Ensemble perspective for catalytic promiscuity: calorimetric analysis of the active site conformational landscape of a detoxification enzyme

Enzymological paradigms have shifted recently to acknowledge the biological importance of catalytic promiscuity. However, catalytic promiscuity is a poorly understood property, and no thermodynamic treatment has described the conformational landscape of promiscuous versus substrate-specific enzymes. Here, two structurally similar glutathione transferase (GST, glutathione S-transferase) isoforms with high specificity or high promiscuity are compared. Differential scanning calorimetry (DSC) indicates a reversible low temperature transition for the promiscuous GSTA1-1 that is not observed with substrate-specific GSTA4-4. This transition is assigned to rearrangement of the C terminus at the active site of GSTA1-1 based on the effects of ligands and mutations. Near-UV and far-UV circular dichroism indicate that this transition is due to repacking of tertiary contacts with the remainder of the subunit, rather than "unfolding" of the C terminus per se. Analysis of the DSC data using a modified Landau theory indicates that the local conformational landscape of the active site of GSTA1-1 is smooth, with barrierless transitions between states. The partition function of the C-terminal states is a broad unimodal distribution at all temperatures within this DSC transition. In contrast, the remainder of the GSTA1-1 subunit and the GSTA4-4 protein exhibit folded and unfolded macrostates with a significant energy barrier separating them. Their partition function includes a sharp unimodal distribution of states only at temperatures that yield either folded or unfolded macrostates. At intermediate temperatures the partition function includes a bimodal distribution. The barrierless rearrangement of the GSTA1-1 active site within a local smooth energy landscape suggests a thermodynamic basis for catalytic promiscuity.     

A quantitative structure-activity relationship study for structurally diverse HIV-1 protease inhibitors: contribution of conformational flexibility to inhibitory activity

In this study, we investigated by linear regression model the SAR data of the 15 HIV-1 protease inhibitors possessing structurally diverse scaffolds. First, a regression model was developed only using the enzyme-inhibitor interaction energy as a term of the model, but did not provide a good correlation with the inhibitory activity (R² = 0.580 and Q² = 0.500). Then, we focused on the conformational flexibility of the inhibitors which may represent the diversity of the inhibitors, and added two conformational parameters into the model, respectively: the number of rotatable bonds of ligands (ΔSrot) and the distortion energy of ligands (ΔElig). The regression model by adding ΔElig successfully improved the quality of the model (R² = 0.771 and Q² = 0.713) while the model with ΔSrot was unsuccessful. The prediction for a training inhibitor by the ΔElig model also showed good agreement with experimental activity. These results suggest that the conformational flexibility of HIV-1 protease inhibitors directly contributes to the enzyme inhibition.     

Conformational transmission in ATP synthase during catalysis: Search for large structural changes

Escherichia coli ATP synthase has eight subunits and functions through transmission of conformational changes between subunits. Defective mutation at Gly-149 was suppressed by the second mutations at the outer surface of the subunit, indicating that the defect by the first mutation was suppressed by the second mutation through long range conformation transmission. Extensive mutant/pseudorevertant studies revealed that / and / subunits interactions are important for the energy coupling between catalysis and H⁺ translocation. In addition, long range interaction between amino and carboxyl terminal regions of the subunit has a critical role(s) for energy coupling. These results suggest that the dynamic conformation change and its transmission are essential for ATP synthase.     

Towards understanding the unbound state of drug compounds: Implications for the intramolecular reorganization energy upon binding

There has been an explosion of structural information for pharmaceutical compounds bound to biological targets, but the conformations and dynamics of compounds free in solution are poorly characterized, if at all. Yet, knowledge of the unbound state is essential to understand the fundamentals of molecular recognition, including the much debated conformational intramolecular reorganization energy of a compound upon binding (ΔE_Reorg). Also, dependable observation of the unbound compounds is important for ligand-based drug discovery, e.g. with pharmacophore modelling. Here, these questions are addressed with long (⩾0.5 μs) state-of-the-art molecular dynamics (MD) simulations of 26 compounds (including 7 approved drugs) unbound in explicit solvent. These compounds were selected to be chemically diverse, with a range of flexibility, and good quality bioactive X-ray structures. The MD-simulated free compounds are compared to their bioactive structure and conformers generated with ad hoc sampling in vacuo or with implicit generalized Born (GB) aqueous solvation models. The GB conformational models clearly depart from those obtained in explicit solvent, and suffer from conformational collapse almost as severe as in vacuo. Thus, the global energy minima in vacuo or with GB are not suitable representations of the unbound state, which can instead be extensively sampled by MD simulations. Many, but not all, MD-simulated compounds displayed some structural similarity to their bioactive structure, supporting the notion of conformational pre-organization for binding. The ligand–protein complexes were also simulated in explicit solvent, to estimate ΔE_Reorg as an enthalpic difference ΔH_Reorg between the intramolecular energies in the bound and unbound states. This fresh approach yielded ΔH_Reorg values ⩽ 6 kcal/mol for 18 out of 26 compounds. For three particularly polar compounds 15 ⩽ ΔH_Reorg ⩽ 20 kcal/mol, supporting the notion that ΔH_Reorg can be substantial. Those large ΔH_Reorg values correspond to a redistribution of electrostatic interactions upon binding. Overall, the study illustrates how MD simulations offer a promising avenue to characterize the unbound state of medicinal compounds.     

A theoretical study of torsional flexibility in the active site of aspartic proteinases: Implications for catalysis

We have performed ab initio Hartree-Fock self-consistent field calculations on the active site of endothiapepsin. The active site was modeled as a formic acid/formate anion moiety (representing the catalytic aspartates, Asp-32 and -215) and a bound water molecule. Residues Gly-34, Ser-35, Gly-217, and Thr-218, which all form hydrogen bonds to the active site, were modeled using formamide and methanol molecules. The water molecule, which is generally believed to function as the attacking nucleophile in catalysis, was allowed to bind to the active site in four distinct configurations. The geometry of each configuration was optimized using two basis sets (4-31G and 4-31G*). The results indicate that in the native enzyme the nucleophilic water is bound in a catalytically inert configuration. However, by rotating the carboxyl group of Asp-32 by about 90° the water molecule can be reorientated to attack the scissile bond of the substrate. A model of the bound enzyme-substrate complex was constructed from the crystal structure of a difluorostatone inhibitor complexed with endothiapepsin. This model suggests that the substrate itself initiates the reorientation of the nucleophilic water immediately prior to catalysis by forcing the carboxyl group of Asp-32 to rotate. The theoretical results predict that the active site of endothiapepsin undergoes a large distortion during substrate binding and this observation has been used to explain some of the kinetics results which have been reported for mutant aspartic proteinases.     

A 3D structural model and dynamics of hepatitis C virus NS3/4A protease (genotype 4a,strain ED43) suggest conformational instability of the catalytic triad: implications in catalysis and drug resistivity

Egypt has the highest prevalence of hepatitis C virus (HCV) infection worldwide with a frequency of 15%. More than 90% of these infections are due to genotype 4, and the subtype 4a (HCV-4a) predominates. Moreover, due to the increased mobility of people, HCV-4a has recently spread to several European countries. The protease domain of the HCV nonstructural protein 3 (NS3) has been targeted for inhibition by several drugs. This approach has had marked success in inhibiting genotype 1 (HCV-1), the predominant genotype in the USA, Europe, and Japan. However, HCV-4a was found to resist inhibition by a number of these drugs, and little progress has been made to understand the structural basis of its drug resistivity. As a step forward, we sequenced the NS3 HCV-4a protease gene (strain ED43) and subsequently built a 3D structural model threaded through a template crystal structure of HCV-1b NS3 protease. The model protease, HCV-4a, shares 83% sequence identity with the template protease, HCV-1b, and has nearly identical rigid structural features. Molecular dynamics simulations predict similar overall dynamics of the two proteases. However, local dynamics and 4D analysis of the interactions between the catalytic triad residues (His57, Asp81, and Ser139) indicate conformational instability of the catalytic site in HCV-4a NS3 protease. These results suggest that the divergent dynamics behavior, more than the rigid structure, could be related to the altered catalytic activity and drug resistivity seen in HCV-4a.     

Effects of energy dissipation rate on islets of Langerhans: Implications for isolation and transplantation

Acute physical stresses can occur in the procurement and isolation process and potentially can contribute to islet death or malfunction upon transplantation. A contractional flow device, previously used to subject suspended cells to well‐defined hydrodynamic forces, has been modified and used to assess the vulnerability of porcine islets of Langerhans to hydrodynamic forces. The flow profiles and velocity gradients in this modified device were modeled using commercial CFD software and characterized, as in previous studies, with the scalar parameter, energy dissipation rate (EDR). Porcine islets were stressed in a single pass at various stress levels (i.e., values of EDR). Membrane integrity, oxygen uptake rate, caspase 3/7 activity, and insulin release were not affected by the levels of fluid stress tested up to an EDR of 2 × 10³ W/m³. Visual observation of the stressed islets suggested that cells at the islet exterior were peeled away at EDR greater than 10,000 W/m³, however, this observation could not be confirmed using image analysis software, which determined the ratio of surface perimeter to total area. The result of this study suggests an upper limit in fluid stress to which islets can be subjected. Such upper limits assist in the design and operation of future islet processing equipment and processes. Biotechnol. Bioeng. 2009;103: 413–423. © 2008 Wiley Periodicals, Inc.     

A global machine learning based scoring function for protein structure prediction

We present a knowledge‐based function to score protein decoys based on their similarity to native structure. A set of features is constructed to describe the structure and sequence of the entire protein chain. Furthermore, a qualitative relationship is established between the calculated features and the underlying electromagnetic interaction that dominates this scale. The features we use are associated with residue–residue distances, residue–solvent distances, pairwise knowledge‐based potentials and a four‐body potential. In addition, we introduce a new target to be predicted, the fitness score, which measures the similarity of a model to the native structure. This new approach enables us to obtain information both from decoys and from native structures. It is also devoid of previous problems associated with knowledge‐based potentials. These features were obtained for a large set of native and decoy structures and a back‐propagating neural network was trained to predict the fitness score. Overall this new scoring potential proved to be superior to the knowledge‐based scoring functions used as its inputs. In particular, in the latest CASP (CASP10) experiment our method was ranked third for all targets, and second for freely modeled hard targets among about 200 groups for top model prediction. Ours was the only method ranked in the top three for all targets and for hard targets. This shows that initial results from the novel approach are able to capture details that were missed by a broad spectrum of protein structure prediction approaches. Source codes and executable from this work are freely available at http://mathmed.org /#Software and http://mamiris.com/ . Proteins 2014; 82:752–759. © 2013 Wiley Periodicals, Inc.     

A simple and inexpensive method for investigating microbiological,enzymatic, or inorganic catalysis using standard histology and microbiology laboratory equipment: assembly,mass transfer properties,hydrodynamic conditions and evaluation

We introduce a generic, simple, and inexpensive method for performing microbiological, enzymatic, or inorganic catalysis with solids using standard histology and microbiology laboratory equipment. Histology cassettes were used to standardize hydrodynamic conditions and to protect the catalysts and their solid supports. Histology cassettes have the following advantages: they are readily available, inexpensive, solvent and acid resistant, automatable, and the slots in the cassette walls allow liquid to circulate freely. Standard Erlenmeyer flasks were used as reaction vessels. We developed a new camera to observe the movement and position of the histology cassettes as well as the liquid in the Erlenmeyer flasks. The camera produces a stable image of the rotating liquid in the Erlenmeyer flask. This visualization method revealed that in a 250?ml Erlenmeyer flask, stable operating conditions are achieved at a shaking frequency of 300?rpm and a fill volume of 30?ml. In vessels with vertical walls, such as beakers or laboratory bottles, the movement of the histology cassette is not reproducible. Mass transfer characterization using a biological model system and the chemical sulfite-oxidation method revealed that the histology cassette does not influence gas-liquid mass transfer.     

A simple and inexpensive method for investigating microbiological, enzymatic, or inorganic catalysis using standard histology and microbiology laboratory equipment: assembly, mass transfer properties, hydrodynamic conditions and evaluation

We introduce a generic, simple, and inexpensive method for performing microbiological, enzymatic, or inorganic catalysis with solids using standard histology and microbiology laboratory equipment. Histology cassettes were used to standardize hydrodynamic conditions and to protect the catalysts and their solid supports. Histology cassettes have the following advantages: they are readily available, inexpensive, solvent and acid resistant, automatable, and the slots in the cassette walls allow liquid to circulate freely. Standard Erlenmeyer flasks were used as reaction vessels. We developed a new camera to observe the movement and position of the histology cassettes as well as the liquid in the Erlenmeyer flasks. The camera produces a stable image of the rotating liquid in the Erlenmeyer flask. This visualization method revealed that in a 250 ml Erlenmeyer flask, stable operating conditions are achieved at a shaking frequency of 300 rpm and a fill volume of 30 ml. In vessels with vertical walls, such as beakers or laboratory bottles, the movement of the histology cassette is not reproducible. Mass transfer characterization using a biological model system and the chemical sulfite-oxidation method revealed that the histology cassette does not influence gas-liquid mass transfer.     

Optimized distance‐dependent atom‐pair‐based potential DOOP for protein structure prediction

The DOcking decoy‐based Optimized Potential (DOOP) energy function for protein structure prediction is based on empirical distance‐dependent atom‐pair interactions. To optimize the atom‐pair interactions, native protein structures are decomposed into polypeptide chain segments that correspond to structural motives involving complete secondary structure elements. They constitute near native ligand–receptor systems (or just pairs). Thus, a total of 8609 ligand–receptor systems were prepared from 954 selected proteins. For each of these hypothetical ligand–receptor systems, 1000 evenly sampled docking decoys with 0–10 Å interface root‐mean‐square‐deviation (iRMSD) were generated with a method used before for protein–protein docking. A neural network‐based optimization method was applied to derive the optimized energy parameters using these decoys so that the energy function mimics the funnel‐like energy landscape for the interaction between these hypothetical ligand–receptor systems. Thus, our method hierarchically models the overall funnel‐like energy landscape of native protein structures. The resulting energy function was tested on several commonly used decoy sets for native protein structure recognition and compared with other statistical potentials. In combination with a torsion potential term which describes the local conformational preference, the atom‐pair‐based potential outperforms other reported statistical energy functions in correct ranking of native protein structures for a variety of decoy sets. This is especially the case for the most challenging ROSETTA decoy set, although it does not take into account side chain orientation‐dependence explicitly. The DOOP energy function for protein structure prediction, the underlying database of protein structures with hypothetical ligand–receptor systems and their decoys are freely available at http://agknapp.chemie.fu‐berlin.de/doop/ . Proteins 2015; 83:881–890. © 2015 Wiley Periodicals, Inc.     

Characteristics of brain connectivity during verbal fluency test: Convolutional neural network for functional near-infrared spectroscopy analysis

Human connectome describes the complicated connection matrix of nervous system among human brain. It also possesses high potential of assisting doctors to monitor the brain injuries and recoveries in patients. In order to unravel the enigma of neuron connections and functions, previous research has strived to dig out the relations between neurons and brain regions. Verbal fluency test (VFT) is a general neuropsychological test, which has been used in functional connectivity investigations. In this study, we employed convolutional neural network (CNN) on a brain hemoglobin concentration changes (ΔHB) map obtained during VFT to investigate the connections of activated brain areas and different mental status. Our results show that feature of functional connectivity can be identified accurately with the employment of CNN on ΔHB mapping, which is beneficial to improve the understanding of brain functional connections.     

Regulatory networks,genes and glycerophospholipid biosynthesis pathway in schistosomiasis: A systems biology view for pharmacological intervention

Understanding network topology through embracing the global dynamical regulation of genes in an active state space rather than traditional one-gene–one trait approach facilitates the rational drug development process. Schistosomiasis, a neglected tropical disease, has glycerophospholipids as abundant molecules present on its surface. Lack of effective clinical solutions to treat pathogens encourages us to carry out systems-level studies that could contribute to the development of an effective therapy. Development of a strategy for identifying drug targets by combined genome-scale metabolic network and essentiality analyses through in silico approaches provides tantalizing opportunity to investigate the role of protein/substrate metabolism. A genome-scale metabolic network model reconstruction represents choline–phosphate cytidyltransferase as the rate limiting enzyme and regulates the rate of phosphatidylcholine (PC) biosynthesis. The uptake of choline was regulated by choline concentration, promoting the regulation of phosphocholine synthesis. In Schistosoma, the change in developmental stage could result from the availability of choline, hampering its developmental cycle. There are no structural reports for this protein. In order to inhibit the activity of choline–phosphate cytidyltransferase (CCT), it was modeled by homology modeling using 1COZ as the template from Bacillus subtilis. The transition-state stabilization and catalytic residues were mapped as ‘HXGH’ and ‘RTEGISTT’ motif. CCT catalyzes the formation of CDP-choline from phosphocholine in which nucleotidyltransferase adds CTP to phosphocholine. The presence of phosphocholine permits the parasite to survive in an immunologically hostile environment. This feature endeavors development of an inhibitor specific for cytidyltransferase in Schistosoma. Flavonolignans were used to inhibit this activity in which hydnowightin showed the highest affinity as compared to miltefosine.