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BACKGROUND Severe combined immunodeficiency (SCID) is characterized by arrested T-lymphocyte production and by B-lymphocyte dysfunction, which result in life-threatening infections. Early diagnosis of SCID through population-based screening of newborns can aid clinical management and help improve outcomes; it also permits the identification of previously unknown factors that are essential for lymphocyte development in humans. METHODS SCID was detected in a newborn before the onset of infections by means of screening of T-cell–receptor excision circles, a biomarker for thymic output. On confirmation of the condition, the affected infant was treated with allogeneic hematopoietic stem-cell transplantation. Exome sequencing in the patient and parents was followed by functional analysis of a prioritized candidate gene with the use of human hematopoietic stem cells and zebrafish embryos. RESULTS The infant had “leaky” SCID (i.e., a form of SCID in which a minimal degree of immune function is preserved), as well as craniofacial and dermal abnormalities and the absence of a corpus callosum; his immune deficit was fully corrected by hematopoietic stem-cell transplantation. Exome sequencing revealed a heterozygous de novo missense mutation, p.N441K, in BCL11B. The resulting BCL11B protein had dominant negative activity, which abrogated the ability of wild-type BCL11B to bind DNA, thereby arresting development of the T-cell lineage and disrupting hematopoietic stem-cell migration; this revealed a previously unknown function of BCL11B. The patient’s abnormalities, when recapitulated in bcl11ba-deficient zebrafish, were reversed by ectopic expression of functionally intact human BCL11B but not mutant human BCL11B. CONCLUSIONS Newborn screening facilitated the identification and treatment of a previously unknown cause of human SCID. Coupling exome sequencing with an evaluation of candidate genes in human hematopoietic stem cells and in zebrafish revealed that a constitutional BCL11B mutation caused human multisystem anomalies with SCID and also revealed a prethymic role for BCL11B in hematopoietic progenitors. (Funded by the National Institutes of Health and others.)

Motivated by the relationship between the folding mechanism and the native structure, we develop a unified approach for predicting folding pathways and tertiary structure using only the primary sequence as input. Simulations begin from a realistic unfolded state devoid of secondary structure and use a chain representation lacking explicit side chains, rendering the simulations many orders of magnitude faster than molecular dynamics simulations. The multiple round nature of the algorithm mimics the authentic folding process and tests the effectiveness of sequential stabilization (SS) as a search strategy wherein 2°structural elements add onto existing structures in a process of progressive learning and stabilization of structure found in prior rounds of folding. Because no a priori knowledge is used, we can identify kinetically significant nonnative interactions and intermediates, sometimes generated by only two mutations, while the evolution of contact matrices is often consistent with experiments. Moreover, structure prediction improves substantially by incorporating information from prior rounds. The success of our simple, homology-free approach affirms the validity of our description of the primary determinants of folding pathways and structure, and the effectiveness of SS as a search strategy.TerItFix | foldons | kinetic traps | Monte Carlo simulation D espite numerous advances since the original sequenceto-structure folding paradigm was proposed over 50 years ago (1), we still lack a general framework that enables simultaneous prediction of the folding mechanism and structure using only the amino acid (aa) sequence [notwithstanding recent successes of all-atom simulations to fold small, fast-folding proteins (2)]. An obvious obstacle is the astronomical number of conformations available to a polypeptide. Proteins overcome this obstacle by sampling a limited set of conformations, guided by the folding process itself. However, most successful structure prediction methods do not consider the folding mechanism when sampling conformations. Conversely, many methods for predicting folding mechanism rely on knowledge of the final structure (e.g., Gō models).Another obstacle emerges because many non-native and nearnative conformations often differ by only a few RT, which is at or beyond the ability of current energy functions to reliably distinguish. A related difficulty arises because the native state is the global free energy minimum even if three competing propertieslocal backbone torsional angle preferences, hydrogen bonded 2°structure, and 3°packing-are not individually optimized. For example, 3°context can overcome local biases in determining the final 2°structure (3). Hence, a successful framework should couple 3°context to 2°structure formation, rather than relying on a strict hierarchical approach.