SearcharxivSearch

arXiv subjects

Pengzhi Zhang

Publications and source records attributed to Pengzhi Zhang.

3 recordsLinked to original sources

Chemistry-informed Machine Learning Explains Calcium-binding Proteins Fuzzy Shape for Communicating Changes in the Atomic States of Calcium Ions

Proteins' fuzziness are features for communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. Binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit, but it is unclear whether the limited experimental data available can be used to train models to accurately predict the charges of calcium-binding protein variants. Here, we developed a chemistry-informed, machine-learning algorithm that implements a game theoretic approach to explain the output of a machine-learning model without the prerequisite of an excessively large database for high-performance prediction of atomic charges. We used the ab initio electronic structure data representing calcium ions and the structures of the disordered segments of calcium-binding peptides with surrounding water molecules to train several explainable models. Network theory was used to extract the topological features of atomic interactions in the structurally complex data dictated by the coordination chemistry of a calcium ion, a potent indicator of its charge state in protein. With our designs, we provided a framework of explainable machine learning model to annotate atomic charges of calcium ions in calcium-binding proteins with domain knowledge in response to the chemical changes in an environment based on the limited size of scientific data in a genome space.

q-bio.QM

CTRAMER: An open source software package for correlating interfacial charge transfer rate constants with donor acceptor geometries in organic photovoltaic materials

In this paper we present CTRAMER (Charge Transfer RAtes from Molecular dynamics, Electronic structure, and Rate theory), an open source software package for calculating interfacial charge transfer (CT) rate constants in organic photovoltaic (OPV) materials based on ab initio calculations and molecular dynamics simulations. The software is based on identifying representative donor acceptor geometries within interfacial structures obtained from molecular dynamics simulation of donor acceptor blends and calculating the corresponding Fermi s golden rule CT rate constants within the framework of the linearized semiclassical approximation. While the methods used are well established, the integration of these state of the art ideas from different disciplines to study photoinduced CT between excited states and explicit environment, in our opinion, makes this package unique and innovative. The software also provides tools for plotting other observables of interest. After outlining the features and implementation details, usage and performance of the software are demonstrated with results from an example OPV system.

cond-mat.mtrl-sci

Determining the atomic charge of calcium ion requires the information of its coordination geometry in an EF-hand motif

It is challenging to parameterize the force field for calcium ions (Ca2+) in calcium-binding proteins because of their unique coordination chemistry that involves the surrounding atoms required for stability. In this work, we observed wide variation in Ca2+ binding loop conformations of the Ca2+-binding protein calmodulin (CaM), which adopts the most populated ternary structures determined from the MD simulations, followed by ab initio quantum mechanical (QM) calculations on all twelve amino acids in the loop that coordinate Ca2+ in aqueous solution. Ca2+ charges were derived by fitting to the electrostatic potential (ESP) in the context of a classical or polarizable force field (PFF). We discovered that the atomic radius of Ca2+ in conventional force fields is too large for the QM calculation to capture the variation in the coordination geometry of Ca2+ in its ionic form, leading to unphysical charges. Specifically, we found that the fitted atomic charges of Ca2+ in the context of PFF depend on the coordinating geometry of electronegative atoms from the amino acids in the loop. Although nearby water molecules do not influence the atomic charge of Ca2+, they are crucial for compensating for the coordination of Ca2+ due to the conformational flexibility in the EF-hand loop. Our method advances the development of force fields for metal ions and protein binding sites in dynamic environments.

q-bio.BM