Pharmaceutical-Grade Rigosertib Is a Microtubule-Destabilizing Agent.

We recently used CRISPRi/a-based chemical-genetic screens and cell biological, biochemical, and structural assays to determine that rigosertib, an anti-cancer agent in phase III clinical trials, kills cancer cells by destabilizing microtubules. Reddy and co-workers (Baker et al., 2020, this issue of Molecular Cell) suggest that a contaminating degradation product in commercial formulations of rigosertib is responsible for the microtubule-destabilizing activity. Here, we demonstrate that cells treated with pharmaceutical-grade rigosertib (>99.9% purity) or commercially obtained rigosertib have qualitatively indistinguishable phenotypes across multiple assays. The two formulations have indistinguishable chemical-genetic interactions with genes that modulate microtubule stability, both destabilize microtubules in cells and in vitro, and expression of a rationally designed tubulin mutant with a mutation in the rigosertib binding site (L240F TUBB) allows cells to proliferate in the presence of either formulation. Importantly, the specificity of the L240F TUBB mutant for microtubule-destabilizing agents has been confirmed independently. Thus, rigosertib kills cancer cells by destabilizing microtubules, in agreement with our original findings.

Combined CRISPRi/a-Based Chemical Genetic Screens Reveal that Rigosertib Is a Microtubule-Destabilizing Agent.

Chemical libraries paired with phenotypic screens can now readily identify compounds with therapeutic potential. A central limitation to exploiting these compounds, however, has been in identifying their relevant cellular targets. Here, we present a two-tiered CRISPR-mediated chemical-genetic strategy for target identification: combined genome-wide knockdown and overexpression screening as well as focused, comparative chemical-genetic profiling. Application of these strategies to rigosertib, a drug in phase 3 clinical trials for high-risk myelodysplastic syndrome whose molecular target had remained controversial, pointed singularly to microtubules as rigosertib's target. We showed that rigosertib indeed directly binds to and destabilizes microtubules using cell biological, in vitro, and structural approaches. Finally, expression of tubulin with a structure-guided mutation in the rigosertib-binding pocket conferred resistance to rigosertib, establishing that rigosertib kills cancer cells by destabilizing microtubules. These results demonstrate the power of our chemical-genetic screening strategies for pinpointing the physiologically relevant targets of chemical agents.

A robust platform for integrative spatial multi-omics analysis to map immune responses to SARS-CoV-2 infection in lung tissues.

The SARS-CoV-2 (COVID-19) virus has caused a devastating global pandemic of respiratory illness. To understand viral pathogenesis, methods are available for studying dissociated cells in blood, nasal samples, bronchoalveolar lavage fluid and similar, but a robust platform for deep tissue characterization of molecular and cellular responses to virus infection in the lungs is still lacking. We developed an innovative spatial multi-omics platform to investigate COVID-19-infected lung tissues. Five tissue-profiling technologies were combined by a novel computational mapping methodology to comprehensively characterize and compare the transcriptome and targeted proteome of virus infected and uninfected tissues. By integrating spatial transcriptomics data (Visium, GeoMx and RNAScope) and proteomics data (CODEX and PhenoImager HT) at different cellular resolutions across lung tissues, we found strong evidence for macrophage infiltration and defined the broader microenvironment surrounding these cells. By comparing infected and uninfected samples, we found an increase in cytokine signalling and interferon responses at different sites in the lung and showed spatial heterogeneity in the expression level of these pathways. These data demonstrate that integrative spatial multi-omics platforms can be broadly applied to gain a deeper understanding of viral effects on cellular environments at the site of infection and to increase our understanding of the impact of SARS-CoV-2 on the lungs.

MILCDock: Machine Learning Enhanced Consensus Docking for Virtual Screening in Drug Discovery.

Molecular docking tools are regularly used to computationally identify new molecules in virtual screening for drug discovery. However, docking tools suffer from inaccurate scoring functions with widely varying performance on different proteins. To enable more accurate ranking of active over inactive ligands in virtual screening, we created a machine learning consensus docking tool, MILCDock, that uses predictions from five traditional molecular docking tools to predict the probability a ligand binds to a protein. MILCDock was trained and tested on data from both the DUD-E and LIT-PCBA docking datasets and shows improved performance over traditional molecular docking tools and other consensus docking methods on the DUD-E dataset. LIT-PCBA targets proved to be difficult for all methods tested. We also find that DUD-E data, although biased, can be effective in training machine learning tools if care is taken to avoid DUD-E's biases during training.

Evaluation of Deep Neural Network ProSPr for Accurate Protein Distance Predictions on CASP14 Targets.

The field of protein structure prediction has recently been revolutionized through the introduction of deep learning. The current state-of-the-art tool AlphaFold2 can predict highly accurate structures; however, it has a prohibitively long inference time for applications that require the folding of hundreds of sequences. The prediction of protein structure annotations, such as amino acid distances, can be achieved at a higher speed with existing tools, such as the ProSPr network. Here, we report on important updates to the ProSPr network, its performance in the recent Critical Assessment of Techniques for Protein Structure Prediction (CASP14) competition, and an evaluation of its accuracy dependency on sequence length and multiple sequence alignment depth. We also provide a detailed description of the architecture and the training process, accompanied by reusable code. This work is anticipated to provide a solid foundation for the further development of protein distance prediction tools.

Considerations for Incision and Flap Design With Implant Therapy in the Esthetic Zone.

The planning and design of any incision in the esthetic zone should be carried out based on biologic principles and with careful consideration of the desired esthetic outcome. Different incision and flap designs have been identified for implant and implant-related surgeries in the esthetic zone. Those include; flapless, vestibular incision, papilla sparing, envelope, triangular, and trapezoidal. The specific aim of this article is to outline various important factors that influence healing, to discuss the advantages/disadvantages of several key incision/flap designs, and to help guide the clinician in treatment planning tooth replacement in the esthetic zone.

Detecting selection in immunoglobulin sequences.

The ability to detect selection by analyzing mutation patterns in experimentally derived immunoglobulin (Ig) sequences is a critical part of many studies. Such techniques are useful not only for understanding the response to pathogens, but also to determine the role of antigen-driven selection in autoimmunity, B cell cancers and the diversification of pre-immune repertoires in certain species. Despite its importance, quantifying selection in experimentally derived sequences is fraught with difficulties. The necessary parameters for statistical tests (such as the expected frequency of replacement mutations in the absence of selection) are non-trivial to calculate, and results are not easily interpretable when analyzing more than a handful of sequences. We have developed a web server that implements our previously proposed Focused binomial test for detecting selection. Several features are integrated into the web site in order to facilitate analysis, including V(D)J germline segment identification with IMGT alignment, batch submission of sequences and integration of additional test statistics proposed by other groups. We also implement a Z-score-based statistic that increases the power of detecting selection while maintaining specificity, and further allows for the combined analysis of sequences from different germlines. The tool is freely available at http://clip.med.yale.edu/selection.

A probabilistic view of protein stability, conformational specificity, and design.

Various approaches have used neural networks as probabilistic models for the design of protein sequences. These "inverse folding" models employ different objective functions, which come with trade-offs that have not been assessed in detail before. This study introduces probabilistic definitions of protein stability and conformational specificity and demonstrates the relationship between these chemical properties and the [Formula: see text] Boltzmann probability objective. This links the Boltzmann probability objective function to experimentally verifiable outcomes. We propose a novel sequence decoding algorithm, referred to as "BayesDesign", that leverages Bayes' Rule to maximize the [Formula: see text] objective instead of the [Formula: see text] objective common in inverse folding models. The efficacy of BayesDesign is evaluated in the context of two protein model systems, the NanoLuc enzyme and the WW structural motif. Both BayesDesign and the baseline ProteinMPNN algorithm increase the thermostability of NanoLuc and increase the conformational specificity of WW. The possible sources of error in the model are analyzed.

Training undergraduate research assistants with an outcome-oriented and skill-based mentoring strategy.

Effective mentoring of undergraduate students is a growing requirement for the promotion of faculty at many universities. It is often challenging for young investigators to define a successful mentoring strategy, partially due to the absence of a broadly accepted definition of what mentoring should entail. To overcome this, an outcome-oriented mentoring framework was developed and used with more than 25 students over three years. It was found that a systematic mentoring approach can help students quickly realize their scientific potential and result in meaningful contributions to science. This report especially shows how the Critical Assessment of Protein Structure Prediction (CASP14) challenge was used to amplify student research efforts. As a result of this challenge, multiple publications, presentations and scholarships were awarded to the participating students. The mentoring framework continues to see much success in allowing undergraduate students, including students from underrepresented groups, to foster scientific talent and make meaningful contributions to the scientific community.

Modified Lip Repositioning with Esthetic Crown Lengthening: A Combined Approach to Treating Excessive Gingival Display.

Lip repositioning surgery to address excessive gingival display induced by different etiologies has received major attention recently. Several techniques and variations have been reported, including myotomy or repositioning of the levator labii superioris muscle, Le Fort impaction, maxillary gingivectomies, botulinum toxin injections, and lip stabilization. This study reports a case of excessive gingival display treated by a modified combined approach. A 25-year-old woman with a 4- to 8-mm gingival display when smiling caused by a combination of short clinical crowns induced by an altered passive eruption and hypermobility of the upper lip underwent a staged esthetic crown-lengthening procedure followed by a modified lip repositioning technique. A description of the technique and a comparison with other modes of therapy is discussed. This modified approach for treating the hypermobile lip included a bilateral removal of a partial-thickness strip of mucosa from the maxillary buccal vestibule without severing the muscle, leaving the midline frenum intact and suturing the lip mucosa to the mucogingival line. The narrower vestibule and increased tooth length resulted in a symmetric and pleasing gingival display when smiling that remained stable over time. With proper diagnosis and sequence of therapy, modified lip repositioning surgery combined with esthetic crown lengthening can be used predictably to treat excessive gingival display and enhance smile esthetics.

Novel Approach to Managing Malsequenced and Malpositioned Immediately Placed Implants in the Esthetic Zone.

Esthetic implant therapy can be challenging in the anterior maxilla, and meticulous treatment is often required to deliver optimal esthetics. Close collaboration between surgical and prosthetic team members using the novel approach of prosthetic crown lengthening helped camouflage a shallow implant platform location, providing the proper gingival frame for esthetic restorations. This case report presents an interdisciplinary approach that included ridge augmentation, second-stage crown lengthening, and prosthetic soft tissue manipulation to address an implant placed too shallow in the alveolus of an extraction socket.

Reduced expression of gamma interferon in serum and marked lymphoid depletion induced by Porphyromonas gingivalis increase murine morbidity and mortality due to cytomegalovirus infection.

Porphyromonas gingivalis, a gram-negative anaerobe, is a major etiological agent of severe forms of periodontal disease. Although periodontal disease is considered a localized disease, accumulating evidence indicates that it may lead to a predisposition to a decline in immunocompetence. Human cytomegalovirus (CMV) commonly infects all human populations without producing significant clinical symptoms. Immunocompromised patients usually develop a primary or reactivated CMV infection, which is associated with high rates of morbidity and mortality. The aim of this study was to determine whether P. gingivalis increases animal susceptibility to CMV infection. Mice were inoculated with CMV and infected locally with P. gingivalis 3 days after the virus inoculation. Mortality rates were monitored, and traces of viral DNA and bacterial infection were detected systemically by using real-time PCR. Local and systemic cytokine secretion was measured, and histological sections were used to assess the pathological state of infected organs. P. gingivalis- and CMV-coinfected mice showed dramatically higher mortality rates than mice infected with P. gingivalis or CMV only. Although the organs of coinfected mice exhibited decreased viral titers, distinct necrosis and tissue damage were more evident in the livers and spleens of these mice than in those of mice infected with CMV only. Furthermore, systemic gamma interferon levels were decreased in coinfected mice, and marked lymphoid depletion was observed in their necrotic organs. In parallel control Escherichia coli-CMV coinfection experiments, the mortality and pathological results were the same as those found in mice infected with CMV only. Our results suggest a specific influence of P. gingivalis on the mouse immune response, causing increased susceptibility to CMV infection.