Similarities and Differences in Ligand Binding to Protein and RNA Targets: The Case of Riboflavin.

It is nowadays clear that RNA molecules can play active roles in several biological processes. As a result, an increasing number of RNAs are gradually being identified as potentially druggable targets. In particular, noncoding RNAs can adopt highly organized conformations that are suitable for drug binding. However, RNAs are still considered challenging targets due to their complex structural dynamics and high charge density. Thus, elucidating relevant features of drug-RNA binding is fundamental for advancing drug discovery. Here, by using Molecular Dynamics simulations, we compare key features of ligand binding to proteins with those observed in RNA. Specifically, we explore similarities and differences in terms of (i) conformational flexibility of the target, (ii) electrostatic contribution to binding free energy, and (iii) water and ligand dynamics. As a test case, we examine binding of the same ligand, namely riboflavin, to protein and RNA targets, specifically the riboflavin (RF) kinase and flavin mononucleotide (FMN) riboswitch. The FMN riboswitch exhibited enhanced fluctuations and explored a wider conformational space, compared to the protein target, underscoring the importance of RNA flexibility in ligand binding. Conversely, a similar electrostatic contribution to the binding free energy of riboflavin was found. Finally, greater stability of water molecules was observed in the FMN riboswitch compared to the RF kinase, possibly due to the different shape and polarity of the pockets.

"A Feeling of Safeness and Freedom": The Promotion of Mental Health Recovery Through Co-Production in an Italian Community Organization.

In mental health promotion, recovery is a process that leads to personal strengthening, control over crucial life decisions, and participation in communities through relevant professional, educational, or family social roles. Co-production, a key aspect of the recovery-oriented approach, emphasizes collaboration and active participation of people with mental health first-hand experience, family members, and citizens. Even though studies on co-production are limited and fragmented, there is evidence that co-production leads to positive outcomes, including improved well-being, empowerment, social connectedness, inclusion, and personal competencies. This study aimed to contribute to the limited literature on co-production in mental health by evaluating the co-production process in a non-profit mental health organization and its impact on empowerment processes and personal recovery outcomes. The research team adopted a collaborative approach and conducted qualitative research, including 13 individual semi-structured interviews and four focus groups. Results showed how the different dimensions of empowerment are promoted in and by the organization: (a) co-production processes supported empowered outcomes on an individual level, such as self-awareness; (b) the organization was perceived to promote empowering processes, such as a sense of safeness and protection; (c) co-production was a mean to build and maintain a network with mental health services that acknowledges the dignity and value of each subjectivity and promotes participation and recovery. Peer support workers were seen as facilitators of mental illness management, and the organization as a place for sharing mental health experiences and fostering individual recovery journeys.

Integrated Approach Including Docking, MD Simulations, and Network Analysis Highlights the Action Mechanism of the Cardiac hERG Activator RPR260243.

hERG is a voltage-gated potassium channel involved in the heart contraction whose defections are associated with the cardiac arrhythmia Long QT Syndrome type 2. The activator RPR260243 (RPR) represents a possible candidate to pharmacologically treat LQTS2 because it enhances the opening of the channel. However, the molecular detail of its action mechanism remains quite elusive. Here, we address the problem using a combination of docking, molecular dynamics simulations, and network analysis. We show that the drug preferably binds at the interface between the voltage sensor and the pore, enhancing the canonical activation path and determining a whole-structure rearrangement of the channel that slightly impairs inactivation.

Ion Conduction Mechanism as a Fingerprint of Potassium Channels.

K+-channels are membrane proteins that regulate the selective conduction of potassium ions across cell membranes. Although the atomic mechanisms of K+ permeation have been extensively investigated, previous work focused on characterizing the selectivity and occupancy of the binding sites, the role of water molecules in the conduction process, or the identification of the minimum energy pathways enabling permeation. Here, we exploit molecular dynamics simulations and the analytical power of Markov state models to perform a comparative study of ion conduction in three distinct channel models. Significant differences emerged in terms of permeation mechanisms and binding site occupancy by potassium ions and/or water molecules from 100 µs cumulative trajectories. We found that, at odds with the current paradigm, each system displays a characteristic permeation mechanism, and thus, there is not a unique way by which potassium ions move through K+-channels. The high functional diversity of K+-channels can be attributed in part to the differences in conduction features that have emerged from this work. This study provides crucial information and further inspiration for wet-lab chemists designing new synthetic strategies to produce versatile artificial ion channels that emulate membrane transport for their applications in diagnosis, sensors, the next generation of water treatment technologies, etc., as the ability of synthetic channels to transport molecular ions across a bilayer in a controlled way is usually governed through the choice of metal ions, their oxidation states, or their coordination geometries.

Targeting the JAK/STAT Pathway: A Combined Ligand- and Target-Based Approach.

Janus kinases (JAKs) are a family of proinflammatory enzymes able to mediate the immune responses and the inflammatory cascade by modulating multiple cytokine expressions as well as various growth factors. In the present study, the inhibition of the JAK-signal transducer and activator of transcription (STAT) signaling pathway is explored as a potential strategy for treating autoimmune and inflammatory disorders. A computationally driven approach aimed at identifying novel JAK inhibitors based on molecular topology, docking, and molecular dynamics simulations was carried out. For the best candidates selected, the inhibitory activity against JAK2 was evaluated in vitro. Two hit compounds with a novel chemical scaffold, 4 (IC50 = 0.81 µM) and 7 (IC50 = 0.64 µM), showed promising results when compared with the reference drug Tofacitinib (IC50 = 0.031 µM).

Kinetics of Drug Binding and Residence Time.

The kinetics of drug binding and unbinding is assuming an increasingly crucial role in the long, costly process of bringing a new medicine to patients. For example, the time a drug spends in contact with its biological target is known as residence time (the inverse of the kinetic constant of the drug-target unbinding, 1/koff). Recent reports suggest that residence time could predict drug efficacy in vivo, perhaps even more effectively than conventional thermodynamic parameters (free energy, enthalpy, entropy). There are many experimental and computational methods for predicting drug-target residence time at an early stage of drug discovery programs. Here, we review and discuss the methodological approaches to estimating drug binding kinetics and residence time. We first introduce the theoretical background of drug binding kinetics from a physicochemical standpoint. We then analyze the recent literature in the field, starting from the experimental methodologies and applications thereof and moving to theoretical and computational approaches to the kinetics of drug binding and unbinding. We acknowledge the central role of molecular dynamics and related methods, which comprise a great number of the computational methods and applications reviewed here. However, we also consider kinetic Monte Carlo. We conclude with the outlook that drug (un)binding kinetics may soon become a go/no go step in the discovery and development of new medicines.

Conduction and Gating Properties of the TRAAK Channel from Molecular Dynamics Simulations with Different Force Fields.

In recent years, the K2P family of potassium channels has been the subject of intense research activity. Owing to the complex function and regulation of this family of ion channels, it is common practice to complement experimental findings with the atomistic description provided by computational approaches such as molecular dynamics (MD) simulations, especially, in light of the unprecedented timescales accessible at present. However, despite recent substantial improvements, the accuracy of MD simulations is still undermined by the intrinsic limitations of force fields. Here, we systematically assessed the performance of the most popular force fields employed to study ion channels at timescales that are orders of magnitude greater than the ones accessible when these energy functions were first developed. Using 32 µs of trajectories, we investigated the dynamics of a member of the K2P ion channel family, the TRAAK channel, using two established force fields in simulations of biological systems: AMBER and CHARMM. We found that while results are comparable on the nanosecond timescales, significant inconsistencies arise at microsecond timescales.

Exploring Conformational Dynamics of the Extracellular Venus flytrap Domain of the GABAB Receptor: A Path-Metadynamics Study.

γ-Aminobutyric acid (GABA) is the main inhibitory neurotransmitter in the central nervous system (CNS). Dysfunctional GABAergic neurotransmission is associated with numerous neurological and neuropsychiatric disorders. The GABAB receptor (GABAB-R) is a heterodimeric class C G protein-coupled receptor (GPCR) comprised of GABAB1a/b and GABAB2 subunits. The orthosteric binding site for GABA is located in the extracellular Venus flytrap (VFT) domain of the GABAB1a/b. Knowledge about molecular mechanisms and druggable receptor conformations associated with activation is highly important to understand the receptor function and for rational drug design. Currently, the conformational changes of the receptor upon activation are not well described. On the basis of other class C members, the VFT is proposed to fluctuate between an open/inactive and closed/active state and one of these conformations is stabilized upon ligand binding. In the present study, we investigated the dynamics of the GABAB1b-R VFT in the apo form by combining unbiased molecular dynamics with path-metadynamics. Our simulations confirmed the open/inactive and closed/active state as the main conformations adopted by the receptor. Sizeable energy barriers were found between stable minima, suggesting a relatively slow interconversion. Previously undisclosed metastable states were also identified, which might hold potential for future drug discovery efforts.

Targeting the Protein Tunnels of the Urease Accessory Complex: A Theoretical Investigation.

Urease is a nickel-containing enzyme that is essential for the survival of several and often deadly pathogenic bacterial strains, including Helicobacter pylori. Notwithstanding several attempts, the development of direct urease inhibitors without side effects for the human host remains, to date, elusive. The recently solved X-ray structure of the HpUreDFG accessory complex involved in the activation of urease opens new perspectives for structure-based drug discovery. In particular, the quaternary assembly and the presence of internal tunnels for nickel translocation offer an intriguing possibility to target the HpUreDFG complex in the search of indirect urease inhibitors. In this work, we adopted a theoretical framework to investigate such a hypothesis. Specifically, we searched for putative binding sites located at the protein-protein interfaces on the HpUreDFG complex, and we challenged their druggability through structure-based virtual screening. We show that, by virtue of the presence of tunnels, some protein-protein interfaces on the HpUreDFG complex are intrinsically well suited for hosting small molecules, and, as such, they possess good potential for future drug design endeavors.

Predicting Residence Time and Drug Unbinding Pathway through Scaled Molecular Dynamics.

Computational approaches currently assist medicinal chemistry through the entire drug discovery pipeline. However, while several computational tools and strategies are available to predict binding affinity, predicting the drug-target binding kinetics is still a matter of ongoing research. Here, we challenge scaled molecular dynamics simulations to assess the off-rates for a series of structurally diverse inhibitors of the heat shock protein 90 (Hsp90) covering 3 orders of magnitude in their experimental residence times. The derived computational predictions are in overall good agreement with experimental data. Aside from the estimation of exit times, unbinding pathways were assessed through dimensionality reduction techniques. The data analysis framework proposed in this work could lead to better understanding of the mechanistic aspects related to the observed kinetic behavior.

Fully Flexible Docking via Reaction-Coordinate-Independent Molecular Dynamics Simulations.

Predicting the geometry of protein-ligand binding complexes is of primary importance for structure-based drug discovery. Molecular dynamics (MD) is emerging as a reliable computational tool for use in conjunction with, or an alternative to, docking methods. However, simulating the protein-ligand binding process often requires very expensive simulations. This drastically limits the practical application of MD-based approaches. Here, we propose a general framework to accelerate the generation of putative protein-ligand binding modes using potential-scaled MD simulations. The proposed dynamical protocol has been applied to two pharmaceutically relevant systems (GSK-3ß and the N-terminal domain of HSP90α). Our approach is fully independent of any predefined reaction coordinate (or collective variable). It identified the correct binding mode of several ligands and can thus save valuable computational time in dynamic docking simulations.

Binding Residence Time through Scaled Molecular Dynamics: A Prospective Application to hDAAO Inhibitors.

Traditionally, a drug potency is expressed in terms of thermodynamic quantities, mostly Kd, and empirical IC50 values. Although binding affinity as an estimate of drug activity remains relevant, it is increasingly clear that it is also important to include (un)binding kinetic parameters in the characterization of potential drug-like molecules. Herein, we used standard in silico screening to identify a series of structurally related inhibitors of hDAAO, a flavoprotein involved in schizophrenia and neuropathic pain. We applied a novel methodology, based on scaled molecular dynamics, to rank them according to their residence times. Notably, we challenged the application in a prospective fashion for the first time. The good agreement between experimental residence times and the predicted residence times highlighted the procedure's reliability in both predictive and refinement scenarios. Additionally, through further inspection of the performed simulations, we substantiated a previous hypothesis on the involvement of a protein loop during ligand unbinding.

Development of a multisite model for Ni(II) ion in solution from thermodynamic and kinetic data.

Force-field parameters are developed for a multisite model of Ni(II) ions to be used in molecular dynamics simulations combined to enhanced sampling methods. The performances of two charge-partitioning schemes are validated by taking into account structural, thermodynamic, and kinetic observables. One of the two models, featuring partial charges on the dummy atoms only, matches both Ni(II) free energy of solvation and water exchange rates. Such model is particularly suited to study complexation events at a fully dynamic description. © 2017 Wiley Periodicals, Inc.

Dynamic Docking: A Paradigm Shift in Computational Drug Discovery.

Molecular docking is the methodology of choice for studying in silico protein-ligand binding and for prioritizing compounds to discover new lead candidates. Traditional docking simulations suffer from major limitations, mostly related to the static or semi-flexible treatment of ligands and targets. They also neglect solvation and entropic effects, which strongly limits their predictive power. During the last decade, methods based on full atomistic molecular dynamics (MD) have emerged as a valid alternative for simulating macromolecular complexes. In principle, compared to traditional docking, MD allows the full exploration of drug-target recognition and binding from both the mechanistic and energetic points of view (dynamic docking). Binding and unbinding kinetic constants can also be determined. While dynamic docking is still too computationally expensive to be routinely used in fast-paced drug discovery programs, the advent of faster computing architectures and advanced simulation methodologies are changing this scenario. It is feasible that dynamic docking will replace static docking approaches in the near future, leading to a major paradigm shift in in silico drug discovery. Against this background, we review the key achievements that have paved the way for this progress.

Conformational SERS Classification of K-Ras Point Mutations for Cancer Diagnostics.

Point mutations in Ras oncogenes are routinely screened for diagnostics and treatment of tumors (especially in colorectal cancer). Here, we develop an optical approach based on direct SERS coupled with chemometrics for the study of the specific conformations that single-point mutations impose on a relatively large fragment of the K-Ras gene (141 nucleobases). Results obtained offer the unambiguous classification of different mutations providing a potentially useful insight for diagnostics and treatment of cancer in a sensitive, fast, direct and inexpensive manner.

Mechanism of the Pseudoirreversible Binding of Amantadine to the M2 Proton Channel.

The M2 proton channel of influenza A virus is an integral membrane protein involved in the acidification of the viral interior, a step necessary for the release of the viral genetic material and replication of new virions. The aim of this study is to explore the mechanism of drug (un)binding to the M2 channel in order to gain insight into the structural and energetic features relevant for the development of novel inhibitors. To this end, we have investigated the binding of amantadine (Amt) to the wild type (wt) M2 channel and its V27A variant using multiple independent molecular dynamics simulations, exploratory conventional metadynamics, and multiple-walkers well-tempered metadynamics calculations. The results allow us to propose a sequential mechanism for the (un)binding of Amt to the wt M2 channel, which involves the adoption of a transiently populated intermediate (up state) leading to the thermodynamically favored down binding mode in the channel pore. Furthermore, they suggest that chloride anions play a relevant role in stabilizing the down binding mode of Amt to the wt channel, giving rise to a kinetic trapping that explains the experimentally observed pseudoirreversible inhibition of the wt channel by Amt. We propose that this trapping mechanism underlies the inhibitory activity of potent M2 channel blockers, as supported by the experimental confirmation of the irreversible binding of a pyrrolidine analogue from electrophysiological current assays. Finally, the results reveal that the thermodynamics and kinetics of Amt (un)binding is very sensitive to the V27A mutation, providing a quantitative rationale to the drastic decrease in inhibitory potency against the V27A variant. Overall, these findings pave the way to explore the inhibitory activity of Amt-related analogues in mutated M2 channel variants, providing guidelines for the design of novel inhibitors against resistant virus strains.

Revealing DNA interactions with exogenous agents by surface-enhanced Raman scattering.

The standard protocols for DNA analysis largely involve polymerase chain reaction (PCR). However, DNA structures bound to chemical agents cannot be PCR-amplified, and therefore any sequence changes induced by external agents may be neglected. Thus, the development of analytical tools capable of characterizing the biochemical mechanisms associated with chemically induced DNA damage is demanded for the rational design of more effective chemotherapy drugs, understanding the mode of actions of carcinogenic chemicals, and monitoring the genotypic toxicology of environments. Here we report a fast, high-throughput, low-cost method for the characterization and quantitative recognition of DNA interactions with exogenous agents based on surface-enhanced Raman scattering spectroscopy. As representative chemical agents, we selected a chemotherapeutic drug (cisplatin) which forms covalent adducts with DNA, a duplex intercalating agent (methylene blue), and a cytotoxic metal ion (Hg(II)) which inserts into T:T mismatches. Rich structural information on the DNA complex architecture and properties is provided by the unique changes of their SERS spectra, which also offer an efficient analytical tool to quantify the extent of such binding.

Mechanistic insights into Pin1 peptidyl-prolyl cis-trans isomerization from umbrella sampling simulations.

The peptidyl-proyl isomerase Pin1 plays a key role in the regulation of phospho(p)-Ser/Thr-Pro proteins, acting as a molecular timer of the cell cycle. After recognition of these motifs, Pin1 catalyzes the rapid cis-trans isomerization of proline amide bonds of substrates, contributing to maintain the equilibrium between the two conformations. Although a great interest has arisen on this enzyme, its catalytic mechanism has long been debated. Here, the cis-trans isomerization of a model peptide system was investigated by means of umbrella sampling simulations in the Pin1-bound and unbound states. We obtained free energy barriers consistent with experimental data, and identified several enzymatic features directly linked to the acceleration of the prolyl bond isomerization. In particular, an enhanced autocatalysis, the stabilization of perturbed ground state conformations, and the substrate binding in a procatalytic conformation were found as main contributions to explain the lowering of the isomerization free energy barrier.

Probing allosteric communication with combined molecular dynamics simulations and network analysis.

Understanding the allosteric mechanisms within biomolecules involved in diseases is of paramount importance for drug discovery. Indeed, characterizing communication pathways and critical hotspots in signal transduction can guide a rational approach to leverage allosteric modulation for therapeutic purposes. While the atomistic signatures of allosteric processes are difficult to determine experimentally, computational methods can be a remarkable resource. Network analysis built on Molecular Dynamics simulation data is particularly suited in this respect and is gradually becoming of routine use. Herein, we collect the recent literature in the field, discussing different aspects and available options for network construction and analysis. We further highlight interesting refinements and extensions, eventually providing our perspective on this topic.

Fragment Merging, Growing, and Linking Identify New Trypanothione Reductase Inhibitors for Leishmaniasis.

Trypanothione reductase (TR) is a suitable target for drug discovery approaches against leishmaniasis, although the identification of potent inhibitors is still challenging. Herein, we harnessed a fragment-based drug discovery (FBDD) strategy to develop new TR inhibitors. Previous crystallographic screening identified fragments 1-3, which provided ideal starting points for a medicinal chemistry campaign. In silico investigations revealed critical hotspots in the TR binding site, guiding our structure- and ligand-based structure-actvity relationship (SAR) exploration that yielded fragment-derived compounds 4-14. A trend of improvement in Leishmania infantum TR inhibition was detected along the optimization and confirmed by the crystal structures of 9, 10, and 14 in complex with Trypanosoma brucei TR. Compound 10 showed the best TR inhibitory profile (Ki = 0.2 µM), whereas 9 was the best one in terms of in vitro and ex vivo activity. Although further fine-tuning is needed to improve selectivity, we demonstrated the potentiality of FBDD on a classic but difficult target for leishmaniasis.