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Abstract: Regulation of lineage biases in hematopoietic stem and progenitor cells (HSPCs) is pivotal for balanced hematopoietic output. However, little is known about the mechanism behind lineage choice in HSPCs. Here, we show that messenger RNA (mRNA) decay factors regnase-1 (Reg1; Zc3h12a) and regnase-3 (Reg3; Zc3h12c) are essential for determining lymphoid fate and restricting myeloid differentiation in HSPCs. Loss of Reg1 and Reg3 resulted in severe impairment of lymphopoiesis and a mild increase in myelopoiesis in the bone marrow. Single-cell RNA sequencing analysis revealed that Reg1 and Reg3 regulate lineage directions in HSPCs via the control of a set of myeloid-related genes. Reg1- and Reg3-mediated control of mRNA encoding Nfkbiz, a transcriptional and epigenetic regulator, was essential for balancing lymphoid/myeloid lineage output in HSPCs in vivo. Furthermore, single-cell assay for transposase-accessible chromatin sequencing analysis revealed that Reg1 and Reg3 control the epigenetic landscape on myeloid-related gene loci in early stage HSPCs via Nfkbiz. Consistently, an antisense oligonucleotide designed to inhibit Reg1- and Reg3-mediated Nfkbiz mRNA degradation primed hematopoietic stem cells toward myeloid lineages by enhancing Nfkbiz expression. Collectively, the collaboration between posttranscriptional control and chromatin remodeling by the Reg1/Reg3-Nfkbiz axis governs HSPC lineage biases, ultimately dictating the fate of lymphoid vs myeloid differentiation., (© 2024 American Society of Hematology. Published by Elsevier Inc. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)

RNA-LIM is a procedure that can analyze various pseudo-potentials describing the affinity between single-stranded RNA (ssRNA) ribonucleotides and surface amino acids to produce a coarse-grained estimate of the structure of the ssRNA at the protein interface. The search algorithm works by evolving an ssRNA chain, of known sequence, as a series of walks between fixed sites on a protein surface. Optimal routes are found by application of a set of minimal "limiting" restraints derived jointly from (i) selective sampling of the ribonucleotide amino acid affinity pseudo-potential data, (ii) limited surface path exploration by prior determination of surface arc lengths, and (iii) RNA structural specification obtained from a statistical potential gathered from a library of experimentally determined ssRNA structures. We describe the general approach using a NAST (Nucleic Acid Simulation Tool)-like approximation of the ssRNA chain and a generalized pseudo-potential reflecting the location of nucleic acid binding residues. Minimum and maximum performance indicators of the methodology are established using both synthetic data, for which the pseudo-potential defining nucleic acid binding affinity is systematically degraded, and a representative real case, where the RNA binding sites are predicted by the amplified antisense RNA (aaRNA) method. Some potential uses and extensions of the routine are discussed. RNA-LIM analysis programs along with detailed instructions for their use are available on request from the authors., (Crown Copyright © 2014. Published by Elsevier Inc. All rights reserved.)

Intrinsically disordered domains have been reported to play important roles in signal transduction networks by introducing cooperativity into protein-protein interactions. Unlike intrinsically disordered domains that become ordered upon binding, the EF-SAM domain in the stromal interaction molecule (STIM) 1 is distinct in that it is ordered in the monomeric state and partially unfolded in its oligomeric state, with the population of the two states depending on the local Ca(2+) concentration. The oligomerization of STIM1, which triggers extracellular Ca(2+) influx, exhibits cooperativity with respect to the local endoplasmic reticulum Ca(2+) concentration. Although the physiological importance of the oligomerization reaction is well established, the mechanism of the observed cooperativity is not known. Here, we examine the response of the STIM1 EF-SAM domain to changes in Ca(2+) concentration using mathematical modeling based on in vitro experiments. We find that the EF-SAM domain partially unfolds and dimerizes cooperatively with respect to Ca(2+) concentration, with Hill coefficients and half-maximal activation concentrations very close to the values observed in vivo for STIM1 redistribution and extracellular Ca(2+) influx. Our mathematical model of the dimerization reaction agrees quantitatively with our analytical ultracentrifugation-based measurements and previously published free energies of unfolding. A simple interpretation of these results is that Ca(2+) loss effectively acts as a denaturant, enabling cooperative dimerization and robust signal transduction. We present a structural model of the Ca(2+)-unbound EF-SAM domain that is consistent with a wide range of evidence, including resistance to proteolytic cleavage of the putative dimerization portion., (Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The CAPRI (Critical Assessment of Predicted Interactions) and CASP (Critical Assessment of protein Structure Prediction) experiments have demonstrated the power of community-wide tests of methodology in assessing the current state of the art and spurring progress in the very challenging areas of protein docking and structure prediction. We sought to bring the power of community-wide experiments to bear on a very challenging protein design problem that provides a complementary but equally fundamental test of current understanding of protein-binding thermodynamics. We have generated a number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments, suggesting that there may be important physical chemistry missing in the energy calculations. A total of 28 research groups took up the challenge of determining what is missing: we provided structures of 87 designed complexes and 120 naturally occurring complexes and asked participants to identify energetic contributions and/or structural features that distinguish between the two sets. The community found that electrostatics and solvation terms partially distinguish the designs from the natural complexes, largely due to the nonpolar character of the designed interactions. Beyond this polarity difference, the community found that the designed binding surfaces were, on average, structurally less embedded in the designed monomers, suggesting that backbone conformational rigidity at the designed surface is important for realization of the designed function. These results can be used to improve computational design strategies, but there is still much to be learned; for example, one designed complex, which does form in experiments, was classified by all metrics as a nonbinder., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

We report the tertiary structure predictions for 95 proteins ranging in size from 17 to 160 residues starting from known secondary structure. Predictions are obtained from global minimization of an empirical potential function followed by the application of a refined atomic overlap potential. The minimization strategy employed represents a variant of the Monte Carlo plus minimization scheme of Li and Scheraga applied to a reduced model of the protein chain. For all of the cases except beta-proteins larger than 75 residues, a native-like structure, usually 4-6 A root-mean-square deviation from the native, is located. For beta-proteins larger than 75 residues, the energy gap between native-like structures and the lowest energy structures produced in the simulation is large, so that low RMSD structures are not generated starting from an unfolded state. This is attributed to the lack of an explicit hydrogen bond term in the potential function, which we hypothesize is necessary to stabilize large assemblies of beta-strands., (Copyright 1999 Academic Press.)

We describe new methods for predicting protein tertiary structures to low resolution given the specification of secondary structure and a limited set of long-range NMR distance constraints. The NMR data sets are derived from a realistic protocol involving completely deuterated 15N and 13C-labeled samples. A global optimization method, based upon a modification of the alphaBB (branch and bound) algorithm of Floudas and co-workers, is employed to minimize an objective function combining the NMR distance restraints with a residue-based protein folding potential containing hydrophobicity, excluded volume, and van der Waals interactions. To assess the efficacy of the new methodology, results are compared with benchmark calculations performed via the X-PLOR program of Brünger and co-workers using standard distance geometry/molecular dynamics (DGMD) calculations. Seven mixed alpha/beta proteins are examined, up to a size of 183 residues, which our methods are able to treat with a relatively modest computational effort, considering the size of the conformational space. In all cases, our new approach provides substantial improvement in root-mean-square deviation from the native structure over the DGMD results; in many cases, the DGMD results are qualitatively in error, whereas the new method uniformly produces high quality low-resolution structures. The DGMD structures, for example, are systematically non-compact, which probably results from the lack of a hydrophobic term in the X-PLOR energy function. These results are highly encouraging as to the possibility of developing computational/NMR protocols for accelerating structure determination in larger proteins, where data sets are often underconstrained., (Copyright 1999 Academic Press.)