RESP2: An uncertainty aware multi-target multi-property optimization AI pipeline for antibody discovery.

Discovery of therapeutic antibodies against infectious disease pathogens presents distinct challenges. Ideal candidates must possess not only the properties required for any therapeutic antibody (e.g.

TUnA: an uncertainty-aware transformer model for sequence-based protein-protein interaction prediction.

Protein-protein interactions (PPIs) are important for many biological processes, but predicting them from sequence data remains challenging. Existing deep learning models often cannot generalize to proteins not present in the training set and do not provide uncertainty estimates for their predictions. To address these limitations, we present TUnA, a Transformer-based uncertainty-aware model for PPI prediction.

For antibody sequence generative modeling, mixture models may be all you need.

Motivation: Antibody therapeutic candidates must exhibit not only tight binding to their target but also good developability properties, especially low risk of immunogenicity.

Results: In this work, we fit a simple generative model, SAM, to sixty million human heavy and seventy million human light chains. We show that the probability of a sequence calculated by the model distinguishes human sequences from other species with the same or better accuracy on a variety of benchmark datasets containing >400 million sequences than any other model in the literature, outperforming large language models (LLMs) by large margins.

Linear-Scaling Kernels for Protein Sequences and Small Molecules Outperform Deep Learning While Providing Uncertainty Quantitation and Improved Interpretability.

Gaussian process (GP) is a Bayesian model which provides several advantages for regression tasks in machine learning such as reliable quantitation of uncertainty and improved interpretability. Their adoption has been precluded by their excessive computational cost and by the difficulty in adapting them for analyzing sequences (e.g.

The association between ventriculostomy - Related infection and clinical outcomes: A systematic review and meta-analysis.

Background: Ventriculostomy - related infection (VRI) is a common complication of patients who require placement of an external ventricular drain (EVD). The clinical outcomes of people who are diagnosed with VRI is poorly characterised. We performed a systematic review and meta-analysis to assess the association between VRI, and clinical outcomes and resource use, in patients treated with an EVD.

The RESP AI model accelerates the identification of tight-binding antibodies.

High-affinity antibodies are often identified through directed evolution, which may require many iterations of mutagenesis and selection to find an optimal candidate. Deep learning techniques hold the potential to accelerate this process but the existing methods cannot provide the confidence interval or uncertainty needed to assess the reliability of the predictions. Here we present a pipeline called RESP for efficient identification of high affinity antibodies.

Engineering human JMJD2A tudor domains for an improved understanding of histone peptide recognition.

JMJD2A is a histone lysine demethylase which recognizes and demethylates H3K9me3 and H3K36me3 residues and is overexpressed in various cancers. It utilizes a tandem tudor domain to facilitate its own recruitment to histone sites, recognizing various di- and tri-methyl lysine residues with moderate affinity. In this study, we successfully engineered the tudor domain of JMJD2A to specifically bind to H4K20me3 with a 20-fold increase of affinity and improved selectivity.

Selection of QPX7831, an Orally Bioavailable Prodrug of Boronic Acid β-Lactamase Inhibitor QPX7728.

In recognition of the need for effective oral therapies to treat Gram-negative bacterial infections, efforts were directed toward identifying an oral prodrug of β-lactamase inhibitor clinical candidate QPX7728. Seventeen prodrugs were synthesized; key properties investigated were rates of cleavage to the active form in vitro, pharmacokinetics across species, and crystallinity. Compound (QPX7831 Sodium) emerged with optimal properties across all key attributes.

The promise of graphene-based transistors for democratizing multiomics studies.

As biological research has synthesized genomics, proteomics, metabolomics, and transcriptomics into systems biology, a new multiomics approach to biological research has emerged. Today, multiomics studies are challenging and expensive. An experimental platform that could unify the multiple omics approaches to measurement could increase access to multiomics data by enabling more individual labs to successfully attempt multiomics studies.

Rapid and Electronic Identification and Quantification of Age-Specific Circulating Exosomes via Biologically Activated Graphene Transistors.

Increasing access to modern clinical practices concomitantly extends lifespan, ironically revealing new classes of degenerative and inflammatory diseases of later years. Here, an electronic graphene field-effect transistor (gFET) is reported, termed EV-chip, for label-free, rapid identification and quantification of exosomes (EV) associated with aging through specific surface markers, CD63 and CD151. Studies suggest that blood-derived exosomes carry specific biomolecules that can be used toward diagnostic applications of age and health.

Engineering a Histone Reader Protein by Combining Directed Evolution, Sequencing, and Neural Network Based Ordinal Regression.

Directed evolution is a powerful approach for engineering proteins with enhanced affinity or specificity for a ligand of interest but typically requires many rounds of screening/library mutagenesis to obtain mutants with desired properties. Furthermore, mutant libraries generally only cover a small fraction of the available sequence space. Here, for the first time, we use ordinal regression to model protein sequence data generated through successive rounds of sorting and amplification of a protein-ligand system.

Discovery of Cyclic Boronic Acid QPX7728, an Ultrabroad-Spectrum Inhibitor of Serine and Metallo-β-lactamases.

Despite major advances in the β-lactamase inhibitor field, certain enzymes remain refractory to inhibition by agents recently introduced. Most important among these are the class B (metallo) enzyme NDM-1 of Enterobacteriaceae and the class D (OXA) enzymes of . Continuing the boronic acid program that led to vaborbactam, efforts were directed toward expanding the spectrum to allow treatment of a wider range of organisms.

Activity of Simulated Human Dosage Regimens of Meropenem and Vaborbactam against Carbapenem-Resistant Enterobacteriaceae in an Hollow-Fiber Model.

The objective of these studies was to evaluate the exposures of meropenem and vaborbactam that would produce antibacterial activity and prevent resistance development in carbapenem-resistant carbapenemase (KPC)-producing strains when tested at an inoculum of 10 CFU/ml. Thirteen isolates, three isolates, and one isolate were examined in an hollow-fiber model over 32 h. Simulated dosage regimens of 1 to 2 g of meropenem with 1 to 2 g of vaborbactam, with meropenem administered every 8 h by a 3-h infusion based on phase 1 or phase 3 patient pharmacokinetic data, were studied in the model.

Activity of Meropenem-Vaborbactam in Mouse Models of Infection Due to KPC-Producing Carbapenem-Resistant Enterobacteriaceae.

Meropenem-vaborbactam (Vabomere) is highly active against Gram-negative pathogens, especially carbapenemase (KPC)-producing, carbapenem-resistant The objective of these studies was to evaluate the efficacy of meropenem alone and in combination with vaborbactam in mouse thigh and lung infection models. Thighs or lungs of neutropenic mice were infected with KPC-producing carbapenem-resistant , with meropenem MICs ranging from ≤0.06 to 8 mg/liter in the presence of 8 mg/liter vaborbactam.

Survival Outcomes of Elderly Patients With Glioblastoma Multiforme in Their 75th Year or Older Treated With Adjuvant Therapy.

Purpose: To assess the outcomes of the most elderly cohort of patients with a diagnosis of glioblastoma multiforme (GBM) after intensity modulated radiation therapy (IMRT).

Methods And Materials: The data of patients with GBM who had underwent IMRT from May 2007 to December 2015 were entered into a prospective database. Analysis was performed on the data from patients diagnosed during or after 75 years of age.