ArticleJournal of chemical information and modeling2026
Computer-Aided Drug Design for Type 2 Diabetes-Related Enzymes: SILCS-Based Fragment Mapping, Pharmacophore Modeling, and Virtual Screening.
Article in Journal of chemical information and modeling, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Highly charged enzyme active sites present a challenge for conventional Site Identification by Ligand Competitive Saturation (SILCS) because strongly interacting charged probes can suppress sampling of neutral fragments, while additive force fields do not explicitly account for electronic polarization. To address these limitations, we developed a comprehensive SILCS-based computational framework and applied it to the N-terminal and C-terminal domains of maltase-glucoamylase and to α-amylase. Both the conventional mixed-probe SILCS workflow and a modified neutral-charged protocol were evaluated using the CHARMM additive and Drude polarizable force fields. FragMap convergence analysis demonstrated reliable sampling across all systems, with the neutral-charged protocol alleviating competitive exclusion effects observed in conventional simulations. In highly charged catalytic pockets, the conventional workflow was dominated by cationic probe sampling, suppressing neutral and hydrogen-bonding features. Separation of charged and neutral probes restored chemically diverse interaction patterns, improving representation of hydrogen-bond donor, acceptor, and hydrophobic hotspots. Incorporation of the Drude polarizable force field further enhanced resolution of electrostatic and hydrogen-bonding interactions. Energy-based SILCS-Pharmacophore models were generated from the neutral-charged FragMaps and used for virtual screening of the Maybridge and ChemBridge libraries. Hits were refined using SILCS-MC, ranked by ligand grid free energy (LGFE) and ligand efficiency (LE), and analyzed through scaffold- and fingerprint-based clustering. Integration of energetic and structural analyses enabled identification of favorable scaffolds and functional group patterns associated with strong binding efficiency. Together, this study develops, evaluates, and applies an improved SILCS workflow to three enzymes associated with type 2 diabetes (T2D), demonstrating its utility for characterizing highly charged active sites and prioritizing candidate inhibitors.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.