Biology subjects

Mican, J.

Publications and source records attributed to Mican, J..

4 recordsLinked to original sources

bioRxiv2026

ProtXAI: Explainable AI Reveals Structural Determinants of Protein Dynamics

Molecular dynamics simulations provide atomistic views of protein motions, but conventional analyses often struggle with extracting subtle mechanistic insights from complex trajectories. Here, we present an integrated framework, ProtXAI, combining molecular dynamics and explainable artificial intelligence (XAI), to identify residue-level determinants of conformational change across diverse protein systems. By leveraging inter-residue distance dynamics, deep learning, and sequential relevance propagation, the approach captures both local fluctuations and long-range communication pathways within protein structures. We applied this framework to three mechanistically distinct systems: apolipoprotein E4 (ApoE4), staphylokinase (SAK) variants, and an ancestral luciferase. Across these applications, our XAI-based approach recovered experimentally supported dynamic hotspots: ligand-responsive hinges in ApoE4, mutation-dependent flexibility shifts in SAK, and evolutionary redistribution of motions in the luciferase. ProtXAI also revealed additional long-range couplings not accessible to classical analysis. Together, these findings demonstrate that combining molecular dynamics with XAI provides a general and scalable strategy for dissecting protein dynamics and uncovering structural determinants of function, stability, and evolutionary changes without prior bias. This approach thus advances the current methodological repertoire for analysing proteins and their intrinsic properties. HighlightsMolecular dynamics simulations are increasingly accessible, yet scalable tools for comparative analysis remain limited. We demonstrate that machine learning coupled with explainable AI can automatically extract structural determinants of protein dynamics from trajectories. ProtXAI identifies key dynamic regions across diverse scenarios, including comparison of protein variants, understanding ligand modulation, and single-trajectory analysis. ProtXAI enables scalable, unbiased interpretation of long trajectories, providing an alternative to manual, time-intensive analysis.

bioinformatics↗

bioRxiv2026

Investigating the Conformational Flexibility of Staphylokinase Across Multiple Time Scales

Cardiovascular diseases, including ischemic stroke, necessitate improved thrombolytic agents. A microbe-encoded plasminogen activator staphylokinase (SAK) is a promising alternative to the widely used tissue plasminogen activator (tPA) due to its high fibrin specificity and low production cost. To overcome potential immunogenicity hampering its use in clinical settings, the low-immunogenic variants SAK SY155 and SAK THR174 were previously engineered. However, the molecular basis underlying their reduced immunogenicity is not understood and requires detailed elucidation. Here, we determine molecular structures and compare flexibility between low-immunogenic and immunogenic SAK variants, using a combination of experimental and computational structural techniques. Our analyses show that all variants share the canonical SAK fold and retain similar plasminogen activation kinetics, despite the number of introduced substitutions. Crucially, the low-immunogenic variants exhibit distinct flexibility profiles, with SAK THR174 showing substantially increased flexibility in the H1 helix and B3 region. SAK SY155 exhibits an increased flexibility in the H1-B3 loop and propensity to homodimerize. These flexibility changes are found in the known immunogenic epitopes. Our multi-scale flexibility analysis provides the molecular explanation for the reduced immunogenicity, altered thermostability, and retained fibrinolytic function of the engineered variants. This information is critical for the design of next-generation thrombolytics.

biochemistry↗

bioRxiv2026

Fibrin Selective Alteplase with Improved Thrombolysis and Inhibition Resistance Engineered by Rational Design

Thrombolytic enzymes represent an important class of proteolytic biocatalysts for medical applications, yet currently used FDA-approved variants, including alteplase and tenecteplase, remain limited by suboptimal catalytic efficiency, off-target activity, and susceptibility to inhibition. These limitations reflect the complexity of enzyme function in physiological environments, where therapeutic performance depends on the simultaneous optimization of multiple catalytic and biophysical properties. Here, we introduce a multi-objective enzyme engineering strategy for the design of next-generation thrombolytic proteases, explicitly targeting multiple properties required for therapeutic performance. Our approach combines computer-aided design, evolutionary reconstruction, and literature-guided mutation selection to improve catalytic activity, fibrin selectivity, inhibition resistance, and functional lifetime within a single workflow. This framework is coupled with systematic biochemical characterization, in vitro evaluation of clot penetration and fibrinolytic activity, and in vivo validation of efficacy and safety. By addressing multiple performance parameters simultaneously, this strategy enables efficient navigation of trade-offs that typically limit enzyme optimization. Using this approach, we identify Brnoteplase as a lead variant with enhanced fibrin selectivity, improved resistance to inhibition, and superior clot penetration, resulting in increased effective catalytic lifetime and enabling bolus administration. In vivo studies demonstrate enhanced thrombolysis and recanalization with reduced hemorrhagic complications. These findings provide a broadly applicable framework for designing proteolytic biocatalysts suitable for complex biological environments.

biochemistry↗

bioRxiv2026

Biochemical and Immunological Properties of Engineered Low-Immunogenic Staphylokinases for Next-Generation Thrombolytic Therapy

Staphylokinase (SAK) is a highly fibrin-specific plasminogen activator with significant potential as a safe and affordable thrombolytic. Yet, its clinical translation can be limited by potential immunogenicity. To accelerate the development of improved thrombolytics, a critical step is identifying the most suitable molecular template. Therefore, we performed a comparative analysis of biochemical and immunological properties of three engineered low-immunogenic variants (SAK SY155, SAK THR174, and SAK STAR FRIDA) and two wild-types (SAK STAR and SAK 42D), using a newly established panel of assays. All variants retained potent thrombolytic activity, with SAK SY155 displaying the highest catalytic efficiency and fibrin-clot permeability. However, this advantage did not fully translate into improved clot reduction under flow conditions. Comprehensive immunological profiling, including T lymphocyte proliferation, dendritic cell maturation, mouse immunization models, and human serum reactivity tests, confirmed decreased immunogenicity for two low-immunogenic variants. Overall, low-immunogenic SAK SY155 emerged as the most promising template for rational engineering of next-generation thrombolytics.

biochemistry↗