK 03795) was selected as a potential lead to be employed in future Shh inhibitor design.

Pharmacophore based virtual screening, molecular docking studies to design potent heat shock protein 90 inhibitors.

The identification of important chemical features of Heat Shock Protein 90 (HSP90) inhibitors will be helpful to discover the potent candidate to inhibit the HSP90 activity. The best hypothesis from Hip-Hop, Hypo1, one hydrogen bond donor (HBD), two hydrogen bond acceptors (HBA), and two hydrophobic (H) and structure-based hypothesis, SB_Hypo1, one HBA, one HBD and four H features, were generated using Discovery Studio and LigandScout, respectively. Test and decoy sets were used to corroborate the best hypotheses and the validated hypotheses were used to screen the chemical databases. Subsequently, the screened compounds were filtered by applying the rule of five, ADMET and molecular docking. Finally, four compounds were obtained as novel leads to inhibit the HSP90 activity.

Potential virtual lead identification in the discovery of renin inhibitors: application of ligand and structure-based pharmacophore modeling approaches.

Renin, an enzyme by cleaving angiotensinogen to angiotensin-I, controls the first and rate-limiting step of renin-angiotensin system that is associated with blood pressure. Thus Ligand and structure-based pharmacophore models were developed in this study to identify new potential leads inhibiting this rate-limiting enzyme as an efficient way to treat blood pressure. X-ray predicted binding modes of most active compounds were used in ligand-based approach whereas the 3D structural information of renin was used in structure-based approach. Pharmacophore models were validated using various methods and utilized in database searching to identify potential hits. Drug-like filters and molecular docking studies led us identifying the final hits to be employed in designing new class of future renin inhibitors.

Discovery of potential integrin VLA-4 antagonists using pharmacophore modeling, virtual screening and molecular docking studies.

Very late antigen-4 (VLA-4) is an integrin protein, and its antagonists are useful as anti-inflammatory drugs. The aim of this study is to discover novel virtual lead compounds to use them in designing potent VLA-4 antagonists. A best pharmacophore model was generated with correlation coefficient of 0.935, large cost difference of 114.078, comprising two hydrogen bond acceptors and three hydrophobic features. It was further validated and used in database screening for potential VLA-4 antagonists. A homology model of VLA-4 was built and employed in molecular docking of screened hit compounds. Finally, two compounds were identified as potential virtual leads to be deployed in the designing of novel potent VLA-4 antagonists.

Pharmacophore-based virtual screening and Bayesian model for the identification of potential human leukotriene A4 hydrolase inhibitors.

Leukotriene A4 hydrolase (LTA4H), an enzyme involved in the conversion of LTA4 to LTB4, is an emerging and important anti-inflammatory target. This study demonstrates the development of quantitative pharmacophore hypothesis and Bayesian model and their applications in identification of potential human LTA4H (hLTA4H) inhibitors. The best hypothesis with a high correlation coefficient value of 0.951 was validated using different methods including a test set containing 136 compounds. It was further used as a three-dimensional query in database searching to retrieve virtual leads for hLTA4H inhibition. Molecular docking study was employed to identify the compounds that bind the active site with high affinity. Developed Bayesian model suggested molecular features favoring and not favoring the inhibition of hLTA4H.

Potent BACE-1 inhibitor design using pharmacophore modeling, in silico screening and molecular docking studies.

BACKGROUND: Beta-site amyloid precursor protein cleaving enzyme (BACE-1) is a single-membrane protein belongs to the aspartyl protease class of catabolic enzymes. This enzyme involved in the processing of the amyloid precursor protein (APP). The cleavage of APP by BACE-1 is the rate-limiting step in the amyloid cascade leading to the production of two peptide fragments Aß40 and Aß42. Among two peptide fragments Aß42 is the primary species thought to be responsible for the neurotoxicity and amyloid plaque formation that lead to memory and cognitive defects in Alzheimer's disease (AD). AD is a ravaging neurodegenerative disorder for which no disease-modifying treatment is currently available. Inhibition of BACE-1 is expected to stop amyloid plaque formation and emerged as an interesting and attractive therapeutic target for AD. METHODS: Ligand-based computational approach was used to identify the molecular chemical features required for the inhibition of BACE-1 enzyme. A training set of 20 compounds with known experimental activity was used to generate pharmacophore hypotheses using 3D QSAR Pharmacophore Generation module available in Discovery studio. The hypothesis was validated by four different methods and the best hypothesis was utilized in database screening of four chemical databases like Maybridge, Chembridge, NCI and Asinex. The retrieved hit compounds were subjected to molecular docking study using GOLD 4.1 program. RESULTS: Among ten generated pharmacophore hypotheses, Hypo 1 was chosen as best pharmacophore hypothesis. Hypo 1 consists of one hydrogen bond donor, one positive ionizable, one ring aromatic and two hydrophobic features with high correlation coefficient of 0.977, highest cost difference of 121.98 bits and lowest RMSD value of 0.804. Hypo 1 was validated using Fischer randomization method, test set with a correlation coefficient of 0.917, leave-one-out method and decoy set with a goodness of hit score of 0.76. The validated Hypo 1 was used as a 3D query in database screening and retrieved 773 compounds with the estimated activity value <100 nM. These hits were docked into the active site of BACE-1 and further refined based on molecular interactions with the essential amino acids and good GOLD fitness score. CONCLUSION: The best pharmacophore hypothesis, Hypo 1, with high predictive ability contains chemical features required for the effective inhibition of BACE-1. Using Hypo 1, we have identified two compounds with diverse chemical scaffolds as potential virtual leads which, as such or upon further optimization, can be used in the designing of new BACE-1 inhibitors.

Molecular docking and pharmacophore filtering in the discovery of dual-inhibitors for human leukotriene A4 hydrolase and leukotriene C4 synthase.

Combination of drugs for multiple targets has been a standard treatment in treating various diseases. A single chemical entity that acts upon multiple targets is emerging nowadays because of their predictable pharmacokinetic and pharmacodynamic properties. We have employed a computer-aided methodology combining molecular docking and pharmacophore filtering to identify chemical compounds that can simultaneously inhibit the human leukotriene hydrolase (hLTA4H) and the human leukotriene C4 synthase (hLTC4S) enzymes. These enzymes are the members of arachidonic acid pathway and act upon the same substrate, LTA4, producing different inflammatory products. A huge set of 4966 druglike compounds from the Maybridge database were docked into the active site of hLTA4H using the GOLD program. Common feature pharmacophore models were developed from the known inhibitors of both the targets using Accelrys Discovery Studio 2.5. The hits from the hLTA4H docking were filtered to match the chemical features of both the pharmacophore models. The compounds that resulted from the pharmacophore filtering were docked into the active site of hLTC4S and the hits those bind well at both the active sites and matched the pharmacophore models were identified as possible dual inhibitors for hLTA4H and hLTC4S enzymes. Reverse validation was performed to ensure the results of the study.

Development, evaluation and application of 3D QSAR Pharmacophore model in the discovery of potential human renin inhibitors.

BACKGROUND: Renin has become an attractive target in controlling hypertension because of the high specificity towards its only substrate, angiotensinogen. The conversion of angiotensinogen to angiotensin I is the first and rate-limiting step of renin-angiotensin system and thus designing inhibitors to block this step is focused in this study. METHODS: Ligand-based quantitative pharmacophore modeling methodology was used in identifying the important molecular chemical features present in the set of already known active compounds and the missing features from the set of inactive compounds. A training set containing 18 compounds including active and inactive compounds with a substantial degree of diversity was used in developing the pharmacophore models. A test set containing 93 compounds, Fischer randomization, and leave-one-out methods were used in the validation of the pharmacophore model. Database screening was performed using the best pharmacophore model as a 3D structural query. Molecular docking and density functional theory calculations were used to select the hit compounds with strong molecular interactions and favorable electronic features. RESULTS: The best quantitative pharmacophore model selected was made of one hydrophobic, one hydrogen bond donor, and two hydrogen bond acceptor features with high a correlation value of 0.944. Upon validation using an external test set of 93 compounds, Fischer randomization, and leave-one-out methods, this model was used in database screening to identify chemical compounds containing the identified pharmacophoric features. Molecular docking and density functional theory studies have confirmed that the identified hits possess the essential binding characteristics and electronic properties of potent inhibitors. CONCLUSION: A quantitative pharmacophore model of predictive ability was developed with essential molecular features of a potent renin inhibitor. Using this pharmacophore model, two potential inhibitory leads were identified to be used in designing novel and future renin inhibitors as antihypertensive drugs.