Integrating comparative modeling and accelerated simulations reveals conformational and energetic basis of actomyosin force generation.

Muscle contraction is performed by arrays of contractile proteins in the sarcomere. Serious heart diseases, such as cardiomyopathy, can often be results of mutations in myosin and actin. Direct characterization of how small changes in the myosin-actin complex impact its force production remains challenging. Molecular dynamics (MD) simulations, although capable of studying protein structure-function relationships, are limited owing to the slow timescale of the myosin cycle as well as a lack of various intermediate structures for the actomyosin complex. Here, employing comparative modeling and enhanced sampling MD simulations, we show how the human cardiac myosin generates force during the mechanochemical cycle. Initial conformational ensembles for different myosin-actin states are learned from multiple structural templates with Rosetta. This enables us to efficiently sample the energy landscape of the system using Gaussian accelerated MD. Key myosin loop residues, whose substitutions are related to cardiomyopathy, are identified to form stable or metastable interactions with the actin surface. We find that the actin-binding cleft closure is allosterically coupled to the myosin motor core transitions and ATP-hydrolysis product release from the active site. Furthermore, a gate between switch I and switch II is suggested to control phosphate release at the prepowerstroke state. Our approach demonstrates the ability to link sequence and structural information to motor functions.

Protein structure analysis of the interactions between SARS-CoV-2 spike protein and the human ACE2 receptor: from conformational changes to novel neutralizing antibodies.

The recent severe acute respiratory syndrome, known as Coronavirus Disease 2019 (COVID-19) has spread so much rapidly and severely to induce World Health Organization (WHO) to declare a state of emergency over the new coronavirus SARS-CoV-2 pandemic. While several countries have chosen the almost complete lock-down for slowing down SARS-CoV-2 spread, the scientific community is called to respond to the devastating outbreak by identifying new tools for diagnosis and treatment of the dangerous COVID-19. With this aim, we performed an in silico comparative modeling analysis, which allows gaining new insights into the main conformational changes occurring in the SARS-CoV-2 spike protein, at the level of the receptor-binding domain (RBD), along interactions with human cells angiotensin-converting enzyme 2 (ACE2) receptor, that favor human cell invasion. Furthermore, our analysis provides (1) an ideal pipeline to identify already characterized antibodies that might target SARS-CoV-2 spike RBD, aiming to prevent interactions with the human ACE2, and (2) instructions for building new possible neutralizing antibodies, according to chemical/physical space restraints and complementary determining regions (CDR) mutagenesis of the identified existing antibodies. The proposed antibodies show in silico high affinity for SARS-CoV-2 spike RBD and can be used as reference antibodies also for building new high-affinity antibodies against present and future coronaviruses able to invade human cells through interactions of their spike proteins with the human ACE2. More in general, our analysis provides indications for the set-up of the right biological molecular context for investigating spike RBD-ACE2 interactions for the development of new vaccines, diagnostic kits, and other treatments based on the targeting of SARS-CoV-2 spike protein.

Differences in Charge Distribution in Leishmania tarentolae Leishmanolysin Result in a Reduced Enzymatic Activity.

Leishmania tarentolae is a non-pathogenic trypanosomatid isolated from lizards widely used for heterologous protein expression and extensively studied to understand the pathogenic mechanisms of leishmaniasis. The repertoire of leishmanolysin genes was reported to be expanded in L. tarentolae genome, but no proteolytic activity was detected. Here, we analyzed L. tarentolae leishmanolysin proteins from the genome to the structural levels and evaluated the enzymatic activity of the wild-type and overexpressing mutants of leishmanolysin. A total of 61 leishmanolysin sequences were retrieved from the L. tarentolae genome. Five of them were selected for phylogenetic analysis, and for three of them, we built 3D models based on the crystallographic structure of L. major ortholog. Molecular dynamics simulations of these models disclosed a less negative electrostatic potential compared to the template. Subsequently, L. major LmjF.10.0460 and L. tarentolae LtaP10.0650 leishmanolysins were cloned in a pLEXSY expression system into L. tarentolae. Proteins from the wild-type and the overexpressing parasites were submitted to enzymatic analysis. Our results revealed that L. tarentolae leishmanolysins harbor a weak enzymatic activity about three times less abundant than L. major leishmanolysin. Our findings strongly suggest that the less negative electrostatic potential of L. tarentolae leishmanolysin can be the reason for the reduced proteolytic activity detected in this parasite.

In Situ Structural Restraints from Cross-Linking Mass Spectrometry in Human Mitochondria.

The field of structural biology is increasingly focusing on studying proteins in situ, i.e., in their greater biological context. Cross-linking mass spectrometry (CLMS) is contributing to this effort, typically through the use of mass spectrometry (MS)-cleavable cross-linkers. Here, we apply the popular noncleavable cross-linker disuccinimidyl suberate (DSS) to human mitochondria and identify 5518 distance restraints between protein residues. Each distance restraint on proteins or their interactions provides structural information within mitochondria. Comparing these restraints to protein data bank (PDB)-deposited structures and comparative models reveals novel protein conformations. Our data suggest, among others, substrates and protein flexibility of mitochondrial heat shock proteins. Through this study, we bring forward two central points for the progression of CLMS towards large-scale in situ structural biology: First, clustered conflicts of cross-link data reveal in situ protein conformation states in contrast to error-rich individual conflicts. Second, noncleavable cross-linkers are compatible with proteome-wide studies.

Benchmarking GPCR homology model template selection in combination with de novo loop generation.

G protein-coupled receptors (GPCR) comprise the largest family of membrane proteins and are of considerable interest as targets for drug development. However, many GPCR structures remain unsolved. To address the structural ambiguity of these receptors, computational tools such as homology modeling and loop modeling are often employed to generate predictive receptor structures. Here we combined both methods to benchmark a protocol incorporating homology modeling based on a locally selected template and extracellular loop modeling that additionally evaluates the presence of template ligands during these modeling steps. Ligands were also docked using three docking methods and two pose selection methods to elucidate an optimal ligand pose selection method. Results suggest that local template-based homology models followed by loop modeling produce more accurate and predictive receptor models than models produced without loop modeling, with decreases in average receptor and ligand RMSD of 0.54 Å and 2.91 Å, respectively. Ligand docking results showcased the ability of MOE induced fit docking to produce ligand poses with atom root-mean-square deviation (RMSD) values at least 0.20 Å lower (on average) than the other two methods benchmarked in this study. In addition, pose selection methods (software-based scoring, ligand complementation) selected lower RMSD poses with MOE induced fit docking than either of the other methods (averaging at least 1.57 Å lower), indicating that MOE induced fit docking is most suited for docking into GPCR homology models in our hands. In addition, target receptor models produced with a template ligand present throughout the modeling process most often produced target ligand poses with RMSD values ≤ 4.5 Å and Tanimoto coefficients > 0.6 after selection based on ligand complementation than target receptor models produced in the absence of template ligands. Overall, the findings produced by this study support the use of local template homology modeling in combination with de novo ECL2 modeling in the presence of a ligand from the template crystal structure to generate GPCR models intended to study ligand binding interactions.

Asp271 is critical for substrate interaction with the surface binding site in ß-agarase a from Zobellia galactanivorans.

In the marine environment agar degradation is assured by bacteria that contain large agarolytic systems with enzymes acting in various endo- and exo-modes. Agarase A (AgaA) is an endo-glycoside hydrolase of family 16 considered to initiate degradation of agarose. Agaro-oligosaccharide binding at a unique surface binding site (SBS) in AgaA from Zobellia galactanivorans was investigated by computational methods in conjunction with a structure/sequence guided approach of site-directed mutagenesis probed by surface plasmon resonance binding analysis of agaro-oligosaccharides of DP 4-10. The crystal structure has shown that agaro-octaose interacts via H-bonds and aromatic stacking along 7 subsites (L through R) of the SBS in the inactive catalytic nucleophile mutant AgaA-E147S. D271 is centrally located in the extended SBS where it forms H-bonds to galactose and 3,6-anhydrogalactose residues of agaro-octaose at subsites O and P. We propose D271 is a key residue in ligand binding to the SBS. Thus AgaA-E147S/D271A gave slightly decreasing KD values from 625 ± 118 to 468 ± 13 µM for agaro-hexaose, -octaose, and -decaose, which represent 3- to 4-fold reduced affinity compared with AgaA-E147S. Molecular dynamics simulations and interaction analyses of AgaA-E147S/D271A indicated disruption of an extended H-bond network supporting that D271 is critical for the functional SBS. Notably, neither AgaA-E147S/W87A nor AgaA-E147S/W277A, designed to eliminate stacking with galactose residues at subsites O and Q, respectively, were produced in soluble form. W87 and W277 may thus control correct folding and structural integrity of AgaA.

A benchmark study of loop modeling methods applied to G protein-coupled receptors.

G protein-coupled receptors (GPCR) are important drug discovery targets. Despite progress, many GPCR structures have not yet been solved. For these targets, comparative modeling is used in virtual ligand screening to prioritize experimental efforts. However, the structure of extracellular loop 2 (ECL2) is often poorly predicted. This is significant due to involvement of ECL2 in ligand binding for many Class A GPCR. Here we examine the performance of loop modeling protocols available in the Rosetta (cyclic coordinate descent [CCD], KIC with fragments [KICF] and next generation KIC [NGK]) and Molecular Operating Environment (MOE) software suites (de novo search). ECL2 from GPCR crystal structures served as the structure prediction targets and were divided into four sets depending on loop length. Results suggest that KICF and NGK sampled and scored more loop models with sub-angstrom and near-atomic accuracy than CCD or de novo search for loops of 24 or fewer residues. None of the methods were able to sample loop conformations with near-atomic accuracy for the longest targets ranging from 25 to 32 residues based on 1000 models generated. For these long loop targets, increased conformational sampling is necessary. The strongly conserved disulfide bond between Cys3.25 and Cys45.50 in ECL2 proved an effective filter. Setting an upper limit of 5.1 Å on the S-S distance improved the lowest RMSD model included in the top 10 scored structures in Groups 1-4 on average between 0.33 and 1.27 Å. Disulfide bond formation and geometry optimization of ECL2 provided an additional incremental benefit in structure quality.

Combining theoretical and experimental data to decipher CFTR 3D structures and functions.

Cryo-electron microscopy (cryo-EM) has recently provided invaluable experimental data about the full-length cystic fibrosis transmembrane conductance regulator (CFTR) 3D structure. However, this experimental information deals with inactive states of the channel, either in an apo, quiescent conformation, in which nucleotide-binding domains (NBDs) are widely separated or in an ATP-bound, yet closed conformation. Here, we show that 3D structure models of the open and closed forms of the channel, now further supported by metadynamics simulations and by comparison with the cryo-EM data, could be used to gain some insights into critical features of the conformational transition toward active CFTR forms. These critical elements lie within membrane-spanning domains but also within NBD1 and the N-terminal extension, in which conformational plasticity is predicted to occur to help the interaction with filamin, one of the CFTR cellular partners.

Experimental Approaches and Computational Modeling of Rat Serum Albumin and Its Interaction with Piperine.

The bioactive piperine (1-piperoyl piperidine) compound found in some pepper species (Piper nigrum linn and Piper sarmentosum Roxb) has been shown to have therapeutic properties and to be useful for well-being. The tests used to validate these properties were performed in vitro or with small rats. However, in all these assays, the molecular approach was absent. Although the first therapeutic trials relied on the use of rats, no proposal was mentioned either experimentally or computationally at the molecular level regarding the interaction between piperine and rat serum albumin (RSA). In the present study, several spectroscopic techniques were employed to characterize rat serum albumin and, aided by computational techniques, the protein modeling was proposed. From the spectroscopic results, it was possible to estimate the binding constant (3.9 × 104 M-1 at 288 K) using the Stern-Volmer model and the number of ligands (three) associated with the protein applying interaction density function model. The Gibbs free energy, an important thermodynamic parameter, was determined (-25 kJ/mol), indicating that the interaction was spontaneous. This important set of experimental results served to parameterize the computational simulations. The results of molecular docking and molecular dynamics matched appropriately made it possible to have detailed microenvironments of RSA accessed by piperine.

Model Comparisons of the Effectiveness and Cost-Effectiveness of Vaccination: A Systematic Review of the Literature.

OBJECTIVES: To describe all published articles that have conducted comparisons of model-based effectiveness and cost-effectiveness results in the field of vaccination. Specific objectives were to 1) describe the methodologies used and 2) identify the strengths and limitations of the studies. METHODS: We systematically searched MEDLINE and Embase databases for studies that compared predictions of effectiveness and cost-effectiveness of vaccination of two or more mathematical models. We categorized studies into two groups on the basis of their data source for comparison (previously published results or new simulation results) and performed a qualitative synthesis of study conclusions. RESULTS: We identified 115 eligible articles (only 5% generated new simulations from the reviewed models) examining the effectiveness and cost-effectiveness of vaccination against 14 pathogens (69% of studies examined human papillomavirus, influenza, and/or pneumococcal vaccines). The goal of most of studies was to summarize evidence for vaccination policy decisions, and cost-effectiveness was the most frequent outcome examined. Only 33%, 25%, and 3% of studies followed a systematic approach to identify eligible studies, assessed the quality of studies, and performed a quantitative synthesis of results, respectively. A greater proportion of model comparisons using published studies followed a systematic approach to identify eligible studies and to assess their quality, whereas more studies using new simulations performed quantitative synthesis of results and identified drivers of model conclusions. Most comparative modeling studies concluded that vaccination was cost-effective. CONCLUSIONS: Given the variability in methods used to conduct/report comparative modeling studies, guidelines are required to enhance their quality and transparency and to provide better tools for decision making.

Identification of small molecular inhibitors for efflux protein Rv2688c of Mycobacterium tuberculosis.

Mycobacterium tuberculosis (Mtb) is the pathogen, which causes tuberculosis. The development of multidrug-resistant and extensively drug-resistant strains in Mtb is due to an efflux mechanism of antibiotics in the bacteria. The efflux pump proteins in the bacteria are implicated in the active efflux of antibiotics. The efflux pump protein, "fluoroquinolones export ATP-binding protein Rv2688c" (FEAB), is considered as a potential therapeutic target to prevent tuberculosis. In the present work, in silico protocols are applied to identify inhibitors for the FEAB protein to arrest the efflux mechanism. Comparative modeling techniques are used to build the protein structure. The generated structure consists of 9 helices, 13 beta strands, and 3 ß sheets. The active site is predicted using active site prediction server tools. The virtual screening protocols are carried out to generate small ligand inhibitor structures. The identified ligand molecules show selective binding with Ser97, Glu99, Lys149, Asp171, Glu172, and Ser175 amino acid residues of the protein. The ligand molecules are subjected to in silico prediction of pharmaco kinetic properties, and the predicted IC50 (HERG) of all the molecules are less than -5.0, which is indicative of the identified ligand molecules is being potentially good FEAB inhibitors.

Optimal healthcare decision making under multiple mathematical models: application in prostate cancer screening.

Important decisions related to human health, such as screening strategies for cancer, need to be made without a satisfactory understanding of the underlying biological and other processes. Rather, they are often informed by mathematical models that approximate reality. Often multiple models have been made to study the same phenomenon, which may lead to conflicting decisions. It is natural to seek a decision making process that identifies decisions that all models find to be effective, and we propose such a framework in this work. We apply the framework in prostate cancer screening to identify prostate-specific antigen (PSA)-based strategies that perform well under all considered models. We use heuristic search to identify strategies that trade off between optimizing the average across all models' assessments and being "conservative" by optimizing the most pessimistic model assessment. We identified three recently published mathematical models that can estimate quality-adjusted life expectancy (QALE) of PSA-based screening strategies and identified 64 strategies that trade off between maximizing the average and the most pessimistic model assessments. All prescribe PSA thresholds that increase with age, and 57 involve biennial screening. Strategies with higher assessments with the pessimistic model start screening later, stop screening earlier, and use higher PSA thresholds at earlier ages. The 64 strategies outperform 22 previously published expert-generated strategies. The 41 most "conservative" ones remained better than no screening with all models in extensive sensitivity analyses. We augment current comparative modeling approaches by identifying strategies that perform well under all models, for various degrees of decision makers' conservativeness.

New insights about the structural rearrangements required for substrate translocation in the bovine mitochondrial oxoglutarate carrier.

The oxoglutarate carrier (OGC) belongs to the mitochondrial carrier family and plays a key role in important metabolic pathways. Here, site-directed mutagenesis was used to conservatively replace lysine 122 by arginine, in order to investigate new structural rearrangements required for substrate translocation. K122R mutant was kinetically characterized, exhibiting a significant Vmax reduction with respect to the wild-type (WT) OGC, whereas Km value was unaffected, implying that this substitution does not interfere with 2-oxoglutarate binding site. Moreover, K122R mutant was more inhibited by several sulfhydryl reagents with respect to the WT OGC, suggesting that the reactivity of some cysteine residues towards these Cys-specific reagents is increased in this mutant. Different sulfhydryl reagents were employed in transport assays to test the effect of the cysteine modifications on single-cysteine OGC mutants named C184, C221, C224 (constructed in the WT background) and K122R/C184, K122R/C221, K122R/C224 (constructed in the K122R background). Cysteines 221 and 224 were more deeply influenced by some sulfhydryl reagents in the K122R background. Furthermore, the presence of 2-oxoglutarate significantly enhanced the degree of inhibition of K122R/C221, K122R/C224 and C224 activity by the sulfhydryl reagent 2-Aminoethyl methanethiosulfonate hydrobromide (MTSEA), suggesting that cysteines 221 and 224, together with K122, take part to structural rearrangements required for the transition from the c- to the m-state during substrate translocation. Our results are interpreted in the light of the homology model of BtOGC, built by using as a template the X-ray structure of the bovine ADP/ATP carrier isoform 1 (AAC1).

Inhibition of human endogenous retrovirus-K by antiretroviral drugs.

BACKGROUND: Human endogenous retroviruses (HERVs) are genomic sequences of retroviral origin which were believed to be integrated into germline chromosomes millions of years ago and account for nearly 8% of the human genome. Although mostly defective and inactive, some of the HERVs may be activated under certain physiological and pathological conditions. While no drugs are designed specifically targeting HERVs, there are a panel of antiretroviral drugs designed against the human immunodeficiency virus and approved by the Federal Drug Administration (FDA). RESULTS: We determined if these antiretroviral drugs may also be effective in inhibiting HERVs. We constructed a plasmid with consensus HERV-K sequence for testing the effect of antiretroviral drugs on HERV-K. We first determined the effects of nucleoside and non-nucleotide reverse transcriptase (RT) inhibitors on HERV-K by product enhanced reverse transcription assay. We found that all RT inhibitors could significantly inhibit HERV-K RT activity. To determine the effects of antiretroviral drugs on HERV-K infection and viral production, we pseudotyped HERV-K with VSV-G and used the pseudotyped HERV-K virus to infect HeLa cells. HERV-K production was measured by quantitative real time polymerase chain reaction. We found that RT inhibitors Abacavir and Zidovudine, and integrase inhibitor Raltegravir could effectively block HERV-K infection and production. However, protease inhibitors were not as effective as RT and integrase inhibitors. CONCLUSIONS: In summary, we identified several FDA approved antiretroviral drugs that can effectively inhibit HERV-K. These antiretrovirals may open new prospects for studying HERV-K pathophysiology and potentially for exploring treatment of diseases in which HERV-K has been implicated.

Nitric oxide synthase in plants: Where do we stand?

Over the past twenty years, nitric oxide (NO) has emerged as an important player in various plant physiological processes. Although many advances in the understanding of NO functions have been made, the question of how NO is produced in plants is still challenging. It is now generally accepted that the endogenous production of NO is mainly accomplished through the reduction of nitrite via both enzymatic and non-enzymatic mechanisms which remain to be fully characterized. Furthermore, experimental arguments in favour of the existence of plant nitric oxide synthase (NOS)-like enzymes have been reported. However, recent investigations revealed that land plants do not possess animal NOS-like enzymes while few algal species do. Phylogenetic and structural analyses reveals interesting features specific to algal NOS-like proteins.

Model distinguishability and inference robustness in mechanisms of cholera transmission and loss of immunity.

Mathematical models of cholera and waterborne disease vary widely in their structures, in terms of transmission pathways, loss of immunity, and a range of other features. These differences can affect model dynamics, with different models potentially yielding different predictions and parameter estimates from the same data. Given the increasing use of mathematical models to inform public health decision-making, it is important to assess model distinguishability (whether models can be distinguished based on fit to data) and inference robustness (whether inferences from the model are robust to realistic variations in model structure). In this paper, we examined the effects of uncertainty in model structure in the context of epidemic cholera, testing a range of models with differences in transmission and loss of immunity structure, based on known features of cholera epidemiology. We fit these models to simulated epidemic and long-term data, as well as data from the 2006 Angola epidemic. We evaluated model distinguishability based on fit to data, and whether the parameter values, model behavior, and forecasting ability can accurately be inferred from incidence data. In general, all models were able to successfully fit to all data sets, both real and simulated, regardless of whether the model generating the simulated data matched the fitted model. However, in the long-term data, the best model fits were achieved when the loss of immunity structures matched those of the model that simulated the data. Two parameters, one representing person-to-person transmission and the other representing the reporting rate, were accurately estimated across all models, while the remaining parameters showed broad variation across the different models and data sets. The basic reproduction number (R0) was often poorly estimated even using the correct model, due to practical unidentifiability issues in the waterborne transmission pathway which were consistent across all models. Forecasting efforts using noisy data were not successful early in the outbreaks, but once the epidemic peak had been achieved, most models were able to capture the downward incidence trajectory with similar accuracy. Forecasting from noise-free data was generally successful for all outbreak stages using any model. Our results suggest that we are unlikely to be able to infer mechanistic details from epidemic case data alone, underscoring the need for broader data collection, such as immunity/serology status, pathogen dose response curves, and environmental pathogen data. Nonetheless, with sufficient data, conclusions from forecasting and some parameter estimates were robust to variations in the model structure, and comparative modeling can help to determine how realistic variations in model structure may affect the conclusions drawn from models and data.

Theoretical analysis of somatostatin receptor 5 with antagonists and agonists for the treatment of neuroendocrine tumors.

We report on SSTR5 receptor modeling and its interaction with reported antagonist and agonist molecules. Modeling of the SSTR5 receptor was carried out using multiple templates with the aim of improving the precision of the generated models. The selective SSTR5 antagonists, agonists and native somatostatin SRIF-14 were employed to propose the binding site of SSTR5 and to identify the critical residues involved in the interaction of the receptor with other molecules. Residues Q2.63, D3.32, Q3.36, C186, Y7.34 and Y7.42 were found to be highly significant for their strong interaction with the receptor. SSTR5 antagonists were utilized to perform a 3D quantitative structure-activity relationship study. A comparative molecular field analysis (CoMFA) was conducted using two different alignment schemes, namely the ligand-based and receptor-based alignment methods. The best statistical results were obtained for ligand-based ([Formula: see text], [Formula: see text] = 0.988, noc = 4) and receptor-guided methods (docked mode 1:[Formula: see text], [Formula: see text], noc = 5), (docked mode 2:[Formula: see text] = 0.555, [Formula: see text], noc = 5). Based on CoMFA contour maps, an electropositive substitution at [Formula: see text], [Formula: see text] and [Formula: see text] position and bulky group at [Formula: see text] position are important in enhancing molecular activity.

Assessment of refinement of template-based models in CASP11.

CASP11 (the 11th Meeting on the Critical Assessment of Protein Structure Prediction) ran a blind experiment in the refinement of protein structure predictions, the fourth such experiment since CASP8. As with the previous experiments, the predictors were provided with one starting structure from the server models of each of a selected set of template-based modeling targets and asked to refine the coordinates of the starting structure toward native. We assessed the refined structures with the Z-scores of the standard CASP measures, which compare the model-target similarities of the models from all the predictors. Furthermore, we assessed the refined structures with "relative measures," which compare the improvement in accuracy of each model with respect to the starting structure. The latter provides an assessment of the extent to which each predictor group is able to improve the starting structures toward native. We utilized heat maps to display improvements in the Calpha-Calpha distance matrix for each model. The heat maps labeled with each element of secondary structure helped us to identify regions of refinement toward native in each model. Most positively scoring models show modest improvements in multiple regions of the structure, while in some models we were able to identify significant repositioning of N/C-terminal segments and internal elements of secondary structure. The best groups were able to improve more than 70% of the targets from the starting models, and by an average of 3-5% in the standard CASP measures. Proteins 2016; 84(Suppl 1):260-281. © 2016 Wiley Periodicals, Inc.

Comprehensive Cross-Linking Mass Spectrometry Reveals Parallel Orientation and Flexible Conformations of Plant HOP2-MND1.

The HOP2-MND1 heterodimer is essential for meiotic homologous recombination in plants and other eukaryotes and promotes the repair of DNA double-strand breaks. We investigated the conformational flexibility of HOP2-MND1, important for understanding the mechanistic details of the heterodimer, with chemical cross-linking in combination with mass spectrometry (XL-MS). The final XL-MS workflow encompassed the use of complementary cross-linkers, quenching, digestion, size exclusion enrichment, and HCD-based LC-MS/MS detection prior to data evaluation. We applied two different homobifunctional amine-reactive cross-linkers (DSS and BS(2)G) and one zero-length heterobifunctional cross-linker (EDC). Cross-linked peptides of four biological replicates were analyzed prior to 3D structure prediction by protein threading and protein-protein docking for cross-link-guided molecular modeling. Miniaturization of the size-exclusion enrichment step reduced the required starting material, led to a high amount of cross-linked peptides, and allowed the analysis of replicates. The major interaction site of HOP2-MND1 was identified in the central coiled-coil domains, and an open colinear parallel arrangement of HOP2 and MND1 within the complex was predicted. Moreover, flexibility of the C-terminal capping helices of both complex partners was observed, suggesting the coexistence of a closed complex conformation in solution.

Rosetta comparative modeling for library design: Engineering alternative inducer specificity in a transcription factor.

Structure-based rational mutagenesis for engineering protein functionality has been limited by the scarcity and difficulty of obtaining crystal structures of desired proteins. On the other hand, when high-throughput selection is possible, directed evolution-based approaches for gaining protein functionalities have been random and fortuitous with limited rationalization. We combine comparative modeling of dimer structures, ab initio loop reconstruction, and ligand docking to select positions for mutagenesis to create a library focused on the ligand-contacting residues. The rationally reduced library requirement enabled conservative control of the substitutions by oligonucleotide synthesis and bounding its size within practical transformation efficiencies (∼ 10(7) variants). This rational approach was successfully applied on an inducer-binding domain of an Acinetobacter transcription factor (TF), pobR, which shows high specificity for natural effector molecule, 4-hydroxy benzoate (4HB), but no native response to 3,4-dihydroxy benzoate (34DHB). Selection for mutants with high transcriptional induction by 34DHB was carried out at the single-cell level under flow cytometry (via green fluorescent protein expression under the control of pobR promoter). Critically, this selection protocol allows both selection for induction and rejection of constitutively active mutants. In addition to gain-of-function for 34DHB induction, the selected mutants also showed enhanced sensitivity and response for 4HB (native inducer) while no sensitivity was observed for a non-targeted but chemically similar molecule, 2-hydroxy benzoate (2HB). This is unique application of the Rosetta modeling protocols for library design to engineer a TF. Our approach extends applicability of the Rosetta redesign protocol into regimes without a priori precision structural information.