Generalized biomolecular modeling and design with RoseTTAFold All-Atom

Deep learning methods have revolutionized protein structure prediction and design but are currently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA) which combines a residue-based representation of amino acids and DNA bases with an atomic representation of all other groups to model assemblies containing proteins, nucleic acids, small molecules, metals, and covalent modifications given their sequences and chemical structures. By fine tuning on denoising tasks we obtain RFdiffusionAA, which builds protein structures around small molecules. Starting from random distributions of amino acid residues surrounding target small molecules, we design and experimentally validate, through crystallography and binding measurements, proteins that bind the cardiac disease therapeutic digoxigenin, the enzymatic cofactor heme, and the light harvesting molecule bilin

A new class of transcription factors mediates brassinosteroid-regulated gene expression in Arabidopsis

Brassinosteroids (BRs) signal through a plasma membrane-localized receptor kinase to regulate plant growth and development. We showed previously that a novel protein, BES1, accumulates in the nucleus in response to BRs, where it plays a role in BR-regulated gene expression; however, the mechanism by which BES1 regulates gene expression is unknown. In this study, we dissect BES1 subdomains and establish that BES1 is a transcription factor that binds to and activates BR target gene promoters both in vitro and in vivo. BES1 interacts with a basic helix-loop-helix protein, BIM1, to synergistically bind to E box (CANNTG) sequences present in many BR-induced promoters. Loss-of-function and gain-of-function mutants of BIM1 and its close family members display BR response phenotypes. Thus, BES1 defines a new class of plant-specific transcription factors that cooperate with transcription factors such as BIM1 to regulate BR-induced genes

Comparative analysis of regulatory information and circuits across distant species

Despite the large evolutionary distances, metazoan species show remarkable commonalities, which has helped establish fly and worm as model organisms for human biology(1,2). Although studies of individual elements and factors have explored similarities in gene regulation, a large-scale comparative analysis of basic principles of transcriptional regulatory features is lacking. We mapped the genome-wide binding locations of 165 human, 93 worm, and 52 fly transcription-regulatory factors (RFs) generating a total of 1,019 data sets from diverse cell-types, developmental stages, or conditions in the three species, of which 498 (48.9%) are presented here for the first time. We find that structural properties of regulatory networks are remarkably conserved and that orthologous RF families recognize similar binding motifs in vivo and show some similar co-associations. Our results suggest that gene-regulatory properties previously observed for individual factors are general principles of metazoan regulation that are remarkably well-preserved despite extensive functional divergence of individual network connections. The comparative maps of regulatory circuitry provided here will drive an improved understanding in the regulatory underpinnings of model organism biology and how these relate to human biology, development, and disease

Integrative analysis of the Caenorhabditis elegans genome by the modENCODE project

We systematically generated large-scale data sets to improve genome annotation for the nematode Caenorhabditis elegans, a key model organism. These data sets include transcriptome profiling across a developmental time course, genome-wide identification of transcription factor–binding sites, and maps of chromatin organization. From this, we created more complete and accurate gene models, including alternative splice forms and candidate noncoding RNAs. We constructed hierarchical networks of transcription factor–binding and microRNA interactions and discovered chromosomal locations bound by an unusually large number of transcription factors. Different patterns of chromatin composition and histone modification were revealed between chromosome arms and centers, with similarly prominent differences between autosomes and the X chromosome. Integrating data types, we built statistical models relating chromatin, transcription factor binding, and gene expression. Overall, our analyses ascribed putative functions to most of the conserved genome

Integrative analysis of the caenorhabditis elegans genome by the modENCODE project

We systematically generated large-scale data sets to improve genome annotation for the nematode Caenorhabditis elegans, a key model organism. These data sets include transcriptome profiling across a developmental time course, genome-wide identification of transcription factor-binding sites, and maps of chromatin organization. From this, we created more complete and accurate gene models, including alternative splice forms and candidate noncoding RNAs. We constructed hierarchical networks of transcription factor-binding and microRNA interactions and discovered chromosomal locations bound by an unusually large number of transcription factors. Different patterns of chromatin composition and histone modification were revealed between chromosome arms and centers, with similarly prominent differences between autosomes and the X chromosome. Integrating data types, we built statistical models relating chromatin, transcription factor binding, and gene expression. Overall, our analyses ascribed putative functions to most of the conserved genome