Ancient Loss of Catalytic Selenocysteine Spurred Convergent Adaptation in a Mammalian Oxidoreductase

Selenocysteine, the 21st amino acid specified by the genetic code, is a rare selenium-containing residue found in the catalytic site of selenoprotein oxidoreductases. Selenocysteine is analogous to the common cysteine amino acid, but its selenium atom offers physical-chemical properties not provided by the corresponding sulfur atom in cysteine. Catalytic sites with selenocysteine in selenoproteins of vertebrates are under strong purifying selection, but one enzyme, glutathione peroxidase 6 (GPX6), independently exchanged selenocysteine for cysteine <100 million years ago in several mammalian lineages. We reconstructed and assayed these ancient enzymes before and after selenocysteine was lost and up to today and found them to have lost their classic ability to reduce hydroperoxides using glutathione. This loss of function, however, was accompanied by additional amino acid changes in the catalytic domain, with protein sites concertedly changing under positive selection across distant lineages abandoning selenocysteine in glutathione peroxidase 6. This demonstrates a narrow evolutionary range in maintaining fitness when sulfur in cysteine impairs the catalytic activity of this protein, with pleiotropy and epistasis likely driving the observed convergent evolution. We propose that the mutations shared across distinct lineages may trigger enzymatic properties beyond those in classic glutathione peroxidases, rather than simply recovering catalytic rate. These findings are an unusual example of adaptive convergence across mammalian selenoproteins, with the evolutionary signatures possibly representing the evolution of novel oxidoreductase functions.

Identification of Aggregation Mechanism of Acetylated PHF6* and PHF6 Tau Peptides Based on Molecular Dynamics Simulations and Markov State Modeling

The microtubule-associated protein tau (MAPT) has a critical role in the development and preservation of the nervous system. However, tau's dysfunction and accumulation in the human brain can lead to several neurodegenerative diseases, such as Alzheimer's disease, Down's syndrome, and frontotemporal dementia. The microtubule binding (MTB) domain plays a significant, important role in determining the tau's pathophysiology, as the core of paired helical filaments PHF6* (275VQIINK280) and PHF6 (306VQIVYK311) of R2 and R3 repeat units, respectively, are formed in this region, which promotes tau aggregation. Post-translational modifications, and in particular lysine acetylation at K280 of PHF6* and K311 of PHF6, have been previously established to promote tau misfolding and aggregation. However, the exact aggregation mechanism is not known. In this study, we established an atomic-level nucleation-extension mechanism of the separated aggregation of acetylated PHF6* and PHF6 hexapeptides, respectively, of tau. We show that the acetylation of the lysine residues promotes the formation of β-sheet enriched high-ordered oligomers. The Markov state model analysis of ac-PHF6* and ac-PHF6 aggregation revealed the formation of an antiparallel dimer nucleus which could be extended from both sides in a parallel manner to form mixed-oriented and high-ordered oligomers. Our study describes the detailed mechanism for acetylation-driven tau aggregation, which provides valuable insights into the effect of post-translation modification in altering the pathophysiology of tau hexapeptides.

CDK6 is activated by the atypical cyclin I to promote E2F-mediated gene expression and cancer cell proliferation

Cyclin-dependent kinases (CDKs), together with their cyclin partners, are the master cell cycle regulators. Remarkably, the cyclin family was extended to include atypical cyclins, characterized by distinctive structural features, but their partner CDKs remain elusive. Here, we conducted a yeast two-hybrid screen to identify new atypical cyclin-CDK complexes. We identified 10 new complexes, including a complex between CDK6 and cyclin I (CCNI), which was found to be active against retinoblastoma protein. CCNI upregulation increased the proliferation of breast cancer cells in vitro and in vivo, with a magnitude similar to that seen upon cyclin D upregulation, an effect that was abrogated by CDK6 silencing or palbociclib treatment. In line with these findings, CCNI downregulation led to a decrease in cell number and a reduction in the percentage of cells reaching S-phase. Finally, CCNI upregulation correlated with high expression of E2F target genes in large panels of cancer cell lines and tissue samples from breast cancer patients. In conclusion, we unveil CCNI as a new player in the pathways that activate CDK6, enriching the wiring of cell cycle control.

New Mutations in HFE2 and TFR2 Genes Causing Non HFE-Related Hereditary Hemochromatosis

Hereditary hemochromatosis (HH) is an iron metabolism disease clinically characterized by excessive iron deposition in parenchymal organs such as liver, heart, pancreas, and joints. It is caused by mutations in at least five different genes. HFE hemochromatosis is the most common type of hemochromatosis, while non-HFE related hemochromatosis are rare cases. Here, we describe six new patients of non-HFE related HH from five different families. Two families (Family 1 and 2) have novel nonsense mutations in the HFE2 gene have novel nonsense mutations (p.Arg63Ter and Asp36ThrfsTer96). Three families have mutations in the TFR2 gene, one case has one previously unreported mutation (Family A-p.Asp680Tyr) and two cases have known pathogenic mutations (Family B and D-p.Trp781Ter and p.Gln672Ter respectively). Clinical, biochemical, and genetic data are discussed in all these cases. These rare cases of non-HFE related hereditary hemochromatosis highlight the importance of an earlier molecular diagnosis in a specialized center to prevent serious clinical complications.

SBMOpenMM: A Builder of Structure-Based Models for OpenMM

Molecular dynamics (MD) simulations have become a standard tool to correlate the structure and function of biomolecules and significant advances have been made in the study of proteins and their complexes. A major drawback of conventional MD simulations is the difficulty and cost of obtaining converged results, especially when exploring potential energy surfaces containing considerable energy barriers. This limits the wide use of MD calculations to determine the thermodynamic properties of biomolecular processes. Indeed, this is true when considering the conformational entropy of such processes, which is ultimately critical in assessing the simulations' convergence. Alternatively, a wide range of structure-based models (SBMs) has been used in the literature to unravel the basic mechanisms of biomolecular dynamics. These models introduce simplifications that focus on the relevant aspects of the physical process under study. Because of this, SBMs incorporate the need to modify the force field definition and parameters to target specific biophysical simulations. Here we introduce SBMOpenMM, a Python library to build force fields for SBMs, that uses the OpenMM framework to create and run SBM simulations. The code is flexible and user-friendly and profits from the high customizability and performance provided by the OpenMM platform.

Dynamic chromatin association of IκBα is regulated by acetylation and cleavage of histone H4

IκBs exert principal functions as cytoplasmic inhibitors of NF-kB transcription factors. Additional roles for IκB homologues have been described, including chromatin association and transcriptional regulation. Phosphorylated and SUMOylated IκBα (pS-IκBα) binds to histones H2A and H4 in the stem cell and progenitor cell compartment of skin and intestine, but the mechanisms controlling its recruitment to chromatin are largely unknown. Here, we show that serine 32-36 phosphorylation of IκBα favors its binding to nucleosomes and demonstrate that p-IκBα association with H4 depends on the acetylation of specific H4 lysine residues. The N-terminal tail of H4 is removed during intestinal cell differentiation by proteolytic cleavage by trypsin or chymotrypsin at residues 17-19, which reduces p-IκBα binding. Inhibition of trypsin and chymotrypsin activity in HT29 cells increases p-IκBα chromatin binding but, paradoxically, impaired goblet cell differentiation, comparable to IκBα deletion. Taken together, our results indicate that dynamic binding of IκBα to chromatin is a requirement for intestinal cell differentiation and provide a molecular basis for the understanding of the restricted nuclear distribution of p-IκBα in specific stem cell compartments.

Computational exploration of the binding mode of heme-dependent stimulators into the active catalytic domain of soluble guanylate cyclase

Soluble guanylate cyclase (sGC), the main target of nitric oxide (NO), has been proven to have a significant role in coronary artery disease, pulmonary hypertension, erectile dysfunction, and myocardial infarction. One of its agonists, BAY 41-2272 (Riociguat), has been recently approved for treatment of pulmonary arterial hypertension (PHA), while some others are in clinical phases of development. However, the location of the binding sites for the two known types of agonists, heme-dependent stimulators and heme-independent activators, is a matter of debate, particularly for the first group where both a location on the regulatory (H-NOX) and on the catalytic domain have been suggested by different authors. Here, we address its potential location on the catalytic domain, the unique well characterized at the structural level, by an "in silico" approach. Homology models of the catalytic domain of sGC in "inactive" or "active" conformations were constructed using the structure of previously described crystals of the catalytic domains of "inactive" sGCs (2WZ1, 3ET6) and of "active" adenylate cyclase (1CJU). Each model was submitted to six independent molecular dynamics simulations of about 1 μs. Docking of YC-1, a classic heme-dependent stimulator, to all frames of representative trajectories of "inactive" and "active" conformations, followed by calculation of absolute binding free energies with the linear interaction energy (LIE) method, revealed a potential high-affinity binding site on the "active" structure. The site, located between the pseudo-symmetric and the catalytic site just over the loop β2 -β3 , does not overlap with the forskolin binding site on adenylate cyclases. Proteins 2016; 84:1534-1548. © 2016 Wiley Periodicals, Inc.

Methylglyoxal produced by amyloid-β peptide-induced nitrotyrosination of triosephosphate isomerase triggers neuronal death in Alzheimer's disease

Amyloid-β peptide (Aβ) aggregates induce nitro-oxidative stress, contributing to the characteristic neurodegeneration found in Alzheimer's disease (AD). One of the most strongly nitrotyrosinated proteins in AD is the triosephosphate isomerase (TPI) enzyme which regulates glycolytic flow, and its efficiency decreased when it is nitrotyrosinated. The main aims of this study were to analyze the impact of TPI nitrotyrosination on cell viability and to identify the mechanism behind this effect. In human neuroblastoma cells (SH-SY5Y), we evaluated the effects of Aβ42 oligomers on TPI nitrotyrosination. We found an increased production of methylglyoxal (MG), a toxic byproduct of the inefficient nitro-TPI function. The proapoptotic effects of Aβ42 oligomers, such as decreasing the protective Bcl2 and increasing the proapoptotic caspase-3 and Bax, were prevented with a MG chelator. Moreover, we used a double mutant TPI (Y165F and Y209F) to mimic nitrosative modifications due to Aβ action. Neuroblastoma cells transfected with the double mutant TPI consistently triggered MG production and a decrease in cell viability due to apoptotic mechanisms. Our data show for the first time that MG is playing a key role in the neuronal death induced by Aβ oligomers. This occurs because of TPI nitrotyrosination, which affects both tyrosines associated with the catalytic center.

TRIFORCE: Tessellated Semianalytical Solvent Exposed Surface Areas and Derivatives

We present a new approach to the calculation of solvent-accessible surface areas of molecules with potential application to surface area based methods for determination of solvation free energies. As in traditional analytical and statistical approaches, this new algorithm, called TRIFORCE, reports both component areas and derivatives as a function of the atomic coordinates and radii. Unique to TRIFORCE are the rapid and scalable approaches for the determination of sphere intersection points and numerical estimation of the surface areas, derivatives, and other properties that can be associated with the surface area facets. The algorithm performs a special tessellation and semianalytical integration that uses a precomputed look-up table. This provides a simple way to balance numerical accuracy and memory usage. TRIFORCE calculates derivatives in the same manner, enabling application in force-dependent activities such as molecular geometry minimization. TRIFORCE is available free of charge for academic purposes as both a C++ library, which can be directly interfaced to existing molecular simulation packages, and a web-accessible application.

Chromatin-bound IκBα regulates a subset of polycomb target genes in differentiation and cancer

IκB proteins are the primary inhibitors of NF-κB. Here, we demonstrate that sumoylated and phosphorylated IκBα accumulates in the nucleus of keratinocytes and interacts with histones H2A and H4 at the regulatory region of HOX and IRX genes. Chromatin-bound IκBα modulates Polycomb recruitment and imparts their competence to be activated by TNFα. Mutations in the Drosophila IκBα gene cactus enhance the homeotic phenotype of Polycomb mutants, which is not counteracted by mutations in dorsal/NF-κB. Oncogenic transformation of keratinocytes results in cytoplasmic IκBα translocation associated with a massive activation of Hox. Accumulation of cytoplasmic IκBα was found in squamous cell carcinoma (SCC) associated with IKK activation and HOX upregulation.

New model of cystic fibrosis transmembrane conductance regulator proposes active channel-like conformation

The cystic fibrosis transmembrane conductance regulator (CFTR) is an unusual ABC transporter, functioning as a chloride channel critical for fluid homeostasis in multiple organs. Disruption of CFTR function is associated with cystic fibrosis making it an attractive therapeutic target. In addition, CFTR blockers are being developed as potential antidiarrheals. CFTR drug discovery is hampered by the lack of high resolution structural data, and considerable efforts have been invested in modeling the channel structure. Although previously published CFTR models that have been made publicly available mostly agree with experimental data relating to the overall structure, they present the channel in an outward-facing conformation that does not agree with expected properties of a "channel-like" structure. Here, we make available a model of CFTR in such a "channel-like" conformation, derived by a unique modeling approach combining restrained homology modeling and ROSETTA refinement. In contrast to others, the present model is in agreement with expected channel properties such as pore shape, dimensions, solvent accessibility, and experimentally derived distances. We have used the model to explore the interaction of open channel blockers within the pore, revealing a common binding mode and ionic interaction with K95, in agreement with experimental data. The binding-site was further validated using a virtual screening enrichment experiment, suggesting the model might be suitable for drug discovery. In addition, we subjected the model to a molecular dynamics simulation, revealing previously unaddressed salt-bridge interactions that may be important for structure stability and pore-lining residues that may take part in Cl(-) conductance.

Knowledge management for systems biology a general and visually driven framework applied to translational medicine

BACKGROUND

To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype-phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory.

RESULTS

To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data.

CONCLUSIONS

We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene--disease and gene--compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.

Statistical analysis of global connectivity and activity distributions in cellular networks

Various molecular interaction networks have been claimed to follow power-law decay for their global connectivity distribution. It has been proposed that there may be underlying generative models that explain this heavy-tailed behavior by self-reinforcement processes such as classical or hierarchical scale-free network models. Here, we analyze a comprehensive data set of protein-protein and transcriptional regulatory interaction networks in yeast, an Escherichia coli metabolic network, and gene activity profiles for different metabolic states in both organisms. We show that in all cases the networks have a heavy-tailed distribution, but most of them present significant differences from a power-law model according to a stringent statistical test. Those few data sets that have a statistically significant fit with a power-law model follow other distributions equally well. Thus, while our analysis supports that both global connectivity interaction networks and activity distributions are heavy-tailed, they are not generally described by any specific distribution model, leaving space for further inferences on generative models. Supplementary Material is available online at www.liebertonline.com.

The Virtual Physiological Human ToolKit

The Virtual Physiological Human (VPH) is a major European e-Science initiative intended to support the development of patient-specific computer models and their application in personalized and predictive healthcare. The VPH Network of Excellence (VPH-NoE) project is tasked with facilitating interaction between the various VPH projects and addressing issues of common concern. A key deliverable is the 'VPH ToolKit'--a collection of tools, methodologies and services to support and enable VPH research, integrating and extending existing work across Europe towards greater interoperability and sustainability. Owing to the diverse nature of the field, a single monolithic 'toolkit' is incapable of addressing the needs of the VPH. Rather, the VPH ToolKit should be considered more as a 'toolbox' of relevant technologies, interacting around a common set of standards. The latter apply to the information used by tools, including any data and the VPH models themselves, and also to the naming and categorizing of entities and concepts involved. Furthermore, the technologies and methodologies available need to be widely disseminated, and relevant tools and services easily found by researchers. The VPH-NoE has thus created an online resource for the VPH community to meet this need. It consists of a database of tools, methods and services for VPH research, with a Web front-end. This has facilities for searching the database, for adding or updating entries, and for providing user feedback on entries. Anyone is welcome to contribute.

Simulation methods with extended stability for stiff biochemical Kinetics

Background

With increasing computer power, simulating the dynamics of complex systems in chemistry and biology is becoming increasingly routine. The modelling of individual reactions in (bio)chemical systems involves a large number of random events that can be simulated by the stochastic simulation algorithm (SSA). The key quantity is the step size, or waiting time, τ, whose value inversely depends on the size of the propensities of the different channel reactions and which needs to be re-evaluated after every firing event. Such a discrete event simulation may be extremely expensive, in particular for stiff systems where τ can be very short due to the fast kinetics of some of the channel reactions. Several alternative methods have been put forward to increase the integration step size. The so-called τ-leap approach takes a larger step size by allowing all the reactions to fire, from a Poisson or Binomial distribution, within that step. Although the expected value for the different species in the reactive system is maintained with respect to more precise methods, the variance at steady state can suffer from large errors as τ grows.

Results

In this paper we extend Poisson τ-leap methods to a general class of Runge-Kutta (RK) τ-leap methods. We show that with the proper selection of the coefficients, the variance of the extended τ-leap can be well-behaved, leading to significantly larger step sizes.

Conclusions

The benefit of adapting the extended method to the use of RK frameworks is clear in terms of speed of calculation, as the number of evaluations of the Poisson distribution is still one set per time step, as in the original τ-leap method. The approach paves the way to explore new multiscale methods to simulate (bio)chemical systems.

Computational study on the carboligation reaction of acetohidroxyacid synthase: new approach on the role of the HEThDP- intermediate

Acetohydroxyacid synthase (AHAS) is a thiamin diphosphate dependent enzyme that catalyses the decarboxylation of pyruvate to yield the hydroxyethyl-thiamin diphosphate (ThDP) anion/enamine intermediate (HEThDP(-)). This intermediate reacts with a second ketoacid to form acetolactate or acetohydroxybutyrate as products. Whereas the mechanism involved in the formation of HEThDP(-) from pyruvate is well understood, the role of the enzyme in controlling the carboligation reaction of HEThDP(-) has not been determined yet. In this work, molecular dynamics (MD) simulations were employed to identify the aminoacids involved in the carboligation stage. These MD studies were carried out over the catalytic subunit of yeast AHAS containing the reaction intermediate (HEThDP(-)) and a second pyruvate molecule. Our results suggest that additional acid-base ionizable groups are not required to promote the catalytic cycle, in contrast with earlier proposals. This finding leads us to postulate that the formation of acetolactate relies on the acid-base properties of the HEThDP(-) intermediate itself. PM3 semiempirical calculations were employed to obtain the energy profile of the proposed mechanism on a reduced model of the active site. These calculations confirm the role of HEThDP(-) intermediate as the ionizable group that promotes the carboligation and product formation steps of the catalytic cycle.

Amyloid-dependent triosephosphate isomerase nitrotyrosination induces glycation and tau fibrillation

Alzheimer's disease neuropathology is characterized by neuronal death, amyloid beta-peptide deposits and neurofibrillary tangles composed of paired helical filaments of tau protein. Although crucial for our understanding of the pathogenesis of Alzheimer's disease, the molecular mechanisms linking amyloid beta-peptide and paired helical filaments remain unknown. Here, we show that amyloid beta-peptide-induced nitro-oxidative damage promotes the nitrotyrosination of the glycolytic enzyme triosephosphate isomerase in human neuroblastoma cells. Consequently, nitro-triosephosphate isomerase was found to be present in brain slides from double transgenic mice overexpressing human amyloid precursor protein and presenilin 1, and in Alzheimer's disease patients. Higher levels of nitro-triosephosphate isomerase (P < 0.05) were detected, by Western blot, in immunoprecipitates from hippocampus (9 individuals) and frontal cortex (13 individuals) of Alzheimer's disease patients, compared with healthy subjects (4 and 9 individuals, respectively). Triosephosphate isomerase nitrotyrosination decreases the glycolytic flow. Moreover, during its isomerase activity, it triggers the production of the highly neurotoxic methylglyoxal (n = 4; P < 0.05). The bioinformatics simulation of the nitration of tyrosines 164 and 208, close to the catalytic centre, fits with a reduced isomerase activity. Human embryonic kidney (HEK) cells overexpressing double mutant triosephosphate isomerase (Tyr164 and 208 by Phe164 and 208) showed high methylglyoxal production. This finding correlates with the widespread glycation immunostaining in Alzheimer's disease cortex and hippocampus from double transgenic mice overexpressing amyloid precursor protein and presenilin 1. Furthermore, nitro-triosephosphate isomerase formed large beta-sheet aggregates in vitro and in vivo, as demonstrated by turbidometric analysis and electron microscopy. Transmission electron microscopy (TEM) and atomic force microscopy studies have demonstrated that nitro-triosephosphate isomerase binds tau monomers and induces tau aggregation to form paired helical filaments, the characteristic intracellular hallmark of Alzheimer's disease brains. Our results link oxidative stress, the main etiopathogenic mechanism in sporadic Alzheimer's disease, via the production of peroxynitrite and nitrotyrosination of triosephosphate isomerase, to amyloid beta-peptide-induced toxicity and tau pathology.

Analysis of electrostatic contributions to the selectivity of interactions between RING-finger domains and ubiquitin-conjugating enzymes

The zinc-coordinated protein motifs known as RING-finger domains, present on a class of ubiquitin ligases (E3's), recruit ubiquitin-conjugating enzymes (E2s), tethering them to substrate proteins for covalent modification with ubiquitin. Each RING-finger domain can recruit different E2s, and these interactions are frequently selective, in that certain RING-finger domains associate preferentially with certain E2s. This selectivity acquires particular biological relevance when the recruited E2s exert specialized functions. We have explored the determinants that specify the presence or absence of experimentally detectable interaction between two RING-finger domains, those on RNF11 and RNF103, and two E2s, UBC13, a specialized E2 that catalyzes ubiquitin chain elongation through Lys63 of ubiquitin, and UbcH7, which mediates polyubiquitylation through Lys48. Through the iterative use of computational predictive tools and experimental validations, we have found that these interactions and their selectivity are partly governed by the combinations of electrostatic interactions linking specific residues of the contact interfaces. Our analysis also predicts that the main determinants of selectivity of these interactions reside on the RING-finger domains, rather than on the E2s. The application of some of these rules of interaction selectivity has permitted us to experimentally manipulate the selectivity of interaction of the RING-finger domain-E2 pairs under study.

The role of residue stability in transient protein-protein interactions involved in enzymatic phosphate hydrolysis. A computational study

Finding why protein-protein interactions (PPIs) are so specific can provide a valuable tool in a variety of fields. Statistical surveys of so-called transient complexes (like those relevant for signal transduction mechanisms) have shown a tendency of polar residues to participate in the interaction region. Following this scheme, residues in the unbound partners have to compete between interacting with water or interacting with other residues of the protein. On the other hand, several works have shown that the notion of active site electrostatic preorganization can be used to interpret the high efficiency in enzyme reactions. This preorganization can be related to the instability of the residues important for catalysis. In some enzymes, in addition, conformational changes upon binding to other proteins lead to an increase in the activity of the enzymatic partner. In this article the linear response approximation version of the semimacroscopic protein dipoles Langevin dipoles (PDLD/S-LRA) model is used to evaluate the stability of several residues in two phosphate hydrolysis enzymes upon complexation with their activating partners. In particular, the residues relevant for PPI and for phosphate hydrolysis in the CDK2/Cyclin A and Ras/GAP complexes are analyzed. We find that the evaluation of the stability of residues in these systems can be used to identify not only active site regions but it can also be used as a guide to locate "hot spots" for PPIs. We also show that conformational changes play a major role in positioning interfacing residues in a proper "energetic" orientation, ready to interact with the residues in the partner protein surface. Thus, we extend the preorganization theory to PPIs, extrapolating the results we obtained from the above-mentioned complexes to a more general case. We conclude that the correlation between stability of a residue in the surface and the likelihood that it participates in the interaction can be a general fact for transient PPIs.

Framework-based design of a new all-purpose molecular simulation application: the Adun simulator

Here we present Adun, a new molecular simulator that represents a paradigm shift in the way scientific programs are developed. The traditional algorithm centric methods of scientific programming can lead to major maintainability and productivity problems when developing large complex programs. These problems have long been recognized by computer scientists; however, the ideas and techniques developed to deal with them have not achieved widespread adoption in the scientific community. Adun is the result of the application of these ideas, including pervasive polymorphism, evolutionary frameworks, and refactoring, to the molecular simulation domain. The simulator itself is underpinned by the Adun Framework, which separates the structure of the program from any underlying algorithms, thus giving a completely reusable design. The aims are twofold. The first is to provide a platform for rapid development and implementation of different simulation types and algorithms. The second is to decrease the learning barrier for new developers by providing a rigorous and well-defined structure. We present some examples on the use of Adun by performing simple free-energy simulations for the adiabatic charging of a single ion, using both free-energy perturbation and the Bennett's method. We also illustrate the power of the design by detailing the ease with which ASEP/MD, an elaborated mean field QM/MM method originally written in FORTRAN 90, was implemented into Adun.

Towards a MIP-based alignment and docking in computer-aided drug design

Structural alignment of ligands in their biological conformation is a crucial step in the building of pharmacophoric models in structure-based drug design. In addition, docking algorithms are limited in some cases by the quality of the scoring functions and the limited flexibility of the environment that the different programs allow. On the other hand, GRID molecular interaction potentials (MIPs) have been used for a long time in 3D-QSAR studies. However, in most of these studies the alignment of the molecules is performed on the basis of geometrical or physico-chemical criteria that differ from the MIPs used in the partial least squares statistical analysis. We have previously developed a method to use the same scoring function for the molecular alignment and for 3D-QSAR studies. This methodology, based on the use of GRID potentials, consists in the weighted averaging of similarities of the relevant MIPs of the molecules to be aligned. Here we present a method to obtain the weights for the different GRID probes in the average based on the structural information on protein-ligand complexes for relevant systems. The method, implemented in MIPSIM, is shown to yield good accuracy in the prediction of the alignments for two systems: a set of three inhibitors of dihydrofolate reductase and a set of fifteen non-nucleoside HIV-1 reverse transcriptase inhibitors (NNRTIs). The smooth GRID potentials are shown to capture the flexible character of the active site, as opposed to traditional docking scoring energy functions.

On the generation of catalytic antibodies by transition state analogues

The effective design of catalytic antibodies represents a major conceptual and practical challenge. It is implicitly assumed that a proper transition state analogue (TSA) can elicit a catalytic antibody (CA) that will catalyze the given reaction in a similar way to an enzyme that would evolve (or was evolved) to catalyze this reaction. However, in most cases it was found that the TSA used produced CAs with relatively low rate enhancement as compared to the corresponding enzymes, when these exist. The present work explores the origin of this problem, by developing two approaches that examine the similarity of the TSA and the corresponding transition state (TS). These analyses are used to assess the proficiency of the CA generated by the given TSA. Both approaches focus on electrostatic effects that have been found to play a major role in enzymatic reactions. The first method uses molecular interaction potentials to look for the similarity between the TSA and the TS and, in principle, to help in designing new haptens by using 3D quantitative structure-activity relationships. The second and more quantitative approach generates a grid of Langevin dipoles, which are polarized by the TSA, and then uses the grid to bind the TS. Comparison of the resulting binding energy with the binding energy of the TS to the grid that was polarized by the TS provides an estimate of the proficiency of the given CA. Our methods are used in examining the origin of the difference between the catalytic power of the 1F7 CA and chorismate mutase. It is demonstrated that the relatively small changes in charge and structure between the TS and TSA are sufficient to account for the difference in proficiency between the CA and the enzyme. Apparently the environment that was preorganized to stabilize the TSA charge distribution does not provide a sufficient stabilization to the TS. The general implications of our findings and the difficulties in designing a perfect TSA are discussed. Finally, the possible use of our approach in screening for an optimal TSA is pointed out.