A5069497722- Protein Structure and Dynamics
- Chemical Synthesis and Analysis
- Computational Drug Discovery Methods
- Enzyme Structure and Function
- Machine Learning in Bioinformatics
- RNA and protein synthesis mechanisms
- Biochemical and Structural Characterization
- Advanced biosensing and bioanalysis techniques
- CRISPR and Genetic Engineering
- Mass Spectrometry Techniques and Applications
- Video Surveillance and Tracking Methods
- Advanced Vision and Imaging
- Force Microscopy Techniques and Applications
- Chemical Synthesis and Characterization
- Biosensors and Analytical Detection
- Advanced Text Analysis Techniques
- Genomics and Phylogenetic Studies
- Text and Document Classification Technologies
- Glycosylation and Glycoproteins Research
- Topic Modeling
- Advanced Electron Microscopy Techniques and Applications
- Advanced Image and Video Retrieval Techniques
- Monoclonal and Polyclonal Antibodies Research
- Inorganic Chemistry and Materials
University of Florida
2021-2024
Zero to Three
2022
Shenyang Aerospace University
2012
Carnegie Mellon University
2009
AlphaFold has revolutionized structural biology by predicting highly accurate structures of proteins and their complexes with peptides other proteins. However, for protein-peptide systems, we are also interested in identifying the highest affinity binder among a set candidate peptides. We present novel competitive binding assay using to predict receptor presence two For systems which individual well predicted, captures higher bound state, peptide unbound form statistical significance. test...
CRISPR-Cas-based diagnostics have the potential to elevate nucleic acid detection. CRISPR-Cas systems can be combined with a pre-amplification step in one-pot reaction simplify workflow and reduce carryover contamination. Here, we report an engineered Cas12b improved thermostability that falls within optimal temperature range (60°C–65°C) of reverse transcription-loop-mediated isothermal amplification (RT-LAMP). Using de novo structural analyses, introduce mutations wild-type BrCas12b tighten...
ABSTRACT Machine learning has revolutionized structural biology by solving the problem of predicting structures from sequence information. The community is pushing limits interpretability and application these algorithms beyond their original objective. Already, AlphaFold’s ability to predict bound conformations for complexes surpassed performance docking methods, especially protein-peptide binding. A key question methods differentiate binding affinities between several peptides that bind...
Abstract Peptides mediate up to 40% of protein interactions, their high specificity and ability bind in places where small molecules cannot make them potential drug candidates. However, predicting peptide–protein complexes remains more challenging than protein–protein or protein–small molecule part due the flexibility peptides have. In this review, we look at advances docking, molecular simulations machine learning tackle problems related such as structures, binding affinities even kinetics....
Abstract Peptide‐based drugs offer high specificity, potency, and selectivity. However, their inherent flexibility differences in conformational preferences between free bound states create unique challenges that have hindered progress effective drug discovery pipelines. The emergence of AlphaFold (AF) Artificial Intelligence (AI) presents new opportunities for enhancing peptide‐based discovery. We explore recent advancements facilitate a successful peptide pipeline, considering peptides'...
Peptides are prevalent in biology, mediating as many 40% of protein-protein interactions, and involved other cellular functions such transport signaling. Their ability to bind with high specificity make them promising therapeutical agents intermediate properties between small molecules large biologics. Beyond their biological role, peptides can be programmed self-assembly, they already being used for diverse oligonuclotide delivery, tissue regeneration or drugs. However, the transient nature...
Much of our understanding folding mechanisms comes from interpretations experimental ϕ and ψ value analysis, relating the differences in stability transition state ensemble (TSE) folded state. We introduce a unified approach combining simulations Bayesian inference to provide atomistic detail for mechanism proteins G L their mutants. Proteins fold similar topologies despite low sequence similarity, but differ pathways. A fast redesign protein G, NuG2, switches pathways folds through pathway...
We present new algorithms to classify structural ensembles of macromolecules based on the recently proposed extended similarity measures. Molecular dynamics provides a wealth information systems biological interest. As computer power increases, we capture larger and conformational transitions between states. Typically, clustering statistical mechanics treatment system identify relevant The key advantage our approach is that newly introduced indices reduce computational complexity assessing...
Cryo-electron microscopy data are becoming more prevalent and accessible at higher resolution levels, leading to the development of new computational tools determine atomic structure macromolecules. However, while existing adapted from X-ray crystallography suitable for highest-resolution maps, needed lower-resolution levels account map heterogeneity. In this article, we introduce CryoFold 2.0, an integrative physics-based approach that combines Bayesian inference ability handle multiple...
Abstract AlphaFold has revolutionized structural biology by predicting highly accurate structures of proteins and their complexes with peptides other proteins. However, for protein‐peptide systems, we are also interested in identifying the highest affinity binder among a set candidate peptides. We present novel competitive binding assay using to predict receptor presence two For systems which individual well predicted, captures higher bound state, peptide unbound form statistical...
AlphaFold2 (AF2) has revolutionized protein structure prediction. However, a common confusion lies in equating the
Latent Semantic Analysis (LSA) is a technology which used to analyze the latent concepts. LSA based on Vector Space Model (VSM) and statistics, it usually takes Singular Value Decomposition (SVD) as kernel algorithm. Always, increases scale of training data improve system performance. However, needs many extra operations, also generates too much cooccurrence paths are unreasonable between different features, problem noise will be serious disadvantage. This paper proposes new method called...
ABSTRACT We present new algorithms to classify structural ensembles of macromolecules, based on the recently proposed extended similarity measures. Molecular Dynamics provides a wealth information systems biologically interest. As computer power increases we capture larger and conformational transitions between states. Typically, clustering statistical mechanics treatment system identify relevant biological The key advantage our approach is that newly introduced similiarity indices reduce...
Abstract Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-based diagnostics have elevated nucleic acid detection in terms of sensitivity, specificity, and rapidity recent years. CRISPR-Cas systems can be combined with a pre-amplification step one-pot reaction to simplify workflow reduce carryover contamination. Here, we report an engineered Cas12b system from Brevibacillus (eBrCas12b) improved thermostability that falls within the optimal range (60-65°C) Reverse...
Multi-camera systems have been widely used in many video surveillance applications. When an event happens and is monitored across multiple cameras, it easy for expert to generate the corresponding spatial representation comprehend series of event. However, not trivial users new environment. With support from psychological evidences, we propose approach mimic generating pictorial-based mental images when a target moving views cameras. First conduct ball-rolling experiment compare this with...
ABSTRACT Much of our understanding folding mechanisms comes from interpretations experimental ϕ and ψ value analysis – relating the differences in stability transition state ensemble (TSE) folded state. We introduce a unified approach combining simulations Bayesian inference to provide atomistic detail for mechanism protein G, L their mutants. Protein G fold similar topologies despite low sequence similarity, but differ pathways. A fast redesign NuG2, switches pathways folds through pathway...