Wetenschapstoets Defensienota ‘Sterker Nederland, Veiliger Europa': het doel heiligt de middelen? Of andersom?

Institutions, Decisions and Collective Behaviou

Accelerating drug target inhibitor discovery with a deep generative foundation model

Inhibitor discovery for emerging drug-target proteins is challenging, especially when target structure or active molecules are unknown. Here, we experimentally validate the broad utility of a deep generative framework trained at-scale on protein sequences, small molecules, and their mutual interactions-unbiased toward any specific target. We performed a protein sequence-conditioned sampling on the generative foundation model to design small-molecule inhibitors for two dissimilar targets: the spike protein receptor-binding domain (RBD) and the main protease from SARS-CoV-2. Despite using only the target sequence information during the model inference, micromolar-level inhibition was observed in vitro for two candidates out of four synthesized for each target. The most potent spike RBD inhibitor exhibited activity against several variants in live virus neutralization assays. These results establish that a single, broadly deployable generative foundation model for accelerated inhibitor discovery is effective and efficient, even in the absence of target structure or binder information

Neutralization potency of monoclonal antibodies recognizing dominant and subdominant epitopes on SARS-CoV-2 Spike is impacted by the B.1.1.7 variant

Interaction of the SARS-CoV-2 Spike receptor binding domain (RBD) with the receptor ACE2 on host cells is essential for viral entry. RBD is the dominant target for neutralizing antibodies, and several neutralizing epitopes on RBD have been molecularly characterized. Analysis of circulating SARS-CoV-2 variants has revealed mutations arising in the RBD, N-terminal domain (NTD) and S2 subunits of Spike. To understand how these mutations affect Spike antigenicity, we isolated and characterized >100 monoclonal antibodies targeting epitopes on RBD, NTD, and S2 from SARS-CoV-2-infected individuals. Approximately 45% showed neutralizing activity, of which ∼20% were NTD specific. NTD-specific antibodies formed two distinct groups: the first was highly potent against infectious virus, whereas the second was less potent and displayed glycan-dependant neutralization activity. Mutations present in B.1.1.7 Spike frequently conferred neutralization resistance to NTD-specific antibodies. This work demonstrates that neutralizing antibodies targeting subdominant epitopes should be considered when investigating antigenic drift in emerging variants

Neutralization potency of monoclonal antibodies recognizing dominant and subdominant epitopes on SARS-CoV-2 Spike is impacted by the B.1.1.7 variant

Interaction of the SARS-CoV-2 Spike receptor binding domain (RBD) with the receptor ACE2 on host cells is essential for viral entry. RBD is the dominant target for neutralizing antibodies, and several neutralizing epitopes on RBD have been molecularly characterized. Analysis of circulating SARS-CoV-2 variants has revealed mutations arising in the RBD, N-terminal domain (NTD) and S2 subunits of Spike. To understand how these mutations affect Spike antigenicity, we isolated and characterized >100 monoclonal antibodies targeting epitopes on RBD, NTD, and S2 from SARS-CoV-2-infected individuals. Approximately 45% showed neutralizing activity, of which ∼20% were NTD specific. NTD-specific antibodies formed two distinct groups: the first was highly potent against infectious virus, whereas the second was less potent and displayed glycan-dependant neutralization activity. Mutations present in B.1.1.7 Spike frequently conferred neutralization resistance to NTD-specific antibodies. This work demonstrates that neutralizing antibodies targeting subdominant epitopes should be considered when investigating antigenic drift in emerging variants

The SARS-CoV-2 neutralizing antibody response to SD1 and its evasion by BA.2.86

Under pressure from neutralising antibodies induced by vaccination or infection the SARS-CoV-2 spike gene has become a hotspot for evolutionary change, leading to the failure of all mAbs developed for clinical use. Most potent antibodies bind to the receptor binding domain which has become heavily mutated. Here we study responses to a conserved epitope in sub-domain-1 (SD1) of spike which have become more prominent because of mutational escape from antibodies directed to the receptor binding domain. Some SD1 reactive mAbs show potent and broad neutralization of SARS-CoV-2 variants. We structurally map the dominant SD1 epitope and provide a mechanism of action by blocking interaction with ACE2. Mutations in SD1 have not been sustained to date, but one, E554K, leads to escape from mAbs. This mutation has now emerged in several sublineages including BA.2.86, reflecting selection pressure on the virus exerted by the increasing prominence of the anti-SD1 response

Computational shelf-life dating : complex systems approaches to food quality and safety

Shelf-life is defined as the time that a product is acceptable and meets the consumers expectations regarding food quality. It is the result of the conjunction of all services in production, distribution, and consumption. Shelf-life dating is one of the most difficult tasks in food engineering. Market pressure has lead to the implementation of shelf-life by sensory analyses, which may not reflect the full quality spectra. Moreover, traditional methods for shelf-life dating and small-scale distribution chain tests cannot reproduce in a laboratory the real conditions of storage, distribution, and consumption on food quality. Today, food engineers are facing the challenges to monitor, diagnose, and control the quality and safety of food products. The advent of nanotechnology, multivariate sensors, information systems, and complex systems will revolutionize the way we manage, distribute, and consume foods. The informed consumer demands foods, under the legal standards, at low cost, high standards of nutritional, sensory, and health benefits. To accommodate the new paradigms, we herein present a critical review of shelf-life dating approaches with special emphasis in computational systems and future trends on complex systems methodologies applied to the prediction of food quality and safety.Fundo Europeu de Desenvolvimento Regional (FEDER) - Programa POS-ConhecimentoFundação para a Ciência e a Tecnologia (FCT) - SFRH/BPD/26133/2005, SFRH/ BPD/20735/200

Emerging variants develop total escape from potent monoclonal antibodies induced by BA.4/5 infection

The rapid evolution of SARS-CoV-2 is driven in part by a need to evade the antibody response in the face of high levels of immunity. Here, we isolate spike (S) binding monoclonal antibodies (mAbs) from vaccinees who suffered vaccine break-through infections with Omicron sub lineages BA.4 or BA.5. Twenty eight potent antibodies are isolated and characterised functionally, and in some cases structurally. Since the emergence of BA.4/5, SARS-CoV-2 has continued to accrue mutations in the S protein, to understand this we characterize neutralization of a large panel of variants and demonstrate a steady attrition of neutralization by the panel of BA.4/5 mAbs culminating in total loss of function with recent XBB.1.5.70 variants containing the so-called ‘FLip’ mutations at positions 455 and 456. Interestingly, activity of some mAbs is regained on the recently reported variant BA.2.86

Pan-cancer whole-genome analyses of metastatic solid tumours

Contains fulltext : 215492.pdf (publisher's version ) (Open Access)Metastatic cancer is a major cause of death and is associated with poor treatment efficacy. A better understanding of the characteristics of late-stage cancer is required to help adapt personalized treatments, reduce overtreatment and improve outcomes. Here we describe the largest, to our knowledge, pan-cancer study of metastatic solid tumour genomes, including whole-genome sequencing data for 2,520 pairs of tumour and normal tissue, analysed at median depths of 106x and 38x, respectively, and surveying more than 70 million somatic variants. The characteristic mutations of metastatic lesions varied widely, with mutations that reflect those of the primary tumour types, and with high rates of whole-genome duplication events (56%). Individual metastatic lesions were relatively homogeneous, with the vast majority (96%) of driver mutations being clonal and up to 80% of tumour-suppressor genes being inactivated bi-allelically by different mutational mechanisms. Although metastatic tumour genomes showed similar mutational landscape and driver genes to primary tumours, we find characteristics that could contribute to responsiveness to therapy or resistance in individual patients. We implement an approach for the review of clinically relevant associations and their potential for actionability. For 62% of patients, we identify genetic variants that may be used to stratify patients towards therapies that either have been approved or are in clinical trials. This demonstrates the importance of comprehensive genomic tumour profiling for precision medicine in cancer