Search NASA⌕ Search

DOE OSTI · 1627421

APBSmem: A Graphical Interface for Electrostatic Calculations at the Membrane

Abstract

Electrostatic forces are one of the primary determinants of molecular interactions. They help guide the folding of proteins, increase the binding of one protein to another and facilitate protein-DNA and protein-ligand binding. A popular method for computing the electrostatic properties of biological systems is to numerically solve the Poisson-Boltzmann (PB) equation, and there are several easy-to-use software packages available that solve the PB equation for soluble proteins. Here we present a freely available program, called APBSmem, for carrying out these calculations in the presence of a membrane. The Adaptive Poisson-Boltzmann Solver (APBS) is used as a back-end for solving the PB equation, and a Java-based graphical user interface (GUI) coordinates a set of routines that introduce the influence of the membrane, determine its placement relative to the protein, and set the membrane potential. The software Jmol is embedded in the GUI to visualize the protein inserted in the membrane before the calculation and the electrostatic potential after completing the computation. We expect that the ease with which the GUI allows one to carry out these calculations will make this software a useful resource for experimenters and computational researchers alike. Three examples of membrane protein electrostatic calculations are carried out to illustrate how to use APBSmem and to highlight the different quantities of interest that can be calculated.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Callenberg, Keith M., Choudhary, Om P., de Forest, Gabriel L., Gohara, David W., Baker, Nathan A., Grabe, Michael. 2010-09-29. APBSmem: A Graphical Interface for Electrostatic Calculations at the Membrane. https://doi.org/10.1371/journal.pone.0012722

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

Soil metagenomics umbrella narrative

Implementing accessible, authentic research experiences in introductory courses is challenging, particularly at institutions serving diverse student populations. To address this gap, we developed and deployed a Course-based Undergraduate Research Experience (CURE) focused on plant-microbe interactions in General Biology II at Northeastern Illinois University (NEIU), a minority-serving institution with a diverse student body. Students grew sugar beets (Beta vulgaris), extracted DNA from the rhizoplane, and used the Department of Energy Systems Biology Knowledgebase (KBase) for bioinformatic analysis to compare microbial relative abundance in fertilized versus unfertilized soil. Over five semesters, the CURE engaged 103 students and leveraged the intuitive KBase platform to make complex sequencing data accessible. Pre/post-course survey data revealed significant increases in student self-assessed research skills, including the ability to explain results and determine the types of data to collect. Furthermore, students reported significant gains in confidence related to experimental design and hypothesis development, alongside a strong increase in familiarity with KBase. Informal faculty feedback indicated high student engagement and appreciation for the real-world connections (e.g. food systems, agriculture, and health). This scalable, low-cost model effectively integrates data science tools into the foundational curriculum, demonstrating a potent strategy for boosting research skills and broadening participation in authentic scientific inquiry among diverse undergraduate students.

59 BASIC BIOLOGICAL SCIENCES↗

Genome-resolved insights into microbial diversity and elemental cycling in Winogradsky columns

We retained 18 MAGs with ≥50% completion and <10% contamination (i.e., at least medium quality). Of these, 10 had >90% completion and <5% contamination; however, only one (Paceibacteria Bin.003_MG) can be described as high-quality, as the others lacked a full suite of 5S, 16S, and 23S rRNA genes. To maximize the diversity of our recovered MAGs, we also retained one MAG (Chromatiaceae Bin.008_AM) with >40% (but less than 50%) completion and <5% contamination, as well as one (Rhodopseudomonas Bin.015_MK) with >90% completion and <20% (but>10%) contamination. Interestingly, significant chimerism was not detected in this MAG (40) , suggesting that the elevated contamination (20%) may instead reflect two closely related strains collapsing into a single bin. Consistent with this, contig coverage was bimodal, with roughly 17% of the assembly at ~115x and the remaining 83% at ~282x, while GC content remained uniform across both groups (~64%), arguing against contamination from a taxonomically distinct source.

59 BASIC BIOLOGICAL SCIENCES↗