Biology subjects

Erman, B.

Publications and source records attributed to Erman, B..

26 records · Page 2Linked to original sources

bioRxiv2020

Comparative effects of oncogenic mutations G12C, G12V, G13D, and Q61H on local conformations and dynamics of K-Ras

K-Ras is the most frequently mutated protein in human cancers. However, until very recently, its oncogenic mutants were viewed as undruggable. To develop inhibitors that directly target oncogenic K-Ras mutants, we need to understand both their mutant-specific and pan-mutant dynamics and conformations. Recently, we have investigated how the most frequently observed K-Ras mutation in cancer patients, G12D, changes its local dynamics and conformations1. Here, we extend our analysis to study and compare the local effects of other frequently observed oncogenic mutations, G12C, G12V, G13D and Q61H. For this purpose, we have performed Molecular Dynamics (MD) simulations of each mutant when active (GTP-bound) and inactive (GDP-bound), analyzed their trajectories, and compared how each mutant changes local residue conformations, inter-protein distance distributions, local flexibility and residue pair correlated motions. Our results reveal that in the four active oncogenic mutants we have studied, the 2 helix moves closer to the C-terminal of the 3 helix. However, P-loop mutations cause 3 helix to move away from Loop7, and only G12 mutations change the local conformational state populations of the protein. Furthermore, the motions of coupled residues are mutant-specific: G12 mutations lead to new negative correlations between residue motions, while Q61H destroys them. Overall, our findings on the local conformational states and protein dynamics of oncogenic K-Ras mutants can provide insights for both mutant-selective and pan-mutant targeted inhibition efforts.

biophysics↗

bioRxiv2020

Fluctuation, correlation and perturbation-response behavior of nature-made and artificial nanobodies

Nanobodies, like other antibodies bind their targets through complementarity determining regions (CDRs). Improving nanobody-antigen binding affinities by introducing mutations in these CDRs is critical for biotechnological applications. However, any mutation is expected to introduce changes in the behavior of the protein, such as fluctuations of residues, correlation of fluctuations of residue pairs, response of a residue to perturbation of another. Most importantly, the nanoscale dynamics of the protein may change. In these respects, the problem is similar to the general problem of dynamic allostery, a perturbation at one site affecting the response at another site. Using the Gaussian Network Model of proteins, we show that CDR mutations indeed modify the fluctuation profile and dynamics of the nanobody. Effects are not confined to CDR regions but extend throughout the full structure. We introduce a computational scheme where fluctuations of a residue are perturbed by a force and response amplitude and response time of the remaining residues are determined. Response to a perturbation of a residue shows a synchronous and an asynchronous component. The model is used to quantify the effects of mutation on protein dynamics: highly perturbable residues and highly responsive residues of the nanobody are determined. Residues whose perturbation has no effect on protein behavior may also be determined with the present model. Three known nanobodies produced by nature are used as an illustrative example and their various modifications which we generated by CDR residue mutations are analyzed.

biophysics↗

bioRxiv2020

Structural Analysis of the PATZ1 BTB domain homodimer

PATZ1 is a transcriptional repressor belonging to the ZBTB family that is functionally expressed in T-lymphocytes, as well as in a ubiquitous fashion. PATZ1 targets the Cd8 gene in lymphocyte development and interacts with the p53 protein to control genes important in proliferation and DNA damage response. PATZ1 exerts its activity through an N-terminal BTB domain that mediates dimerization and co-repressor interactions and a C-terminal zinc finger motif-containing domain that mediates DNA binding. Here, the crystal structures of the murine and zebrafish PATZ1 BTB domains are reported at 2.3 and 1.8 [A] resolution respectively. The structures reveal that, like other ZBTB structures, the PATZ1 BTB domain forms a stable homodimer and likely binds co-repressors through a lateral surface groove that is formed upon dimerization. Analysis of the lateral groove reveals a large acidic patch in this region which contrasts previously resolved basic co-repressor binding interfaces in other ZBTB proteins. A large 30 amino acids glycine- and alanine-rich central loop, unique to mammalian PATZ1 amongst all ZBTB proteins, could not be resolved likely due to its flexibility. Modelling of this loop indicates that it can participate in the dimerization interface of BTB monomers. SynopsisThe crystal structures of the PATZ1 BTB domain in mammals and fish are homodimers. The core dimer conformation of these BTB proteins is dynamically stable, despite the presence of highly flexible regions in the dimerization interface.

molecular biology↗

bioRxiv2019

ModiBodies: A computational method for modifying nanobodies to improve their antigen binding affinity and specificity

Nanobodies are special derivatives of antibodies, which consist of only a single chain. Their hydrophilic side prevents them from having the solubility and aggregation problems of conventional antibodies, and they retain the similar size and affinity of the binding area to the antigen. Nanobodies have become of considerable interest for next-generation biotechnological tools for antigen recognition. They can be easily engineered due to their high stability and compact size. They have three complementarity determining regions, CDRs, which are enlarged to provide a similar binding surface to that of regular antibodies. The binding residues are more exposed to the environment. One common strategy to improve protein solubility is to replace hydrophobic residues with hydrophilic ones on the binding surface which contributes to both stability and solubility of nanobodies.[1] Here, we propose an algorithm that uses the 3D structures of protein-nanobody complexes as the initial structures and by successive mutations in the CDR domains to find optimum binding amino acids for hypervariable residues of CDRs to increase the binding affinity and nanobody selectivity. We used the MDM4-VH9 complex, (PDB id 2VYR), fructose-bisphosphate aldolase from Trypanosoma congolense, (PDB id 5O0W), and human lysozyme, (PDB id 4I0C). as benchmark studies and identified similar amino acid patterns in hypervariable residues of CDRs with experimentally optimized ones. According to this method, better binding nanobodies can be generated by using this algorithm in a short time. We suggest that this method can complement existing immune and synthetic library-based methods, without the need of experiments or large libraries.

bioengineering↗

bioRxiv2019

How many bits of information can be transferred within a protein and how fast?

Amount and rate of information that may be transferred from one residue to another in a protein is quantified using the transfer entropy concept of information theory. Information transfer from one residue to the second is defined as the decrease in the uncertainty in the second residue due to coupling with past values of the first. Three types of information transfer between pairs of residues are defined: transfer between residues that are (i) close in both space and along the primary protein chain, (ii) close in space but distant along the chain, and (iii) distant in space and along the chain may be distinguished. The widely studied third PDZ domain from the synaptic protein PSD-95 is used as an example. The three types of transfer show that residues close in space and chain transfer the largest amount of information. Transfer along the primary chain is also significant. Predictions of the model show that significant amount of transfer may also take place between spatially distant pairs of residues. The latter forms the basis of dynamic allostery in proteins. The role of information transfer between distant pairs in relation to coevolution has been controversial, some works assigning it to near neighbor residue pairs only and others supporting long range coupling. The present paper shows that significant amount of information may be transferred between distant pairs in PSD-95.Transfer rates of the order of gigabytes per second are predicted by the present theory. Information transfer between a specific set of residue pairs exhibit strong directionality, or causality, an observation that may be of use in protein engineering and drug design.

biophysics↗

bioRxiv2017

The Effects Of Oncogenic G12D Mutation On K-Ras Structure, Conformation And Dynamics

K-Ras is the most frequently mutated oncoprotein in human cancers, and G12D is its most prevalent mutation. To understand how G12D mutation impacts K-Ras function, we need to understand how it alters the regulation of its dynamics. Here, we present local changes in K-Ras structure, conformation and dynamics upon G12D mutation, from long-timescale Molecular Dynamics simulations of active (GTP-bound) and inactive (GDP-bound) forms of wild-type and mutant K-Ras, with an integrated investigation of atomistic-level changes, local conformational shifts and correlated residue motions. Our results reveal that the local changes in K-Ras are specific to bound nucleotide (GTP or GDP), and we provide a structural basis for this. Specifically, we show that G12D mutation causes a shift in the population of local conformational states of K-Ras, especially in Switch-II (SII) and 3-helix regions, in favor of a conformation that is associated with a catalytically impaired state through structural changes; it also causes SII motions to anti-correlate with other regions. This detailed picture of G12D mutation effects on the local dynamic characteristics of both active and inactive protein helps enhance our understanding of local K-Ras dynamics, and can inform studies on the development of direct inhibitors towards the treatment of K-RasG12D-driven cancers.

biophysics↗

bioRxiv2016

Entropy Transfer between Residue Pairs Shows that Allostery is an Intrinsic Propertyof Proteins: Quantifying Allosteric Communication in Ubiquitin

AbstractIt has recently been proposed by Gunasakaran et al. that allostery may be an intrinsic property of all proteins. Here, we apply Schreibers transfer entropy formulation to the non-allosteric protein Ubiquitin and show that there are indeed systematic pathways of entropy and information transfer between residues that correlate well with the activities of the protein. We use 600 nanosecond molecular dynamics trajectories for Ubiquitin and its complex with human polymerase iota and evaluate entropy transfer between all pairs of residues of Ubiquitin and quantify the binding susceptibility changes upon complex formation. Calculations show that specific residues act as entropy reservoirs in Ubiquitin and others as entropy sinks. Using the plausible conjecture that extracting entropy from a residue makes it more susceptible for interaction with a partner, we explain the ternary complex formation of Ubiquitin in terms of entropy transfer. Finally, we show that time delayed correlation of fluctuations of two interacting residues possesses an intrinsic causality that tells which residue controls the interaction and which one is controlled. Our work shows that time delayed correlations, entropy transfer and causality are the required new concepts for explaining allosteric communication in proteins.\n\nAuthor SummaryAllosteric communication is essential for the function of proteins. Recent work shows that allostery results from dynamic processes in the protein associated with atomic fluctuations leading to entropic interactions that involve ensemble of pathways rather than discrete two state transitions. Based on this new picture of allostery, it was proposed that allostery may indeed be an intrinsic property of all proteins. In order to test this hypothesis, we derive the computational tools for quantifying allosteric communication, and explain allostery in terms of entropy transfer, a new concept based on information theory. We use long molecular dynamics simulations of proteins from which we calculate the transfer of entropy between pairs of residues. Results of simulations show that certain residues act as entropy sources while others as entropy sinks. Evaluation of time delayed correlations shows the presence of causality of interactions that allow us to differentiate between residues that are drivers in allosteric activity and those that are driven. Identification of driver-driven relations is important for drug design. Using the example of Ubiquitin, a protein that is not known to be allosteric, we identify paths of information transfer that control its binding to diverse partners in the Ubiquitin-Proteasome System. We conclude that allosteric communication resulting from entropy transfer between residues is an intrinsic property of all proteins.

biophysics↗

bioRxiv2016

Causality, Transfer Entropy and Allosteric Communication Landscapes inProteins with Harmonic Interactions

A fast and approximate method of generating allosteric communication landscapes is presented by using Schreiber's entropy transfer concept in combination with the Gaussian Network Model of proteins. Predictions of the model and the allosteric communication landscapes generated show that information transfer in proteins does not necessarily take place along a single path, but through an ensemble of pathways. The model emphasizes that knowledge of entropy only is not sufficient for determining allosteric communication and additional information based on time delayed correlations has to be introduced, which leads to the presence of causality in proteins. The model provides a simple tool for mapping entropy sink-source relations into pairs of residues. Residues that should be manipulated to control protein activity may be determined with this approach. This should be of great importance for allosteric drug design and for understanding the effects of mutations on protein function. The model is applied to determine allosteric communication in two proteins, Ubiquitin and Pyruvate Kinase. Predictions are in agreement with detailed molecular dynamics simulations and experimental evidence.\n\nSignificanceProteins perform their function by an exchange of information within themselves and with their environments through correlated fluctuations of their atoms. Fluctuations of one atom may drive the fluctuations of another. Information transmitted in this way leads to allosteric communication which is described as the process in which action at one site of the protein is transmitted to another site at which the protein performs its activity. Disruption of allosteric communication by mutation for example leads to disease. The present paper incorporates information theoretic concepts into the well known Gaussian Network Model of proteins and allows for rapid characterization of allosteric communication landscapes for normal functioning as well as malfunctioning proteins.

biophysics↗