Analyzing Machupo virus-receptor binding by molecular dynamics simulations

In many biological applications, we would like to be able to computationally predict mutational effects on affinity in protein-protein interactions. However, many commonly used methods to predict these effects perform poorly in important test cases. In particular, the effects of multiple mutations, non-alanine substitutions, and flexible loops are difficult to predict with available tools and protocols. We present here an existing method applied in a novel way to a new test case; we interrogate affinity differences resulting from mutations in a host-virus protein-protein interface. We use steered molecular dynamics (SMD) to computationally pull the machupo virus (MACV) spike glycoprotein (GP1) away from the human transferrin receptor (hTfR1). We then approximate affinity using the maximum applied force of separation and the area under the force-versus-distance curve. We find, even without the rigor and planning required for free energy calculations, that these quantities can provide novel biophysical insight into the GP1/hTfR1 interaction. First, with no prior knowledge of the system we can differentiate among wild type and mutant complexes. Moreover, we show that this simple SMD scheme correlates well with relative free energy differences computed via free energy perturbation. Second, although the static co-crystal structure shows two large hydrogen-bonding networks in the GP1/hTfR1 interface, our simulations indicate that one of them may not be important for tight binding. Third, one viral site known to be critical for infection may mark an important evolutionary suppressor site for infection-resistant hTfR1 mutants. Finally, our approach provides a framework to compare the effects of multiple mutations, individually and jointly, on protein-protein interactions.Comment: 33 pages, 8 figures, 5 table

Improving Syntactic Relationships Between Language and Objects

This paper presents the integration of natural language processing and computer vision to improve the syntax of the language generated when describing objects in images. The goal was to not only understand the objects in an image, but the interactions and activities occurring between the objects. We implemented a multi-modal neural network combining convolutional and recurrent neural network architectures to create a model that can maximize the likelihood of word combinations given a training image. The outcome was an image captioning model that leveraged transfer learning techniques for architecture components. Our novelty was to quantify the effectiveness of transfer learning schemes for encoders and decoders to qualify which were the best for improving syntactic relationships. Our work found the combination of ResNet feature extraction and fine-tuned BERT word embeddings to be the best performing architecture across two datasets - a valuable discovery for those continuing this work considering the cost of compute for these complex models

Mining Patents with Large Language Models Demonstrates Congruence of Functional Labels and Chemical Structures

Predicting chemical function from structure is a major goal of the chemical sciences, from the discovery and repurposing of novel drugs to the creation of new materials. Recently, new machine learning algorithms are opening up the possibility of general predictive models spanning many different chemical functions. Here, we consider the challenge of applying large language models to chemical patents in order to consolidate and leverage the information about chemical functionality captured by these resources. Chemical patents contain vast knowledge on chemical function, but their usefulness as a dataset has historically been neglected due to the impracticality of extracting high-quality functional labels. Using a scalable ChatGPT-assisted patent summarization and word-embedding label cleaning pipeline, we derive a Chemical Function (CheF) dataset, containing 100K molecules and their patent-derived functional labels. The functional labels were validated to be of high quality, allowing us to detect a strong relationship between functional label and chemical structural spaces. Further, we find that the co-occurrence graph of the functional labels contains a robust semantic structure, which allowed us in turn to examine functional relatedness among the compounds. We then trained a model on the CheF dataset, allowing us to assign new functional labels to compounds. Using this model, we were able to retrodict approved Hepatitis C antivirals, uncover an antiviral mechanism undisclosed in the patent, and identify plausible serotonin-related drugs. The CheF dataset and associated model offers a promising new approach to predict chemical functionality.Comment: Under revie

Periodic solutions and refractory periods in the soliton theory for nerves and the locust femoral nerve

Close to melting transitions it is possible to propagate solitary electromechanical pulses which reflect many of the experimental features of the nerve pulse including mechanical dislocations and reversible heat production. Here we show that one also obtains the possibility of periodic pulse generation when the boundary condition for the nerve is the conservation of the overall length of the nerve. This condition generates an undershoot beneath the baseline (`hyperpolarization') and a `refractory period', i.e., a minimum distance between pulses. In this paper, we outline the theory for periodic solutions to the wave equation and compare these results to action potentials from the femoral nerve of the locust (locusta migratoria). In particular, we describe the frequently occurring minimum-distance doublet pulses seen in these neurons and compare them to the periodic pulse solutions.Comment: 10 pages, 6 Figure

Proteomic and functional analyses of the virion transmembrane proteome of cyprinid herpesvirus 3

Virion transmembrane proteins (VTPs) mediate key functions in the herpesvirus infectious cycle. Cyprinid herpesvirus 3 (CyHV-3) is the archetype of fish alloherpesviruses. The present study was devoted to CyHV-3 VTPs. Using mass spectrometry approaches, we identified 16 VTPs of the CyHV-3 FL strain. Mutagenesis experiments demonstrated that eight of these proteins are essential for viral growth in vitro (ORF32, ORF59, ORF81, ORF83, ORF99, ORF106, ORF115, and ORF131), and eight are non-essential (ORF25, ORF64, ORF65, ORF108, ORF132, ORF136, ORF148, and ORF149). Among the non-essential proteins, deletion of ORF25, ORF132, ORF136, ORF148, or ORF149 affects viral replication in vitro, and deletion of ORF25, ORF64, ORF108, ORF132, or ORF149 impacts plaque size. Lack of ORF148 or ORF25 causes attenuation in vivo to a minor or major extent, respectively. The safety and efficacy of a virus lacking ORF25 were compared to those of a previously described vaccine candidate deleted for ORF56 and ORF57 (Δ56-57). Using quantitative PCR, we demonstrated that the ORF25 deleted virus infects fish through skin infection and then spreads to internal organs as reported previously for the wild-type parental virus and the Δ56-57 virus. However, compared to the parental wild-type virus, the replication of the ORF25 deleted virus was reduced in intensity and duration to levels similar to those observed for the Δ56-57 virus. Vaccination of fish with a virus lacking ORF25 was safe but had low efficacy at the doses tested. This characterization of the virion transmembrane proteome of CyHV-3 provides a firm basis for further research on alloherpesvirus VTPs. IMPORTANCE Virion transmembrane proteins play key roles in the biology of herpesviruses. Cyprinid herpesvirus 3 (CyHV-3) is the archetype of fish alloherpesviruses and the causative agent of major economic losses in common and koi carp worldwide. In this study of the virion transmembrane proteome of CyHV-3, the major findings were: (i) the FL strain encodes 16 virion transmembrane proteins; (ii) eight of these proteins are essential for viral growth in vitro; (iii) seven of the non-essential proteins affect viral growth in vitro, and two affect virulence in vivo; and (iv) a mutant lacking ORF25 is highly attenuated but induces moderate immune protection. This study represents a major breakthrough in understanding the biology of CyHV-3 and will contribute to the development of prophylactic methods. It also provides a firm basis for the further research on alloherpesvirus virion transmembrane proteins

Adaptive rationality: An evolutionary perspective on cognitive bias

A casual look at the literature in social cognition reveals a vast collection of biases, errors, violations of rational choice, and failures to maximize utility. One is tempted to draw the conclusion that the human mind is woefully muddled. We present a three-category evolutionary taxonomy of evidence of biases: biases are (a) heuristics, (b) error management effects, or (c) experimental artifacts. We conclude that much of the research on cognitive biases can be profitably reframed and understood in evolutionary terms. An adaptationist perspective suggests that the mind is remarkably well designed for important problems of survival and reproduction, and not fundamentally irrational. Our analysis is not an apologia intended to place the rational mind on a pedestal for admiration. Rather, it promises practical outcomes including a clearer view of the architecture of systems for judgment and decision making, and exposure of clashes between adaptations designed for the ancestral past and the demands of the present

Complex Spatial Dynamics of Oncolytic Viruses In Vitro: Mathematical and Experimental Approaches

Oncolytic viruses replicate selectively in tumor cells and can serve as targeted treatment agents. While promising results have been observed in clinical trials, consistent success of therapy remains elusive. The dynamics of virus spread through tumor cell populations has been studied both experimentally and computationally. However, a basic understanding of the principles underlying virus spread in spatially structured target cell populations has yet to be obtained. This paper studies such dynamics, using a newly constructed recombinant adenovirus type-5 (Ad5) that expresses enhanced jellyfish green fluorescent protein (EGFP), AdEGFPuci, and grows on human 293 embryonic kidney epithelial cells, allowing us to track cell numbers and spatial patterns over time. The cells are arranged in a two-dimensional setting and allow virus spread to occur only to target cells within the local neighborhood. Despite the simplicity of the setup, complex dynamics are observed. Experiments gave rise to three spatial patterns that we call “hollow ring structure”, “filled ring structure”, and “disperse pattern”. An agent-based, stochastic computational model is used to simulate and interpret the experiments. The model can reproduce the experimentally observed patterns, and identifies key parameters that determine which pattern of virus growth arises. The model is further used to study the long-term outcome of the dynamics for the different growth patterns, and to investigate conditions under which the virus population eliminates the target cells. We find that both the filled ring structure and disperse pattern of initial expansion are indicative of treatment failure, where target cells persist in the long run. The hollow ring structure is associated with either target cell extinction or low-level persistence, both of which can be viewed as treatment success. Interestingly, it is found that equilibrium properties of ordinary differential equations describing the dynamics in local neighborhoods in the agent-based model can predict the outcome of the spatial virus-cell dynamics, which has important practical implications. This analysis provides a first step towards understanding spatial oncolytic virus dynamics, upon which more detailed investigations and further complexity can be built

Solid-supported iodonium salts for fluorinations

Solid-supported iodonium salt precursors have been prepared and used for the production of fluoroarenes. The importance of the resin functionality for the attachment of the iodonium salt moieties has been demonstrated. Furthermore, the production of new iodonium salt precursors for fluorination has been achieved by an alternative and improved method with respect to those previously described. The successful radiofluorination of a simple solid-supported precursor with no-carrier-added (n.c.a.) [18F]fluoride shows the suitability of the method for the production of useful PET synthons

Sequential multi-locus transcranial magnetic stimulation for treatment of obsessive-compulsive disorder with comorbid major depression: A case series

Obsessive-compulsive disorder (OCD) and major depressive disorder (MDD) are highly comorbid [1], with depressive symptoms amplifying the chronicity and severity of OCD symptoms. Comorbid illness decreases quality of life and daily functioning [2] and is associated with greater suicidality and more frequent inpatient hospitalizations [3]. Furthermore, comorbid OCD/depression is associated with poorer response to OCD-focused psychological and pharmacological treatments [4]. Epidemiologic studies have shown that OCD symptoms generally precedes the occurrence of depression, suggesting a causal interacting model in which OCD predisposes to development of depressive symptoms [5]. In line with that causal model, Tadayonnejad et al. showed aberrant effective (directional) connectivity between OCD and MDD circuits may be a potential network mechanism of depressive symptom genesis or worsening in OCD-MDD [6]. The challenging nature of this comorbidity necessitates the development of novel, more effective treatments

Sequential multi-locus transcranial magnetic stimulation for treatment of obsessive-compulsive disorder with comorbid major depression: A case series

Obsessive-compulsive disorder (OCD) and major depressive disorder (MDD) are highly comorbid [1], with depressive symptoms amplifying the chronicity and severity of OCD symptoms. Comorbid illness decreases quality of life and daily functioning [2] and is associated with greater suicidality and more frequent inpatient hospitalizations [3]. Furthermore, comorbid OCD/depression is associated with poorer response to OCD-focused psychological and pharmacological treatments [4]. Epidemiologic studies have shown that OCD symptoms generally precedes the occurrence of depression, suggesting a causal interacting model in which OCD predisposes to development of depressive symptoms [5]. In line with that causal model, Tadayonnejad et al. showed aberrant effective (directional) connectivity between OCD and MDD circuits may be a potential network mechanism of depressive symptom genesis or worsening in OCD-MDD [6]. The challenging nature of this comorbidity necessitates the development of novel, more effective treatments