Discovery of a Novel DCAF1 Ligand Using a Drug-Target Interaction Prediction Model: Generalizing Machine Learning to New Drug Targets.

DCAF1 functions as a substrate recruitment subunit for the RING-type CRL4 and the HECT family EDVP E3 ubiquitin ligases. The WDR domain of DCAF1 serves as a binding platform for substrate proteins and is also targeted by HIV and SIV lentiviral adaptors to induce the ubiquitination and proteasomal degradation of antiviral host factors. It is therefore attractive both as a potential therapeutic target for the development of chemical inhibitors and as an E3 ligase that could be recruited by novel PROTACs for targeted protein degradation.

Synthesis of Carvone Derivatives and In Silico and In Vitro Screening of Anti-Inflammatory Activity in Murine Macrophages.

The chemical modification of natural compounds is a promising strategy to improve their frequently poor bioavailability and low potency. This study aimed at synthesizing chemical derivatives of carvone, a natural monoterpene with anti-inflammatory properties, which we recently identified, and evaluating their potential anti-inflammatory activity. Fourteen chemical derivatives of carvone were synthesized, purified and their chemical structures confirmed.

Multiscale interactome analysis coupled with off-target drug predictions reveals drug repurposing candidates for human coronavirus disease.

The COVID-19 pandemic has highlighted the urgent need for the identification of new antiviral drug therapies for a variety of diseases. COVID-19 is caused by infection with the human coronavirus SARS-CoV-2, while other related human coronaviruses cause diseases ranging from severe respiratory infections to the common cold. We developed a computational approach to identify new antiviral drug targets and repurpose clinically-relevant drug compounds for the treatment of a range of human coronavirus diseases.

Proteome-Scale Drug-Target Interaction Predictions: Approaches and Applications.

Drug-Target interaction predictions are an important cornerstone of computer-aided drug discovery. While predictive methods around individual targets have a long history, the application of proteome-scale models is relatively recent. In this overview, we will provide the context required to understand advances in this emerging field within computational drug discovery, evaluate emerging technologies for suitability to given tasks, and provide guidelines for the design and implementation of new drug-target interaction prediction models.

Interplay of self-association and conformational flexibility in regulating protein function.

Many functional roles have been attributed to homodimers, the most common mode of protein self-association, notably in the regulation of enzymes, ion channels, transporters and transcription factors. Here we review findings that offer new insights into the different roles conformational flexibility plays in regulating homodimer function. Intertwined homodimers of two-domain proteins and their related family members display significant conformational flexibility, which translates into concerted motion between structural domains.

Comprehensive mapping of cystic fibrosis mutations to CFTR protein identifies mutation clusters and molecular docking predicts corrector binding site.

Cystic Fibrosis (CF) is caused by mutations in the CFTR gene, of which over 2000 have been reported to date. Mutations have yet to be analyzed in aggregate to assess their distribution across the tertiary structure of the CFTR protein, an approach that could provide valuable insights into the structure-function relationship of CFTR. In addition, the binding site of Class I correctors (VX-809, VX-661, and C18) is not well understood.

The Antiretroviral Agent Nelfinavir Mesylate: A Potential Therapy for Systemic Sclerosis.

Objective: Transforming growth factor β1 (TGFβ1) is considered a key factor in fibrogenesis, and blocking TGFβ1 signaling pathways diminishes fibrogenesis in animal models. The objective of this study was to determine whether nelfinavir mesylate (NFV), a drug approved by the Food and Drug Administration (FDA) for treating HIV infection, could be repurposed to treat pulmonary fibrosis in patients with systemic sclerosis (SSc).

Methods: Normal human lung, ventricular, and skin fibroblasts as well as lung fibroblasts from SSc patients were used to determine the effects of NFV on fibroblast-to-myofibroblast differentiation mediated by TGFβ1.

Structural coverage of the proteome for pharmaceutical applications.

Structure-based computational drug discovery efforts have traditionally focused on the structure of a single, well-known drug target. Important applications, such as target deconvolution and the analysis of polypharmacology, require proteome-scale molecular docking and have been inaccessible to structure-based in silico approaches. One important reason for this inaccessibility was that the structure of most proteins was not known.

Computational proteome-wide screening predicts neurotoxic drug-protein interactome for the investigational analgesic BIA 10-2474.

The investigational compound BIA 10-2474, designed as a long-acting and reversible inhibitor of fatty acid amide hydrolase for the treatment of neuropathic pain, led to the death of one participant and hospitalization of five others due to intracranial hemorrhage in a Phase I clinical trial. Putative off-target activities of BIA 10-2474 have been suggested to be major contributing factors to the observed neurotoxicity in humans, motivating our study's proteome-wide screening approach to investigate its polypharmacology. Accordingly, we performed an in silico screen against 80,923 protein structures reported in the Protein Data Bank.

The Landscape of Intertwined Associations in Homooligomeric Proteins.

We present an overview of the full repertoire of intertwined associations in homooligomeric proteins. This overview summarizes recent findings on the different categories of intertwined associations in known protein structures, their assembly modes, the properties of their interfaces, and their structural plasticity. Furthermore, the current body of knowledge on the so-called three-dimensional domain-swapped systems is reexamined in the context of the wider landscape of intertwined homooligomers, with a particular focus on the mechanistic aspects that underpin intertwined self-association processes in proteins.

Landscape of intertwined associations in multi-domain homo-oligomeric proteins.

This study charts the landscape of multi-domain protein structures that form intertwined homodimers by exchanging structural domains between subunits. A representative dataset of such homodimers was derived from the Protein Data Bank, and their structural and topological properties were compared to those of a representative set of non-intertwined homodimers. Most of the intertwined dimers form closed assemblies with head-to-tail arrangements, where the subunit interface involves contacts between dissimilar domains.

Intertwined associations in structures of homooligomeric proteins.

Intertwined homo-oligomers are complexes comprising identical protein subunits, where small segments or compact protein substructures (domains) are exchanged between the subunits. Using a formal definition of intertwined homo-oligomers, we survey the Protein Data Bank for all such complexes. Results show that intertwining occurs in 13,442 (24%) of all surveyed structures.