Jul 2026· Journal of Chemical Information and Modeling· 0 citations· 40 references
Computer ScienceMedicine
TL;DR
A novel "induce-and-identify" workflow that integrates mixed solvent molecular dynamics simulations with SiteMap is developed and validated, enabling the exploration of a broader range of druggable targets by effectively inducing and identifying cryptic binding sites.
Abstract
Identifying cryptic binding sites in proteins remains a challenge in structure-based drug discovery because these sites are often not apparent in apo structures. Here, we developed and validated a novel "induce-and-identify" workflow that integrates mixed solvent molecular dynamics (MxMD) simulations with SiteMap. This approach leverages MxMD to sample protein conformations to expose hidden pockets, which are then effectively identified and ranked by SiteMap. Using a challenging data set of 65 cryptic binding sites, the developed workflow identified the cryptic binding site within the top 5 predictions in 78.5% of cases. These results suggest that the proposed MxMD + SiteMap workflow provides a robust and valuable tool for early phase drug discovery, enabling the exploration of a broader range of druggable targets by effectively inducing and identifying cryptic binding sites.
Lacuna, an open-source Python tool for discovering cryptic binding pockets, generates a conformational ensemble from any input structure, detects pockets independently in every conformer, clusters the detections into persistent sites across the ensemble, and ranks those sites with a model fitted on within-structure pai...
A computational framework in which residues with high cryptic-pocket propensity are used as mutation handles to perturb the free-energy landscape and expose ligand-compatible open states even in the absence of ligand binding is presented, providing a practical framework for studying and targeting cryptic pockets.
Reshob Routh, Mithun Radhakrishna· Journal of Chemical Informat...· 0 citations
Certain proteins known to be involved in life-threatening diseases have remained challenging therapeutic targets for decades, simply because a suitable binding pocket for a potent molecular inhibitor could not be identified in their ground-state apo structures. In the past decade, the discovery of cryptic pockets in ch...
N. Vithani, She Zhang, Judith Günther et al.· Journal of the American Chem...· 0 citations
CrypKANet is an innovative multimodal predictive framework for cryptic binding site identification that integrates EGNN, gated attention mechanisms, and Kolmogorov-Arnold Network (KAN) and exhibits excellent generalization performance on protein-protein interaction sites and ligand binding site tasks.
Yong-Xian Fan, Xianchen Zheng, Yang-Feng Zhu et al.· IEEE journal of biomedical a...· 0 citations
HydroDock is extended to challenging targets with open binding pockets, populated by highly mobile water molecules that are the most troublesome for drug design, and improved docking accuracy with increases of 28% (10%) in median structural (and ranking) performance.
Bayar Bayarsaikhan, C. Hetényi, B. Z. Zsidó· ACS Physical Chemistry Au· 0 citations
Co-folding models hold immense potential for allosteric drug discovery, but have been severely hampered by their systematic bias toward orthosteric ligand binding. While fragment screening has been proposed for allosteric binding site discovery, we show that co-folding models still suffer from memorization in which che...
Justin Purnomo, Kunyang Sun, T. Head-Gordon· bioRxiv· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
