AlphaFold illuminates half of the dark human proteins.

We investigate the use of confidence scores to evaluate the accuracy of a given AlphaFold (AF2) protein model for drug discovery. Prediction of accuracy is improved by not considering confidence scores below 80 due to the effects of disorder. On a set of recent crystal structures, 95% are likely to have accurate folds. Conformational discordance in the training set has a much more significant effect on accuracy than sequence divergence. We propose criteria for models and residues that are possibly useful for virtual screening. Based on these criteria, AF2 provides models for half of understudied (dark) human proteins and two-thirds of residues in those models.

Doing Genetic and Genomic Biology Using the Legume Information System and Associated Resources.

In this chapter, we introduce the main components of the Legume Information System ( https://legumeinfo.org ) and several associated resources. Additionally, we provide an example of their use by exploring a biological question: is there a common molecular basis, across legume species, that underlies the photoperiod-mediated transition from vegetative to reproductive development, that is, days to flowering? The Legume Information System (LIS) holds genetic and genomic data for a large number of crop and model legumes and provides a set of online bioinformatic tools designed to help biologists address questions and tasks related to legume biology. Such tasks include identifying the molecular basis of agronomic traits; identifying orthologs/syntelogs for known genes; determining gene expression patterns; accessing genomic datasets; identifying markers for breeding work; and identifying genetic similarities and differences among selected accessions. LIS integrates with other legume-focused informatics resources such as SoyBase ( https://soybase.org ), PeanutBase ( https://peanutbase.org ), and projects of the Legume Federation ( https://legumefederation.org ).

Correction: California condor microbiomes: Bacterial variety and functional properties in captive-bred individuals.

[This corrects the article DOI: 10.1371/journal.pone.0225858.].

California condor microbiomes: Bacterial variety and functional properties in captive-bred individuals.

Around the world, scavenging birds such as vultures and condors have been experiencing drastic population declines. Scavenging birds have a distinct digestive process to deal with higher amounts of bacteria in their primary diet of carcasses in varying levels of decay. These observations motivate us to present an analysis of captive and healthy California condor (Gymnogyps californianus) microbiomes to characterize a population raised together under similar conditions. Shotgun metagenomic DNA sequences were analyzed from fecal and cloacal samples of captive birds. Classification of shotgun DNA sequence data with peptide signatures using the Sequedex package provided both phylogenetic and functional profiles, as well as individually annotated reads for targeted confirmatory analysis. We observed bacterial species previously associated with birds and gut microbiomes, including both virulent and opportunistic pathogens such as Clostridium perfringens, Propionibacterium acnes, Shigella flexneri, and Fusobacterium mortiferum, common flora such as Lactobacillus johnsonii, Lactobacillus ruminus, and Bacteroides vulgatus, and mucosal microbes such as Delftia acidovorans, Stenotrophomonas maltophilia, and Corynebacterium falsnii. Classification using shotgun metagenomic reads from phylogenetic marker genes was consistent with, and more specific than, analysis based on 16S rDNA data. Classification of samples based on either phylogenetic or functional profiles of genomic fragments differentiated three types of samples: fecal, mature cloacal and immature cloacal, with immature birds having approximately 40% higher diversity of microbes.

Constructing rigorous and broad biosurveillance networks for detecting emerging zoonotic outbreaks.

Determining optimal surveillance networks for an emerging pathogen is difficult since it is not known beforehand what the characteristics of a pathogen will be or where it will emerge. The resources for surveillance of infectious diseases in animals and wildlife are often limited and mathematical modeling can play a supporting role in examining a wide range of scenarios of pathogen spread. We demonstrate how a hierarchy of mathematical and statistical tools can be used in surveillance planning help guide successful surveillance and mitigation policies for a wide range of zoonotic pathogens. The model forecasts can help clarify the complexities of potential scenarios, and optimize biosurveillance programs for rapidly detecting infectious diseases. Using the highly pathogenic zoonotic H5N1 avian influenza 2006-2007 epidemic in Nigeria as an example, we determined the risk for infection for localized areas in an outbreak and designed biosurveillance stations that are effective for different pathogen strains and a range of possible outbreak locations. We created a general multi-scale, multi-host stochastic SEIR epidemiological network model, with both short and long-range movement, to simulate the spread of an infectious disease through Nigerian human, poultry, backyard duck, and wild bird populations. We chose parameter ranges specific to avian influenza (but not to a particular strain) and used a Latin hypercube sample experimental design to investigate epidemic predictions in a thousand simulations. We ranked the risk of local regions by the number of times they became infected in the ensemble of simulations. These spatial statistics were then complied into a potential risk map of infection. Finally, we validated the results with a known outbreak, using spatial analysis of all the simulation runs to show the progression matched closely with the observed location of the farms infected in the 2006-2007 epidemic.

Rapid phylogenetic and functional classification of short genomic fragments with signature peptides.

BACKGROUND: Classification is difficult for shotgun metagenomics data from environments such as soils, where the diversity of sequences is high and where reference sequences from close relatives may not exist. Approaches based on sequence-similarity scores must deal with the confounding effects that inheritance and functional pressures exert on the relation between scores and phylogenetic distance, while approaches based on sequence alignment and tree-building are typically limited to a small fraction of gene families. We describe an approach based on finding one or more exact matches between a read and a precomputed set of peptide 10-mers. RESULTS: At even the largest phylogenetic distances, thousands of 10-mer peptide exact matches can be found between pairs of bacterial genomes. Genes that share one or more peptide 10-mers typically have high reciprocal BLAST scores. Among a set of 403 representative bacterial genomes, some 20 million 10-mer peptides were found to be shared. We assign each of these peptides as a signature of a particular node in a phylogenetic reference tree based on the RNA polymerase genes. We classify the phylogeny of a genomic fragment (e.g., read) at the most specific node on the reference tree that is consistent with the phylogeny of observed signature peptides it contains. Using both synthetic data from four newly-sequenced soil-bacterium genomes and ten real soil metagenomics data sets, we demonstrate a sensitivity and specificity comparable to that of the MEGAN metagenomics analysis package using BLASTX against the NR database. Phylogenetic and functional similarity metrics applied to real metagenomics data indicates a signal-to-noise ratio of approximately 400 for distinguishing among environments. Our method assigns ~6.6 Gbp/hr on a single CPU, compared with 25 kbp/hr for methods based on BLASTX against the NR database. CONCLUSIONS: Classification by exact matching against a precomputed list of signature peptides provides comparable results to existing techniques for reads longer than about 300 bp and does not degrade severely with shorter reads. Orders of magnitude faster than existing methods, the approach is suitable now for inclusion in analysis pipelines and appears to be extensible in several different directions.

A unified model of protein dynamics.

Protein functions require conformational motions. We show here that the dominant conformational motions are slaved by the hydration shell and the bulk solvent. The protein contributes the structure necessary for function. We formulate a model that is based on experiments, insights from the physics of glass-forming liquids, and the concepts of a hierarchically organized energy landscape. To explore the effect of external fluctuations on protein dynamics, we measure the fluctuations in the bulk solvent and the hydration shell with broadband dielectric spectroscopy and compare them with internal fluctuations measured with the Mössbauer effect and neutron scattering. The result is clear. Large-scale protein motions are slaved to the fluctuations in the bulk solvent. They are controlled by the solvent viscosity, and are absent in a solid environment. Internal protein motions are slaved to the beta fluctuations of the hydration shell, are controlled by hydration, and are absent in a dehydrated protein. The model quantitatively predicts the rapid increase of the mean-square displacement above approximately 200 K, shows that the external beta fluctuations determine the temperature- and time-dependence of the passage of carbon monoxide through myoglobin, and explains the nonexponential time dependence of the protein relaxation after photodissociation.

Crystal structure of beta-D-xylosidase from Thermoanaerobacterium saccharolyticum, a family 39 glycoside hydrolase.

1,4-beta-D-Xylan is the major component of plant cell-wall hemicelluloses. beta-D-Xylosidases are involved in the breakdown of xylans into xylose and belong to families 3, 39, 43, 52, and 54 of glycoside hydrolases. Here, we report the first crystal structure of a member of family 39 glycoside hydrolase, i.e. beta-D-xylosidase from Thermoanaerobacterium saccharolyticum strain B6A-RI. This study also represents the first structure of any beta-xylosidase of the above five glycoside hydrolase families. Each monomer of T. saccharolyticum beta-xylosidase comprises three distinct domains; a catalytic domain of the canonical (beta/alpha)(8)-barrel fold, a beta-sandwich domain, and a small alpha-helical domain. We have determined the structure in two forms: D-xylose-bound enzyme and a covalent 2-deoxy-2-fluoro-alpha-D-xylosyl-enzyme intermediate complex, thus providing two snapshots in the reaction pathway. This study provides structural evidence for the proposed double displacement mechanism that involves a covalent intermediate. Furthermore, it reveals possible functional roles for His228 as the auxiliary acid/base and Glu323 as a key residue in substrate recognition.

The TB structural genomics consortium: providing a structural foundation for drug discovery.

Structural genomics, the large-scale determination of protein structures, promises to provide a broad structural foundation for drug discovery. The tuberculosis (TB) Structural Genomics Consortium is devoted to encouraging, coordinating, and facilitating the determination of structures of proteins from Mycobacterium tuberculosis and hopes to determine 400 TB protein structures over 5 years. The Consortium has determined structures of 28 proteins from TB to date. These protein structures are already providing a basis for drug discovery efforts.

Engineering soluble proteins for structural genomics.

Structural genomics has the ambitious goal of delivering three-dimensional structural information on a genome-wide scale. Yet only a small fraction of natural proteins are suitable for structure determination because of bottlenecks such as poor expression, aggregation, and misfolding of proteins, and difficulties in solubilization and crystallization. We propose to overcome these bottlenecks by producing soluble, highly expressed proteins that are derived from and closely related to their natural homologs. Here we demonstrate the utility of this approach by using a green fluorescent protein (GFP) folding reporter assay to evolve an enzymatically active, soluble variant of a hyperthermophilic protein that is normally insoluble when expressed in Escherichia coli, and determining its structure by X-ray crystallography. Analysis of the structure provides insight into the substrate specificity of the enzyme and the improved solubility of the variant.