Barry D. Olafson

Fe and Ni AB initio effective potentials for use in molecular calculations

Abstract We present effective potentials to replace the Ar core electrons of Fe and Ni. These effective potentials are obtained from ab initio ground state wavefunctions of Fe and Ni and are tested by comparing with ab initio SCF calculations for excited states of Fe, Fe + , Fe 2+ , Fe 3+ , Ni, Ni + , Ni 2+ , and the FeH + molecule.

THEORETICAL STUDIES OF OXYGEN BINDING

We discussed the bonding of O2 to hemoglobin using results of ab initio calculations of idealized portions of the Hb molecule. The bond between Fe and O2 is formed by coupling a triplet state (intermediate spin state) of Fe to the triplet ground state of O2 (analogous to the bonding of O to O2 in ozone). The coordination sphere of the Fe reduces the energy separation between the quintet, triplet, and singlet states, making an intermediate spin state accessible for bond formation. This provides the mechanism by which an O2 molecule can easily and reversibly bind to Hb. Neither the diamagnetic (t2g) excited state of Fe nor the excited singlet state of O2 play a role in the formation of the FeO2 bond. We also discussed the role of the Fe intra-atomic exchange terms and show how they serve to store electronic energy upon bond formation. An example was given, illustrating how this stored electronic energy can then be used to drive enzymatic reactions. Metal atoms such as ferrous Fe are capable of existing in several distinct electronic configurations, depending upon the ligands. Our objective here has been to illustrate the different characteristics of these Fe configurations and to indicate why various axial ligands stabilize particular Fe configurations. In addition, we have sketched the type of orbital descriptions arising from theoretical wavefunctions and illustrated how to use these descriptions to predict chemical phenomena.

ProtaBank: A repository for protein design and engineering data

We present ProtaBank, a repository for storing, querying, analyzing, and sharing protein design and engineering data in an actively maintained and updated database. ProtaBank provides a format to describe and compare all types of protein mutational data, spanning a wide range of properties and techniques. It features a user‐friendly web interface and programming layer that streamlines data deposition and allows for batch input and queries. The database schema design incorporates a standard format for reporting protein sequences and experimental data that facilitates comparison of results across different data sets. A suite of analysis and visualization tools are provided to facilitate discovery, to guide future designs, and to benchmark and train new predictive tools and algorithms. ProtaBank will provide a valuable resource to the protein engineering community by storing and safeguarding newly generated data, allowing for fast searching and identification of relevant data from the existing literature, and exploring correlations between disparate data sets. ProtaBank invites researchers to contribute data to the database to make it accessible for search and analysis. ProtaBank is available at https://protabank.org.

SPINFAST: Using structure alignment profiles to enhance the accuracy and assess the reliability of protein side‐chain modeling

We present a novel, knowledge‐based method for the side‐chain addition step in protein structure modeling. The foundation of the method is a conditional probability equation, which specifies the probability that a side‐chain will occupy a specific rotamer state, given a set of evidence about the rotamer states adopted by the side‐chains at aligned positions in structurally homologous crystal structures. We demonstrate that our method increases the accuracy of homology model side‐chain addition when compared with the widely employed practice of preserving the side‐chain conformation from the homology template to the target at conserved residue positions. Furthermore, we demonstrate that our method accurately estimates the probability that the correct rotamer state has been selected. This interesting result implies that our method can be used to understand the reliability of each and every side‐chain in a protein homology model. Proteins 2006.