Eugene I. Shakhnovich

Molecular Biology · 1989–2019

A researcher in the Science corpus: 15 papers; trusts 28 researchers and is trusted by 25 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 120 citations into it; #5,530 of 17,773 by trust here, #8,570 by citations
• Genetics — 39 citations into it; #950 of 6,854 by trust here, #2,712 by citations
• Materials Chemistry — 18 citations into it
• Computational Biology & Bioinformatics — 14 citations into it; #336 of 660 by trust here, #579 by citations
• Computational Theory and Mathematics — 11 citations into it
• Spectroscopy — 10 citations into it
• Computational Chemistry & Drug Discovery — 5 citations into it; #233 of 425 by trust here, #285 by citations
• Plant Science — 5 citations into it

Whom Eugene I. Shakhnovich trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Stephen L. Mayo
2. S. Miyazawa
3. Konstantin B. Zeldovich
4. Robert L. Jernigan
5. Manfred J. Sippl
6. Jay W. Ponder
7. Richard A. Goldstein
8. Leonid A. Mirny
9. Mark A. DePristo
10. C. Scott Wylie

Who trusts Eugene I. Shakhnovich overall

1. Changyu Hu
2. Leonid A. Mirny
3. Sahand Hormoz
4. S. Miyazawa
5. Jae-Shick Yang
6. Adrian W. R. Serohijos
7. Michael Feig
8. Xiang Li
9. Konstantin B. Zeldovich
10. S. Bershtein

Papers from Eugene I. Shakhnovich's perspective

Ordered by how strongly the researchers Eugene I. Shakhnovich trusts endorse each paper. Same corpus, a different order for every researcher.

1. SCOP: a structural classification of proteins database for the investigation of sequences and structures.
2. Estimation of effective interresidue contact energies from protein crystal structures: quasi-chemical approximation
3. A method to identify protein sequences that fold into a known three-dimensional structure.
4. Missense meanderings in sequence space: a biophysical view of protein evolution
5. CHARMM: A program for macromolecular energy, minimization, and dynamics calculations
6. Calculation of conformational ensembles from potentials of mean force. An approach to the knowledge-based prediction of local structures in globular proteins.
7. A new approach to protein fold recognition
8. Residue-residue potentials with a favorable contact pair term and an unfavorable high packing density term, for simulation and threading.
9. Engineering of stable and fast-folding sequences of model proteins.
10. Protein stability promotes evolvability.

Their papers

• Protein folding thermodynamics and dynamics: where physics, chemistry, and biology meet. (2006) — 345 citations
• All-atom ab initio folding of a diverse set of proteins. (2006) — 94 citations
• Merging molecular mechanism and evolution: theory and computation at the interface of biophysics and evolutionary population genetics (2014) — 82 citations
• Positive and Negative Design in Stability and Thermal Adaptation of Natural Proteins (2006) — 138 citations
• Soluble oligomerization provides a beneficial fitness effect on destabilizing mutations (2011) — 106 citations
• A biophysical protein folding model accounts for most mutational fitness effects in viruses (2011) — 193 citations
• Protein and DNA Sequence Determinants of Thermophilic Adaptation (2006) — 317 citations
• Common activation mechanism of class A GPCRs (2019) — 453 citations
• Protein stability imposes limits on organism complexity and speed of molecular evolution (2007) — 266 citations
• Protein design: a perspective from simple tractable models (1998)
• How to derive a protein folding potential? A new approach to an old problem. (1996)
• SMoG: de Novo Design Method Based on Simple, Fast, and Accurate Free Energy Estimates. 1. Methodology and Supporting Evidence (1996)
• Engineering of stable and fast-folding sequences of model proteins. (1993)
• Implications of thermodynamics of protein folding for evolution of primary sequences (1990)
• Formation of unique structure in polypeptide chains. Theoretical investigation with the aid of a replica approach. (1989)