Supporting the identification of novel fragment-based positive allosteric modulators using a supervised molecular dynamics approach: A retrospective analysis considering the human A2A adenosine receptor as a key example

Structure-driven fragment-based (SDFB) approaches have provided efficient methods for the identification of novel drug candidates. This strategy has been largely applied in discovering several pharmacological ligand classes, including enzyme inhibitors, receptor antagonists and, more recently, also allosteric (positive and negative) modulators. Recently, Siegal and collaborators reported an interesting study, performed on a detergent-solubilized StaR adenosine A2A receptor, describing the existence of both fragment-like negative allosteric modulators (NAMs), and fragment-like positive allosteric modulators (PAMs). From this retrospective study, our results suggest that Supervised Molecular Dynamics (SuMD) simulations can support, on a reasonable time scale, the identification of fragment-like PAMs following their receptor recognition pathways and characterizing the possible allosteric binding sites

Pomeron Physics at the LHC

We present current and ongoing research aimed at identifying Pomeron effects at the LHC in both the weak and strongly coupled regimes of QCD.Comment: 11 pages, 9 figures, 1 table. ISMD-2017 proceedings, will be published on-line on the EPJ Web of Conferences; References adde

Probing BFKL dynamics at hadronic colliders in jet gap jet events

In this report, we give the Balitsky Fadin Kuraev Lipton formalism for jet gap jet events at hadronic colliders. We also discuss the case where in addition at least one proton is intact in the final state in diffractive events

Forward dijet production at the LHC within an impact parameter dependent TMD approach

We investigate possible signatures of gluon saturation using forward $p+A \to j+j+X$ di-jet production processes at the Large Hadron Collider. In the forward rapidity region, this is a highly asymmetric process where partons with large longitudinal momentum fraction $x$ in the dilute projectile are used as a probe to resolve the small $x$ partonic content of the dense target. Such dilute-dense processes can be described in the factorization framework of Improved Transverse Momentum Distributions (ITMDs). We present a new model for ITMDs where we explicitly introduce the impact parameter ($b$) dependence in the ITMDs, to properly account for the nuclear enhancement of gluon saturation effects, and discuss the phenomenological consequences for $p-Pb$, $p-Xe$ and $p-O$ collisions at the LHC. While the case of $p-p$ and $e-p$ collisions is used to fix the model parameters, we find that, on average, the nuclear enhancement of the saturation scale is noticeably weaker than expected from naive scaling with a simple dependence on the atomic number. Since our model explicitly accounts for event-by-event fluctuations of the nuclear geometry, it can also be applied to study forward central correlations in $p-A$ collisions

A Supervised Molecular Dynamics Approach to Unbiased Ligand–Protein Unbinding

The recent paradigm shift toward the use of the kinetics parameters in place of thermodynamic constants is leading the computational chemistry community to develop methods for studying the mechanisms of drug binding and unbinding. From this standpoint, molecular dynamics (MD) plays an important role in delivering insight at the molecular scale. However, a known limitation of MD is that the time scales are usually far from those involved in ligand–receptor unbinding events. Here, we show that the algorithm behind supervised MD (SuMD) can simulate the dissociation mechanism of druglike small molecules while avoiding the input of any energy bias to facilitate the transition. SuMD was tested on seven different intermolecular complexes, covering four G protein-coupled receptors: the A2A and A1 adenosine receptors, the orexin 2 and the muscarinic 2 receptors, and the soluble globular enzyme epoxide hydrolase. SuMD well-described the multistep nature of ligand–receptor dissociation, rationalized previous experimental data and produced valuable working hypotheses for structure–kinetics relationships

Is the Stalk of the SARS-CoV-2 Spike Protein Druggable?

The spike protein is key to SARS-CoV-2 high infectivity because it facilitates the receptor binding domain (RBD) encounter with ACE2. As targeting subunit S1 has not yet delivered an ACE2-binding inhibitor, we have assessed the druggability of the conserved segment of the spike protein stalk within subunit S2 by means of an integrated computational approach that combines the molecular docking of an optimized library of fragments with high-throughput molecular dynamics simulations. The high propensity of the spike protein to mutate in key regions that are responsible for the recognition of the human angiotensin-converting enzyme 2 (hACE2) or for the recognition of antibodies, has made subunit S1 of the spike protein difficult to target. Despite the inherent flexibility of the stalk region, our results suggest two hidden interhelical binding sites, whose accessibility is only partially hampered by glycan residues