Somatic cells can be inefficiently and stochastically reprogrammed into induced pluripotent stem (iPS) cells by exogenous expression of Oct4 (also called Pou5f1), Sox2, Klf4 and Myc (hereafter referred to as OSKM). The nature of the predominant rate-limiting barrier(s) preventing the majority of cells to successfully and synchronously reprogram remains to be defined. Here we show that depleting Mbd3, a core member of the Mbd3/NuRD (nucleosome remodelling and deacetylation) repressor complex, together with OSKM transduction and reprogramming in naive pluripotency promoting conditions, result in deterministic and synchronized iPS cell reprogramming (near 100% efficiency within seven days from mouse and human cells). Our findings uncover a dichotomous molecular function for the reprogramming factors, serving to reactivate endogenous pluripotency networks while simultaneously directly recruiting the Mbd3/NuRD repressor complex that potently restrains the reactivation of OSKM downstream target genes. Subsequently, the latter interactions, which are largely depleted during early pre-implantation development in vivo, lead to a stochastic and protracted reprogramming trajectory towards pluripotency in vitro. The deterministic reprogramming approach devised here offers a novel platform for the dissection of molecular dynamics leading to establishing pluripotency at unprecedented flexibility and resolution.

Natural proteins must both fold into a stable conformation and exert their molecular function. To date, computational design has successfully produced stable and atomically accurate proteins by using so-called "ideal" folds rich in regular secondary structures and almost devoid of loops and destabilizing elements, such as cavities. Molecular function, such as binding and catalysis, however, often demands nonideal features, including large and irregular loops and buried polar interaction networks, which have remained challenging for fold design. Through five design/experiment cycles, we learned principles for designing stable and functional antibody variable fragments (Fvs). Specifically, we (i) used sequence-design constraints derived from antibody multiple-sequence alignments, and (ii) during backbone design, maintained stabilizing interactions observed in natural antibodies between the framework and loops of complementarity-determining regions (CDRs) 1 and 2. Designed Fvs bound their ligands with midnanomolar affinities and were as stable as natural antibodies, despite having >30 mutations from mammalian antibody germlines. Furthermore, crystallographic analysis demonstrated atomic accuracy throughout the framework and in four of six CDRs in one design and atomic accuracy in the entire Fv in another. The principles we learned are general, and can be implemented to design other nonideal folds, generating stable, specific, and precise antibodies and enzymes.ue to their versatility, dozens of antibodies are in routine clinical use to diagnose and treat the most intransigent diseases and thousands more are used as research reagents. These antibodies were all isolated either by animal immunization or from synthetic repertoires that mimic the diversity of vertebrate immune systems. Notwithstanding these successes, however, natural repertoires have limitations, including biases and redundancy in representing the vast potential sequence and conformation space available to antibodies, and many antibodies exhibit polyspecificity and low expressibility, failing to meet the stringent requirements of research or clinical use (1-3). It has therefore been a longstanding goal of protein engineering to "build antibodies from first principles" (4).Computational protein design has mostly targeted so-called "ideal" proteins with high secondary-structure content, where polar backbone atoms form regular, short-range hydrogen bonds (5-9); irregularities, such as those seen in long loop regions, were almost absent from these designs. By contrast, the functional surfaces of most natural proteins, including antibodies, contain nonideal features, such as unpaired polar groups, buried charges, and long loops that are essential for function (10, 11). It has therefore been postulated that computational design of "nonideal" backbone and sequence features is of fundamental importance for understanding protein structure, stability, and function, and may open the way to the application of computational-design methodology to difficult problems ...

Computational design of protein function has made substantial progress, generating new enzymes, binders, inhibitors, and nanomaterials not previously seen in nature. However, the ability to design new protein backbones for function--essential to exert control over all polypeptide degrees of freedom--remains a critical challenge. Most previous attempts to design new backbones computed the mainchain from scratch. Here, instead, we describe a combinatorial backbone and sequence optimization algorithm called AbDesign, which leverages the large number of sequences and experimentally determined molecular structures of antibodies to construct new antibody models, dock them against target surfaces and optimize their sequence and backbone conformation for high stability and binding affinity. We used the algorithm to produce antibody designs that target the same molecular surfaces as nine natural, high-affinity antibodies; in five cases interface sequence identity is above 30%, and in four of those the backbone conformation at the core of the antibody binding surface is within 1 Å root-mean square deviation from the natural antibodies. Designs recapitulate polar interaction networks observed in natural complexes, and amino acid sidechain rigidity at the designed binding surface, which is likely important for affinity and specificity, is high compared to previous design studies. In designed anti-lysozyme antibodies, complementarity-determining regions (CDRs) at the periphery of the interface, such as L1 and H2, show greater backbone conformation diversity than the CDRs at the core of the interface, and increase the binding surface area compared to the natural antibody, potentially enhancing affinity and specificity.

SummaryThe Msn2 and Msn4 transcription factors play crucial roles in the yeast general stress response. Previous studies identified several large functional domains of Msn2, mainly through crude truncations. Here, using bioinformatics and experimental approaches to examine Msn2 structure-function relationships, we have identified new functional motifs in the Msn2 transcriptional-activating domain (TAD). Msn2 is predicted to adopt an intrinsically disordered structure with two short structural motifs in its TAD. Mutations in these motifs dramatically decreased Msn2 transcriptional activity, yeast stress survival and Msn2 nuclear localization levels. Using the split-ubiquitin assay, we found that these motifs are important for the interaction of Msn2 with Gal11, a subunit of the mediator complex. Finally, we show that one of these motifs is functionally conserved in several yeast species, highlighting a common mechanism of Msn2 transcriptional activation throughout yeast evolution.

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