Ligand-dependent aggregation of chicken hemoglobin AI

The hemoglobin A_I component of the white leghorn chicken may potentially provide an animal model for the $\text{in vitro}$ aggregation behavior of human hemoglobin S. In solutions of low ionic strength, it has been found to undergo a striking loss of solubility upon deoxygenation, leading to the formation of macromolecular aggregates. This property is not shared by the other major chicken hemoglobin component, designated A_II. Compositional and NH₂-terminal sequence analysis indicate that extensive primary structural differences reside in the alpha chains of these two hemoglobins. The beta chains appear to be identical. Examination by electron microscopy suggests that the deoxyhemoglobin A_I forms microcrystalline arrays. The A_I component shows diminished reactivity with ¹³CO₂, as judged from ¹³C NMR measurements.     

AI in 3D compound design

The success of Artificial Intelligence (AI) across a wide range of domains has fuelled significant interest in its application to designing novel compounds and screening compounds against a specific target. However, many existing AI methods either do not account for the 3D structure of the target at all or struggle to capture meaningful spatial information from the target. In this Opinion, we highlight a range of recent structure-aware approaches which utilise deep learning for compound design and virtual screening. We discuss how such methods can be better integrated into existing drug discovery pipelines by facilitating the design of compounds which conform to a specified design hypothesis and by uncovering key protein-ligand interactions which can be used to aid molecule design.     

Ssh AI restriction endonuclease from Salmonella shikmonah

A new type II restriction endonuclease, SshAI, was purified from Salmonella shikmonah TK139 of kangaroo origin. The recognition and cleavage specificity of Ssh AI was determined to be 5'-CC/TNAGG-3', identical to that of SauI from Streptomyces aureofaciens and Bsu36I from Bacillus subtilis. Based on closely related and in part overlapping recognition specificities of Ssh AI and other restriction endonucleases, a close evolutionary relationship is proposed for all known Salmonella restriction endonucleases.     

Processing of proapolipoprotein AI requires specific conformation

Apolipoprotein AI of human high-density lipoproteins is secreted by hepatocytes as a proapolipoprotein with a N-terminal hexapeptide sequence (Arg-His-Phe-Trp-Gln-Gln-) which differs from the prosequence of rat apolipoprotein AI (Trp-Asp-Phe-Trp-Gln-Gln). The two proteins have in common the unusual cleavage site -Gln-Gln-Asp-Glu-. It is hydrolysed by a specific serum proteinase with the release of mature apo AI. We synthesized a model substrate for the study of the final processing of pro-apo AI by the serum proteinase. It is an undecapeptide embracing the human pro-hexapeptide sequence and the first five N-terminal residues of apo AI, covalently linked to a hydrophilic resin. The N-terminal arginine residue was 3H-labelled. [formula; see text] This sequence was not cleaved by human serum under the conditions under which rat serum processes the pro-form of apo AI secreted by rat hepatocytes. Pepsin and chymotrypsin fragmented the undecapeptide at sites characteristic for these proteinases. We conclude that the proteolytic cleavage at the specific site (-Gln-Gln-Asp-Glu-) requires the correct conformation in addition to the specific amino-acid sequence.     

A fluorescent probe study of salmine AI

A fluorescent probe, 1-p-toluidinylnapthalene-8-sulfonate (1,8-TNS), was used to study the nonpolar sites on salmine AI. Fluorescence enhancement resulting from binding between the probe and the protein occurs at a wavelength of maximum emission of 497-500 nm, indicating the existence of moderately nonpolar binding sites on salmine AI.Fluorescence enhancement decreases as the ionic strength of the solvent is increased from 0.002 M to 0.050 M. Fluorescence increases with increasing acidity although this effect is not correlated to the pKa of 1,8-TNS. Positive cooperative binding takes place between 1,8-TNS and salmine AI. Equilibrium dialysis indicates that binding occurs only under conditions resulting in significant fluorescent enhancement. The binding was also studied using thin film dialysis, which is much faster than equilibrium dialysis and avoids the observed changes in probe-protein interaction that occur over long time periods with the latter system.     

Advancing structural biology through breakthroughs in AI

The past century has witnessed an exponential increase in our atomic-level understanding of molecular and cellular mechanisms from a structural perspective, with multiple landmark achievements contributing to the field. This, coupled with recent and continuing breakthroughs in artificial intelligence methods such as AlphaFold2, and enhanced computational power, is enabling our understanding of protein structure and function at unprecedented levels of accuracy and predictivity. Here, we describe some of the major recent advances across these fields, and describe, as these technologies coalesce, the potential to utilise our enhanced knowledge of intricate cellular and molecular systems to discover novel therapeutics to alleviate human suffering.     

Insemination factors related to timed AI in cattle

Six-day-old bovine ova/embryos were recovered non-surgically and used as biomonitors to evaluate time of artificial insemination. These embryos/ova provided information regarding fertilization status and embryo quality, as well as quantitative and qualitative data regarding associated accessory sperm. Both sperm access to the ovum (addressed by accessory sperm) and fertilization status/embryo quality were important in addressing pregnancy rate for specific intervals from the onset of estrus to insemination. Based on these biomonitors, early insemination failed to achieve optimum pregnancy rate due to inadequate access of sperm to the ovum (i.e., low fertilization rate, manifested by low accessory sperm numbers). However, embryo quality was high in early inseminations, which favors pregnancy. Late insemination failed to achieve optimum pregnancy rate (due to reduced embryo quality), however, sperm access to the ovum was highest. Thus, the selection of an insemination time to achieve optimum pregnancy rate appeared to be a compromise between the two extreme intervals. For timed-AI programs, consideration of the time of ovulation (and its variability) becomes important, in addition to conventional considerations, such as semen handling, site of insemination, and bull selection.     

Use of a five-day progesterone-based timed AI protocol to determine if flunixin meglumine improves pregnancy per timed AI in dairy heifers

Two experiments were conducted to test the hypothesis that the 5 d Co-Synch + CIDR (Controlled Internal Drug Release insert containing progesterone) protocol could be applied as an efficient timed AI (TAI) protocol in dairy heifers, and that treatment with flunixin meglumine (FM) during the period of CL maintenance would increase pregnancy per TAI (P/TAI) and late survival of embryos. Objectives were: 1) in Experiment 1, to compare P/TAI with the 5 d Co-Synch + CIDR protocol to a PGF_2α/GnRH protocol; and 2) in Experiment 2, to determine if FM administered 15.5 and 16 d after first TAI would increase P/TAI, using the 5 d Co-Synch + CIDR protocol with a new or previously used (5 d) CIDR insert.In Experiment 1, 248 heifers were assigned randomly to either the PGF_2α/GnRH protocol (n = 120) or the 5 d Co-Synch + CIDR protocol (n = 128). Pregnancy per TAI did not differ between the 5 d Co-Synch + CIDR protocol (53.1%) and the PGF_2α/GnRH protocol (45.8%; P = 0.22). In Experiment 2, 325 heifers synchronized with the 5 d Co-Synch + CIDR protocol were assigned randomly to receive two injections of FM (FM group; n = 158) at 15.5 and 16 d after TAI, or to remain as untreated controls (n = 165). Pregnancy per TAI in Experiment 2 was 59.4 and 59.5% at 45 d for control and FM groups, respectively, with no differences between groups (P = 0.83). The 5 d Co-Synch + CIDR protocol resulted in an acceptable P/TAI in dairy heifers. However, FM did not improve P/TAI in dairy heifers.     

Procurement,commissioning and QA of AI based solutions: An MPE’s perspective on introducing AI in clinical practice

PurposeIn this study, we propose a framework to help the MPE take up a unique and important role at the introduction of AI solutions in clinical practice, and more in particular at procurement, acceptance, commissioning and QA.Material and methodsThe steps for the introduction of Medical Radiological Equipment in a hospital setting were extrapolated to AI tools. Literature review and in-house experience was added to prepare similar, yet dedicated test methods.ResultsProcurement starts from the clinical cases to be solved and is usually a complex process with many stakeholders and possibly many candidate AI solutions. Specific KPIs and metrics need to be defined. Acceptance testing follows, to verify the installation and test for critical exams. Commissioning should test the suitability of the AI tool for the intended use in the local institution. Results may be predicted from peer reviewed papers that treat representative populations. If not available, local data sets can be prepared to assess the KPIs, or ‘virtual clinical trials’ could be used to create large, simulated test data sets. Quality assurance must be performed periodically to verify if KPIs are stable, especially if the software is upscaled or upgraded, and as soon as self-learning AI tools would enter the medical practice.DiscussionMPEs are well placed to bridge between manufacturer and medical team and help from procurement up to reporting to the management board. More work is needed to establish consolidated test protocols.