Reconstruction of ARNT PAS-B Unfolding Pathways by Steered Molecular Dynamics and Artificial Neural Networks

Insights into the Dissociation Process and Binding Pattern of the BRCT7/8-PHF8 Complex

DNA topoisomerase 2-binding protein 1 (Topbp1) plays a crucial role in activating the ataxia-telangiectasia mutated and rad3-related (ATR) complex to initiate DNA damage repair responses. For this process to occur, it is necessary for PHF8 to dissociate from Topbp1. Topbp1 binds to the acidic patch sequence (APS) of PHF8 through its C-terminal BRCT7/8 domain, and disrupting this interaction could be a promising strategy for cancer treatment. To investigate the dissociation process and binding pattern of BRCT7/8-PHF8, we employed enhanced sampling techniques, such as steered molecular dynamics (SMD) simulations and accelerated molecular dynamics (aMD) simulations, along with self-organizing maps (SOM) and time-resolved force distribution analysis (TRFDA) methodologies. Our results demonstrate that the dissociation of PHF8 from BRCT7/8 starts from the N-terminus, leading to the unfolding of the N-terminal helix. Additionally, we identified critical residues that play a pivotal role in this dissociation process. These findings provide valuable insights into the disassociation of PHF8 from BRCT7/8, which could potentially guide the development of novel drugs targeting Topbp1 for cancer therapy.

Crystal structure of archaeal IF5A-DHS complex reveals insights into the hypusination mechanism

The translation factor IF5A is highly conserved in Eukarya and Archaea and undergoes a unique post-translational hypusine modification by the deoxyhypusine synthase (DHS) enzyme. DHS transfers the butylamine moiety from spermidine to IF5A using NAD as a cofactor, forming a deoxyhypusine intermediate. IF5A is a key player in protein synthesis, preventing ribosome stalling in proline-rich sequences during translation elongation and facilitating translation elongation and termination. Additionally, human eIF5A participates in various essential cellular processes and contributes to cancer metastasis, with inhibiting hypusination showing anti-proliferative effects. The hypusination pathway of IF5A is therefore an attractive new therapeutic target. We elucidated the 2.0 Å X-ray crystal structure of the archaeal DHS-IF5A complex, revealing hetero-octameric architecture and providing a detailed view of the complex active site including the hypusination loop. This structure, along with biophysical data and molecular dynamics simulations, provides new insights into the catalytic mechanism of the hypusination reaction.

Mechanism of RGD-conjugated nanodevice binding to its target protein integrin αVβ3 by atomistic molecular dynamics and machine learning

Active targeting strategies have been proposed to enhance the selective uptake of nanoparticles (NPs) by diseased cells, and recent experimental findings have proven the effectiveness of this approach. However, no mechanistic studies have yet revealed the atomistic details of the interactions between ligand-activated NPs and integrins. As a case study, here we investigate, by means of advanced molecular dynamics simulations (MD) and machine learning methods (namely equilibrium MD, binding free energy calculations and training of self-organized maps), the interaction of a cyclic-RGD-conjugated PEGylated TiO2 NP (the nanodevice) with the extracellular segment of integrin αVβ3 (the target), the latter experimentally well-known to be over-expressed in several solid tumors. Firstly, we proved that the cyclic-RGD ligand binding to the integrin pocket is established and kept stable even in the presence of the cumbersome realistic model of the nanodevice. In this respect, the unsupervised machine learning analysis allowed a detailed comparison of the ligand/integrin binding in the presence and in the absence of the nanodevice, which unveiled differences in the chemical features. Then, we discovered that unbound cyclic RGDs conjugated to the NP largely contribute to the interactions between the nanodevice and the integrin. Finally, by increasing the density of cyclic RGDs on the PEGylated TiO2 NP, we observed a proportional enhancement of the nanodevice/target binding. All these findings can be exploited to achieve an improved targeting selectivity and cellular uptake, and thus a more successful clinical outcome.

Multimerization of HIF enhances transcription of target genes containing the hypoxia ancillary sequence

Transcriptional activity of the hypoxia inducible factor (HIF) relies on the formation of a heterodimer composed of an oxygen-regulated α-subunit and a stably expressed β-subunit. Heterodimeric HIF activates expression by binding to RCGTG motifs within promoters of hypoxia-activated genes. Some hypoxia targets also possess an adjacent HIF ancillary sequence (HAS) reported to increase transcription but whose function remains obscure. Here, we investigate the contribution of the HAS element to the hypoxia response and its mechanism of action, using the HAS-containing prolyl 4-hydroxylase subunit α1 (P4HA1) as a gene model in NIH/3T3 mouse embryonic fibroblasts and HEK293 human embryonic kidney cells. Our HIF overexpression experiments demonstrate that the HAS motif is essential for full induction by hypoxia and that the presence of the tandem HAS/HIF, as opposed to HIF-only sequences, provides HIF proteins with the capacity to form complexes of stoichiometry beyond the classical heterodimer, likely tetramers, to cooperatively potentiate hypoxia-induced transcription. We also provide evidence of the crucial role played by the Fα helix of the PAS-B domain of the HIF1β subunit to support the interaction between heterodimers. Functional analysis showed that human genes containing the HAS/HIF motifs are better responders to hypoxia, and their promoters are enriched for specific transcription factor binding sites. Gene ontology enrichment revealed a predominance of HAS/HIF in genes primarily related to tissue formation and development. Our findings add an extra level of regulation of the hypoxia/HIF signaling through multimerization of HIF proteins on regulatory elements containing the HAS/HIF motifs.

Molecular Dynamics for the Optimal Design of Functionalized Nanodevices to Target Folate Receptors on Tumor Cells

Atomistic details on the mechanism of targeting activity by biomedical nanodevices of specific receptors are still scarce in the literature, where mostly ligand/receptor pairs are modeled. Here, we use atomistic molecular dynamics (MD) simulations, free energy calculations, and machine learning approaches on the case study of spherical TiO2 nanoparticles (NPs) functionalized with folic acid (FA) as the targeting ligand of the folate receptor (FR). We consider different FA densities on the surface and different anchoring approaches, i.e., direct covalent bonding of FA γ-carboxylate or through polyethylene glycol spacers. By molecular docking, we first identify the lowest energy conformation of one FA inside the FR binding pocket from the X-ray crystal structure, which becomes the starting point of classical MD simulations in a realistic physiological environment. We estimate the binding free energy to be compared with the existing experimental data. Then, we increase complexity and go from the isolated FA to a nanosystem decorated with several FAs. Within the simulation time framework, we confirm the stability of the ligand-receptor interaction, even in the presence of the NP (with or without a spacer), and no significant modification of the protein secondary structure is observed. Our study highlights the crucial role played by the spacer, FA protonation state, and density, which are parameters that can be controlled during the nanodevice preparation step.

Metadynamics simulations for the investigation of drug loading on functionalized inorganic nanoparticles

Inorganic nanoparticles show promising properties that allow them to be efficiently used as drug carriers. The main limitation in this type of application is currently the drug loading capacity, which can be overcome with a proper functionalization of the nanoparticle surface. In this study, we present, for the first time, a computational approach based on metadynamics to estimate the binding free energy of the doxorubicin drug (DOX) to a functionalized TiO₂ nanoparticle under different pH conditions. On a thermodynamic basis, we demonstrate the robustness of our approach to capture the overall mechanism behind the pH-triggered release of DOX due to environmental pH changes. Notably, binding free energy estimations align well with what is expected for a pH-sensitive drug delivery system. Based on our results, we envision the use of metadynamics as a promising computational tool for the rational design and in silico optimization of organic ligands with improved drug carrier properties.

Free energy and kinetic rate calculation via non-equilibrium molecular simulation: application to biomolecules

Non-equilibrium molecular dynamics (NEMD) simulation has been recognized as a powerful tool for examining biomolecules and provides fruitful insights into not only non-equilibrium but also equilibrium processes. We review recent advances in NEMD simulation and relevant, fundamental results of non-equilibrium statistical mechanics. We first introduce Crooks fluctuation theorem and Jarzynski equality that relate free energy difference to work done on a physical system during a non-equilibrium process. The theorems are beneficial for the analysis of NEMD trajectories. We then describe rate theory, a framework to calculate molecular kinetics from a non-equilibrium process; this theoretical framework enables us to calculate a reaction time-mean-first passage time-from NEMD trajectories. We, in turn, present recent NEMD techniques that apply an external force to a system to enhance molecular dissociation and introduce their application to biomolecules. Lastly, we show the current status of an appropriate selection of reaction coordinates for NEMD simulation.

Insight into the Initial Stages of the Folding Process in Onconase Revealed by UNRES

The unfolded state of proteins presents many challenges to elucidate the structural basis for biological function. This state is characterized by a large degree of structural heterogeneity which makes it difficult to generate structural models. However, recent experiments into the initial folding events of the 104-residue ribonuclease homologue onconase (ONC) were able to identify the regions in the protein that participate in the initial folding of this protein. Therefore, to gain additional structural insight into the unfolded state of proteins, this study utilized molecular dynamics simulations using the UNited-RESidue (UNRES) force field to evaluate whether there is a good agreement between the experimentally determined initial structures and the structures identified by computer simulations along a folding pathway. Indeed, these UNRES simulations accurately identified the two regions experimentally observed to form the initial native structure along the folding pathway of ONC. In addition, these regions are determined to be chain folding initiation sites (CFIS) according to methods developed previously. Subsequent self-organization maps (SOM) analysis has revealed key structural states involved in these early folding events.

Recognizing the Binding Pattern and Dissociation Pathways of the p300 Taz2-p53 TAD2 Complex

The dynamic association and dissociation between proteins are the basis of cellular signal transduction. This process becomes much more complicated if one or both interaction partners are intrinsically disordered because intrinsically disordered proteins can undergo disorder-to-order transitions upon binding to their partners. p53, a transcription factor with disordered regions, plays significant roles in many cellular signaling pathways. It is critical to understand the binding/unbinding mechanism involving these disordered regions of p53 at the residue level to reveal how p53 performs its biological functions. Here, we studied the dissociation process of the intrinsically disordered N-terminal transactivation domain 2 (TAD2) of p53 and the transcriptional adaptor zinc-binding 2 (Taz2) domain of transcriptional coactivator p300 using a combination of classical molecular dynamics, steered molecular dynamics, self-organizing maps, and time-resolved force distribution analysis (TRFDA). We observed two different dissociation pathways with different probabilities. One dissociation pathway starts from the TAD2 N-terminus and propagates to the α-helix and finally the C-terminus. The other dissociation pathway is in the opposite order. Subsequent TRFDA results reveal that key residues in TAD2 play critical roles. Besides the residues in agreement with previous experimental results, we also highlighted some other residues that play important roles in the disassociation process. In the dissociation process, non-native interactions were formed to partially compensate for the energy loss due to the breaking of surrounding native interactions. Moreover, our statistical analysis results of other experimentally determined complex structures involving either Taz2 or TAD2 suggest that the binding of the Taz2-TAD2 complex is mainly governed by the binding site of Taz2, which includes three main binding regions. Therefore, the complexes involving Taz2 may follow similar binding/unbinding behaviors, which could be studied together to generate common principles.

Design and Implementation of a Multidimensional Visualization Reconstruction System for Old Urban Spaces Based on Neural Networks

This article presents an in-depth study and analysis of the construction of a convolutional neural network model and multidimensional visualization system of old urban space and proposes the design of a multifaceted visualization reconstruction system of old urban space based on a neural network. It also quantitatively analyzes the essential spatial attribute characteristics of urban shadow areas as nodes of the overall urban dynamic network in three dimensions—spatial connection strength, spatial connection distance, and spatial connection direction—summarizes the characteristics of urban old spatial structure from the perspective of a dynamic network, and then proposes the model of urban old spatial design from the perspective of an active network. The shallow depth of the network structure is used to reduce the parameters in the learning process of reconfigurable convolutional neural networks using data sets so that the model learns more general features. For the situation where the number of data sets is small, data augmentation is used to expand the size of the data sets and improve the recognition accuracy of the reconfigurable convolutional neural network. A real-time update method of multifaceted data visualization for big data scenarios is proposed and implemented to reduce the network load and network latency caused by charts of multidimensional data changes, reduce the data error rate, and maintain the system stability in the old urban space concurrency scenario.

PathDetect-SOM: A Neural Network Approach for the Identification of Pathways in Ligand Binding Simulations

Understanding the process of ligand–protein recognition is important to unveil biological mechanisms and to guide drug discovery and design. Enhanced-sampling molecular dynamics is now routinely used to simulate the ligand binding process, resulting in the need for suitable tools for the analysis of large data sets of binding events. Here, we designed, implemented, and tested PathDetect-SOM, a tool based on self-organizing maps to build concise visual models of the ligand binding pathways sampled along single simulations or replicas. The tool performs a geometric clustering of the trajectories and traces the pathways over an easily interpretable 2D map and, using an approximate transition matrix, it can build a graph model of concurrent pathways. The tool was tested on three study cases representing different types of problems and simulation techniques. A clear reconstruction of the sampled pathways was derived in all cases, and useful information on the energetic features of the processes was recovered. The tool is available at https://github.com/MottaStefano/PathDetect-SOM.