Prediction of Protein Allosteric Signalling Pathways and Functional Residues Through Paths of Optimised Propensity

Synthetic Biology for Designing Allostery and its Potential Biomedical Applications

Allosteric regulation of protein function, where a perturbation at one site induces a conformational shift or alters dynamics at a distal functional site, plays a key role in numerous biological processes. The ability to introduce allostery using synthetic biology principles holds significant potential both for biomedical and biotechnological applications, and for advancing our understanding of natural allostery. By customizing target proteins for sensing specific chemical or physical signals, including ligand binding and environmental cues, we aim to allosterically modulate the function of a target protein depending on the selected triggers. This approach, unlike active-site targeting, offers greater specificity and selectivity and can allosterically couple diverse physiological processes. Synthetic biology strategies have been developed recently for designed allosteric protein regulation, including the design of allosteric modulators such as domain insertion, generation of de novo allosteric protein switches, and application of engineered allosteric mechanisms to control cellular functions. We examine the application of artificial intelligence (AI)-based generative protein design and other important milestones, challenges and opportunities in this field, highlighting how these approaches could be applied for the development of new therapeutic strategies.

Caspase family in autoimmune diseases

Programmed cell death (PCD) plays a crucial role in maintaining tissue homeostasis, with its primary forms including apoptosis, pyroptosis, and necroptosis. The caspase family is central to these processes, and its complex functions across different cell death pathways and other non-cell death roles have been closely linked to the pathogenesis of autoimmune diseases. This article provides a comprehensive review of the role of the caspase family in autoimmune diseases such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes (T1D), and multiple sclerosis (MS). It particularly emphasizes the intricate functions of caspases within various cell death pathways and their potential as therapeutic targets, thereby offering innovative insights and a thorough discussion in this field. In terms of therapy, strategies targeting caspases hold significant promise. We emphasize the importance of a holistic understanding of caspases in the overall concept of cell death, exploring their unique functions and interrelationships across multiple cell death pathways, including apoptosis, pyroptosis, necroptosis, and PANoptosis. This approach transcends the limitations of previous studies that focused on singular cell death pathways. Additionally, caspases play a key role in non-cell death functions, such as immune cell activation, cytokine processing, inflammation regulation, and tissue repair, thereby opening new avenues for the treatment of autoimmune diseases. Regulating caspase activity holds the potential to restore immune balance in autoimmune diseases. Potential therapeutic approaches include small molecule inhibitors (both reversible and irreversible), biological agents (such as monoclonal antibodies), and gene therapies. However, achieving specific modulation of caspases to avoid interference with normal physiological functions remains a major challenge. Future research must delve deeper into the regulatory mechanisms of caspases and their associated complexes linked to PANoptosis to facilitate precision medicine. In summary, this article offers a comprehensive and in-depth analysis, providing a novel perspective on the complex roles of caspases in autoimmune diseases, with the potential to catalyze breakthroughs in understanding disease mechanisms and developing therapeutic strategies.

Allostery

Allostery describes the ability of biological macromolecules to transmit signals spatially through the molecule from an allosteric site – a site that is distinct from orthosteric binding sites of primary, endogenous ligands – to the functional or active site. This review starts with a historical overview and a description of the classical example of allostery – hemoglobin – and other well-known examples (aspartate transcarbamoylase, Lac repressor, kinases, G-protein-coupled receptors, adenosine triphosphate synthase, and chaperonin). We then discuss fringe examples of allostery, including intrinsically disordered proteins and inter-enzyme allostery, and the influence of dynamics, entropy, and conformational ensembles and landscapes on allosteric mechanisms, to capture the essence of the field. Thereafter, we give an overview over central methods for investigating molecular mechanisms, covering experimental techniques as well as simulations and artificial intelligence (AI)-based methods. We conclude with a review of allostery-based drug discovery, with its challenges and opportunities: with the recent advent of AI-based methods, allosteric compounds are set to revolutionize drug discovery and medical treatments.

Dynamical responses predict a distal site that modulates activity in an antibiotic resistance enzyme

β-Lactamases, which hydrolyse β-lactam antibiotics, are key determinants of antibiotic resistance. Predicting the sites and effects of distal mutations in enzymes is challenging. For β-lactamases, the ability to make such predictions would contribute to understanding activity against, and development of, antibiotics and inhibitors to combat resistance. Here, using dynamical non-equilibrium molecular dynamics (D-NEMD) simulations combined with experiments, we demonstrate that intramolecular communication networks differ in three class A SulpHydryl Variant (SHV)-type β-lactamases. Differences in network architecture and correlated motions link to catalytic efficiency and β-lactam substrate spectrum. Further, the simulations identify a distal residue at position 89 in the clinically important Klebsiella pneumoniae carbapenemase 2 (KPC-2), as a participant in similar networks, suggesting that mutation at this position would modulate enzyme activity. Experimental kinetic, biophysical and structural characterisation of the naturally occurring, but previously biochemically uncharacterised, KPC-2G89D mutant with several antibiotics and inhibitors reveals significant changes in hydrolytic spectrum, specifically reducing activity towards carbapenems without effecting major structural or stability changes. These results show that D-NEMD simulations can predict distal sites where mutation affects enzyme activity. This approach could have broad application in understanding enzyme evolution, and in engineering of natural and de novo enzymes.

Dynamically driven correlations in elastic net models reveal sequence of events and causality in proteins

An explicit analytic solution is given for the Langevin equation applied to the Gaussian Network Model of a protein subjected to both a random and a deterministic periodic force. Synchronous and asynchronous components of time correlation functions are derived and an expression for phase differences in the time correlations of residue pairs is obtained. The synchronous component enables the determination of dynamic communities within the protein structure. The asynchronous component reveals causality, where the time correlation function between residues i and j differs depending on whether i is observed before j or vice versa, resulting in directional information flow. Driver and driven residues in the allosteric process of cyclophilin A and human NAD-dependent isocitrate dehydrogenase are determined by a perturbation-scanning technique. Factors affecting phase differences between fluctuations of residues, such as network topology, connectivity, and residue centrality, are identified. Within the constraints of the isotropic Gaussian Network Model, our results show that asynchronicity increases with viscosity and distance between residues, decreases with increasing connectivity, and decreases with increasing levels of eigenvector centrality.

Allosteric communication and signal transduction in proteins

Allostery is one of the cornerstones of biological function, as it plays a fundamental role in regulating protein activity. The modelling of allostery has gradually moved from a conformation-based framework, linked to structural changes, to dynamics-based allostery, whereby the effects of ligand binding propagate via signal transduction from the allosteric site to other regions of the protein via inter-residue interactions. Characterising such allosteric signalling pathways, which do not necessarily lead to conformational changes, has been pursued experimentally and complemented by computational analysis of protein networks to detect subtle dynamic propagation paths. Considering allostery from the perspective of signal transduction broadens the understanding of allosteric mechanisms, underscores the importance of protein topology, and can provide insights into allosteric drug design.

Allosteric drugs: New principles and design approaches

Focusing on an important biomedical implication of allostery - design of allosteric drugs, we describe characteristics of allosteric sites, effectors, and their modes of actions distinguishing them from the orthosteric counterparts and calling for new principles and protocols in the quests for allosteric drugs. We show the importance of considering both binding affinity and allosteric signaling in establishing the structure-activity relationships (SARs) toward design of allosteric effectors, arguing that pairs of allosteric sites and their effector ligands - the site-effector pairs - should be generated and adjusted simultaneously in the framework of what we call directed design protocol. Key ideas and approaches for designing allosteric effectors including reverse perturbation, targeted and agnostic analysis are also discussed here. Several promising computational approaches are highlighted, along with the need for and potential advantages of utilizing generative models to facilitate discovery/design of new allosteric drugs.