Conformational Dynamics and Protein Allostery: Molecular Simulations, Network Modeling and Machine Learning Approaches
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Biophysics".
Deadline for manuscript submissions: 31 August 2024 | Viewed by 1979
Special Issue Editor
Interests: computational biology; structural bioinformatics; computational virology; computational systems biology; theoretical and computational approaches for studies of protein dynamics; mechanisms of allosteric regulation; network modeling of biomolecular systems; machine learning; allosteric drug discovery and engineering of allosteric functions; AI and machine learning approaches for exploring allosteric landscapes and drug design
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The fundamental biological importance and complexity of allosterically regulated proteins stems from their central role in signal transduction and a variety of cellular processes. Although significance of allosteric phenomenon for biology has been recognized for a long time, the molecular mechanisms of protein allostery remain elusive due to a complex interplay of thermodynamic and dynamic changes that are difficult to observe and simulate. The quantitative elucidation of these highly dynamic processes require a multi-faceted platform of innovative computational and experimental approaches that can dissect fundamental principles of allosteric regulation and advance atomistic characterization of allosteric states, interactions and mechanisms. This Special Issue will cover recent computational and experimental advances in studies of conformational dynamics and protein allostery, and mechanisms of allosteric regulation. The Special Issue will a involve a broad range of methodological and applicational topics including multiscale simulation approaches and AI-augmented enhanced sampling methods for exploring protein conformational dynamics and allostery; dynamic network methods for atomistic modeling of protein allostery, computational and experimental approaches for detection of allosteric states, interactions, communications and allosteric regulatory hotspots; integration of computational approaches with NMR methods for interrogation of allosteric protein functions and identification of functional allosteric networks; high-throughput deep mutational scanning of allosteric protein functions; applications of Alpha-fold structural prediction methods for studies of protein dynamics and allostery; new frontiers in integrating machine learning and enhanced sampling techniques for characterization of allostery; and recent advances in structural biology approaches for studies of allosteric systems; allostery and the function of molecular machines and protein complexes; directed evolution and engineering of allostery employing enhanced sampling, Markov state models and machine learning. This Special Issue will explore the most recent advances in elucidating the molecular mechanisms underlying allostery as well as a broad range of applications involving molecular systems.
Prof. Dr. Gennady Verkhivker
Guest Editor
Manuscript Submission Information
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Keywords
- protein structure
- conformational dynamics
- modeling of protein allostery
- allosteric regulation
- allosteric protein landscapes
- network biology
- enhanced sampling approaches
- AI-augmented protein modeling
- Markov state models
- machine learning and protein dynamics
- structural characterization of allosteric systems with cryo-EM, NMR, smFRET
- integrative biophysical approaches and allostery
- allosteric drug discovery
