Autoinhibited Protein Database: a curated database of autoinhibitory domains and their autoinhibition mechanisms.

Autoinhibition, a crucial allosteric self-regulation mechanism in cell signaling, ensures signal propagation exclusively in the presence of specific molecular inputs. The heightened focus on autoinhibited proteins stems from their implication in human diseases, positioning them as potential causal factors or therapeutic targets. However, the absence of a comprehensive knowledgebase impedes a thorough understanding of their roles and applications in drug discovery. Addressing this gap, we introduce Autoinhibited Protein Database (AiPD), a curated database standardizing information on autoinhibited proteins. AiPD encompasses details on autoinhibitory domains (AIDs), their targets, regulatory mechanisms, experimental validation methods, and implications in diseases, including associated mutations and post-translational modifications. AiPD comprises 698 AIDs from 532 experimentally characterized autoinhibited proteins and 2695 AIDs from their 2096 homologs, which were retrieved from 864 published articles. AiPD also includes 42 520 AIDs of computationally predicted autoinhibited proteins. In addition, AiPD facilitates users in investigating potential AIDs within a query sequence through comparisons with documented autoinhibited proteins. As the inaugural autoinhibited protein repository, AiPD significantly aids researchers studying autoinhibition mechanisms and their alterations in human diseases. It is equally valuable for developing computational models, analyzing allosteric protein regulation, predicting new drug targets, and understanding intervention mechanisms AiPD serves as a valuable resource for diverse researchers, contributing to the understanding and manipulation of autoinhibition in cellular processes. Database URL: http://ssbio.cau.ac.kr/databases/AiPD.

Analysis methods for the gut microbiome in neuropsychiatric and neurodegenerative disorders.

For a long time, the central nervous system was believed to be the only regulator of cognitive functions. However, accumulating evidence suggests that the composition of the microbiome is strongly associated with brain functions and diseases. Indeed, the gut microbiome is involved in neuropsychiatric diseases (e.g., depression, autism spectrum disorder, and anxiety) and neurodegenerative diseases (e.g., Parkinson's disease and Alzheimer's disease). In this review, we provide an overview of the link between the gut microbiome and neuropsychiatric or neurodegenerative disorders. We also introduce analytical methods used to assess the connection between the gut microbiome and the brain. The limitations of the methods used at present are also discussed. The accurate translation of the microbiome information to brain disorder could promote better understanding of neuronal diseases and aid in finding alternative and novel therapies.

A Novel Vitronectin Peptide Facilitates Differentiation of Oligodendrocytes from Human Pluripotent Stem Cells (Synthetic ECM for Oligodendrocyte Differentiation).

Differentiation of oligodendrocytes (ODs) presents a challenge in regenerative medicine due to their role in various neurological diseases associated with dysmyelination and demyelination. Here, we designed a peptide derived from vitronectin (VN) using in silico docking simulation and examined its use as a synthetic substrate to support the differentiation of ODs derived from human pluripotent stem cells. The designed peptide, named VNP2, promoted OD differentiation induced by the overexpression of SOX10 in OD precursor cells compared with Matrigel and full-length VN. ODs differentiated on VNP2 exhibited greater contact with axon-mimicking nanofibers than those differentiated on Matrigel. Transcriptomic analysis revealed that the genes associated with morphogenesis, cytoskeleton remodeling, and OD differentiation were upregulated in cells grown on VNP2 compared with cells grown on Matrigel. This new synthetic VN-derived peptide can be used to develop a culture environment for efficient OD differentiation.