Central lung gene expression associates with myofibroblast features in idiopathic pulmonary fibrosis.

RATIONALE: Contribution of central lung tissues to pathogenesis of idiopathic pulmonary fibrosis (IPF) remains unknown. OBJECTIVE: To ascertain the relationship between cell types of IPF-central and IPF-peripheral lung explants using RNA sequencing (RNA-seq) transcriptome. METHODS: Biopsies of paired IPF-central and IPF-peripheral along with non-IPF lungs were selected by reviewing H&E data. Criteria for differentially expressed genes (DEG) were set at false discovery rate <5% and fold change >2. Computational cell composition deconvolution was performed. Signature scores were computed for each cell type. FINDINGS: Comparison of central IPF versus non-IPF identified 1723 DEG (1522 upregulated and 201 downregulated). Sixty-two per cent (938/1522) of the mutually upregulated genes in central IPF genes were also upregulated in peripheral IPF versus non-IPF. Moreover, 85 IPF central-associated genes (CAG) were upregulated in central IPF versus both peripheral IPF and central non-IPF. IPF single-cell RNA-seq analysis revealed the highest CAG signature score in myofibroblasts and significantly correlated with a previously published activated fibroblasts signature (r=0.88, p=1.6×10-4). CAG signature scores were significantly higher in IPF than in non-IPF myofibroblasts (p=0.013). Network analysis of central-IPF genes identified a module significantly correlated with the deconvoluted proportion of myofibroblasts in central IPF and anti-correlated with inflammation foci trait in peripheral IPF. The module genes were over-represented in idiopathic pulmonary fibrosis signalling pathways. INTERPRETATION: Gene expression in central IPF lung regions demonstrates active myofibroblast features that contributes to disease progression. Further elucidation of pathological transcriptomic state of cells in the central regions of the IPF lung that are relatively spared from morphological rearrangements may provide insights into molecular changes in the IPF progression.

PCSK6 and Survival in Idiopathic Pulmonary Fibrosis.

Rationale: Idiopathic pulmonary fibrosis (IPF) is a devastating disease characterized by limited treatment options and high mortality. A better understanding of the molecular drivers of IPF progression is needed. Objectives: To identify and validate molecular determinants of IPF survival. Methods: A staged genome-wide association study was performed using paired genomic and survival data. Stage I cases were drawn from centers across the United States and Europe and stage II cases from Vanderbilt University. Cox proportional hazards regression was used to identify gene variants associated with differential transplantation-free survival (TFS). Stage I variants with nominal significance (P < 5 × 10-5) were advanced for stage II testing and meta-analyzed to identify those reaching genome-wide significance (P < 5 × 10-8). Downstream analyses were performed for genes and proteins associated with variants reaching genome-wide significance. Measurements and Main Results: After quality controls, 1,481 stage I cases and 397 stage II cases were included in the analysis. After filtering, 9,075,629 variants were tested in stage I, with 158 meeting advancement criteria. Four variants associated with TFS with consistent effect direction were identified in stage II, including one in an intron of PCSK6 (proprotein convertase subtilisin/kexin type 6) reaching genome-wide significance (hazard ratio, 4.11 [95% confidence interval, 2.54-6.67]; P = 9.45 × 10-9). PCSK6 protein was highly expressed in IPF lung parenchyma. PCSK6 lung staining intensity, peripheral blood gene expression, and plasma concentration were associated with reduced TFS. Conclusions: We identified four novel variants associated with IPF survival, including one in PCSK6 that reached genome-wide significance. Downstream analyses suggested that PCSK6 protein plays a potentially important role in IPF progression.

Longitudinal lung function and gas transfer in individuals with idiopathic pulmonary fibrosis: a genome-wide association study.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is an incurable lung disease characterised by progressive scarring leading to alveolar stiffness, reduced lung capacity, and impeded gas transfer. We aimed to identify genetic variants associated with declining lung capacity or declining gas transfer after diagnosis of IPF. METHODS: We did a genome-wide meta-analysis of longitudinal measures of forced vital capacity (FVC) and diffusing capacity of the lung for carbon monoxide (DLCO) in individuals diagnosed with IPF. Individuals were recruited to three studies between June, 1996, and August, 2017, from across centres in the US, UK, and Spain. Suggestively significant variants were investigated further in an additional independent study (CleanUP-IPF). All four studies diagnosed cases following American Thoracic Society/European Respiratory Society guidelines. Variants were defined as significantly associated if they had a meta-analysis p<5 × 10-8 when meta-analysing across all discovery and follow-up studies, had consistent direction of effects across all four studies, and were nominally significant (p<0·05) in each study. FINDINGS: 1329 individuals with a total of 5216 measures were included in the FVC analysis. 975 individuals with a total of 3361 measures were included in the DLCO analysis. For the discovery genome-wide analyses, 7 611 174 genetic variants were included in the FVC analysis and 7 536 843 in the DLCO analysis. One variant (rs115982800) located in an antisense RNA gene for protein kinase N2 (PKN2) showed a genome-wide significant association with FVC decline (-140 mL/year per risk allele [95% CI -180 to -100]; p=9·14 × 10-12). INTERPRETATION: Our analysis identifies a genetic variant associated with disease progression, which might highlight a new biological mechanism for IPF. We found that PKN2, a Rho and Rac effector protein, is the most likely gene of interest from this analysis. PKN2 inhibitors are currently in development and signify a potential novel therapeutic approach for IPF. FUNDING: Action for Pulmonary Fibrosis, Medical Research Council, Wellcome Trust, and National Institutes of Health National Heart, Lung, and Blood Institute.

Combined hepatocellular carcinoma-cholangiocarcinoma in a patient with Fontan-associated liver disease.

We present a rare case of combined hepatocellular carcinoma-cholangiocarcinoma in a woman with a history of univentricular congenital heart disease requiring multiple corrective operations including Fontan procedure. During workup for elevated alpha fetal protein, a right hepatic lobe lesion was identified with biopsy showing poorly differentiated hepatocellular carcinoma. She underwent successful segment 5 liver resection. Final pathology demonstrated combined hepatocellular carcinoma-cholangiocarcinoma. She was treated with gemcitabine/oxaliplatin adjuvant chemotherapy and had no evidence of recurrent disease at her 12-month follow-up. To our knowledge, this is the first case reported in of successful treatment of this rare malignancy in the setting of Fontan-associated liver disease and highlights the importance of a robust screening protocol in this patient population. Semiannual screening for the development of primary liver malignancy should start by 10 years post-Fontan and continue until heart-liver transplantation may be performed. It is important to note that cirrhosis is not a pre-requisite for the development of hepatocellular carcinoma or cholangiocarcinoma in these patients.

Evaluation of a whole-exome sequencing pipeline and benchmarking of causal germline variant prioritizers.

Most causal variants of Mendelian diseases are exonic. Whole-exome sequencing (WES) has become the diagnostic gold standard, but causative variant prioritization constitutes a bottleneck. Here we assessed an in-house sample-to-sequence pipeline and benchmarked free prioritization tools for germline causal variants from WES data. WES of 61 unselected patients with a known genetic disease cause was obtained. Variant prioritizations were performed by diverse tools and recorded to obtain a diagnostic yield when the causal variant was present in the first, fifth, and 10th top rankings. A fraction of causal variants was not captured by WES (8.2%) or did not pass the quality control criteria (13.1%). Most of the applications inspected were unavailable or had technical limitations, leaving nine tools for complete evaluation. Exomiser performed best in the top first rankings, while LIRICAL led in the top fifth rankings. Based on the more conservative top 10th rankings, Xrare had the highest diagnostic yield, followed by a three-way tie among Exomiser, LIRICAL, and PhenIX, then followed by AMELIE, TAPES, Phen-Gen,  AIVar, and VarNote-PAT. Xrare, Exomiser, LIRICAL, and PhenIX are the most efficient options for variant prioritization in real patient WES data.

Genomic amplification of chromosome 20q13.33 is the early biomarker for the development of sporadic colorectal carcinoma.

BACKGROUND: Colorectal carcinoma (CRC) is the third most common cancer in the world and also the third leading cause of cancer-related mortality in Taiwan. CRC tumorigenesis is a multistep process, starting from mutations causing loss of function of tumor suppressor genes, canonically demonstrated in adenomatous polyposis coli pathogenesis. Although many genes or chromosomal alterations have been shown to be involved in this process, there are still unrecognized molecular events within CRC tumorigenesis. Elucidating these mechanisms may help improve the management and treatment. METHODS: In this study, we aimed to identify copy number alteration of the smallest chromosomal regions that is significantly associated with sporadic CRC tumorigenesis using high-resolution array-based Comparative Genomic Hybridization (aCGH) and quantitative Polymerase chain reaction (qPCR). In addition, microsatellite instability assay and sequencing-based mutation assay were performed to illustrate the initiation event of CRC tumorigenesis. RESULTS: A total of 571 CRC patients were recruited and 377 paired CRC tissues from sporadic CRC cases were used to define the smallest regions with chromosome copy number changes. In addition, 198 colorectal polyps from 160 patients were also used to study the role of 20q13.33 gain in CRC tumorigenesis. We found that gain in 20q13.33 is the main chromosomal abnormalities in this patient population and counts 50.9 and 62.8% in CRC and colon polyps, respectively. Furthermore, APC and KRAS gene mutations were profiled simultaneously and co-analyzed with microsatellite instability and 20q13.33 gain in CRC patients. Our study showed that the frequency of 20q13.33 copy number gain was highest among all reported CRC mutations. CONCLUSION: As APC or KRAS mutations are currently identified as the most important targets for CRC therapy, this study proposes that 20q13.33 copy number gain and the associated chromosomal genes function as promising biomarkers for both early stage detection and targeted therapy of sporadic CRCs in the future.

TIAM2S Mediates Serotonin Homeostasis and Provokes a Pro-Inflammatory Immune Microenvironment Permissive for Colorectal Tumorigenesis.

The short isoform of human TIAM2 has been shown to promote proliferation and invasion in various cancer cells. However, the roles of TIAM2S in immune cells in relation to tumor development have not been investigated. To characterize the effects of TIAM2S, we generated TIAM2S-overexpressing mouse lines and found that aged TIAM2S-transgenic (TIAM2S-TG) developed significantly higher occurrence of lymphocytic infiltration and tumorigenesis in various organs, including colon. In addition, TIAM2S-TG is more sensitized to AOM-induced colon tumor development, suggesting a priming effect toward tumorigenesis. In the light of our recent findings that TIAM2S functions as a novel regulator of cellular serotonin level, we found that serotonin, in addition to Cox2, is a unique inflammation marker presented in the colonic lesion sites in the aged TG animals. Furthermore, our results demonstrated that ectopic TIAM2S altered immunity via the expansion of T lymphocytes; this was especially pronounced in CD8+ T cells in combination with CXCL13/BCA-1 pro-inflammatory chemokine in the serum of TIAM2S-TG mice. Consequently, T lymphocytes and B cells were recruited to the lesion sites and stimulated IL-23/IL17A expression to form the tertiary lymphoid organs. Collectively, our research suggests that TIAM2S provokes a pro-inflammatory immune microenvironment permissive to colorectal tumorigenesis through the serotonin-induced immunomodulatory effects.

Novel, provable algorithms for efficient ensemble-based computational protein design and their application to the redesign of the c-Raf-RBD:KRas protein-protein interface.

The K* algorithm provably approximates partition functions for a set of states (e.g., protein, ligand, and protein-ligand complex) to a user-specified accuracy ε. Often, reaching an ε-approximation for a particular set of partition functions takes a prohibitive amount of time and space. To alleviate some of this cost, we introduce two new algorithms into the osprey suite for protein design: fries, a Fast Removal of Inadequately Energied Sequences, and EWAK*, an Energy Window Approximation to K*. fries pre-processes the sequence space to limit a design to only the most stable, energetically favorable sequence possibilities. EWAK* then takes this pruned sequence space as input and, using a user-specified energy window, calculates K* scores using the lowest energy conformations. We expect fries/EWAK* to be most useful in cases where there are many unstable sequences in the design sequence space and when users are satisfied with enumerating the low-energy ensemble of conformations. In combination, these algorithms provably retain calculational accuracy while limiting the input sequence space and the conformations included in each partition function calculation to only the most energetically favorable, effectively reducing runtime while still enriching for desirable sequences. This combined approach led to significant speed-ups compared to the previous state-of-the-art multi-sequence algorithm, BBK*, while maintaining its efficiency and accuracy, which we show across 40 different protein systems and a total of 2,826 protein design problems. Additionally, as a proof of concept, we used these new algorithms to redesign the protein-protein interface (PPI) of the c-Raf-RBD:KRas complex. The Ras-binding domain of the protein kinase c-Raf (c-Raf-RBD) is the tightest known binder of KRas, a protein implicated in difficult-to-treat cancers. fries/EWAK* accurately retrospectively predicted the effect of 41 different sets of mutations in the PPI of the c-Raf-RBD:KRas complex. Notably, these mutations include mutations whose effect had previously been incorrectly predicted using other computational methods. Next, we used fries/EWAK* for prospective design and discovered a novel point mutation that improves binding of c-Raf-RBD to KRas in its active, GTP-bound state (KRasGTP). We combined this new mutation with two previously reported mutations (which were highly-ranked by osprey) to create a new variant of c-Raf-RBD, c-Raf-RBD(RKY). fries/EWAK* in osprey computationally predicted that this new variant binds even more tightly than the previous best-binding variant, c-Raf-RBD(RK). We measured the binding affinity of c-Raf-RBD(RKY) using a bio-layer interferometry (BLI) assay, and found that this new variant exhibits single-digit nanomolar affinity for KRasGTP, confirming the computational predictions made with fries/EWAK*. This new variant binds roughly five times more tightly than the previous best known binder and roughly 36 times more tightly than the design starting point (wild-type c-Raf-RBD). This study steps through the advancement and development of computational protein design by presenting theory, new algorithms, accurate retrospective designs, new prospective designs, and biochemical validation.

Sepsis-associated acute respiratory distress syndrome in individuals of European ancestry: a genome-wide association study.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a lung inflammatory process caused mainly by sepsis. Most previous studies that identified genetic risks for ARDS focused on candidates with biological relevance. We aimed to identify novel genetic variants associated with ARDS susceptibility and to provide complementary functional evidence of their effect in gene regulation. METHODS: We did a case-control genome-wide association study (GWAS) of 1935 European individuals, using patients with sepsis-associated ARDS as cases and patients with sepsis without ARDS as controls. The discovery stage included 672 patients admitted into a network of Spanish intensive care units between January, 2002, and January, 2017. The replication stage comprised 1345 individuals from two independent datasets from the MESSI cohort study (Sep 22, 2008-Nov 30, 2017; USA) and the VISEP (April 1, 2003-June 30, 2005) and MAXSEP (Oct 1, 2007-March 31, 2010) trials of the SepNet study (Germany). Results from discovery and replication stages were meta-analysed to identify association signals. We then used RNA sequencing data from lung biopsies, in-silico analyses, and luciferase reporter assays to assess the functionallity of associated variants. FINDINGS: We identified a novel genome-wide significant association with sepsis-associated ARDS susceptibility (rs9508032, odds ratio [OR] 0·61, 95% CI 0·41-0·91, p=5·18 × 10-8) located within the Fms-related tyrosine kinase 1 (FLT1) gene, which encodes vascular endothelial growth factor receptor 1 (VEGFR-1). The region containing the sentinel variant and its best proxies acted as a silencer for the FLT1 promoter, and alleles with protective effects in ARDS further reduced promoter activity (p=0·0047). A literature mining of all previously described ARDS genes validated the association of vascular endothelial growth factor A (VEGFA; OR 0·55, 95% CI 0·41-0·73; p=4·69 × 10-5). INTERPRETATION: A common variant within the FLT1 gene is associated with sepsis-associated ARDS. Our findings support a role for the vascular endothelial growth factor signalling pathway in ARDS pathogenesis and identify VEGFR-1 as a potential therapeutic target. FUNDING: Instituto de Salud Carlos III, European Regional Development Funds, Instituto Tecnológico y de Energías Renovables.

Minimization-Aware Recursive K*: A Novel, Provable Algorithm that Accelerates Ensemble-Based Protein Design and Provably Approximates the Energy Landscape.

Protein design algorithms that model continuous sidechain flexibility and conformational ensembles better approximate the in vitro and in vivo behavior of proteins. The previous state of the art, iMinDEE-A*-K*, computes provable ɛ-approximations to partition functions of protein states (e.g., bound vs. unbound) by computing provable, admissible pairwise-minimized energy lower bounds on protein conformations, and using the A* enumeration algorithm to return a gap-free list of lowest-energy conformations. iMinDEE-A*-K* runs in time sublinear in the number of conformations, but can be trapped in loosely-bounded, low-energy conformational wells containing many conformations with highly similar energies. That is, iMinDEE-A*-K* is unable to exploit the correlation between protein conformation and energy: similar conformations often have similar energy. We introduce two new concepts that exploit this correlation: Minimization-Aware Enumeration and Recursive K*. We combine these two insights into a novel algorithm, Minimization-Aware Recursive K* (MARK*), which tightens bounds not on single conformations, but instead on distinct regions of the conformation space. We compare the performance of iMinDEE-A*-K* versus MARK* by running the Branch and Bound over K* (BBK*) algorithm, which provably returns sequences in order of decreasing K* score, using either iMinDEE-A*-K* or MARK* to approximate partition functions. We show on 200 design problems that MARK* not only enumerates and minimizes vastly fewer conformations than the previous state of the art, but also runs up to 2 orders of magnitude faster. Finally, we show that MARK* not only efficiently approximates the partition function, but also provably approximates the energy landscape. To our knowledge, MARK* is the first algorithm to do so. We use MARK* to analyze the change in energy landscape of the bound and unbound states of an HIV-1 capsid protein C-terminal domain in complex with a camelid VHH, and measure the change in conformational entropy induced by binding. Thus, MARK* both accelerates existing designs and offers new capabilities not possible with previous algorithms.

Computational Analysis of Energy Landscapes Reveals Dynamic Features That Contribute to Binding of Inhibitors to CFTR-Associated Ligand.

The CFTR-associated ligand PDZ domain (CALP) binds to the cystic fibrosis transmembrane conductance regulator (CFTR) and mediates lysosomal degradation of mature CFTR. Inhibition of this interaction has been explored as a therapeutic avenue for cystic fibrosis. Previously, we reported the ensemble-based computational design of a novel peptide inhibitor of CALP, which resulted in the most binding-efficient inhibitor to date. This inhibitor, kCAL01, was designed using osprey and evinced significant biological activity in in vitro cell-based assays. Here, we report a crystal structure of kCAL01 bound to CALP and compare structural features against iCAL36, a previously developed inhibitor of CALP. We compute side-chain energy landscapes for each structure to not only enable approximation of binding thermodynamics but also reveal ensemble features that contribute to the comparatively efficient binding of kCAL01. Finally, we compare the previously reported design ensemble for kCAL01 vs the new crystal structure and show that, despite small differences between the design model and crystal structure, significant biophysical features that enhance inhibitor binding are captured in the design ensemble. This suggests not only that ensemble-based design captured thermodynamically significant features observed in vitro, but also that a design eschewing ensembles would miss the kCAL01 sequence entirely.

Novel idiopathic pulmonary fibrosis susceptibility variants revealed by deep sequencing.

BACKGROUND: Specific common and rare single nucleotide variants (SNVs) increase the likelihood of developing sporadic idiopathic pulmonary fibrosis (IPF). We performed target-enriched sequencing on three loci previously identified by a genome-wide association study to gain a deeper understanding of the full spectrum of IPF genetic risk and performed a two-stage case-control association study. METHODS: A total of 1.7 Mb of DNA from 181 IPF patients was deep sequenced (>100×) across 11p15.5, 14q21.3 and 17q21.31 loci. Comparisons were performed against 501 unrelated controls and replication studies were assessed in 3968 subjects. RESULTS: 36 SNVs were associated with IPF susceptibility in the discovery stage (p<5.0×10-8). After meta-analysis, the strongest association corresponded to rs35705950 (p=9.27×10-57) located upstream from the mucin 5B gene (MUC5B). Additionally, a novel association was found for two co-inherited low-frequency SNVs (<5%) in MUC5AC, predicting a missense amino acid change in mucin 5AC (lowest p=2.27×10-22). Conditional and haplotype analyses in 11p15.5 supported the existence of an additional contribution of MUC5AC variants to IPF risk. CONCLUSIONS: This study reinforces the significant IPF associations of these loci and implicates MUC5AC as another key player in IPF susceptibility.

TYRO3: A potential therapeutic target in cancer.

IMPACT STATEMENT: Cancer is among the leading causes of death worldwide. In 2016, 8.9 million people are estimated to have died from various forms of cancer. The current treatments, including surgery with chemotherapy and/or radiation therapy, are not effective enough to provide full protection from cancer, which highlights the need for developing novel therapy strategies. In this review, we summarize the molecular biology of a unique member of a subfamily of receptor tyrosine kinase, TYRO3 and discuss the new insights in TYRO3-targeted treatment for cancer therapy.

OSPREY 3.0: Open-source protein redesign for you, with powerful new features.

We present osprey 3.0, a new and greatly improved release of the osprey protein design software. Osprey 3.0 features a convenient new Python interface, which greatly improves its ease of use. It is over two orders of magnitude faster than previous versions of osprey when running the same algorithms on the same hardware. Moreover, osprey 3.0 includes several new algorithms, which introduce substantial speedups as well as improved biophysical modeling. It also includes GPU support, which provides an additional speedup of over an order of magnitude. Like previous versions of osprey, osprey 3.0 offers a unique package of advantages over other design software, including provable design algorithms that account for continuous flexibility during design and model conformational entropy. Finally, we show here empirically that osprey 3.0 accurately predicts the effect of mutations on protein-protein binding. Osprey 3.0 is available at http://www.cs.duke.edu/donaldlab/osprey.php as free and open-source software. © 2018 Wiley Periodicals, Inc.

Focused Neuro-Otological Review of Superficial Siderosis of the Central Nervous System.

BACKGROUND: Infratentorial siderosis (iSS) is a progressive degenerative disorder targeting primarily the cerebellum and cranial nerve eighth; therefore, progressive ataxia and its neuro-otological findings are common. Toxicity from hemosiderin involves selectively vulnerable neurons and glia in these posterior fossa structures. Other neurologic findings may be present, though our focus relates to the cochlea-vestibular cerebellar involvement. Radiographic evidence of siderosis may be the result of recurrent, albeit covert bleeding in the subarachnoid space, or the consequence of an overt post-traumatic or aneurysmal subarachnoid hemorrhage (SAH). The radiographic iSS appearance is identical regardless of the SAH cause. A recent study provides compelling evidence to search and correct possible hemorrhage sources in the spinal canal. The removal of residual existing hemosiderin deposits that may potentially cause clinical symptoms remains as a major therapeutic challenge. METHODS: We reviewed large data sources and identified salient papers that describe the pathogenesis, clinical and neurotologic manifestations, and the radiographic features of iSS. RESULTS: The epidemiology of iSS is unknown. In a recent series, clinically evident iSS was associated with recurrent SAH; by contrast, in a follow-up period ranging from weeks up to 11 years after a monophasic episode of SAH, radiographic siderosis was clinically silent. However, the post-aneurysmal or post-trauma SAH sample size in this single study was small and their observation period relatively short; moreover, the burden of intraneuronal hemosiderin is likely greater with recurrent SAH. There are a few reports of late iSS, several decades after traumatic SAH. A recent report found subjective hearing loss in aneurysmal SAH individuals with radiographic siderosis. Only in recent years, it is safe to perform magnetic resonance imaging (MRI) in post-aneurysmal SAH, because of the introduction of titanium, MRI-compatible aneurysm clips. CONCLUSION: iSS can be associated with significant neurotologic and cerebellar morbidity; the recurrent SAH variant is frequently clinically symptomatic, has a shorter latency and greater neurotologic disability. In these cases, a thorough search and management of a covert source of bleeding may stop clinical progression. The frequency and clinical course of radiographic iSS after traumatic and post-aneurysmal SAH is largely unknown. Detection of radiographic iSS after trauma or aneurysm bleeding suggests that the slower clinical course could benefit from an effective intervention if it became available. The use of cochlear implants is a valid alternative with advanced hearing impairment.

BBK* (Branch and Bound Over K*): A Provable and Efficient Ensemble-Based Protein Design Algorithm to Optimize Stability and Binding Affinity Over Large Sequence Spaces.

Computational protein design (CPD) algorithms that compute binding affinity, Ka, search for sequences with an energetically favorable free energy of binding. Recent work shows that three principles improve the biological accuracy of CPD: ensemble-based design, continuous flexibility of backbone and side-chain conformations, and provable guarantees of accuracy with respect to the input. However, previous methods that use all three design principles are single-sequence (SS) algorithms, which are very costly: linear in the number of sequences and thus exponential in the number of simultaneously mutable residues. To address this computational challenge, we introduce BBK*, a new CPD algorithm whose key innovation is the multisequence (MS) bound: BBK* efficiently computes a single provable upper bound to approximate Ka for a combinatorial number of sequences, and avoids SS computation for all provably suboptimal sequences. Thus, to our knowledge, BBK* is the first provable, ensemble-based CPD algorithm to run in time sublinear in the number of sequences. Computational experiments on 204 protein design problems show that BBK* finds the tightest binding sequences while approximating Ka for up to 105-fold fewer sequences than the previous state-of-the-art algorithms, which require exhaustive enumeration of sequences. Furthermore, for 51 protein-ligand design problems, BBK* provably approximates Ka up to 1982-fold faster than the previous state-of-the-art iMinDEE/[Formula: see text]/[Formula: see text] algorithm. Therefore, BBK* not only accelerates protein designs that are possible with previous provable algorithms, but also efficiently performs designs that are too large for previous methods.

A critical analysis of computational protein design with sparse residue interaction graphs.

Protein design algorithms enumerate a combinatorial number of candidate structures to compute the Global Minimum Energy Conformation (GMEC). To efficiently find the GMEC, protein design algorithms must methodically reduce the conformational search space. By applying distance and energy cutoffs, the protein system to be designed can thus be represented using a sparse residue interaction graph, where the number of interacting residue pairs is less than all pairs of mutable residues, and the corresponding GMEC is called the sparse GMEC. However, ignoring some pairwise residue interactions can lead to a change in the energy, conformation, or sequence of the sparse GMEC vs. the original or the full GMEC. Despite the widespread use of sparse residue interaction graphs in protein design, the above mentioned effects of their use have not been previously analyzed. To analyze the costs and benefits of designing with sparse residue interaction graphs, we computed the GMECs for 136 different protein design problems both with and without distance and energy cutoffs, and compared their energies, conformations, and sequences. Our analysis shows that the differences between the GMECs depend critically on whether or not the design includes core, boundary, or surface residues. Moreover, neglecting long-range interactions can alter local interactions and introduce large sequence differences, both of which can result in significant structural and functional changes. Designs on proteins with experimentally measured thermostability show it is beneficial to compute both the full and the sparse GMEC accurately and efficiently. To this end, we show that a provable, ensemble-based algorithm can efficiently compute both GMECs by enumerating a small number of conformations, usually fewer than 1000. This provides a novel way to combine sparse residue interaction graphs with provable, ensemble-based algorithms to reap the benefits of sparse residue interaction graphs while avoiding their potential inaccuracies.

LUTE (Local Unpruned Tuple Expansion): Accurate Continuously Flexible Protein Design with General Energy Functions and Rigid Rotamer-Like Efficiency.

Most protein design algorithms search over discrete conformations and an energy function that is residue-pairwise, that is, a sum of terms that depend on the sequence and conformation of at most two residues. Although modeling of continuous flexibility and of non-residue-pairwise energies significantly increases the accuracy of protein design, previous methods to model these phenomena add a significant asymptotic cost to design calculations. We now remove this cost by modeling continuous flexibility and non-residue-pairwise energies in a form suitable for direct input to highly efficient, discrete combinatorial optimization algorithms such as DEE/A* or branch-width minimization. Our novel algorithm performs a local unpruned tuple expansion (LUTE), which can efficiently represent both continuous flexibility and general, possibly nonpairwise energy functions to an arbitrary level of accuracy using a discrete energy matrix. We show using 47 design calculation test cases that LUTE provides a dramatic speedup in both single-state and multistate continuously flexible designs.

BWM*: A Novel, Provable, Ensemble-based Dynamic Programming Algorithm for Sparse Approximations of Computational Protein Design.

Sparse energy functions that ignore long range interactions between residue pairs are frequently used by protein design algorithms to reduce computational cost. Current dynamic programming algorithms that fully exploit the optimal substructure produced by these energy functions only compute the GMEC. This disproportionately favors the sequence of a single, static conformation and overlooks better binding sequences with multiple low-energy conformations. Provable, ensemble-based algorithms such as A* avoid this problem, but A* cannot guarantee better performance than exhaustive enumeration. We propose a novel, provable, dynamic programming algorithm called Branch-Width Minimization* (BWM*) to enumerate a gap-free ensemble of conformations in order of increasing energy. Given a branch-decomposition of branch-width w for an n-residue protein design with at most q discrete side-chain conformations per residue, BWM* returns the sparse GMEC in O([Formula: see text]) time and enumerates each additional conformation in merely O([Formula: see text]) time. We define a new measure, Total Effective Search Space (TESS), which can be computed efficiently a priori before BWM* or A* is run. We ran BWM* on 67 protein design problems and found that TESS discriminated between BWM*-efficient and A*-efficient cases with 100% accuracy. As predicted by TESS and validated experimentally, BWM* outperforms A* in 73% of the cases and computes the full ensemble or a close approximation faster than A*, enumerating each additional conformation in milliseconds. Unlike A*, the performance of BWM* can be predicted in polynomial time before running the algorithm, which gives protein designers the power to choose the most efficient algorithm for their particular design problem.

Temporal and spatial expression of tight junction genes during zebrafish pronephros development.

The kidney is comprised of nephrons - epithelial tubes with specialized segments that reabsorb and secrete solutes, perform osmoregulation, and produce urine. Different nephron segments exhibit unique combinations of ion channels, transporter proteins, and cell junction proteins that govern permeability between neighboring cells. The zebrafish pronephros is a valuable model to study the mechanisms of vertebrate nephrogenesis, but many basic features of segment gene expression in renal progenitors and mature nephrons have not been characterized. Here, we analyzed the temporal and spatial expression pattern of tight junction components during zebrafish kidney ontogeny. During nephrogenesis, renal progenitors show discrete expression domains of claudin (cldn) 15a, cldn8, occludin (ocln) a, oclnb, tight junction protein (tjp) 2a, tjp2b, and tjp3. Interestingly, transcripts encoding these genes exhibit dynamic spatiotemporal domains during the time when pronephros segment domains are established. These data provide a useful gene expression map of cell junction components during zebrafish nephrogenesis. As such, this information complements the existing molecular map of nephron segment characteristics, and can be used to characterize kidney development mutants as well as various disease models, in addition to aiding in the elucidation of mechanisms governing epithelial regeneration after acute nephron injury.