Searching for protein binding sites from Molecular Dynamics simulations and paramagnetic fragment-based NMR studies

Pharmacological Chaperones and Protein Conformational Diseases: Approaches of Computational Structural Biology

Whenever a protein fails to fold into its native structure, a profound detrimental effect is likely to occur, and a disease is often developed. Protein conformational disorders arise when proteins adopt abnormal conformations due to a pathological gene variant that turns into gain/loss of function or improper localization/degradation. Pharmacological chaperones are small molecules restoring the correct folding of a protein suitable for treating conformational diseases. Small molecules like these bind poorly folded proteins similarly to physiological chaperones, bridging non-covalent interactions (hydrogen bonds, electrostatic interactions, and van der Waals contacts) loosened or lost due to mutations. Pharmacological chaperone development involves, among other things, structural biology investigation of the target protein and its misfolding and refolding. Such research can take advantage of computational methods at many stages. Here, we present an up-to-date review of the computational structural biology tools and approaches regarding protein stability evaluation, binding pocket discovery and druggability, drug repurposing, and virtual ligand screening. The tools are presented as organized in an ideal workflow oriented at pharmacological chaperones' rational design, also with the treatment of rare diseases in mind.

A molecular spectroscopy approach for the investigation of early phase ochronotic pigment development in Alkaptonuria

Alkaptonuria (AKU), a rare genetic disorder, is characterized by the accumulation of homogentisic acid (HGA) in organs due to a deficiency in functional levels of the enzyme homogentisate 1,2-dioxygenase (HGD), required for the breakdown of HGA, because of mutations in the HGD gene. Over time, HGA accumulation causes the formation of the ochronotic pigment, a dark deposit that leads to tissue degeneration and organ malfunction. Such behaviour can be observed also in vitro for HGA solutions or HGA-containing biofluids (e.g. urine from AKU patients) upon alkalinisation, although a comparison at the molecular level between the laboratory and the physiological conditions is lacking. Indeed, independently from the conditions, such process is usually explained with the formation of 1,4-benzoquinone acetic acid (BQA) as the product of HGA chemical oxidation, mostly based on structural similarity between HGA and hydroquinone that is known to be oxidized to the corresponding para-benzoquinone. To test such correlation, a comprehensive, comparative investigation on HGA and BQA chemical behaviours was carried out by a combined approach of spectroscopic techniques (UV spectrometry, Nuclear Magnetic Resonance, Electron Paramagnetic Resonance, Dynamic Light Scattering) under acid/base titration both in solution and in biofluids. New insights on the process leading from HGA to ochronotic pigment have been obtained, spotting out the central role of radical species as intermediates not reported so far. Such evidence opens the way for molecular investigation of HGA fate in cells and tissue aiming to find new targets for Alkaptonuria therapy.

Applications of Solution NMR in Drug Discovery

During the past decades, solution nuclear magnetic resonance (NMR) spectroscopy has demonstrated itself as a promising tool in drug discovery. Especially, fragment-based drug discovery (FBDD) has benefited a lot from the NMR development. Multiple candidate compounds and FDA-approved drugs derived from FBDD have been developed with the assistance of NMR techniques. NMR has broad applications in different stages of the FBDD process, which includes fragment library construction, hit generation and validation, hit-to-lead optimization and working mechanism elucidation, etc. In this manuscript, we reviewed the current progresses of NMR applications in fragment-based drug discovery, which were illustrated by multiple reported cases. Moreover, the NMR applications in protein-protein interaction (PPI) modulators development and the progress of in-cell NMR for drug discovery were also briefly summarized.

Transient pockets as mediators of gas molecules routes inside proteins: The case study of dioxygen pathway in homogentisate 1,2-dioxygenase and its implication in Alkaptonuria development

Alkaptonuria (AKU) is an ultra-rare disease caused by mutations in homogentisate 1,2-dioxygenase (HGD) enzyme, characterized by the loss of enzymatic activity and the accumulation of its substrate, homogentisic acid (HGA) in different tissues, leading to ochronosis and organ degeneration. Although the pathological effects of HGD mutations are largely studied, less is known about the structure of the enzyme, in particular the pathways for dioxygen diffusion to the active site, required for the enzymatic reaction, are still uninvestigated. In the present project, the combination of two in silico techniques, Molecular Dynamics (MD) simulation and Implicit Ligand Sampling (ILS), was used to delineate gas diffusion routes in HGD enzyme. A route from the central opening of the hexameric structure of the enzyme to the back of the active site trough the protein moiety was identified as the path for dioxygen diffusion, also overlapping with a transient pocket, which then assumes an important role in dioxygen diffusion. Along the route the sequence location of the missense variant E401Q, responsible for AKU development, was also found, suggesting such mutation to be conducive of enzymatic activity loss by altering the flow dynamics of dioxygen. Our in silico approach allowed also to delineate the route of HGA substrate to the active site, until now only supposed.

Applications of in Silico Methods for Design and Development of Drugs Targeting Protein-Protein Interactions

BACKGROUND

Identification of Protein-Protein Interactions (PPIs) is a major challenge in modern molecular biology and biochemistry research, due to the unquestionable role of proteins in cells, biological process and pathological states. Over the past decade, the PPIs have evolved from being considered a highly challenging field of research to being investigated and examined as targets for pharmacological intervention.

OBJECTIVE

Comprehension of protein interactions is crucial to known how proteins come together to build signalling pathways, to carry out their functions, or to cause diseases, when deregulated. Multiplicity and great amount of PPIs structures offer a huge number of new and potential targets for the treatment of different diseases.

METHODS

Computational techniques are becoming predominant in PPIs studies for their effectiveness, flexibility, accuracy and cost. As a matter of fact, there are effective in silico approaches which are able to identify PPIs and PPI site. Such methods for computational target prediction have been developed through molecular descriptors and data-mining procedures.

RESULTS

In this review, we present different types of interactions between protein-protein and the application of in silico methods for design and development of drugs targeting PPIs. We described computational approaches for the identification of possible targets on protein surface and to detect of stimulator/ inhibitor molecules.

CONCLUSION

A deeper study of the most recent bioinformatics methodologies for PPIs studies is vital for a better understanding of protein complexes and for discover new potential PPI modulators in therapeutic intervention.

Molecular-Simulation-Driven Fragment Screening for the Discovery of New CXCL12 Inhibitors

Fragment-based drug discovery (FBDD) has become a mainstream approach in drug design because it allows the reduction of the chemical space and screening libraries while identifying fragments with high protein-ligand efficiency interactions that can later be grown into drug-like leads. In this work, we leverage high-throughput molecular dynamics (MD) simulations to screen a library of 129 fragments for a total of 5.85 ms against the CXCL12 monomer, a chemokine involved in inflammation and diseases such as cancer. Our in silico binding assay was able to recover binding poses, affinities, and kinetics for the selected library and was able to predict 8 mM-affinity fragments with ligand efficiencies higher than 0.3. All of the fragment hits present a similar chemical structure, with a hydrophobic core and a positively charged group, and bind to either sY7 or H1S68 pockets, where they share pharmacophoric properties with experimentally resolved natural binders. This work presents a large-scale screening assay using an exclusive combination of thousands of short MD adaptive simulations analyzed with a Markov state model (MSM) framework.

Toward a generalized computational workflow for exploiting transient pockets as new targets for small molecule stabilizers: Application to the homogentisate 1,2-dioxygenase mutants at the base of rare disease Alkaptonuria

Alkaptonuria (AKU) is an inborn error of metabolism where mutation of homogentisate 1,2-dioxygenase (HGD) gene leads to a deleterious or misfolded product with subsequent loss of enzymatic degradation of homogentisic acid (HGA) whose accumulation in tissues causes ochronosis and degeneration. There is no licensed therapy for AKU. Many missense mutations have been individuated as responsible for quaternary structure disruption of the native hexameric HGD. A new approach to the treatment of AKU is here proposed aiming to totally or partially rescue enzyme activity by targeting of HGD with pharmacological chaperones, i.e. small molecules helping structural stability. Co-factor pockets from oligomeric proteins have already been successfully exploited as targets for such a strategy, but no similar sites are present at HGD surface; hence, transient pockets are here proposed as a target for pharmacological chaperones. Transient pockets are detected along the molecular dynamics trajectory of the protein and filtered down to a set of suitable sites for structural stabilization by mean of biochemical and pharmacological criteria. The result is a computational workflow relevant to other inborn errors of metabolism requiring rescue of oligomeric, misfolded enzymes.

Investigations into the killing activity of an antimicrobial peptide active against extensively antibiotic-resistant K. pneumon iae and P. aeruginosa

SET-M33 is a multimeric antimicrobial peptide active against Gram-negative bacteria in vitro and in vivo. Insights into its killing mechanism could elucidate correlations with selectivity. SET-M33 showed concentration-dependent bactericidal activity against colistin-susceptible and resistant isolates of P. aeruginosa and K. pneumoniae. Scanning and transmission microscopy studies showed that SET-M33 generated cell blisters, blebs, membrane stacks and deep craters in K. pneumoniae and P. aeruginosa cells. NMR analysis and CD spectra in the presence of sodium dodecyl sulfate micelles showed a transition from an unstructured state to a stable α-helix, driving the peptide to arrange itself on the surface of micelles. SET-M33 kills Gram-negative bacteria after an initial interaction with bacterial LPS. The molecule becomes then embedded in the outer membrane surface, thereby impairing cell function. This activity of SET-M33, in contrast to other similar antimicrobial peptides such as colistin, does not generate resistant mutants after 24h of exposure, non-specific interactions or toxicity against eukaryotic cell membranes, suggesting that SET-M33 is a promising new option for the treatment of Gram-negative antibiotic-resistant infections.

Hot spot mapping of protein surfaces with TEMPOL: Bovine pancreatic RNase A as a model system

TEMPOL spin-label has been used to identify surface exposure of protein nuclei from NMR analysis of the induced paramagnetic relaxation enhancements (PRE). The absence of linear dependence between atom depths and observed PRE reveals that specific mechanisms drive the approach of the paramagnet to the protein surface. RNase A represents a unique protein system to explore the fine details of the information offered by TEMPOL induced PRE, due to the abundance of previous results, obtained in solution and in the crystal, dealing with surface dynamics behavior of this protein. MD simulations in explicit solvent have been performed, also in the presence of TEMPOL, in order to delineate the role of intermolecular hydrogen bonds (HB) on PRE extents. Comparison of our results with the ones obtained from multiple solvent crystal structure (MSCS) studies yields information on the specificities that these two techniques have for characterizing protein-ligand interactions, a fundamental step in the development of reliable surface druggability predictors.

Exploiting Transient Protein States for the Design of Small-Molecule Stabilizers of Mutant p53

The destabilizing p53 cancer mutation Y220C creates an extended crevice on the surface of the protein that can be targeted by small-molecule stabilizers. Here, we identify different classes of small molecules that bind to this crevice and determine their binding modes by X-ray crystallography. These structures reveal two major conformational states of the pocket and a cryptic, transiently open hydrophobic subpocket that is modulated by Cys220. In one instance, specifically targeting this transient protein state by a pyrrole moiety resulted in a 40-fold increase in binding affinity. Molecular dynamics simulations showed that both open and closed states of this subsite were populated at comparable frequencies along the trajectories. Our data extend the framework for the design of high-affinity Y220C mutant binders for use in personalized anticancer therapy and, more generally, highlight the importance of implementing protein dynamics and hydration patterns in the drug-discovery process.

Overcoming Chemical, Biological, and Computational Challenges in the Development of Inhibitors Targeting Protein-Protein Interactions

Protein-protein interactions (PPIs) underlie the majority of biological processes, signaling, and disease. Approaches to modulate PPIs with small molecules have therefore attracted increasing interest over the past decade. However, there are a number of challenges inherent in developing small-molecule PPI inhibitors that have prevented these approaches from reaching their full potential. From target validation to small-molecule screening and lead optimization, identifying therapeutically relevant PPIs that can be successfully modulated by small molecules is not a simple task. Following the recent review by Arkin et al., which summarized the lessons learnt from prior successes, we focus in this article on the specific challenges of developing PPI inhibitors and detail the recent advances in chemistry, biology, and computation that facilitate overcoming them. We conclude by providing a perspective on the field and outlining four innovations that we see as key enabling steps for successful development of small-molecule inhibitors targeting PPIs.

Progress in discovery of small-molecule modulators of protein-protein interactions via fragment screening

Protein-protein interactions (PPIs) present a formidable challenge to medicinal chemistry. The extended and open nature of many binding sites at protein interfaces has made it difficult to find useful chemical matter by traditional screening methods using standard screening libraries. This Digest focuses on the progress that has been made in discovering small-molecule modulators for a diverse selection of PPI targets using fragment screening and highlights the utility of this strategy in this context.