Biology subjects

Frohlking, T.

Publications and source records attributed to Frohlking, T..

3 recordsLinked to original sources

bioRxiv2025

A Transferable and Robust Computational Framework for Class A GPCR Activation Free Energies

The activation of G-protein coupled receptors is involved in many bio-medically important cellular pathways. However, capturing it with molecular simulations is far from trivial as it requires capturing both local and global motions. We recently achieved this goal in a specific receptor (the {beta}1-adrenergic receptor, or ADRB1) by combining a multiple replica enhanced sampling approach with tailored collective variables. While that approach can be applied to other receptors, it would require a tedious and error-prone choice and refinement of the collective variables, and in particular of the main path-like variable. Herein, we introduce an effective and stream-lined evolved strategy for defining the CVs that reduces user intervention while still achieving a robust free energy convergence. We apply it to two apo-GPCRs of pharmacological relevance, ADRB1 and the {micro}-opioid receptor. In the first case we show that the reconstructed free energies agree with those obtained with the previous tailored approach, while for the {micro}-opioid receptor activation we gain novel biological insights. The proposed method can be easily applied to other class A GPCRs, paving the avenue to the systematic elucidation of the activation mechanisms of many crucial drug targets. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=199 HEIGHT=200 SRC="FIGDIR/small/692536v1_ufig1.gif" ALT="Figure 1"> View larger version (6K): org.highwire.dtl.DTLVardef@9fae49org.highwire.dtl.DTLVardef@16b5288org.highwire.dtl.DTLVardef@f79af1org.highwire.dtl.DTLVardef@1dd71d8_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2025

CryptoBank: A Resource for the Identification and Prediction of Cryptic Sites in Proteins

Cryptic binding sites in proteins, which are hidden in the absence of a ligand, offer opportunities to modulate targets previously considered undruggable. However, the scarcity of experimentally validated examples limits the development of predictive tools. Here, we introduce CryptoBank, a large-scale database of cryptic sites identified by applying a machine learning model to detect ligand-induced conformational changes in over 5.5 million structural alignments of unbound (apo) and bound (holo) protein pairs from the Protein Data Bank (PDB). Our analysis reveals that cryptic pockets are widespread, occurring in approximately 16.3% of protein clusters. Leveraging this resource, we fine-tuned a protein language model (PLM) to predict cryptic sites directly from protein sequence information. This sequence-based model achieves high precision (PR AUC 0.8) when query sequences share more than 20% identity with CryptoBank entries. Critically, we demonstrate its broader utility by predicting a cryptic site in human TPP1, a protein with less than 20% sequence identity to any CryptoBank entry, and validating its opening using molecular dynamics simulations. CryptoBank and the predictive PLM are publicly accessible via a web server, providing valuable resources for cryptic site discovery and drug development.

bioinformatics↗

bioRxiv2021

Towards Convergence in Folding Simulations of RNA Tetraloops: Comparison of Enhanced Sampling Techniques and Effects of Force Field Corrections

Atomistic molecular dynamics (MD) simulations represent established technique for investigation of RNA structural dynamics. Despite continuous development, contemporary RNA simulations still suffer from suboptimal accuracy of empirical potentials (force fields, ffs) and sampling limitations. Development of efficient enhanced sampling techniques is important for two reasons. First, they allow to overcome the sampling limitations and, second, they can be used to quantify ff imbalances provided they reach a sufficient convergence. Here, we study two RNA tetraloops (TLs), namely the GAGA and UUCG motifs. We perform extensive folding simulations and calculate folding free energies ({Delta}Gfold) with the aim to compare different enhanced sampling techniques and to test several modifications of the nonbonded terms extending the AMBER OL3 RNA ff. We demonstrate that replica exchange solute tempering (REST2) simulations with 12-16 replicas do not show any sign of convergence even when extended to time scale of 120 s per replica. However, combination of REST2 with well-tempered metadynamics (ST-MetaD) achieves good convergence on a time-scale of 5-10 s per replica, improving the sampling efficiency by at least two orders of magnitude. Effects of ff modifications on {Delta}Gfold energies were initially explored by the reweighting approach and then validated by new simulations. We tested several manually-prepared variants of gHBfix potential which improve stability of the native state of both TLs by up to ~2 kcal/mol. This is sufficient to conveniently stabilize the folded GAGA TL while the UUCG TL still remains under-stabilized. Appropriate adjustment of van der Waals parameters for C-H...O5 base-phosphate interaction are also shown to be capable of further stabilizing the native states of both TLs by ~0.6 kcal/mol.

biophysics↗