Multiple Binding Events Research Articles

Single-molecule imaging of SWI/SNF chromatin remodelers reveals bromodomain-mediated and cancer-mutants-specific landscape of multi-modal DNA-binding dynamics

Despite their prevalent cancer implications, the in vivo dynamics of SWI/SNF chromatin remodelers and how misregulation of such dynamics underpins cancer remain poorly understood. Using live-cell single-molecule tracking, we quantify the intranuclear diffusion and chromatin-binding of three key subunits common to all major human SWI/SNF remodeler complexes (BAF57, BAF155 and BRG1), and resolve two temporally distinct stable binding modes for the fully assembled complex. Super-resolved density mapping reveals heterogeneous, nanoscale remodeler binding “hotspots” across the nucleoplasm where multiple binding events (especially longer-lived ones) preferentially cluster. Importantly, we uncover distinct roles of the bromodomain in modulating chromatin binding/targeting in a DNA-accessibility-dependent manner, pointing to a model where successive longer-lived binding within “hotspots” leads to sustained productive remodeling. Finally, systematic comparison of six common BRG1 mutants implicated in various cancers unveils alterations in chromatin-binding dynamics unique to each mutant, shedding insight into a multi-modal landscape regulating the spatio-temporal organizational dynamics of SWI/SNF remodelers.

Quantitative study of early-stage transient bacterial adhesion to bioactive glass and glass ceramics: atomic force microscopic observations

Antimicrobial potential of bioactive glass (BAG) makes it promising for implant applications, specifically overcoming the toxicity concerns associated with traditional antibacterial nanoparticles. The 58S composition of BAG (with high Ca and absence of Na) has been known to exhibit excellent bioactivity and antibacterial behaviour, but the mechanisms behind have not been investigated in detail. In this pioneering study, we are using Atomic Force Microscopy (AFM) to gain insights into 58S BAG’s adhesive interactions with planktonic cells of both gram-positive (Staphylococcus aureus) and gram-negative (Escherichia coli) bacteria; along with the impact of crystallinity on antibacterial properties. We have recorded greater bacterial inhibition by amorphous BAG compared to semi-crystalline glass–ceramics and stronger effect against gram-negative bacteria via conventional long-term antibacterial tests. AFM force distance curves has illustrated substantial bonding between bacteria and BAG within the initial one second (observed at a gap of 250 ms) of contact, with multiple binding events. Further, stronger adhesion of BAG with E.coli (~ 6 nN) compared to S. aureus (~ 3 nN) has been found which can be attributed to more adhesive nano-domains (size effect) distributed uniformly on E.coli surface. This study has revealed direct evidence of impact of contact time and 58S BAG’s crystalline phase on bacterial adhesion and antimicrobial behaviour. Current study has successfully demonstrated the mode and mechanisms of initial bacterial adhesion with 58S BAG. The outcome can pave the way towards improving the designing of implant surfaces for a range of biomedical applications.

EIF1 and eIF5 dynamically control translation start site fidelity.

Translation initiation defines the identity of a synthesized protein through selection of a translation start site on a messenger RNA. This process is essential to well-controlled protein synthesis, modulated by stress responses, and dysregulated in many human diseases. The eukaryotic initiation factors eIF1 and eIF5 interact with the initiator methionyl-tRNAi Met on the 40S ribosomal subunit to coordinate start site selection. Here, using single-molecule analysis of in vitro reconstituted human initiation combined with translation assays in cells, we examine eIF1 and eIF5 function. During translation initiation on a panel of RNAs, we monitored both proteins directly and in real time using single-molecule fluorescence. As expected, eIF1 loaded onto mRNAs as a component of the 43S initiation complex. Rapid (~ 2 s) eIF1 departure required a translation start site and was delayed by alternative start sites and a longer 5' untranslated region (5'UTR). After its initial departure, eIF1 rapidly and transiently sampled initiation complexes, with more prolonged sampling events on alternative start sites. By contrast, eIF5 only transiently bound initiation complexes late in initiation immediately prior to association of eIF5B, which allowed joining of the 60S ribosomal subunit. eIF5 association required the presence of a translation start site and was inhibited and destabilized by alternative start sites. Using both knockdown and overexpression experiments in human cells, we validated that eIF1 and eIF5 have opposing roles during initiation. Collectively, our findings demonstrate how multiple eIF1 and eIF5 binding events control start-site selection fidelity throughout initiation, which is tuned in response to changes in the levels of both proteins.

Photonic Crystal Surface Mode Real-Time Imaging of RAD51 DNA Repair Protein Interaction with the ssDNA Substrate.

Photonic crystals (PCs) are promising tools for label-free sensing in drug discovery screening, diagnostics, and analysis of ligand-receptor interactions. Imaging of PC surface modes has emerged as a novel approach to the detection of multiple binding events at the sensor surface. PC surface modification and decoration with recognition units yield an interface providing the highly sensitive detection of cancer biomarkers, antibodies, and oligonucleotides. The RAD51 protein plays a central role in DNA repair via the homologous recombination pathway. This recombinase is essential for the genome stability and its overexpression is often correlated with aggressive cancer. RAD51 is therefore a potential target in the therapeutic strategy for cancer. Here, we report the designing of a PC-based array sensor for real-time monitoring of oligonucleotide-RAD51 recruitment by means of surface mode imaging and validation of the concept of this approach. Our data demonstrate that the designed biosensor ensures the highly sensitive multiplexed analysis of association-dissociation events and detection of the biomarker of DNA damage using a microfluidic PC array. The obtained results highlight the potential of the developed technique for testing the functionality of candidate drugs, discovering new molecular targets and drug entities. This paves the way to further adaption and bioanalytical use of the biosensor for high-content screening to identify new DNA repair inhibitor drugs targeting the RAD51 nucleoprotein filament or to discover new molecular targets.

Electrostatic modulation of multiple binding events between loquacious-PD and double-stranded RNA.

Electrostatics can alter the RNA-binding properties of proteins that display structure selectivity without sequence specificity. Loquacious-PD relies on this broad scope response to mediate the interaction of endonucleases with double stranded RNAs. Multimodal spectroscopic probes with in situ perturbations reveal an efficient and stable binding mechanism that disfavors high protein density complexes and is sensitive to local electrostatics.

Isolation of PD-L1 Extracellular Vesicle Subpopulations Using DNA Computation Mediated Microfluidic Tandem Separation.

Accurate isolation of targeted extracellular vesicle (EV) is challenging due to the antigenic heterogeneity of EV subpopulations which are from different cell origins. Most EV subpopulations lack a single marker whose expression cleanly distinguishes them from mixed populations of closely related EVs. Here, a modular platform capable of taking multiple binding events as input, performing logic computations, and producing two independent outputs for tandem microchips for EV subpopulation isolation, is developed. Taking advantages of the excellent selectivity of dual-aptamer recognition and the sensitivity of tandem microchips, this method achieves, for the first time, sequential isolation of tumor PD-L1 EVs and non-tumor PD-L1 EVs. As a result, the developed platform can not only effectively distinguish cancer patients from healthy donors but also provides new clues for assessing immune heterogeneity. Moreover, the captured EVs can be released through a DNA hydrolysis reaction with high efficiency, which is compatible with downstream mass spectrometry for EV proteome profiling. Overall, this strategy is expected to isolate different EV subpopulations, translate EVs into reliable clinical biomarkers, and accurately investigate the biological functions of different EV subsets.

Conformations of p90 Ribosomal S6 Kinase (RSK) Activation

Protein kinase have evolved to be dynamic macromolecular switches that alternate between inactive and active conformations. Although most kinase are typically phosphorylated and activated by other kinases, relatively little is known about the detailed mechanistic steps required for one kinase to activate another. The p90 ribosomal S6 kinases (RSKs) are a family of serine/threonine kinases that lie downstream of the Ras‐MAPK pathway and regulate cell proliferation, cell survival, cell growth, and cell motility. RSK is an interesting model system to study kinase activation because it contains two distinct kinase domains, an N‐terminal kinase (NTK), and a C‐terminal kinase (CTK) in the same polypeptide chain. The NTK is a member of the AGC kinase superfamily, and the CTK is a member of the CAMK family. A flexible linker bridges the NTK and CTK, and embedded within the linker is the highly conserved tail of AGC kinases (AGC tail) which contains the conserved turn and hydrophobic motifs (HF). RSK has a complex activation mechanism that includes sequential phosphorylation events and requires two additional kinases: extracellular signal‐regulated kinase (ERK2) and 3‐phosphoinositide‐dependent protein kinase 1 (PDK1). ERK2 phosphorylates the CTK and the turn motif. The phosphorylated CTK is then able to phosphorylate the linker at the HF, this enables PDK1 to bind the linker and then phosphorylate and activate the NTK2. The precise structural details of RSK kinase activation are not fully understood and a more rigorous biochemical characterization could provide valuable insight into how kinase complexes assemble and how the linker facilitates multiple binding and phosphorylation events.To gain a better understanding of the FL RSK2‐ERK2 signaling complex we have used cryoEM and hydrogen deuterium exchange mass spectrometry (HDX) to gain insight into the overall shape and solvent accessibility of the overall complex. We have determined a low‐resolution density map of the RSK2‐ERK2 complex, revealing a compact shape. Additionally, all three kinase domains are relatively well protected from solvent, with the exception of the activation loops of the CTK, and the aC helix of the NTK. While the tails of RSK2 and linker (AGC tail) are highly solvent exposed. We hypothesize that the linker region needs such solvent accessibility in order to enable the various interactions and phosphorylation events necessary for RSK activation. We have also utilized peptide array binding experiments to determine the residues within the linker that are necessary to enable ERK2 phosphorylation of the turn motif, CTK phosphorylation of the HF, and PDK1 binding and subsequent phosphorylation of the NTK activation loop. ERK2 appears to bind to the linker and NTK in a multivalent fashion via the C‐lobe (300‐320) and the N‐lobe. The CTK seems to primarily interact with HF in the linker. And PDK1 binds to both the HF and a conserved FDX1‐2Y/F motif in the linker.

How does a small molecule bind at a cryptic binding site?

Protein-protein interactions (PPIs) are ubiquitous biomolecular processes that are central to virtually all aspects of cellular function. Identifying small molecules that modulate specific disease-related PPIs is a strategy with enormous promise for drug discovery. The design of drugs to disrupt PPIs is challenging, however, because many potential drug-binding sites at PPI interfaces are “cryptic”: When unoccupied by a ligand, cryptic sites are often flat and featureless, and thus not readily recognizable in crystal structures, with the geometric and chemical characteristics of typical small-molecule binding sites only emerging upon ligand binding. The rational design of small molecules to inhibit specific PPIs would benefit from a better understanding of how such molecules bind at PPI interfaces. To this end, we have conducted unbiased, all-atom MD simulations of the binding of four small-molecule inhibitors (SP4206 and three SP4206 analogs) to interleukin 2 (IL2)—which performs its function by forming a PPI with its receptor—without incorporating any prior structural information about the ligands’ binding. In multiple binding events, a small molecule settled into a stable binding pose at the PPI interface of IL2, resulting in a protein–small-molecule binding site and pose virtually identical to that observed in an existing crystal structure of the IL2-SP4206 complex. Binding of the small molecule stabilized the IL2 binding groove, which when the small molecule was not bound emerged only transiently and incompletely. Moreover, free energy perturbation (FEP) calculations successfully distinguished between the native and non-native IL2–small-molecule binding poses found in the simulations, suggesting that binding simulations in combination with FEP may provide an effective tool for identifying cryptic binding sites and determining the binding poses of small molecules designed to disrupt PPI interfaces by binding to such sites.

Single-Molecule Sampling of Dihydrofolate Reductase Shows Kinetic Pauses and an Endosteric Effect Linked to Catalysis.

The ability to sample multiple reactions on the same single enzyme is important to link rare intermediates with catalysis and to unravel the role of conformational changes. Despite decades of efforts, however, the single-molecule characterization of nonfluorogenic enzymes during multiple catalytic turnovers has been elusive. Here, we show that nanopore currents allow sampling the dynamic exchange between five structural intermediates during E. coli dihydrofolate reductase (DHFR) catalysis. We found that an endosteric effect promotes the binding of the substrate to the enzyme with a specific hierarchy. The chemical step then switched the enzyme from the closed to the occluded conformation, which in turn promotes the release of the reduced cofactor NADP+. Unexpectedly, only a few reactive complexes lead to catalysis. Furthermore, second-long catalytic pauses were observed, possibly reflecting an off-path conformation generated during the reaction. Finally, the free energy from multiple cofactor binding events were required to release the product and switch DHFR back to the reactive conformer. This catalytic fueled concerted mechanism is likely to have evolved to improve the catalytic efficiency of DHFR under the high concentrations of NADP+ in E. coli and might be a general feature for complex enzymatic reactions where the binding and release of the products must be tightly controlled.

Mechanics of CRISPR-Cas12a and engineered variants on λ-DNA.

Cas12a is an RNA-guided endonuclease that is emerging as a powerful genome-editing tool. Here, we selected a target site on bacteriophage λ-DNA and used optical tweezers combined with fluorescence to provide mechanistic insight into wild type Cas12a and three engineered variants, where the specific dsDNA and the unspecific ssDNA cleavage are dissociated (M1 and M2) and a third one which nicks the target DNA (M3). At low forces wtCas12a and the variants display two main off-target binding sites, while on stretched dsDNA at higher forces numerous binding events appear driven by the mechanical distortion of the DNA and partial matches to the crRNA. The multiple binding events onto dsDNA at high tension do not lead to cleavage, which is observed on the target site at low forces when the DNA is flexible. In addition, activity assays also show that the preferential off-target sites for this crRNA are not cleaved by wtCas12a, indicating that λ-DNA is only severed at the target site. Our single molecule data indicate that the Cas12a scaffold presents singular mechanical properties, which could be used to generate new endonucleases with biomedical and biotechnological applications.

Allosteric conformational ensembles have unlimited capacity for integrating information.

Integration of binding information by macromolecular entities is fundamental to cellular functionality. Recent work has shown that such integration cannot be explained by pairwise cooperativities, in which binding is modulated by binding at another site. Higher-order cooperativities (HOCs), in which binding is collectively modulated by multiple other binding events, appear to be necessary but an appropriate mechanism has been lacking. We show here that HOCs arise through allostery, in which effective cooperativity emerges indirectly from an ensemble of dynamically interchanging conformations. Conformational ensembles play important roles in many cellular processes but their integrative capabilities remain poorly understood. We show that sufficiently complex ensembles can implement any form of information integration achievable without energy expenditure, including all patterns of HOCs. Our results provide a rigorous biophysical foundation for analysing the integration of binding information through allostery. We discuss the implications for eukaryotic gene regulation, where complex conformational dynamics accompanies widespread information integration.

Role of D-serine Binding to the NMDA Receptor Ligand-Binding Domain

The N-methyl-D-aspartate receptor (NMDAR) is a ligand-gated ion channel that promotes synaptic plasticity critical for learning and memory. NMDAR activation is initiated by binding of two different neurotransmitter agonists to the ligand-binding domains (LBDs). Specifically, the GluN2 subunit binds glutamate, while the GluN1 subunit binds either glycine or D-serine. While the mechanisms of glycine and glutamate binding to NMDAR LBDs have already been determined, little is known about the mechanisms by which D-serine can bind to and activate the receptor. To probe binding mechanisms, we performed multi-microsecond molecular dynamics simulations of the GluN1/GluN2A LBD dimer in the presence of freely diffusing D-serine and glutamate and observed multiple binding and unbinding events. While D-serine is primarily a GluN1 agonist, we surprisingly observed that D-serine binds to both GluN1 and GluN2A NMDAR subunits. Computing interaction frequencies between LBD residues and D-serine revealed residues important for agonist binding. However, we observed that binding pathways are made up of sequences of interactions that guide D-serine into the binding site. To identify properties of these pathways, we developed a framework for analyzing binding pathways by geometric and spatial similarity, which allowed us to cluster them according to the region of the LBD with which D-serine interacts. This allowed us to identify groups of residues that work together to contribute to particular binding pathways. We determined that D-serine and glutamate bind by similar pathways and found that D-serine is able to stabilize the active LBD conformation. Lastly, we determined that N-linked glycans at physiologically relevant glycosylation sites generally do not interfere with agonist-binding pathways to modulate LBD activity. These insights highlight the versatility of D-serine as an NMDAR agonist and its unique role in receptor activation.

Estimating the accuracy of the MARTINI model towards the investigation of peripheral protein-membrane interactions.

Peripheral membrane proteins play a major role in numerous biological processes by transiently associating with cellular membranes, often with extreme membrane specificity. Because of the short-lived nature of these interactions, molecular dynamics (MD) simulations have emerged as an appealing tool to characterize at the structural level the molecular details of the protein-membrane interface. Transferable coarse-grained (CG) MD simulations, in particular, offer the possibility to investigate the spontaneous association of peripheral proteins with lipid bilayers of different compositions at limited computational cost, but they are hampered by the lack of a reliable a priori estimation of their accuracy and thus typically require a posteriori experimental validation. In this article, we investigate the ability of the MARTINI CG force field, specifically the 3 open-beta version, to reproduce known experimental observations regarding the membrane binding behavior of 12 peripheral membrane proteins and peptides. Based on observations of multiple binding and unbinding events in several independent replicas, we found that, despite the presence of false positives and false negatives, this model is mostly able to correctly characterize the membrane binding behavior of peripheral proteins, and to identify key residues found to disrupt membrane binding in mutagenesis experiments. While preliminary, our investigations suggest that transferable chemical-specific CG force fields have enormous potential in the characterization of the membrane binding process by peripheral proteins, and that the identification of negative results could help drive future force field development efforts.

Chromatin Looping Shapes KLF5-Dependent Transcriptional Programs in Human Epithelial Cancers.

Activation of transcription factors is a key driver event in cancer. We and others have recently reported that the Krüppel-like transcription factor KLF5 is activated in multiple epithelial cancer types including squamous cancer and gastrointestinal adenocarcinoma, yet the functional consequences and the underlying mechanisms of this activation remain largely unknown. Here we demonstrate that activation of KLF5 results in strongly selective KLF5 dependency for these cancer types. KLF5 bound lineage-specific regulatory elements and activated gene expression programs essential to cancer cells. HiChIP analysis revealed that multiple distal KLF5 binding events cluster and synergize to activate individual target genes. Immunoprecipitation-mass spectrometry assays showed that KLF5 interacts with other transcription factors such as TP63 and YAP1, as well as the CBP/EP300 acetyltransferase complex. Furthermore, KLF5 guided the CBP/EP300 complex to increase acetylation of H3K27, which in turn enhanced recruitment of the bromodomain protein BRD4 to chromatin. The 3D chromatin architecture aggregated KLF5-dependent BRD4 binding to activate polymerase II elongation at KLF5 target genes, which conferred a transcriptional vulnerability to proteolysis-targeting chimera-induced degradation of BRD4. Our study demonstrates that KLF5 plays an essential role in multiple epithelial cancers by activating cancer-related genes through 3D chromatin loops, providing an evidence-based rationale for targeting the KLF5 pathway. SIGNIFICANCE: An integrative 3D genomics methodology delineates mechanisms underlying the function of KLF5 in multiple epithelial cancers and suggests potential strategies to target cancers with aberrantly activated KLF5.

Simulating Multiple Substrate-Binding Events by γ-Glutamyltransferase Using Accelerated Molecular Dynamics.

γ-Glutamyltransferase (GGT) is an enzyme that uses γ-glutamyl compounds as substrates and catalyzes their transfer to a water molecule or an acceptor substrate with varied physiological function in bacteria, plants, and animals. Crystal structures of GGT are known for different species and in different states of the chemical reaction; however, the structural dynamics of the substrate binding to the catalytic site of GGT are unknown. Here, we modeled Escherichia coli GGT's glutamine binding by using a swarm of accelerated molecular dynamics (aMD) simulations. Characterization of multiple binding events identified three structural binding motifs composed of polar residues in the binding pocket that govern glutamine binding into the active site. Simulated open and closed conformations of a lid-loop protecting the binding cavity suggest its role as a gating element by allowing or blocking substrates entry into the binding pocket. Partially open states of the lid-loop are accessible within thermal fluctuations, while the estimated free energy cost of a complete open state is 2.4 kcal/mol. Our results suggest that both specific electrostatic interactions and GGT conformational dynamics dictate the molecular recognition of substrate-GGT complexes.

A boosted unbiased molecular dynamics method for predicting ligands binding mechanisms: probing the binding pathway of dasatinib to Src-kinase.

Small molecules such as metabolites and drugs play essential roles in biological processes and pharmaceutical industry. Knowing their interactions with biomacromolecular targets demands a deep understanding of binding mechanisms. Dozens of papers have suggested that discovering of the binding event by means of conventional unbiased molecular dynamics (MD) simulation urges considerable amount of computational resources, therefore, only one who holds a cluster or a supercomputer can afford such extensive simulations. Thus, many researchers who do not own such resources are reluctant to take the benefits of running unbiased MD simulation, in full atomistic details, when studying a ligand binding pathway. Many researchers are impelled to be content with biased MD simulations which seek its validation due to its intrinsic preconceived framework. In this work, we have presented a workable stratagem to encourage everyone to perform unbiased (unguided) MD simulations, in this case a protein-ligand binding process, by typical desktop computers and so achieve valuable results in nanosecond time scale. Here, we have described a dynamical binding's process of an anticancer drug, the dasatinib, to the c-Src kinase in full atomistic details for the first time, without applying any biasing force or potential which may lead the drug to artificial interactions with the protein. We have attained multiple independent binding events which occurred in the nanosecond time scales, surprisingly as little as ∼30 ns. Both the protonated and deprotonated forms of the dasatinib reached the crystallographic binding mode without having any major intermediate state during induction. The links of the tutorial and technical documents are accessible in the article. Supplementary data are available at Bioinformatics online.

A Closer Look at Anandamide Interaction With TRPV1.

The transient receptor potential subfamily vanilloid type 1 ion channel (TRPV1), located in the peripheral nervous system has been implicated in the perception of pain and possesses the ability to be modulated by various cannabinoid ligands. Because of its location, TRPV1 is an ideal target for the development of novel pain therapeutics. Literature precedent suggests a wide range of cannabinoid ligands can activate TRPV1, but the location and mode of entry is not well understood. Understanding the modes in which cannabinoids can enter and bind to TRPV1 can aid in rational drug design. The first endogenous ligand identified for TRPV1 was the endocannabinoid, anandamide (AEA). The Molecular Dynamics (MD) studies discussed here investigate the entry mode of AEA into TRPV1. During the course of the 10+ microsecond MD simulations, two distinct binding modes were observed: AEA binding in the tunnel formed by the S1–S4 region, and AEA binding in the vanilloid binding pocket, with preference for the former. Unbiased MD simulations have revealed multiple spontaneous binding events into the S1–S4 region, with only one event of AEA binding the vanilloid binding pocket. These results suggest that AEA enters TRPV1 via a novel location between helices S1–S4 via the lipid bilayer.

Top-down machine learning approach for high-throughput single-molecule analysis.

Single-molecule approaches provide enormous insight into the dynamics of biomolecules, but adequately sampling distributions of states and events often requires extensive sampling. Although emerging experimental techniques can generate such large datasets, existing analysis tools are not suitable to process the large volume of data obtained in high-throughput paradigms. Here, we present a new analysis platform (DISC) that accelerates unsupervised analysis of single-molecule trajectories. By merging model-free statistical learning with the Viterbi algorithm, DISC idealizes single-molecule trajectories up to three orders of magnitude faster with improved accuracy compared to other commonly used algorithms. Further, we demonstrate the utility of DISC algorithm to probe cooperativity between multiple binding events in the cyclic nucleotide binding domains of HCN pacemaker channel. Given the flexible and efficient nature of DISC, we anticipate it will be a powerful tool for unsupervised processing of high-throughput data across a range of single-molecule experiments.

Poly-Enrich: count-based methods for gene set enrichment testing with genomic regions.

Gene set enrichment (GSE) testing enhances the biological interpretation of ChIP-seq data and other large sets of genomic regions. Our group has previously introduced two GSE methods for genomic regions: ChIP-Enrich for narrow regions and Broad-Enrich for broad regions. Here, we introduce Poly-Enrich, which has wider applicability, additional capabilities and models the number of peaks assigned to a gene using a generalized additive model with a negative binomial family to determine gene set enrichment, while adjusting for gene locus length. As opposed to ChIP-Enrich, Poly-Enrich works well even when nearly all genes have a peak, illustrated by using Poly-Enrich to characterize pathways and types of genic regions enriched with different families of repetitive elements. By comparing Poly-Enrich and ChIP-Enrich results with ENCODE ChIP-seq data, we found that the optimal test depends more on the pathway being regulated than on properties of the transcription factors. Using known transcription factor functions, we discovered clusters of related biological processes consistently better modeled with Poly-Enrich. This suggests that the regulation of certain processes may be modified by multiple binding events, better modeled by a count-based method. Our new hybrid method automatically uses the optimal method for each gene set, with correct FDR-adjustment.

Accurate Determination of Cavitand Binding Free Energies via Unrestrained Advanced Sampling.

Calculation of binding free energies, which characterize the stability and specificity of molecular interactions (e.g., drug formulations), has been established as an important application of modern computational chemistry. Though several methodologies currently exist within the literature, there is always a need for improvements in speed and accuracy that allow for efficient and accurate chemical screening. In this paper we explore the application of an unrestrained advanced sampling method, adaptive biasing force (ABF), to the calculation of standard binding free energies for a set of molecular host-guest systems for which the binding free energy is well-known: the cucurbit[7]uril-hosted systems utilized in the HYDROPHOBE challenge [ Assaf et al. J. Phys. Chem. B 2017 , 121 , 11144 - 11162 ]. We demonstrate that the use of the ABF advanced sampling method yields values systematically closer to experiment, with a lower uncertainty in the calculation, than thermodynamic integration and restrained sampling techniques commonly used in the literature. We hypothesize that this is due to the algorithm's ability to drive multiple binding and dissociation events through applied bias forces. These results show the promise of unrestrained advanced sampling methods along well-defined reaction coordinates to the calculation of binding energies in host-guest systems.