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A model of haematopoiesis that links self-organisation with symmetric and asymmetric cell division is presented in this paper. It is assumed that all cell divisions are completely random events, and that the daughter cells resulting from symmetric and asymmetric stem cell divisions are, in general, phenotypically identical, and still, the haematopoietic system has the flexibility to self-renew, produce mature cells by differentiation, and regenerate undifferentiated and differentiated cells when necessary, due to self-organisation. As far as we know, no previous model implements symmetric and asymmetric division as the result of self-organisation. The model presented in this paper is inspired by experiments on the Drosophila germline stem cell, which imply that under normal conditions, the stem cells typically divide asymmetrically, whereas during regeneration, the rate of symmetric division increases. Moreover, the model can reproduce several of the results from experiments on female Safari cats. In particular, the model can explain why significant fluctuation in the phenotypes of haematopoietic cells was observed in some cats, when the haematopoietic system had reached normal population level after regeneration. To our knowledge, no previous model of haematopoiesis in Safari cats has captured this phenomenon., (Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The binding of P1 variants of bovine pancreatic trypsin inhibitor (BPTI) to trypsin has been investigated by means of molecular dynamics simulations. The specific interaction formed between the amino acid at the primary binding (P1) position of the binding loop of BPTI and the specificity pocket of trypsin was estimated by use of the linear interaction energy (LIE) method. Calculations for 13 of the naturally occurring amino acids at the P1 position were carried out, and the results obtained were found to correlate well with the experimental binding free energies. The LIE calculations rank the majority of the 13 variants correctly according to the experimental association energies and the mean error between calculated and experimental binding free energies is only 0.38 kcal/mole, excluding the Glu and Asp variants, which are associated with some uncertainties regarding protonation and the possible presence of counter-ions. The three-dimensional structures of the complex with three of the P1 variants (Asn, Tyr, and Ser) included in this study have not at present been solved by any experimental techniques and, therefore, were modeled on the basis of experimental data from P1 variants of similar size. Average structures were calculated from the MD simulations, from which specific interactions explaining the broad variation in association energies were identified. The present study also shows that explicit treatment of the complex water-mediated hydrogen bonding network at the protein-protein interface is of crucial importance for obtaining reliable binding free energies. The successful reproduction of relative binding energies shows that this type of methodology can be very useful as an aid in rational design and redesign of biologically active macromolecules.

Organisms that live in constantly cold environments have to adapt their metabolism to low temperatures, but mechanisms of enzymatic adaptation to cold environments are not fully understood. Cold active trypsin catalyses reactions more efficiently and binds ligands more strongly in comparison to warm active trypsin. We have addressed this issue by means of comparative free energy calculations studying the binding of positively charged ligands to two trypsin homologues. Stronger inhibition of the cold active trypsin by benzamidine and positively charged P1-variants of BPTI is caused by rather subtle electrostatic effects. The different affinity of benzamidine originates solely from long range interactions, while the increased binding of P1-Lys and -Arg variants of BPTI is attributed to both long and short range effects that are enhanced in the cold active trypsin compared to the warm active counterpart. Electrostatic interactions thus provide an efficient strategy for cold adaptation of trypsin.

A qualitative evaluation of electrostatic features of the substrate binding region of seven isoenzymes of trypsin has been performed by using the continuum electrostatic model for the solution of the Poisson-Boltzmann equation. The sources of the electrostatic differences among the trypsins have been sought by comparative calculations on selective charges: all charges, conserved charges, partial charges, unique cold trypsin charges, and a number of charge mutations. As expected, most of the negative potential at the S(1) region of all trypsins is generated from Asp(189), but the potential varies significantly among the seven trypsin isoenzymes. The three cold active enzymes included in this study possess a notably lower potential at and around the S(1)-pocket compared with the warm active counterparts; this finding may be the main contribution to the increased binding affinity. The source of the differences are nonconserved charged residues outside the specificity pocket, producing electric fields at the S(1)-pocket that are different in both sign and magnitude. The surface charges of the mesophilic trypsins generally induce the S(1) pocket positively, whereas surface charges of the cold trypsins produce a negative electric field of this region. Calculations on mutants, where charged amino acids were substituted between the trypsins, showed that mutations in Loop2 (residues 221B and 224) and residue 175, in particular, were responsible for the low potential of the cold enzymes., (Copyright 2000 Wiley-Liss, Inc.)

The association energy upon binding of different amino acids in the specificity pocket of trypsin was evaluated by free energy perturbation calculations on complexes between bovine trypsin (BT) and bovine pancreatic trypsin inhibitor (BPTI). Three simulations of mutations of the primary binding residue (P(1)) were performed (P(1)-Ala to Gly, P(1)-Met to Gly and P(1)-Met to Ala) and the resulting differences in association energy (DeltaDeltaG(a)) are 2. 28, 5.08 and 2.93 kcal/mol for P(1)-Ala to Gly, P(1)-Met to Gly and to Ala with experimental values of 1.71, 4.62 and 2.91 kcal/mol, respectively. The calculated binding free energy differences are hence in excellent agreement with the experimental binding free energies. The binding free energies, however, were shown to be highly dependent on water molecules at the protein-protein interface and could only be quantitatively estimated if the correct number of such water molecules was included. Furthermore, the cavities that were formed when a large amino acid side-chain is perturbed to a smaller one seem to create instabilities in the systems and had to be refilled with water molecules in order to obtain reliable results. In addition, if the protein atoms that were perturbed away were not replaced by water molecules, the simulations dramatically overestimated the initial state of the free energy perturbations.

It is well established that the dynamic motion of proteins plays an important functional role, and that the adaptation of a protein molecule to its environment requires optimization of internal non-covalent interactions and protein-solvent interactions. Serine proteinases in general, and trypsin in particular has been used as a model system in exploring possible structural features for cold adaptation. In this study, a 500 p.s. and a 1200 p.s. molecular dynamics (MD) simulation at 300 K of both anionic salmon trypsin and cationic bovine trypsin are analyzed in terms of molecular flexibility, internal non-covalent interactions and protein-solvent interactions. The present MD simulations do not indicate any increased flexibility of the cold adapted enzyme on an overall basis. However, the apparent higher flexibility and deformability of the active site of anionic salmon trypsin may lower the activation energy for ligand binding and for catalysis, and might be a reason for the increased binding affinity and catalytic efficiency compared to cationic bovine trypsin.