Rapamycin-sensitive mechanisms confine the growth of fission yeast below the temperatures detrimental to cell physiology.

Cells cease to proliferate above their growth-permissible temperatures, a ubiquitous phenomenon generally attributed to heat damage to cellular macromolecules. We here report that, in the presence of rapamycin, a potent inhibitor of Target of Rapamycin Complex 1 (TORC1), the fission yeast Schizosaccharomyces pombe can proliferate at high temperatures that usually arrest its growth. Consistently, mutations to the TORC1 subunit RAPTOR/Mip1 and the TORC1 substrate Sck1 significantly improve cellular heat resistance, suggesting that TORC1 restricts fission yeast growth at high temperatures. Aiming for a more comprehensive understanding of the negative regulation of high-temperature growth, we conducted genome-wide screens, which identified additional factors that suppress cell proliferation at high temperatures. Among them is Mks1, which is phosphorylated in a TORC1-dependent manner, forms a complex with the 14-3-3 protein Rad24, and suppresses the high-temperature growth independently of Sck1. Our study has uncovered unexpected mechanisms of growth restraint even below the temperatures deleterious to cell physiology.

Theoretical study of the interactions between peptide tyrosine tyrosine [PYY (1-36)], a newly identified modulator in type 2 diabetes pathophysiology, with receptors NPY1R and NPY4R.

PURPOSE: Diabetes mellitus is a common condition in the clinically obese. Bariatric surgery is one of the ways to put type 2 diabetes in remission. Recent findings propose the appetite-regulator peptide tyrosine tyrosine (PYY) as a therapeutic option for patients with type 2 diabetes. This novel gut hormone restores impaired insulin and glucagon secretion in pancreatic islets and is implicated in type 2 diabetes reversal after bariatric surgery. The current study elucidates the interactions between PYY and the NPY1R and NPY4R receptors using computational methods. METHODS: Protein structure prediction, molecular docking simulation, and molecular dynamics (MD) simulation were performed to elucidate the interactions of PYY with NPY1R and NPY4R. RESULTS: The predicted binding models of PYY-NPY receptors are in agreement with those described in the literature, although different interaction partners are presented for the C-terminal tail of PYY. Non-polar interactions are predicted to drive the formation of the protein complex. The calculated binding energies show that PYY has higher affinity for NPY4R (ΔGGBSA = -65.08 and ΔGPBSA = -87.62 kcal/mol) than for NPY1R (ΔGGBSA = -23.11 and ΔGPBSA = -50.56 kcal/mol). CONCLUSIONS: Based on the constructed models, the binding conformations obtained from docking and MD simulation for both the PYY-NPY1R and PYY-NPY4R complexes provide a detailed map of possible interactions. The calculated binding energies show a higher affinity of PYY for NPY4R. These findings may help to understand the mechanisms behind the improvement of diabetes following bariatric surgery.

Optimisation of human VH domain antibodies specific to Mycobacterium tuberculosis heat shock protein (HSP16.3).

Mycobacterium tuberculosis (Mtb) 16.3 kDa heat shock protein 16.3 (HSP16.3) is a latency-associated antigen that can be targeted for latent tuberculosis (TB) diagnostic and therapeutic development. We have previously developed human VH domain antibodies (dAbs; clone E3 and F1) specific against HSP16.3. In this work, we applied computational methods to optimise and design the antibodies in order to improve the binding affinity with HSP16.3. The VH domain antibodies were first docked to the dimer form of HSP16.3 and further sampled using molecular dynamics simulation. The calculated binding free energy of the HSP16.3-dAb complexes showed non-polar interactions were responsible for the antigen-antibody association. Per-residue free energy decomposition and computational alanine scanning have identified one hotspot residue for E3 (Y391) and 4 hotspot residues for F1 (M394, Y396, R397 and M398). These hotspot residues were then mutated and evaluated by binding free energy calculations. Phage ELISA assay was carried out on the potential mutants (E3Y391W, F1M394E, F1R397N and F1M398Y). The experimental assay showed improved binding affinities of E3Y391W and F1M394E against HSP16.3 compared with the wild type E3 and F1. This case study has thus showed in silico methods are able to assist in optimisation or improvement of antibody-antigen binding.

Computer-Aided Antibody Design: An Overview.

The use of monoclonal antibody as the next generation protein therapeutics with remarkable success has surged the development of antibody engineering to design molecules for optimizing affinity, better efficacy, greater safety and therapeutic function. Therefore, computational methods have become increasingly important to generate hypotheses, interpret and guide experimental works. In this chapter, we discussed the overall antibody design by computational approches.