A5037059090- RNA and protein synthesis mechanisms
- Protein Structure and Dynamics
- RNA modifications and cancer
- DNA and Nucleic Acid Chemistry
- Computational Drug Discovery Methods
- RNA Research and Splicing
- Chemical Synthesis and Analysis
- Machine Learning in Materials Science
- Enzyme Structure and Function
- Advanced biosensing and bioanalysis techniques
- Mass Spectrometry Techniques and Applications
- Genomics and Phylogenetic Studies
- Genetics, Bioinformatics, and Biomedical Research
- Advanced NMR Techniques and Applications
- Fungal and yeast genetics research
- Bacteriophages and microbial interactions
- Mosquito-borne diseases and control
- Cancer-related molecular mechanisms research
- Metabolomics and Mass Spectrometry Studies
- Chemical Thermodynamics and Molecular Structure
- Iron Metabolism and Disorders
- Chromosomal and Genetic Variations
- Bacterial Genetics and Biotechnology
- Child Nutrition and Water Access
- Plant biochemistry and biosynthesis
University of Michigan
2016-2025
Arrakis Therapeutics (United States)
2023-2024
University of California, Irvine
2009-2023
Brooklyn College
2006-2013
City University of New York
2006-2013
The Graduate Center, CUNY
2006-2013
Nymirum (United States)
2013
Princeton University
1984
Association for Asian Studies
1984
We describe a strategy for constructing atomic resolution dynamical ensembles of RNA molecules, spanning up to millisecond timescales, that combines molecular dynamics (MD) simulations with NMR residual dipolar couplings (RDC) measured in elongated RNA. The are generated via Monte Carlo procedure by selecting snap-shot from an MD trajectory reproduce experimentally RDCs. Using this approach, we construct two variants the transactivation response element (TAR) containing three (HIV-1) and...
The ribosome utilizes hydrogen bonding between mRNA codons and aminoacyl-tRNAs to ensure rapid accurate protein production. Chemical modification of nucleobases can adjust the strength pattern this alter synthesis. We investigate how N1-methylpseudouridine (m
Molecular dynamics (MD) simulations can be a powerful tool for modeling complex dissociative processes such as ligand unbinding. However, many biologically relevant occur on timescales that far exceed the of typical MD simulations. Here, we implement and apply an enhanced sampling method in which specific energy terms potential function are selectively "scaled" to accelerate events during Using unbinding example process, scaled up ligand-water interactions attempt increase rate After...
Determining the three-dimensional (3D) structures of ribonucleic acid (RNA)-small molecule ligand complexes is critical to understanding molecular recognition in RNA. Computer docking can, principle, be used predict 3D structure RNA-small complexes. Unfortunately, retrospective analysis has shown that scoring functions are typically for pose prediction tend misclassify non-native poses as native and vice versa. Here, we use machine learning train a set classifiers estimate relative...
ABSTRACT Tandem repeat (TR) regions are common in yeast adhesins, but their structures unknown, and activities poorly understood. TR Candida albicans Als proteins conserved glycosylated 36-residue sequences with cell-cell aggregation activity (J. M. Rauceo, R. De Armond, H. Otoo, P. C. Kahn, S. A. Klotz, N. K. Gaur, Lipke, Eukaryot. Cell 5:1664–1673, 2006). Ab initio modeling either Rosetta or LINUS generated consistent of three-stranded antiparallel β-sheet domains, whereas randomly...
The development of methods for predicting NMR chemical shifts with high accuracy and speed is increasingly allowing use these abundant, readily accessible measurements in determining the structure dynamics proteins. For nucleic acids, however, despite availability semiempirical (1)H shifts, their has not yet been examined. Here, we show that offer powerful restraints RNA determination, discrimination native from non-native states to within 2-4 Å, <3 Å when highly flexible residues are...
Multiprotein complexes are central to our understanding of cellular biology, as they play critical roles in nearly every biological process. Despite many impressive advances associated with structural characterization techniques, large and highly-dynamic protein too often refractory analysis by conventional, high-resolution approaches. To fill this gap, ion mobility-mass spectrometry (IM-MS) methods have emerged a promising approach for characterizing the structures challenging assemblies...
In recent years, peer-assisted learning has emerged as a new and effective medical education modality. Near-peer tutoring utilizes senior student serving an instructor to junior student. 2019, the University of California, Irvine, School Medicine (UCISOM) implemented near-peer model beginning with first-year anatomy physiology curricula. Following successful pilot program, UCISOM launched full-fledged program in 2020 named Collaborative Learning Communities (CLC) Medical Students Teachers....
We introduce a simple and fast approach for predicting RNA chemical shifts from interatomic distances that performs with an accuracy similar to existing predictors enables the first shift-restrained simulations of be carried out. Our analysis demonstrates applied restraints can effectively guide conformational sampling toward regions space are more consistent than initial coordinates used simulations. As such, our should widely applicable in mapping landscape RNAs via shift-guided molecular...
Enhanced sampling techniques are used to increase the frequency of "rare events" during computer simulations complex molecules. Although methods exist that allow accurate thermodynamics be recovered from enhanced simulations, recovering kinetics proves more challenging. Here we present an extrapolation approach allows reliable potential-scaled MD simulations. The approach, based on Kramers' rate theory, is simple and computationally efficient, without defining reaction coordinates. To test...
Here, we report the implementation and application of a simple, structure-aware framework to generate target-specific screening libraries. Our approach combines advances in generative artificial intelligence (AI) with conventional molecular docking explore chemical space conditioned on unique physicochemical properties active site biomolecular target. As demonstration, used our framework, which refer as sample-and-dock, construct focused libraries for cyclin-dependent kinase type-2 (CDK2)...
Proteins are often characterized in terms of their primary, secondary, tertiary, and quaternary structure. Algorithms such as define secondary structure proteins (DSSP) can automatically assign protein based on the backbone hydrogen-bonding pattern. However, assignment elements (SSEs) becomes a challenge when only Cα coordinates available. In this work, we present C-alpha output (PCASSO), fast accurate program for assigning SSEs using positions. PCASSO achieves ∼95% accuracy with respect to...
The use of NMR-derived chemical shifts in protein structure determination and prediction has received much attention, and, as such, many methods have been developed to predict from three-dimensional (3D) coordinates. In contrast, little attention paid predicting RNA Using the random forest machine learning approach, we RAMSEY, which is capable both (1)H protonated (13)C this report, introduce assess its accuracy, demonstrate sensitivity RAMSEY-predicted 3D structure.
The rapid and accurate calculation of solvent accessible surface area (SASA) is extremely useful in the energetic analysis biomolecules. For example, SASA models can be used to estimate transfer free energy associated with biophysical processes, when combined coarse‐grained simulations, particularly for accounting solvation effects within framework implicit models. In such cases, a fast accurate, residue‐wise predictor highly desirable. Here, we develop predictive model that estimates SASAs...
Given the demonstrated utility of coarse-grained modeling and simulations approaches in studying protein structure dynamics, developing methods that allow experimental observables to be directly recovered from models is great importance. In this work, we develop one such method enables backbone chemical shifts (1HN, 1Hα, 13Cα, 13C, 13Cβ, 15N) predicted Cα coordinates. We show our Cα-based method, LARMORCα, predicts with comparable accuracy some all-atom approaches. More importantly,...
Here, we describe the discovery of compounds that inhibit self-splicing in group II introns. Using docking calculations, targeted catalytic active site within Oceanobacillus iheyensis IIC intron and virtually screened a library lead-like compounds. From this initial virtual screen, identified three unique scaffolds splicing vitro. Additional tests revealed an analog lead scaffold inhibits intron-dependent manner. Furthermore, exhibited activity against from different class: yeast ai5γ IIB...
Identifying potential ligand binding cavities is a critical step in structure-based screening of biomolecular targets. Cavity mapping methods can detect such cavities; however, for ribonucleic acid (RNA) targets, determining which the detected are "ligandable" remains an unsolved challenge. In this study, we trained set machine learning classifiers to distinguish ligandable RNA from decoy cavities. Application our two independent test sets demonstrated that could recover decoys with AUC >...
The ribosome relies on hydrogen bonding interactions between mRNA codons and incoming aminoacyl-tRNAs to ensure rapid accurate protein production. inclusion of chemically modified bases into mRNAs has the potential alter strength pattern synthesis. We investigated how Nl-methylpseudouridine (m 1 Ψ) modification, commonly incorporated therapeutic vaccine sequences, influences ability react with cognate near-cognate tRNAs release factors. find that presence a single m Ψ does not substantially...