Demo Data from VLDB 2026 / reviewers in the wild / expert
Ali Rana Atilgan
dblp:97/8193
· DBLP profile ↗
5ranked-venue papers
0as first author
1since 2021 · last 2025
0000-0003-0604-6301ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 4Systems, architecture and hardware · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
2 papers |
Bioinformatics and computational biology · 57% Computational science and engineering · 43% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational science and engineering › computational chemistry › molecular simulation › molecular dynamics
molecular dynamics analysis |
0.6 | 2 | 2018 | MODE-TASK: large-scale protein motion tools · Bioinform. 2018 MD-TASK: a software suite for analyzing molecular dynamics trajectories · Bioinform. 2017 |
Bioinformatics and computational biology › protein dynamics
protein dynamics analysis |
0.3 | 1 | 2018 | MODE-TASK: large-scale protein motion tools · Bioinform. 2018 |
Bioinformatics and computational biology › structural biology › protein structure and function
protein structure and dynamics |
0.3 | 1 | 2018 | MODE-TASK: large-scale protein motion tools · Bioinform. 2018 |
Bioinformatics and computational biology
structural bioinformatics |
0.3 | 1 | 2017 | MD-TASK: a software suite for analyzing molecular dynamics trajectories · Bioinform. 2017 |
Computational science and engineering › computational chemistry › molecular simulation
molecular dynamics |
0.1 | 1 | 2017 | MD-TASK: a software suite for analyzing molecular dynamics trajectories · Bioinform. 2017 |
Methods — techniques the papers use, named apart from their topics
t-distributed stochastic neighbor embedding · 0.3principal component analysis · 0.3normal mode analysis · 0.3multidimensional scaling · 0.3anisotropic network model · 0.3perturbation response scanning · 0.3graph theory · 0.3dynamic cross-correlation · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | High Throughput Mutational Scanning of a Protein via Alchemistry on a High-Performance Computing ResourceabstractABSTRACT Antibiotic resistance presents a significant challenge to public health, as bacteria can develop resistance to antibiotics through random mutations during their life cycles, making the drugs ineffective. Understanding how these mutations contribute to drug resistance at the molecular level is crucial for designing new treatment approaches. Recent advancements in molecular biology tools have made it possible to conduct comprehensive analyses of protein mutations. Computational methods for assessing molecular fitness, such as binding energies, are not as precise as experimental techniques like deep mutational scanning. Although full atomistic alchemical free energy calculations offer the necessary precision, they are seldom used to assess high throughput data as they require significantly more computational resources. We generated a computational library using deep mutational scanning for dihydrofolate reductase (DHFR), a protein commonly studied in antibiotic resistance research. Due to resource limitations, we analyzed 33 out of 159 positions, identifying 16 single amino acid replacements. Calculations were conducted for DHFR in its drug‐free state and in the presence of two different inhibitors. We demonstrate the feasibility of such calculations, made possible due to the enhancements in computational resources and their optimized use. Tandac F. Guclu, Busra Tayhan, Ebru Çetin, Ali Rana Atilgan, Canan Atilgan |
Concurr. Comput. Pract. Exp. | 4 |
| 2018 | MODE-TASK: large-scale protein motion toolsabstractSummary: MODE-TASK, a novel and versatile software suite, comprises Principal Component Analysis, Multidimensional Scaling, and t-Distributed Stochastic Neighbor Embedding techniques using Molecular Dynamics trajectories. MODE-TASK also includes a Normal Mode Analysis tool based on Anisotropic Network Model so as to provide a variety of ways to analyse and compare large-scale motions of protein complexes for which long MD simulations are prohibitive. Beside the command line function, a GUI has been developed as a PyMOL plugin. Availability and implementation: MODE-TASK is open source, and available for download from https://github.com/RUBi-ZA/MODE-TASK. It is implemented in Python and C++. It is compatible with Python 2.x and Python 3.x and can be installed by Conda. Supplementary information: Supplementary data are available at Bioinformatics online. Caroline J. Ross, Bilal Nizami, Michael Glenister, Olivier Sheik Amamuddy, Ali Rana Atilgan, Canan Atilgan, Özlem Tastan Bishop |
Bioinform. | 5 |
| 2017 | MD-TASK: a software suite for analyzing molecular dynamics trajectoriesabstractSUMMARY: Molecular dynamics (MD) determines the physical motions of atoms of a biological macromolecule in a cell-like environment and is an important method in structural bioinformatics. Traditionally, measurements such as root mean square deviation, root mean square fluctuation, radius of gyration, and various energy measures have been used to analyze MD simulations. Here, we present MD-TASK, a novel software suite that employs graph theory techniques, perturbation response scanning, and dynamic cross-correlation to provide unique ways for analyzing MD trajectories. AVAILABILITY AND IMPLEMENTATION: MD-TASK has been open-sourced and is available for download from https://github.com/RUBi-ZA/MD-TASK , implemented in Python and supported on Linux/Unix. CONTACT: [email protected]. David K. Brown, David L. Penkler, Olivier Sheik Amamuddy, Caroline J. Ross, Ali Rana Atilgan, Canan Atilgan, Özlem Tastan Bishop |
Bioinform. | 5 |
| 2013 | Designing Molecular Dynamics Simulations to Shift Populations of the Conformational States of CalmodulinabstractWe elucidate the mechanisms that lead to population shifts in the conformational states of calcium-loaded calmodulin (Ca(2+)-CaM). We design extensive molecular dynamics simulations to classify the effects that are responsible for adopting occupied conformations available in the ensemble of NMR structures. Electrostatic interactions amongst the different regions of the protein and with its vicinal water are herein mediated by lowering the ionic strength or the pH. Amino acid E31, which is one of the few charged residues whose ionization state is highly sensitive to pH differences in the physiological range, proves to be distinctive in its control of population shifts. E31A mutation at low ionic strength results in a distinct change from an extended to a compact Ca(2+)-CaM conformation within tens of nanoseconds, that otherwise occur on the time scales of microseconds. The kinked linker found in this particular compact form is observed in many of the target-bound forms of Ca(2+)-CaM, increasing the binding affinity. This mutation is unique in controlling C-lobe dynamics by affecting the fluctuations between the EF-hand motif helices. We also monitor the effect of the ionic strength on the conformational multiplicity of Ca(2+)-CaM. By lowering the ionic strength, the tendency of nonspecific anions in water to accumulate near the protein surface increases, especially in the vicinity of the linker. The change in the distribution of ions in the vicinal layer of water allows N- and C- lobes to span a wide variety of relative orientations that are otherwise not observed at physiological ionic strength. E31 protonation restores the conformations associated with physiological environmental conditions even at low ionic strength. Ayse Ozlem Aykut, Ali Rana Atilgan, Canan Atilgan |
PLoS Comput. Biol. | 2 |
| 2009 | Perturbation-Response Scanning Reveals Ligand Entry-Exit Mechanisms of Ferric Binding ProteinabstractWe study apo and holo forms of the bacterial ferric binding protein (FBP) which exhibits the so-called ferric transport dilemma: it uptakes iron from the host with remarkable affinity, yet releases it with ease in the cytoplasm for subsequent use. The observations fit the "conformational selection" model whereby the existence of a weakly populated, higher energy conformation that is stabilized in the presence of the ligand is proposed. We introduce a new tool that we term perturbation-response scanning (PRS) for the analysis of remote control strategies utilized. The approach relies on the systematic use of computational perturbation/response techniques based on linear response theory, by sequentially applying directed forces on single-residues along the chain and recording the resulting relative changes in the residue coordinates. We further obtain closed-form expressions for the magnitude and the directionality of the response. Using PRS, we study the ligand release mechanisms of FBP and support the findings by molecular dynamics simulations. We find that the residue-by-residue displacements between the apo and the holo forms, as determined from the X-ray structures, are faithfully reproduced by perturbations applied on the majority of the residues of the apo form. However, once the stabilizing ligand (Fe) is integrated to the system in holo FBP, perturbing only a few select residues successfully reproduces the experimental displacements. Thus, iron uptake by FBP is a favored process in the fluctuating environment of the protein, whereas iron release is controlled by mechanisms including chelation and allostery. The directional analysis that we implement in the PRS methodology implicates the latter mechanism by leading to a few distant, charged, and exposed loop residues. Upon perturbing these, irrespective of the direction of the operating forces, we find that the cap residues involved in iron release are made to operate coherently, facilitating release of the ion. Canan Atilgan, Ali Rana Atilgan |
PLoS Comput. Biol. | 2 |