Reshaping biomolecular structure prediction through strategic conformational exploration with HelixFold-S1

May combine two claims.

Compared with conventional unguided sampling, HF-S1 substantially improves prediction accuracy at equivalent sampling effort, with the largest gains for challenging protein-antibody complexes.

“Compared with conventional unguided sampling, HelixFold-S1 substantially improves prediction accuracy at equivalent sampling effort, with the largest gains observed for challenging protein-antibody complexes.”

May combine two claims.

For HF3, precision remains nearly constant across sampling steps, as the order of sampled conformations is effectively random.

“For HF3, which performs aimless sampling, precision remains nearly constant across steps, as the order of sampled conformations is effectively random.”

May combine two claims.

HF-S1 can still improve predictions for protein-ligand binding sites, but the relative gains are smaller compared with other complex types.

“Finally, protein-ligand binding sites are highly constrained, so while HF-S1 can still improve predictions, the relative gains are smaller compared with other complex types.”

• AssumptionRests on an assumption: Protein-ligand binding sites are highly constrained.

May combine two claims.

Improvements are pronounced for Top-1, Top-5, and Top-25, although Top-1 gains exhibit greater variability.

“The improvements are pronounced for Top-1, Top-5, and Top-25, underscoring HF-S1's robustness across multiple ranking thresholds, although the Top-1 gains exhibit greater variability, potentially reflecting sensitivity to the selection of conformations based on the confidence score.”

May combine two claims.

Current confidence scores do not always reliably identify the most accurate structures, as high-confidence predictions may not correspond to true structural accuracy while low-confidence predictions can still include near-native conformations.

“Current confidence scores do not always reliably identify the most accurate structures, as high-confidence predictions may not correspond to true structural accuracy while low-confidence predictions can still include near-native conformations (Fig. S3).”

May combine two claims.

Across complex types, most targets fall into the HF-S1 std higher category, particularly protein-antibody, protein-RNA, and protein-DNA complexes, where the HF-S1 std higher category accounts for roughly twice as many targets as the HF3 std higher category.

“Across complex types, most targets fall into the HF-S1 std higher category, particularly protein-antibody, protein-RNA, and protein-DNA complexes, where the HF-S1 std higher category accounts for roughly twice as many targets as the HF3 std higher category.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

Predicted contact probabilities provide a rough indicator of prediction difficulty and sampling utility.

“Predicted contact probabilities also provide a rough indicator of prediction difficulty and sampling utility.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Polar or charged residues such as Asp, Glu, and Lys often exhibit lower contact probabilities.

“Conversely, polar or charged residues, such as Asp, Glu, and Lys, often exhibit lower probabilities”

May combine two claims.

HF-S1 consistently outperforms both HF3 and HF3 w/ AFSample across all complex types, with the magnitude of improvement highest for protein-antibody complexes, followed by protein-protein and protein-RNA/DNA interfaces, and smallest for protein-ligand binding sites.

“HF-S1 consistently outperforms both HF3 and HF3 w/ AFSample across all complex types, with the magnitude of improvement highest for protein-antibody complexes, followed by protein-protein and protein-RNA/DNA interfaces, and smallest for protein-ligand binding sites.”

May combine two claims.

For protein-antibody complexes, HF-S1 achieves over a 55% improvement relative to HF3 and 33% relative to HF3 w/ AFSample.

“The largest gains are observed for protein-antibody complexes, where HF-S1 achieves over a 55% improvement relative to HF3 and 33% relative to HF3 w/ AFSample.”

May combine two claims.

Targets with intermediate contact probabilities achieved the greatest improvements from multi-sample prediction relative to single-sample predictions, while those with low or high probabilities saw more modest gains.

“We found that targets with intermediate contact probabilities achieved the greatest improvements, while those with low or high probabilities saw more modest gains.”

May combine two claims.

Protein-ligand complexes consistently exhibit high contact probabilities, suggesting that HF-S1 can often localize ligand binding sites with high confidence.

“Protein-ligand complexes consistently exhibit high contact probabilities, suggesting that HF-S1 can often localize ligand binding sites with high confidence.”

May combine two claims.

Lower-probability targets consistently yielded poorer predictions, while higher-probability targets were predicted with high precision.

“Targets were stratified into high, medium, and low groups, revealing a strong correlation across datasets: lower-probability targets consistently yielded poorer predictions, while higher-probability targets were predicted with high precision.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Hydrophobic pairs such as Leu-Leu and Met-Met tend to show higher predicted contact probabilities.

“Hydrophobic pairs such as Leu-Leu and Met-Met tend to show higher predicted probabilities”

May combine two claims.

Predicted inter-chain contact probabilities correlate strongly with structural difficulty and provide a practical guide for allocating sampling effort across targets.

“Predicted inter-chain contact probabilities correlate strongly with structural difficulty and provide a practical guide for allocating sampling effort across targets.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

The approach is generalizable to other folding models to enhance structural precision.

“The approach is generalizable to other folding models to enhance structural precision.”

The quote only partly states this claim.

Extensive sampling progressively improves structural accuracy.

“c, Comparison of HF-S1 with various baseline models on protein-antibody complexes released in 2024 (n=74), showing that extensive sampling progressively improves structural accuracy.”

May combine two claims.

The oracle DockQ values for all models show a consistent upward trend as the number of sampling iterations increases, aligning with the characteristics of a scaling law.

“The results reveal a consistent upward trend in the oracle DockQ values for all models as the number of sampling iterations increases, aligning with the characteristics of a scaling law.”

May combine two claims.

On the Protein-DNA test set, the top-1 iLDDT score for the S1-integrated model does not show a statistically significant enhancement, but notable improvements are observed in the top-5, top-10, and top-25 iLDDT metrics.

“Specifically, on the Protein-DNA test set, while the top-1 iLDDT score for the model integrated with S1 does not show a statistically significant enhancement, notable improvements are observed in the top-5, top-10, and top-25 iLDDT metrics.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

Predicted contact probabilities reflect residue physicochemical preferences.

“e, Predicted contact probabilities reflect residue physicochemical preferences.”

May combine two claims.

As the rank number increases, the probability values decline at a slower rate, resulting in a more long-tailed distribution.

“Moreover, as the rank number increases, the probability values decline at a slower rate, resulting in a more long-tailed distribution.”

May combine two claims.

HF-S1 shows a broader distribution of structural precision, whereas HF3 predictions are more concentrated.

“HF-S1 shows a broader distribution of structural precision, whereas HF3 predictions are more concentrated.”

May combine two claims.

Two inter-chain residue pairs (R43-N26 and V103-L28) selected from HF-S1's predicted contact map and applied as spatial restraints during folding yielded two distinct binding conformations that both satisfied the defined contact distances (R43-N26 approximately 3.1 Å; V103-L28 approximately 4.2 Å).

“Two inter-chain residue pairs (R43-N26 and V103-L28) were selected from HF-S1's predicted contact map and applied as spatial restraints during folding, yielding two distinct binding conformations that both satisfied the defined contact distances (R43-N26 ≈ 3.1 Å; V103-L28 ≈ 4.2 Å).”

Classified as probably not a substantial claim. May combine two claims.

Target-level standard deviation of structural precision among sampled conformations for HF3 and HF-S1; higher values indicate greater conformational diversity.

“a, Target-level standard deviation of structural precision among sampled conformations for HF3 and HF-S1.Each point represents a target; higher values indicate greater conformational diversity.”

May combine two claims.

Guided planning reshapes conformational exploration and enables more efficient and accurate structural inference.

“These results demonstrate that guided planning reshapes conformational exploration and enables more efficient and accurate structural inference.”

May combine two claims.

By enforcing constraints on individual interfacial contacts, guided sampling helps capture correct local interactions, although single-contact constraints alone are not sufficient to fully determine the global geometry of larger, more complex interfaces.

“By enforcing constraints on individual interfacial contacts, guided sampling helps capture correct local interactions, although single-contact constraints alone are not sufficient to fully determine the global geometry of these larger, more complex interfaces.”

May combine two claims.

The largest gains for protein-antibody complexes likely reflect the structural diversity of antigen-binding sites, which makes conventional sampling less effective at capturing native-like geometries, whereas HF-S1's guided sampling increases the likelihood of generating correct interfacial contacts.

“This likely reflects the structural diversity of antigen-binding sites, which makes conventional sampling less effective at capturing native-like geometries, whereas HF-S1's guided sampling strategy increases the likelihood of generating correct interfacial contacts.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

Because HF-S1 may employ a distinct definition of contacts from those folding models, the baseline models may not reach their best performance under this evaluation.

“Because HF-S1 may employ a distinct definition of contacts from those folding models, the baseline models may not reach their best performance under this evaluation.”

May combine two claims.

Leveraging contact probabilities as structural constraints improves efficiency and prioritizes structurally meaningful regions of the conformational landscape.

“This behavior highlights that leveraging contact probabilities as structural constraints not only improves efficiency but also prioritizes structurally meaningful regions of the conformational landscape.”

May combine two claims.

Low contact probability generally corresponds to more difficult targets, which often require additional sampling to achieve accurate predictions.

“This indicates that low contact probability generally corresponds to more difficult targets, which often require additional sampling to achieve accurate predictions.”

Classified as probably not a substantial claim. May combine two claims.

Chai-1 currently supports contact constraints only for protein-protein complexes, so results are reported for protein-antibody and protein-protein systems only.

“Moreover, Chai-1 currently supports contact constraints only for protein-protein complexes, and results are therefore reported for protein-antibody and protein-protein systems only.”

Classified as probably not a substantial claim. May combine two claims.

Sequences were clustered by similarity, and one representative per cluster was randomly chosen to ensure diversity and reduce redundancy.

“Sequences were clustered by similarity [21], and one representative per cluster was randomly chosen to ensure diversity and reduce redundancy.”

• cites [21] Silva, G., Cui, J. Y., Dalgarno, D. C., Lisi, G. P. & Rubenstein, B. M. High-throughput prediction of protein conformational distributions with subsampled AlphaFold2. Nat. Commun. 15, 2464 (2024). sourceNot checked yet

  Not checked in the free run.

Classified as probably not a substantial claim. May combine two claims.

Protenix w/ S1 and Chai-1 w/ S1 were run without redundancy contact pruning, whereas HF-S1 fully applies RCP during sampling.

“To enable parallel evaluation, Protenix w/ S1 and Chai-1 w/ S1 were run without redundancy contact pruning (RCP), which requires sequential sampling, whereas HF-S1 fully applies RCP during sampling.”

May combine two claims.

For lower-probability targets, predicted contact maps are weak across the board, suggesting that a much larger number of samples may be needed to identify accurate structures.

“For lower-probability targets, the predicted contact maps are weak across the board, suggesting that a much larger number of samples may be needed to identify accurate structures.”

Classified as probably not a substantial claim.

For protein-ligand complexes, ligands that appeared in the training data were excluded.

“For protein-ligand complexes, any ligands that appeared in the training data were further excluded.”

Probably not a substantial claim: may not pass S4 (based). May combine two claims.

By operating in the simplified space of contacts rather than directly in the high-dimensional structural space, the model achieves greater computational efficiency and facilitates the contact-conditioned structure prediction task.

“By operating in the simplified space of contacts-rather than directly in the complex, high-dimensional structural space-the model achieves greater computational efficiency and facilitates the contact-conditioned structure prediction task.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Chai-1 w/ S1 is restricted to protein-protein/antibody datasets, as it only accepts residue-residue contact constraints as input.

“It should be noted that Chai-1 w/ S1 is restricted to protein-protein/antibody datasets, as it only accepts residue-residue contact constraints as input.”

Probably not a substantial claim: may not pass S4 (based).

Executing the contact prediction task five times and averaging the resulting matrices reduces prediction variance.

“In the Contact Prediction stage, the contact prediction task is executed five times to reduce prediction variance, producing five contact probability matrices.These matrices are averaged element-wise to generate the final contact probability matrix”

May combine two claims.

Redundant contact pruning ensures that each newly sampled contact introduces novel constraints and helps maintain diversity among sampled structures.

“This ensures that each newly sampled contact introduces novel constraints and helps maintain diversity among sampled structures.”

May combine two claims.

HF-S1 facilitates an increase in the diversity of model prediction results, thereby enhancing the probability of the model achieving superior sampling.

“This suggests that HF-S1 facilitates an increase in the diversity of model prediction results, thereby enhancing the probability of the model achieving superior sampling.”

Probably not a substantial claim: may not pass S3 (load-bearing).

HF3 w/ AFsample adopts a more sophisticated multi-setting approach according to the AlphaFold settings used in AFsample.

“Notably, the inference configuration for HF3 w/ AFsample adopts a more sophisticated multi-setting approach, according to the AlphaFold settings used in AFsample [12].”

• cites [12] Bryant, P. & Noé, F. Improved protein complex prediction with AlphaFold-multimer by denoising the MSA profile. PLoS Comput. Biol. 20, 1012253 (2024). sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

The uncertainty observed in protein-antibody complexes can be attributed to the inherent characteristics of these molecules.

“The uncertainty observed in protein-antibody complexes can be attributed to the inherent characteristics of these molecules.”

• AssumptionRests on an assumption: Antigen-antibody interactions are diverse, with antibodies able to recognize and bind to a wide range of antigens with varying structures.

Probably not a substantial claim: may not pass S4 (based).

Guided exploration in planning-based sampling directs sampling toward more informative conformations.

“b, Guided exploration in planning-based sampling, directing sampling toward more informative conformations.”

Classified as probably not a substantial claim.

The contact prediction task serves as a basis for generating contact constraints during inference.

“The contact prediction task aims to estimate the probability that each inter-chain token pair is in atomic contact, serving as a basis for generating contact constraints during inference.”

May combine two claims.

Although the S1-integrated model is capable of identifying more accurate conformations, the precision limitations of the confidence score restrict the ability to fully reflect the effectiveness of its conformational search when solely comparing the highest-scoring conformation.

“This suggests that although the S1-integrated model is capable of identifying more accurate conformations, the precision limitations of the confidence score restrict the ability to fully reflect the effectiveness of its conformational search when solely comparing the highest-scoring conformation.”

May combine two claims.

The long-tailed distribution suggests that there are numerous potential contacts with non-negligible probabilities, making it challenging to pinpoint the exact interaction sites.

“The long-tailed distribution suggests that there are numerous potential contacts with non-negligible probabilities, making it challenging to pinpoint the exact interaction sites.”

May combine two claims.

HF-S1 demonstrates clear improvements, reflecting its enhanced ability to accurately identify epitope regions through contact-guided sampling.

“Notably, HF-S1 demonstrates clear improvements, reflecting its enhanced ability to accurately identify epitope regions through contact-guided sampling.”