Biology subjects

Tan, Z.

Publications and source records attributed to Tan, Z..

At least 55 records · Page 3Linked to original sources

bioRxiv2021

Fast anther dehiscence state recognition system establishing by deep learning to screen heat tolerant cotton

Cotton is one of the most economically important crops in the world. The fertility of male reproductive organs is a key determinant of cotton yield. The anther dehiscence or indehiscence directly determine the probability of fertilization in cotton. Thus, the rapid and accurate identification of cotton anther dehiscence status is important for judging anther growth status and promoting genetic breeding research. The development of computer vision technology and the advent of big data have prompted the application of deep learning techniques to agricultural phenotype research. Therefore, two deep learning models (Faster R-CNN and YOLOv5) were proposed to detect the number and dehiscence status of anthers. The single-stage model based on YOLOv5 has higher recognition efficiency and the ability to deploy to the mobile end. Breeding researchers can apply this model to terminals to achieve a more intuitive understanding of cotton anther dehiscence status. Moreover, three improvement strategies of Faster R-CNN model were proposed, the improved model has higher detection accuracy than YOLOv5 model. In addition, the percentage of dehiscent anther of randomly selected 30 cotton varieties were observed from cotton population under normal temperature and high temperature (HT) conditions through the integrated Faster R-CNN model and manual observation. The result showed HT varying decreased the percentage of dehiscent anther in different cotton lines, consistent with the manual method. Thus, this system can help us to rapid and accurate identification of HT-tolerant cotton. One sentence summaryThe deep learning technique was applied to identify the anther dehiscence state for the first time to quickly screen heat tolerant cotton varieties and help to explore key genetic improvement genes.

bioengineering↗

bioRxiv2021

Kinesin-binding protein remodels the kinesin motor to prevent microtubule-binding

Kinesins are tightly regulated in space and time to control their activation in the absence of cargo-binding. Kinesin-binding protein (KIFBP) was recently discovered to bind the catalytic motor heads of 8 of the 45 known kinesin superfamily members and inhibit binding to microtubules. In humans, mutation of KIFBP gives rise to Goldberg-Shprintzen syndrome (GOSHS), but the kinesin(s) that is misregulated to produce clinical features of the disease is not known. Understanding the structural mechanism by which KIFBP selects its kinesin binding partners will be key to unlocking this knowledge. Using a combination of cryo-electron microscopy and crosslinking mass spectrometry, we determined structures of KIFBP alone and in complex with two mitotic kinesins, revealing regions of KIFBP that participate in complex formation. KIFBP adopts an alpha-helical solenoid structure composed of TPR repeats. We find that KIFBP uses a 2-pronged mechanism to remodel kinesin motors and block microtubule-binding. First, KIFBP engages the microtubule-binding interface and sterically blocks interaction with microtubules. Second, KIFBP induces allosteric conformational changes to the kinesin motor head that displace a key structural element in the kinesin motor head (-helix 4) required for microtubule binding. We identified two regions of KIFBP necessary for in vitro kinesin-binding as well as cellular regulation during mitosis. Taken together, this work establishes the mechanism of kinesin inhibition by KIFBP and provides the first example of motor domain remodeling as a means to abrogate kinesin activity.

cell biology↗

bioRxiv2021

Inferring population structure in biobank-scale genomic data

Inferring the structure of human populations from genetic variation data is a key task in population and medical genomic studies. While a number of methods for population structure inference have been proposed, current methods are impractical to run on biobank-scale genomic datasets containing millions of individuals and genetic variants. We introduce SCOPE, a method for population structure inference that is orders of magnitude faster than existing methods while achieving comparable accuracy. SCOPE infers population structure in about a day on a dataset containing one million individuals and variants as well as on the UK Biobank dataset containing 488,363 individuals and 569,346 variants. Furthermore, SCOPE can leverage allele frequencies from previous studies to improve the interpretability of population structure estimates.

bioinformatics↗

bioRxiv2020

Bifidobacteria-mediated immune system imprinting early in life

Immune-microbe interactions early in life influence an individuals risk of developing allergies, asthma and some autoimmune disorders. Breastfeeding helps guide the development of healthy immune-microbe relationships, in part by providing nutrients to specialized microbes that in turn benefit the host and its developing immune system. Such bacteria having co-evolved with humans are associated with reduced risks of immune mediated diseases but are increasingly rare in modern societies. Here we map an immunological sequence of events, triggered by microbial colonization that distinguish children with different gut bacterial composition. Lack of bifidobacterial species is associated with elevated markers of intestinal inflammation and immune dysregulation and in a randomized trial of breastfed infants, the infant-adapted Bifidobacterium infantis EVC001 silenced intestinal Th2 and Th17 immune responses, while inducing IFN{beta}, and its metabolites skew T-cell polarization in vitro, from Th2 towards Th1, suggesting a healthier immune imprinting during the first critical months of life. HIGHLIGHTSAn ordered sequence of immune changes after birth, driven by microbial interactions Low gut Bifidobacterium abundance is associated with markers of intestinal inflammation Feeding B. infantis EVC001 silenced intestinal Th2 and Th17 but upregulates IFN{beta} B. infantis EVC001 metabolites and/or enteric cytokines skew naive T-cell polarization towards Th1 and away from Th2

immunology↗

bioRxiv2020

Characterization and expression QTL analysis of TaABI4, a pre-harvest sprouting related gene in wheat

Pre-harvest sprouting (PHS) induced by the decline of seed dormancy causes a severe reduction in crop yield and flour quality. In this study, we isolated and characterized TaABI4, an ABA-responsive transcription factor that participates in regulating seed germination in wheat. Sequence analysis revealed that TaABI4 has three homologues, located on chromosomes 1A/1B/1D. TaABI4 contains a conserved AP2 domain, and AP2-associated, LRP, and potential PEST motifs. Putative cis-acting regulatory elements (CE1-like box, W-box, ABRE elements, and RY-elements) were identified in the TaABI4 promoter region that showed high conservation in 17 wheat cultivars and wheat-related species. Expression profiling of TaABI4 indicated that it is a seed-specific gene accumulating during the middle stages of seed development. Transcript accumulation of TaABI4 in wheat cultivar Chuanmai 32 (CM32, PHS susceptible) was 5.07-fold and 1.39-fold higher than that in synthetic hexaploidy wheat SHW-L1 (PHS resistant) at 15DPA and 20DPA, respectively. Six expression quantitative trait loci (eQTL) of TaABI4 on chromosome 2A, 2D, 3B, and 4A were characterized based on the accumulated transcripts of TaABI4 in SHW-L1 and CM32 derived recombinant inbred lines. These QTLs explained from 10.7% to 46.1% of the trait variation with 4.53~10.59 of LOD scores, which contain genes that may affect the expression of TaABI4.

genetics↗

bioRxiv2020

SARS-CoV-2 Quasispecies provides insight into its genetic dynamics during infection

A novel coronavirus disease (COVID-19) caused by SARS-CoV-2 has been pandemic worldwide. The genetic dynamics of quasispecies afford RNA viruses a great fitness on cell tropism and host range. However, no quasispecies data of SARS-CoV-2 have been reported yet. To explore quasispecies haplotypes and its transmission characteristics, we carried out single-molecule real-time (SMRT) sequencing of the full-length of SARS-CoV-2 spike gene within 14 RNA samples from 2 infection clusters, covering first-to third-generation infected-patients. We observed a special quasispecies structure of SARS-CoV-2 (modeled as One-King): one dominant haplotype (mean abundance ~70.15%) followed by numerous minor haplotypes (mean abundance < 0.10%). We not only discovered a novel dominant haplotype of F1040 but also realized that minor quasispecies were also worthy of attention. Notably, some minor haplotypes (like F1040 and currently pandemic one G614) could potentially reveal adaptive and converse into the dominant one. However, minor haplotypes exhibited a high transmission bottleneck (~6% could be stably transmitted), and the new adaptive/dominant haplotypes were likely originated from genetic variations within a host rather than transmission. The evolutionary rate was estimated as 2.68-3.86 x 10-3 per site per year, which was larger than the estimation at consensus genome level. The One-King model and conversion event expanded our understanding of the genetic dynamics of SARS-CoV-2, and explained the incomprehensible phenomenon at the consensus genome level, such as limited cumulative mutations and low evolutionary rate. Moreover, our findings suggested the epidemic strains may be multi-host origin and future traceability would face huge difficulties.

pathology↗

bioRxiv2020

Binding of the SARS-CoV-2 Spike Protein to Glycans

The pandemic of SARS-CoV-2 has caused a high number of deaths in the world. To combat it, it is necessary to develop a better understanding of how the virus infects host cells. Infection normally starts with the attachment of the virus to cell-surface glycans like heparan sulfate (HS) and sialic acid-containing oligosaccharides. In this study, we examined and compared the binding of the subunits and spike (S) proteins of SARS-CoV-2 and SARS-CoV, MERS-CoV to these glycans. Our results revealed that the S proteins and subunits can bind to HS in a sulfation-dependent manner, the length of HS is not a critical factor for the binding, and no binding with sialic acid residues was detected. Overall, this work suggests that HS binding may be a general mechanism for the attachment of these coronaviruses to host cells, and supports the potential importance of HS in infection and in the development of antiviral agents against these viruses.Competing Interest StatementThe authors have declared no competing interest.View Full Text

biochemistry↗

bioRxiv2020

Detect Genomic G-Quadruplexes in Living Animal Cells with a Tiny Artificial Protein Probe

G-quadruplex (G4) structures formed by guanine-rich nucleic acids are implicated in essential physiological processes and serve as important drug targets. The genome-wide detection of G4s in living cells is important for exploring the biological role of G4s but has not yet been achieved due to the lack of a suitable G4 probe. We engineered a 6.7 kDa G4 probe (G4P) protein that binds G4s with high affinity and specificity. We used it to capture G4s in living human, mouse, and chicken cells with the ChIP-Seq technology, yielding genome-wide landscape as well as details on the positions, frequencies, and sequence identities of G4 formation in these cells. Our results indicate that transcription is accompanied by a robust formation of G4s in genes. In human cells, we detected up to >123,000 G4 peaks, of which >1/3 had a fold increase of [≥]5 and were present in >60% promoters and ~70% genes. Being much smaller than a scFv antibody (27 kDa) or even a nanobody (12-15 kDa), we expect that the G4P may find diverse applications in biology, medicine, and molecular devices as a G4 affinity agent.

biochemistry↗

bioRxiv2020

JavaDL: a Java-based Deep Learning Tool to Predict Drug Responses

MotivationAccurate prediction of drug response in each patient is the holy grail in personalized medicine. Recently, deep learning techniques have been witnessed with revival in a variety of areas such as image processing and genomic data analysis, and they will be useful for the coming age of big data analysis in pharmaceutical research and chemogenomic applications. This provides us an impetus to develop a novel deep learning platform to accurately and reliably predict the response of cancer to different drug treatments. ResultsIn this study, we describe a Java-based implementation of deep neural network (DNN) method, termed JavaDL, to predict cancer responses to drugs solely based on their chemical features. To this end, we devised a novel cost function by adding a regularization term which suppresses overfitting. We also adopted an "early stopping" strategy to further reduce overfit and improve the accuracy and robustness of our models. Currently the software has been integrated with a genetic algorithm-based variable selection approach and implemented as part of our JavaDL package. To evaluate our program, we compared it with several machine learning programs including SVM and kNN. We observed that JavaDL either significantly outperforms other methods in model building and prediction or obtains better results in handling big data analysis. Finally, JavaDL was employed to predict drug responses of several highly aggressive triple-negative breast cancer cell lines, and the results showed robust and accurate predictions with r2 as high as 0.80. AvailabilityThe program is freely available at https://imdlab.mdanderson.org/JavaDL/JavaDL.php.

bioinformatics↗

bioRxiv2020

Relatively semi-conservative replication and a folded slippage model for simple repeat sequences

Simple sequence repeats (SSRs) are found ubiquitously in almost all genome, and their formation mechanism is ambiguous yet. Here, the SSRs were analyzed in 55 randomly selected segments of genomes from a fairly wide range of species, with introducing more open standard for extensively mining repeats. A high percentage of repeats were discovered in these segments, which is inconsistent with the current theory suggested that repeats tend to disappear over long-term evolution. Therefore, a mechanism is most probably responsible for continually producing repeats during replication to balance continuous repeat disappearance, which may makes the replicating process relatively semi-conservative. To improve the current straight-line slippage model, we proposed a folded slippage model involving the geometric space of nucleotides and hydrogen bond stability to explain the high-percent SSR occurrence, which can describe SSR expansion and contraction more reasonably. And analysis of external forces in the folding template strands suggested that the microsatellites tend to expand than contract. Our research may provide implements for contributions of microsatellites to genome evolution and complement semi-conservative replication.

molecular biology↗

bioRxiv2020

Distinct organization of two cortico-cortical feedback pathways

Neocortical feedback is critical for processes like attention, prediction, and learning. A mechanistic understanding of its function requires deciphering its cell-type wiring logic. Recent studies revealed a disinhibitory circuit between motor and sensory areas in mice, where feedback preferentially targets vasointestinal peptide-expressing interneurons, in addition to pyramidal cells. It is unknown whether this circuit motif is a general cortico-cortical feedback organizing principle. Combining multiple simultaneous whole-cell recordings with optogenetics we found that in contrast to this wiring rule, feedback between the hierarchically organized visual areas (lateral-medial to V1) preferentially activated somatostatin-expressing interneurons. Functionally, both feedback circuits temporally sharpened feed-forward excitation by eliciting a transient increase followed by a prolonged decrease in pyramidal firing rate under sustained feed-forward input. However, under feed-forward transient input, the motor-sensory feedback facilitated pyramidal cell bursting while visual feedback increased spike time precision. Our findings argue for multiple feedback motifs implementing different dynamic non-linear operations.

neuroscience↗

bioRxiv2019

MYPT1 O-GlcNAcylation Dictates Timely Disjunction of Centrosomes

The role of O-linked N-acetylglucosamine (O-GlcNAc) modification in the cell cycle has been enigmatic. Previously, both O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA) disruption have been shown to derail the mitotic centrosome numbers, suggesting that mitotic O-GlcNAc oscillation needs to be in concert with mitotic progression to account for centrosome integrity. Here we attempted to address the underlying molecular mechanism by both chemical approaches and biological assays, and observed that Thiamet-G (OGA inhibitor) incubation strikingly elevated centrosomal distances, suggestive of premature centrosome disjuction. These aberrancies could be overcome by inhibiting Polo-like kinase 1 (Plk1), a mitotic master kinase. Plk1 inactivation is modulated by the Myosin Phosphatase Targeting Subunit 1 (MYPT1)-Protein Phosphatase 1 c{beta} (PP1c{beta}) complex. Interestingly, MYPT1 is abundantly O-GlcNAcylated and the modified residues have been detected in a recent O-GlcNAc profiling screen utilizing chemoenzymatic labeling and bioorthogonal conjugation. We demonstrate that MYPT1 is O-GlcNAcylated at T577, S585, S589 and S601, which antagonizes CDK1-dependent phosphorylation at S473, subsequently attenuating the association between MYPT1 and Plk1, and promoting PLK1 activity. Thus under high O-GlcNAc, Plk1 is untimely activated, conducive to inopportune centrosome separation and disrupting the cell cycle. We propose that too much O-GlcNAc is equally deleterious as too little O-GlcNAc, and a fine balance between the OGT/OGA duo is indispensible for successful mitotic divisions.

biochemistry↗

bioRxiv2019

Identification of Chikungunya virus nucleocapsid core assembly modulators

AbstractThe alphavirus Chikungunya virus is transmitted to humans via infected mosquitos. Most infected humans experience symptoms which can range from short-term fatigue and fever to debilitating arthritis that can last for months or years. Some patients relapse and experience symptoms months or years after the initial bout of disease. The capsid protein of Chikungunya virus forms a shell around the viral RNA genome; this structure is called the nucleocapsid core. The core protects the genome during virus transmission and with the correct environmental trigger, this proteinaceous shell dissociates and releases the viral genome to initiate infection. We hypothesized that targeting compounds to interfere with the nucleocapsid cores function would constrain virus spread either by inhibiting the release of viral genomes during entry or by reducing the number of infectious virus particles assembled. We implemented a high throughput, in vitro, FRET-based assay to monitor nucleic acid packaging by purified Chikungunya capsid protein as a proxy for nucleocapsid core assembly and disassembly. We screened 10,000 compounds and found 45 that substantially modulated the assembly of core-like particles. A subset of compounds was selected to study their effects in virus-infected vertebrate cells. Our results show that four compounds inhibit infectious virus production by at least 90% in a dose-dependent manner. The most promising inhibitor was tested and found to reduce the amount of nucleocapsid cores inside the cell during Chikungunya virus infection. These compounds could be the foundation for anti-viral therapeutics.\n\nHighlightsO_LIA FRET-based assay to detect nucleic acid packaging by Chikungunya virus capsid protein\nC_LIO_LIIdentification of small molecules that modulate core-like particle assembly\nC_LIO_LIA subset of compounds that interfere with in vitro assembly also inhibit Chikungunya virus production in cell culture\nC_LIO_LIIdentification of antiviral molecules that may not be identified by assays using reporter viruses\nC_LIO_LIPotential starting compounds for developing direct-acting antivirals\nC_LI

microbiology↗

bioRxiv2019

Extensive genetic diversity of bat-borne polyomaviruses reveals inter-family host-switching events

Polyomaviruses (PyVs) are small, double-stranded DNA tumor viruses carried by diverse vertebrates. PyVs have previously been considered highly host restricted in mammalian hosts, with host-switching events thought rare or nonexistent. Prior investigations have revealed short-range host-switching events of PyVs in two different African bat species within the horseshoe bat genus Rhinolophus. Herein, we have conducted a systematic investigation of PyVs in 1,083 archived bat samples collected from five provinces across China, and identified 192 PyVs from 186 bats from 15 host species within 6 families (Rhinolophidae, Vespertilionidae, Hipposideridae, Emballonuridae, Miniopteridae and Pteropodidae) representing 28 newly-described PyVs, indicative of extensive genetic diversity of bat PyVs. Surprisingly, two PyVs were identified in multiple bat species from different families, and another PyV clustered phylogenetically with PyVs carried by bats from a different host family, indicative of three inter-family PyV host-switching events. The time to most recent common ancestor (tMRCA) of the three events was estimated at 0.02-11.6 million years ago (MYA), which is inconsistent with the estimated tMRCA of their respective bat hosts (36.3-66.7 MYA), and is most parsimoniously explained by host-switching events. PyVs identified from geographically separated Chinese horseshoe bat species in the present study showed close genetic identities, and clustered with each other and with PyVs from African horseshoe bats, allowing assessment of the effects of positive selection in VP1 within the horseshoe bat family Rhinolophidae. Correlation analysis indicated that co-evolution with their hosts contributed much more to evolutionary divergence of PyV than geographic distance. In conclusion, our findings provide the first evidence of inter-family host-switching events of PyV in mammals and challenge the prevailing evolutionary paradigm for strict host restriction of mammalian PyVs.\n\nAuthor summarySince the discovery of murine polyomavirus in the 1950s, polyomaviruses (PyVs) have been considered both genetically stable and highly host-restricted in their mammalian hosts. In this study, we have identified multiple cases of host-switching events of PyVs by large scale surveillance in diverse bat species collected in China. These host-switching events occurred between bat families living in the same colony, indicating that a large population with frequent contacts between different bat species may represent an ecological niche facilitating PyV host-switching. The cases studied involved members of bats from several families, including horseshoe bats, which were previously found to harbor a number of highly virulent viruses to both humans and domestic animals. Our findings have provided evidence that even highly host-specific DNA viruses can transmit between bats of different species and indicate an increased propensity for spillover events involving horseshoe bats. We propose an evolutionary scheme for bat-borne PyVs in which intra-host divergence and host-switching has generated the diverse PyVs in present day bats. This scheme provides a useful model to study the evolution of PyVs in other hosts and, potentially, the modeling of bat zoonoses and the transmission of other DNA viruses in other mammals, including humans.

microbiology↗

bioRxiv2019

Identification of viruses with the potential to infect human

The virus has caused much mortality and morbidity to humans, and still posed a serious threat to the global public health. The virome with the human-infection potential is far from complete. Novel viruses have been discovered at an unprecedented pace as the rapid development of viral metagenomics. However, there is still a lack of a method for rapidly identifying the virus with the human-infection potential. This study built several machine learning models for discriminating the human-infecting viruses from other viruses based on the frequency of k-mers in the viral genomic sequences. The k-nearest neighbor (KNN) model could predict the human-infecting virus with an accuracy of over 90%. Even for the KNN models built on the contigs as short as 1kb, they performed comparably to those built on the viral genomes, suggesting that the models could be used to identify the human-infecting virus from the viral metagenomic sequences. This work could help for discovery of novel human-infecting virus in metagenomics studies.

bioinformatics↗

bioRxiv2019

CRISPR/Cas9-based mutagenesis frequently provokes on-target mRNA misregulation

The introduction of insertion-deletions (INDELs) by activation of the error-prone non-homologous end-joining (NHEJ) pathway underlies the mechanistic basis of CRISPR/Cas9-directed genome editing. The ability of CRISPR/Cas9 to achieve gene elimination (knockouts) is largely attributed to the emergence of a pre-mature termination codon (PTC) from a frameshift-inducing INDEL that elicits non-sense mediated decay (NMD) of the mutant mRNA. Yet, the impact on gene expression as a consequence of CRISPR/Cas9-introduced INDELs into RNA regulatory sequences has been largely left uninvestigated. By tracking DNA-mRNA-protein relationships in a collection of CRISPR/Cas9-edited cell lines that harbor frameshift-inducing INDELs in various targeted genes, we detected the production of foreign mRNAs or proteins in [~]50% of the cell lines. We demonstrate that these aberrant protein products are derived from the introduction of INDELs that promote internal ribosomal entry, convert pseudo-mRNAs into protein encoding molecules, or induce exon skipping by disruption of exon splicing enhancers (ESEs). Our results using CRISPR/Cas9-introduced INDELs reveal facets of an epigenetic genome buffering apparatus that likely evolved to mitigate the impact of such mutations introduced by pathogens and aberrant DNA damage repair, and that more recently pose challenges to manipulating gene expression outcomes using INDEL-based mutagenesis.

molecular biology↗

bioRxiv2018

Effect of soybean molasses-adsorbents on in vitro ruminal fermentation characteristics, milk production performance in lactating dairy cows

This study aimed to evaluate the in vitro fermentation characteristics of corncob powder (CRP), wheat bran (WB), rice husk (RH), defatted bran (DB) and soybean hulls (SH) when mixed with soybean molasses at a ratio of 30:100 (dry matter basis), using a batch culture incubation. During in vitro study, SH showed better fermentation characteristics (including greater maximum gas production, shorter time to achieve half of Vf, greater concentrations of acetate, propionate and total VFA, and less initial fractional rate of degradation) than other four substrates, while WB had the greatest values of DM and NDF disappearance, NH3-N and butyrate concentrations among substrates. A randomized complete block designed in vivo experiment was conducted with 24 Holstein cows (534 {+/-} 58 kg BW, 2.8 {+/-} 0.7 parity, 129 {+/-} 23 d in milk) randomly assigned to three experimental diets: Control, WB (WB adsorbed to soybean molasses replaced 150 g of corn meal per 1000 g of diet dry matter [DM]) or SH (SH adsorbed to soybean molasses replaced 100 g of wheat bran and 50 g corn meal per 1000 g of diet DM). The results indicated that cows received WB diet had greater (P<0.01) milk fat and total milk solid content than cows fed control and SH diets, and cows received WB and SH diets tended to have greater (P<0.01) milk protein content and blood glutamic-pyruvic transaminase concentration than cows fed control diet. Furtherly, cows received WB diet had greater (P<0.01) blood amylase and lactate dehydrogenase concentration than that of cows fed control diet during middle lactation.\n\nIn conclusion, dietary supplementation of molasses adsorbed by-products like WB and SH have positive effect on promoting rumen fermentation, milk quality and blood metabolism in early- and middle-lactating dairy cows. The results offered a new products and feeding way in dairy farming

animal behavior and cognition↗

bioRxiv2018

Chemically Accurate Relative Folding Stability of RNA Hairpins from Molecular Simulations

This study describes a comparison between melts and simulated stabilities of the same RNAs that could be used to benchmark RNA force fields, and potentially to determine future melt-ing experiments. Using umbrella sampling molecular simulations of three 12-nucleotide RNA hairpin stem loops, for which there are experimentally determined free energies of unfold-ing, we projected unfolding onto the reaction coordinate of end to end (5' to 3' hydroxyl oxygen) distance. We estimate the free energy change of the transition from the native con-formation to a fully extended conformation--the stretched state--with no hydrogen bonds between non-neighboring bases. Each simulation was performed four times using the AM-BER FF99+bsc0+{chi}OL3 force field and each window, spaced at 1 [A] intervals, was sampled for 1 s, for a total of 552 s of simulation. We compared differences in the simulated free energy changes to analogous differences in free energies from optical melting experiments using ther-modynamic cycles where the free energy change between stretched and random coil sequences is assumed to be sequence independent. The differences between experimental and simulated {Delta}{Delta}G{degrees} are on average 1.00 {+/-} 0.66 kcal/mol, which is chemically accurate and suggests analo-gous simulations could be used predictively. We also report a novel method to identify where replica free energies diverge along the reaction coordinate, thus indicating where additional sampling would most improve convergence. We conclude by discussing methods to more economically perform such simulations.

biophysics↗