Directed protein evolution is central to biomedical applications but faces challenges such as experimental complexity, inefficient multiproperty optimization, and local maxima traps. Although in silico methods that use protein language models (PLMs) can provide modeled fitness landscape guidance, they struggle to generalize across diverse protein families and map to protein activity. We present EVOLVEpro, a few-shot active learning framework that combines PLMs and regression models to rapidly improve protein activity. EVOLVEpro surpasses current methods, yielding up to 100-fold improvements in desired properties. We demonstrate its effectiveness across six proteins in RNA production, genome editing, and antibody binding applications. These results highlight the advantages of few-shot active learning with minimal experimental data over zero-shot predictions. EVOLVEpro opens new possibilities for artificial intelligence–guided protein engineering in biology and medicine.

Discovery of point mutations in the genes encoding isocitrate dehydrogenases (IDH) in gliomas about a decade ago has challenged our view of the role of metabolism in tumor progression and provided a new stratification strategy for malignant gliomas. IDH enzymes catalyze the conversion of isocitrate to alpha-ketoglutarate (α-KG), an intermediate in the citric acid cycle. Specific mutations in the genes encoding IDHs cause neomorphic enzymatic activity that produces D-2-hydroxyglutarate (2-HG) and result in the inhibition of α-KG-dependent enzymes such as histone and DNA demethylases. Thus, chromatin structure and gene expression profiles in IDH-mutant gliomas appear to be different from those in IDH-wildtype gliomas. IDH mutations are highly common in lower grade gliomas (LGG) and secondary glioblastomas, and they are among the earliest genetic events driving tumorigenesis. Therefore, inhibition of mutant IDH enzymes in LGGs is widely accepted as an attractive therapeutic strategy. On the other hand, the metabolic consequences derived from IDH mutations lead to selective vulnerabilities within tumor cells, making them more sensitive to several therapeutic interventions. Therefore, instead of shutting down mutant IDH enzymes, exploiting the selective vulnerabilities caused by them might be another attractive and promising strategy. Here, we review therapeutic options and summarize current preclinical and clinical studies on IDH-mutant gliomas.

Programmable RNA-guided DNA nucleases perform numerous roles in prokaryotes, but the extent of their spread outside prokaryotes is unclear. Fanzors, the eukaryotic homolog of prokaryotic TnpB proteins, have been detected in genomes of eukaryotes and large viruses, but their activity and functions in eukaryotes remain unknown. Here, we characterize Fanzors as RNA-programmable DNA endonucleases, using biochemical and cellular evidence. We found diverse Fanzors that frequently associate with various eukaryotic transposases. Reconstruction of Fanzors evolution revealed multiple radiations of RuvC-containing TnpB homologs in eukaryotes. Fanzor genes captured introns and proteins acquired nuclear localization signals, indicating extensive, long-term adaptation to functioning in eukaryotic cells. Fanzor nucleases contain a rearranged catalytic site of the RuvC domain, similar to a distinct subset of TnpBs, and lack collateral cleavage activity. We demonstrate that Fanzors can be harnessed for genome editing in human cells, highlighting the potential of these widespread eukaryotic RNA-guided nucleases for biotechnology applications.

Small molecule inhibitors have previously been investigated in different studies as possible therapeutics in the treatment of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). In the current drug repurposing study, we identified the leukotriene (D4) receptor antagonist montelukast as a novel agent that simultaneously targets two important drug targets of SARS-CoV-2. We initially demonstrated the dual inhibition profile of montelukast through multiscale molecular modeling studies. Next, we characterized its effect on both targets by different in vitro experiments including the enzyme (main protease) inhibition-based assay, surface plasmon resonance (SPR) spectroscopy, pseudovirus neutralization on HEK293T/hACE2+TMPRSS2, and virus neutralization assay using xCELLigence MP real-time cell analyzer. Our integrated in silico and in vitro results confirmed the dual potential effect of montelukast both on the main protease enzyme inhibition and virus entry into the host cell (spike/ACE2). The virus neutralization assay results showed that SARS-CoV-2 virus activity was delayed with montelukast for 20 h on the infected cells. The rapid use of new small molecules in the pandemic is very important today. Montelukast, whose pharmacokinetic and pharmacodynamic properties are very well characterized and has been widely used in the treatment of asthma since 1998, should urgently be completed in clinical phase studies and, if its effect is proved in clinical phase studies, it should be used against coronavirus disease 2019 (COVID-19).

Dysregulation of the epigenome due to alterations in chromatin modifier proteins commonly contribute to malignant transformation. To interrogate the roles of epigenetic modifiers in cancer cells, we generated an epigenome-wide CRISPR-Cas9 knockout library (EPIKOL) that targets a wide-range of epigenetic modifiers and their cofactors. We conducted eight screens in two different cancer types and showed that EPIKOL performs with high efficiency in terms of sgRNA distribution and depletion of essential genes. We discovered novel epigenetic modifiers that regulate triple-negative breast cancer (TNBC) and prostate cancer cell fitness. We confirmed the growth-regulatory functions of individual candidates, including SS18L2 and members of the NSL complex (KANSL2, KANSL3, KAT8) in TNBC cells. Overall, we show that EPIKOL, a focused sgRNA library targeting ~800 genes, can reveal epigenetic modifiers that are essential for cancer cell fitness under in vitro and in vivo conditions and enable the identification of novel anti-cancer targets. Due to its comprehensive epigenome-wide targets and relatively high number of sgRNAs per gene, EPIKOL will facilitate studies examining functional roles of epigenetic modifiers in a wide range of contexts, such as screens in primary cells, patient-derived xenografts as well as in vivo models.