Situating the Phosphonated Calixarene–Cytochrome C Association by Molecular Dynamics Simulations. DOI Creative Commons
Alessio Bartocci, Élise Dumont

Published: Nov. 7, 2023

Protein-calixarenes binding plays an increasing, central role in many applications, spanning from molecular recognition to drug delivery strategies and protein inhibition. These ligands obey a specific bio-supramolecular chemistry, which can be revealed by computational ap- proaches such as dynamics simulations. In this paper, we rely on all-atom, explicit- solvent simulations capture the electrostatically-driven association of phosphonated calix-[4]-arene with cytochome-C, critically relies surface-exposed paired lysines. Beyond two sites identified direct agreement X-ray struc- ture, has larger structural impact dynamics. Our simulations, then, allow comparison analogous calixarenes, namely sulfonato, similarly re- ported “molecular glue”. work contribute robust silico predictive tool assess for any given interest crystallization, specificity macromolecular cage whose endo/exo orientation binding.

Language: Английский

Pragmatic Coarse-Graining of Proteins: Models and Applications DOI
Luís Borges-Araújo, Ilias Patmanidis, Akhil Pratap Singh

et al.

Journal of Chemical Theory and Computation, Journal Year: 2023, Volume and Issue: 19(20), P. 7112 - 7135

Published: Oct. 3, 2023

The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role field. However, biological processes involving large-scale protein assemblies or long time scale dynamics still computationally expensive study atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide overview what call pragmatic CG models, which strategies combining, at least part, physics-based implementation top-down approach their parametrization. particular, focus on most residues represented two beads, allowing retain some degree chemical specificity. A description main modern is provided, including review recent applications outlook future perspectives

Language: Английский

Citations

48
Martini3-IDP: improved Martini 3 force field for disordered proteins DOI Creative Commons
Liguo Wang, Christopher Brasnett, Luís Borges-Araújo

et al.

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: March 24, 2025

Coarse-grained (CG) molecular dynamics (MD) is widely used for the efficient simulation of intrinsically disordered proteins (IDPs). The Martini model, one most popular CG force fields in biomolecular simulation, was reported to yield too compact IDP conformations, limiting its applications. Addressing this, we optimized bonded parameters based on fitting reference simulations a diverse set IDPs at atomistic resolution, resulting Martini3-based protein model coined Martini3-IDP. This leads expanded greatly improving reproduction experimentally measured radii gyration. Moreover, contrary ad-hoc fixes scaling protein-protein or protein-water interactions, Martini3-IDP keeps overall interaction balance underlying 3. To validate that, perform comprehensive testing including full-length multidomain proteins, IDP-lipid membrane binding and IDP-small molecule binding, confirming ability successfully capture complex interplay between components. Finally, recently emerging concept condensate, through liquid-liquid phase separation, also reproduced by number both homotypic heterotypic systems. With improved expand simulate processes involving environments, spatio-temporal scales inaccessible with all-atom models. Here, authors introduce Martini3-IDP, refined that addresses prior over-compact structures. Validated across systems, it captures interactions condensates.

Language: Английский

Citations

3
Effective Molecular Dynamics from Neural Network-Based Structure Prediction Models DOI Creative Commons
Alexander Jussupow, Ville R. I. Kaila

Journal of Chemical Theory and Computation, Journal Year: 2023, Volume and Issue: 19(7), P. 1965 - 1975

Published: March 24, 2023

Recent breakthroughs in neural network-based structure prediction methods, such as AlphaFold2 and RoseTTAFold, have dramatically improved the quality of computational protein prediction. These models also provide statistical confidence scores that can estimate uncertainties predicted structures, but it remains unclear to what extent these are related intrinsic conformational dynamics proteins. Here, we compare with explicit large-scale molecular simulations 28 one- two-domain proteins varying degrees flexibility. We demonstrate a strong correlation between motion derived from extensive atomistic further derive an elastic network model based on AlphFold2 (AF-ENM), which benchmark combination coarse-grained simulations. show our AF-ENM method reproduces global accuracy, providing powerful way effective using models.

Language: Английский

Citations

23
Assessing the Martini 3 protein model: A review of its path and potential DOI
Luís Borges-Araújo, Gilberto P. Pereira, Mariana Valério

et al.

Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics, Journal Year: 2024, Volume and Issue: 1872(4), P. 141014 - 141014

Published: April 25, 2024

Language: Английский

Citations

11
Alchemical Transformations and Beyond: Recent Advances and Real-World Applications of Free Energy Calculations in Drug Discovery DOI

Runtong Qian,

Jing Xue,

You Xu

et al.

Journal of Chemical Information and Modeling, Journal Year: 2024, Volume and Issue: 64(19), P. 7214 - 7237

Published: Oct. 3, 2024

Computational methods constitute efficient strategies for screening and optimizing potential drug molecules. A critical factor in this process is the binding affinity between candidate molecules targets, quantified as free energy. Among various estimation methods, alchemical transformation stand out their theoretical rigor. Despite challenges force field accuracy sampling efficiency, advancements algorithms, software, hardware have increased application of energy perturbation (FEP) calculations pharmaceutical industry. Here, we review practical applications FEP discovery projects since 2018, covering both ligand-centric residue-centric transformations. We show that relative steadily achieved chemical real-world applications. In addition, discuss alternative physics-based simulation incorporation deep learning into calculations.

Language: Английский

Citations

8
Revolutionizing Molecular Design for Innovative Therapeutic Applications through Artificial Intelligence DOI Creative Commons

Ahrum Son,

Jongham Park, Woojin Kim

et al.

Molecules, Journal Year: 2024, Volume and Issue: 29(19), P. 4626 - 4626

Published: Sept. 29, 2024

The field of computational protein engineering has been transformed by recent advancements in machine learning, artificial intelligence, and molecular modeling, enabling the design proteins with unprecedented precision functionality. Computational methods now play a crucial role enhancing stability, activity, specificity for diverse applications biotechnology medicine. Techniques such as deep reinforcement transfer learning have dramatically improved structure prediction, optimization binding affinities, enzyme design. These innovations streamlined process allowing rapid generation targeted libraries, reducing experimental sampling, rational tailored properties. Furthermore, integration approaches high-throughput techniques facilitated development multifunctional novel therapeutics. However, challenges remain bridging gap between predictions validation addressing ethical concerns related to AI-driven This review provides comprehensive overview current state future directions engineering, emphasizing their transformative potential creating next-generation biologics advancing synthetic biology.

Language: Английский

Citations

6
Identification of inhibitors targeting the energy-coupling factor (ECF) transporters DOI Creative Commons
Eleonora Diamanti, Paulo C. T. Souza, Inda Setyawati

et al.

Communications Biology, Journal Year: 2023, Volume and Issue: 6(1)

Published: Nov. 20, 2023

Abstract The energy-coupling factor (ECF) transporters are a family of transmembrane proteins involved in the uptake vitamins wide range bacteria. Inhibition activity these could reduce viability pathogens that depend on vitamin uptake. central role transport metabolism bacteria and absence from humans make ECF an attractive target for inhibition with selective chemical probes. Here, we report identification promising class inhibitors transporters. We used coarse-grained molecular dynamics simulations Lactobacillus delbrueckii ECF-FolT2 ECF-PanT to profile binding mode mechanism this novel chemotype. results corroborate postulated pave way further drug-discovery efforts.

Language: Английский

Citations

11
Bartender: Martini 3 Bonded Terms via Quantum Mechanics-Based Molecular Dynamics DOI
Gilberto P. Pereira, Riccardo Alessandri, Moisés Domínguez

et al.

Journal of Chemical Theory and Computation, Journal Year: 2024, Volume and Issue: 20(13), P. 5763 - 5773

Published: June 26, 2024

Coarse-grained (CG) molecular dynamics (MD) simulations have grown in applicability over the years. The recently released version of Martini CG force field (Martini 3) has been successfully applied to simulate many processes, including protein–ligand binding. However, current ligand parametrization scheme is manual and requires an a priori reference all-atom (AA) simulation for benchmarking. For systems with suboptimal AA parameters, which are often unknown, this translates into model that does not reproduce true dynamical behavior underlying molecule. Here, we present Bartender, quantum mechanics (QM)/MD-based tool written Go. Bartender harnesses power QM produces reasonable bonded terms 3 models small molecules efficient user-friendly manner. small, ring-like molecules, generates whose properties indistinguishable from human-made models. more complex, drug-like ligands, it able fit functional forms beyond simple harmonic dihedrals thus better captures their behavior. both increase efficiency accuracy 3-based high-throughput applications by producing numerically stable physically realistic

Language: Английский

Citations

4
Alchemical Free Energy Calculations on Membrane-Associated Proteins DOI Creative Commons
Michail Papadourakis, Hryhory Sinenka, Pierre Matricon

et al.

Journal of Chemical Theory and Computation, Journal Year: 2023, Volume and Issue: 19(21), P. 7437 - 7458

Published: Oct. 30, 2023

Membrane proteins have diverse functions within cells and are well-established drug targets. The advances in membrane protein structural biology revealed lipid binding sites on proteins, while computational methods such as molecular simulations can resolve the thermodynamic basis of these interactions. Particularly, alchemical free energy calculations shown promise calculation reliable reproducible energies protein-ligand protein-lipid complexes membrane-associated systems. In this review, we present an overview representative studies G-protein-coupled receptors, ion channels, transporters well interactions, with emphasis best practices critical aspects running simulations. Additionally, analyze challenges successes when proteins. Finally, highlight value discovery their applicability pharmaceutical industry.

Language: Английский

Citations

11
Computational advances in discovering cryptic pockets for drug discovery DOI Creative Commons
Martijn P. Bemelmans, Zoe Cournia, Kelly L. Damm‐Ganamet

et al.

Current Opinion in Structural Biology, Journal Year: 2025, Volume and Issue: 90, P. 102975 - 102975

Published: Jan. 7, 2025

Language: Английский

Citations

0