1. Review of combinatorial searching in protein modeling: A. Perez, J.A. Morrone, & K. Dill. Accelerating physical simulations of proteins by leveraging external knowledge. WIREs Comput Mol Sci 125, e1309 (2017).
2. Peptides binding to proteins: J. A. Morrone et al. Molecular Simulations Identify Binding Poses and Approximate Affinities of Stapled α-Helical Peptides to MDM2 and MDMX. J Chem Theory Comput 13, 863–869 (2017).
3. Peptides binding to proteins: J. A. Morrone, A. Perez, J. MacCallum, & K. Dill.
Computed Binding of Peptides to Proteins with MELD-Accelerated Molecular Dynamics.
J Chem Theory Comput 13, 870–876 (2017).
4. MELD predictions of protein structures in the CASP event: A. Perez, J. A. Morrone, E. Brini, J. L. MacCallum, & K. Dill. Blind protein structure prediction using accelerated free-energy simulations. Science Advances 2, e1601274–e1601274 (2016).
5. Review of computational physical modeling of proteins: A. Perez, J. A. Morrone, C. Simmerling, & K. Dill. Advances in free-energy-based simulations of protein folding and ligand binding. Curr Opin Struct Biol 36, 25–31 (2016).
6. Tests and improvements of the SEA solvation model: E. Brini, S.S. Paranahewage, C.J. Fennell, K.A. Dill, Adapting the semi-explicit assembly solvation model for estimating water-cyclohexane partitioning with the SAMPL5 molecules. Journal of Computer-Aided Molecular Design, (2016).
7. Review of combinatorial search methods for biomolecules: A. Perez, J. L. MacCallum, E. A. Coutsias & K. Dill. Constraint methods that accelerate free-energy simulations of biomolecules. J Chem Phys 143, 243143 (2015).
8. Predicting small protein structures from sequences: A. Perez, J. L. MacCallum, & K. Dill. Accelerating molecular simulations of proteins using Bayesian inference on weak information. Proc Natl Acad Sci USA 112, 11846–11851 (2015).
9. Determining protein structures from limited data: J. L. MacCallum, A. Perez, & K. Dill. Determining protein structures by combining semireliable data with atomistic physical models by Bayesian inference. Proc Natl Acad Sci USA 112, 6985–6990 (2015).
10. SAMPL tests of the SEA solvation model: L. Li, K.A. Dill, C.J. Fennell, Testing the semi-explicit assembly model of aqueous solvation in the SAMPL4 challenge. J Comput Aided Mol Des., 28: 259-264 (2014).
11. Salt effects in the SEA solvation model: L. Li, C.J. Fennell, and K.A. Dill, Small molecule solvation changes due to the presence of salt are governed by the cost of solvent cavity formation and dispersion. J Chem Phys, 141: 22D518 (2014).
12. Fast and accurate SEA solvation model: C.J. Fennell, C.W. Kehoe, and K.A. Dill, Modeling aqueous solvation with semi-explicit assembly. Proc Natl Acad Sci USA, 108 (8): 3234-3239 (2011).
LauferWorks 