Deciphering complex mechanisms of resistance and loss of potency through coupled molecular dynamics and machine learning [preprint]

Drug resistance threatens many critical therapeutics through mutations in the drug target. The molecular mechanisms by which combinations of mutations, especially involving those distal from the active site, alter drug binding to confer resistance are poorly understood and thus difficult to counteract. A strategy coupling parallel molecular dynamics simulations and machine learning to identify conserved mechanisms underlying resistance was developed. A series of 28 HIV-1 protease variants with up to 24 varied substitutions were used as a rigorous model of this strategy. Many of the mutations were distal from the active site and the potency to darunavir varied from low pM to near μM. With features extracted from molecular dynamics simulations, elastic network machine learning was applied to correlate physical interactions at the molecular level with potency loss. This fit to within 1 kcal/mol of experimental potency for both the training and test sets, outperforming MM/GBSA calculations. Feature reduction resulted in a model with 4 specific features that correspond to interactions critical for potency regardless of enzyme variant. These predictive features throughout the enzyme would not have been identified without dynamics and machine learning and specifically varied with potency. This approach enables capturing the conserved dynamic molecular mechanisms by which complex combinations of mutations confer resistance and identifying critical interactions which serve as bellwethers over a wide range of inhibitor potency. Machine learning models leveraging molecular dynamics can thus elucidate mechanisms that confer loss of affinity due to variations distal from the active site, such as in drug resistance

An Adversarial Dance: Toward an Understanding of Insiders’ Responses to Organizational Information Security Measures

Despite the increased focus on organizational security policies and programs, some employees continue to engage in maladaptive responses to security measures (i.e., behaviors other than those recommended, intended, or prescribed). To help shed light on insiders’ adaptive and maladaptive responses to IS security measures, we conducted a case study of an organization at the forefront of security policy initiatives. Drawing on the beliefs-actions-outcomes (BAO) model to analyze our case data, we uncover a potentially nonvirtuous cycle consisting of security-related beliefs, actions, and outcomes, which we refer to as an “adversarial dance.” Explaining our results, we describe a novel belief framework that identifies four security belief profiles and uncovers an underexplored outcome of IS security: insiders’ lived security experiences. We find that individuals’ unfavorable lived security experiences produce counterproductive security-related beliefs that, in turn, lead to maladaptive behaviors. Maladaptive behaviors create new potential for security risk, leading to increased organizational security measures to counter them. Thus, the adversarial dance continues, as the new security measures have the potential to reinforce counterproductive security-related beliefs about the importance and risk of IS security and lead to new maladaptive behaviors. To help situate our findings within the current security literature, we integrate the results with prior research based on extant theories. While this paper is not the first to suggest that security measures can elicit maladaptive behaviors, the emergent belief framework and expanded BAO model of IS security constitute an important contribution to the behavioral IS security literature

Interdependence of Inhibitor Recognition in HIV-1 Protease

Molecular recognition is a highly interdependent process. Subsite couplings within the active site of proteases are most often revealed through conditional amino acid preferences in substrate recognition. However, the potential effect of these couplings on inhibition and thus inhibitor design is largely unexplored. The present study examines the interdependency of subsites in HIV-1 protease using a focused library of protease inhibitors, to aid in future inhibitor design. Previously a series of darunavir (DRV) analogs was designed to systematically probe the S1\u27 and S2\u27 subsites. Co-crystal structures of these analogs with HIV-1 protease provide the ideal opportunity to probe subsite interdependency. All-atom molecular dynamics simulations starting from these structures were performed and systematically analyzed in terms of atomic fluctuations, intermolecular interactions, and water structure. These analyses reveal that the S1\u27 subsite highly influences other subsites: the extension of the hydrophobic P1\u27 moiety results in 1) reduced van der Waals contacts in the P2\u27 subsite, 2) more variability in the hydrogen bond frequencies with catalytic residues and the flap water, and 3) changes in the occupancy of conserved water sites both proximal and distal to the active site. In addition, one of the monomers in this homodimeric enzyme has atomic fluctuations more highly correlated with DRV than the other monomer. These relationships intricately link the HIV-1 protease subsites and are critical to understanding molecular recognition and inhibitor binding. More broadly, the interdependency of subsite recognition within an active site requires consideration in the selection of chemical moieties in drug design; this strategy is in contrast to what is traditionally done with independent optimization of chemical moieties of an inhibitor

Towards Controlling the Acceptance Factors for a Collaborative Platform in Engineering Design

International audienceThis paper might serve as a guide to take step towards a better acceptance of computer-based Knowledge management (KM) tools in institutional setting. At first time, it investigates a set of factors with different origins which are proved to have an effect on usage decision. Secondly, we set a list of candidate factor which are supposed to influence future users of a collaborative KM platform (Dimocode). At the end, we develop a methodology to take into account the selected factors and master their positive or negative impacts. The contents of this paper would be an appropriate framework in the way of Knowledge management systems (KMS) deployment

The Added Complications of Climate Change: Understanding and Managing Biodiversity, Ecosystems, and Ecosystem Services Under Multiple Stressors.

Ecosystems around the world are already threatened by land-use and land-cover change, extraction of natural resources, biological disturbances, and pollution. These environmental stressors have been the primary source of ecosystem degradation to date, and climate change is now exacerbating some of their effects. Ecosystems already under stress are likely to have more rapid and acute reactions to climate change; it is therefore useful to understand how multiple stresses will interact, especially as the magnitude of climate change increases. Understanding these interactions could be critically important in the design of climate adaptation strategies, especially because actions taken by other sectors (eg energy, agriculture, transportation) to address climate change may create new ecosystem stresses

Emotions in business-to-business service relationships

Emotion in business-to-business service relationships regarding cargo services is explored. The service relationship is characterised by mutual trust and cooperation. Contact is mainly via telephone or e-mail with some face-to-face interactions and participants providing a complex, multi-skilled seamless service. Experience rather than training plays a vital role with long-term service relationships built up and maintained. Emotional sensitivity is acquired partly by experience and a repeat customer base but mainly through a genuine desire to help and get to know others. In contrast to the view of emotional labour bringing managerial control or adverse affects to service staff, the emotion engendered by this work is authentic expression bringing personal satisfaction

STING expression and response to treatment with STING ligands in premalignant and malignant disease.

Human papilloma virus positive (HPV+) tumors represent a large proportion of anal, vulvar, vaginal, cervical and head and neck squamous carcinomas (HNSCC) and late stage invasive disease is thought to originate from a premalignant state. Cyclic dinucleotides that activate STimulator of INterferon Genes (STING) have been shown to cause rapid regression of a range of advanced tumors. We aimed to investigate STING ligands as a novel treatment for papilloma. We tested therapies in a spontaneous mouse model of papilloma of the face and anogenital region that histologically resembles human HPV-associated papilloma. We demonstrate that STING ligands cause rapid regression of papilloma, associated with T cell infiltration, and are significantly more effective than Imiquimod, a current immunotherapy for papilloma. In humans, we show that STING is expressed in the basal layer of normal skin and lost during keratinocyte differentiation. We found STING was expressed in all HPV-associated cervical and anal dysplasia and was strongly expressed in the cancer cells of HPV+ HNSCC but not in HPV-unrelated HNSCC. We found no strong association between STING expression and progressive disease in non-HPV oral dysplasia and oral pre-malignancies that are not HPV-related. These data demonstrate that STING is expressed in basal cells of the skin and is retained in HPV+ pre-malignancies and advanced cancers, but not in HPV-unrelated HNSCC. However, using a murine HNSCC model that does not express STING, we demonstrate that STING ligands are an effective therapy regardless of expression of STING by the cancer cells

Multiparametric immune profiling in HPV- oral squamous cell cancer.

Evaluation of T lymphocyte frequency provides prognostic information for patients with oral squamous cell cancer (OSCC). However, the effect of simultaneously evaluating T cell frequency and assessing suppressive elements and defects in antigen-processing machinery (APM) has not been clarified. Simultaneous characterization of CD3+, CD8+, FoxP3+, CD163+, and PD-L1+ cells using multispectral imaging was performed on sections from 119 patients with HPV- OSCC. Expression of β2-microglobulin, MHC class I heavy chain, and large multifunctional peptidase 10 was quantified, and all data were correlated with patient outcome. We found that, consistent with previous reports, high numbers of CD8+ T cells at the invasive margin correlated significantly with prolonged overall survival (OS), while the number of FoxP3+ or PD-L1+ cells did not. Compiling the number of FoxP3+ or PD-L1+ cells within 30 μm of CD8+ T cells identified a significant association with a high number of suppressive elements close to CD8+ T cells and reduced OS. Integrating this information into a cumulative suppression index (CSI) increased correlation with OS. Incorporating tumor expression levels of APM components with CSI further improved prognostic power. This multiparametric immune profiling may be useful for stratifying patients with OSCC for clinical trials

Pay progression in routinised service sector work: navigating the internal labour market in a fast food multinational company

The United Kingdom's widespread use of low‐skill, low‐paid employment has been well documented. It has been argued internal labour markets (ILMs) benefit such workers, affording them with opportunities for progression. Relatively little is known, however, about the impact of ILMs on entry level workers undertaking routinised service sector work. Drawing on qualitative data, this article explores the prospects on offer in a market leading, fast food multinational company. Potential enabling features include on‐the‐job training, a transparent and integrated pay structure and a professed culture of progression. Occupational movements to positions above the low‐pay threshold are, however, relatively rare. We conjecture this contradiction is the result of the business context in which the firm operates. The findings suggest that in sectors where price leadership strategies dominate, escape from low pay is likely to be exceptional, even within large organisations featuring some of the classic characteristics of ‘pure’ or strong ILMs