Harnessing Deep Learning Methods for Voltage-Gated Ion Channel Drug Discovery.

Voltage-gated ion channels (VGICs) are pivotal in regulating electrical activity in excitable cells and are critical pharmaceutical targets for treating many diseases including cardiac arrhythmia and neuropathic pain. Despite their significance, challenges such as achieving target selectivity persist in VGIC drug development. Recent progress in deep learning, particularly diffusion models, has enabled the computational design of protein binders for any clinically relevant protein based solely on its structure. These developments coincide with a surge in experimental structural data for VGICs, providing a rich foundation for computational design efforts. This review explores the recent advancements in computational protein design using deep learning and diffusion methods, focusing on their application in designing protein binders to modulate VGIC activity. We discuss the potential use of these methods to computationally design protein binders targeting different regions of VGICs, including the pore domain, voltage-sensing domains, and interface with auxiliary subunits. We provide a comprehensive overview of the different design scenarios, discuss key structural considerations, and address the practical challenges in developing VGIC-targeting protein binders. By exploring these innovative computational methods, we aim to provide a framework for developing novel strategies that could significantly advance VGIC pharmacology and lead to the discovery of effective and safe therapeutics.

Protein stability prediction by fine-tuning a protein language model on a mega-scale dataset.

Protein stability plays a crucial role in a variety of applications, such as food processing, therapeutics, and the identification of pathogenic mutations. Engineering campaigns commonly seek to improve protein stability, and there is a strong interest in streamlining these processes to enable rapid optimization of highly stabilized proteins with fewer iterations. In this work, we explore utilizing a mega-scale dataset to develop a protein language model optimized for stability prediction. ESMtherm is trained on the folding stability of 528k natural and de novo sequences derived from 461 protein domains and can accommodate deletions, insertions, and multiple-point mutations. We show that a protein language model can be fine-tuned to predict folding stability. ESMtherm performs reasonably on small protein domains and generalizes to sequences distal from the training set. Lastly, we discuss our model's limitations compared to other state-of-the-art methods in generalizing to larger protein scaffolds. Our results highlight the need for large-scale stability measurements on a diverse dataset that mirrors the distribution of sequence lengths commonly observed in nature.

Trends in Practice Among Shoulder Specialists in the Management of Frozen Shoulder: A Consensus Survey.

Background: The management of frozen shoulder (FS) differs depending on experience level and variation between scientific guidelines and actual practice. Purpose: To determine the current trends and practices in the management of FS among shoulder specialists and compare them with senior shoulder specialists. Study Design: Consensus statement. Methods: A team of 15 senior shoulder specialists (faculty group) prepared a questionnaire comprising 26 questions regarding the definition, terminology, clinical signs, investigations, management, and prognosis of FS. The questionnaire was mailed to all the registered shoulder specialists of Shoulder and Elbow Society, India (SESI) (specialist group; n = 230), as well as to the faculty group (n = 15). The responses of the 2 groups were compared, and levels of consensus were determined: strong (>75%), broad (60%-74.9%), inconclusive (40%-59.9%), or disagreement (<40%). Result: Overall, 142 of the 230 participants in the specialist group and all 15 participants in the faculty group responded to the survey. Both groups strongly agreed that plain radiographs are required to rule out a secondary cause of FS, routine magnetic resonance imaging is not indicated to confirm FS, nonsteroidal anti-inflammatory drugs should be administered at bedtime, steroid injection (triamcinolone or methylprednisolone) is the next best option if analgesics fail to provide pain relief, passive physical therapy should be avoided in the freezing phase, <10% of patients would require any surgical intervention, and patients with diabetes and thyroid dysfunction tend to fare poorly. There was broad agreement that routine thyroid dysfunction screening is unnecessary for women, a single 40-mg steroid injection via intra-articular route is preferred, and arthroscopic capsular release (ACR) results in a better outcome than manipulation under anesthesia (MUA). Agreement was inconclusive regarding the use of combined random blood sugar (RBS) and glycosylated hemoglobin versus lone RBS to screen for diabetes in patients with FS, preference of ACR versus MUA to treat resistant FS, and the timing of surgical intervention. There was disagreement over the most appropriate term for FS, the preferred physical therapy modality for pain relief, the most important movement restriction for early diagnosis of FS, and complications seen after MUA. Conclusion: This survey summarized the trend in prevalent practices regarding FS among the shoulder specialists and senior shoulder surgeons of SESI.

Analgesia requirements after interscalene block for shoulder arthroscopy: the 5 days following surgery.

INTRODUCTION: Excellent initial post-operative analgesia for patients undergoing arthroscopic shoulder surgery can be provided with a single-shot interscalene brachial plexus block. However there have been concerns that when the block wears off, patients may experience pain and this may occur at home. Some investigators have advocated the use of continuous ambulatory local anaesthetic infusions following hospital discharge. We prospectively studied pain scores, analgesic requirements and satisfaction of patients at home in the first 5 days following arthroscopic shoulder surgery to see whether continuous infusion would be of benefit. RESULTS: Fifteen percent of patients experienced severe pain at some time over the first 3 days, and this percentage decreased to 7% by day 5. However 97% of our patients were satisfied with their post-operative oral analgesia management and less than 5% contacted their GP for further analgesia issues. Over 80% of our patients required only simple analgesics following hospital discharge. CONCLUSION: Post-operative continuous ambulatory local anaesthetic infusions may not be justified following this intermediate magnitude of surgery.

Patellar tendon length after knee arthroplasty with and without preservation of the infrapatellar fat pad.

Our aim was to assess whether there was any significant difference in change in patellar tendon length after knee arthroplasty, when the infrapatellar fat pad was either preserved or excised. Three-year radiographic follow-up was studied on 73 primary knee arthroplasty patients. The infrapatellar fat pad was completely preserved in 38 cases and completely excised in 35. At 3 years there was a significant patellar tendon shortening of 4.2% (P = .0004) in the fat pad excision group and no significant change in the fat pad preservation group (P = .82). The difference between the 2 groups was significant (P = .004). Our results show that patella tendon length does not always shorten after knee arthroplasty and that preservation of the infrapatellar fat pad may be a factor in preventing such shortening.