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Of the targets for HIV-1 therapeutics, the capsid core is a relatively unexploited but alluring drug target due to its indispensable roles throughout virus replication. Because of this, we aimed to identify "clickable" covalent modifiers of the HIV-1 capsid protein (CA) for future functionalization. We screened a library of fluorosulfate compounds that can undergo sulfur(VI) fluoride exchange (SuFEx) reactions, and five compounds were identified as hits. These molecules were further characterized for antiviral effects. Several compounds impacted in vitro capsid assembly. One compound, BBS-103, covalently bound CA via a SuFEx reaction to Tyr145 and had antiviral activity in cell-based assays by perturbing virus production, but not uncoating. The covalent binding of compounds that target the HIV-1 capsid could aid in the future design of antiretroviral drugs or chemical probes that will help study aspects of HIV-1 replication., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Mycobacterium tuberculosis (Mtb) is the most common infection among people with HIV (PWH). Mtb disease-associated inflammation could affect HIV-directed immune responses in PWH. We show that HIV antibodies are broader and more potent in PWH in the presence as compared to the absence of Mtb disease. With co-existing Mtb disease, the virus in PWH also encounters unique antibody selection pressure. The Mtb-linked HIV antibody enhancement associates with specific mediators important for B cell and antibody development. This Mtb humoral augmentation does not occur due to cross-reactivity, a generalized increase in all antibodies, or differences in duration or amount of antigen exposure. We speculate that the co-localization of Mtb and HIV in lymphatic tissues leads to the emergence of potent HIV antibodies. PWH's Mtb disease status has implications for the future use of HIV broadly neutralizing antibodies as prophylaxis or treatment and the induction of better humoral immunity., Competing Interests: The authors declare no competing interests., (© 2023 The Author(s).)

Models of insulin secretory vesicles from pancreatic beta cells have been created using the cellPACK suite of tools to research, curate, construct and visualise the current state of knowledge. The model integrates experimental information from proteomics, structural biology, cryoelectron microscopy and X-ray tomography, and is used to generate models of mature and immature vesicles. A new method was developed to generate a confidence score that reconciles inconsistencies between three available proteomes using expert annotations of cellular localisation. The models are used to simulate soft X-ray tomograms, allowing quantification of features that are observed in experimental tomograms, and in turn, allowing interpretation of X-ray tomograms at the molecular level., Competing Interests: The authors declare no conflicts of interest., (© The Author(s) 2022.)

Background: Genome-wide association studies (GWAS) aim to correlate phenotypic changes with genotypic variation. Upon transcription, single nucleotide variants (SNVs) may alter mRNA structure, with potential impacts on transcript stability, macromolecular interactions, and translation. However, plant genomes have not been assessed for the presence of these structure-altering polymorphisms or "riboSNitches.", Results: We experimentally demonstrate the presence of riboSNitches in transcripts of two Arabidopsis genes, ZINC RIBBON 3 (ZR3) and COTTON GOLGI-RELATED 3 (CGR3), which are associated with continentality and temperature variation in the natural environment. These riboSNitches are also associated with differences in the abundance of their respective transcripts, implying a role in regulating the gene's expression in adaptation to local climate conditions. We then computationally predict riboSNitches transcriptome-wide in mRNAs of 879 naturally inbred Arabidopsis accessions. We characterize correlations between SNPs/riboSNitches in these accessions and 434 climate descriptors of their local environments, suggesting a role of these variants in local adaptation. We integrate this information in CLIMtools V2.0 and provide a new web resource, T-CLIM, that reveals associations between transcript abundance variation and local environmental variation., Conclusion: We functionally validate two plant riboSNitches and, for the first time, demonstrate riboSNitch conditionality dependent on temperature, coining the term "conditional riboSNitch." We provide the first pan-genome-wide prediction of riboSNitches in plants. We expand our previous CLIMtools web resource with riboSNitch information and with 1868 additional Arabidopsis genomes and 269 additional climate conditions, which will greatly facilitate in silico studies of natural genetic variation, its phenotypic consequences, and its role in local adaptation., (© 2022. The Author(s).)

We have identified novel HIV-1 capsid inhibitors targeting the PF74 binding site. Acting as the building block of the HIV-1 capsid core, the HIV-1 capsid protein plays an important role in the viral life cycle and is an attractive target for antiviral development. A structure-based virtual screening workflow for hit identification was employed, which includes docking 1.6 million commercially-available drug-like compounds from the ZINC database to the capsid dimer, followed by applying two absolute binding free energy (ABFE) filters on the 500 top-ranked molecules from docking. The first employs the Binding Energy Distribution Analysis Method (BEDAM) in implicit solvent. The top-ranked compounds are then refined using the Double Decoupling method in explicit solvent. Both docking and BEDAM refinement were carried out on the IBM World Community Grid as part of the FightAIDS@Home project. Using this virtual screening workflow, we identified 24 molecules with calculated binding free energies between - 6 and - 12 kcal/mol. We performed thermal shift assays on these molecules to examine their potential effects on the stability of HIV-1 capsid hexamer and found that two compounds, ZINC520357473 and ZINC4119064 increased the melting point of the latter by 14.8 °C and 33 °C, respectively. These results support the conclusion that the two ZINC compounds are primary hits targeting the capsid dimer interface. Our simulations also suggest that the two hit molecules may bind at the capsid dimer interface by occupying a new sub-pocket that has not been exploited by existing CA inhibitors. The possible causes for why other top-scored compounds suggested by ABFE filters failed to show measurable activity are discussed., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Building structural models of entire cells has been a long-standing cross-discipline challenge for the research community, as it requires an unprecedented level of integration between multiple sources of biological data and enhanced methods for computational modeling and visualization. Here, we present the first 3D structural models of an entire Mycoplasma genitalium (MG) cell, built using the CellPACK suite of computational modeling tools. Our model recapitulates the data described in recent whole-cell system biology simulations and provides a structural representation for all MG proteins, DNA and RNA molecules, obtained by combining experimental and homology-modeled structures and lattice-based models of the genome. We establish a framework for gathering, curating and evaluating these structures, exposing current weaknesses of modeling methods and the boundaries of MG structural knowledge, and visualization methods to explore functional characteristics of the genome and proteome. We compare two approaches for data gathering, a manually-curated workflow and an automated workflow that uses homologous structures, both of which are appropriate for the analysis of mesoscale properties such as crowding and volume occupancy. Analysis of model quality provides estimates of the regularization that will be required when these models are used as starting points for atomic molecular dynamics simulations., Competing Interests: Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Summary: Genome sequencing projects annotate protein-coding gene models with multiple transcripts, aiming to represent all of the available transcript evidence. However, downstream analyses often operate on only one representative transcript per gene locus, sometimes known as the canonical transcript. To choose canonical transcripts, Transcript Ranking and Canonical Election (TRaCE) holds an 'election' in which a set of RNA-seq samples rank transcripts by annotation edit distance. These sample-specific votes are tallied along with other criteria such as protein length and InterPro domain coverage. The winner is selected as the canonical transcript, but the election proceeds through multiple rounds of voting to order all the transcripts by relevance. Based on the set of expression data provided, TRaCE can identify the most common isoforms from a broad expression atlas or prioritize alternative transcripts expressed in specific contexts., Availability and Implementation: Transcript ranking code can be found on GitHub at {{https://github.com/warelab/TRaCE}}., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2021. Published by Oxford University Press.)

CellPAINT is an interactive digital tool that allows non-expert users to create illustrations of the molecular structure of cells and viruses. We present a new release with several key enhancements, including the ability to generate custom ingredients from structure information in the Protein Data Bank, and interaction, grouping, and locking functions that streamline the creation of assemblies and illustration of large, complex scenes. An example of CellPAINT as a tool for hypothesis generation in the interpretation of cryoelectron tomograms is presented. CellPAINT is freely available at http://ccsb.scripps.edu/cellpaint., Competing Interests: Conflict of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The structural study of icosahedral viruses has a long and impactful history in both crystallographic methodology and molecular biology. The evolution of the Protein Data Bank has paralleled and supported these studies providing readily accessible formats dealing with novel features associated with viral particle symmetries and subunit interactions. This overview describes the growth in size and complexity of icosahedral viruses from the first early studies of small RNA plant viruses and human picornaviruses up to the larger and more complex bacterial phage, insect, and human disease viruses such as Zika, hepatitis B, Adeno and Polyoma virus. The analysis of icosahedral viral capsid protein domain folds has shown striking similarities, with the beta jelly roll motif observed across multiple evolutionarily divergent species. The icosahedral symmetry of viruses drove the development of noncrystallographic symmetry averaging as a powerful phasing method, and the constraints of maintaining this symmetry resulted in the concept of quasi-equivalence in viral structures. Symmetry also played an important early role in demonstrating the power of cryo-electron microscopy as an alternative to crystallography in generating atomic resolution structures of these viruses. The Protein Data Bank has been a critical resource for assembling and disseminating these structures to a wide community, and the virus particle explorer (VIPER) was developed to enable users to easily generate and view complete viral capsid structures from their asymmetric building blocks. Finally, we share a personal perspective on the early use of computer graphics to communicate the intricacies, interactions, and beauty of these virus structures., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

The AutoDock suite provides a comprehensive toolset for computational ligand docking and drug design and development. The suite builds on 30 years of methods development, including empirical free energy force fields, docking engines, methods for site prediction, and interactive tools for visualization and analysis. Specialized tools are available for challenging systems, including covalent inhibitors, peptides, compounds with macrocycles, systems where ordered hydration plays a key role, and systems with substantial receptor flexibility. All methods in the AutoDock suite are freely available for use and reuse, which has engendered the continued growth of a diverse community of primary users and third-party developers., (© 2020 The Protein Society.)

Experimental information from microscopy, structural biology, and bioinformatics may be integrated to build structural models of entire cells with molecular detail. This integrative modeling is challenging in several ways: the intrinsic complexity of biology results in models with many closely packed and heterogeneous components; the wealth of available experimental data is scattered among multiple resources and must be gathered, reconciled, and curated; and computational infrastructure is only now gaining the capability of modeling and visualizing systems of this complexity. We present recent efforts to address these challenges, both with artistic approaches to depicting the cellular mesoscale, and development and application of methods to build quantitative models., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Interest is growing for 3D models of the biological mesoscale, the intermediate scale between the nanometer scale of molecular structure and micrometer scale of cellular biology. However, it is currently difficult to gather, curate and integrate all the data required to define such models. To address this challenge we developed Mesoscope (mesoscope.scripps.edu/beta), a web-based data integration and curation tool. Mesoscope allows users to begin with a listing of molecules (such as data from proteomics), and to use resources at UniProt and the PDB to identify, prepare and validate appropriate structures and representations for each molecule, ultimately producing a portable output file used by CellPACK and other modeling tools for generation of 3D models of the biological mesoscale. The availability of this tool has proven essential in several exploratory applications, given the high complexity of mesoscale models and the heterogeneity of the available data sources.

When implementing the latest innovations to reduce health care-associated infections, it is important not to overlook basic infection prevention principles such as hand hygiene, isolation precautions, use of personal protective equipment, and cleaning and low-level disinfection. Like many facilities, we implemented a multifaceted approach to reduce hospital-onset Clostridioides difficile infections. In this paper, we share simple tools that we found helpful in improving infection prevention practices by addressing knowledge gaps among staff, visitors, and patients., (Copyright © 2019 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.)

Tuberculosis, caused by Mycobacterium tuberculosis ( M. tuberculosis ), kills 1.6 million people annually. To bridge the gap between structure- and cell-based drug discovery strategies, we are pioneering a computer-aided discovery paradigm that merges structure-based virtual screening with ligand-based, machine learning methods trained with cell-based data. This approach successfully identified N -(3-methoxyphenyl)-7-nitrobenzo[ c ][1,2,5]oxadiazol-4-amine (JSF-2164) as an inhibitor of purified InhA with whole-cell efficacy versus in vitro cultured M. tuberculosis . When the intrabacterial drug metabolism (IBDM) platform was leveraged, mechanistic studies demonstrated that JSF-2164 underwent a rapid F 420 H 2 -dependent biotransformation within M. tuberculosis to afford intrabacterial nitric oxide and two amines, identified as JSF-3616 and JSF-3617. Thus, metabolism of JSF-2164 obscured the InhA inhibition phenotype within cultured M. tuberculosis . This study demonstrates a new docking/Bayesian computational strategy to combine cell- and target-based drug screening and the need to probe intrabacterial metabolism when clarifying the antitubercular mechanism of action.

The small program Illustrate generates non-photorealistic images of biological molecules for use in dissemination, outreach, and education. The method has been used as part of the "Molecule of the Month," an ongoing educational column at the RCSB Protein Data Bank (http://rcsb.org). Insights from 20 years of application of the program are presented, and the program has been released both as open-source Fortran at GitHub and through an interactive web-based interface., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Visualizations of hierarchical data can often be explored interactively. For example, in geographic visualization, there are continents, which can be subdivided into countries, states, counties and cities. Similarly, in models of viruses or bacteria at the highest level are the compartments, and below that are macromolecules, secondary structures (such as α-helices), amino-acids, and on the finest level atoms. Distinguishing between items can be assisted through the use of color at all levels. However, currently, there are no hierarchical and adaptive color mapping techniques for very large multi-scale visualizations that can be explored interactively. We present a novel, multi-scale, color-mapping technique for adaptively adjusting the color scheme to the current view and scale. Color is treated as a resource and is smoothly redistributed. The distribution adjusts to the scale of the currently observed detail and maximizes the color range utilization given current viewing requirements. Thus, we ensure that the user is able to distinguish items on any level, even if the color is not constant for a particular feature. The coloring technique is demonstrated for a political map and a mesoscale structural model of HIV. The technique has been tested by users with expertise in structural biology and was overall well received., (© 2019 The Authors. Computer Graphics Forum published by Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd.)

A coarse-grain computational method integrates biophysical and structural data to generate models of HIV-1 genomic RNA, nucleocapsid and integrase condensed into a mature ribonucleoprotein complex. Several hypotheses for the initial structure of the genomic RNA and oligomeric state of integrase are tested. In these models, integrase interaction captures features of the relative distribution of gRNA in the immature virion and increases the size of the RNP globule, and exclusion of nucleocapsid from regions with RNA secondary structure drives an asymmetric placement of the dimerized 5'UTR at the surface of the RNP globule., Competing Interests: The authors have declared that no competing interests exist.

To perform massive-scale replica exchange molecular dynamics (REMD) simulations for calculating binding free energies of protein-ligand complexes, we implemented the asynchronous replica exchange (AsyncRE) framework of the binding energy distribution analysis method (BEDAM) in implicit solvent on the IBM World Community Grid (WCG) and optimized the simulation parameters to reduce the overhead and improve the prediction power of the WCG AsyncRE simulations. We also performed the first massive-scale binding free energy calculations using the WCG distributed computing grid and 301 ligands from the SAMPL4 challenge for large-scale binding free energy predictions of HIV-1 integrase complexes. In total there are ∼10000 simulated complexes, ∼1 million replicas, and ∼2000 μs of aggregated MD simulations. Running AsyncRE MD simulations on the WCG requires accepting a trade-off between the number of replicas that can be run (breadth) and the number of full RE cycles that can be completed per replica (depth). As compared with synchronous Replica Exchange (SyncRE) running on tightly coupled clusters like XSEDE, on the WCG many more replicas can be launched simultaneously on heterogeneous distributed hardware, but each full RE cycle requires more overhead. We compared the WCG results with that from AutoDock and more advanced RE simulations including the use of flattening potentials to accelerate sampling of selected degrees of freedom of ligands and/or receptors related to slow dynamics due to high energy barriers. We propose a suitable strategy of RE simulations to refine high throughput docking results which can be matched to corresponding computing resources: from HPC clusters, to small or medium-size distributed campus grids, and finally to massive-scale computing networks including millions of CPUs like the resources available on the WCG.

HIV-1 capsid protein (CA) plays critical roles in both early and late stages of the viral replication cycle. Mutagenesis and structural experiments have revealed that capsid core stability significantly affects uncoating and initiation of reverse transcription in host cells. This has led to efforts in developing antivirals targeting CA and its assembly, although none of the currently identified compounds are used in the clinic for treatment of HIV infection. A specific interaction that is primarily present in pentameric interfaces in the HIV-1 capsid core was identified and is reported to be important for CA assembly. This is shown by multidisciplinary characterization of CA site-directed mutants using biochemical analysis of virus-like particle formation, transmission electron microscopy of in vitro assembly, crystallographic studies, and molecular dynamic simulations. The data are consistent with a model where a hydrogen bond between CA residues E28 and K30' from neighboring N-terminal domains (CA NTD s) is important for CA pentamer interactions during core assembly. This pentamer-preferred interaction forms part of an N -terminal d omain i nterface (NDI) pocket that is amenable to antiviral targeting. IMPORTANCE Precise assembly and disassembly of the HIV-1 capsid core are key to the success of viral replication. The forces that govern capsid core formation and dissociation involve intricate interactions between pentamers and hexamers formed by HIV-1 CA. We identified one particular interaction between E28 of one CA and K30' of the adjacent CA that appears more frequently in pentamers than in hexamers and that is important for capsid assembly. Targeting the corresponding site could lead to the development of antivirals which disrupt this interaction and affect capsid assembly., (Copyright © 2019 Craveur et al.)

Understanding the effects of spin-orbit coupling (SOC) and many-body interactions on spin transport is important in condensed matter physics and spintronics. This topic has been intensively studied for spin carriers such as electrons but barely explored for charge-neutral bosonic quasiparticles (including their condensates), which hold promises for coherent spin transport over macroscopic distances. Here, we explore the effects of synthetic SOC (induced by optical Raman coupling) and atomic interactions on the spin transport in an atomic Bose-Einstein condensate (BEC), where the spin-dipole mode (SDM, actuated by quenching the Raman coupling) of two interacting spin components constitutes an alternating spin current. We experimentally observe that SOC significantly enhances the SDM damping while reducing the thermalization (the reduction of the condensate fraction). We also observe generation of BEC collective excitations such as shape oscillations. Our theory reveals that the SOC-modified interference, immiscibility, and interaction between the spin components can play crucial roles in spin transport.

Objectives: To characterize the diversity and prevalence of thoraco-abdominal abnormalities in Bardet-Biedl syndrome (BBS), a model ciliopathy for understanding the role of cilia in human health., Study Design: The Clinical Registry Investigating BBS, a worldwide registry exploring the phenotype and natural history of BBS, was used to conduct the study. Protected health information was obtained by subject or family interview and Health Insurance Portability and Accountability Act-approved release of data including imaging studies and genetic testing. Echocardiography and imaging findings were independently confirmed by 2 cardiologists., Results: Thoraco-abdominal abnormalities were identified in 6 of 368 (1.6%) subjects with a minimum prevalence of 1 in 60 Clinical Registry Investigating BBS participants. Diverse laterality defects were observed suggesting that the underlying ciliopathy randomly alters embryonic left-right axis orientation. Congenital heart disease, common in heterotaxy, was present in 2 subjects. Additional defects, uncommonly reported in BBS, were observed in the central nervous, genitourinary, gastrointestinal, and musculoskeletal systems in the subjects. No BBS genotype was favored in the cohort. One subject had genetic and clinical phenotype diagnostic of both primary ciliary dyskinesia and BBS., Conclusions: The variety of thoraco-abdominal abnormalities in BBS suggests the pleiotropic nature of these anomalies is not confined to a single pattern or genotype. Clinicians providing care to individuals with BBS should consider the increased prevalence of thoraco-abdominal anomalies in BBS. Individuals with features suggestive of other ciliopathies, such as primary ciliary dyskinesia, should undergo further evaluation for additional genetic disorders., Trial Registration: ClinicalTrials.gov: NCT02329210., (Copyright © 2018 Elsevier Inc. All rights reserved.)

CellPAINT allows nonexpert users to create interactive mesoscale illustrations that integrate a variety of biological data. Like popular digital painting software, scenes are created using a palette of molecular "brushes." The current release allows creation of animated scenes with an HIV virion, blood plasma, and a simplified T-cell.

Visualization has been a key technology in the progress of structural molecular biology for as long as the field has existed. This perspective describes the nature of the visualization process in structural studies, how it has evolved over the years, and its relationship to the changes in technology that have supported and driven it. It focuses on how technical advances have changed the way we look at and interact with molecular structure, and how structural biology has fostered and challenged that technology., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Mesoscale molecular modeling is providing a new window into the inner workings of living cells. Modeling of genomes, however, remains a technical challenge, due to their large size and complexity. We describe a lattice method for rapid generation of bacterial nucleoid models that integrates experimental data from a variety of biophysical techniques and provides a starting point for simulation and hypothesis generation. The current method builds models of a circular bacterial genome with supercoiled plectonemes, packed within the small space of the bacterial cell. Lattice models are generated for Mycoplasma genitalium and Escherichia coli nucleoids, and used to simulate interaction data. The method is rapid enough to allow generation of multiple models when analyzing structure/function relationships, and we demonstrate use of the lattice models in creation of an all-atom representation of an entire cell.

The widespread use of lead (Pb) shot in shooting activities, including at former shooting ranges, continues to pose environmental risks. The La Crosse River Marsh (located in Wisconsin, USA) is a biologically diverse urban riparian wetland with a legacy of Pb-contaminated sediment resulting from its use as a trap shooting range from 1929-1963. Within the shot fall zone, shot densities exceed 43,000 pellets/m 2 and surface sediments exceed 25,000 mg/kg in some areas. This study used the Zebrafish as a model to determine the acute toxicity of these contaminated sediments. Zebrafish were exposed to sediments containing approximately 13 to 13,450 mg/kg Pb for 5 days (8-120 hr post-fertilization). The toxic responses to sediments were non-monotonic. Only exposure to sediments containing "mid-range" concentrations of Pb (4580 mg/kg) induced mild skeletal malformations and a sluggish C-start response indicating that Pb was marginally bioavailable. Expression of δ-aminolevulinic acid dehydratase (ALA-D) also indicated the potential for uptake of Pb from sediments. Our findings suggest that Pb within the La Crosse River Marsh sediments is not readily bioavailable to Zebrafish, and while this metal poses a minimal acute toxicological risk, toxicity due to chronic exposure of low concentrations of Pb is possible. Further, our data demonstrated that induction of ALA-D gene expression in Zebrafish embryos shows promise as an alternative to ALA-D enzyme activity as a biomarker for acute Pb exposure under lab conditions.

HIV-1 is rare among viruses for having a low number of envelope glycoprotein (Env) spikes per virion, i.e., ∼7 to 14. This exceptional feature has been associated with avoidance of humoral immunity, i.e., B cell activation and antibody neutralization. Virus-like particles (VLPs) with increased density of Env are being pursued for vaccine development; however, these typically require protein engineering that alters Env structure. Here, we used instead a strategy that targets the producer cell. We employed fluorescence-activated cell sorting (FACS) to sort for cells that are recognized by trimer cross-reactive broadly neutralizing antibody (bnAb) and not by nonneutralizing antibodies. Following multiple iterations of FACS, cells and progeny virions were shown to display higher levels of antigenically correct Env in a manner that correlated between cells and cognate virions ( P = 0.027). High-Env VLPs, or hVLPs, were shown to be monodisperse and to display more than a 10-fold increase in spikes per particle by electron microscopy (average, 127 spikes; range, 90 to 214 spikes). Sequencing revealed a partial truncation in the C-terminal tail of Env that had emerged in the sort; however, iterative rounds of "cell factory" selection were required for the high-Env phenotype. hVLPs showed greater infectivity than standard pseudovirions but largely similar neutralization sensitivity. Importantly, hVLPs also showed superior activation of Env-specific B cells. Hence, high-Env HIV-1 virions, obtained through selection of producer cells, represent an adaptable platform for vaccine design and should aid in the study of native Env. IMPORTANCE The paucity of spikes on HIV is a unique feature that has been associated with evasion of the immune system, while increasing spike density has been a goal of vaccine design. Increasing the density of Env by modifying it in various ways has met with limited success. Here, we focused instead on the producer cell. Cells that stably express HIV spikes were screened on the basis of high binding by bnAbs and low binding by nonneutralizing antibodies. Levels of spikes on cells correlated well with those on progeny virions. Importantly, high-Env virus-like particles (hVLPs) were produced with a manifest array of well-defined spikes, and these were shown to be superior in activating desirable B cells. Our study describes HIV particles that are densely coated with functional spikes, which should facilitate the study of HIV spikes and their development as immunogens., (Copyright © 2017 American Society for Microbiology.)

HIV-1 integrase (IN) is essential for virus replication and represents an important multifunctional therapeutic target. Recently discovered quinoline-based allosteric IN inhibitors (ALLINIs) potently impair HIV-1 replication and are currently in clinical trials. ALLINIs exhibit a multimodal mechanism of action by inducing aberrant IN multimerization during virion morphogenesis and by competing with IN for binding to its cognate cellular cofactor LEDGF/p75 during early steps of HIV-1 infection. However, quinoline-based ALLINIs impose a low genetic barrier for the evolution of resistant phenotypes, which highlights a need for discovery of second-generation inhibitors. Using crystallographic screening of a library of 971 fragments against the HIV-1 IN catalytic core domain (CCD) followed by a fragment expansion approach, we have identified thiophenecarboxylic acid derivatives that bind at the CCD-CCD dimer interface at the principal lens epithelium-derived growth factor (LEDGF)/p75 binding pocket. The most active derivative (5) inhibited LEDGF/p75-dependent HIV-1 IN activity in vitro with an IC 50 of 72 μm and impaired HIV-1 infection of T cells at an EC 50 of 36 μm The identified lead compound, with a relatively small molecular weight (221 Da), provides an optimal building block for developing a new class of inhibitors. Furthermore, although structurally distinct thiophenecarboxylic acid derivatives target a similar pocket at the IN dimer interface as the quinoline-based ALLINIs, the lead compound, 5, inhibited IN mutants that confer resistance to quinoline-based compounds. Collectively, our findings provide a plausible path for structure-based development of second-generation ALLINIs., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

We describe ADChemCast, a method for using results from virtual screening to create a richer representation of a target binding site, which may be used to improve ranking of compounds and characterize the determinants of ligand-receptor specificity. ADChemCast clusters docked conformations of ligands based on shared pairwise receptor-ligand interactions within chemically similar structural fragments, building a set of attributes characteristic of binders and nonbinders. Machine learning is then used to build rules from the most informational attributes for use in reranking of compounds. In this report, we use ADChemCast to improve the ranking of compounds in 11 diverse proteins from the Database of Useful Decoys-Enhanced (DUD-E) and demonstrate the utility of the method for characterizing relevant binding attributes in HIV reverse transcriptase.

Small molecules are powerful tools for investigating protein function and can serve as leads for new therapeutics. Most human proteins, however, lack small-molecule ligands, and entire protein classes are considered 'undruggable'. Fragment-based ligand discovery can identify small-molecule probes for proteins that have proven difficult to target using high-throughput screening of complex compound libraries. Although reversibly binding ligands are commonly pursued, covalent fragments provide an alternative route to small-molecule probes, including those that can access regions of proteins that are difficult to target through binding affinity alone. Here we report a quantitative analysis of cysteine-reactive small-molecule fragments screened against thousands of proteins in human proteomes and cells. Covalent ligands were identified for >700 cysteines found in both druggable proteins and proteins deficient in chemical probes, including transcription factors, adaptor/scaffolding proteins, and uncharacterized proteins. Among the atypical ligand-protein interactions discovered were compounds that react preferentially with pro- (inactive) caspases. We used these ligands to distinguish extrinsic apoptosis pathways in human cell lines versus primary human T cells, showing that the former is largely mediated by caspase-8 while the latter depends on both caspase-8 and -10. Fragment-based covalent ligand discovery provides a greatly expanded portrait of the ligandable proteome and furnishes compounds that can illuminate protein functions in native biological systems.

Computational docking can be used to predict bound conformations and free energies of binding for small-molecule ligands to macromolecular targets. Docking is widely used for the study of biomolecular interactions and mechanisms, and it is applied to structure-based drug design. The methods are fast enough to allow virtual screening of ligand libraries containing tens of thousands of compounds. This protocol covers the docking and virtual screening methods provided by the AutoDock suite of programs, including a basic docking of a drug molecule with an anticancer target, a virtual screen of this target with a small ligand library, docking with selective receptor flexibility, active site prediction and docking with explicit hydration. The entire protocol will require ∼5 h.

We describe two methods of automated covalent docking using Autodock4: the two-point attractor method and the flexible side chain method. Both methods were applied to a training set of 20 diverse protein-ligand covalent complexes, evaluating their reliability in predicting the crystallographic pose of the ligands. The flexible side chain method performed best, recovering the pose in 75% of cases, with failures for the largest inhibitors tested. Both methods are freely available at the AutoDock website (http://autodock.scripps.edu)., (© 2015 The Protein Society.)

Automated docking of drug-like molecules into receptors is an essential tool in structure-based drug design. While modeling receptor flexibility is important for correctly predicting ligand binding, it still remains challenging. This work focuses on an approach in which receptor flexibility is modeled by explicitly specifying a set of receptor side-chains a-priori. The challenges of this approach include the: 1) exponential growth of the search space, demanding more efficient search methods; and 2) increased number of false positives, calling for scoring functions tailored for flexible receptor docking. We present AutoDockFR-AutoDock for Flexible Receptors (ADFR), a new docking engine based on the AutoDock4 scoring function, which addresses the aforementioned challenges with a new Genetic Algorithm (GA) and customized scoring function. We validate ADFR using the Astex Diverse Set, demonstrating an increase in efficiency and reliability of its GA over the one implemented in AutoDock4. We demonstrate greatly increased success rates when cross-docking ligands into apo receptors that require side-chain conformational changes for ligand binding. These cross-docking experiments are based on two datasets: 1) SEQ17 -a receptor diversity set containing 17 pairs of apo-holo structures; and 2) CDK2 -a ligand diversity set composed of one CDK2 apo structure and 52 known bound inhibitors. We show that, when cross-docking ligands into the apo conformation of the receptors with up to 14 flexible side-chains, ADFR reports more correctly cross-docked ligands than AutoDock Vina on both datasets with solutions found for 70.6% vs. 35.3% systems on SEQ17, and 76.9% vs. 61.5% on CDK2. ADFR also outperforms AutoDock Vina in number of top ranking solutions on both datasets. Furthermore, we show that correctly docked CDK2 complexes re-create on average 79.8% of all pairwise atomic interactions between the ligand and moving receptor atoms in the holo complexes. Finally, we show that down-weighting the receptor internal energy improves the ranking of correctly docked poses and that runtime for AutoDockFR scales linearly when side-chain flexibility is added.

Isoniazid (INH) is usually administered to treat latent Mycobacterium tuberculosis (Mtb) infections and is used in combination therapy to treat active tuberculosis (TB). Unfortunately, resistance to this drug is hampering its clinical effectiveness. INH is a prodrug that must be activated by Mtb catalase-peroxidase (KatG) before it can inhibit InhA (Mtb enoyl-acyl-carrier-protein reductase). Isoniazid-resistant cases of TB found in clinical settings usually involve mutations in or deletion of katG, which abrogate INH activation. Compounds that inhibit InhA without requiring prior activation by KatG would not be affected by this resistance mechanism and hence would display continued potency against these drug-resistant isolates of Mtb. Virtual screening experiments versus InhA in the GO Fight Against Malaria (GO FAM) project were designed to discover new scaffolds that display base-stacking interactions with the NAD cofactor. GO FAM experiments included targets from other pathogens, including Mtb, when they had structural similarity to a malaria target. Eight of the 16 soluble compounds identified by docking against InhA plus visual inspection were modest inhibitors and did not require prior activation by KatG. The best two inhibitors discovered are both fragment-sized compounds and displayed Ki values of 54 and 59 μM, respectively. Importantly, the novel inhibitors discovered have low structural similarity to known InhA inhibitors and thus help expand the number of chemotypes on which future medicinal chemistry efforts can be focused. These new fragment hits could eventually help advance the fight against INH-resistant Mtb strains, which pose a significant global health threat.

Molecular docking is a powerful tool used in drug discovery and structural biology for predicting the structures of ligand-receptor complexes. However, the accuracy of docking calculations can be limited by factors such as the neglect of protein reorganization in the scoring function; as a result, ligand screening can produce a high rate of false positive hits. Although absolute binding free energy methods still have difficulty in accurately rank-ordering binders, we believe that they can be fruitfully employed to distinguish binders from nonbinders and reduce the false positive rate. Here we study a set of ligands that dock favorably to a newly discovered, potentially allosteric site on the flap of HIV-1 protease. Fragment binding to this site stabilizes a closed form of protease, which could be exploited for the design of allosteric inhibitors. Twenty-three top-ranked protein-ligand complexes from AutoDock were subject to the free energy screening using two methods, the recently developed binding energy analysis method (BEDAM) and the standard double decoupling method (DDM). Free energy calculations correctly identified most of the false positives (≥83%) and recovered all the confirmed binders. The results show a gap averaging ≥3.7 kcal/mol, separating the binders and the false positives. We present a formula that decomposes the binding free energy into contributions from the receptor conformational macrostates, which provides insights into the roles of different binding modes. Our binding free energy component analysis further suggests that improving the treatment for the desolvation penalty associated with the unfulfilled polar groups could reduce the rate of false positive hits in docking. The current study demonstrates that the combination of docking with free energy methods can be very useful for more accurate ligand screening against valuable drug targets.

The large size and relative complexity of many plant genomes make creation, quality control, and dissemination of high-quality gene structure annotations challenging. In response, we have developed MAKER-P, a fast and easy-to-use genome annotation engine for plants. Here, we report the use of MAKER-P to update and revise the maize (Zea mays) B73 RefGen_v3 annotation build (5b+) in less than 3 h using the iPlant Cyberinfrastructure. MAKER-P identified and annotated 4,466 additional, well-supported protein-coding genes not present in the 5b+ annotation build, added additional untranslated regions to 1,393 5b+ gene models, identified 2,647 5b+ gene models that lack any supporting evidence (despite the use of large and diverse evidence data sets), identified 104,215 pseudogene fragments, and created an additional 2,522 noncoding gene annotations. We also describe a method for de novo training of MAKER-P for the annotation of newly sequenced grass genomes. Collectively, these results lead to the 6a maize genome annotation and demonstrate the utility of MAKER-P for rapid annotation, management, and quality control of grasses and other difficult-to-annotate plant genomes., (© 2015 American Society of Plant Biologists. All Rights Reserved.)

cellPACK assembles computational models of the biological mesoscale, an intermediate scale (10-100 nm) between molecular and cellular biology scales. cellPACK's modular architecture unites existing and novel packing algorithms to generate, visualize and analyze comprehensive three-dimensional models of complex biological environments that integrate data from multiple experimental systems biology and structural biology sources. cellPACK is available as open-source code, with tools for validation of models and with 'recipes' and models for five biological systems: blood plasma, cytoplasm, synaptic vesicles, HIV and a mycoplasma cell. We have applied cellPACK to model distributions of HIV envelope protein to test several hypotheses for consistency with experimental observations. Biologists, educators and outreach specialists can interact with cellPACK models, develop new recipes and perform packing experiments through scripting and graphical user interfaces at http://cellPACK.org/.

Here, we review some of the opportunities and challenges that we face in computational modeling of HIV therapeutic targets and structural biology, both in terms of methodology development and structure-based drug design (SBDD). Computational methods have provided fundamental support to HIV research since the initial structural studies, helping to unravel details of HIV biology. Computational models have proved to be a powerful tool to analyze and understand the impact of mutations and to overcome their structural and functional influence in drug resistance. With the availability of structural data, in silico experiments have been instrumental in exploiting and improving interactions between drugs and viral targets, such as HIV protease, reverse transcriptase, and integrase. Issues such as viral target dynamics and mutational variability, as well as the role of water and estimates of binding free energy in characterizing ligand interactions, are areas of active computational research. Ever-increasing computational resources and theoretical and algorithmic advances have played a significant role in progress to date, and we envision a continually expanding role for computational methods in our understanding of HIV biology and SBDD in the future.