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

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

Set-Theoretic Types for Polymorphic Variants

Polymorphic variants are a useful feature of the OCaml language whose current definition and implementation rely on kinding constraints to simulate a subtyping relation via unification. This yields an awkward formalization and results in a type system whose behaviour is in some cases unintuitive and/or unduly restrictive. In this work, we present an alternative formalization of poly-morphic variants, based on set-theoretic types and subtyping, that yields a cleaner and more streamlined system. Our formalization is more expressive than the current one (it types more programs while preserving type safety), it can internalize some meta-theoretic properties, and it removes some pathological cases of the current implementation resulting in a more intuitive and, thus, predictable type system. More generally, this work shows how to add full-fledged union types to functional languages of the ML family that usually rely on the Hindley-Milner type system. As an aside, our system also improves the theory of semantic subtyping, notably by proving completeness for the type reconstruction algorithm.Comment: ACM SIGPLAN International Conference on Functional Programming, Sep 2016, Nara, Japan. ICFP 16, 21st ACM SIGPLAN International Conference on Functional Programming, 201

A Pathway Model to Understand the Evolution of Spike Protein Binding to ACE2 in SARS-CoV-2 Variants

After the SARS-CoV-2 Wuhan variant that gave rise to the pandemic, other variants named Delta, Omicron, and Omicron-2 sequentially became prevalent, with mutations spread around the viral genome, including on the spike (S) protein; in order to understand the resultant in gains in infectivity, we interrogated in silico both the equilibrium binding and the binding pathway of the virus’ receptor-binding domain (RBD) to the angiotensin-converting enzyme 2 (ACE2) receptor. We interrogated the molecular recognition between the RBD of different variants and ACE2 through supervised molecular dynamics (SuMD) and classic molecular dynamics (MD) simulations to address the effect of mutations on the possible S protein binding pathways. Our results indicate that compensation between binding pathway efficiency and stability of the complex exists for the Omicron BA.1 receptor binding domain, while Omicron BA.2′s mutations putatively improved the dynamic recognition of the ACE2 receptor, suggesting an evolutionary advantage over the previous strains

The role of bevacizumab in solid tumours: A literature based meta-analysis of randomised trials

BACKGROUND: Bevacizumab is a humanised monoclonal antibody which blocks the binding of circulating vascular endothelial growth factor to its receptors. To date, the Food and Drug Administration has approved bevacizumab for the treatment of several solid tumours. To assess the impact of bevacizumab-based regimens on outcome in these advanced solid tumour types, we performed a meta-analysis. We included all of the randomised trials (phase II or III) where bevacizumab was tested in the first line setting compared with a control arm, including chemotherapy, placebo or other anti-neoplastic agents. METHODS: A literature-based meta-analysis of randomised controlled trials (RCTs) in accordance with the preferences for reported items in systematic reviews and meta-analyses guidelines were undertaken. The primary end-point considered was overall survival (OS). The secondary end-points were progression-free survival (PFS) time, response rate and safety. A subgroup analysis was performed to highlight any differences between studies in different tumour types for all end-points. RESULTS: The pooled analysis from RCTs on bevacizumab-based regimens revealed significantly increased OS (hazard ratio [HR] for death 0.92, 95% confidence interval [CI]: 0.88-0.95; P < 0.0001), PFS (HR: 0.72, 95% CI: 0.67-0.78; P < 0.00001) and response rate (risk ratio: 1.38, 95% CI: 1.27-1.50; P < 0.00001) compared to control arm in solid tumours overall and in colorectal, lung, ovarian and renal cancer as single indications. However, notably, no effect on survival was seen in breast cancer. CONCLUSION: This study confirmed that bevacizumab-based regimens result in a significant effect on survival and response in advanced colorectal, lung, ovarian and kidney cancer. In cancers where bevacizumab failed overall as in breast cancer, a dedicated biomarkers analysis is warranted to select the proper subgroup of patient that might have the adequate clinical benefi

Exploring Ligand Binding to Calcitonin Gene-Related Peptide Receptors

Class B1 G protein-coupled receptors (GPCRs) are important targets for many diseases, including cancer, diabetes, and heart disease. All the approved drugs for this receptor family are peptides that mimic the endogenous activating hormones. An understanding of how agonists bind and activate class B1 GPCRs is fundamental for the development of therapeutic small molecules. We combined supervised molecular dynamics (SuMD) and classic molecular dynamics (cMD) simulations to study the binding of the calcitonin gene-related peptide (CGRP) to the CGRP receptor (CGRPR). We also evaluated the association and dissociation of the antagonist telcagepant from the extracellular domain (ECD) of CGRPR and the water network perturbation upon binding. This study, which represents the first example of dynamic docking of a class B1 GPCR peptide, delivers insights on several aspects of ligand binding to CGRPR, expanding understanding of the role of the ECD and the receptor-activity modifying protein 1 (RAMP1) on agonist selectivity