AlphaFold 3 (AF3) and Boltz-2 are state-of-the-art AI-based tools for biomolecular structure prediction, but whether their predictions provide useful guidance for lead optimization, SAR interpretation, and virtual screening remains insufficiently characterized. We benchmarked their performance using newly determined soluble epoxide hydrolase co-crystal structures and matched activity data together with a curated post-training-cutoff dataset spanning kinases, allosteric modulators, covalent systems, PROTACs, molecular glues, fragments, membrane proteins, RNA binders, and activity-cliff pairs. Both models recovered canonical orthosteric enzyme and kinase complexes, including key DFG/αC conformational states, whereas allosteric, membrane-protein, and induced-proximity complexes remained challenging. Pharmacophore RMSD was often lower than overall ligand RMSD, indicating preservation of key recognition features despite imperfect whole-ligand alignment. AF3 minPAE correlated with pose accuracy, and very low minPAE values (<0.85 Å) were strongly enriched for accurate poses. Model confidence scores were not associated with experimental activity, whereas Boltz-2 predicted affinity captured relative activity trends and distinguished the activity-cliff pair, although its performance varied across ligand series.
Cytochrome P450 3A4 (CYP3A4) metabolizes roughly half of all marketed drugs, and its inhibition can cause clinically significant drug-drug interactions. The enzyme accommodates chemically diverse ligands, making binding modes and metabolic outcomes difficult to predict. Previous X-ray crystallography efforts have leveraged a truncated construct without the N-terminal segment that tethers CYP3A4 to the membrane. Here we show that the same construct assembles into a symmetric trimer that can be resolved by cryo-EM and determine structures of both unliganded and ligand-bound CYP3A4. Multiple ligands are resolved with density consistent with several mutually exclusive conformations. Protein remodeling to reshape the binding pocket is concentrated in the F/G loop, which is poorly resolved and unmodeled in many X-ray structures. These features likely underlie the poor predictive performance of co-folding methods on this target. The routine use of cryo-EM to resolve CYP3A4 ligand-bound complexes will provide the ground truth data needed to make predictive models of drug metabolism useful in practice.
Anna K. Orta, Jan-Hannes Schäfer, G. Correy et al.· bioRxiv· 0 citations
HER2/ERBB2 kinase inhibition provides a useful case study for connecting curated bioactivity data, ligand-based modelling, chemical-space design, and structure-based triage. This study developed an applicability-domain-aware workflow for prioritizing scaffold-constrained HER2 kinase inhibitor analogs. Exact nanomolar IC50 records from ChEMBL target CHEMBL1824 were cleaned, converted to pIC50 values, aggregated at molecule level, and encoded as 2,048-bit Morgan fingerprints. Tree-ensemble classifiers gave the strongest ligand-based performance, and repeated scaffold-split validation was used to estimate scaffold-level generalization. Four HER2-associated Bemis-Murcko frameworks were selected for constrained R-group enumeration, yielding 500,000 valid analogs. Composite screening combined predicted HER2 activity, maximum-reference Tanimoto similarity as an applicability-domain measure, preferred physicochemical filters, and parent-scaffold priority, followed by Butina diversity selection of 100 docking-ready ligands. Synthetic-feasibility triage indicated that 94 of the 100 final ligands passed conservative RDKit-based medicinal-chemistry criteria. Wild-type docking, Prime MMGBSA rescoring, interaction-fingerprint comparison, and profiling against L755S, T798I, V777L, and V842I HER2 mutant receptors prioritized GEN_0015905 as the leading wild-type MMGBSA analog and highlighted GEN_0268162, GEN_0394004, and GEN_0015892 as follow-up candidates with smaller predicted wild-type-to-mutant score shifts. The workflow provides a reproducible computational route for selecting experimentally testable HER2 analogs while keeping model extrapolation, chemical diversity, and structure-based interpretation explicit. Repeated validation also showed the expected drop from random-split to scaffold-split performance, with random forest ROC-AUC decreasing from 0.973 ± 0.006 under repeated random splits to 0.956 ± 0.015 under repeated scaffold splits.
P. A. Akinnusi· Computational biology and ch...· 0 citations
A category-stratified, statistically powered benchmark comparing pose prediction from receptor conformational ensembles against AlphaFold2, used as a matched static-structure baseline, across 29 protein–ligand systems spanning cryptic-pocket, induced-fit, water-mediated, and autoimmune-indication target classes is presented.
Ryan Varghese, Pooja Tiwary, Krishil Oswal· bioRxiv· 0 citations
It is found that, while AF3 can perform well in favourable settings, this performance is uneven across applications and its predictions and use of confidence metrics will depend strongly on the specific application area and must be interpreted with respect to training-set overlap.
O. Follonier, Yan Liu, Pablo Campomanes et al.· bioRxiv· 1 citation
Emerging SARS-CoV-2 variants highlight the need for orally active, low-toxicity antivirals. We designed seven para-substituted flavonoid hybrids (M1–M7) against the main protease (Mpro). In silico ADME filtering revealed zero Lipinski, Veber, or Ghose violations, a SwissADME bioavailability score of 0.55, and selected favorable predicted absorption and transporter endpoints relative to lopinavir, without implying measured pharmacokinetic superiority. ProTox-III indicated that amino and nitro substitution increased predicted genotoxicity liabilities, whereas cyano and methoxy substitution reduced selected endocrine-related signals. AutoDock Vina docking to Mpro (PDB 9C8Q; redocking RMSD 0.316 Å) ranked the nitro analogue M6 first among the designed compounds (−8.1 kcal mol−1), with contacts involving His41 and neighboring active-site residues. During the 100 ns GROMACS simulations, the protein backbone remained stable, whereas M6 adopted a late reoriented pose that was retained in the active-site region and supported by late-window per-residue energetic contributions. DFT calculations at the B3LYP/6-311G(d,p) level identified the narrowest HOMO-LUMO gap (3.44 eV) and highest electrophilicity (ω = 6.2 eV) for M6. Overall, M6 is prioritized as a computational lead requiring Mpro inhibition, antiviral, and cytotoxicity validation.
Jawaher H. Alqahtani, Mohammed Ouachekradi, Bahia Abdelfattah et al.· Current Issues in Molecular...· 0 citations
Computational findings suggest that ligand 4 represents a promising alkynyl-3-carboxamide-based lead scaffold for further development as a potential legumain-targeted therapeutic candidate for AD.
Afifa I Noor, H. N. Suha, Istiak Hossain et al.· Physical Chemistry, Chemical...· 0 citations
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