Jernigan Group

Jernigan Laboratory

Welcome to Jernigan lab website!

Our primary focus is on computations on cells, proteins, nucleic acids, and small molecules, and their interactions. Often we work at the interface between sequence and structure and on the relationship between dynamics and mechanism.  In this latter case we often use simple models to improve comprehension of mechanisms. We often perform datamining and data analyses.

We are located at Department of Biochemistry, Biophysics, and Molecular Biology at Iowa State University Ames, Iowa. Our research is pushing toward the comprehension of the functions of and mechanisms of larger structures, and the use of large, diverse data to construct models of these.

Jernigan's research background:

  • Mining information from protein structures and using it to evaluate predicted structures – Miyazawa-Jernigan potentials, elastic network deformations of structures, protein and ribosome mechanism.
  • Knowledgeable about a wide variety of research subjects, from the physical sciences to the biological sciences, from biomedicine to genomics, with a broad view of basic and applied research.
  • A recognized authority in computational and structural biology, with broader interests in bioinformatics, genomics, structural biology, protein engineering and sub-cellular biology
  • High impact publications – 1 paper ~ 1900 citations, and 49 papers with > 100 citations each
  • 20,000+ citations, h-index 67
  • Fellow, AAAS
  • Fellow, Biophysical Society
  • Book “Protein Actions” 2018 PROSE award for best textbook in the biological and life sciences.
Medical and evolution applications

Medical and Evolution Applications

Higher Order Correlations in Biology

Higher Order Correlations in Biology

Dynamics and Mechanisms

Dynamics and Mechanisms

Current Projects

  • Improving Protein Sequence Matching
  • Understanding Protein Packing
  • Improved Protein Potentials - especially Entropies
  • Understanding Protein Mutants - Discriminating Bad from Good
  • Protein Engineering
  • Protein Mechanism from Dynamics
  • Simplifying and Improving Protein Calculations
  • Many-Body Correlations from Sequences
  • Connecting Sequence Correlations to Dynamics
Protein language model

Protein Language Model Performs Remote Homolog Detection

Detection of a Remote Homolog for HPO30 and Validation with Predicted Structure Comparison. (a) Alignment of HPO30 and human homolog Q8NCR9 found by PLAST. Sequence identity is 21.5%, with gap ratio of 32.8%. Identical residues are colored based on chemical features. (b) Structure matching of the two Alphafold2 predicted structures of HPO30 (red) and CLRN3 (blue) human homolog that is found by PLAST. Structural alignment of 160 core residues has RSMD = 3.4 Å.


News release about our new Bioenergy Grant 

New grant from NIH-HGRI Novel Use of Genome Information to Understand Mutations

Grant from NIH-NIGMS Protein Sequence Matching

Sayane Shome (recent PhD grad) to Stanford Medicine as a postdoc in the lab of Nima Aghaeepour!

Pranav Khade (recent PhD grad) to St. Jude's Children's Research Hospital as a postdoc.

4/29/22  Pranav Khade wins Research Excellence Award (REX).

An interview with Ben Litterer (undergrad researcher in our lab) in an ISU LAS publication.

Kejue Jia and Mesih Kilinc just completed in one day a massive multiple sequence algnment of 100,000 protein sequences!  The first of many to come....


Presenting keynote lecture at ISMB/ISCB COSI 3DSIG in Madison, WI on July 13

2 lectures:

Unprecedented Opportunities for Datamining of Protein Sequences and Structures

Unprecedented Opportunities for Careers in Protein Science